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Articles
2100
www.thelancet.com Vol 403 May 18, 2024
Global burden of 288 causes of death and life expectancy
decomposition in 204 countries and territories and
811 subnational locations, 1990–2021: a systematic analysis
for the Global Burden of Disease Study 2021
GBD 2021 Causes of Death Collaborators*
Summary
Background Regular, detailed reporting on population health by underlying cause of death is fundamental for public
health decision making. Cause-specific estimates of mortality and the subsequent eects on life expectancy worldwide
are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important
following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality
rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing
a nuanced understanding of the eect of these causes on global populations.
Methods The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated
mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories
and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data
from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among
others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of
Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of dierent
statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—
with alternative strategies adapted to model causes with insucient data, substantial changes in reporting over the study
period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-
location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs)
were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed
life expectancy by cause of death, location, and year to show cause-specific eects on life expectancy from 1990 to 2021.
We also used the coecient of variation and the fraction of population aected by 90% of deaths to highlight
concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements
for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age
groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other
pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower
respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-
of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other
data types were added to those used in previous GBD rounds.
Findings The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending
order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory
infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with
94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading
five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position.
In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths
[250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per
100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region
(48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per
100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated
causes. Decomposition of global and regional life expectancy showed the positive eect that reductions in deaths from
enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved
survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and
2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was
highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years
(6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest
reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally,
53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021,
Lancet 2024; 403: 2100–32
Published Online
April 3, 2024
https://doi.org/10.1016/
S0140-6736(24)00367-2
This online publication has been
corrected. The corrected version
first appeared at thelancet.com
on April 19, 2024
See Comment page 1956
*Collaborators are listed at the
end of the Article
Correspondence to:
Prof Simon I Hay, Institute for
Health Metrics and Evaluation,
University of Washington,
Seattle, WA 98195, USA
sihay@uw.edu
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Introduction
For more than three decades, the Global Burden of
Diseases, Injuries, and Risk Factors Study (GBD) has
been systematically and comprehensively recording and
analysing causes of human death stratified by age, sex,
and time across the world.1,2 This information has been
used to guide policy solutions, reduce modifiable risk
factors, monitor and evaluate national and sub-national
health interventions, and ultimately improve health
recommendations at both regional and local levels.1
Assessing trends in cause-specific mortality is essential
to inform health policy that must continuously evolve to
account for rapid changes to the global health landscape,
such as the COVID-19 pandemic.3 Comprehensive
updates to levels and trends in causes of death give
insight into emerging global health challenges and can
facilitate benchmarking in the case of a new pandemic or
other events that can lead to a staggering loss of life.
Therefore, documenting novel changes to mortality, such
as an emerging pandemic, in real time, is important.
Causes of death are not uniformly distributed between
populations; rather, large variability in the leading
causes often reflects important social and geographical
dierences.4 These dierences can include access to and
quality of health care, timeliness of health system
responsiveness, and exposure to causes that are
endemic to specific geographical locations.4 Mortality
patterns continually evolve, as some areas become
successful in their reduction eorts, whereas other
causes persist within specific locations. The past
30 years have seen improvements among many causes
of mortality, some of which have considerably narrowed
in geographical range and are now concentrated within
smaller areas worldwide. This change enables us to
identify the resulting areas of concentrated mortality—
areas where deaths from that cause are occurring within
a limited subset of the global population. Our analysis
provides an opportunity to answer important epidem-
iological questions that have been at the forefront of
global and public health discourse—eg, which causes
have contributed to the largest increase or decrease in
life expectancy, which locations are experiencing greater
concentrations of preventable causes of death, and how
has COVID-19 and other pandemic-related mortality
(OPRM) aected life expectancy and the overall fatal
burden of diseases? Regional variation in many of the
leading causes of death remains evident in these most
recent estimates, representing important opportunities
for creating tailored health policy to improve disparities
and alleviate concentrations of mortality.
GBD 2021 provides an updated, comprehensive set of
the fatal burden of disease summarised with cause-
specific mortality metrics and years-of-life-lost (YLLs)
metrics for 288 causes by age and sex across
204 countries and territories from 1990 to 2021, an
update from the previously published estimates
covering 1990–2019. In this study, we present mortality
concentrations and a decomposition analysis of life
expectancy due to dierent causes of death and illustrate
the impact of causes of death on global, regional, and
country-specific life expectancy, as well as highlighting
locations that are most aected by concentrated
geographical mortality burden. As with previous
iterations of GBD, this cycle incorporates newly
available data sources and improved methodological
approaches to re-estimate the entire time series,
providing updated estimates that supersede all previous
GBD cause-of-death publications. GBD 2021 includes
an estimation of several dierent models for disease
and injury outcomes. This manuscript was produced as
part of the GBD Collaborator Network and in accordance
with the GBD Protocol.5
and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern.
The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections,
malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.
Interpretation Long-standing gains in life expectancy and reductions in many of the leading causes of death have been
disrupted by the COVID-19 pandemic, the adverse eects of which were spread unevenly among populations. Despite
the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved
global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from
1990 and 2021, obscuring the negative eect in the years of the pandemic. Additionally, our findings regarding regional
variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality
trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These
changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy,
present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in
mortality concentration might reveal areas where successful public health interventions have been implemented.
Translating these successes to locations where certain causes of death remain entrenched can inform policies that work
to improve life expectancy for people everywhere.
Funding Bill & Melinda Gates Foundation.
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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Methods
Overview
In GBD 2021, we produced estimates for each
epidemiological quantity of interest for 288 causes of
death by age-sex-location-year for 25 age groups from
birth to 95 years and older; for males, females, and both
sexes combined; in 204 countries and territories grouped
into 21 regions and seven super-regions; and for every
year from 1990 to 2021. GBD 2021 also includes
subnational analyses for 21 countries and territories
Research in context
Evidence before this study
The Global Burden of Diseases, Injuries, and Risk Factors Study
(GBD) has provided regular updates on the complex patterns
and trends in population health around the world since the first
GBD publication in 1993. With each subsequent iteration, there
have been important methodological updates, new datasets
included, and an expanded list of causes, risk factors, and
locations for which estimates of the burden of disease are
produced. In 1993, mortality and years of life lost (YLLs) were
reported for 107 categories of diseases that covered all possible
causes of death, for eight regions. In the last GBD cycle—GBD
2019—estimates of mortality and YLLs were produced for
286 causes of death in 204 countries and territories, including
all WHO member states, and for subnational locations in
21 countries and territories, for every year from 1990 to 2019.
Although many groups have reported on national-level, cause-
specific mortality and other population-health metrics,
including the WHO World Health Statistics reports, GBD is the
most detailed and transparent research effort to date. Further,
estimates of COVID-19-related deaths in 2020 and 2021 have
been reported by several sources, including GBD studies that
have quantified excess mortality due to the pandemic within a
subset of GBD locations. However, no previous publications
have quantified the effect of COVID-19 on life expectancy, while
considering the full spectrum of disease mortality over the past
three decades, across all countries and territories. This study
presents, for the first time, 288 causes of death from 1990 to
2021, complementary to the all-cause mortality findings
presented in the GBD 2021 Demographics analysis. Combined,
these studies provide a comprehensive view of all-cause and
cause-specific mortality from 1990 to 2021.
Added value of this study
Alongside the all-cause mortality and life-expectancy
assessments in companion publications for GBD 2021, this
analysis delineates cause-specific mortality and its effect on life
expectancy. This study includes a comprehensive decomposition
analysis elucidating the primary cause of death influencing life
expectancy on a global, regional, and national level.
Additionally, we present causes of death and YLLs for all
countries and territories, providing policy makers with valuable
insights into variations in cause-specific mortality. This study is
also the first of its kind to publish 2021 estimates of COVID-19-
related deaths and YLLs for 204 countries and territories in the
context of the global burden of disease. Although other
publications have estimated deaths due to COVID-19, those
deaths have not previously been compared with deaths from
other causes. By modelling COVID-19 deaths within a hierarchy
of mutually exclusive and collectively exhaustive causes of
death, this study provides policy makers with information that
is essential for setting health priorities around the world.
To obtain more comprehensive insights from life expectancy, it
is necessary to break it down into age-specific mortality, which
is influenced by cause-specific mortality rates. We examined the
effect of COVID-19 and other causes of death on life expectancy
by decomposing death counts into different cause-specific
mortality rates across various dimensions, including country or
territory, region, super-region, and five distinct time periods:
1990–2000, 2000–2010, 2010–2019, 2019–2021, and
1990–2021. We could therefore systematically calibrate the
COVID-19 pandemic against other causes of mortality over the
period 1990–2021. Finally, our study identified several causes of
death that exhibited increased geographical concentration over
time—ie, causes with a disproportionate impact within a specific
geographical area compared with the rest of the global
observations. This analysis provides policy makers important
information on regional variation and inequalities in cause-
specific mortality. Also new to GBD 2021, we report on
12 additional causes of death: COVID-19 and other pandemic-
related mortality, pulmonary arterial hypertension, and
nine cancer types—hepatoblastoma, Burkitt lymphoma, other
non-Hodgkin lymphoma, eye cancer, retinoblastoma, other eye
cancers, soft tissue and other extraosseous sarcomas, malignant
neoplasm of bone and articular cartilage, and neuroblastoma
and other peripheral nervous-cell tumours. Granularity of the
estimation of deaths in children younger than 5 years was
enhanced by the addition of four new age groups: 1–5 months,
6–11 months, 12–23 months, and 2–4 years.
Implications of all the available evidence
Our study provides a full analysis of causes of death worldwide
and across time, alongside the changing patterns in life
expectancy precipitated by those causes. Increasing
geographical concentration of mortality was observed for many
causes of death, highlighting disparities between regions and
substantial differences in cause-specific contributions to life
expectancy. On a global scale, this information provides an
opportunity to examine whether reductions in mortality were
resilient to the onset of a novel pandemic. On a regional level,
the estimates generated by our study provide important detail
on the evolving impact of causes of death among countries,
allowing crucial insight into differential success by geography,
time, and cause. The comprehensive nature of GBD 2021 cause-
of-death estimation provides valuable opportunities to learn
from mortality gains and losses, helping to accelerate progress
in reducing mortality.
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(appendix 1 section 2.1). An international network of
collaborators provides, reviews, and analyses the available
data to generate these metrics; GBD 2021 drew on the
expertise of more than 11 000 collaborators from more
than 160 countries and territories.
The methods used to generate these estimates closely
followed those for GBD 2019.6 These methods have been
extensively peer reviewed over previous rounds of the
GBD study4,6–9 and as part of the peer-review process for
GBD 2021. Here, we provide an overview of the methods
with an emphasis on the main methodology changes
since GBD 2019; a comprehensive description of the
analytical methods for GBD 2021 is provided in
appendix 1. Detailed descriptions of analytical methods
and models for each cause of death are also available in a
searchable online tool.
The GBD 2021 cause-of-death estimates described here
include cause-specific mortality and the premature death
metric (YLLs). We calculated YLLs as the number of
deaths for each cause-age-sex-location-year multiplied by
the standard life expectancy at each age (appendix 1
section 6.3). Standard life expectancy is calculated from
the lowest age-specific mortality rate between countries.10
Briefly, we estimated cause-specific death rates for
209 causes using the Cause of Death Ensemble model
(CODEm), and we used alternative strategies to model
causes with little data, substantial changes in reporting
over the study period, or unusual epidemiology. The
modelling strategy used for all causes of death can be
found in appendix 1 (table S10). CODEm is a modelling
tool developed specifically for GBD that assesses the out-
of-sample predictive validity of dierent statistical models
and covariate permutations and then combines the
results from those assessments to produce cause-specific
estimates of the burden of mortality. Methodological
improvements for cause-of-death estimates in the present
round of estimation focused on several key areas. First,
cause-of-death data were updated to include age data for
the following age groups younger than 5 years:
1–5 months, 6–11 months, 12–23 months, and 2–4 years.
Second, we implemented enhanced methods to account
for stochastic variation in cause-of-death data and improve
the estimation of small cause fractions present in less
common causes of death. Third, we added 199 new
country-years of vital registration cause-of-death data,
5 country-years of surveillance data, 21 country-years of
verbal autopsy data, and 94 country-years of other data
types. Lastly, we incorporated COVID-19 and OPRM,
which includes excess mortality associated with the
COVID-19 pandemic, excluding deaths from COVID-19,
lower respiratory infections, measles, malaria, and
pertussis.
The GBD disease and injury hierarchy
GBD classifies diseases and injuries into a hierarchy with
four levels that include both fatal and non-fatal causes.
Level 1 causes include three broad aggregate categories
(communicable, maternal, neonatal, and nutritional
[CMNN] diseases; non-communicable diseases [NCDs];
and injuries) and Level 2 disaggregates those categories
into 22 clusters of causes, which are further disaggregated
into Level 3 and Level 4 causes. At the most detailed level,
288 fatal causes are estimated. For a full list of causes of
death by level, see appendix 1 (table S2). For GBD 2021, we
separately report on 12 causes of death for the first time:
COVID-19, OPRM, pulmonary arterial hypertension, and
nine cancer types: hepatoblastoma, Burkitt lymphoma,
other non-Hodgkin lymphoma, eye cancer, retinoblastoma,
other eye cancers, soft tissue and other extraosseous
sarcomas, malignant neoplasm of bone and articular
cartilage, and neuroblastoma and other peripheral
nervous cell tumours.
Data sources, processing, and assessing for
completeness
The GBD 2021 cause-of-death database included data
sources identified in previous rounds of estimation in
addition to 9248 new sources (appendix 1 table S5). We
included multiple data types to capture the widest array
of information, including vital registration and verbal
autopsy for all 288 causes as well as survey, census,
surveillance, cancer registry, police records, open-source
databases, and minimally invasive tissue sampling. To
standardise these data so that they can be compared by
cause, age, sex, location, and time, we applied a set of
data processing corrections. First, deaths with insucient
age data to estimate the GBD age groups or missing age
and sex data underwent age and sex splitting to assign
GBD age groups as well as sex (appendix 1 section 3.5).
Additionally, garbage codes, which are non-specific,
implausible, or intermediate, rather than underlying
cause of death codes from the International Classification
of Diseases, were redistributed to appropriate targets to
assign the underlying cause of death.11 We excluded data
sources with more than 50% of all deaths assigned to
major garbage codes (class 1 or class 2 garbage codes) in
a given year for a specific location (location-year) to
mitigate the potential for bias from these sources
(appendix 1 section 3.7). For GBD 2021, we established a
buer system so that location-years that were included in
the previous GBD cycle would not be dropped from the
current cycle as long as less than 55% of all deaths were
assigned to major garbage codes. This 5% buer ensured
greater consistency in data source inclusion from one
cycle to the next.
Assessing data completeness illustrates the coverage
from a data source on overall mortality for the country.
Vital registration and verbal autopsy data
completeness—a source-specific estimate of the
percentage of total cause-specific deaths that are reported
in a given location and year—was assessed by location-
year, and sources with less than 50% completeness were
excluded. We excluded 142 country-years of data because
of completeness. As with garbage codes, we used a
See Online for appendix 1
For a searchable repository of
cause-specific model details see
https://www.healthdata.org/
gbd/methods-appendices-2021
For the GBD data sources see
https://ghdx.healthdata.org/
gbd-2021/sources
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5% buer so that sources included in the previous GBD
cycle would not be excluded from the current cycle if
they had at least 45% completeness, allowing us to retain
24 country-years that had previously been dropped. We
then multiplied the estimated all-cause mortality for
each age-sex-location-year by the cause fraction for the
corresponding age-sex-location-year to adjust all
included sources to 100% completeness. Verbal autopsy
and vital registration data availability, completeness, and
quality rating for each location-year are available in
appendix 1 (section 3), as well as full details on all data
processing corrections.
Improvements in GBD 2021 to cause of death data
processing and estimation
Adjustments for stochastic variation
In GBD 2021, we made two primary improvements to the
methods used to reduce stochastic variation, most
aecting causes of death with small sample sizes. First,
we updated the Bayesian algorithm used in the noise
reduction of these data to improve the preservation of
real trends in data with large sample sizes, and imparted
additional information from regional trends for data with
small sample sizes. Second, the non-zero floor, a method
that addresses distorted data shapes and nonsensical
trends caused by small numbers when transformed to
log space, was updated to be time-invariant and
independent of demographic inputs. The full details of
these two key improvements, as well as other
improvements that address stochastic variation, can be
found in appendix 1 (section 3.14).
COVID-19 and OPRM estimation
We derived COVID-19 and OPRM estimates from an
analysis of the overall excess mortality due to the
COVID-19 pandemic from January 1, 2020, to
December 31, 2021. Full details of the estimation of
excess mortality, COVID-19 deaths, and OPRM are
provided in appendix 1 (section 5). To estimate excess
mortality, we first developed a database of all-cause
mortality by week and month after accounting for
reporting lags, anomalies such as heat waves, and under-
registration of deaths. Next, we developed an ensemble
model to predict expected deaths in the absence of the
COVID-19 pandemic for the years 2020 and 2021. In
location and time combinations with data used for these
models, we estimated excess mortality as observed
mortality minus expected mortality. To estimate excess
mortality for location-years without data, we developed a
statistical model to directly predict the excess mortality
due to COVID-19, using covariates that pertained to both
the COVID-19 pandemic and background population-
health-related metrics at the population level before
SARS-CoV-2 emerged. Uncertainty was propagated
through each step of this estimation procedure.12
To produce the final estimates of COVID-19 deaths
used in GBD 2021, we used a counterfactual approach.
The counterfactual estimates the number of deaths if
infection detection rates were at the highest observed
value for each location-year. Using the ratio of
counterfactual over estimated excess deaths and the ratio
of reported COVID-19 deaths over excess deaths, we
calculated the ratio of total COVID-19 deaths over
reported COVID-19 deaths and multiplied this figure by
the number of reported COVID-19 deaths for our final
estimates of COVID-19 deaths.12
To account for increases in excess mortality in 2020 and
2021 that could not be attributed to particular causes, we
introduced a residual cause, OPRM. We identified four
causes of death—lower respiratory infections, measles,
malaria, and pertussis—as related to the COVID-19
pandemic and having reliable enough estimates to not
contribute to OPRM. Thus, we calculated OPRM as the
dierence between excess mortality and the sum of
deaths due to COVID-19 and these four causes.12
Presentation of cause-specific mortality estimates
Cause-specific mortality estimates for 2021 are given in
death counts and age-standardised rates per
100 000 population, calculated using the GBD standard-
population structure.10 For changes over time, we present
percentage changes over the period 1990–2021, and
annualised rates of change as the dierence in the
natural log of the values at the start and end of the time
interval divided by the number of years in the interval.
We computed uncertainty intervals (UIs) for all metrics
using the mean estimate across 1000 draws (appendix 1
sections 2–3), and 95% UIs are given as the 2·5th and
97·5th percentiles of that distribution.
Life-expectancy decomposition
The objective of life-expectancy decomposition is to
analyse the dierence in life expectancy by age and
location, quantifying contributions from specific causes
(appendix 1 section 7). We examined temporal trends in
causes over continuous time periods across dierent
locations. We aimed to identify the eect of causes
of death on life expectancy by using three main
decomposition steps. For this study, we investigated the
top-20 Level 2 and Level 3 GBD causes contributing to
change in life expectancy. The remaining causes were
then combined as “other communicable and maternal
disorders” or “other NCDs”. The first step involved
decomposing the dierence in life expectancy by age.
We calculated age-specific contributions to understand
the variation in life expectancy across dierent
age groups. In the second step, each age-specific
contribution was further decomposed into cause-age-
specific contributions. This analysis allowed for the
identification of the specific causes of death that
contributed to the dierences in life expectancy within
each age group. Finally, we aggregated the cause-age-
specific contributions across age groups to produce
cause-specific contributions to the overall dierence
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in life expectancy. This aggregation provided a
comprehensive understanding of how dierent causes
of death contributed to the observed variations in life
expectancy. By applying this decomposition approach,
we gain insights into the relative eect of dierent
causes of death on changes in life expectancy by age and
location.
Calculation of mortality concentration
Concentrated causes in GBD refer to causes that exhibit a
disproportionate impact in a specific geographical subset
of the data compared with the rest of the global
observations. In GBD 2021, we used two dierent methods
to identify these concentrated causes: coecient of
variation and mortality concentration.
Coefficient of variation
For each GBD cause, we calculated a coecient of
variation using standard statistical methods. This
measure assesses the variability of a population relative
to its mean.13 The observations considered for this
calculation were national, age-standardised, both-sex
mortality rates, using the mean mortality rate between
2019 and 2021. Causes with larger coecients of
variation have data that are less centred around the
mean and indicate a greater likelihood of a concentrated
cause.
Mortality concentration
To identify concentrations of mortality—geographical
locations or groups of locations with populations that
are disproportionately aected by a particular cause—
we first calculated the total number of all-age, both-sex
deaths in 2021 by cause in each of the 811 subnational
locations and sorted these locations by number of
deaths in descending order. We then calculated the
cumulative percentage of deaths by dividing location-
specific cumulative deaths by the number of global
deaths for each cause. When the cumulative percentage
reached or exceeded 90% for a given cause, we divided
the population of the geographical subset included in
that cumulative percentage by the total global population
in 2021, using population estimates from the GBD
population model described in previous publications.10,12
This identification of geographical subsets that contain
at least 90% of deaths from a given cause but represent
a comparatively small share of the global population
was used to identify potential inequalities in the
Non-communicable diseases
Communicable, maternal, neonatal, and nutritional causes
Injuries
Ischaemic heart disease
Stroke
COPD
Lower respiratory infections
Diarrhoeal diseases
Neonatal disorders
Tuberculosis
Lung cancer
Alzheimer's and other dementias
Cirrhosis
Stomach cancer
Road injuries
Hypertensive heart disease
Diabetes
Colorectal cancer
Congenital defects
Self-harm
Chronic kidney disease
Malaria
Measles
Falls
HIV/AIDS
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
34
158·9 (147·4 to 165·4)
144·3 (134·0 to 152·3)
71·9 (64·6 to 77·5)
61·8 (57·0 to 66·8)
60·6 (46·7 to 79·6)
46·0 (43·5 to 48·9)
40·0 (34·1 to 44·6)
27·6 (26·1 to 29·0)
25·1 (6·0 to 66·1)
24·4 (22·3 to 27·5)
22·0 (20·1 to 24·0)
21·8 (20·9 to 22·8)
20·9 (17·1 to 23·3)
18·2 (17·0 to 19·1)
15·6 (14·5 to 16·3)
15·2 (9·6 to 19·7)
14·9 (12·8 to 15·8)
14·9 (13·7 to 16·4)
12·5 (6·1 to 26·0)
11·0 (3·9 to 22·6)
10·9 (9·8 to 11·8)
5·9 (4·5 to 7·8)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
67
Ischaemic heart disease
Stroke
COPD
Lower respiratory infections
Neonatal disorders
Alzheimer's and other dementias
Lung cancer
Diabetes
Chronic kidney disease
Diarrhoeal diseases
Cirrhosis
Hypertensive heart disease
Road injuries
Tuberculosis
Colorectal cancer
Stomach cancer
Falls
HIV/AIDS
Malaria
Self-harm
Congenital defects
Measles
89·3 (81·6 to 95·6)
46·1 (42·0 to 49·8)
30·7 (26·8 to 35·3)
25·0 (6·2 to 65·0)
23·7 (21·8 to 25·8)
19·8 (18·5 to 20·8)
17·1 (12·4 to 23·2)
17·1 (15·9 to 18·5)
15·1 (14·2 to 16·0)
14·9 (13·7 to 16·4)
12·6 (11·6 to 13·4)
11·5 (9·9 to 12·9)
10·3 (8·8 to 11·2)
9·8 (9·0 to 11·0)
9·3 (3·7 to 18·3)
9·2 (8·6 to 9·7)
8·9 (7·7 to 10·9)
110·9 (102·5 to 116·9)
34·7 (31·5 to 37·5)
18·6 (16·9 to 19·8)
16·9 (14·1 to 18·6)
1·4 (0·5 to 3·0)
Ischaemic heart disease
COVID-19
Stroke
COPD
Other pandemic-related death
Neonatal disorders
Lower respiratory infections
Alzheimer's and other dementias
Lung cancer
Diabetes
Chronic kidney disease
Cirrhosis liver
Hypertensive heart disease
Diarrheal diseases
Road injuries
Tuberculosis
Colorectal cancer
Stomach cancer
Malaria
Falls
108·7 (99·8 to 115·6)
94·0 (89·2 to 100·0)
87·4 (79·5 to 94·4)
45·2 (40·7 to 49·8)
32·3 (24·8 to 43·3)
29·6 (25·3 to 34·4)
28·7 (26·0 to 31·1)
25·2 (6·4 to 65·6)
23·5 (21·2 to 25·9)
19·6 (18·2 to 20·8)
18·5 (16·7 to 19·9)
16·6 (15·2 to 18·2)
16·3 (13·7 to 18·1)
15·4 (10·9 to 20·9)
14·6 (13·6 to 15·6)
14·0 (12·6 to 15·8)
12·4 (11·2 to 13·4)
11·2 (9·6 to 12·6)
10·5 (3·9 to 21·4)
9·9 (8·5 to 10·8)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
HIV/AID
S8
·7 (8·1 to 9·6)22
Self-har
m9
·0 (8·3 to 9·6)21
Leading causes 1990 Age-standardised rate
of deaths per 100000,
1990
Leading causes 2019 Age-standardised rate
of deaths per 100000,
2019
Leading causes 2021 Age-standardised rate
of deaths per 100000,
2021
Figure 1: Leading Level 3 causes of global deaths and age-standardised death rate per 100 000 population for males and females combined, 1990, 2019, and 2021
Figure shows the 20 leading causes of death in descending order. Causes are connected by lines between time periods; solid lines represent an increase or lateral shift in ranking and dashed lines are
decreases in rank. COPD=chronic obstructive pulmonary disease. Lung cancer=tracheal, bronchus, and lung cancer.
Articles
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incidence of mortality between locations and
populations. In addition to identifying these
concentrations of mortality in 2021, we repeated this
same analysis for 1990. By comparing the respective
proportions of aected global population in these two
years, we were able to dierentiate causes that showed
increased, decreased, or unchanged concentrations of
mortality. The causes highlighted in this study were
those characterised by an age-standardised mortality
rate greater than 0·5 per 100 000 population. The
purpose of presenting mortality concentrations is to
illustrate causes that are disproportionately aecting
specific populations, when previously that cause aected
large swaths of the population. Thus, we did not
calculate the mortality concentration for causes that are
endemic to certain regions, as the mortality rate is
already known to be concentrated among specific parts
of the global population. We excluded two endemic
causes, Ebola virus disease and Chagas disease, from
this calculation.
GBD research and reporting practices
This research is compliant with the Guidelines for
Accurate and Transparent Health Estimates Reporting
recommendations (GATHER; appendix 1 table S4).14
Software packages used in the cause-of-death analysis for
GBD 2021 were Python (version 3.10.4), Stata
(version 13.1), and R (version 4.2.1). Statistical code used
for GBD estimation is publicly available online.
Role of the funding source
The funder of this study had no role in study design, data
collection, data analysis, data interpretation, or the
writing of the report.
Results
Estimates described in the Article are viewable in
appendix 2. Detailed results for each cause of death in
the analysis are available in downloadable form through
the GBD Results tool and via visual exploration through
the online tool GBD Compare. Summaries of results for
each cause of death included in the analysis are available
online.
Global causes of death
From 1990 to 2019, the annual rate of change in global
deaths from all causes ranged from –0·9% (95% UI
–2·7 to 0·8) to 2·4% (0·1 to 4·7; appendix 2 figure S1).
The corresponding annual rates of change in the global
age-standardised mortality rate ranged from –3·3%
(–5·0 to –1·6) to 0·4% (–1·9 to 2·5). In 2020, however,
the total number of deaths worldwide increased
by 10·8% (6·4 to 15·4) compared with 2019, from
57·0 million deaths (54·9 to 59·5) in 2019 to
63·1 million deaths (60·6 to 65·9) in 2020. This trend
persisted in 2021, with an increase of 7·5% (3·1 to 12·4)
relative to 2020, to 67·9 million (65·0 to 70·8) deaths.
The age-standardised mortality rate followed a similar
pattern, increasing by 8·1% (3·9 to 12·4) in 2020 and
See Online for appendix 2
To view and download
estimates from the GBD Results
tool see https://www.vizhub.
healthdata.org/gbd-results
To explore estimates of health
burden using GBD Compare see
https://www.vizhub.healthdata.
org/gbd-compare
For summaries of results for
each cause of death see https://
www.healthdata.org/research-
analysis/diseases-injuries-risks/
factsheets
Ischaemic heart disease, 2019
Ischaemic heart disease, 2020
Ischaemic heart disease, 2021
COVID-19, 2020
COVID-19, 2021
Stroke, 2019
Stroke, 2020
Stroke, 2021
COPD, 2019
COPD, 2020
COPD, 2021
OPRM, 2020
OPRM, 2021
Lower respiratory infections, 2019
Lower respiratory infections, 2020
Lower respiratory infections, 2021
Neonatal disorders, 2019
Neonatal disorders, 2020
Neonatal disorders, 2021
Alzheimer's and other dementias, 2019
Alzheimer's and other dementias, 2020
Alzheimer's and other dementias, 2021
Lung cancer, 2019
Lung cancer, 2020
Lung cancer, 2021
Diabetes, 2019
Diabetes, 2020
Diabetes, 2021
0
20
40
60
80
100
120
Mortality rate per 100
000 population
110·9
109·4
108·7
58·7
94·0 89·3 88·3 87·4
46·1 45·5 45·2
16·7
32·3
34·7
30·4 28·7 30·7 30·3 29·6
25·0 24·9 25·2
23·7 23·5 23·5
19·8 19·7 19·6
Figure 2: Age-standardised mortality rate per 100 000 population for the ten leading Level 3 causes of death globally, 2019–21
Whisker plot in which the y-axis represents the age-standardised mortality rate and the x-axis represents a selected cause-year. Causes are arranged from highest to
lowest age-standardised mortality rate, with each cause assigned a distinct colour for identification. The whiskers represent the 95% uncertainty interval.
COPD=chronic obstructive pulmonary disease. OPRM=other pandemic-related mortality.
For the statistical code see
http://ghdx.healthdata.org/gbd-
2021/code
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2107
Global Central Europe,
eastern Europe,
and central Asia
High income Latin America
and Caribbean
North Africa and
Middle East
South Asia Southeast Asia,
east Asia, and
Oceania
Sub-Saharan
Africa
2020
1
Cause Ischaemic heart
disease
Ischaemic heart
disease
Ischaemic heart
disease
COVID-19 Ischaemic heart
disease
Ischaemic heart
disease
Stroke COVID-19
Age-standardised rate (per
100 000 population)
109·4
(100·7–116·1)
215·3
(199·2–225·7)
51·4
(45·1–54·6)
133.7
(121·5–145·3)
205·2
(182·7–225·6)
150·3
(139·7–162·2)
142·8
(123·9–159·8)
158·9
(148·5–170·0)
Number 8 840 000
(8 180 000–
9 360 000)
1 410 000
(1 310 000–
1 480 000)
1 290 000
(1 110 000–
1 390 000)
799 000
(725 000–
869 000)
760 000
(681 000–
838 000
1 960 000
(1 820 000–
2 110 000)
3 460 000
(3 030 000–
3 880 000)
659 000
(615 000–
706 000)
2
Cause Stroke Stroke COVID-19 Ischaemic heart
disease
COVID-19 Chronic
obstructive
pulmonary
disease
Ischaemic heart
disease
Stroke
Age-standardised rate (per
100 000 population)
88·3
(80·2–95·0)
110·7
(102·7–115·6)
41·8
(40·8–42·8)
84·3
(77·2–89·4)
123·9
(106·8–137·1)
104·1
(92·3–117·0)
110·8
(97·3–124·6)
126·2
(113·4–140·4)
Number 7 140 000
(6 500 000–
7 680 000)
726 000
(675 000–
758 000)
930 000
(908 000–
952 000)
496 000
(454 000–
525 000)
483 000
(415 000–
537 000)
1 230 000
(1 090 000–
1 370 000)
2 570 000
(2 260 000–
2 880 000)
481 000
(432 000–
538 000)
3
Cause COVID-19 COVID-19 Stroke Stroke Stroke COVID-19 Chronic
obstructive
pulmonary disease
Ischaemic heart
disease
Age-standardised rate (per
100 000 population)
58·7
(55·8–62·4)
72·9
(64·1–81·7)
29·0
(24·7–31·2)
47·5
(43·4–50·5)
103·8
(92·0–115·6)
101·8
(95·0–108·5)
66·9
(57·4–77·0)
92·9
(83·1–103·0)
Number 4 800 000
(4 560 000–
5 110 000)
467 000
(411 000–
523 000)
764 000
(636 000–
830 000)
278 000
(255 000–
296 000)
370 000
(329 000–
414 000)
1 320 000
(1 230 000–
1 400 000)
1 500 000
(1 290 000–
1 730 000)
346 000
(309 000–
388 000)
4
Cause Chronic
obstructive
pulmonary
disease
Other COVID-19
pandemic-related
outcomes
Alzheimer’s
disease and other
dementias
Diabetes mellitus Hypertensive
heart disease
Stroke Tracheal,
bronchus, and
lung cancer
Lower
respiratory
infections
Age-standardised rate (per
100 000 population)
45·5
(41·2–49·6)
41·0
(32·9–51·9)
26·5
(6·74–65·1)
36·5
(33·9–38·9)
40·2
(32·0–46·7)
83·3
(75·7–90·4)
34·8
(29·0–41·0)
88·5
(77·8–98·2)
Number 3 650 000
(3 320 000–
3 970 000
264 000
(212 000–
333 000)
774 000
(198 000–
1 900 000)
217 000
(202 000–
231 000)
138 000
(110 000–
160 000)
1 060 000
(969 000–
1 150 000)
938 000
(783 000–
1 110 000)
588 000
(494 000–
686 000)
5
Cause Lower
respiratory
infections
Tracheal,
bronchus, and
lung cancer
Tracheal,
bronchus, and
lung cancer
Lower
respiratory
infections
Chronic kidney
disease
Diarrhoeal
diseases
Alzheimer’s
disease and other
dementias
Malaria
Age-standardised rate (per
100 000 population)
30·4
(27·7–32·9)
25·5
(24·4–26·5)
25·9
(23·8–27·0)
32·8
(29·6–35·1)
37·9
(33·3–42·4)
50·2
(32·0–79·4)
27·9
(6·76–74·8)
67·9
(22·6–145·0)
Number 2 280 000
(2 080 000–
2 460 000)
168 000
(161 000–
174 000)
581 000
(526 000–
610 000)
187 000
(169 000–
200 000)
142 000
(125 000–
159 000)
591 000
(381 000–
940 000)
562 000
(136 000–
1 490 000)
713 000
(251 000–
1 480 000)
6
Cause Neonatal
disorders
Cirrhosis and
other chronic
liver diseases
Chronic
obstructive
pulmonary
disease
Chronic kidney
disease
Other COVID-19
pandemic-
related outcomes
Neonatal
disorders
Lower respiratory
infections
Tuberculosis
Age-standardised rate (per
100 000 population)
30·3
(26·3–35·0)
22·5
(21·7–23·3)
19·2
(16·9–20·3)
30·9
(28·3–33·1)
30·4
(11·4–52·0)
43·8
(37·2–51·6)
21·2
(18·9–23·6)
67·3
(56·7–77·8)
Number 1 910 000
(1 650 000–
2 200 000)
131 000
(127 000–
136 000)
490 000
(424 000–
522 000)
184 000
(169 000–
197 000)
121 000
(46 500–
207 000)
672 000
(571 000–
792 000)
424 000
(378 000–
469 000)
378 000
(313 000–
442 000)
(Table 1 continues on next page)
Articles
2108
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Global Central Europe,
eastern Europe,
and central Asia
High income Latin America
and Caribbean
North Africa and
Middle East
South Asia Southeast Asia,
east Asia, and
Oceania
Sub-Saharan
Africa
(Continued from previous page)
7
Cause Alzheimer’s
disease and
other dementias
Alzheimer’s
disease and
other dementias
Colon and rectum
cancer
Chronic
obstructive
pulmonary
disease
Diabetes mellitus Lower respiratory
infections
Hypertensive
heart disease
HIV/AIDS
Age-standardised rate (per
100 000 population)
24·9
(6·16–65·0)
20·8
(4·88–55·3)
14·7
(13·2–15·6)
25·0
(22·5–26·5)
29·4
(26·4–32·3)
40·0
(35·8–44·7)
20·1
(14·1–24·8)
65·8
(59·9–73·2)
Number 1 890 000
(470 000–
4 940 000)
136 000
(32 100–
362 000)
344 000
(300 000–
367 000)
144 000
(130 000–
152 000)
113 000
(101 000–
124 000)
522 000
(465 000–
582 000)
459 000
(320 000–
562 000)
539 000
(487 000–
612 000)
8
Cause Tracheal,
bronchus, and
lung cancer
Lower
respiratory
infections
Chronic kidney
disease
Interpersonal
violence
Chronic
obstructive
pulmonary
disease
Tuberculosis Stomach cancer Diarrhoeal
diseases
Age-standardised rate (per
100 000 population)
23·5
(21·3–25·8)
19·5
(18·3–20·8)
14·0
(12·1–15·3)
23·5
(22·4–24·8)
26·9
(23·9–29·7)
34·2
(30·1–40·1)
18·4
(14·2–22·0)
57·0
(36·2–79·4)
Number 1 970 000
(1 780 000–
2 160 000)
96 200
(91 200–
101 000)
364 000
(307 000–
399 000)
147 000
(140 000–
155 000)
92 400
(82 500–
102 000)
509 000
(450 000–
597 000)
491 000
(380 000–
589 000)
452 000
(324 000–
588 000)
9
Cause Diabetes
mellitus
Cardiomyopathy
and myocarditis
Lower respiratory
infections
Other COVID-19
pandemic-
related
outcomes
Alzheimer’s
disease and other
dementias
Diabetes mellitus Road injuries Other COVID-19
pandemic-
related
outcomes
Age-standardised rate (per
100 000 population)
19·7
(18·4–20·9)
19·2
(17·9–20·4)
13·6
(11·8–14·6)
20·9
(10·3–33·3)
25·7
(6·30–67·6)
33·1
(29·8–36·0)
15·7
(13·9–17·6)
50·5
(31·3–70·8)
Number 1 630 000
(1 520 000–
1 720 000)
113 000
(105 000–
121 000)
361 000
(306 000–
390 000)
125 000
(59 600–
199 000)
73 600
(17 900–
198 000)
419 000
(378 000–
457 000)
380 000
(335 000–
429 000)
245 000
(159 000–
339 000)
10
Cause Chronic kidney
disease
Colon and
rectum cancer
Self-harm Alzheimer’s
disease and
other dementias
Lower respiratory
infections
Other COVID-19
pandemic-related
outcomes
Chronic kidney
disease
Neonatal
disorders
Age-standardised rate (per
100 000 population)
18·6
(16·9–19·9)
18·6
(17·6–19·4)
10·9
(10·5–11·2)
20·8
(5·14–53·8)
25·4
(22·4–28·5)
28·2
(18·5–39·5)
15·3
(13·4–17·0)
50·0
(42·1–59·2)
Number 1 500 000
(1 360 000–
1 610 000)
122 000
(115 000–
127 000)
149 000
(142 000–
153 000)
119 000
(29 200–
308 000)
103 000
(91 000–
116 000)
370 000
(246 000–
514 000)
376 000
(333 000–
420 000)
889 000
(749 000–
1 050 000)
2021
1
Cause Ischaemic heart
disease
Ischaemic heart
disease
Ischaemic heart
disease
COVID-19 Ischaemic heart
disease
COVID-19 Stroke COVID-19
Age-standardised rate (per
100 000 population)
108·7
(99·8–115·6)
213·6
(196·1–229·1)
51·0
(44·9–54·2)
195·4
(182·1–211·4)
202·8
(179·7–225·9)
156·5
(150·4–164·4)
141·1
(123·2–159·7)
271·0
(250·1–290·7)
Number 8 990 000
(8 290 000–
9 550 000)
1 410 000
(1 290 000–
1 510 000)
1 310 000
(1 120 000–
1 400 000)
1 200 000
(1 110 000–
1 290 000)
769 000
(679 000–
863 000)
2 060 000
(1 980 000–
2 170 000)
3 550 000
(3 100 000–
4 020 000)
1 150 000
(1 060 000–
1 240 000)
2
Cause COVID-19 COVID-19 COVID-19 Ischaemic heart
disease
COVID-19 Ischaemic heart
disease
Ischaemic heart
disease
Stroke
Age-standardised rate (per
100 000 population)
94·0
(89·2–100·0)
168·8
(150·6–186·1)
48·1
(47·4–48·8)
83·8
(75·9–90·6)
172·4
(150·3–191·5)
149·1
(136·4–161·8)
110·4
(94·9–124·6)
124·7
(111·8–138·6)
Number 7 890 000
(7 490 000–
8 400 000)
1 100 000
(982 000–
1 210 000)
1 070 000
(1 060 000–
1 090 000)
504 000
(457 000–
545 000)
698 000
(608 000–
777 000)
1 990 000
(1 820 000–
2 160 000)
2 660 000
(2 290 000–
3 000 000)
484 000
(432 000–
544 000)
(Table 1 continues on next page)
Articles
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2109
Global Central Europe,
eastern Europe,
and central Asia
High income Latin America
and Caribbean
North Africa and
Middle East
South Asia Southeast Asia,
east Asia, and
Oceania
Sub-Saharan
Africa
(Continued from previous page)
3
Cause Stroke Stroke Stroke Stroke Stroke Chronic
obstructive
pulmonary
disease
Chronic
obstructive
pulmonary disease
Other COVID-19
pandemic-
related
outcomes
Age-standardised rate (per
100 000 population)
87·4
(79·5–94·4)
109·8
(101·6–116·6)
28·8
(24·5–30·9)
46·7
(42·3–50·2)
101·9
(89·2–114·4)
101·6
(90·3–114·2)
66·6
(56·2–77·7)
123·9
(87·7–159.5)
Number 7 250 000
(6 600 000–
7 820 000)
725 000
(671 000–
770 000)
771 000
(641 000–
838 000)
279 000
(254 000–
301 000)
372 000
(325 000–
421 000)
1 230 000
(1 100 000–
1 380 000)
1 560 000
(1 310 000–
1 820 000)
584 000
(418 000–
757 000)
4
Cause Chronic
obstructive
pulmonary
disease
Other COVID-19
pandemic-related
outcomes
Alzheimer’s
disease and other
dementias
Other COVID-19
pandemic-
related
outcomes
Other COVID-19
pandemic-
related outcomes
Stroke Tracheal,
bronchus, and
lung cancer
Ischaemic heart
disease
Age-standardised rate (per
100 000 population)
45·2
(40·7–49·8)
50·0
(34·8–68·7)
26·5
(6·74–64·8)
39·0
(22·5–58·4)
64·5
(34·4–100·6)
81·8
(74·2–89·6)
34·8
(28·8–41·1)
92·8
(83·3–103·5)
Number 3 720 000
(3 360 000–
4 090 000)
321 000
(223 000–
438 000)
792 000
(203 000–
1 940 000)
236 000
(135 000–
355 000)
265 000
(139 000–
414 000)
1 070 000
(968 000–
1 170 000)
970 000
(800 000–
1 150 000)
352 000
(316 000–
396 000)
5
Cause Other COVID-19
pandemic-
related
outcomes
Tracheal,
bronchus, and
lung cancer
Tracheal,
bronchus, and
lung cancer
Diabetes mellitus Hypertensive
heart disease
Other COVID-19
pandemic-related
outcomes
Alzheimer’s
disease and other
dementias
Lower
respiratory
infections
Age-standardised rate (per
100 000 population)
32·3
(24·8–43·3)
25·1
(23·7–26·6)
25·9
(23·8–27·0)
36·3
(33·2–39·3)
39·5
(31·3–46·3)
63·3
(50·4–77·2)
28·9
(7·41–78·6)
85·4
(75·3–95·0)
Number 2 690 000
(2 060 000–
3 610 000)
167 000
(157 000–
176 000)
591 000
(537 000–
620 000)
221 000
(202 000–
239 000)
138 000
(109 000–
162 000)
838 000
(674 000–
1 020 000)
608 000
(155 000–
1 670 000)
563 000
(472 000–
655 000)
6
Cause Neonatal
disorders
Cirrhosis and
other chronic
liver diseases
Chronic
obstructive
pulmonary
disease
Chronic kidney
disease
Chronic kidney
disease
Diarrhoeal
diseases
COVID-19 Malaria
Age-standardised rate (per
100 000 population)
29·6
(25·3–34·4)
22·3
(21·0–23·5)
19·1
(16·8–20·2)
30·7
(27·8–33·5)
37·7
(32·7–42·8)
47·8
(30·2–75·7)
23·2
(16·3–37·2)
65·9
(23·6–136·7)
Number 1 830 000
(1 570 000–
2 130 000)
131 000
(123 000–
138 000)
495 000
(428 000–
527 000)
187 000
(170 000–
204 000)
145 000
(126 000–
164 000)
573 000
(372 000–
908 000)
606 000
(425 000–
974 000)
704 000
(265 000–
1 400 000)
7
Cause Lower
respiratory
infections
Alzheimer’s
disease and
other dementias
Colon and rectum
cancer
Lower
respiratory
infections
Diabetes mellitus Neonatal
disorders
Lower respiratory
infections
Tuberculosis
Age-standardised rate (per
100 000 population)
28·7
(26·0–31·1)
20·8
(4·94–55·6)
14·7
(13·1–15·5)
30·4
(27·0–33·3)
29·3
(25·9–32·5)
42·0
(35·6–50·2)
20·9
(18·6–23·4)
65·8
(56·1–76·9)
Number 2 180 000
(1 980 000–
2 360 000)
137 000
(32 500–
370 000)
348 000
(304 000–
372 000)
177 000
(157 000–
194 000)
116 000
(102 000–
129 000)
636 000
(538 000–
760 000)
431 000
(384 000–
482 000)
373 000
(313 000–
439 000)
8
Cause Alzheimer’s
disease and
other dementias
Cardiomyopathy
and myocarditis
Chronic kidney
disease
Chronic
obstructive
pulmonary
disease
Chronic
obstructive
pulmonary
disease
Lower respiratory
infections
Hypertensive
heart disease
HIV/AIDS
Age-standardised rate (per
100 000 population)
25·2
(6·36–65·6)
19·1
(17·5–20·7)
13·9
(12·0–15·1)
24·7
(22·1–26·4)
26·4
(23·2–29·6)
39·2
(34·2–44·6)
19·8
(14·0–24·3)
61·4
(55·8–68·5)
Number 1 960 000
(499 000–
5 120 000)
112 000
(103 000–
122 000)
368 000
(310 000–
402 000)
145 000
(130 000–
156 000)
92 700
(82 000–
104 000)
516 000
(451 000–
584 000)
470 000
(333 000–
575 000)
515 000
(467 000–
583 000)
(Table 1 continues on next page)
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an additional 5·2% (1·0 to 9·7) in 2021. In 2020 and
2021, deaths from COVID-19 and OPRM changed the
pattern of mortality for the leading causes of age-
standardised death (figures 1, 2; table 1). At Level 3 of
the GBD cause-classification hierarchy, the rankings of
the four causes of death with the highest age-
standardised mortality rates were the same in 2019 as
they were in 1990, with each showing a steady decline
in its age-standardised death rate (figure 1). These
causes were, in descending order, ischaemic heart
disease, stroke, chronic obstructive pulmonary disease,
and lower respiratory infections. In 2021, however,
COVID-19 replaced stroke as the second leading cause
of age-standardised death globally (with 94·0 deaths
[95% UI 89·2 to 100·0] per 100 000 population), with
stroke becoming the third leading cause. Additionally,
OPRM—which includes excess mortality associated
with the pandemic, excluding COVID-19, lower
respiratory infections, measles, and pertussis causes—
emerged as the fifth leading cause of age-standardised
deaths in 2021; lower respiratory infections decreased
from the fourth to the seventh leading cause. The eect
of COVID-19 on age-standardised mortality was similar
to that of chronic obstructive pulmonary disease in 2020
but increased by 60·2% (53·1 to 67·6) in 2021,
becoming similar to that of stroke and ischaemic heart
disease (figure 2; table 1).
COVID-19 and OPRM
Our estimates show that 4·80 million (95% UI 4·56–5·11)
deaths due to COVID-19 occurred globally in 2020, and
7·89 million (7·49–8·40) in 2021. Age-standardised rates
of death due to COVID-19 were highly variable among
GBD super-regions (table 1). In 2021, the rankings from
highest to lowest were sub-Saharan Africa (271·0 deaths
[250·1–290·7] per 100 000 population); Latin America
and the Caribbean (195·4 deaths [182·1–211·4] per
100 000 population); north Africa and the Middle East
(172·4 deaths [150·3–191·5] per 100 000 population);
central Europe, eastern Europe, and central Asia
(168·8 deaths [150·6–186·1] per 100 000 population);
south Asia (156·5 deaths [150·4–164·4] per
100 000 population); high income (48·1 deaths
[47·4–48·8] per 100 000 population); and southeast Asia,
east Asia, and Oceania (23·2 deaths [16·3–37·2] per
100 000 population; table 1).
Deaths from both COVID-19 and OPRM also varied
substantially by age, with older ages being
disproportionately aected (table 2). Individuals aged
70–74 years had the highest number of deaths from both
COVID-19 and OPRM in 2020 and again in 2021. The
highest percentage of total deaths from COVID-19 was
found in those aged 40–44 years, whereas the highest
mortality rate occurred in those aged 95 years and older.
Death rates from OPRM were high among older age
groups and among the youngest ages, with a rate of
141·2 deaths (95% UI 58·0–277·5) per 100 000 population
for infants aged 0–6 days, and 77·3 deaths (44·0–118·0)
per 100 000 population in infants aged 7–27 days. At a
global scale, COVID-19 deaths and OPRM were slightly
higher for males than for females in most age groups
in 2021 (appendix 2 figure S5). Exceptions to this trend
include those aged 90–94 years and those aged 95 years
and older (appendix 2 figure S5).
Global Central Europe,
eastern Europe,
and central Asia
High income Latin America
and Caribbean
North Africa and
Middle East
South Asia Southeast Asia,
east Asia, and
Oceania
Sub-Saharan
Africa
(Continued from previous page)
9
Cause Tracheal,
bronchus, and
lung cancer
Colon and
rectum cancer
Lower respiratory
infections
Interpersonal
violence
Alzheimer’s
disease and other
dementias
Tuberculosis Stomach cancer Diarrhoeal
diseases
Age-standardised rate (per
100 000 population)
23·5
(21·2–25·9)
18·5
(17·4–19·6)
11·9
(10·2–12·7)
23·3
(21·7–24·8)
25·7
(6·22–66·8)
33·1
(29·0–39·1)
18·1
(14·4–21·8)
54·4
(33·9–76·7)
Number 2 020 000
(1 820 000–
2 220 000)
122 000
(115 000–
129 000)
321 000
(267 000–
348 000)
147 000
(137 000–
156 000)
73 900
(18 000–
198 000)
501 000
(441 000–
587 000)
500 000
(397 000–
605 000)
434 000
(310 000–
570 000)
10
Cause Diabetes
mellitus
Lower
respiratory
infections
Self-harm Alzheimer’s
disease and
other dementias
Cirrhosis and
other chronic
liver diseases
Diabetes mellitus Road injuries Neonatal
disorders
Age-standardised rate (per
100 000 population)
19·6
(18·2–20·8)
16·5
(15·4–17·7)
10·8
(10·4–11·0)
20·8
(5·18–54·3)
23·2
(20·2–26·8)
32·8
(29·5–36·1)
15·5
(13·6–17·5)
48·6
(40·3–58·1)
Number 1 660 000
(1 540 000–
1 760 000)
82 800
(77 800–87 500)
148 000
(141 000–
152 000)
121 000
(30 300–
317 000)
99 600
(86 100–
116 000)
426 000
(383 000–
468 000)
379 000
(331 000–
430 000)
873 000
(724 000–
1 040 000)
Table 1: Number of deaths and age-standardised mortality rates for ten leading Level 3 causes of death in 2020 and 2021, globally and by super-region, for all ages and males and females
combined
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2111
Leading causes of global YLLs
The causes of death with the highest age-standardised
YLL rates show shifting epidemiological trends from
CMNN diseases to NCDs at Level 3 of the cause
hierarchy (appendix 2 figure S2). Globally, the leading
three causes of age-standardised YLLs in 1990 were all
CMNN diseases. Ranked in descending order, these
causes were neonatal disorders, lower respiratory
infections, and diarrhoeal diseases. In 2019, neonatal
disorders remained the leading cause of age-
standardised YLLs, but the second and third leading
causes were replaced by NCDs: ischaemic heart disease
(ranked second) and stroke (ranked third). In 2021,
COVID-19 was the second-leading cause of global age-
standardised YLLs, making the leading two causes
CMNN diseases (with neonatal disorders ranked first),
with ischaemic heart disease ranked third. Among the
leading causes of age-standardised YLLs, malaria was
the only cause to show an increase in age-standardised
YLL rates between 2019 and 2021 (ranking ninth in 2019
and seventh in 2021).
Decomposition of global life expectancy
We found long-standing positive trends in global life
expectancy since the early 1990s, with steady increases
occurring across each decade between 1990 and 2019
(appendix 2 table S4). Altogether, the global increase in life
expectancy from 1990 to 2019 totalled 7·8 years (95% UI
7·1–8·5). In 2019–21, however, we found a global decline
in life expectancy of 2·2 years due to deaths from
COVID-19 and OPRM combined. This decrease was partly
oset by reductions in other diseases, for a net reduction
in global life expectancy of 1·6 years. Despite this notable
reduction, we observed an overall increase in life
expectancy of 6·2 years (5·4–7·0) across the entire study
period. This decomposition analysis provides insights into
the specific causes that influenced changes in life
expectancy over the defined time periods. Among the
various contributing factors to a change in life expectancy,
the cause with the greatest eect on the increase in life
expectancy worldwide was the reduction in deaths caused
by enteric infections (figure 3). This category includes
diarrhoeal, typhoid, and paratyphoid diseases. A reduction
Deaths Deaths per 100 000 population Percentage of total deaths
COVID-19
2020
COVID-19
2021
Other
COVID-19
pandemic-
related
outcomes
2020
Other
COVID-19
pandemic-
related
outcomes
2021
COVID-19
2020
COVID-19
2021
Other
COVID-19
pandemic-
related
outcomes
2020
Other
COVID-19
pandemic-
related
outcomes
2021
COVID-19
2020
COVID-19
2021
Other
COVID-19
pandemic-
related
outcomes
2020
Other
COVID-19
pandemic-
related
outcomes
2021
Early neonatal 0 1 3518 3462 0·0 <0·1 141·4 141·2 0·0% <0·1% 0·2% 0·2%
Late neonatal 3 5 5069 5641 <0·1 0·1 68·5 77·3 <0·1% <0·1% 1·1% 1·3%
1−5 months 170 287 24269 26 647 0·3 0·5 44·4 49·6 <0·1% <0·1% 3·1% 3·6%
6−11 months 234 394 20 478 30 883 0·4 0·6 31·7 48·9 <0·1% 0·1% 3·5% 5·5%
12–23 months 998 1644 19 042 30 550 0·8 1·3 14·5 23·8 0·2% 0·3% 3·7% 6·2%
2–4 years 8500 14 386 14 730 23 574 2·1 3·6 3·6 5·8 1·2% 2·1% 2·0% 3·4%
5–9 years 7052 11 393 5377 8196 1·0 1·7 0·8 1·2 1·9% 3·2% 1·5% 2·3%
10–14 years 8553 14 405 1588 2715 1·3 2·2 0·2 0·4 2·8% 4·8% 0·5% 0·9%
15–19 years 17 032 26 852 5932 12 576 2·8 4·3 1·0 2·0 3·1% 4·8% 1·1% 2·2%
20–24 years 25 528 40 743 8219 17 453 4·3 6·8 1·4 2·9 3·6% 5·5% 1·2% 2·4%
25–29 years 47 857 78 496 12581 28 816 8·1 13·3 2·1 4·9 5·9% 9·2% 1·6% 3·4%
30–34 years 81 232 137 979 21 625 49 808 13·4 22·8 3·6 8·2 7·9% 12·3% 2·1% 4·5%
35–39 years 112 228 195 380 29 877 69 402 20·5 34·8 5·5 12·4 9·0% 14·1% 2·4% 5·0%
40–44 years 165 337 287 099 44 391 102 041 33·5 57·4 9·0 20·4 10·3% 16·0% 2·8% 5·7%
45–49 years 207 940 355 388 55 989 124 899 44·0 75·1 11·8 26·4 10·1% 15·7% 2·7% 5·5%
50–54 years 253 491 426 785 67 629 147 651 57·7 95·9 15·4 33·2 9·1% 14·0% 2·4% 4·8%
55–59 years 336 162 564 508 90 815 191 441 87·5 142·7 23·6 48·4 9·0% 13·8% 2·4% 4·7%
60–64 years 460 769 774 879 125 433 262 008 146·1 242·1 39·8 81·9 9·8% 15·0% 2·7% 5·1%
65–69 years 564 371 957 557 155 431 321 301 209·4 347·1 57·7 116·5 9·4% 14·5% 2·6% 4·9%
70–74 years 585 549 989 888 156 931 325 295 298·7 480·9 80·1 158·0 8·8% 13·2% 2·4% 4·3%
75–79 years 539 515 861 796 135 849 276 402 417·1 653·4 105·0 209·6 7·9% 11·8% 2·0% 3·8%
80–84 years 551 014 888 813 146 084 277786 638·9 1014·8 169·4 317·2 7·5% 11·3% 2·0% 3·5%
85–89 years 427 770 658 875 106 842 191 824 959·3 1441·1 239·6 419·5 6·9% 10·0% 1·7% 2·9%
90–94 years 280 605 426 185 67 297 114 449 1608·9 2382·3 385·9 639·8 7·5% 10·8% 1·8% 2·9%
≥95 years 120 173 174 390 24 074 42 104 2298·6 3199·6 460·5 772·5 7·8% 10·7% 1·6% 2·6%
Table 2: Number of deaths, age-standardised mortality rates, and percentage of total deaths due to COVID-19 and other pandemic-related mortality by age, globally
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in deaths from these diseases is responsible for a
substantial increase in life expectancy of 1·1 years during
1990–2021, but this increase was most pronounced
between 1990 and 2000 compared with other time periods.
The second-largest eect on increasing life expectancy is
attributed to the reduction in deaths from lower respiratory
infection, contributing 0·9 years of gained life expectancy
from 1990 to 2021. Other leading factors include reduced
mortality from stroke, CMNN diseases, neonatal deaths,
ischaemic heart disease, and neoplasms, each of which
increased global life expectancy by 0·6–0·8 years over the
study period. Changing rates of HIV/AIDS and malaria
mortality both contributed positively to the overall global
life expectancy in some years but negatively aected life
expectancy in others. Beginning in 2000, reductions in
HIV/AIDS-related mortality were evident following
substantial negative eects in earlier years. Reductions in
deaths from malaria, however, were less sustained,
increasing life expectancy by 0·1 years from 2010 to 2019
but having no eect from 2019 to 2021. Across all causes,
the largest eect on the change in global life expectancy
was from COVID-19, which resulted in a decline of
1·6 years between 2019 and 2021.
Decomposition of super-region, regional, and country-
level life expectancy
Each of the seven super-regions experienced an overall
increase in life expectancy between 1990 and 2021, despite
progress in each being dierentially aected by COVID-19
(figures 4, 5). Southeast Asia, east Asia, and Oceania
showed the highest gain, with a net improvement of
8·3 years (95% UI 6·7–9·9), while also being the least
aected by COVID-19, which contributed a loss in life
expectancy of just 0·4 years. The overall increase in life
expectancy in southeast Asia, east Asia, and Oceania can
largely be attributed to reduced mortality from chronic
respiratory diseases, contributing to a gain of 1·2 years,
whereas reduced mortality from stroke, lower respiratory
infections, and neoplasms were among other causes that
contributed to the 8·3-year (6·7–9·9) increase. The second-
largest gain occurred in south Asia, where life expectancy
increased by 7·8 years (6·7–8·9), which can be largely
attributed to reduced mortality from enteric infectious
diseases, contributing a substantial gain of 3·1 years in life
expectancy. The largest reduction in overall life expectancy
due to COVID-19 occurred in the super-region of Latin
America and the Caribbean, which experienced a loss of
3·6 years. Reductions in deaths due to malaria throughout
sub-Saharan Africa led to an increase in life expectancy of
0·8 years for the super-region.
The dierential eect of COVID-19 on reduced life
expectancy was observed across GBD regions (figure 6).
Although most regions experienced overall improve-
ments in life expectancy between 1990 and 2021, a
reduction occurred in southern sub-Saharan Africa,
which faced the greatest impact of HIV and was also
Enteric infections, 1·1 years
LRI, 0·9 years
Stroke, 0·8 years
Other communicable diseases, 0·6 years
Ischaemic heart disease, 0·6 years
Neoplasms, 0·6 years
Neonatal disorders, 0·6 years
Tuberculosis, 0·5 years
Other NCDs, 0·5 years
COPD, 0·5 years
Unintentional injuries*, 0·4 years
Measles, 0·3 years
Digestive diseases, 0·3 years
Nutritional deficiencies, 0·2 years
Transport injuries, 0·2 years
Suicide and homicide†, 0·2 years
Malaria, 0·1 years
HIV/AIDS, 0·0 years
Diabetes and CKD, –0·1 years
OPRM, –0·6 years
COVID-19, –1·6 years
–2·0 –1·5 –1·0 –0·5 0 0·5 1·0 1·5
Life expectancy gained (years)
1990–2000
2000–10
2010–19
2019–21
0·4 0·40·3 0·1
–1·6
–0·6
–0·4 0·20·2
–0·1 0·1
0·10·1
0·10·1
0·10·1
0·1 0·10·1
0·1 0·20·1
0·1 0·10·1
0·1 0·20·1
0·2 0·20·1 0·1
0·1 0·20·1
0·1 0·20·2
0·1 0·30·2
0·1 0·20·2
0·2 0·20·2 0·1
0·2 0·30·3
0·3 0·30·2 0·1
Figure 3: Change in life expectancy attributable to leading causes of death for males and females combined, 1990–2000, 2000–10, 2010–19, and 2019–21,
globally
Each row represents the change in global life expectancy from 1990 to 2021 for a given cause. The total change in life expectancy is further broken down by different
colours to represent changes over time periods. A bar to the right of 0 represents an increase in life expectancy due to changes in the given time period, and a bar to
the left of 0 represents a decrease in life expectancy due to a given time period. For readability, labels indicating a change in life expectancy of less than 0·05 years are
not shown. CKD=chronic kidney disease. COPD=chronic obstructive pulmonary disease. LRI=lower respiratory infection. NCD=non-communicable disease.
OPRM=other pandemic-related mortality. *Does not include natural disasters. †Does not include war and terrorism.
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2113
Figure 5: Change in life expectancy attributable to leading causes of death among super-regions, 1990–2021
Each row represents the change in life expectancy from 1990 to 2021 for a given super-region. A bar to the right of 0 represents an increase in life expectancy due to changes in the given cause, and a
bar to the left of 0 represents a decrease in life expectancy for a given cause. For readability, labels indicating a change in life expectancy of less than 0·3 years are not shown. CKD=chronic kidney
disease. COPD=chronic obstructive pulmonary disease. LRI=lower respiratory infection. NCD=non-communicable disease. OPRM=other pandemic-related mortality. *Does not include natural disasters.
†Does not include war and terrorism.
–0·4 0·40·6 0·
60
·60·50·7 0·40·8 1·21·01·2
–0·7 –3·6
–1·2 1·8 1·2 0·9
–0·7 –2·4
0·70·8 0·70·7 0·4 0·40·4 0·40·9
1·2 0·50·6 1·0 0·4 0·5
–0·9 –2·3 0·40·6 0·9 0·60·9 0·4 0·51·1 1·1 1·2
–1·2 –2·4 1·9 1·4 0·80·9 0·60·5 0·41·11·5
–0·8 –1·9 0·53·1 1·0 0·5
0·5
0·90·4 0·4 1·4 0·41·2
Southeast Asia, east Asia, and Oceania, 8·3 years
South Asia, 7·8 years
Sub-Saharan Africa, 7·8 years
North Africa and Middle East, 5·7 years
High income, 4·5 years
Latin America and Caribbean, 2·7 years
Central europe, Eastern Europe, and central Asia, 2·1 years
–6·0 –2·0–4·0 0 2·0 4·0 6·0 8·0 10·0 12·0
Change in life expectancy (years)
Super-region
COPD
COVID-19
Diabetes and CKD
Digestive diseases
Enteric infections
HIV/AIDS
Ischaemic heart disease
LRI
Malaria
Measles
Natural disasters and conflict
and terrorism
Neonatal disorders
Neoplasms
Nutritional deficiencies
OPRM
Other communicable
diseases
Other NCDs
Stroke
Suicide and homicide*
Transport injuries
Tuberculosis
Unintentional injuries†
Figure 4: Age-standardised mortality rate of COVID-19 and OPRM, 2021
Global choropleth maps of COVID-19 (A) and OPRM (B) for 2021 that show sub-national detail where available. OPRM=other pandemic-related mortality.
<1·4
1·4 to <44
44 to <90·6
90·6 to <121
121 to <151·3
151·3 to <181·2
181·2 to <209·3
209·3 to <248·6
248·6 to 295·4
>295·4
Age-standardised mortality rate
per 100
000
ACOVID-19, 2021
BOPRM, 2021
<0·2
0·2 to <1·8
1·8 to <8·1
8·1 to <23·8
23·8 to <47·9
47·9 to <62·5
62·5 to <78·2
78·2 to <97·5
97·5 to 130·1
>130·1
Age-standardised mortality rate
per 100
000
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heavily aected by COVID-19. The overall decrease in life
expectancy of 4·3 years (95% UI 3·0–5·8) included a
reduction of 2·4 years due to HIV/AIDS and 3·4 years
due to COVID-19, which were only partly oset by
reductions in mortality due to other causes. Notably,
COVID-19 reduced life expectancy in Andean Latin
America by 4·9 years, although the region had an overall
gain of 2·6 years (1·0–4·1) between 1990 and 2021. The
eect of COVID-19 in eastern sub-Saharan Africa, which
resulted in a reduction in life expectancy of 2·7 years,
was oset by steady improvements across many dierent
causes, which resulted in the highest overall increase in
life expectancy among GBD regions (10·7 years
[9·0–12·2]). Control of enteric infections in this region
contributed to an increase in life expectancy of 1·9 years,
along with reductions in lower respiratory infections and
tuberculosis, each of which contributed to an additional
1·6 years’ increase in life expectancy. Each region in
sub-Saharan Africa experienced reductions in the
number of enteric infections, which improved life
expectancy in those regions between 0·8 and 2·4 years.
HIV/AIDS had a substantial negative eect on life-
expectancy trends in southern sub-Saharan Africa from
1990 to 2021 (appendix 2 figure S27). Despite improve-
ments in each of the time periods 2000–2010, 2010–2019,
and 2019–2021, this region was unable to recover the
9·0 years lost during 1990–2000. Although we found a net
decline in deaths due to HIV/AIDS between 2000 and 2019,
improvements slowed substantially from 2019 to 2021,
when only 0·2 years in life expectancy were gained as a
result of reduced HIV/AIDS mortality. Conversely, eastern
sub-Saharan Africa had the highest level of recovery to their
life expectancy among the regions, gaining 1·5 years of life
expectancy over the entire study period.
In 1990, malaria-related deaths had almost no eect on
life expectancy in eight of the 21 GBD regions (appendix 2
figure S13). By 2021, however, 90% of malaria deaths across
all age groups occurred in locations with only 12% of the
global population. Eorts to control malaria in various
regions of sub-Saharan Africa have yielded modest gains in
life expectancy. Central sub-Saharan Africa gained 0·7 years
in life expectancy between 2000 and 2010, western sub-
Saharan Africa gained 0·9 years during 2010–19, and
eastern sub-Saharan Africa gained 0·7 years in 2000–10.
Despite these advancements, many regions with malaria
transmission experienced a decline in life expectancy
from 2019 to 2021. The most noticeable reductions were in
eastern sub-Saharan Africa, with a decrease of 0·2 years,
followed by western sub-Saharan Africa, which lost
0·1 years in life expectancy over the same period.
At the national level, some of the highest gains in life
expectancy between 1990 and 2021 occurred in the eastern
region of sub-Saharan Africa (appendix 2 figure S12). Life
expectancy in Ethiopia increased by 18·2 years (95% UI
16·3–19·8) as a result of reductions in deaths from many
causes, most notably other communicable and maternal
disorders (3·2 years), tuberculosis (3·1 years), and enteric
infectious diseases (2·4 year). The largest reduction in life
expectancy occurred in Lesotho, at 12·9 years (10·1–15·7),
largely attributed to increased deaths from HIV/AIDS,
which resulted in a reduction of 7·3 years (appendix 2
figures S12, S27, table S4).
Figure 6: Effect of COVID-19 on life expectancy by GBD region, 2019–21
For readability, labels indicating a change in life expectancy of less than 0·05 years are not shown. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study.
East Asia, –0·0 years
High-income Asia Pacific, –0·1 years
Australasia, –0·1 years
Western Europe, –1·0 years
Southeast Asia, –1·4 years
Oceania, –1·5 years
Western sub-Saharan Africa, –1·8 years
High-income North America, –1·8 years
South Asia, –1·9 years
Central sub-Saharan Africa, –2·0 years
Central Asia, –2·1 years
Central Europe, –2·2 years
North Africa and Middle East, –2·3 years
Southern Latin America, –2·3 years
Caribbean, –2·4 years
Eastern Europe, –2·6 years
Eastern sub-Saharan Africa, –2·7 years
Southern sub-Saharan Africa, –3·4 years
Tropical Latin America, –3·4 years
Central Latin America, –3·5 years
Andean Latin America, –4·9 years
–5·0 –4·0 –3·0 –2·0 –1·0 0
Change in life expectancy (years)
GBD region
–0·1
–0·1
–1·0
–1·4
–1·5
–1·8
–1·8
–1·9
–2·0
–2·1
–2·2
–2·3
–2·3
–2·4
–2·6
–2·7
–3·4
–3·4
–3·5
–4·9
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Effect of CMNN diseases on life expectancy and trends
in mortality concentration
Among CMNN causes, several key trends emerged in their
eect on global life expectancy and the localisation of
deaths over time. First, the reduction of deaths due to
enteric disease had a substantial impact on global life
expectancy, with notable regional variations (figure 7). As
160 countries and territories made progress in reducing
CMNN disease-related mortality, mortality concentration
emerged. Deaths became more concentrated into certain
countries or regions, persisting alongside advancements
made in other parts of the world. An illustrative example is
the shift in deaths due to enteric diseases in children
younger than 5 years, with 90% of deaths occurring in
locations containing 63% of the population of children
younger than 5 years in 1990, decreasing to locations
containing 51% of the population by 2021 (appendix 2
figure S28). Second, the reduction in the number of lower
respiratory infections yielded positive eects on life
expectancy in some regions. Regions such as Andean Latin
America and western and eastern sub-Saharan Africa had
gains of 1·6 years in life expectancy due to reduced deaths
from lower respiratory infections. This progress is further
underscored by the transformation from 90% of deaths
from lower respiratory infections in children younger than
5 years occurring in locations with 71% of the population
of the under-5 population in 1990 to 90% occurring in
locations with 58% of the under-5 population by 2021,
signalling substantial improvements in some regions and
increased concentration of this cause in others (figure 8;
appendix 2 figure S29). Third, HIV/AIDS had a substantial
impact on life-expectancy trends, particularly in southern
sub-Saharan Africa, and with 90% of deaths concentrated
in locations containing 46% of the entire population and
39% of the under-5 population in 2021 (appendix 2
figures S27, S30). However, HIV/AIDS was less
concentrated in 2021 than in 1990. Fourth, eorts to control
malaria in sub-Saharan Africa resulted in modest gains in
life expectancy. Similarly, 90% of malaria-related deaths in
2021 occurred in locations containing only 12% of the
entire population and 20% of the under-5 population,
showing mortality concentration (figure 5; appendix 2
figures S13, 31). Fifth, reductions in tuberculosis-related
deaths had a positive eect on life expectancy across all
regions, and changes in mortality rates indicated mortality
concentration, with 90% of deaths occurring in locations
containing 66% of the entire population in 1990, decreasing
to 62% by 2021 (figure 9; appendix 2 figure S14). Lastly,
although measles had a relatively small global eect on life
expectancy, this cause showed high mortality concentration.
The disease remained contained globally, with 90% of
deaths concentrated in locations containing only 15% of
the entire population and 24% of the under-5 population in
2021 (figure 3; appendix 2 figure S15).
Reductions in neonatal deaths contributed to a
0·6-year increase in global life expectancy. Also, 90% of
neonatal deaths were concentrated in locations
containing 71% of the population in 1990, decreasing to
51% by 2021 (appendix 2 figures S16, S34). Finally,
nutritional deficiencies had a relatively small global
impact on life expectancy but substantial eects on
specific regions—eastern sub-Saharan Africa, central
Figure 7: Effect of enteric infectious diseases on life expectancy by time period and GBD region, 1990–2021
For readability, labels indicating a change in life expectancy of less than 0·05 years are not shown. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study.
South Asia, 3·1 years
Western sub-Saharan Africa, 2·4 years
Central sub-Saharan Africa, 2·0 years
Eastern sub-Saharan Africa, 1·9 years
Southeast Asia, 1·6 years
Southern sub-Saharan Africa, 0·8 years
Central Latin America, 0·8 years
Tropical Latin America, 0·8 years
Caribbean, 0·7 years
Andean Latin America, 0·7 years
Oceania, 0·6 years
North Africa and Middle East, 0·6 years
Central Asia, 0·4 years
East Asia, 0·2 years
Southern Latin America, 0·1 years
Eastern Europe, 0·0 years
Central Europe, 0·0 years
High-income Asia Pacific, 0·0 years
Australasia, 0·0 years
Western Europe, –0·0 years
High-income North America, –0·0 years
3·53·02·52·01·51·00·5–0·5 0
Change in life expectancy (years)
GBD region
1990–2000
2000–10
2010–19
2019–21
1·4 0·90·7 0·1
0·5 0·81·0 0·2
0·1 0·71·0 0·1
0·6 0·60·5 0·1
1·0 0·40·2
0·3 0·20·3 0·1
0·6 0·2
0·5 0·20·1
0·4 0·10·2
0·4 0·20·1
0·3 0·10·2
0·3 0·20·1
0·2 0·20·1
0·2 0·1
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Figure 8: Effect of lower respiratory infections on life expectancy by time period and GBD region, 1990–2021
For readability, labels indicating a change in life expectancy of less than 0·05 years are not shown. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study.
Western sub-Saharan Africa, 1·6 years
Andean Latin America, 1·6 years
Eastern sub-Saharan Africa, 1·6 years
Central Asia, 1·4 years
Central Sub-Saharan Africa, 1·4 years
East Asia, 1·1 years
South Asia, 1·0 years
North Africa and Middle East, 0·9 years
Southeast Asia, 0·9 years
Oceania, 0·8 years
High-income Asia Pacific, 0·7 years
Central Latin America, 0·6 years
Tropical Latin America, 0·6 years
Southern sub-Saharan Africa, 0·6 years
Caribbean, 0·5 years
Central Europe, 0·3 years
High-income North America, 0·2 years
Western Europe, 0·2 years
Australasia, 0·1 years
Eastern Europe, 0·1 years
Southern Latin America, 0·1 years
1·81·51·21·00·80·50·2–0·2 0
Change in life expectancy (years)
GBD region
1990–2000
2000–10
2010–19
2019–21
0·3 0·6
0·3
0·6
0·7
0·6
0·5
0·2
0·2
0·2
0·10·3
0·20·1
0·1
0·30·3
0·20·1
0·10·1
0·2
0·1
0·40·1
0·30·2
0·40·2
0·20·2
0·40·3
0·5
0·2
0·8
0·3
0·5
0·3 0·3
0·4
0·3
0·1 0·1
0·2
0·4
0·4 0·2
–0·1 0·40·2
0·2 0·10·2
0·1 0·10·1
0·1 0·1
0·10·1
0·1 0·10·1
–0·1 0·10·2
–0·1 –0·10·3
Figure 9: Change in life expectancy attributable to leading causes of death among GBD regions, 1990–2021
Each row represents the change in life expectancy from 1990 to 2021 for a given GBD region. A bar to the right of 0 represents an increase in life expectancy due to changes in the given cause, and a bar
to the left of 0 represents a decrease in life expectancy for a given cause. For readability, labels indicating a change in life expectancy of less than 0·3 years are not shown. CKD=chronic kidney disease.
COPD=chronic obstructive pulmonary disease. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study. LRI=lower respiratory infection. NCD=non-communicable disease. OPRM=other
pandemic-related mortality. *Does not include war and terrorism. †Does not include natural disasters.
Eastern sub-Saharan Africa, 10·7 years
East Asia, 9·8 years
Central sub-Saharan Africa, 8·4 years
Western sub-Saharan Africa, 7·9 years
South Asia, 7·8 years
High-income Asia Pacific, 7·1 years
Australasia, 6·6 years
North Africa and Middle East, 5·7 years
Southeast Asia, 5·6 years
Western Europe, 5·5 years
Tropical Latin America, 4·3 years
Southern Latin America, 4·1 years
Central Europe, 4·0 years
Central Asia, 2·9 years
Andean Latin America, 2·6 years
High-income North America, 1·8 years
Oceania, 1·7 years
Caribbean, 1·7 years
Central Latin America, 1·3 years
Eastern Europe, 0·6 years
Southern sub-Saharan Africa, –4·3 years
–10·0 0–0·5 0·5 10·0 15·0
Change in life expectancy (years)
GBD region
COPD
COVID-19
Diabetes and CKD
Digestive diseases
Enteric infections
HIV/AIDS
Ischaemic heart disease
LRI
Malaria
Measles
Natural disasters and conflict and terrorism
Neonatal disorders
Neoplasms
Nutritional deficiencies
OPRM
Other communicable diseases
Other NCDs
Stroke
Suicide and homicide*
Transport injuries
Tuberculosis
Unintentional injuries†
–1·3 –2·7 1·9 1·5 1·6 1·00·9 0·6 0·8 0·8 0·50·4 0·41·61·8
1·5
–1·0
–1·0 –1·8 2·4
–0·8 –1·9 0·5 3·1 1·0
1·0
1·4
0·4 0·9 0·7 1·3 1·80·5 0·5
2·7 1·3 0·5 0·8 0·4
–0·9 –2·3
–0·5
–4·9–1·8
–0·8 –1·4
–0·8
–0·4
–1·4
–1·0
–1·0
–0·8
–2·4 –3·4–1·5
–3·4
–2·3
–1·0
0·4 1·1 0·8 1·0 0·4 1·0 1·4 0·4 0·7
–2·0 2·0 0·4 1·4 1·2 0·60·4 0·5 1·6 0·40·4 1·3 0·4
1·6
1·6
0·8 1·1 0·6 1·5 0·40·4 0·8
0·5 0·9 0·4 0·41·2 0·4
0·4
0·4
0·40·4
0·6 1·1 0·9
0·9
1·1 0·6
0·6 0·7 0·6
1·2 0·9 0·4 0·5
2·0 1·2 0·5 1·0 0·4
0·4 0·8 1·2 0·6 1·0 0·4 1·4
1·4
0·4
0·4
1·5 0·6
0·6 0·7
1·0 0·5 1·1 0·5
–2·2 1·8 0·50·5 0·5
–2·1 0·50·4 1·0 1·4 0·8
0·8
0·5
0·50·5
0·5
0·7 0·7 0·6 1·6
–1·8 1·9 1·3
1·1 0·7
–1·5 0·6 0·6 0·4 0·40·40·8
0·8
–2·4 0·7 1·0 0·5 0·5
–3·5 0·4 0·40·8 0·6
0·4
0·4
0·40·50·90·6
0·6
0·60·40·40·40·5
–2·6 1·0
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sub-Saharan Africa, and south Asia saw notable
increases. We found a shift towards mortality
concentration, with 90% of nutritional deficiency-related
deaths in children younger than 5 years concentrated in
locations containing 49% of the population in this age
group by 2021, compared with 59% in 1990 (appendix 2
figures S18, S35). Overall, CMNN diseases showed a
large degree of mortality concentration.
Effect of NCDs on life expectancy and trends in
mortality concentration
Among NCDs, several findings reflect their eect on
global life expectancy and death concentration. Reductions
in stroke led to a notable gain in life expectancy of
0·8 years, but stroke deaths were not concentrated, with
90% occurring in locations containing 84% of the global
population (appendix 2 figures S23, S36). Similarly,
ischaemic heart disease had a substantial eect on
improvement to life expectancy, contributing 0·6 years to
global life expectancy; yet, as with stroke, ischaemic heart
disease showed little mortality concentration, with 90% of
deaths concentrated in locations containing 84% of
the population in 2021 (appendix 2 figures S17, S37).
Neoplasms added 0·6 years to life expectancy, with high-
income regions greatly benefiting; as with other NCDs,
90% of neoplasms deaths occurred in locations containing
86% of the population in 2021, indicating a consistent risk
of dying from cancer regardless of geography (appendix 2
figures S19, S38). Chronic respiratory diseases contributed
an increase of 0·5 years to life expectancy, with east Asia
contributing the most to this increase through substantial
improvements in mortality in China. Chronic respiratory
diseases also showed little mortality concentration, with
90% of deaths occurring in locations containing 79% of
the population (appendix 2 figures S20, S39). Digestive
diseases and cirrhosis had a substantial negative eect on
life expectancy, with little improvement from 2010 to 2019,
and showed little mortality concentration (appendix 2
figures S21, S40). Diabetes and kidney diseases had a
negative eect on life expectancy, resulting in a global loss
of 0·1 years in life expectancy. This cause also had little
mortality concentration, with 90% of deaths occurring in
locations representing 89% of the population (appendix 2
figures S22, S41). Overall, NCDs largely did not show
concentration, meaning that we did not observe mortality
from these causes moving towards more restricted
geographical areas (appendix 2 figure S42).
Effect of injuries on life expectancy and trends in
mortality concentration
The reduction in transport injuries had a positive eect on
life expectancy, contributing to a gain of 0·2 years.
However, as with NCDs, transport injury-related mortality
was not concentrated, with 90% of deaths concentrated in
locations containing 88% of the population in 1990,
decreasing slightly to 84% of the population by 2021
(appendix 2 figures S24, S43). Unintentional injuries also
showed little mortality concentration, with 90% of deaths
occurring in locations containing 88% of the population in
2021 (appendix 2 figures S26, S44). Lastly, the overall
reduction in mortality rates from self-harm and
interpersonal violence contributed to a 0·2-year increase in
life expectancy with variable mortality concentration,
showing concentration in central and tropical Latin
America and South Africa, but not exclusively in these
locations (appendix 2 figures S25, S45).
Discussion
Main findings
The COVID-19 pandemic has emerged as one of the most
defining global health events of recent history. Our latest
comprehensive estimates of cause-specific mortality give
insight into the global landscape of disease before and
during the first 2 years of the pandemic, revealing the
important changes in disease-burden patterns that
followed. After more than three decades of consistent
improvements in global life expectancy and declining age-
standardised death rates, COVID-19 reversed long-
standing progress and disrupted trends in the
epidemiological transition. As the second leading cause of
age-standardised deaths in 2021, COVID-19 had a
pronounced influence on the reduction in global life
expectancy that occurred. The heterogeneous influence of
the disease across the globe provides important insights
for improving future pandemic preparedness and
ensuring that nations are equitably equipped to respond to
new outbreaks. Additionally, our analysis of geographical
and temporal trends in mortality enables us to observe the
changing patterns in causes of death worldwide. Many
causes have exhibited a reduced geographical reach—a
reflection of dedicated and persistent mitigation eorts to
reduce the burden of certain causes, as well as potential
changes to risk-factor exposure.15 This study oers an
opportunity to apply the lessons learned from these
successes to further reduce deaths from causes that are
now present within smaller, more concentrated areas
throughout the world.
The COVID-19 pandemic
The emergence and spread of COVID-19 follows a similar
pattern of regional heterogeneity that is common among
many leading communicable causes of death, with higher
rates of infection and increased fatalities occurring in
lower-resource settings.6,16,17 Although heterogeneity in
COVID-19 outcomes in 2020 and 2021 varied by the
income status of a country or territory, outcomes were also
directly related to age, government actions to close borders,
and the implementation of transmission-reduction
policies.18 This general pattern did not always hold true at
the national level, however, where estimates from some
high-income countries showed a much greater burden
than would have been expected, indicating important
opportunities for improved pandemic preparedness and
response in these nations.19 The varying eects across
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locations emphasises the complexity of the pandemic.
Diverse social, economic, and political influences
contributed to the variations in death rates observed
between locations. In general, areas with advanced health-
care systems and robust medical facilities were better able
to manage abrupt increases in the number of COVID-19
cases. By contrast, locations with poorer health-care
infrastructure were less equipped to handle the surge in
infections that occurred,20 although strong health-care
systems did not singularly influence the outcome of the
pandemic.19 Improving preparedness for future pandemics
should also include engagement strategies to enhance the
trust that individuals place in public health recom-
mendations.19 Additionally, identifying methods to
enhance death-reporting systems3 and overcome political
obstacles to ensure accurate reporting will be crucial steps
for monitoring COVID-19 and future pandemic
occurrences.21,22
Our study shows that COVID-19 was one of the leading
global causes of death during the first 2 years of the
pandemic and provides an opportunity to delineate
between the disease’s direct and indirect mortality eects
as well as its eect on life expectancy. As previously
predicted,3 COVID-19 shifted baseline patterns of
mortality for diseases and injuries that were aected by
physical-distancing measures and other government-
mandated restrictions. Deferred care-seeking during the
height of the pandemic also probably contributed to
shifts in patterns of mortality for some diseases and
injuries and might also have contributed to the
emergence of pandemic-related deaths not attributable
directly to COVID-19, lower respiratory infections,
measles, malaria, or pertussis (OPRM). Deferred care-
seeking might also have been a contributing factor in the
notable divergence in the age distribution in deaths
between COVID-19 and OPRM, whereby COVID-19
deaths were substantially higher in older ages, whereas
the highest rate of OPRM was seen in older ages as well
as in children younger than 23 months. Mortality might
have increased in the youngest ages because caregivers
might have hesitated to seek medical care during the
peak of the virus’s spread. Understanding these
disparities is imperative for shaping future health
policies and preparedness eorts.
Important trends in life expectancy
Advancements over the past three decades in the
prevention and control of infectious diseases have
contributed to increases in life expectancy in many
locations, increasing the need to support populations
living with NCDs.23 The global decline in life expectancy
that occurred in 2020 and 2021 confounds the longer-
term trend of increase.10 Our decomposition analysis
suggests that this decline was predominantly a result of
the pandemic (combined COVID-19 and OPRM), but the
degree of severity varied greatly by location. Although
large improvements in many causes—including
HIV/AIDS and lower respiratory and enteric infections—
somewhat counterbalanced the decline, the decrease in
life expectancy was also compounded by increasing rates
of mortality from other causes, such as diabetes and
kidney diseases.
The eect of COVID-19 on life expectancy showed
varying degrees of severity, ranging from a large loss of
4·9 years in Andean Latin America to almost no change
in east Asia. From 1990 to 2021, reductions in many of
the leading causes of death resulted in overall life-
expectancy increases across most regions, despite heavy
setbacks for many because of the COVID-19 pandemic.
We found that despite Andean Latin America having the
largest regional reduction in life expectancy due to the
pandemic, overall life-expectancy reductions across the
region were tempered by improvements in other causes,
with reductions in rates of death from lower respiratory
infections and neonatal disorders responsible for an
increase in life expectancy of 2·6 years overall between
1990 and 2021. The impressive reductions in neonatal
disorders throughout many countries in Andean Latin
America have been attributed to the improvements made
in implementing eective maternal and neonatal health
intervention strategies.24
The reduction in life expectancy in southern sub-
Saharan Africa also exceeded the global average by a
substantial margin, with a reduction of 3·4 years due to
COVID-19. Although life expectancy in the region was
substantially aected by the COVID-19 pandemic, the
reduction was also attributable to high mortality rates
from HIV/AIDS. Some nations with high pandemic-
related death tolls were among those already burdened
by high rates of other infectious diseases. Several
countries in southern sub-Saharan Africa navigated the
challenges of the pandemic, alongside long histories of
combatting some of the highest HIV/AIDS prevalence
rates in the world.25,26 A subset of countries were faced
with a triple burden of COVID-19, HIV/AIDS, and
tuberculosis.27 The combined burden of these causes
across southern sub-Saharan Africa was not oset by
sucient improvements in mortality from other causes,
leading to an overall reduction in the region’s life
expectancy of more than 4 years over the entire study
period.
Cause-specific patterns of mortality concentration
Estimates of mortality concentration reflect shifting
patterns of disease over time, from diseases that have a
widespread presence moving to more geographically
reduced subsets of the global population. These changes
highlight dierences between populations and their
progress towards reducing mortality due to diseases and
injuries. These findings also provide an important
opportunity to improve how best public health practices
are applied to further disease reduction. Broadly,
widespread declines in many communicable diseases
resulted in mortality from these causes exhibiting more
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2119
concentrated geographical distributions in 2021 relative to
patterns seen in 1990. The degree of mortality concentration
estimated by this study for enteric and lower respiratory
infections, malaria, HIV/AIDS, neonatal disorders, and
tuberculosis reflects substantial global progress in
reducing mortality from these causes over the study
period, underscoring the success of several public health
campaigns, global commitments, and improvements in
communicable-disease programmes.28–30 Estimates of
mortality concentration can be used to examine where
disease mitigation strategies have been successful, where
they can be further implemented to reduce inequality, and
where more research might be needed to develop eective
treatment and intervention strategies.
Notably, our estimates support previous findings31 that
show deaths from malaria are becoming increasingly
concentrated and are now particularly concentrated
within western sub-Saharan Africa, with an additional
corridor running through central Africa and into
Mozambique. Countries in western sub-Saharan Africa
with the highest under-5 death rates from malaria in
2021 included Burkina Faso, Sierra Leone, and Niger.
This concentration of malaria mortality reflects both
dierential rates of population growth across Africa, as
well as the varying rates of progress in reducing
transmission, most notably by malaria nets treated with
long-lasting insecticide and in strengthening case
management.32 At a time of growing threats to progress
against malaria, including emerging parasite and vector
resistance and budgetary pressures, but also amid
promising new tools such as second vaccine for malaria,
it is more important than ever that changing patterns of
mortality are quantified and understood.33,34
Enteric infections showed large disease concentration.
Under-5 deaths from enteric infections were largely
concentrated within sub-Saharan Africa and south Asia.
Countries in sub-Saharan Africa and south Asia with the
highest under-5 death rates from enteric infections in
2021 included Chad, South Sudan, and the Central African
Republic. There are many contributing factors that should
be considered when examining how to reduce enteric
infections in the remaining concentrated locations.
Alongside the provision of oral rehydration solution and
rotavirus vaccines, critical public health improvements
such as in water, sanitation, and hygiene might have
contributed to decreases in enteric deaths.35,36 Childhood
growth failure, also a leading risk factor for deaths from
lower respiratory infections, malaria, and measles, must
be addressed through interventions to improve women’s
health including anaemia, promotion of early exclusive
breastfeeding, and management of acute malnutrition,
among others.37,38 Countries with the highest burden of
infectious disease mortality in children younger than
5 years tend to be geographically clustered, suggesting
multisectoral approaches are necessary to continue
reducing mortality in the countries with the highest
rates.39
A broad and recurring theme from this study is that
reductions in enteric infections contributed to improved
life expectancies over the past several decades. The
reductions in childhood mortality associated with
diarrhoeal diseases that have occurred across many parts
of Africa35,40–42 can also be partly explained by many
combined local eorts in improved immunisation;43 access
to water, sanitation, and hygiene facilities;12,44
breastfeeding;45 oral rehydration therapy;46 and zinc
supplementation,15 alongside global initiatives such as the
Global Action Plan for the Prevention and Control of
Pneumonia and Diarrhea.47 Given that enteric disease-
related mortality and specifically diarrhoeal disease-related
mortality continued to decline during the COVID-19
pandemic, the post-pandemic period might oer
opportunities to accelerate progress on prevention and
treatment. Diarrhoeal diseases are particularly amenable
to public health intervention, and given this cause’s high
burden among children, we must continue to direct
resources towards its prevention.47,48 Several locations still
do not have the necessary financing, governance, and
political commitment to reduce rates of enteric infections.49
To accelerate progress in reducing enteric disease-related
mortality, routine and catch-up immunisation programmes
must be strengthened and expanded, including building
on the global success of the rotavirus roll-out50 and
countering disruptions in childhood immunisation during
the pandemic.51 Additionally, eorts should focus on
advancing candidate vaccines against enterotoxigenic
Escherichia coli, norovirus, and shigella.51–55
Our study also found that some vaccine-preventable
diseases, such as measles, have shown widespread
reductions in mortality rates and were geographically
concen trated. Under-5 deaths from measles were
concentrated within western and eastern sub-Saharan
Africa. Although multiple factors contribute to decreases
in infectious disease burden, improvements in measles
mortality have largely been attributable to the global
availability of a safe and eective vaccine against measles,
producing life-long immunity, with two-dose ecacy
exceeding 95%.56 Measles incidence has decreased
dramatically where vaccination eorts have been
successful, including North America, South America,
Europe, and Australia;57–61 although, since 2016, endemic
measles transmission has been re-established in ten
countries that previously had achieved measles
elimination.61 We found that, as of 2021, measles mortality
was concentrated in countries and regions with
insucient access to the measles vaccine, particularly in
sub-Saharan Africa. Although valuable insights can be
drawn from countries that have achieved measles control
through eective vaccination programmes and
surveillance systems, interventions still must be tailored
to the aected communities and countries for successful
reductions in mortality.62
Some infectious diseases, such as HIV/AIDS, also
showed mortality concentration. Deaths from HIV/AIDS
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were largely concentrated within sub-Saharan Africa, most
notably southern sub-Saharan Africa. Countries in sub-
Saharan Africa with the highest age-standardised mortality
rate in 2021 included Lesotho, Eswatini, and Botswana.
Countries in sub-Saharan Africa with the highest under-5
death rates from HIV in 2021 included Lesotho, Equatorial
Guinea, and Guinea-Bissau. This concentration highlights
how HIV-control campaigns, preventative measures,63,64
improved treatment with the emergence of antiretroviral
therapy,65 access to testing and health care,66 and research
advancements might have contributed to the reduced
global mortality of HIV. Despite these successes,
substantial barriers remain to reducing HIV mortality,
such as stigma discouraging people from accessing
treatment and care,67,68 insucient health-care
infrastructure,69 access to testing,70 coverage of antiretroviral
therapy,71 and complications due to co-occurring diseases
such as tuberculosis and HIV.72 Preventative measures are
particularly important for the reduction of HIV mortality
because HIV prevalence is the primary contributor to high
mortality rates. Although countries can learn from
successful HIV campaigns and strategies, global support
is needed to ensure HIV treatment and preventative
measures are accessible to all populations at risk.70,73,74
In many high-income nations, the overall rate of
neonatal deaths decreased between 1990 and 2021,
becoming more concentrated over time. Deaths from
neonatal disorders in 2021 were concentrated within sub-
Saharan Africa and south Asia.75 Countries in these
regions with the highest under-5 death rates from
neonatal disorders in 2021 included Mali, South Sudan,
and Sierra Leone. However, the disparity in mortality
between high-income and low-income countries and
regions highlights inequality in progress. Newborn care
that can reduce mortality includes resuscitation,
prevention of hypothermia and infection, in-facility
delivery, and exclusive breastfeeding.76,77 Neonatal
mortality might be reduced globally if policy makers
examine the strategies that led to successes elsewhere.78
Conversely, although the burden of many NCDs has
also been reducing, these causes have typically not
followed the same pattern of mortality concentration
seen in CMNN diseases. These trends emphasise a key
distinction in the spatial dynamics of NCDs compared
with many communicable diseases. Although non-
communicable causes might not exhibit the same degree
of concentration as communicable causes, the mortality
burden has changed in distribution, reducing over time
in high-income countries and regions, while persisting
in low-income countries and regions. Age-standardised
mortality rates due to NCDs decreased in most locations
within the high-income; Latin America and the
Caribbean; north Africa and the Middle east; and central
Europe, eastern Europe, and central Asia super-regions
between 1990 and 2021. However, NCDs in the south
Asia; sub-Saharan Africa; and southeast Asia, east Asia,
and Oceania super-regions have either increased or
decreased at notably lower levels in 2021 compared with
in 1990. Examples of this trend include ischaemic heart
disease, neoplasms, and stroke, all of which largely
declined over the study period—although their
reductions have been widely dispersed and not as
targeted as the CMNN causes. These findings show that
NCDs do not appear to be moving towards more
condensed geographical locations over time in the same
way that many CMNN diseases are, which could make
interventions and policies more complex to implement.
Ultimately, the extent of mortality concentration
reflects both the progress achieved in health-care
advancements and the shortcomings that persist in their
equitable implementation. Disease concentration is
evidence that there are eective interventions and
policies that have successfully reduced disease burden in
many locations, but these innovations have not been
equitably distributed throughout the world or have been
ineective at addressing the specific challenges certain
populations face. There remains a global need to improve
access to new interventions and vaccines, to invest in the
implementation of validated public health policies, and
to strategise with geographical sources of disease in
mind. Future eorts should continue the ongoing
mitigation of communicable diseases, focusing on
locations where these causes have become more
geographically concentrated, while also initiating eorts
to combat chronic causes within low-resourced settings.
Additionally, patterns of high geographical concentration
among infectious causes and low geographical
concentration among chronic causes reflect the global
epidemiological transition, wherein mortality rates of
infectious deaths declined throughout most years of our
study. The increased concentration of a cause of death,
particularly communicable diseases, illustrates success
in mitigation that can be adapted within the countries
and regions with mortality concentration identified in
our study, with the potential to greatly reduce mortality
from those causes of death.
Limitations
Methodological advancements have enabled GBD 2021
to produce cause-specific estimates of mortality more
easily than in previous iterations; however, as with any
study of this scope, there are several important limitations
to acknowledge. Cause-specific limitations for every
cause of death in GBD are detailed in appendix 1
(section 3). Here, we describe cross-cutting limitations
with applicability across many causes. First, sparsity of
data or unreliability of data from specific regions, time
periods, or age groups can influence the accuracy of our
estimates, particularly poor data quality and coverage
from western, eastern, southern, and central sub-
Saharan Africa and south Asia. Second, the quality of
cause-of-death and verbal-autopsy data rely on accurately
coded death certificates to the international standards set
by the International Classification of Diseases and are
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2121
subject to the practice of the doctor completing the death
certificate, who may or may not have received training to
facilitate comparability of reporting underlying causes
of death. This process is further complicated by
comorbidities at the time of death, which might aect
the accuracy of both vital-registration and verbal-autopsy
data sources. A key data-processing method for GBD is
the re-allocation of incorrectly or vaguely assigned
deaths—referred to as garbage codes11—to a more
accurate, plausible underlying cause of death. This step
helps to create comparable cause-specific estimates of
mortality by underlying cause. Third, GBD assesses
quality of cause-of-death data partly by examining levels
of completeness, which indicate the accuracy with which
the vital registration can capture deaths that occur in a
location-year, irrespective of the percentage of garbage
coding. Data completeness depends on the percentage of
well-certified data, which is not necessarily indicative of
low garbage coding. Fourth, some sources of uncertainty,
including the covariates used in models, are not captured
in our estimation process. Fifth, we used a negative
binomial modelling approach to improve our estimation
of deaths for some causes with over-dispersed data, but
do not have a standardised empirical approach for
selecting causes to which we apply this method. Sixth, to
provide estimates for locations with low levels of
completeness, as well as to address the lags in data
reporting that occur, our estimates for the most recent
years depend more heavily on the modelling process. For
causes where data are limited, providing estimates with
appropriate uncertainty is preferable to providing no
information. Seventh, in the calculation of life expectancy
decomposition, there is instability when the dierence in
all-cause deaths is too small. In this case, we use the
reduced Das Gupta equation (appendix 1 section 7).
Additionally, to avoid assigning positive life-expectancy
contributions to COVID-19-related causes, if the signs
for the change in life expectancy and all-cause deaths
were the same, we used the same reduced Das Gupta
formula, except in the case that the cause in question was
COVID-19-related (either COVID-19 or OPRM), when a
modified version was used. When viewing life expectancy
decomposition, it is important to understand the eects
of fatal discontinuity events, such as earthquakes or
conflict. If life-expectancy decomposition is calculated for
2 consecutive years, we can see the eect of unique,
stochastic events, but for the longer time periods, the
interpretation of the eect of these events will be
misleading. This method works well with causes that
have continuous time trends, and not for causes that
have mortality spikes in select years and locations. This
type of event confounds true health trends within a time
period because the absence or presence of a disaster is
seen as a change in life expectancy. Finally, this cycle of
GBD contains additional limitations that pertain to
modelling deaths and related mortality from the
COVID-19 pandemic. The limitations of the methods
used to calculate COVID-19 have been fully outlined in
previous publications,12 but it is important to reiterate
that COVID-19 estimates are limited by data-source
availability. The methods to estimate COVID-19-related
deaths were especially limited in certain regions, such as
sub-Saharan Africa, which means our estimates in these
areas are solely driven by relationships with covariates.
Future development of these data sources is crucial
because estimates improve as the quality of the
underlying data sources improves. Subsequent GBD
cycles will provide revised estimates after additional data
for recent years become available.
Future directions
In the next iteration of GBD, we will include over
100 location-years of vital registration and other data
types that have been reported since GBD 2021 estimates
were produced. Additionally, we will continue to expand
the estimation of causes of death by disaggregating broad
categories of causes of death into more detailed causes
where available. These improvements aim to enhance
precision and timeliness of estimates of COVID-19-
related deaths and other cause of death. We also plan to
simplify our approach to estimating COVID-19-related
deaths. In lieu of the residual OPRM category reported in
GBD 2021, we will use all available location-years of
cause-of-death data to attribute mortality to specific
causes, removing this residual category. We anticipate
that this method will facilitate more timely and actionable
insights for public health planning and policy making,
especially as we expect to observe more regular and
modellable mortality patterns in the post-pandemic
years. Through these advancements, we will improve the
utility and accuracy of the GBD study as a tool for
eective public strategies.
Conclusion
Findings from GBD 2021 provide a comprehensive
overview of long-term mortality trends along with
important insights into the COVID-19 pandemic years.
The COVID-19 pandemic fundamentally changed the
landscape of global health and mortality. As a leading
cause of death, COVID-19 reduced life expectancy in
2 years nearly as much as reductions in communicable
and NCDs have improved it over decades. The changes in
mortality caused by the pandemic were not predictable
through the standard GBD estimation methods and
required the development and application of novel
estimation methods as the pandemic emerged in real
time. These timely updates on causes of death are
essential for monitoring progress, identifying prevailing
health concerns, guiding targeted interventions, and
optimising resource allocation. GBD 2021 shows that
better life expectancy outcomes might be achieved by
leveraging past successes in mortality reduction. If future
policy eorts are guided by the successes made in
countries and regions with eective disease-mitigation
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programmes, such achievements might be replicated in
locations where high mortality persists. While COVID-19
and other health challenges continue, GBD 2021 can oer
valuable guidance for public health investment and policy
making.
GBD 2021 Causes of Death Collaborators
Mohsen Naghavi*, Kanyin Liane Ong*, Amirali Aali, Hazim S Ababneh,
Yohannes Habtegiorgis Abate, Cristiana Abbafati,
Rouzbeh Abbasgholizadeh, Mohammadreza Abbasian,
Mohsen Abbasi-Kangevari, Hedayat Abbastabar, Samar Abd ElHafeez,
Michael Abdelmasseh, Sherief Abd-Elsalam, Ahmed Abdelwahab,
Mohammad Abdollahi, Mohammad-Amin Abdollahifar,
Meriem Abdoun, Deldar Morad Abdulah, Auwal Abdullahi,
Mesfin Abebe, Samrawit Shawel Abebe, Aidin Abedi,
Kedir Hussein Abegaz, E S Abhilash, Hassan Abidi, Olumide Abiodun,
Richard Gyan Aboagye, Hassan Abolhassani, Meysam Abolmaali,
Mohamed Abouzid, Girma Beressa Aboye, Lucas Guimarães Abreu,
Woldu Aberhe Abrha, Dariush Abtahi, Samir Abu Rumeileh,
Hasan Abualruz, Bilyaminu Abubakar, Eman Abu-Gharbieh,
Niveen ME Abu-Rmeileh, Salahdein Aburuz, Ahmed Abu-Zaid,
Manfred Mario Kokou Accrombessi, Tadele Girum Adal,
Abdu A Adamu, Isaac Yeboah Addo, Giovanni Addolorato,
Akindele Olupelumi Adebiyi, Victor Adekanmbi, Abiola Victor Adepoju,
Charles Oluwaseun Adetunji, Juliana Bunmi Adetunji,
Temitayo Esther Adeyeoluwa, Daniel Adedayo Adeyinka,
Olorunsola Israel Adeyomoye, Biruk Adie Adie Admass,
Qorinah Estiningtyas Sakilah Adnani, Saryia Adra,
Aanuoluwapo Adeyimika Afolabi, Muhammad Sohail Afzal, Saira Afzal,
Suneth Buddhika Agampodi, Pradyumna Agasthi, Manik Aggarwal,
Shahin Aghamiri, Feleke Doyore Agide, Antonella Agodi,
Anurag Agrawal, Williams Agyemang-Duah, Bright Opoku Ahinkorah,
Aqeel Ahmad, Danish Ahmad, Firdos Ahmad, Muayyad M Ahmad,
Sajjad Ahmad, Shahzaib Ahmad, Tauseef Ahmad, Keivan Ahmadi,
Amir Mahmoud Ahmadzade, Ali Ahmed, Ayman Ahmed,
Haroon Ahmed, Luai A Ahmed, Mehrunnisha Sharif Ahmed,
Meqdad Saleh Ahmed, Muktar Beshir Ahmed, Syed Anees Ahmed,
Marjan Ajami, Budi Aji, Essona Matatom Akara, Hossein Akbarialiabad,
Karolina Akinosoglou, Tomi Akinyemiju, Mohammed Ahmed Akkaif,
Samuel Akyirem, Hanadi Al Hamad, Syed Mahfuz Al Hasan,
Fares Alahdab, Samer O Alalalmeh, Tariq A Alalwan, Ziyad Al-Aly,
Khurshid Alam, Manjurul Alam, Noore Alam,
Rasmieh Mustafa Al-amer, Fahad Mashhour Alanezi, Turki M Alanzi,
Sayer Al-Azzam, Almaza Albakri, Mohammed Albashtawy,
Mohammad T AlBataineh, Jacqueline Elizabeth Alcalde-Rabanal,
Khalifah A Aldawsari, Wafa A Aldhaleei, Robert W Aldridge,
Haileselasie Berhane Alema, Mulubirhan Assefa Alemayohu,
Sharifullah Alemi, Yihun Mulugeta Alemu, Adel Ali Saeed Al-Gheethi,
Khalid F Alhabib, Fadwa Alhalaiqa Naji Alhalaiqa,
Mohammed Khaled Al-Hanawi, Abid Ali, Amjad Ali, Liaqat Ali,
Mohammed Usman Ali, Rafat Ali, Shahid Ali, Syed Shujait Shujait Ali,
Gianfranco Alicandro, Sheikh Mohammad Alif, Reyhaneh Alikhani,
Yousef Alimohamadi, Ahmednur Adem Aliyi, Mohammad A M Aljasir,
Syed Mohamed Aljunid, François Alla, Peter Allebeck,
Sabah Al-Marwani, Sadeq Ali Ali Al-Maweri, Joseph Uy Almazan,
Hesham M Al-Mekhlafi, Louay Almidani, Omar Almidani,
Mahmoud A Alomari, Basem Al-Omari, Jordi Alonso, Jaber S Alqahtani,
Shehabaldin Alqalyoobi, Ahmed Yaseen Alqutaibi,
Salman Khalifah Al-Sabah, Zaid Altaany, Awais Altaf, Jaar A Al-Tawfiq,
Khalid A Altirkawi, Deborah Oyine Aluh, Nelson Alvis-Guzman,
Hassan Alwafi, Yaser Mohammed Al-Worafi, Hany Aly, Safwat Aly,
Karem H Alzoubi, Reza Amani, Azmeraw T Amare, Prince M Amegbor,
Edward Kwabena Ameyaw, Tarek Tawfik Amin, Alireza Amindarolzarbi,
Sohrab Amiri, Mohammad Hosein Amirzade-Iranaq, Hubert Amu,
Dickson A Amugsi, Ganiyu Adeniyi Amusa, Robert Ancuceanu,
Deanna Anderlini, David B Anderson, Pedro Prata Andrade,
Catalina Liliana Andrei, Tudorel Andrei, Colin Angus, Abhishek Anil,
Sneha Anil, Amir Anoushiravani, Hossein Ansari, Ansariadi Ansariadi,
Alireza Ansari-Moghaddam, Catherine M Antony, Ernoiz Antriyandarti,
Davood Anvari, Saeid Anvari, Saleha Anwar, Sumadi Lukman Anwar,
Razique Anwer, Anayochukwu Edward Anyasodor, Muhammad Aqeel,
Juan Pablo Arab, Jalal Arabloo, Mosab Arafat, Aleksandr Y Aravkin,
Demelash Areda, Abdulfatai Aremu, Olatunde Aremu, Hany Arin,
Mesay Arkew, Benedetta Armocida, Michael Benjamin Arndt,
Johan Ärnlöv, Mahwish Arooj, Anton A Artamonov, Judie Arulappan,
Raphael Taiwo Aruleba, Ashokan Arumugam, Malke Asaad,
Mohsen Asadi-Lari, Akeza Awealom Asgedom,
Mona Asghariahmadabad, Mohammad Asghari-Jafarabadi,
Muhammad Ashraf, Armin Aslani, Thomas Astell-Burt,
Mohammad Athar, Seyyed Shamsadin Athari,
Bantalem Tilaye Tilaye Atinafu, Habtamu Wondmagegn Atlaw,
Prince Atorkey, Maha Moh’d Wahbi Atout, Alok Atreya, Avinash Aujayeb,
Marcel Ausloos, Abolfazl Avan, Atalel Fentahun Awedew,
Amlaku Mulat Aweke, Beatriz Paulina Ayala Quintanilla,
Haleh Ayatollahi, Jose L Ayuso-Mateos, Seyed Mohammad Ayyoubzadeh,
Sina Azadnajafabad, Rui M S Azevedo, Ahmed Y Azzam, Darshan B B,
Abraham Samuel Babu, Muhammad Badar, Ashish D Badiye,
Soroush Baghdadi, Nasser Bagheri, Sara Bagherieh, Sulaiman Bah,
Saeed Bahadorikhalili, Najmeh Bahmanziari, Ruhai Bai, Atif Amin Baig,
Jennifer L Baker, Abdulaziz T Bako, Ravleen Kaur Bakshi,
Senthilkumar Balakrishnan, Madhan Balasubramanian,
Ovidiu Constantin Baltatu, Kiran Bam, Maciej Banach,
Soham Bandyopadhyay, Palash Chandra Banik, Hansi Bansal,
Kannu Bansal, Franca Barbic, Martina Barchitta, Mainak Bardhan,
Erfan Bardideh, Suzanne Lyn Barker-Collo, Till Winfried Bärnighausen,
Francesco Barone-Adesi, Hiba Jawdat Barqawi, Lope H Barrero,
Amadou Barrow, Sandra Barteit, Lingkan Barua, Zarrin Basharat,
Azadeh Bashiri, Afisu Basiru, Pritish Baskaran, Buddha Basnyat,
Quique Bassat, João Diogo Basso, Ann V L Basting, Sanjay Basu,
Kavita Batra, Bernhard T Baune, Mohsen Bayati,
Nebiyou Simegnew Bayileyegn, Thomas Beaney, Neeraj Bedi,
Massimiliano Beghi, Emad Behboudi, Priyamadhaba Behera,
Amir Hossein Behnoush, Masoud Behzadifar, Maryam Beiranvand,
Diana Fernanda Bejarano Ramirez, Yannick Béjot,
Sefealem Assefa Belay, Chalie Mulu Belete, Michelle L Bell,
Muhammad Bashir Bello, Olorunjuwon Omolaja Bello, Luis Belo,
Apostolos Beloukas, Rose Grace Bender, Isabela M Bensenor,
Azizullah Beran, Zombor Berezvai, Alemshet Yirga Berhie,
Betyna N Berice, Robert S Bernstein, Gregory J Bertolacci,
Paulo J G Bettencourt, Kebede A Beyene, Devidas S Bhagat,
Akshaya Srikanth Bhagavathula, Neeraj Bhala, Ashish Bhalla,
Dinesh Bhandari, Kayleigh Bhangdia, Nikha Bhardwaj, Pankaj Bhardwaj,
Prarthna V Bhardwaj, Ashish Bhargava, Sonu Bhaskar, Vivek Bhat,
Gurjit Kaur Bhatti, Jasvinder Singh Bhatti, Manpreet S Bhatti,
Rajbir Bhatti, Zulfiqar A Bhutta, Boris Bikbov, Jessica Devin Bishai,
Catherine Bisignano, Francesca Bisulli, Atanu Biswas, Bijit Biswas,
Saeid Bitaraf, Bikes Destaw Bitew, Veera R Bitra, Tone Bjørge,
Micheal Kofi Boachie, Mary Sefa Boampong, Anca Vasilica Bobirca,
Virginia Bodolica, Aadam Olalekan Bodunrin, Eyob Ketema Bogale,
Kassawmar Angaw Bogale, Somayeh Bohlouli,
Obasanjo Afolabi Bolarinwa, Archith Boloor, Milad Bonakdar Hashemi,
Aime Bonny, Kaustubh Bora, Berrak Bora Basara, Hamed Borhany,
Arturo Borzutzky, Souad Bouaoud, Antoine Boustany, Christopher Boxe,
Edward J Boyko, Oliver J Brady, Dejana Braithwaite, Luisa C Brant,
Michael Brauer, Alexandra Brazinova, Javier Brazo-Sayavera,
Nicholas J K Breitborde, Susanne Breitner, Hermann Brenner,
Andrey Nikolaevich Briko, Nikolay Ivanovich Briko, Gabrielle Britton,
Julie Brown, Traolach Brugha, Norma B Bulamu, Lemma N Bulto,
Danilo Buonsenso, Richard A Burns, Reinhard Busse, Yasser Bustanji,
Nadeem Shafique Butt, Zahid A Butt,
Florentino Luciano Caetano dos Santos, Daniela Calina,
Luis Alberto Cámera, Luciana Aparecida Campos,
Ismael R Campos-Nonato, Chao Cao, Yin Cao, Angelo Capodici,
Rosario Cárdenas, Sinclair Carr, Giulia Carreras, Juan J Carrero,
Andrea Carugno, Cristina G Carvalheiro, Felix Carvalho,
Márcia Carvalho, Joao Mauricio Castaldelli-Maia,
Carlos A Castañeda-Orjuela, Giulio Castelpietra, Ferrán Catalá-López,
Alberico L Catapano, Maria Sofia Cattaruzza, Christopher R Cederroth,
Luca Cegolon, Francieli Cembranel, Muthia Cenderadewi, Kelly M Cercy,
Ester Cerin, Muge Cevik, Joshua Chadwick, Yaacoub Chahine,
Chiranjib Chakraborty, Promit Ananyo Chakraborty,
Jerey Shi Kai Chan, Raymond N C Chan, Rama Mohan Chandika,
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Eeshwar K Chandrasekar, Chin-Kuo Chang, Jung-Chen Chang,
Gashaw Sisay Chanie, Periklis Charalampous, Vijay Kumar Chattu,
Pankaj Chaturvedi, Victoria Chatzimavridou-Grigoriadou,
Akhilanand Chaurasia, Angela W Chen, An-Tian Chen,
Catherine S Chen, Haowei Chen, Meng Xuan Chen, Simiao Chen,
Ching-Yu Cheng, Esther T W Cheng, Nicolas Cherbuin,
Wondimye Ashenafi Cheru, Ju-Huei Chien, Odgerel Chimed-Ochir,
Ritesh Chimoriya, Patrick R Ching, Jesus Lorenzo Chirinos-Caceres,
Abdulaal Chitheer, William C S Cho, Bryan Chong, Hitesh Chopra,
Sonali Gajanan Choudhari, Rajiv Chowdhury,
Devasahayam J Christopher, Isaac Sunday Chukwu, Eric Chung,
Erin Chung, Eunice Chung, Sheng-Chia Chung,
Muhammad Chutiyami, Zinhle Cindi, Iolanda Cio,
Mareli M Claassens, Rafael M Claro, Kaleb Coberly, Rebecca M Cogen,
Alyssa Columbus, Haley Comfort, Joao Conde, Samuele Cortese,
Paolo Angelo Cortesi, Vera Marisa Costa, Simona Costanzo,
Ewerton Cousin, Rosa A S Couto, Richard G Cowden,
Kenneth Michael Cramer, Michael H Criqui, Natália Cruz-Martins,
Silvia Magali Cuadra-Hernández, Garland T Culbreth, Patricia Cullen,
Matthew Cunningham, Maria paula Curado, Sriharsha Dadana,
Omid Dadras, Siyu Dai, Xiaochen Dai, Zhaoli Dai, Lachlan L Dalli,
Giovanni Damiani, Jiregna Darega Gela, Jai K Das, Saswati Das,
Subasish Das, Ana Maria Dascalu, Nihar Ranjan Dash, Mohsen Dashti,
Anna Dastiridou, Gail Davey, Claudio Alberto Dávila-Cervantes,
Nicole Davis Weaver, Kairat Davletov, Diego De Leo, Katie de Luca,
Aklilu Tamire Debele, Shayom Debopadhaya, Louisa Degenhardt,
Azizallah Dehghan, Lee Deitesfeld, Cristian Del Bo’,
Ivan Delgado-Enciso, Berecha Hundessa Demessa,
Andreas K Demetriades, Ke Deng, Xinlei Deng, Edgar Denova-Gutiérrez,
Niloofar Deravi, Nebiyu Dereje, Nikolaos Dervenis, Emina Dervišević,
Don C Des Jarlais, Hardik Dineshbhai Desai, Rupak Desai,
Vinoth Gnana Chellaiyan Devanbu, Syed Masudur Rahman Dewan,
Arkadeep Dhali, Kuldeep Dhama, Meghnath Dhimal, Sameer Dhingra,
Vishal R Dhulipala, Diana Dias da Silva, Daniel Diaz, Michael J Diaz,
Adriana Dima, Delaney D Ding, Huanghe Ding,
Ricardo Jorge Dinis-Oliveira, M Ashworth Dirac, Shirin Djalalinia,
Thao Huynh Phuong Do, Camila Bruneli do Prado, Saeid Doaei,
Masoud Dodangeh, Milad Dodangeh, Sushil Dohare,
Klara Georgieva Dokova, Christiane Dolecek, Regina-
Mae Villanueva Dominguez, Wanyue Dong, Deepa Dongarwar,
Mario D’Oria, Fariba Dorostkar, E Ray Dorsey, Wendel Mombaque
dos Santos, Rajkumar Doshi, Leila Doshmangir, Robert Kokou Dowou,
Tim Robert Driscoll, Haneil Larson Dsouza, Viola Dsouza, Mi Du,
John Dube, Bruce B Duncan, Andre Rodrigues Duraes,
Senbagam Duraisamy, Oyewole Christopher Durojaiye, Laura Dwyer-
Lindgren, Paulina Agnieszka Dzianach, Arkadiusz Marian Dziedzic,
Abdel Rahman E’mar, Ejemai Eboreime, Alireza Ebrahimi,
Chidiebere Peter Echieh, Hisham Atan Edinur, David Edvardsson,
Kristina Edvardsson, Defi Efendi, Ferry Efendi, Diyan Ermawan Eendi,
Terje Andreas Eikemo, Ebrahim Eini, Michael Ekholuenetale,
Temitope Cyrus Ekundayo, Iman El Sayed, Iat Elbarazi,
Teshome Bekele Elema, Noha Mousaad Elemam, Frank J Elgar,
Islam Y Elgendy, Ghada Metwally Tawfik ElGohary,
Hala Rashad Elhabashy, Muhammed Elhadi, Waseem El-Huneidi,
Legesse Tesfaye Elilo, Omar Abdelsadek Abdou Elmeligy,
Mohamed A Elmonem, Mohammed Elshaer, Ibrahim Elsohaby,
Theophilus I Emeto, Luchuo Engelbert Bain,
Ryenchindorj Erkhembayar, Christopher Imokhuede Esezobor,
Babak Eshrati, Sharareh Eskandarieh, Juan Espinosa-Montero,
Habtamu Esubalew, Farshid Etaee, Natalia Fabin,
Adewale Oluwaseun Fadaka, Adeniyi Francis Fagbamigbe,
Ayesha Fahim, Saman Fahimi, Aliasghar Fakhri-Demeshghieh,
Luca Falzone, Mohammad Fareed, Carla Sofia e Sá Farinha,
MoezAlIslam Ezzat Mahmoud Faris, Pawan Sirwan Faris, Andre Faro,
Abidemi Omolara Fasanmi, Ali Fatehizadeh, Hamed Fattahi,
Nelsensius Klau Fauk, Pooria Fazeli, Valery L Feigin, Alireza Feizkhah,
Ginenus Fekadu, Xiaoru Feng, Seyed-Mohammad Fereshtehnejad,
Abdullah Hamid Feroze, Daniela Ferrante, Alize J Ferrari,
Nuno Ferreira, Getahun Fetensa, Bikila Regassa Feyisa, Irina Filip,
Florian Fischer, Joanne Flavel, David Flood, Bobirca Teodor Florin,
Nataliya A Foigt, Morenike Oluwatoyin Folayan,
Artem Alekseevich Fomenkov, Behzad Foroutan, Masoud Foroutan,
Ingeborg Forthun, Daniela Fortuna, Matteo Foschi,
Kayode Raphael Fowobaje, Kate Louise Francis,
Richard Charles Franklin, Alberto Freitas, Joseph Friedman,
Sara D Friedman, Takeshi Fukumoto, John E Fuller, Blima Fux,
Peter Andras Gaal, Muktar A Gadanya, Abhay Motiramji Gaidhane,
Santosh Gaihre, Emmanuela Gakidou, Yaseen Galali, Natalie C Galles,
Silvano Gallus, Mandukhai Ganbat, Aravind P Gandhi,
Balasankar Ganesan, Mohammad Arfat Ganiyani, MA Garcia-Gordillo,
William M Gardner, Jalaj Garg, Naval Garg, Rupesh K Gautam,
Semiu Olatunde Gbadamosi, Tilaye Gebru Gebi, Miglas W Gebregergis,
Mesfin Gebrehiwot, Teferi Gebru Gebremeskel,
Simona Roxana Georgescu, Tamirat Getachew, Peter W Gething,
Molla Getie, Keyghobad Ghadiri, Sulmaz Ghahramani,
Khalid Yaser Ghailan, Mohammad-Reza Ghasemi,
Ghazal Ghasempour Dabaghi, Afsaneh Ghasemzadeh,
Ahmad Ghashghaee, Fariba Ghassemi, Ramy Mohamed Ghazy,
Ajnish Ghimire, Sama Ghoba, Maryam Gholamalizadeh,
Asadollah Gholamian, Ali Gholamrezanezhad, Nasim Gholizadeh,
Mahsa Ghorbani, Pooyan Ghorbani Vajargah, Aloke Gopal Ghoshal,
Paramjit Singh Gill, Tiany K Gill, Richard F Gillum,
Themba G Ginindza, Alem Girmay, James C Glasbey,
Elena V Gnedovskaya, Laszlo Göbölös, Myron Anthony Godinho,
Amit Goel, Ali Golchin, Mohamad Goldust, Mahaveer Golechha,
Pouya Goleij, Nelson G M Gomes, Philimon N Gona,
Sameer Vali Gopalani, Giuseppe Gorini, Houman Goudarzi,
Alessandra C Goulart, Bárbara Niegia Garcia Goulart, Anmol Goyal,
Ayman Grada, Simon Matthew Graham, Michal Grivna,
Giuseppe Grosso, Shi-Yang Guan, Giovanni Guarducci,
Mohammed Ibrahim Mohialdeen Gubari, Mesay Dechasa Gudeta,
Avirup Guha, Stefano Guicciardi, Rafael Alves Guimarães,
Snigdha Gulati, Damitha Asanga Gunawardane, Sasidhar Gunturu,
Cui Guo, Anish Kumar Gupta, Bhawna Gupta, Manoj Kumar Gupta,
Mohak Gupta, Rajat Das Gupta, Rajeev Gupta, Sapna Gupta,
Veer Bala Gupta, Vijai Kumar Gupta, Vivek Kumar Gupta,
Lami Gurmessa, Reyna Alma Gutiérrez, Farrokh Habibzadeh,
Parham Habibzadeh, Rasool Haddadi, Mostafa Hadei, Najah R Hadi,
Nils Haep, Nima Hafezi-Nejad, Alemayehu Hailu, Arvin Haj-Mirzaian,
Esam S Halboub, Brian J Hall, Sebastian Haller, Rabih Halwani,
Randah R Hamadeh, Sajid Hameed, Samer Hamidi, Erin B Hamilton,
Chieh Han, Qiuxia Han, Asif Hanif, Nasrin Hanifi, Graeme J Hankey,
Fahad Hanna, Md Abdul Hannan, Md Nuruzzaman Haque,
Harapan Harapan, Arief Hargono, Josep Maria Haro,
Ahmed I Hasaballah, Ikramul Hasan, M Tasdik Hasan,
Hamidreza Hasani, Mohammad Hasanian, Abdiwahab Hashi,
Md Saquib Hasnain, Ikrama Hassan, Soheil Hassanipour,
Hadi Hassankhani, Johannes Haubold, Rasmus J Havmoeller,
Simon I Hay, Jiawei He, Jerey J Hebert, Omar E Hegazi,
Golnaz Heidari, Mohammad Heidari, Mahsa Heidari-Foroozan,
Bartosz Helfer, Delia Hendrie, Brenda Yuliana Herrera-Serna,
Claudiu Herteliu, Hamed Hesami, Kamal Hezam, Catherine L Hill,
Yuta Hiraike, Ramesh Holla, Nobuyuki Horita, Md Mahbub Hossain,
Sahadat Hossain, Mohammad-Salar Hosseini, Hassan Hosseinzadeh,
Mehdi Hosseinzadeh, Ahmad Hosseinzadeh Adli, Mihaela Hostiuc,
Sorin Hostiuc, Mohamed Hsairi, Vivian Chia-rong Hsieh,
Rebecca L Hsu, Chengxi Hu, Junjie Huang, Michael Hultström,
Ayesha Humayun, Tsegaye Gebreyes Hundie, Javid Hussain,
M Azhar Hussain, Nawfal R Hussein, Foziya Mohammed Hussien,
Hong-Han Huynh, Bing-Fang Hwang, Segun Emmanuel Ibitoye,
Khalid S Ibrahim, Pulwasha Maria Iftikhar, Desta Ijo, Adalia I Ikiroma,
Kevin S Ikuta, Paul Chukwudi Ikwegbue, Olayinka Stephen Ilesanmi,
Irena M Ilic, Milena D Ilic, Mohammad Tarique Imam,
Mustapha Immurana, Sumant Inamdar, Endang Indriasih,
Muhammad Iqhrammullah, Arnaud Iradukunda,
Kenneth Chukwuemeka Iregbu, Md Rabiul Islam,
Sheikh Mohammed Shariful Islam, Farhad Islami, Faisal Ismail,
Nahlah Elkudssiah Ismail, Hiroyasu Iso, Gaetano Isola, Masao Iwagami,
Chidozie C D Iwu, Ihoghosa Osamuyi Iyamu, Mahalaxmi Iyer,
Linda Merin J, Jalil Jaafari, Louis Jacob, Kathryn H Jacobsen,
Farhad Jadidi-Niaragh, Morteza Jafarinia, Abdollah Jafarzadeh,
Khushleen Jaggi, Kasra Jahankhani, Nader Jahanmehr,
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Haitham Jahrami, Nityanand Jain, Ammar Abdulrahman Jairoun,
Abhishek Jaiswal, Elham Jamshidi, Mark M Janko,
Abubakar Ibrahim Jatau, Sabzali Javadov, Tahereh Javaheri,
Sathish Kumar Jayapal, Shubha Jayaram, Rime Jebai, Sun Ha Jee,
Jayakumar Jeganathan, Anil K Jha, Ravi Prakash Jha, Heng Jiang,
Yingzhao Jin, Olatunji Johnson, Mohammad Jokar, Jost B Jonas,
Tamas Joo, Abel Joseph, Nitin Joseph, Charity Ehimwenma Joshua,
Grace Joshy, Jacek Jerzy Jozwiak, Mikk Jürisson, Vaishali K,
Billingsley Kaambwa, Ali Kabir, Zubair Kabir, Vidya Kadashetti,
Dler Hussein Kadir, Rizwan Kalani, Laleh R Kalankesh,
Leila R Kalankesh, Feroze Kaliyadan, Sanjay Kalra, Vineet Kumar Kamal,
Sivesh Kathir Kamarajah, Rajesh Kamath, Zahra Kamiab,
Naser Kamyari, Thanigaivelan Kanagasabai, Tanuj Kanchan,
Himal Kandel, Arun R Kanmanthareddy, Edmund Wedam Kanmiki,
Kehinde Kazeem Kanmodi, Suthanthira Kannan S,
Sushil Kumar Kansal, Rami S Kantar, Neeti Kapoor,
Mehrdad Karajizadeh, Shama D Karanth, Reema A Karasneh,
Ibraheem M Karaye, André Karch, Asima Karim, Salah Eddin Karimi,
Arman Karimi Behnagh, Faizan Zaar Kashoo,
Qalandar Hussein Abdulkarim Kasnazani, Hengameh Kasraei,
Nicholas J Kassebaum, Molly B Kassel, Joonas H Kauppila, Navjot Kaur,
Norito Kawakami, Gbenga A Kayode, Foad Kazemi, Sina Kazemian,
Tahseen Haider Kazmi, Getu Mosisa Kebebew, Adera Debella Kebede,
Fassikaw Kebede, Tibebeselassie S Keflie, Peter Njenga Keiyoro,
Cathleen Keller, Jaimon Terence Kelly, John H Kempen, Jessica A Kerr,
Emmanuelle Kesse-Guyot, Himanshu Khajuria,
Amirmohammad Khalaji, Nauman Khalid, Anees Ahmed Khalil,
Alireza Khalilian, Faham Khamesipour, Ajmal Khan,
Asaduzzaman Khan, Gulfaraz Khan, Ikramullah Khan, Imteyaz A Khan,
M Nuruzzaman Khan, Maseer Khan, Mohammad Jobair Khan,
Moien AB Khan, Zeeshan Ali Khan, Mahammed Ziauddin Khan suheb,
Shaghayegh Khanmohammadi, Khaled Khatab, Fatemeh Khatami,
Haitham Khatatbeh, Moawiah Mohammad Khatatbeh,
Armin Khavandegar, Hamid Reza Khayat Kashani, Feriha Fatima Khidri,
Elaheh Khodadoust, Mohammad Khorgamphar, Moein Khormali,
Zahra Khorrami, Ahmad Khosravi, Mohammad Ali Khosravi,
Zemene Demelash Kifle, Grace Kim, Jihee Kim, Kwanghyun Kim,
Min Seo Kim, Yun Jin Kim, Ruth W Kimokoti, Kasey E Kinzel,
Adnan Kisa, Sezer Kisa, Desmond Klu, Ann Kristin Skrindo Knudsen,
Jonathan M Kocarnik, Sonali Kochhar, Timea Kocsis, David S Q Koh,
Ali-Asghar Kolahi, Kairi Kolves, Farzad Kompani, Gerbrand Koren,
Soewarta Kosen, Karel Kostev, Parvaiz A Koul,
Sindhura Lakshmi Koulmane Laxminarayana, Kewal Krishan,
Hare Krishna, Varun Krishna, Vijay Krishnamoorthy,
Yuvaraj Krishnamoorthy, Kris J Krohn, Barthelemy Kuate Defo,
Burcu Kucuk Bicer, Md Abdul Kuddus, Mohammed Kuddus,
Ilari Kuitunen, Mukhtar Kulimbet, Vishnutheertha Kulkarni,
Akshay Kumar, Ashish Kumar, Harish Kumar, Manasi Kumar,
Rakesh Kumar, Madhulata Kumari, Fantahun Tarekegn Kumie,
Satyajit Kundu, Om P Kurmi, Asep Kusnali, Dian Kusuma,
Alexander Kwarteng, Ilias Kyriopoulos, Hmwe Hmwe Kyu,
Carlo La Vecchia, Ben Lacey, Muhammad Awwal Ladan, Lucie Laflamme,
Abraham K Lagat, Anton C J Lager, Abdelilah Lahmar,
Daphne Teck Ching Lai, Dharmesh Kumar Lal, Ratilal Lalloo,
Tea Lallukka, Hilton Lam, Judit Lám, Kelsey R Landrum,
Francesco Lanfranchi, Justin J Lang, Berthold Langguth,
Van Charles Lansingh, Ariane Laplante-Lévesque, Bagher Larijani,
Anders O Larsson, Savita Lasrado, Zohra S Lassi, Kamaluddin Latief,
Kaveh Latifinaibin, Paolo Lauriola, Nhi Huu Hanh Le, Thao Thi Thu Le,
Trang Diep Thanh Le, Caterina Ledda, Jorge R Ledesma, Munjae Lee,
Paul H Lee, Seung Won Lee, Shaun Wen Huey Lee, Wei-Chen Lee,
Yo Han Lee, Kate E LeGrand, James Leigh, Elvynna Leong,
Temesgen L Lerango, Ming-Chieh Li, Wei Li, Xiaopan Li, Yichong Li,
Zhihui Li, Virendra S Ligade, Andrew Tiyamike Makhiringa Likaka,
Lee-Ling Lim, Stephen S Lim, Megan Lindstrom, Christine Linehan,
Chaojie Liu, Gang Liu, Jue Liu, Runben Liu, Shiwei Liu, Xiaofeng Liu,
Xuefeng Liu, Erand Llanaj, Michael J Loftus, Rubén López-Bueno,
Platon D Lopukhov, Arianna Maever Loreche, Stefan Lorkowski,
Paulo A Lotufo, Rafael Lozano, Jailos Lubinda, Giancarlo Lucchetti,
Alessandra Lugo, Raimundas Lunevicius, Zheng Feei Ma,
Kelsey Lynn Maass, Nikolaos Machairas, Monika Machoy,
Farzan Madadizadeh, Christian Madsen, Áurea M Madureira-Carvalho,
Azzam A Maghazachi, Sandeep B Maharaj, Soleiman Mahjoub,
Mansour Adam Mahmoud, Alireza Mahmoudi, Elham Mahmoudi,
Razzagh Mahmoudi, Azeem Majeed, Irsa Fatima Makhdoom,
Elaheh Malakan Rad, Venkatesh Maled, Reza Malekzadeh,
Armaan K Malhotra, Kashish Malhotra, Ahmad Azam Malik,
Iram Malik, Deborah Carvalho Malta, Abdullah A Mamun,
Pejman Mansouri, Mohammad Ali Mansournia,
Lorenzo Giovanni Mantovani, Sajid Maqsood, Bishnu P Marasini,
Hamid Reza Marateb, Joemer C Maravilla, Agustina M Marconi,
Parham Mardi, Mirko Marino, Abdoljalal Marjani, Gabriel Martinez,
Bernardo Alfonso Martinez-Guerra, Ramon Martinez-Piedra,
Daniela Martini, Santi Martini, Francisco Rogerlândio Martins-Melo,
Miquel Martorell, Wolfgang Marx, Sharmeen Maryam,
Roy Rillera Marzo, Anthony Masaka, Awoke Masrie,
Stephanie Mathieson, Alexander G Mathioudakis, Manu Raj Mathur,
Jishanth Mattumpuram, Richard Matzopoulos, Richard James Maude,
Andrea Maugeri, Pallab K Maulik, Mahsa Mayeli, Maryam Mazaheri,
Mohsen Mazidi, John J McGrath, Martin McKee,
Anna Laura W McKowen, Susan A McLaughlin, Steven M McPhail,
Enkeleint A Mechili, John Robert Carabeo Medina, Rishi P Mediratta,
Jitendra Kumar Meena, Rahul Mehra, Kamran Mehrabani-Zeinabad,
Entezar Mehrabi Nasab, Tesfahun Mekene Meto,
Gebrekiros Gebremichael Meles, Max Alberto Mendez Mendez-Lopez,
Walter Mendoza, Ritesh G Menezes, Belayneh Mengist,
Alexios-Fotios A Mentis, Sultan Ayoub Meo, Haftu Asmerom Meresa,
Atte Meretoja, Tuomo J Meretoja, Abera M Mersha,
Bezawit Afework Mesfin, Tomislav Mestrovic,
Kukulege Chamila Dinushi Mettananda, Sachith Mettananda,
Peter Meylakhs, Adquate Mhlanga, Laurette Mhlanga, Tianyue Mi,
Tomasz Miazgowski, Georgia Micha, Irmina Maria Michalek,
Ted R Miller, Edward J Mills, Le Huu Nhat Minh, GK Mini,
Pouya Mir Mohammad Sadeghi, Andreea Mirica, Antonio Mirijello,
Erkin M Mirrakhimov, Mizan Kiros Mirutse, Maryam Mirzaei,
Awoke Misganaw, Ashim Mishra, Sanjeev Misra, Philip B Mitchell,
Prasanna Mithra, Chaitanya Mittal, Mohammadreza Mobayen,
Madeline E Moberg, Ashraf Mohamadkhani, Jama Mohamed,
Mouhand F H Mohamed, Nouh Saad Mohamed,
Sakineh Mohammad-Alizadeh-Charandabi, Soheil Mohammadi,
Abdollah Mohammadian-Hafshejani, Noushin Mohammadifard,
Hassen Mohammed, Hussen Mohammed, Mustapha Mohammed,
Salahuddin Mohammed, Shafiu Mohammed, Viswanathan Mohan,
Hoda Mojiri-Forushani, Amin Mokari, Ali H Mokdad, Sabrina Molinaro,
Mariam Molokhia, Sara Momtazmanesh, Lorenzo Monasta,
Stefania Mondello, Mohammad Ali Moni, AmirAli Moodi Ghalibaf,
Maryam Moradi, Yousef Moradi, Maziar Moradi-Lakeh,
Maliheh Moradzadeh, Paula Moraga, Lidia Morawska,
Rafael Silveira Moreira, Negar Morovatdar, Shane Douglas Morrison,
Jakub Morze, Jonathan F Mosser, Rohith Motappa, Vincent Mougin,
Simin Mouodi, Parsa Mousavi, Seyed Ehsan Mousavi,
Amin Mousavi Khaneghah, Emmanuel A Mpolya, Matías Mrejen,
Sumaira Mubarik, Lorenzo Muccioli, Ulrich Otto Mueller, Faraz Mughal,
Sumoni Mukherjee, Francesk Mulita, Kavita Munjal,
Efrén Murillo-Zamora, Fungai Musaigwa, Khaled M Musallam,
Ahmad Mustafa, Ghulam Mustafa, Saravanan Muthupandian,
Raman Muthusamy, Muhammad Muzaar, Woojae Myung,
Ahamarshan Jayaraman Nagarajan, Gabriele Nagel, Pirouz Naghavi,
Aliya Naheed, Ganesh R Naik, Gurudatta Naik, Firzan Nainu,
Sanjeev Nair, Hastyar Hama Rashid Najmuldeen,
Noureddin Nakhostin Ansari, Vinay Nangia, Atta Abbas Naqvi,
Sreenivas Narasimha Swamy, Aparna Ichalangod Narayana,
Shumaila Nargus, Bruno Ramos Nascimento, Gustavo G Nascimento,
Samar Nasehi, Abdulqadir J Nashwan, Zuhair S Natto, Javaid Nauman,
Muhammad Naveed, Biswa Prakash Nayak, Vinod C Nayak,
Athare Nazri-Panjaki, Rawlance Ndejjo, Sabina Onyinye Nduaguba,
Hadush Negash, Ionut Negoi, Ruxandra Irina Negoi,
Serban Mircea Negru, Seyed Aria Nejadghaderi, Chakib Nejjari,
Evangelia Nena, Samata Nepal, Marie Ng, Haruna Asura Nggada,
Georges Nguefack-Tsague, Josephine W Ngunjiri, Anh Hoang Nguyen,
Dang H Nguyen, Hau Thi Hien Nguyen, Phat Tuan Nguyen,
Van Thanh Nguyen, Robina Khan Niazi, Katie R Nielsen,
Yeshambel T Nigatu, Taxiarchis Konstantinos Nikolouzakis,
Ali Nikoobar, Fatemeh Nikoomanesh, Amin Reza Nikpoor,
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Dina Nur Anggraini Ningrum, Chukwudi A Nnaji,
Lawrence Achilles Nnyanzi, Efaq Ali Noman, Shuhei Nomura,
Mamoona Noreen, Nafise Noroozi, Bo Norrving, Jean Jacques Noubiap,
Amanda Novotney, Chisom Adaobi Nri-Ezedi, George Ntaios,
Mpiko Ntsekhe, Virginia Nuñez-Samudio, Dieta Nurrika,
Jerry John Nutor, Bogdan Oancea, Kehinde O Obamiro,
Mary Aigbiremo Oboh, Ismail A Odetokun, Nkechi Martina Odogwu,
Martin James O’Donnell, Michael Safo Oduro,
Akinyemi O D Ofakunrin, Abiola Ogunkoya,
Ayodipupo Sikiru Oguntade, In-Hwan Oh, Hassan Okati-Aliabad,
Sylvester Reuben Okeke, Akinkunmi Paul Okekunle,
Osaretin Christabel Okonji, Andrew T Olagunju,
Muideen Tunbosun Olaiya, Matthew Idowu Olatubi,
Gláucia Maria Moraes Oliveira, Isaac Iyinoluwa Olufadewa,
Bolajoko Olubukunola Olusanya, Jacob Olusegun Olusanya,
Yinka Doris Oluwafemi, Hany A Omar, Ahmed Omar Bali,
Goran Latif Omer, Maureene Auma Ondayo, Sokking Ong,
Obinna E Onwujekwe, Kenneth Ikenna Onyedibe, Michal Ordak,
Orish Ebere Orisakwe, Verner N Orish, Doris V Ortega-Altamirano,
Alberto Ortiz, Wael M S Osman, Samuel M Ostro,
Uchechukwu Levi Osuagwu, Adrian Otoiu, Nikita Otstavnov,
Stanislav S Otstavnov, Amel Ouyahia, Guoqing Ouyang,
Mayowa O Owolabi, Yaz Ozten, Mahesh Padukudru P A,
Alicia Padron-Monedero, Jagadish Rao Padubidri, Pramod Kumar Pal,
Tamás Palicz, Claudia Palladino, Raaele Palladino,
Raul Felipe Palma-Alvarez, Feng Pan, Hai-Feng Pan, Adrian Pana,
Paramjot Panda, Songhomitra Panda-Jonas,
Seithikurippu R Pandi-Perumal, Helena Ullyartha Pangaribuan,
Georgios D Panos, Leonidas D Panos, Ioannis Pantazopoulos,
Anca Mihaela Pantea Stoian, Paraskevi Papadopoulou, Romil R Parikh,
Seoyeon Park, Ashwaghosha Parthasarathi, Ava Pashaei, Maja Pasovic,
Roberto Passera, Deepak Kumar Pasupula, Hemal M Patel, Jay Patel,
Sangram Kishor Patel, Shankargouda Patil, Dimitrios Patoulias,
Venkata Suresh Patthipati, Uttam Paudel, Hamidreza Pazoki Toroudi,
Spencer A Pease, Amy E Peden, Paolo Pedersini, Umberto Pensato,
Veincent Christian Filipino Pepito, Emmanuel K Peprah, Prince Peprah,
João Perdigão, Marcos Pereira, Mario F P Peres,
Arokiasamy Perianayagam, Norberto Perico, Richard G Pestell,
Konrad Pesudovs, Fanny Emily Petermann-Rocha, William A Petri,
Hoang Tran Pham, Anil K Philip, Michael R Phillips,
Daniela Pierannunzio, Manon Pigeolet, David M Pigott,
Thomas Pilgrim, Zahra Zahid Piracha, Michael A Piradov,
Saeed Pirouzpanah, Nishad Plakkal, Evgenii Plotnikov, Vivek Podder,
Dimitri Poddighe, Suzanne Polinder, Kevan R Polkinghorne,
Ramesh Poluru, Ville T Ponkilainen, Fabio Porru, Maarten J Postma,
Govinda Raj Poudel, Akram Pourshams, Naeimeh Pourtaheri,
Sergio I Prada, Pranil Man Singh Pradhan, Thejeswar N Prakasham,
Manya Prasad, Akila Prashant, Elton Junio Sady Prates,
Daniel Prieto Alhambra, TINA PRISCILLA, Natalie Pritchett,
Bharathi M Purohit, Jagadeesh Puvvula, Nameer Hashim Qasim,
Ibrahim Qattea, Asma Saleem Qazi, Gangzhen Qian, Suli Qiu,
Maryam Faiz Qureshi, Mehrdad Rabiee Rad, Amir Radfar,
Raghu Anekal Radhakrishnan, Venkatraman Radhakrishnan,
Hadi Raeisi Shahraki, Quinn Raerty, Alberto Raggi,
Pankaja Raghav Raghav, Nasiru Raheem, Fakher Rahim,
Md Jillur Rahim, Vafa Rahimi-Movaghar, Md Mosfequr Rahman,
Mohammad Hifz Ur Rahman, Mosiur Rahman,
Muhammad Aziz Rahman, Amir Masoud Rahmani, Shayan Rahmani,
Vahid Rahmanian, Sathish Rajaa, Prashant Rajput, Ivo Rakovac,
Shakthi Kumaran Ramasamy, Sheena Ramazanu, Kritika Rana,
Chhabi Lal Ranabhat, Nemanja Rancic, Amey Rane, Chythra R Rao,
Indu Ramachandra Rao, Mithun Rao, Sowmya J Rao,
Drona Prakash Rasali, Davide Rasella, Sina Rashedi, Vahid Rashedi,
Mohammad-Mahdi Rashidi, Ashkan Rasouli-Saravani, Azad Rasul,
Giridhara Rathnaiah Babu, Santosh Kumar Rauniyar, Ramin Ravangard,
Nakul Ravikumar, David Laith Rawaf, Salman Rawaf, Lal Rawal,
Reza Rawassizadeh, Bharat Rawlley, Rabail Zehra Raza, Christian Razo,
Elrashdy Moustafa Mohamed Redwan, Faizan Ur Rehman,
Lennart Reifels, Robert C Reiner Jr, Giuseppe Remuzzi,
Luis Felipe Reyes, Maryam Rezaei, Nazila Rezaei, Negar Rezaei,
Mohsen Rezaeian, Taeho Gregory Rhee, Mavra A Riaz,
Antonio Luiz P Ribeiro, Jennifer Rickard, Hannah R Riva,
Hannah Elizabeth Robinson-Oden, Célia Fortuna Rodrigues,
Mónica Rodrigues, Leonardo Roever, Emma Lynn Best Rogowski,
Peter Rohlo, Debby Syahru Romadlon, Esperanza Romero-Rodríguez,
Michele Romoli, Luca Ronfani, Gholamreza Roshandel, Gregory A Roth,
Himanshu Sekhar Rout, Nitai Roy, Priyanka Roy, Enrico Rubagotti,
Guilherme de Andrade Ruela, Susan Fred Rumisha, Tilleye Runghien,
Godfrey M Rwegerera, Andrzej Rynkiewicz, Chandan S N,
Aly M A Saad, Zahra Saadatian, Korosh Saber,
Maha Mohamed Saber-Ayad, Morteza SaberiKamarposhti,
Siamak Sabour, Simona Sacco, Perminder S Sachdev, Rajesh Sachdeva,
Basema Saddik, Adam Saddler, Bashdar Abuzed Sadee, Ehsan Sadeghi,
Erfan Sadeghi, Farideh Sadeghian, Mohammad Reza Saeb, Umar Saeed,
Fahimeh Safaeinejad, Sher Zaman Safi, Rajesh Sagar,
Amene Saghazadeh, Dominic Sagoe, Fatemeh Saheb Sharif-Askari,
Narjes Saheb Sharif-Askari, Amirhossein Sahebkar,
Soumya Swaroop Sahoo, Umakanta Sahoo, Monalisha Sahu, Zahra Saif,
Mirza Rizwan Sajid, Joseph W Sakshaug, Nasir Salam, Payman Salamati,
Afeez Abolarinwa Salami, Luciane B Salaroli, Mohamed A Saleh,
Sana Salehi, Marwa Rashad Salem, Mohammed Z Y Salem,
Sohrab Salimi, Hossein Samadi Kafil, Sara Samadzadeh,
Saad Samargandy, Yoseph Leonardo Samodra, Abdallah M Samy,
Juan Sanabria, Francesca Sanna, Damian Francesco Santomauro,
Itamar S Santos, Milena M Santric-Milicevic, Bruno Piassi Sao Jose,
Made Ary Sarasmita, Sivan Yegnanarayana Iyer Saraswathy,
Aswini Saravanan, Babak Saravi, Yaser Sarikhani, Tanmay Sarkar,
Rodrigo Sarmiento-Suárez, Gargi Sachin Sarode, Sachin C Sarode,
Arash Sarveazad, Brijesh Sathian, Thirunavukkarasu Sathish,
Maheswar Satpathy, Abu Sayeed, Md Abu Sayeed, Mete Saylan,
Mehdi Sayyah, Nikolaos Scarmeas, Benedikt Michael Schaarschmidt,
Markus P Schlaich, Winfried Schlee, Maria Inês Schmidt,
Ione Jayce Ceola Schneider, Art Schuermans, Austin E Schumacher,
Aletta Elisabeth Schutte, Michaël Schwarzinger, David C Schwebel,
Falk Schwendicke, Mario Šekerija, Siddharthan Selvaraj,
Sabyasachi Senapati, Subramanian Senthilkumaran, Sadaf G Sepanlou,
Dragos Serban, Yashendra Sethi, Feng Sha, Maryam Shabany,
Amir Shafaat, Mahan Shafie, Nilay S Shah, Pritik A Shah,
Syed Mahboob Shah, Saeed Shahabi, Ataollah Shahbandi, Izza Shahid,
Samiah Shahid, Wajeehah Shahid, Hamid R Shahsavari,
Moyad Jamal Shahwan, Ahmed Shaikh, Masood Ali Shaikh,
Alireza Shakeri, Ali S Shalash, Sunder Sham,
Muhammad Aaqib Shamim, Mehran Shams-Beyranvand,
Hina Shamshad, Mohammad Anas Shamsi, Mohd Shanawaz,
Abhishek Shankar, Sadaf Sharfaei, Amin Sharifan, Javad Sharifi-Rad,
Rajesh Sharma, Saurab Sharma, Ujjawal Sharma, Vishal Sharma,
Rajesh P Shastry, Amin Shavandi, Maryam Shayan,
Amr Mohamed Elsayed Shehabeldine, Aziz Sheikh, Rahim Ali Sheikhi,
Jiabin Shen, Adithi Shetty, B Suresh Kumar Shetty,
Pavanchand H Shetty, Peilin Shi, Kenji Shibuya, Desalegn Shiferaw,
Mika Shigematsu, Min-Jeong Shin, Youn Ho Shin, Rahman Shiri,
Reza Shirkoohi, Nebiyu Aniley Shitaye, Aminu Shittu, Ivy Shiue,
K M Shivakumar, Velizar Shivarov, Farhad Shokraneh, Azad Shokri,
Sina Shool, Seyed Afshin Shorofi, Sunil Shrestha, Kerem Shuval,
Emmanuel Edwar Siddig, João Pedro Silva,
Luís Manuel Lopes Rodrigues Silva, Soraia Silva, Colin R Simpson,
Anjali Singal, Abhinav Singh, Balbir Bagicha Singh, Garima Singh,
Jasbir Singh, Narinder Pal Singh, Paramdeep Singh, Surjit Singh,
Dhirendra Narain Sinha, Robert Sinto, Md Shahjahan Siraj,
Sarah Brooke Sirota, Freddy Sitas, Shravan Sivakumar,
Valentin Yurievich Skryabin, Anna Aleksandrovna Skryabina,
David A Sleet, Bogdan Socea, Anton Sokhan, Ranjan Solanki,
Shipra Solanki, Hamidreza Soleimani, Sameh S M Soliman,
Suhang Song, Yimeng Song, Reed J D Sorensen, Joan B Soriano,
Ireneous N Soyiri, Michael Spartalis, Sandra Spearman,
Chandrashekhar T Sreeramareddy, Vijay Kumar Srivastava,
Jerey D Stanaway, Muhammad Haroon Stanikzai, Benjamin A Stark,
Joseph R Starnes, Antonina V Starodubova, Caroline Stein, Dan J Stein,
Fridolin Steinbeis, Caitlyn Steiner, Jaimie D Steinmetz,
Paschalis Steiropoulos, Aleksandar Stevanović, Leo Stockfelt,
Mark A Stokes, Stefan Stortecky, Vetriselvan Subramaniyan,
Muhammad Suleman, Rizwan Suliankatchi Abdulkader, Abida Sultana,
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Haitong Zhe Sun, Jing Sun, Johan Sundström, David Sunkersing,
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Mindy D Szeto, Miklós Szócska, Payam Tabaee Damavandi,
Rafael Tabarés-Seisdedos, Seyyed Mohammad Tabatabaei,
Ozra Tabatabaei Malazy, Seyed-Amir Tabatabaeizadeh, Shima Tabatabai,
Mohammad Tabish, Jyothi Tadkamadla, Santosh Kumar Tadakamadla,
Yasaman Taheri Abkenar, Moslem Taheri Soodejani, Jabeen Taiba,
Ken Takahashi, Iman M Talaat, Ashis Talukder, Mircea Tampa,
Jacques Lukenze Tamuzi, Ker-Kan Tan, Sarmila Tandukar, Haosu Tang,
Hong K Tang, Ingan Ukur Tarigan, Mengistie Kassahun Tariku,
Md Tariqujjaman, Elvis Enowbeyang Tarkang, Razieh Tavakoli Oliaee,
Seyed Mohammad Tavangar, Nuno Taveira, Yibekal Manaye Tefera,
Mohamad-Hani Temsah, Reem Mohamad Hani Temsah,
Masayuki Teramoto, Riki Tesler, Enoch Teye-Kwadjo, Rishu Thakur,
Pugazhenthan Thangaraju, Kavumpurathu Raman Thankappan,
Samar Tharwat, Rasiah Thayakaran, Nihal Thomas,
Nikhil Kenny Thomas, Azalea M Thomson, Amanda G Thrift,
Chern Choong Chern Thum, Lau Caspar Thygesen, Jing Tian,
Ales Tichopad, Jansje Henny Vera Ticoalu, Tala Tillawi,
Tenaw Yimer Tiruye, Mariya Vladimirovna Titova, Marcello Tonelli,
Roman Topor-Madry, Adetunji T Toriola, Anna E Torre, Mathilde Touvier,
Marcos Roberto Tovani-Palone, Jasmine T Tran, Nghia Minh Tran,
Domenico Trico, Samuel Joseph Tromans, Thien Tan Tri Tai Truyen,
Aristidis Tsatsakis, Guesh Mebrahtom Tsegay,
Evangelia Eirini Tsermpini, Munkhtuya Tumurkhuu, Kang Tung,
Stefanos Tyrovolas, Sayed Mohammad Nazim Uddin,
Aniefiok John Udoakang, Arit Udoh, Atta Ullah, Irfan Ullah,
Saeed Ullah, Sana Ullah, Srikanth Umakanthan,
Chukwuma David Umeokonkwo, Brigid Unim,
Bhaskaran Unnikrishnan, Carolyn Anne Unsworth, Era Upadhyay,
Daniele Urso, Jibrin Sammani Usman, Seyed Mohammad Vahabi,
Asokan Govindaraj Vaithinathan, Rohollah Valizadeh,
Sarah M Van de Velde, Jef Van den Eynde, Orsolya Varga, Priya Vart,
Shoban Babu Varthya, Tommi Juhani Vasankari, Milena Vasic,
Siavash Vaziri, Balachandar Vellingiri,
Narayanaswamy Venketasubramanian, Nicholas Alexander Verghese,
Madhur Verma, Massimiliano Veroux, Georgios-Ioannis Verras,
Dominique Vervoort, Jorge Hugo Villafañe, Gabriela Ines Villanueva,
Manish Vinayak, Francesco S Violante, Maria Viskadourou,
Sergey Konstantinovitch Vladimirov, Vasily Vlassov, Bay Vo,
Stein Emil Vollset, Avina Vongpradith, Theo Vos, Isidora S Vujcic,
Rade Vukovic, Hatem A Wafa, Yasir Waheed, Richard G Wamai,
Cong Wang, Ning Wang, Shu Wang, Song Wang, Yanzhong Wang,
Yuan-Pang Wang, Muhammad Waqas, Paul Ward,
Emebet Gashaw Wassie, Stefanie Watson,
Stephanie Louise Watson Watson, Kosala Gayan Weerakoon,
Melissa Y Wei, Robert G Weintraub, Daniel J Weiss, Ronny Westerman,
Joanna L Whisnant, Taweewat Wiangkham,
Dakshitha Praneeth Wickramasinghe,
Nuwan Darshana Wickramasinghe, Angga Wilandika,
Caroline Wilkerson, Peter Willeit, Shadrach Wilson,
Marcin W Wojewodzic, Demewoz H Woldegebreal, Axel Walter Wolf,
Charles D A Wolfe, Yohannes Addisu Wondimagegene, Yen Jun Wong,
Utoomporn Wongsin, Ai-Min Wu, Chenkai Wu, Felicia Wu,
Xinsheng Wu, Zenghong Wu, Juan Xia, Hong Xiao, Yang Xie,
Suowen Xu, Wang-Dong Xu, Xiaoyue Xu, Yvonne Yiru Xu,
Ali Yadollahpour, Kazumasa Yamagishi, Danting Yang, Lin Yang,
Yuichiro Yano, Yao Yao, Habib Yaribeygi, Pengpeng Ye,
Sisay Shewasinad Yehualashet, Metin Yesiltepe, Subah Abderehim Yesuf,
Saber Yezli, Siyan Yi, Amanuel Yigezu, Arzu Yiğit, Vahit Yiğit, Paul Yip,
Malede Berihun Yismaw, Yazachew Yismaw, Dong Keon Yon,
Naohiro Yonemoto, Seok-Jun Yoon, Yuyi You, Mustafa Z Younis,
Zabihollah Yousefi, Chuanhua Yu, Yong Yu, Faith H Yuh,
Siddhesh Zadey, Vesna Zadnik, Nima Zafari, Fathiah Zakham,
Nazar Zaki, Sojib Bin Zaman, Nelson Zamora, Ramin Zand,
Moein Zangiabadian, Heather J Zar, Iman Zare, Armin Zarrintan,
Mohammed G M Zeariya, Zahra Zeinali, Haijun Zhang,
Jianrong Zhang, Jingya Zhang, Liqun Zhang, Yunquan Zhang, Zhi-
Jiang Zhang, Hanqing Zhao, Chenwen Zhong, Juexiao Zhou, Bin Zhu,
Lei Zhu, Makan Ziafati, Magdalena Zielińska, Osama A Zitoun,
Mohammad Zoladl, Zhiyong Zou, Liesl J Zuhlke, Alimuddin Zumla,
Elric Zweck, Samer H Zyoud, Eve E Wool†,
and Christopher J L Murray†.
*Joint first authors.
†Joint senior authors
Affiliations
For list of collaborator aliations see appendix 3
Contributors
Please see appendix 1 section 10 for more detailed information about
individual author contributions to the research, divided into the
following categories: managing the overall research enterprise; writing
the first draft of the manuscript; primary responsibility for applying
analytical methods to produce estimates; primary responsibility for
seeking, cataloguing, extracting, or cleaning data; designing or coding
figures and tables; providing data or critical feedback on data sources;
developing methods or computational machinery; providing critical
feedback on methods or results; drafting the manuscript or revising it
critically for important intellectual content; and managing the
estimation or publications process. The lead, corresponding, and senior
authors had full access to the data in the study and had final
responsibility for the decision to submit for publication.
Declaration of interests
S Afzal reports support for the present manuscript from King Edward
Medical University including study material, research articles, valid data
sources and authentic real time information for this manuscript;
payment or honoraria for lectures, presentations, speakers bureaus,
manuscript writing or educational events from King Edward Medical
University and collaborative partners including University of Johns
Hopkins, University of California, University of Massachusetts,
KEMCAANA, KEMCA-UK Scientific Conferences and Webinars;
support for attending meetings and/or travel from King Edward Medical
University to attend meetings; participation on a Data Safety Monitoring
Board or Advisory Board with National Bioethics Committee Pakistan,
King Edward Medical University Ethical Review Board, as well as Ethical
Review Board Fatima Jinnah Medical University and Sir Ganga Ram
Hospital; leadership or fiduciary roles in board, society, committee or
advocacy groups, paid or unpaid with Pakistan Association of Medical
Editors, Fellow of Faculty of Public Health Royal Colleges UK (FFPH),
and Society of Prevention, Advocacy And Research, King Edward
Medical University (SPARK); and other support as Dean of Public
Health and Preventive Medicine at King Edward Medical University, as
the Chief Editor Annals of King Edward Medical University, as the
Director of Quality Enhancement Cell King Edward Medical University,
as an international-level Fellow of Faculty of Public Health United
Kingdom, as an Advisory Board Member and Chair Scientific Session
KEMCA-UK, as a Chairperson of KEMCAANA (the International
Scientific Conference), as a national-level member on the Research and
Publications Higher Education Commission (HEC Pakistan), as a
member of the Research and Journals Committee (Pakistan) the Medical
and Dental Council (Pakistan), the National Bioethics Committee
(Pakistan), the Corona Experts Advisory Group (Punjab), the Chair of the
Dengue Experts Advisory Group, and a member of the Punjab Residency
Program Research Committee; all outside the submitted work.
R Ancuceanu reports consulting fees from Abbvie; payment or honoraria
for lectures, presentations, speakers’ bureaus, manuscript writing or
educational events from Abbvie, Sandoz, B. Braun, Laropharm, and
MagnaPharm; all outside the submitted work. J Ärnlöv reports payment
or honoraria for lectures, presentations, speakers’ bureaus, manuscript
writing or educational events from AstraZeneca and Novartis for lecture
fees; participation on a Data Safety Monitoring Board or Advisory Board
with AstraZeneca, Astella, Boehringer Ingelheim; all outside the
submitted work. O C Baltatu reports support for the present manuscript
from National Council for Scientific and Technological Development
(CNPq, 304224/2022-7) and Anima Institute (AI research professor
fellowship); Leadership or fiduciary role in other board, society,
committee or advocacy group, paid or unpaid, as Founding Member of
the Health and Biotechnology Advisory Board at Technology Park São
José dos Campos–Center for Innovation in Health Technologies (CITS),
outside the submitted work. T W Bärnighausen reports grants or
contracts from National Institutes of Health, Alexander von Humboldt
Foundation, German National Research Foundation (DFG), European
See Online for appendix 3
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2127
Union, German Ministry of Education and Research, German Ministry
of the Environment, Wellcome, and KfW, all as payments to their
institution; participation on a Data Safety Monitoring Board or Advisory
Board on two Scientific Advisory Boards for NIH-funded research
projects in Africa on Climate Change and Health; stock or stock options
in CHEERS, an SME focusing on approaches to measure climate change
and health-related variables in population cohorts; all outside the
submitted work. S Barteit reports grants from Carl-Zeiss Foundation
and the German research foundation (DFG); stock or stock options in
CHEERS, a for-profit company focusing on climate change and health
evaluation and response systems; all outside the submitted work.
M Beghi reports consulting fees from Lundbeck and Angelini, all
outside the submitted work. Y Bejot reports consulting fees from
Medtronic and Novartis; payment or honoraria for lectures,
presentations, speakers bureaus, manuscript writing or educational
events from BMS, Pfizer, Medtronic, Amgen, NovoNordisk, and Servier;
support for attending meetings and/or travel from Medtronic; leadership
or fiduciary role in other board, society, committee or advocacy group,
unpaid, with the French Neurovascular Society; all outside the submitted
work. M Bell reports grants or contracts from US EPA, NIH, High Tide
Foundation, Health Eects Institute, Yale Women Faculty Forum,
Environmental Defense Fund, Yale Climate Change and Health Center,
Wellcome Trust Foundation, Robert Wood Johnson Foundation, and the
Hutchinson Postdoctoral Fellowship (all paid to their institution);
Consulting fees from Clinique; Payment or honoraria for lectures,
presentations, speakers bureaus, manuscript writing or education events
from Colorado School of Public Health, Duke University, University of
Texas, Data4Justice, Korea University, Organization of Teratology
Information Specialists, University of Pennsylvania, Boston University,
IOP Publishing, NIH, Health Canada, PAC-10, UKRI, AXA Research
Fund Fellowship, Harvard University and the University of Montana;
Support for attending meeting and/or travel from Colorado School of
Public Health, University of Texas, Duke University, Boston University,
University of Pennsylvania, Harvard University, American Journal of
Public Health, Columbia University and Harvard University; Leadership
or fiduciary role in other board, society, committee or advocacy group,
unpaid with Fifth National Climate Assessment and Lancet Countdown,
Johns Hopkins Advisory Board, Harvard external advisory committee for
training grant, WHO Global Air Pollution and Health Technical
Advisory group and the National Academies Panels and Committee; and
paid with the US EPA Clean Air Scientific Advisory Committee
(CASAC); outside the submitted work. L Belo reports other financial or
non-financial interests with UCIBIO – FFUP through support from FCT
in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of
UCIBIO and the project LA/P/0140/2020 of i4HB, all outside the
submitted work. R S Bernstein reports other financial or non-financial
support as a full-time Medical Consultant employee of the California
Department of Public Health in the Center for Heal Care Quality;
outside the submitted work. P J G Bettencourt reports patents planned,
issued, or pending (WO2020229805A1, BR112021022592A2,
EP3965809A1, OA1202100511, US2023173050A1, EP4265271A2, and
EP4275700A2); other financial or non-financial interests with the Botnar
Foundation as project reviewer, outside the submitted work. S Bhaskar
reports grants or contracts from the Japan Society for the Promotion of
Science (JSPS), Japanese Ministry of Education, Culture, Sports, Science
and Technology (MEXT) and JSPS and the Australian Academy of
Science; Leadership or fiduciary role in other board, society, committee
or advocacy group, paid or unpaid with Rotary District 9675 as the
district chair, Global Health & Migration Hub Community as Chair and
Manager (Berlin, Germany), PLOS One, BMC Neurology, Frontiers in
Neurology, Frontiers in Stroke, Frontiers in Public Health and the BMC
Medical Research Methodology as an Editorial Board Member, and as a
Member of the College of Reviewers (Canadian Institutes of Health
Research, Canada); outside the submitted work. B Bikbov reports grants
or contracts from the European Commission and The University of
Rome; Support for attending meetings/travel from the European Renal
Association; Leadership or fiduciary role in other board, society,
committee or advocacy group, unpaid in an advocacy group with the
International Society of Nephrology and unpaid on the Western Europe
Regional Board of the International Society of Nephrology; Other
financial or non-financial support from Scientific-Tools.org; outside the
submitted work. A Biswas reports consulting fees from INTAS
Pharmaceuticals Ltd, India, Lupin Pharmaceuticals, Ltd, India, and
Alkem Laboratories, India as personal payments; payment or honoraria
for lectures, presentations, speakers’ bureaus, manuscript writing or
educational events from Roche Diagnostics, India, as personal
payments; all outside the submitted work. E J Boyko reports payment or
Honoria for lectures, presentations, speakers bureaus, manuscript
writing or education events from the Korean Diabetes Association,
Diabetes Association of the R.O.C (Taiwan), the American Diabetes
Association, and the International Society for the Diabetic Foot; Support
for attending meetings and/or travel from the Korean Diabetes
Association; Diabetes Association of the R.O.C (Taiwan), International
Society for the Diabetic Foot; outside the submitted work. M Carvalho
reports other financial or non-financial interests from LAQV/
REQUIMTE, University of Porto (Porto, Portugal) and acknowledges the
support from FCT under the scope of the project UIDP/50006/2020;
outside the submitted work. E Chung reports support for the present
manuscript from the National Institute of Health NICHD
T32HD007233. J Conde reports grants or contracts form the European
Research Council Starting Grant ERC-StG-2019-848325 (funding
1.5M Euro), outside the submitted work. S Cortese reports grants or
contracts from National Institute for Health and Care Research (NIHR)
and the European Research Executive Agency; payment or honoraria for
lectures, presentations, speakers bureaus, manuscript writing or
educational events from the Association of Child and Adolescent Mental
Health, British Association of Psychopharmacology, Medice, and
Canadian ADHD Resource Alliance; support for attending meetings
and/or travel the Association of Child and Adolescent Mental Health,
British Association of Psychopharmacology, Medice, and Canadian
ADHD Resource Alliance; leadership or fiduciary role in other board,
society, committee or advocacy group, unpaid, with the European ADHD
Guidelines Group and the European Network for Hyperkinetic
Disorders; all outside the submitted work. Sa Das reports leadership or
fiduciary role in other board, society, committee or advocacy group,
unpaid, with the Association for Diagnostics and Laboratory Medicine as
program chair, and the Women in Global Health India Chapter, outside
the submitted work. A Dastiridou reports support for attending
meetings and/or travel from THEA and ABBVIE, outside the submitted
work. L Degenhardt reports untied educational grants from Indivior and
Seqirus to examine new opioid medications in Australia, outside the
submitted work. A K Demetriades reports leadership or fiduciary role in
other board, society, committee or advocacy group, unpaid, with the AO
Knowledge Forum Degenerative Steering Committee, Global Neuro
Foundation Board, and the European Association of Neurological
Societies Board of Ocers, all outside the submitted work. A Faro
reports support for the present manuscript from National Council for
Scientific and Technological Development, CNPq, Brazil as CNPq
Researcher (scholarship). I Filip reports support for the present
manuscript from Avicenna Medical and Clinical Research Institute.
D Flood reports grants or contracts from NHLBI (award number
K23HL161271), the University of Michigan Claude D. Pepper Older
Americans Independence Center (award number 5P30AG024824), and
the University of Michigan Caswell Diabetes Institute Clinical
Translational Research Scholars Program; consulting fees from the
World Health Organization as payments to their institution; leadership
or fiduciary role in other board, society, committee or advocacy group,
unpaid, as Sta Physician for Maya Health Alliance, a non-governmental
health organization in Guatemala; all outside the submitted work.
A A Fomenkov reports support for the present manuscript from
Development of eective biotechnologies based on cell cultures, tissues
and organs of higher plants, microalgae and cyanobacteria. The research
carried out within the state assignment of Ministry of Science and
Higher Education of the Russian Federation (theme No. 122042600086-
7). M Foschi reports consulting fees from Roche and Novartis; support
for attending meetings and/or travel from Biogen, Roche, Novartis,
Sanofi, Bristol, and Merck; leadership or fiduciary role in other board,
society, committee or advocacy group, unpaid, with MBase Foundation;
all outside the submitted work. R Franklin reports grants or contracts
from Heatwaves (Queensland Government, Queensland, Australia) and
Arc Flash (Human Factors, Queensland Government, Queensland,
Australia), and Mobile Plant Safety (Agrifutures); Support for attending
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meetings and/or travel from ACTM Tropical Medicine and Travel
Medicine Conference 2022 and 2023, and ISTM Travel Medicine
Conference in Basel 2023; leadership or fiduciary role in other board,
society, committee or advocacy group, paid or unpaid as the president/
director of Kidsafe, the director of Auschem, a member of the
governance committee of ISASH, the director of Farmsafe, the Vice
President of ACTM, and as a PHAA Injury Prevention SIG Convenor;
outside the submitted work. P S Gill reports support for the present
manuscript from the National Institute for Health and Care Research
(NIHR) as Senior Investigator with payments to their institution; the
views expressed in this publication are those of the author(s) and not
necessarily those of the NIHR or the UK Department of Health and
Social Care. A Guha reports grants or contracts from the American
Heart Association and Department of Defense; consulting fees from
Pfizer, Novartis, and Myovant; leadership or fiduciary role in other
board, society, committee or advocacy group, paid or unpaid, with ZERO
Prostate Cancer Health Equity Task Force and Doctopedia as a founding
medical partner; all outside the submitted work. C Herteliu reports
grants or contracts from the Romanian Ministry of Research Innovation
and Digitalization, MCID, project number ID-585-CTR-42-PFE-2021;
grant of the European Commission Horizon 4P-CAN (Personalised
Cancer Primary Prevention Research through Citizen Participation and
Digitally Enabled Social Innovation); Project “Societal and Economic
Resilience within multi-hazards environment in Romania” funded by
European Union – NextgenerationEU and Romanian Government,
under National Recovery and Resilience Plan for Romania, contract
no.760050/ 23.05.2023, cod PNRR-C9-I8-CF 267/ 29.11.2022, through the
Romanian Ministry of Research, Innovation and Digitalization, within
Component 9, Investment I8; Project “A better understanding of socio-
economic systems using quantitative methods from Physics” funded by
European Union–NextgenerationEU and Romanian Government, under
National Recovery and Resilience Plan for Romania, contract number
760034/ 23.05.2023, cod PNRR-C9-I8-CF 255/ 29.11.2022, through the
Romanian Ministry of Research, Innovation and Digitalization, within
Component 9, Investment I8; outside the submitted work. M Hultström
reports support for the present manuscript from Knut och Alice
Wallenberg Foundation and the Swedish Heart-Lung Foundation, all as
payments to their institution; Support for attending meetings and/or
travel from the American Physiological Society and the Swedish Society
for Anaesthesiology and Intensive Care; leadership or fiduciary role in
other board, society, committee or advocacy group, paid or unpaid, with
the American Physiological Society, Water and Electrolyte Section;
all outside the submitted work. I Ilic and M Ilic report support for the
present manuscript from Ministry of Science, Technological
Development and Innovation of the Republic of Serbia. S M Islam
reports support for the present manuscript from NHMRC and Heart
Foundation, N E Ismail reports leadership or fiduciary role in other
board, society, committee or advocacy group, unpaid, as Bursar (Council
Member) of the Malaysian Academy of Pharmacy, outside the submitted
work. T Joo reports support for the present manuscript from National
Research, Development, and Innovation Oce in Hungary
(RRF-2.3.1-21-2022-00006), Data-Driven Health Division of National
Laboratory for Health Security. G Joshy reports grants or contracts from
the Department of Health and Aged Care 2023 (Understanding the fatal
burden of COVID-19 in residential aged care facilities); support for
attending meetings and/or travel from the Statistical Society of Australia
Grant 2023 supporting conference registration; participation on a Data
Safety Monitoring Board with the Australian Mathematical Sciences
Institute (AMSI) and the Statistical Society of Australia (SSA) for the
project Community-led nutrition and Lifestyle program for weight loss
and metabolic Health: a randomised Controlled trial (ELCHO), 2022;
all outside the submitted work. J Jozwiak reports payment or honoraria
for lectures, presentations, speakers bureaus, manuscript writing or
educational events from Novartis, Adamed, and Amgen; outside the
submitted work. N Kawakami reports grants or contracts from the
Junpukai Foundation and the Department of Digital Mental Health is an
endowment department, supported with an unrestricted grant from
15 enterprises (https://dmh.m.u-tokyo.ac.jp/c); consulting fees from
Riken Institute, JAXA, Sekisui Chemicals, and SB@WORK; leadership
or fiduciary role in other board, society, committee or advocacy group,
paid or unpaid, with the Japan Society for Occupational Health;
all outside the submitted work. J H Kempen reports grants or contracts
from the Massachusetts Eye and Ear Surgery Program and Sight for
Souls through payments to their institution; leadership or fiduciary role
in other board, society, committee or advocacy group, paid or unpaid, as
President of Sight for Souls; stock or stock options with Betaliq and
Tarsier; all outside the submitted work. T Kocsis reports grants or
contracts from Novartis Magyarország Ltd through payment for market
access activities, outside the submitted work. K Krishan reports other
non-financial interests from the UGC Centre of Advanced Study, CAS II,
awarded to the Department of Anthropology, Panjab University
(Chandigarh, India); outside the submitted work. B Lacey reports
support for the present manuscript from the UK Biobank, funded
largely by the UK Medical Research Council and Wellcome, through
their employment at the University of Oxford. M Lee reports support for
the present manuscript from the Ministry of Education of the Republic
of Korea and the National Research Foundation of Korea
(NRF-2021R1I1A4A01057428) and Bio-convergence Technology
Education Program through the Korea Institute for Advancement
Technology (KIAT) funded by the Ministry of Trade, Industry and Energy
(No. P0017805). M-C Li reports grants or contracts from The National
Science and Technology Council in Taiwan (NSTC 112-2410-H-003-031;
leadership or fiduciary role in other board, society, committee or
advocacy group, paid or unpaid, as the technical editor of the Journal of
the American Heart Association; outside the submitted work. J Liu
reports support for the present manuscript from the National Natural
Science Foundation of China (grant number: 72122001; 72211540398).
S Lorkowski reports grants or contracts from Akcea Therapeutics
Germany through payments to their institution; consulting fees from
Danone, Novartis Pharma, Swedish Orphan Biovitrum (SOBI), and
Upfield; payment or honoraria for lectures, presentations, speakers
bureaus, manuscript writing or educational events from Akcea
Therapeutics Germany, AMARIN Germany, Amedes Holding, AMGEN,
Berlin-Chemie, Boehringer Ingelheim Pharma, Daiichi Sankyo
Deutschland, Danone, Hubert Burda Media Holding, Janssen-Cilag,
Lilly Deutschland, Novartis Pharma, Novo Nordisk Pharma, Roche
Pharma, Sanofi-Aventis, and SYNLAB Holding Deutschland & SYNLAB
Akademie; support for attending meetings and/or travel from AMGEN;
participation on a Data Safety Monitoring Board or Advisory Board with
Akcea Therapeutics Germany, AMGEN, Daiichi Sankyo Deutschland,
Novartis Pharma, and Sanofi-Aventis; all outside the submitted work.
M A Mahmoud reports grant or contract funding from the Deputyship
for Research and Innovation, Ministry of Education in Saudi Arabia
(project number 445-5-748). L G Mantovani reports support for the
present manuscript from the Italian Ministry of Health. H R Marateb
reports support for the present manuscript from The Beatriu de Pinós
post-doctoral programme from the Oce of the Secretary of Universities
and Research from the Ministry of Business and Knowledge of the
Government of Catalonia programme: 2020 BP 00261. R Matzopoulos
reports consulting fees from New York University and DG Murray Trust;
Support for attending meetings/travel paid by SA MRC and University
of Cape Town; leadership or fiduciary role in other board, society,
committee or advocacy group, unpaid, as a Board member of Gun Free
South Africa; Stock or Stock options with Sanlam; outside the submitted
work. R J Maude reports support for the present manuscript from
Wellcome Trust [Grant number 220211] as it provides core funding for
Mahidol Oxford Tropical Medicine Research and contributes to his
salary. A-F A Mentis reports grants or contract funding from ‘MilkSafe:
A novel pipeline to enrich formula milk using omics technologies’,
a research co financed by the European Regional Development Fund of
the European Union and Greek national funds through the Operational
Program Competitiveness, Entrepreneurship and Innovation, under the
call RESEARCH - CREATE - INNOVATE (project code: T2EDK-02222),
as well as from ELIDEK (Hellenic Foundation for Research and
Innovation, MIMS-860) (both outside of the present manuscript);
payment for expert testimony from serving as external peer-reviewer for
FONDAZIONE CARIPLO, ITALY; participation in a Data Safety
Monitoring or Advisory Board as Editorial Board Member for
“Systematic Reviews”, for “Annals of Epidemiology”, and as Associate
Editor for “Translational Psychiatry”; stock or stock options from a
family winery; and other financial interests as the current scientific
ocer for BGI Group; outside the submitted work. S A Meo reports
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support from King Saud University, Riyadh, Saudi Arabia
(RSP-2024 R47). T R Miller reports grants or contracts from AB InBev
Foundation, National Institute for Mental Health (Santa Clara County,
CA), and Everytown for Gun Safety; payment for expert testimony in the
states of Michigan, Nevada & New Mexico Mobile County Board of
Health; outside the submitted work. P B Mitchell reports payment or
honoraria for lectures, presentations, speakers’ bureaus, manuscript
writing or educational events, from Janssen (Australia), outside the
submitted work. L Monasta reports support for the present manuscript
from the Ministry of Health (Ricerca Corrente 34/2017) through
payments made to the Institute for Maternal and Child Health IRCCS
Burlo Garofolo. R S Moreira reports grants or contracts from CNPq
Research Productivity Scholarship (National Council for Scientific and
Technological Development) scholarship registration number
316607/2021-5; outside the submitted work. J Mosser reports support for
the present manuscript from the Bill and Melinda Gates Foundation;
grants or contractions from Gavi; Support for attending meetings and/or
travel from the Bill and Melinda Gates Foundation; outside the
submitted work. S Nomura reports support for the present manuscript
from Ministry of Education, Culture, Sports, Science and Technology of
Japan (21H03203) and Precursory Research for Embryonic Science and
Technology from the Japan Science and Technology Agency
(JPMJPR22R8). B Norrving reports participation on a Data Safety
Monitoring Board or Advisory Board with Simbec Orion, outside the
submitted work. A P Okekunle reports support for the present
manuscript from the National Research Foundation of Korea funded by
the Ministry of Science and ICT (2020H1D3A1A04081265). A Ortiz
reports grants or contracts from Sanofi as payments to their institution;
consulting fees, speaker fees or support for travel from, Advicciene,
Astellas, Astrazeneca, Amicus, Amgen, Boehringer Ingelheim,
Fresenius Medical, Care, GSK, Bayer, Sanofi-Genzyme, Menarini,
Mundipharma, Kyowa Kirin, Lilly, Alexion, Freeline, Idorsia, Chiesi,
Otsuka, Novo-Nordisk, Sysmex and Vifor Fresenius Medical Care Renal,
Pharma and is Director of the Catedra, Mundipharma-UAM of diabetic
kidney disease, and the Catedra Astrazeneca-UAM of chronic, kidney
disease and electrolytes; Leadership or fiduciary role in other board,
society, committee or advocacy group, paid or unpaid, with the European
Renal Association; stock or stock options with Telara Farma; all outside
the submitted work. P K Pal reports grants or contracts paid to their
institution from the Indian Council of Medical Research (ICMR), the
Department of Science & Technology (DST)-Science and Engineering
Research Board, the Department of Biotechnology (DBT), DST-Cognitive
Science Research Initiative, Wellcome Trust UK-India Alliance DBT,
PACE scheme of BIRAC, Michael J. Fox Foundation, and SKAN
(Scientific Knowledge for Ageing and Neurological ailments)-Research
Trust; Payment and honoraria for lectures, presentations, speakers
bureaus, manuscript writing or educational events as Faculty/Speaker/
Author from the International Parkinson and Movement Disorder
Society, and Movement Disorder Societies of Korea, Taiwan and
Bangladesh; support for attending meetings and/or travel from the
National Institute of Mental Health and Neurosciences (NIMHANS),
International Parkinson and Movement Disorder Society, and Movement
Disorder Societies of Korea, Taiwan and Bangladesh; Leadership or
fiduciary role in other board, society, committee or advocacy group,
unpaid, as the Past President of Indian Academy of Neurology, Past
Secretary of Asian and Oceanian subsection of International Parkinson
and Movement Disorder Society (MDS-AOS), Editor-in-Chief of Annals
of Movement Disorders, Chair of the Education Committee of
International Parkinson and Movement Disorder Society (IPMDS),
President of the Parkinson Society of Karnataka, Chair of Infection
Related Movement Disorders Study Group of MDS, Member of Rare
Movement Disorders Study Group of International Parkinson and
Movement Disorder Society (IPMDS), Member of Education Committee
of IAPRD, Member of Rating Scales Education and Training Program
Committee of IPMDS, Member of Neurophysiology Task Force of
IPMDS, Member of Movement Disorders in Asia Study Group, Member
of Post-Stroke Movement Disorders, Member of Ataxia Study Group of
IPMDS, and as a Member of Ataxia Global Initiative; all outside the
submitted work. C Palladino reports grants or contracts from FCT –
Fundação para a Ciência e a Tecnologia, I.P. (national funding), under a
contract-programme as defined by DL No. 57/2016 and Law No. 57/2017
(DL57/2016/CP1376/CT0004). DOI 10.54499/DL57/2016/CP1376/CT0004
(https://doi.org/10.54499/DL57/2016/CP1376/CT0004).
R F Palma-Alvarez reports payment or honoraria for lectures,
presentations, speakers bureaus, manuscript writing or educational
events from Angelini, Lundbeck, Casen Recordati and Takeda; support
for attending meetings and/or travel from Janssen and Lundbeck; all
outside the submitted work. A M Pantea Stoian reports consulting fees
from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Novo Nordisk,
Novartis, Sandoz, and Sanofi; payment or honoraria for lectures,
presentations, speakers bureaus, manuscript writing or educational
events from Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Novo
Nordisk, Novartis, Sandoz, Medochemie, Servier, and Sanofi; support for
attending meetings and/or travel from Sanofi, Novo Nordisk, and
Medochemie; Participation on a Data Safety Monitoring Board or
Advisory Board with Astra Zeneca, Eli Lilly, Novo Nordisk, and Sanofi;
Leadership or fiduciary role in other board, society, committee or
advocacy group, unpaid, with the Central European Diabetes Association
and the Association for Renal-Metabolic & Nutritional Studies (ASRMN);
outside the submitted work. R Passera reports Participation on a Data
Safety Monitoring Board or Advisory Board with the non-profit clinical
trial “Consolidation with ADCT-402 (loncastuximab tesirine) after
immunochemotherapy: a phase II study in BTKi-treated/ineligible
Relapse/Refractory Mantle Cell Lymphoma (MCL) patients” - sponsor
FIL, Fondazione Italiana Linfomi, Alessandria-I (unpaid role); leadership
or fiduciary role in other board, society, committee or advocacy group,
paid or unpaid, Member of the Statistical Committee of the EBMT –
European Society for Bone and Marrow Transplantation, Paris-F (unpaid
role); outside the submitted work. A E Peden reports support for the
present manuscript from the [Australian] National Health and Medical
Research Council (Grant Number: APP2009306). V C F Pepito reports
grants or contracts from Sanofi Consumer Healthcare and the
International Initiative for Impact Evaluation; outside the submitted
work. M Pigeolet reports a grant from the Belgian Kids’ Fund for
Pediatric Research, outside the submitted work. T Pilgrim reports grants
paid to the institution without personal remuneration from Biotronik,
Edwards Lifesciences, and ATSens; Payment or honoraria for lectures,
presentations, speakers bureaus, manuscript writing or educational
events from Biotronik, Boston Scientific, Edwards Lifesciences, Abbott,
Medtronic, Biosensors, and Highlife; Participation on a Data Safety
Monitoring Board or Advisory Board for EMPIRE study sponsored by
Biosensors; and receipt of equipment (AT-Patches) from ATSens; outside
the submitted work. D Prieto-Alhambra reports support for the present
manuscript from European Medicines Agency and Innovative Medicines
Initiative, through their institution; grants or contracts from Amgen,
Chiesi-Taylor, Lilly, Janssen, Novartis, and UCB Biopharma through
their institution; consulting fees from Astra Zeneca and UCB
Biopharma; other financial or non-financial interest in Amgen, Astellas,
Janssen, Synapse Management Partners and UCB Biopharma for
supported training programmes; outside the submitted work. A Radfar
reports support for the present manuscript from Avicenna Medical and
Clinical Research Institute. A Rane reports stock or stock options as a
full-time employee at Agios Pharmaceuticals; outside the submitted
work. L F Reyes reports grants or contracts form MSD and Pfizer;
consulting fees from GSK, MSD, and Pfizer; Payment or honoraria for
lectures, presentations, speakers’ bureaus, manuscript writing or
educational events from GSK and Pfizer; payment for expert testimony
from GSK and MSD; support for attending meetings and/or travel from
GSK; outside the submitted work. T G Rhee reports grants or contracts
from the NIH (R21AG070666; R21DA057540; R21AG078972;
R01MH131528; R01AG080647); outside the submitted work. S Sacco
reports grants or contracts from Novartis and Uriach; consulting fees
from Novartis, Allergan-Abbvie, Teva, Lilly, Lundbeck, Pfizer, Novo
Nordisk, Abbott, AstraZeneca; Payment or honoraria for lectures,
presentations, speakers bureaus, manuscript writing or educational
events from Novartis, Allergan-Abbvie, Teva, Lilly, Lundbeck, Pfizer,
Novo Nordisk, Abbott, AstraZeneca; support for attending meetings
and/or travel from Lilly, Novartis, Teva, Lundbeck; leadership or fiduciary
role in other board, society, committee or advocacy group, paid or
unpaid, as the President elect of the European Stroke Organization, and
the Second vice-president of the European Headache Federation; receipt
of equipment, materials, drugs, medical writing, gifts or other services
from Allergan-Abbvie, Novo Nordisk; all outside the submitted work.
P Sachdev reports grants or contracts from national Health and Medical
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Research Council of Australia and the US National Institutes of Health;
Payment or honoraria for lectures from Alkem Labs for the Frontiers of
Psychiatry June 2023 Seminar, Mumbai, India; Participation on a Data
Safety Monitoring Board or Advisory Board with Biogen Australia and
Roche Australia; leadership or fiduciary role in other board, society,
committee or advocacy group, unpaid, with the VASCOG Society and the
World Psychiatric Association; all outside the submitted work.
Y L Samodra reports grants or contracts from Taipei Medical University;
leadership or fiduciary role in other board, society, committee or
advocacy group, paid or unpaid, with the Benang Merah Research
Center; all outside the submitted work. J Sanabria reports support for
attending meetings and/or travel from the Department of Surgery,
Marshall University School of Medicine; three patents pending;
participation in quality assessment and assurance for surgeries of the
Department of Surgery; leadership or fiduciary role in other board,
society, committee or advocacy group, paid or unpaid with SSAT, ASTS,
AHPBA, IHPBA, and AASLD; all outside the submitted work.
N Scarmeas reports grants or contracts with Novo Nordisk as the Local
PI of recruiting site for multinational, multicenter industry sponsored
phase III treatment trial for Alzheimer’s disease with funding paid to
the institution; Participation on a Data Safety Monitoring Board or
Advisory Board with Albert Einstein College of Medicine (NIH funded
study) as the Chair of Data Safety Monitoring Board; all outside the
submitted work. A E Schutte reports Speaker Honoraria from Servier,
Novartis, Sanofi, Medtronic, Abbott, Omron, Aktiia; Support for
attending meetings and/or travel from Servier, Medtronic, and Abbott;
Participation on a Data Safety Monitoring Board or Advisory Board with
Abbott Pharmaceuticals Advisory Board, Skylabs devices Advisory Board;
Leadership or fiduciary role in other board, society, committee or
advocacy group, paid or unpaid, with Co-Chair: National Hypertension
Taskforce of Australia, Board Member: Hypertension Australia,
Company Secretary: Australian Cardiovascular Alliance; all outside the
submitted work. B M Schaarschmidt reports research grants from Else
Kröner-Fresenius Foundatuin, DFG, and PharmaCept; Payment or
honoraria for lectures, presentations, speakers bureaus, manuscript
writing or educational events from AstraZeneca; support for attending
meetings and/or travel from Bayer AG; all outside the submitted work.
M Šekerija reports consulting fees from Roche; Payment or Honoraria
for lectures, presentations, speakers bureaus, manuscript writing or
educational events from Johnson and Johnson, and Astellas; outside the
submitted work. A Sharifan reports leadership or fiduciary role in other
board, society, committee or advocacy group, unpaid with Cochrane as a
steering member of the Cochrane Early Career Professionals Network;
and receipt of thirty days of complimentary access to ScienceDirect,
Scopus, Reaxys, and Geofacets after reviewing manuscripts for two
journals published by Elsevier; outside the submitted work. S Sharma
reports support for the present manuscript from the John J. Bonica
Postdoctoral Fellowship from the International Association for the Study
of Pain (IASP; 2021-2023); Payment or honoraria for lectures,
presentations, speakers bureaus, manuscript writing or educational
events and a travel grant for delivering a talk on “Technologies for pain
education in developing countries” conducted by the Pain Education SIG
of the IASP at the World Pain Congress in Toronto (2022); outside the
submitted work. V Sharma reports other financial or non-financial
support from DFSS (MHA)’s research project (DFSS28(1)2019/EMR/6)
at Institute of Forensic Science & Criminology, Panjab University,
Chandigarh, India, outside the submitted work. K Shibuya reports
support for the present manuscript from Tokyo Foundation for Policy
Research. V Shivarov reports one patent and one utility model with the
Bulgarian Patent Oce; stock or stock options from ICONplc (RSUs);
and other financial interests from an ICONplc salary; all outside the
submitted work. S Shrestha reports other financial interests from the
Graduate Research Merit Scholarship from the School of Pharmacy at
Monash University Malaysia, outside the submitted work. J P Silva
reports support for the present manuscript from the Portuguese
Foundation for Science and Technology through payment of their salary
(contract with reference 2021.01789.CEECIND/CP1662/CT0014).
L M L R Silva reports grants or contracts from CENTRO-04-3559-
FSE-000162, Fundo Social Europeu (FSE), outside the submitted work.
C R Simpson reports grants or contracts from MBIE (NZ), HRC (NZ),
Ministry of Health (NZ), MRC (UK), and CSO (UK); Leadership or
fiduciary role in other board, society, committee or advocacy group, paid
or unpaid with the New Zealand Government Data Ethics Advisory
Group as the Chair; outside the submitted work. D J Stein reports
consulting fees from Discovery Vitality, Johnson & Johnson, Kanna,
L’Oreal, Lundbeck, Orion, Sanofi, Servier, Takeda, and Vistagen, outside
the submitted work. K Stibrant Sunnerhagen reports Leadership or
fiduciary role in other board, society, committee or advocacy group, paid
or unpaid as the head of the scientific committee of the Sweidhs Stroke
Foundation; outside the submitted work. S Stortecky reports grants or
contracts paid to their institution from Edwards Lifesciences, Medtronic,
Abbott, and Boston Scientific; consulting fees from Teleflex; Payment or
honoraria for lectures, presentations, speakers bureaus, manuscript
writing or educational events from Boston Scientific/BTG; outside the
submitted work. A G Thrift reports grants or contracts paid to their
institution from the National Health & Medical Research Council
(Australia) (grant numbers 1171966, 1182071), Heart Foundation (Aus)
and the Stroke Foundation (Australia); outside the submitted
work. J H V Ticoalu reports Leadership or fiduciary role in other board,
society, committee or advocacy group, paid or unpaid, with Benang
Merah Research Center as co-founder, outside the submitted work. M V
Titova reports support for the present manuscript from the Ministry of
Science and Higher Education of the Russian Federation (theme No.
122042600086-7). S J Tromans reports grants or contracts from the 2023
Adult Psychiatric Morbidity Survey team, collecting epidemiological data
on community-based adults living in England. This is a contracted study
from NHS Digital, via the Department of Health and Social Care;
outside the submitted work. P Willeit reports consulting fees from
Novartis; outside the submitted work. M Zielińska reports other
financial interest as an AstraZeneca employee, outside the submitted
work. A Zumla reports grants or contracts from The Pan-African
Network on Emerging and Re-Emerging Infections (PANDORA-ID-NET,
CANTAM-3, and EACCR-3) funded by the European and Developing
Countries Clinical Trials Partnership, the EU Horizon 2020 Framework
Programme, UK National Institute for Health and Care Research Senior
Investigator, and Mahathir Science Award and EU-EDCTP Pascoal
Mocumbi Prize Laureate; Participation on a Data Safety Monitoring
Board or Advisory Board member of the WHO Mass Gatherings Expert
Group and WHO Health Emergencies Programme in Geneva, a
member of the EU-EDCTP3-Global Health (Brussels) Scientific
Committee; all outside the submitted work.
Data sharing
To download the data used in these analyses, please visit the Global
health Data Exchange GBD 2021 website (https://ghdx.healthdata.org/
gbd-2021/sources).
Acknowledgments
Research reported in this publication was supported by the Bill &
Melinda Gates Foundation; Queensland Department of Health,
Australia; UK Department of Health and Social Care; the Norwegian
Institute of Public Health; St Jude Children’s Research Hospital; and the
New Zealand Ministry of Health. The content is solely the responsibility
of the authors and does not necessarily represent the ocial views of the
funders. The Palestinian Central Bureau of Statistics granted the
researchers access to relevant data in accordance with license number
SLN2014-3-170, after subjecting data to processing aiming to preserve the
confidentiality of individual data in accordance with the General
Statistics Law–2000. The researchers are solely responsible for the
conclusions and inferences drawn upon available data. Collection of
these data was made possible by USAID under the terms of cooperative
agreement GPO-A-00-08-000_D3-00. The opinions expressed are those
of the authors and do not necessarily reflect the views of USAID or the
US Government. Data for this research were provided by MEASURE
Evaluation, funded by the US Agency for International Development
(USAID). Views expressed do not necessarily reflect those of USAID,
the US Government, or MEASURE Evaluation. The data reported here
have been supplied by the US Renal Data System (USRDS).
The interpretation and reporting of these data are the responsibility of
the authors and in no way should be seen as an ocial policy or
interpretation of the US Government. This manuscript is based on data
collected and shared by the International Vaccine Institute (IVI) from an
original study it conducted. This manuscript was not prepared in
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2131
collaboration with investigators of IVI and does not necessarily reflect
the opinions or views of IVI. Data for this research were provided by the
Cancer Registry of the Republic of Slovenia. The interpretation and
reporting of these data are the responsibility of the authors and in no
way should be seen as an ocial policy or interpretation of the Statistical
Oce of the Republic of Slovenia. Datasets were provided by the
European Centre for Disease Prevention and Control (ECDC) based on
data provided by WHO and Ministries of Health from the aected
countries. The views and opinions of the authors expressed herein do
not necessarily state or reflect those of the ECDC. The accuracy of the
authors’ statistical analysis and the findings they report are not the
responsibility of the ECDC. The ECDC is not responsible for
conclusions or opinions drawn from the data provided. The ECDC is not
responsible for the correctness of the data and for data management,
data merging, and data collation after provision of the data. The ECDC
shall not be held liable for improper or incorrect use of the data.
Editorial note: The Lancet Group takes a neutral position with respect to
territorial claims in published maps and institutional aliations.
References
1 Murray CJL. The Global Burden of Disease Study at 30 years.
Nat Med 2022; 28: 2019–26.
2 World Bank. World development report 1993: investing in health.
Washington, DC: Oxford University Press, 1993.
3 Wang H, Paulson KR, Pease SA, et al. Estimating excess mortality
due to the COVID-19 pandemic: a systematic analysis of COVID-19-
related mortality, 2020–21. Lancet 2022; 399: 1513–36.
4 Roth GA, Abate D, Abate KH, et al. Global, regional, and national
age-sex-specific mortality for 282 causes of death in 195 countries
and territories, 1980-2017: a systematic analysis for the Global
Burden of Disease Study 2017. Lancet 2018; 392: 1736–88.
5 Institute for Health Metrics and Evaluation. Protocol for the Global
Burden of Diseases, Injuries, and Risk Factors Study (GBD).
Version 4.0. March, 2020. https://www.healthdata.org/sites/default/
files/files/Projects/GBD/March2020_GBD%20Protocol_v4.pdf
(accessed March 15, 2023).
6 Vos T, Lim SS, Abbafati C, et al. Global burden of 369 diseases and
injuries in 204 countries and territories, 1990-2019: a systematic
analysis for the Global Burden of Disease Study 2019. Lancet 2020;
396: 1204–22.
7 GBD 2013 Mortality and Causes of Death Collaborators. Global,
regional, and national age-sex specific all-cause and cause-specific
mortality for 240 causes of death, 1990–2013: a systematic analysis for
the Global Burden of Disease Study 2013. Lancet 2015; 385: 117–71.
8 Wang H, Naghavi M, Allen C, et al. Global, regional, and
national life expectancy, all-cause mortality, and cause-specific
mortality for 249 causes of death, 1980–2015: a systematic
analysis for the Global Burden of Disease Study 2015. Lancet
2016; 388: 1459–544.
9 Naghavi M, Abajobir AA, Abbafati C, et al. Global, regional, and
national age-sex specific mortality for 264 causes of death,
1980–2016: a systematic analysis for the Global Burden of Disease
Study 2016. Lancet 2017; 390: 1151–210.
10 Wang H, Abbas KM, Abbasifard M, et al. Global age-sex-specific
fertility, mortality, healthy life expectancy (HALE), and population
estimates in 204 countries and territories, 1950–2019:
a comprehensive demographic analysis for the Global Burden of
Disease Study 2019. Lancet 2020; 396: 1160–203.
11 Johnson SC, Cunningham M, Dippenaar IN, et al. Public health
utility of cause of death data: applying empirical algorithms to
improve data quality. BMC Med Inform Decis Mak 2021; 21: 175.
12 GBD 2021 Demographics Collaborators. Global age-sex-specific
mortality, life expectancy, and population estimates in 204 countries
and territories and 811 subnational locations, 1950–2021, and the
impact of the COVID-19 pandemic: a comprehensive demographic
analysis for the Global Burden of Disease Study 2021. Lancet 2024;
published online March 11. https://doi.org/10.1016/S0140-
6736(24)00476-8.
13 Doi SAR, Williams GM, eds. Methods of clinical epidemiology.
Berlin, Heidelberg: Springer, 2013.
14 Stevens GA, Alkema L, Black RE, et al. Guidelines for accurate and
transparent health estimates reporting: the GATHER statement.
Lancet 2016; 388: e19–23.
15 Murray CJL, Aravkin AY, Zheng P, et al. GBD 2019 Risk Factors
Collaborators. Global burden of 87 risk factors in 204 countries and
territories, 1990–2019: a systematic analysis for the Global Burden
of Disease Study 2019. Lancet 2020; 396: 1223–49.
16 Levin AT, Owusu-Boaitey N, Pugh S, et al. Assessing the burden
of COVID-19 in developing countries: systematic review, meta-
analysis and public policy implications. BMJ Glob Health 2022;
7: e008477.
17 Barber RM, Sorensen RJD, Pigott DM, et al. Estimating global,
regional, and national daily and cumulative infections with
SARS-CoV-2 through Nov 14, 2021: a statistical analysis. Lancet
2022; 399: 2351–80.
18 Telles CR, Roy A, Ajmal MR, et al. The impact of COVID-19
management policies tailored to airborne SARS-CoV-2 transmission:
policy analysis. JMIR Public Health Surveill 2021; 7: e20699.
19 Bollyky TJ, Hulland EN, Barber RM, et al. Pandemic preparedness
and COVID-19: an exploratory analysis of infection and fatality
rates, and contextual factors associated with preparedness in
177 countries, from Jan 1, 2020, to Sept 30, 2021. Lancet 2022;
399: 1489–512.
20 Filip R, Gheorghita Puscaselu R, Anchidin-Norocel L, Dimian M,
Savage WK. Global challenges to public health care systems during
the COVID-19 pandemic: a review of pandemic measures and
problems. J Pers Med 2022; 12: 1295.
21 The Independent Panel for Pandemic Preparedness and Response.
COVID-19: make it the last pandemic. May 21, 2021. https://
theindependentpanel.org/wp-content/uploads/2021/05/COVID-19-
Make-it-the-Last-Pandemic_final.pdf (accessed Nov 9, 2023).
22 Lazarus JV, Romero D, Kopka CJ, et al. A multinational Delphi
consensus to end the COVID-19 public health threat. Nature 2022;
611: 332–45.
23 Kyu HH, Abate D, Abate KH, et al. Global, regional, and national
disability-adjusted life-years (DALYs) for 359 diseases and injuries
and healthy life expectancy (HALE) for 195 countries and territories,
1990–2017: a systematic analysis for the Global Burden of Disease
Study 2017. Lancet 2018; 392: 1859–922.
24 Haws R, Winch PJ, Castillo J. Innovative community-based
interventions to improve newborn health in Latin America and the
Caribbean. Johns Hopkins University, CORE Group, 2004. https://
coregroup.org/wp-content/uploads/2020/03/LAC-Neonatal-
english_final_pdf.pdf (accessed Nov 3, 2023).
25 Whiteside A, Henry FE. The impact of HIV and AIDS research: a case
study from Swaziland. Health Res Policy Syst 2011; 9 (suppl 1): S9.
26 Dwyer-Lindgren L, Cork MA, Sligar A, et al. Mapping HIV
prevalence in sub-Saharan Africa between 2000 and 2017. Nature
2019; 570: 189–93.
27 Nachega JB, Kapata N, Sam-Agudu NA, et al. Minimizing the
impact of the triple burden of COVID-19, tuberculosis and HIV on
health services in sub-Saharan Africa. Int J Infect Dis 2021;
113 (suppl 1): S16–21.
28 Duarte R, Silva DR, Rendon A, et al. Eliminating tuberculosis in
Latin America: making it the point. J Bras Pneumol 2018;
44: 73–76.
29 WHO. World health statistics 2022: monitoring health for the
SDGs, sustainable development goals. Geneva: World Health
Organization, 2022. https://www.who.int/data/gho/publications/
world-health-statistics (accessed Sept 16, 2022).
30 WHO. World health statistics 2023: monitoring health for the
SDGs, sustainable development goals. Geneva: World Health
Organization, 2023. https://www.who.int/publications-detail-
redirect/9789240074323 (accessed Oct 27, 2023).
31 Rosenthal PJ, John CC, Rabinovich NR. Malaria: how are we doing
and how can we do better? Am J Trop Med Hyg 2019; 100: 239–41.
32 Bhatt S, Weiss DJ, Cameron E, et al. The eect of malaria control on
Plasmodium falciparum in Africa between 2000 and 2015. Nature
2015; 526: 207–11.
33 WHO. WHO recommends R21/Matrix-M vaccine for malaria
prevention in updated advice on immunization. Geneva: World
Health Organization, 2023. https://www.who.int/news/item/02-10-
2023-who-recommends-r21-matrix-m-vaccine-for-malaria-prevention-
in-updated-advice-on-immunization (accessed Oct 24, 2023).
34 Naddaf M. Second malaria vaccine to win global approval is cheaper
and easier to make. Nature 2023; published online Oct 3. https://
doi.org/10.1038/d41586-023-03115-1.
Articles
2132
www.thelancet.com Vol 403 May 18, 2024
35 Black R, Fontaine O, Lamberti L, et al. Drivers of the reduction in
childhood diarrhea mortality 1980-2015 and interventions to eliminate
preventable diarrhea deaths by 2030. J Glob Health 2019; 9: 020801.
36 Troeger CE, Khalil IA, Blacker BF, et al. Quantifying risks and
interventions that have aected the burden of lower respiratory
infections among children younger than 5 years: an analysis for the
Global Burden of Disease Study 2017. Lancet Infect Dis 2020; 20: 60–79.
37 Das JK, Salam RA, Saeed M, Kazmi FA, Bhutta ZA. Eectiveness of
interventions for managing acute malnutrition in children under
five years of age in low-income and middle-income countries:
a systematic review and meta-analysis. Nutrients 2020; 12: 116.
38 Mertens A, Benjamin-Chung J, Colford JM Jr, et al. Causes and
consequences of child growth faltering in low-resource settings.
Nature 2023; 621: 568–76.
39 Reiner RC Jr, Hay SI. The overlapping burden of the three leading
causes of disability and death in sub-Saharan African children.
Nat Commun 2022; 13: 7457.
40 Shah MP, Tate JE, Mwenda JM, Steele AD, Parashar UD. Estimated
reductions in hospitalizations and deaths from childhood diarrhea
following implementation of rotavirus vaccination in Africa.
Expert Rev Vaccines 2017; 16: 987–95.
41 Reiner RC Jr, Graetz N, Casey DC, et al. Variation in childhood
diarrheal morbidity and mortality in Africa, 2000–2015.
N Engl J Med 2018; 379: 1128–38.
42 Burstein R, Henry NJ, Collison ML, et al. Mapping 123 million
neonatal, infant and child deaths between 2000 and 2017. Nature
2019; 574: 353–58.
43 Galles NC, Liu PY, Updike RL, et al. Measuring routine childhood
vaccination coverage in 204 countries and territories, 1980–2019:
a systematic analysis for the Global Burden of Disease Study 2020,
Release 1. Lancet 2021; 398: 503–21.
44 Deshpande A, Miller-Petrie MK, Lindstedt PA, et al. Mapping
geographical inequalities in access to drinking water and sanitation
facilities in low-income and middle-income countries, 2000–17.
Lancet Glob Health 2020; 8: e1162–85.
45 Bhattacharjee NV, Schaeer LE, Hay SI, et al. Mapping inequalities
in exclusive breastfeeding in low- and middle-income countries,
2000-2018. Nat Hum Behav 2021; 5: 1027–45.
46 Wiens KE, Lindstedt PA, Blacker BF, et al. Mapping geographical
inequalities in oral rehydration therapy coverage in low-income and
middle-income countries, 2000–17. Lancet Glob Health 2020;
8: e1038–60.
47 Reiner RC Jr, Graetz N, Casey DC, et al. Local variation in childhood
diarrheal morbidity and mortality in Africa, 2000-2015. N Engl J Med
2018; 379: 1128–38.
48 GBD 2015 Healthcare Access and Quality Collaborators. Healthcare
Access and Quality Index based on mortality from causes amenable
to personal health care in 195 countries and territories, 1990–2015:
a novel analysis from the Global Burden of Disease Study 2015.
Lancet 2017; 390: 231–66.
49 Bill & Melinda Gates Foundation. Enteric and diarrheal diseases.
https://www.gatesfoundation.org/our-work/programs/global-
health/enteric-and-diarrheal-diseases (accessed Oct 26, 2023).
50 Troeger C, Khalil IA, Rao PC, et al. Rotavirus vaccination and the
global burden of rotavirus diarrhea among children younger than
5 years. JAMA Pediatr 2018; 172: 958–65.
51 Causey K, Fullman N, Sorensen RJD, et al. Estimating global and
regional disruptions to routine childhood vaccine coverage during
the COVID-19 pandemic in 2020: a modelling study. Lancet 2021;
398: 522–34.
52 Barros LL, Barros LL, do Carmo RF, et al. Change in rotavirus
vaccine coverage in Brazil from before (2015–2019) through the
COVID-19 pandemic period (2020–2021). Viruses 2023; 15: 292.
53 DeSilva MB, Haapala J, Vazquez-Benitez G, et al. Association of the
COVID-19 pandemic with routine childhood vaccination rates and
proportion up to date with vaccinations across 8 US health systems
in the Vaccine Safety Datalink. JAMA Pediatr 2022; 176: 68–77.
54 WHO. Vaccine-preventable diseases. Geneva: World Health
Organization, 2023. https://www.who.int/teams/immunization-
vaccines-and-biologicals/diseases (accessed Nov 12, 2023).
55 WHO. The big catch-up: an essential immunization recovery plan
for 2023 and beyond. Geneva: World Health Organization, 2023.
https://www.who.int/publications-detail-redirect/9789240075511
(accessed Nov 12, 2023).
56 Moss WJ, Strebel PM. Chapter 38 measles vaccines. In: Plotkin’s
Vaccines, 8th edn. Philadelphia, PA: Elsevier, 2023: 629–63.
57 PAHO, WHO. Measles elimination in the Americas. Sept 27, 2016.
https://www3.paho.org/hq/index.php?option=com_content&view=
article&id=12526:measles-elimination-in-the-americas (accessed
Nov 8, 2023).
58 Gidding HF, Martin NV, Stambos V, et al. Verification of measles
elimination in Australia: application of World Health
Organization regional guidelines. J Epidemiol Glob Health 2016;
6: 197–209.
59 WHO. Tenth meeting of the European Regional Verification
Commission for Measles and Rubella Elimination: summary of
virtual sessions held on Oct 6, 2021, Nov 2, 2021, Dec 8, 2021, and
Feb 16, 2022. https://www.who.int/europe/publications/i/item/
WHO-EURO-2022-6093-45858-66035 (accessed Nov 8, 2023).
60 Sbarra AN, Rolfe S, Nguyen JQ, et al. Mapping routine measles
vaccination in low- and middle-income countries. Nature 2021;
589: 415–19.
61 Minta AA, Ferrari M, Antoni S, et al. Progress toward regional
measles elimination—worldwide, 2000–2021.
MMWR Morb Mortal Wkly Rep 2022; 71: 1489–95.
62 Majekodunmi OB, Oladele EA, Greenwood B. Factors aecting poor
measles vaccination coverage in sub-Saharan Africa with a special
focus on Nigeria: a narrative review. Trans R Soc Trop Med Hyg 2022;
116: 686–93.
63 National Institute of Allergy and Infectious Diseases. Condom use
for preventing HIV infection. 2018. https://www.niaid.nih.gov/
diseases-conditions/condom-use (accessed Nov 6, 2023).
64 National Institute of Allergy and Infectious Diseases. HIV
prevention. 2020. https://www.niaid.nih.gov/diseases-conditions/
hiv-prevention (accessed Nov 6, 2023).
65 Granich R, Gupta S, Hersh B, et al. Trends in AIDS deaths, new
infections and ART coverage in the top 30 countries with the highest
AIDS mortality burden; 1990–2013. PLoS One 2015; 10: e0131353.
66 National Institute of Allergy and Infectious Diseases. HIV
undetectable=untransmittable (U=U), or treatment as prevention.
2019. https://www.niaid.nih.gov/diseases-conditions/treatment-
prevention (accessed Nov 6, 2023).
67 Akpa OM, Adeolu-Olaiya V, Olusegun-Odebiri CA, Aganaba D.
HIV/AIDS-related stigma and access to HIV treatments by people
living with HIV/AIDS: a case study of selected states in north-west
Nigeria. HIV AIDS Rev 2011; 10: 19–25.
68 Oturu K. Stigma in access to HIV treatment in African countries:
the importance of social connections. Grounded Theory Rev 2011;
10: 63–90.
69 Rosen S, Fox MP, Gill CJ. Patient retention in antiretroviral therapy
programs in sub-Saharan Africa: a systematic review. PLoS Med
2007; 4: e298.
70 Global HIV Prevention Working Group. Access to HIV prevention:
closing the gap. Foreign A 2003; 82: 1–42.
71 Ford N, Boulle A, Egger M. Accounting for and responding to HIV-
associated mortality. AIDS 2016; 30: 521–23.
72 Straetemans M, Bierrenbach AL, Nagelkerke N, Glaziou P,
van der Werf MJ. The eect of tuberculosis on mortality in HIV
positive people: a meta-analysis. PLoS One 2010; 5: e15241.
73 Piot P, Bartos M, Larson H, Zewdie D, Mane P. Coming to terms
with complexity: a call to action for HIV prevention. Lancet 2008;
372: 845–59.
74 Gupta GR, Parkhurst JO, Ogden JA, Aggleton P, Mahal A.
Structural approaches to HIV prevention. Lancet 2008; 372: 764–75.
75 Paulson KR, Kamath AM, Alam T, et al. Global, regional, and
national progress towards Sustainable Development Goal 3.2 for
neonatal and child health: all-cause and cause-specific mortality
findings from the Global Burden of Disease Study 2019. Lancet
2021; 398: 870–905.
76 Saugstad OD. Reducing global neonatal mortality is possible.
Neonatology 2011; 99: 250–57.
77 Tura G, Fantahun M, Worku A. The eect of health facility delivery
on neonatal mortality: systematic review and meta-analysis.
BMC Pregnancy Childbirth 2013; 13: 18.
78 Bill & Melinda Gates Foundation. Exemplars in global health.
July 25, 2020. https://www.gatesfoundation.org/ideas/articles/
exemplars-global-health-niranjan-bose (accessed Nov 12, 2023).
