Reduction in child mortality in Ethiopia: analysis of data from demographic and health surveys

Article (PDF Available)inJournal of Global Health · August 2016with 234 Reads
VIEWPOINTS
PAPERS
Electronic supplementary material:
The online version of this article contains supplementary material.
journal of
health
global
Tanya Doherty1,4, Sarah Rohde1,
Donela Besada1, Kate Kerber2,4,
Samuel Manda3,5, Marian Loveday1,
Duduzile Nsibande1, Emmanuelle
Daviaud1, Mary Kinney2, Wanga
Zembe1, Natalie Leon1, Igor Rudan6,
Tedbabe Degefie7, David Sanders4
1
Health Systems Research Unit, South African
Medical Research Council, Cape Town, South
Africa
2
Saving Newborn Lives/Save the Children, Cape
Town, South Africa
3
Biostatistics Research Unit, South African
Medical Research Council, Pretoria, South
Africa
4
School of Public Health, University of the
Western Cape, Cape Town, South Africa
5
School of Mathematics, Statistics and
Computer Science, University of Kwazulu–
Natal, Durban, South Africa
6
Centre for Population Health Sciences
and Global Health Academy, University of
Edinburgh Medical School, Teviot Place,
Edinburgh, Scotland, UK
7
UNICEF, Ethiopia Country Office, Addis
Ababa
Correspondence to:
Prof. Tanya Doherty
Health Systems Research Unit
South African Medical Research Council
Francie van Zijl Drive
Parow
Cape Town 7535
South Africa
tanya.doherty@mrc.ac.za
Reduction in child mortality in Ethiopia: analysis
of data from demographic and health surveys
Background To examine changes in under–5 mortality, coverage of
child survival interventions and nutritional status of children in Ethi-
opia between 2000 and 2011. Using the Lives Saved Tool, the impact
of changes in coverage of child survival interventions on under–5
lives saved was estimated.
Methods Estimates of child mortality were generated using three
Ethiopia Demographic and Health Surveys undertaken between 2000
and 2011. Coverage indicators for high impact child health interven-
tions were calculated and the Lives Saved Tool (LiST) was used to es-
timate child lives saved in 2011.
Results The mortality rate in children younger than 5 years decreased
rapidly from 218 child deaths per 1000 live births (95% condence
interval 183 to 252) in the period 1987–1991 to 88 child deaths per
1000 live births in the period 2007–2011 (78 to 98). The prevalence
of moderate or severe stunting in children aged 6–35 months also
declined signicantly. Improvements in the coverage of interventions
relevant to child survival in rural areas of Ethiopia between 2000 and
2011 were found for tetanus toxoid, DPT3 and measles vaccination,
oral rehydration solution (ORS) and care–seeking for suspected pneu-
monia. The LiST analysis estimates that there were 60 700 child
deaths averted in 2011, primarily attributable to decreases in wasting
rates (18%), stunting rates (13%) and water, sanitation and hygiene
(WASH) interventions (13%).
Conclusions Improvements in the nutritional status of children and
increases in coverage of high impact interventions most notably
WASH and ORS have contributed to the decline in under–5 mortal-
ity in Ethiopia. These proximal determinants however do not fully
explain the mortality reduction which is plausibly also due to the
synergistic effect of major child health and nutrition policies and de-
livery strategies.
www.jogh.orgdoi: 10.7189/jogh.06.020401 1 December 2016 • Vol. 6 No. 2 • 020401
Ethiopia has achieved remarkable declines in under–5 mortality. Accord-
ing to the 2015 UN Inter–Agency Group for Child Mortality Estimation
(IGME) report, Ethiopia reached its target for Millennium Development
Goal 4 for child survival with an estimated under–ve mortality rate of 59
per 1000 live births in 2015, a decline from 205 in 1990. This represents
an average reduction in mortality of 5% per year; higher than the average
for sub–Saharan Africa (2.9%) [1].
VIEWPOINTS
PAPERS
Doherty et al.
Major policy and program activities related to child sur-
vival were initiated in Ethiopia between 2003 and 2013
which built on major reforms starting from the 1990s to
decentralise and reorganise the health system. An ambi-
tious Health Extension Programme (HEP) was launched in
2003 which aimed to provide universal access to mainly
preventive primary health care services [2,3], through more
than 34 000 locally recruited, government–salaried mostly
female health extension workers (HEWs) who receive one
year of training. Two HEWs have been placed in each
health post to serve a kebele, the smallest administrative
unit of about 5000 people. HEWs split their time between
outreach activities and their health post. Outreach activi-
ties include: conducting household visits, organizing com-
munities to participate in the expansion of HEP services,
educating families to adopt healthy life–styles and serve as
‘model families’ in their neighborhood. HEWs focus on de-
livering 16 primary health care (PHC) packages of services
including family health promotion, communicable disease
prevention and control, hygiene and environmental health
and health education and communication services. More
recently in 2011, a network of volunteers (Health Devel-
opment Army), drawn from “model family” households,
support the HEWs by providing essential health messages
to the community [3,4].
The launch of the HEP in 2003 was followed by the Health
Sector Development Programme and the National Child
Survival Strategy in 2005. At around the same time there
was national scale up of community–based treatment of
severe acute malnutrition using ready–to–use therapeutic
food [5]. From 2006, when the HEP was fully operational,
until the end of 2009, HEWs were involved mainly in pre-
ventive and promotive work while their treatment services
included the diagnosis and treatment of only malaria, diar-
rhea (not including low osmolarity ORS) and severe acute
malnutrition. A major health policy change occurred in
2009 which enabled HEWs to administer antibiotics (for
suspected pneumonia) and zinc (for diarrhea) in the com-
munity, while the scale up of integrated community case
management (iCCM) only began in 2011.
This paper examines changes in mortality and coverage of
child survival interventions in Ethiopia between 2000 and
2011. The impact of changes in coverage of child survival
interventions on under–5 lives saved was estimated using
the Lives Saved Tool.
METHODS
Data sources
We used full birth and death history data collected from
women aged 15 to 49 years in nationally representative
surveys: namely the 2000 Demographic and Health Survey
(DHS) the rst DHS to be undertaken in Ethiopia, 2005
DHS and the 2011 DHS to calculate under–5 mortality. The
surveys covered 14 072, 13 721, and 16 702 households
respectively.
To assess trends in coverage of child survival interventions
and nutritional status we used the same three Ethiopian
DHS surveys. The surveys provide detailed information
about the health and nutritional status of women and chil-
dren and coverage of health care services. The analysis in-
cluded all survey data sets available with full data, includ-
ing sampling weights, to allow for re–analysis (see Table S1
in the Online Supplementary Document for further de-
tails on the surveys). To assess coverage of malaria inter-
ventions two separate Malaria Indicator Surveys (MIS) were
used since these surveys sample specically from malaria
endemic areas. Malaria is seasonal in most parts of Ethio-
pia, with variable transmission and prevalence patterns af-
fected by the large diversity in altitude, rainfall, and popu-
lation movement. The MIS from 2007 [6] and 2011 [7]
focus on malarious areas dened as <2000m in altitude
mapped by global positioning system (GPS); hence these
provide a more appropriate estimate of coverage of malar-
ia interventions than the DHS surveys [7]. All of the sur-
veys provided cross–sectional data on intervention cover-
age in their respective years; however for the MIS, primary
data are not available and only point estimates are present-
ed. Denitions and data sources for all indicators can be
found in Table S2 in Online Supplementary Document.
Statistical analysis
We used a direct method for estimating under–5 mortal-
ity based on the synthetic cohort approach [8,9]. Under
this concept, age–specic mortality probabilities for nar-
row age ranges and dened periods are calculated using
death events and exposures. These probabilities are com-
bined to compute the probability that a child has not died
before reaching age 5 years [9]. Under–ve mortality rates
were computed for successive ve year periods preceding
the 2011 DHS. For the purposes of this analysis, mortal-
ity rates were calculated for 5–year periods starting from
1987–1991 up until 2007–2011 (the 5–year period im-
mediately prior to the 2011 DHS). Survival probabilities
were calculated over age ranges; 0, 1–2, 3–5, 6–11, 12–
23, 24–35, 36–47, 48–59 months as recommended by
DHS (Section B in Online Supplementary Document)
[9]. The standard errors for the computed mortality esti-
mates were obtained using the Jackknife variance estima-
tion, a repeated sampling method [8]. A series of mortal-
ity estimates were obtained by deleting and replacing each
primary sampling unit; this produced a sample of un-
der–5 estimates, from which the variance was computed
in turn. We also estimated the average annual change
(AAC) in mortality using mortality estimates for the peri-
December 2016 • Vol. 6 No. 2 • 020401 2 www.jogh.orgdoi: 10.7189/jogh.06.020401
VIEWPOINTS
PAPERS
Child mortality reduction in Ethiopia
ods 1987–1991 and 2007–2011 (Section B in the Online
Supplementary Document).
We analyzed primary data from three Ethiopia DHS sur-
veys to assess coverage trends for 10 indicators which rep-
resent high impact maternal and child health interventions;
three additional malaria intervention indicators are pre-
sented as point estimates. We re–calculated all coverage
indicators using standard indicator denitions [10] for
tracking progress toward MDG 4. The sampling design of
these DHS surveys, such as clustering at enumeration areas
and sampling weights (due to non–proportional sampling),
were taken into account. Except for the malaria indicators,
coverage estimates for rural areas are presented to reect
the focus of the HEP on universal access. We considered
malaria indicators for endemic areas only. The 95% con-
dence intervals were used to assess whether the changes
were signicantly different across the three time periods.
We computed anthropometric indicators for stunting
(height–for–age) and underweight (weight–for–age) in
children younger than three years of age from information
on age, height and weight in the surveys applying the
WHO child growth standards [11]. Moderate or severe (be-
low minus two standard deviations (SD) from the median)
and severe (below minus three standard deviations (SD)
from the median) were calculated for both nutritional mea-
sures. Infant feeding indicators such as exclusive breast-
feeding and micronutrient intake (vitamin A supplementa-
tion) were calculated by age of the child. We used Stata
(version 13) (Stata Corporation, College Station, Texas,
USA) for all mortality and coverage analyses.
We used the Lives Saved Tool (LiST) to estimate the num-
ber of deaths averted in 2011 due to changes in coverage
since 2000. We compared the changes in mortality pro-
duced in LiST with single year estimates from IGME [12]
as well as the ve–year estimates produced in this analysis
using DHS data. LiST uses country–specic or region–spe-
cic baseline information on mortality rates and causes of
death as well as background variables (fertility, exposure to
Plasmodium falciparum, stunting rates) and current cover-
age of more than 60 interventions and their associated ef-
fectiveness values [13-16] relative to specic causes of
death and risk factors to estimate the deaths averted, over-
all and by specic interventions. The modeling methods
have been widely published including discussion of the
limitations [16-18]. We used 2000 as the baseline year and
projected forward to 2011 using all available national data
on changes in intervention coverage and nutritional status
(Section C and Table S5 in the Online Supplementary
Document).
Specic input values used in this LiST application are avail-
able in Table S6 in Online Supplementary Data. The anal-
ysis was done with the program Spectrum/Lives Saved
Tool, version 5.04 (Johns Hopkins University, Baltimore
Maryland, USA).
RESULTS
The national mortality rate in children younger than 5 years
decreased rapidly from 218 child deaths per 1000 live
births (95% CI 183–252) in the period 1987–1991 to 88
child deaths per 1000 live births in the period 2007–2011
(95% CI 78–98) with an average annual change of –4.5%.
The mortality rate was signicantly lower in urban areas,
compared to rural areas up until the most recent period
(2007–2011) where the condence intervals for the two
estimates overlap indicating that the urban mortality esti-
mate was no longer signicantly different from the rural
estimate (Figure 1). Large declines in mortality were also
noted in the poorest wealth quintile and among mothers
with no education (see Figure S2 and Figure S3 in Online
Supplementary Document).
Signicant improvements in the coverage of interventions
relevant to child survival in rural areas of Ethiopia between
2000 and 2011 were noted for all indicators except for vi-
Figure 1. Under–5 mortality rates nationally and in
urban and rural areas, Ethiopia, 1987–2011. Data
are from analysis of the 2011 national Demograph-
ic and Health Survey (DHS) in Ethiopia. Vertical
lines show 95% condence intervals for survival
probabilities for the rural and urban estimates.
Dates on the x–axis represent the 5–year periods
preceding the 2011 Ethiopia DHS. *The 2015
estimate is from the IGME child mortality database
(source: UNICEF, [
1
]).
www.jogh.orgdoi: 10.7189/jogh.06.020401 3 December 2016 • Vol. 6 No. 2 • 020401
VIEWPOINTS
PAPERS
Doherty et al.
tamin A coverage, breastfeeding initiation, exclusive breast-
feeding, skilled attendance at birth and postnatal care (Fig-
ure 2). Coverage of breastfeeding initiation and exclusive
breastfeeding remained high (around 50%) throughout the
period of analysis, skilled attendance at birth and postnatal
care remained low (<5%) and vitamin A supplementation
coverage remained at around 50%. Coverage of improved
water source and sanitation, DPT3 and ORS achieved great-
er gains in the 2000–2005 period while coverage of care-
seeking for suspected pneumonia and measles vaccination
had larger percentage point gains in the 2005 to 2011 pe-
riod.
With regard to malaria indicators, increases were noted in
timely care–seeking for fever and malaria treatment, the
largest being for timely care–seeking for fever rising from
16% to 51%. There was little change in coverage of chil-
dren under–5 sleeping under insecticide–treated nets
(ITNs) (41% to 38%) (Figure 3).
Overall, the prevalence of moderate or severe stunting in
children aged 6–35 months declined signicantly across
both survey periods (2000–2005 and 2005–2011) (Figure
4, panel A) with an overall reduction of 13 percentage
points (pp). The proportion of children who were moder-
Figure 2. Rural coverage levels for high
impact interventions across the continuum of
care in Ethiopia as measured in Demographic
and Health Surveys (DHS); 2000, 2005 and
2011. Bars represent 95% condence
intervals. DPT3 – three doses of diphtheria,
pertussis and tetanus vaccine; ORS – oral
rehydration salts; Breastfeeding initiation
refers to newborn babies put to the breast
within 1 hour of birth; Tetanus Toxoid – per-
centage of women with a live birth in the last
2 years who received at least 2 doses of
tetanus toxoid vaccine during the last
pregnancy; PNC – percent of women with
live births in the past 2 years who received
postnatal care within 2 days after delivery;
EBF – exclusive breastfeeding.
Figure 3. Coverage of malaria interventions in malaria endemic
areas of Ethiopia, Malaria Indicator Surveys 2007 and 2011.
ITN – insecticide treated nets.
December 2016 • Vol. 6 No. 2 • 020401 4 www.jogh.orgdoi: 10.7189/jogh.06.020401
ately or severely underweight also declined signicantly
among children 6–35 months between 2000 and 2005 (by
11 pp) but did not change signicantly between 2005 and
2011. The same trend was seen across all age groups (Fig-
ure 4, panel B).
VIEWPOINTS
PAPERS
Child mortality reduction in Ethiopia
Starting at a baseline mortality rate for children younger than
5 years of 146 per 1000 livebirths in 2000 and using avail-
able mortality and coverage data up until 2011, LiST pre-
dicted under–ve mortality to be 119 in 2011, much higher
than both the IGME 2011 estimate of 71 (56 to 88) and the
2007–2011 5–year DHS estimate of 88 (78 to 98), and plac-
ing it outside the upper condence range of both estimates.
We calculated the proportion of child lives saved in 2011,
by intervention or change in nutritional status, using the
LiST estimation of 60 700 deaths averted in 2011 (relative
to the situation in 2000) as a denominator. The main fac-
tors contributing to the prevention of these deaths in 2011
included nutritional interventions resulting in decreases in
wasting rates (18%, 11 400 deaths averted) and stunting
rates (13%, 8400 deaths averted), water, sanitation and hy-
giene (WASH) interventions (13%, 8300 deaths averted),
ORS for diarrhea (11%, 7200), and the introduction of the
Hib vaccine (10%, 6400 deaths averted) (Figure 5). De-
creases in breastfeeding rates between 2005 and 2011 re-
sulted in an additional 2300 deaths.
DISCUSSION
Ethiopia has achieved a remarkable decline in under–5
mortality which has occurred in both rural and urban areas
and among the poorest and least educated mothers. Our
analysis of rural coverage for child survival interventions
shows signicant change between 2000 and 2011 for sev-
eral high impact interventions including measles and DPT
immunization, ORS coverage, access to an improved water
source and care–seeking for suspected pneumonia. For sev-
eral indicators the biggest coverage change occurred be-
tween 2000 and 2005 (tetanus toxoid, DPT3, improved
water source and sanitation facilities and ORS) possibly re-
ecting early impact from the HEP, initiated two years pri-
or to the 2005 DHS, particularly elements such as outreach
services, greater access to curative care at health post level,
the multi–sectoral approach and a focus on prevention and
promotion through model families. Coverage of care–seek-
ing for suspected pneumonia and coverage of ORS treat-
ment for diarrhea was still low in 2011 (both around 25%)
although this represents a signicant increase from very
low coverage levels (around 10%) for both indicators in
2000.
With respect to nutritional status of children, we report a
signicant decline in both stunting and underweight na-
tionally and our LiST analysis has found that a total of 31%
of deaths averted were estimated to be due to decreases in
stunting and wasting rates. These shifts in nutritional sta-
tus of children do not appear to be driven by improvements
in breastfeeding practices as exclusive breastfeeding re-
mained high across the period 2000–2011 at around 50%
of infants 0–6 months. The changes could plausibly be due
to major policy shifts in nutrition which occurred in the
country between 2004 and 2008 with the scale up of com-
munity management of acute malnutrition at health post
level and the development of a national nutrition strategy
and program [5,19]. An impact evaluation of the commu-
nity–based nutrition program in four regions, delivered by
HEWs and community volunteers, found substantial
changes in infant and young child feeding (increased ex-
clusive breastfeeding) and reductions in stunting preva-
lence [20]. Furthermore, a recent ecological analysis of pat-
terns in stunting and coverage of nutritional programmes
concluded that between 2005 and 2011 the scale up of na-
tional nutritional programmes could plausibly have led to
reductions in stunting [21].
It is difcult to disentangle the mechanisms whereby so-
cio–economic change and improvements in health cover-
age interact to generate mortality reduction as these mech-
anisms can be either direct or indirect and take place
concurrently [22]. There are a number of possible explana-
tions for the discrepancy between the IGME–estimated un-
der–ve mortality rate and that estimated through our LiST
analysis. First, some high impact interventions lack cover-
age data and so cannot be included in model. Second, it is
likely that other contextual changes had inuence, which
are not captured in LiST. At an economic level, large chang-
Figure 4. Prevalence of stunting (A) and underweight (B) by age
in children in Ethiopia in the Demographic and Health Surveys
(DHS); 2000, 2005 and 2011.
www.jogh.orgdoi: 10.7189/jogh.06.020401 5 December 2016 • Vol. 6 No. 2 • 020401
A
B
VIEWPOINTS
PAPERS
Doherty et al.
es have occurred in the per capita GDP which tripled since
2000 to US$ 355 in 2011; similarly per capita expenditure
on health tripled to reach US$ 17.5 in 2011. Furthermore,
Ethiopia has received considerable ofcial development as-
sistance (ODA) for maternal, newborn and child health
(MNCH) and has successfully guided partner support to-
ward the health sector development program enabling joint
nancing to ensure implementation of government policies
and plans [23]. The annual MNCH ODA has increased
from $105 million in 2003 to US$ 215 million in 2010
[24]. Since 2003, Ethiopia has also received US$ 1.4 bil-
lion from the Global Fund, 64% of which was spent on
HIV/AIDS and between 2004 and 2011 Ethiopia received
US$ 1.78 billion from the United States President’s Emer-
gency Plan for AIDS Relief (PEPFAR) [25]. As a result, ex-
ternal resources for health, as a percentage of total health
expenditure, increased from 16% in 2000 to 52% in 2011
[26]. This massive funding input could plausibly have had
spillover effects on wider health system strengthening be-
yond the actual programmes it targeted [27,28].
In addition to meeting the MDG 4 target, Ethiopia has
also met four other MDG targets including MDG 1 (pov-
erty and hunger), MDG 6 (HIV, malaria and other diseas-
es) and MDG 7 (environmental sustainability). Further-
more, at the end of 2015 the country was “on track” to
meet MDGs 2 (universal primary education), 3 (gender
equality and empowering women) and 5 (maternal
health) and was only “off track” on one out of the eight
goals (stabilizing debt) [29]. Evidence is emerging that
progress made across these multiple sectors which ad-
dress crucial health determinants has contributed to the
fast–track progress in reducing maternal and child mor-
tality in Ethiopia [23,29,30]. This progress does come
with some cautionary optimism given the increasing reli-
ance on external resources for health. Other authors have
noted this as a challenge facing Sub–Saharan African
countries in the post–MDG era. English et al. [31] note
that ofcial development assistance (ODA) for health per
capita/y in the WHO African Region increased from US$
2.7 in 2002 to US$ 9.8 in 2010 and while governments’
spending on health has increased, only 6/46 countries in
sub–Saharan Africa have met their Abuja target of 15% of
their expenditure on health [31].
Several indicators, particularly related to maternal and
newborn intervention coverage, showed no improvement
in rural areas over the period under analysis. Rural skilled
attendance at birth and postnatal care coverage were 4%
and 3% respectively in 2011. An analysis of neonatal mor-
tality in Ethiopia found an annual rate of decline of 1.9%
between 1995 and 2010, which was even lower (0.9%) for
early neonatal mortality (death occurring before 7 com-
pleted days of life) the period in which 74% of neonatal
deaths occurred [32]. A recently completed 2014 mini–
DHS reveals some improvement in these indicators which
have reached 9% and 7% respectively, in rural areas in
2014 [33]. Improvement is also seen in another important
maternal indicator namely the total fertility rate which has
declined from 5.5 in 2011 to 4.5 in 2014 in rural areas.
These recent improvements in maternal indicators togeth-
er with the 2013 launch of community–based newborn
care [34] (including sepsis treatment) will hopefully enable
the mortality reductions to continue with accelerated prog-
ress in reducing newborn deaths.
The endline data for this assessment, the 2011 Ethiopia
DHS, occurred at the time of national scale up of the iCCM
program and thus provides a picture of coverage and child
survival in the absence of an established community–based
treatment platform. It is recommended that a comparable
analysis be undertaken following the next full DHS to es-
tablish the impact of the community delivery platform on
child survival and health.
Strengths and weaknesses of this study
A strength of this study is the re–analysis of primary data
to generate mortality and coverage estimates for 10 indica-
tors and nutritional status measures over three time points
together with lives saved modeling and a desk review of
broader factors hypothesized to impact on child survival.
There are several weaknesses to this analysis. First, primary
data were not available for the two MIS to enable us to de-
termine signicant changes in malaria interventions; how-
ever, for care–seeking and malaria treatment the changes in
Figure 5. Percentage of child lives saved in 2011 in Ethiopia, by
intervention. ACTs – Artemisinin–based combination therapies,
ITN – insecticide treated nets, ORS – oral rehydration solution,
WASH – water, sanitation and hygiene.
December 2016 • Vol. 6 No. 2 • 020401 6 www.jogh.orgdoi: 10.7189/jogh.06.020401
VIEWPOINTS
PAPERS
Child mortality reduction in Ethiopia
point estimates are large (>20 percentage points) and the
sample sizes for both surveys were over 5000 households,
therefore it would be scientically plausible that these
changes are statistically signicant. Second, with the LiST
analysis, the household survey indicator denitions do not
perfectly match LiST indicators in all cases, and some cov-
erage indicators–particularly those related to delivery care–
are imputed based on rates of home and facility births. Ad-
ditionally, the DHS data used in this analysis does not
capture some of the interventions included in LiST. These
interventions are often high impact for children, eg, thera-
peutic feeding for severe wasting, and might have changed
during the period under consideration.
CONCLUSIONS
The collective effect of several positive changes in child nu-
tritional status, and increased coverage of high impact in-
terventions including WASH and ORS have contributed to
the decline in under–5 mortality in Ethiopia. These proxi-
mal determinants however do not fully explain the mortal-
ity reduction which is plausibly also due to the synergistic
effect of major child health and nutrition policies and de-
centralized delivery strategies. Ethiopia’s progress conrms
the importance of an integrated approach to child survival
[29] and the post MDG era provides an opportunity,
through the sustainable development goals, which are
comprehensive in addressing specic health interventions
as well as key social determinants, for Ethiopia to continue
to close gaps related to the social determinants of health.
Building on this success will require continued investments
and support for universal health coverage with greater at-
tention to maternal and newborn care.
www.jogh.orgdoi: 10.7189/jogh.06.020401 7 December 2016 • Vol. 6 No. 2 • 020401
Acknowledgments: TD is supported by the National Research Foundation, South Africa. KK and
MK are supported by Save the Children’s Saving Newborn Lives programme, which is funded by a
grant from the Bill & Melinda Gates Foundation. We acknowledge the role of Dr Amanda Mason–
Jones in the development of the protocol for this evaluation and the role of Prof Charles Hongoro
in the country visit.
Funding: South African Medical Research Council; and the National Research Foundation South
Africa. The sponsors of the study had no role in the study design, data collection, data analysis, data
interpretation or in the decision to submit the paper for publication. The evaluation team had full
access to all study data and had nal responsibility for the decision to submit for publication.
Disclaimer: The ndings and conclusions in this manuscript are those of the authors and do not
necessarily represent the views of UNICEF.
Ethical approval: This study was approved by the ethics committee of the South African Medical
Research Council (EC026–9/2012). Approval was also provided by the UNICEF Ethiopia country
ofce.
Data sharing: No additional data available. DHS survey datasets are available on request from DHS.
Authorship contribution: TD, KK, MK, DS, SR, DB, ML, IR and DN conceptualised the study. ML
and TD developed the protocol, study design, and data collection materials. ML and DN partici-
pated in the country evaluation visit in October 2012. SM and DB conceptualised the mortality
analysis and data quality assessments, which were done by them. SR and DB led the work on qual-
ity assessment and reanalysis of datasets on intervention coverage, with participation by SM. MK
and KK did the LiST analysis. TD, SR, DB, KK, MK, SM, ML, DN, ED, WZ, NL and DS participated
in a two–day workshop in Cape Town in February 2014, to review and interpret the preliminary
results. TD and DB prepared the rst draft of the paper. All authors reviewed and contributed to
subsequent drafts and approved the nal version for publication.
Competing interests: All authors have completed the ICMJE uniform disclosure form at http://
www.icmje.org/coi_disclosure.pdf (available upon request from the corresponding author) and de-
clare no conict of interest. IR is an editor–in–chief of the Journal of Global Health. To ensure that
any possible conict of interest relevant to the journal has been addressed, this article was reviewed
according to best practice guidelines of international editorial organizations. TD was employed by
UNICEF in Ethiopia at the time of the study.
VIEWPOINTS
PAPERS
Doherty et al.
1 UNICEF. Levels and trends in child mortality: Report 2015. New York: UNICEF; 2015. Available: http://www.
unicef.org/media/les/Levels_and_Trends_in_Child_Mortality_2014.pdf. Accessed: 10 May 2016.
2 Wakabi W. Extension workers drive Ethiopia's primary health care. Lancet. 2008;372:880. Medline:18795419
doi:10.1016/S0140-6736(08)61381-1
3 Koblinsky M, Tain F, Gaym A, Karim A, Carnell M, Tesfaye S. Responding to the maternal health care challenge:
The Ethiopian Health Extension Program. Ethiop J Health Dev. 2010;24:87-129. doi:10.4314/ejhd.v24i1.62951
4 Leon N, Sanders D, Van Damme W, Besada D, Daviaud E, Oliphant NP, et al. The role of 'hidden' community
volunteers in community–based health service delivery platforms: examples from sub–Saharan Africa. Glob
Health Action. 2015;8:27214. Medline:25770090
5 UNICEF and Federal Ministry of Health Ethiopia. Evaluation of community management of acute malnutrition
in Ethiopia. Addis Ababa: UNICEF, 2013.
6 Jima D, Getachew A, Bilak H, Steketee RW, Emerson PM, Graves PM, et al. Malaria indicator survey 2007, Ethi-
opia: coverage and use of major malaria prevention and control interventions. Malar J. 2010;9:58. Med-
line:20178654 doi:10.1186/1475-2875-9-58
7 The Ethiopian Health and Nutrition Institute. Ethiopia National Malaria Indicator Survey 2011. 2012. Available:
http://www.unicef.org/ethiopia/ET_MIS_2011_Report.pdf. Accessed: 10 May 2016.
8 Pedersen J, Liu J. Child mortality estimation: appropriate time periods for child mortality estimates from full
birth histories. PLoS Med. 2012;9:e1001289. Medline:22952435 doi:10.1371/journal.pmed.1001289
9 Rutstein S, Rojas G. Guide to DHS Statistics. Calverton: ORC Macro; 2006.
10 Bryce J, Terreri N, Victora CG, Mason E, Daelmans B, Bhutta ZA, et al. Countdown to 2015: tracking interven-
tion coverage for child survival. Lancet. 2006;368:1067-76. Medline:16997661 doi:10.1016/S0140-
6736(06)69339-2
11 World Health Organization. The WHO child growth standards. Geneva: World Health Organisation, 2006.
12 Ethiopia Child Mortality Estimates. Available: http://childmortality.org/index.php?r=site/graph#ID=ETH_Ethio-
pia. Accessed: 5 May 2016.
13 Darmstadt GL, Bhutta ZA, Cousens S, Adam T, Walker N, de Bernis L, et al. Evidence–based, cost–effective in-
terventions: how many newborn babies can we save? Lancet. 2005;365:977-88. Medline:15767001 doi:10.1016/
S0140-6736(05)71088-6
14 Bhutta ZA, Ahmed T, Black RE, Cousens S, Dewey K, Giugliani E, et al. What works? Interventions for mater-
nal and child undernutrition and survival. Lancet. 2008;371:417-40. Medline:18206226 doi:10.1016/S0140-
6736(07)61693-6
15 Fox MJ, Martorell R, van den Broek N, Walker N. Assumptions and methods in the Lives Saved Tool (LiST). In-
troduction. BMC Public Health. 2011;11 Suppl 3:I1. Medline:21501425 doi:10.1186/1471-2458-11-S3-I1
16 Boschi–Pinto C, Black RE. Development and use of the Lives Saved Tool: a model to estimate the impact of scal-
ing up proven interventions on maternal, neonatal and child mortality. Int J Epidemiol. 2011;40:520-21. Med-
line:21036879 doi:10.1093/ije/dyq171
17 Stover J, McKinnon R, Winfrey B. Spectrum: a model platform for linking maternal and child survival interven-
tions with AIDS, family planning and demographic projections. Int J Epidemiol. 2010;39 Suppl 1:i7-10. Med-
line:20348129 doi:10.1093/ije/dyq016
18 Walker N, Tam Y, Friberg IK. Overview of the Lives Saved Tool (LiST). BMC Public Health. 2013;13 Suppl 3:S1.
Medline:24564438 doi:10.1186/1471-2458-13-S3-S1
19 Lemma F, Matji J. Delivery platforms for sustained nutrition in Ethiopia. Lancet. 2013;382:488-9. Med-
line:23746774 doi:10.1016/S0140-6736(13)61054-5
20 White J, Mason J. Assessing the impact on child nutrition of the Ethiopia community–based nutrition pro-
gramme. New Orleans: Tulane University, 2012. Available: http://www.unicef.org/evaldatabase/index_73949.
html/. Accessed: 9 May 2016.
21 Wirth JP, Matji J, Woodruff BA, Chamois S, Getahun Z, White JM, et al. Scale up of nutrition and health pro-
grams in Ethiopia and their overlap with reductions in child stunting. Matern Child Nutr. 2016. Published on-
line May 1, 2016. Medline:27132587 doi:10.1111/mcn.12318
22 Victora CG, Black RE, Boerma JT, Bryce J. Measuring impact in the Millennium Development Goal era and be-
yond: a new approach to large–scale effectiveness evaluations. Lancet. 2011;377:85-95. Medline:20619886
doi:10.1016/S0140-6736(10)60810-0
23 Ahmed SM, Rawal LB, Chowdhury SA, Murray J, Arscott–Mills S, Jack S, et al. Cross–country analysis of strat-
egies for achieving progress towards global goals for women’s and children’s health. Bull World Health Organ.
2016;94:351-61. Medline:27147765 doi:10.2471/BLT.15.168450
24 Hsu J, Pitt C, Greco G, Berman P, Mills A. Countdown to 2015: changes in ofcial development assistance to
maternal, newborn, and child health in 2009–10, and assessment of progress since 2003. Lancet. 2012;380:1157-
68. Medline:23000291 doi:10.1016/S0140-6736(12)61415-9
25 PEPFAR. Partnering to achieve epidemic control in Ethiopia. Available: http://www.pepfar.gov/documents/orga-
nization/199586.pdf. Accessed: 9 May 2016.
26 World Bank. World Development Indicators. Available: http://data.worldbank.org/country/ethiopia. Accessed:
18 April 2016.
REFERENCES
December 2016 • Vol. 6 No. 2 • 020401 8 www.jogh.orgdoi: 10.7189/jogh.06.020401
VIEWPOINTS
PAPERS
Child mortality reduction in Ethiopia
27 Assefa Y, Jerene D, Lulseged S, Ooms G, Van Damme W. Rapid scale–up of antiretroviral treatment in Ethiopia:
successes and system–wide effects. PLoS Med. 2009;6:e1000056. Medline:19399154 doi:10.1371/journal.
pmed.1000056
28 Bowser D, Sparkes SP, Mitchell A, Bossert TJ, Barnighausen T, Gedik G, et al. Global Fund investments in hu-
man resources for health: innovation and missed opportunities for health systems strengthening. Health Policy
Plan. 2014;29:986-97. Medline:24197405 doi:10.1093/heapol/czt080
29 Kuruvilla S, Schweitzer J, Bishai D, Chowdhury S, Caramani D, Frost L, et al. Success factors for reducing ma-
ternal and child mortality. Bull World Health Organ. 2014;92:533-44B. Medline:25110379 doi:10.2471/
BLT.14.138131
30 Kuruvilla S, Bustreo F, Kuo T, Mishra CK, Taylor K, Fogstad H, et al. The Global Strategy for Women’s, Children’s
and Adolescents’ Health (2016–2030): a roadmap based on evidence and country experience. Bull World Health
Organ. 2016;94:398-400. Medline:27147772 doi:10.2471/BLT.16.170431
31 English M, English R, English A. Millennium Development Goals progress: a perspective from sub–Saharan Af-
rica. Arch Dis Child. 2015;100 Suppl 1:S57-8. Medline:25613971 doi:10.1136/archdischild-2013-305747
32 Mekonnen Y, Tensou B, Telake DS, Degee T, Bekele A. Neonatal mortality in Ethiopia: trends and determinants.
BMC Public Health. 2013;13:483. Medline:23683315 doi:10.1186/1471-2458-13-483
33 Central Statistical Agency Ethiopia. Ethiopia Mini Demographic and Health Survey 2014. Addis Ababa, 2014.
Available: http://www.unicef.org/ethiopia/Mini_DHS_2014__Final_Report.pdf. Accessed: 19 April 2016.
34 Pearson L, Degee T, Hiluf M, Betamariam W, Wall S, Taylor M, et al. From integrated community case manage-
ment to community–based newborn care. Ethiop Med J. 2014;52:9. Medline:25845067
REFERENCES
www.jogh.orgdoi: 10.7189/jogh.06.020401 9 December 2016 • Vol. 6 No. 2 • 020401

Supplementary resources

  • Article
    Full-text available
    This paper, presented as part of a workshop at the 2016 World Public Health Nutrition Conference, is one of a series of papers focused on ‘magic bullets’ versus community action for nutrition. This paper will describe the evidence base on the impact of CHW programmes for child health and discuss features of successful programmes. This is a timely issue as the World Health Organisation is currently leading a process to develop global guidance on community health worker programmes.
  • Article
    Full-text available
    Despite the tremendous achievement in reducing child mortality and morbidity in the last two decades, diarrhoea is still a major cause of morbidity and mortality among children in many developing countries, including Ethiopia. Hand washing with soap promotion, water quality improvements and improvements in excreta disposal significantly reduces diarrhoeal diseases. The objective of this study was to evaluate the effect of hand washing with soap and water, sanitation and hygiene (WASH) educational Intervention on the incidence of under-five children diarrhoea. A community-based cluster randomized controlled trial was conducted in 24 clusters (sub-Kebelles) in Jigjiga district, Somali region, Eastern Ethiopia from February 1 to July 30, 2015. The trial compared incidence of diarrhoea among under-five children whose primary caretakers receive hand washing with soap and water, sanitation, hygiene educational messages with control households. Generalized estimating equation with a log link function Poisson distribution family was used to compute adjusted incidence rate ratio and the corresponding 95% confidence interval. The results of this study show that the longitudinal adjusted incidence rate ratio (IRR) of diarrhoeal diseases comparing interventional and control households was 0.65 (95% CI 0.57, 0.73) suggesting an overall diarrhoeal diseases reduction of 35%. The results are similar to other trials of WASH educational interventions and hand washing with soap. In conclusion, hand washing with soap practice during critical times and WASH educational messages reduces childhood diarrhoea in the rural pastoralist area.
  • Article
    Water hygiene, sanitation, and proper management of health care wastes at health care facilities are important in preventing infections and improving health and the environment. This article describes the access to safe water and sanitation facilities and the disposal of medical wastes at commune health centers (CHCs) in Vietnam. Data was extracted from the 2015 World Bank Vietnam District and Commune Health Facility Survey. Bivariate and multivariate logistic regression was applied to identify associations of CHCs’ access to improved water and sanitation and their medical waste management. Overall, 72.76% CHCs had access to both improved water and sanitation facilities, and better access was found in the richest communes. Rural CHCs had higher prevalence of appropriate wastewater treatment. The majority of CHCs combusted medical solid wastes by specialized incinerations, contracted out with sanitation companies, or transported them to district health centers. However, the data was insufficient to give in-depth analysis and conclusion on water and sanitation conditions and the management of medical wastes at CHCs. More information should be collected for further analysis and conclusion.
  • Article
    Full-text available
    Background Globally, preventable and treatable childhood conditions such as pneumonia, diarrhoea, malaria, malnutrition and newborn conditions still account for 75% of under-five mortality. To reduce the mortality rate from these conditions, Ethiopia launched an ambitious Health Extension Programme (HEP) in 2003. Trained Community Health Workers (CHWs), named Health Extension Workers (HEWs) were deployed to deliver a package of care which includes integrated Community Case-Management (iCCM) of common childhood diseases. Objectives This qualitative study aimed to explore approaches and strategies used in the HEW training and supervision as part of an evaluation of the Catalytic Initiative to Save a Million Lives. Method A qualitative rapid appraisal study using focus group discussions and in-depth interviews was conducted. Results Training of HEWs followed a cascaded training of trainer approach supported by implementing partners under guidance of the Ministry of Health. A comprehensive planning phase enabled good coverage of districts and consistency in training approaches. Training was complemented by on-going supportive supervision. HEW motivation was enhanced through regular review meetings and opportunities for career progression. Conclusion These findings describe a thorough approach to training and supervision of HEWs delivering iCCM in rural Ethiopia. Ongoing investments by partners will be critical for long-term sustainability.
  • Article
    Full-text available
    In Ethiopia, the under-five mortality rate (U5MR) was reduced by 28% between 2005 and 2011, but the neonatal mortality rate (NMR) remains unchanged and now accounts for 42% of all U5 deaths. This burden is even greater for the large rural population due to poor access to and utilization of maternal and newborn health services. To achieve Millennium Development Goal 4, neonatal mortality must be addressed, specifically the major direct causes – sepsis, birth asphyxia, and preterm delivery. Neonatal sepsis, the major newborn killer in Ethiopia, accounts for more than one third of neonatal deaths, 75% in first week of life when even modest delays in receiving effective care can be deadly. The national scale-up of integrated Community Case Management (iCCM) in 2010-2012 provided a needed boost to the Health Extension Program (HEP) by introducing a package of high quality basic curative interventions meeting the demand of the communities. According to the national guidelines for iCCM, Health Extension Workers assess and classify newborn infections and then refer them to health centers and hospitals for treatment. When re-ferral is not possible or delayed, they can provide pre-referral or even complete treatment with oral antibiotics. There is limited care seeking by caregivers for sick young infants under 2 months of age in the iCCM program. The Federal Ministry of Health (FMOH) established a working group that presented a strategy paper, " Exploring the potential for community-based case management of neonatal sepsis in Ethiopia " in February 2012. The paper analyzed the potential benefits and challenges of introducing community-based sepsis management. Reducing neo-natal mortality is increasingly important not only because the proportion of U5 deaths in the neonatal period is increasing, but also because the health interventions to address neonatal deaths generally differ from those to address other under-five deaths. High levels of home delivery (90%) and cultural beliefs of secluding the newborn challenge identifying and treating sick newborns. Active pregnancy and birth surveillance and postpartum home visits early in the first week are required to identify and manage sick neonates.
  • Article
    Full-text available
    Sub-Saharan Africa is a highly diverse geo-political region. Any brief discussion of the progress made over the last 15 years towards the Millennium Development Goals (MDGs) will therefore not do justice to the true complexity of context and events. Our focus will be MDG4-to reduce child mortality by 66% from 1990 levels. We will touch briefly on MDG1, to eradicate extreme poverty and hunger, MDG2, to achieve universal primary education, and MDG5, to improve maternal health, which are inextricably linked with child well-being. We will also draw on an eclectic mix of additional global indicators. Acknowledging the limitations of this approach, we first offer a summary of expected progress and then point to debates on future goals. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
  • Article
    Full-text available
    This paper provides an overview of the historical development and current status of the Lives Saved Tool (LiST). The paper provides a general explanation of the modeling approach used in the model with links to web sites and other articles with more details. It also details the development process in developing both the model structure as well as the assumptions used in the model. The paper provides information about how LiST has been and is currently being used by various organizations and within national health programs. We also provide a review of the work that has been done to try to validate the outputs of the model.
  • Article
    Full-text available
    Background Tracking of financial resources to maternal, newborn, and child health provides crucial information to assess accountability of donors. We analysed official development assistance (ODA) flows to maternal, newborn, and child health for 2009 and 2010, and assessed progress since our monitoring began in 2003. Methods We coded and analysed all 2009 and 2010 aid activities from the database of the Organisation for Economic Co-operation and Development, according to a functional classification of activities and whether all or a proportion of the value of the disbursement contributed towards maternal, newborn, and child health. We analysed trends since 2003, and reported two indicators for monitoring donor disbursements: ODA to child health per child and ODA to maternal and newborn health per livebirth. We analysed the degree to which donors allocated ODA to 74 countries with the highest maternal and child mortality rates (Countdown priority countries) with time and by type of donor. Findings Donor disbursements to maternal, newborn, and child health activities in all countries continued to increase, to $6511 million in 2009, but slightly decreased for the first time since our monitoring started, to $6480 million in 2010. ODA for such activities to the 74 Countdown priority countries continued to increase in real terms, but its rate of increase has been slowing since 2008. We identified strong evidence that targeting of ODA to countries with high rates of maternal mortality improved from 2005 to 2010. Targeting of ODA to child health also improved but to a lesser degree. The share of multilateral funding continued to decrease but, relative to bilaterals and global health initiatives, was better targeted. Interpretation The recent slowdown in the rate of funding increases is worrying and likely to partly result from the present financial crisis. Tracking of donor aid should continue, to encourage donor accountability and to monitor performance in targeting aid flows to those in most need. Funding Bill & Melinda Gates Foundation; World Bank; Governments of Australia, Canada, Norway, Sweden, and the UK.
  • Article
    Full-text available
    Background The Ethiopian neonatal mortality rate constitutes 42% of under-5 deaths. We aimed to examine the trends and determinants of Ethiopian neonatal mortality. Methods We analyzed the birth history information of live births from the 2000, 2005 and 2011 Ethiopia Demographic and Health Surveys (DHS). We used simple linear regression analyses to examine trends in neonatal mortality rates and a multivariate Cox proportional hazards regression model using a hierarchical approach to examine the associated factors. Results The neonatal mortality rate declined by 1.9% per annum from 1995 to 2010, logarithmically. The early neonatal mortality rate declined by 0.9% per annum and was where 74% of the neonatal deaths occurred. Using multivariate analyses, increased neonatal mortality risk was associated with male sex (hazard ratio (HR) = 1.38; 95% confidence interval (CI), 1.23 − 1.55); neonates born to mothers aged < 18 years (HR = 1.41; 95% CI, 1.15 − 1.72); and those born within 2 years of the preceding birth (HR = 2.19; 95% CI, 1.89 − 2.51). Winter birth increased the risk of dying compared with spring births (HR = 1.28; 95% CI, 1.08 − 1.51). Giving two Tetanus Toxoid Injections (TTI) to the mothers before childbirth decreased neonatal mortality risk (HR = 0.44; 95% CI, 0.36 − 0.54). Neonates born to women with secondary or higher schooling vs. no education had a lower risk of dying (HR = 0.68; 95% CI, 0.49 − 0.95). Compared with neonates in Addis Ababa, neonates in Amhara (HR: 1.88; 95% CI: 1.26 − 2.83), Benishangul Gumuz (HR: 1.75; 95% CI: 1.15 − 2.67) and Tigray (HR: 1.54; 95% CI: 1.01 − 2.34) regions carried a significantly higher risk of death. Conclusions Neonatal mortality must decline more rapidly to achieve the Millennium Development Goal (MDG) 4 target for under-5 mortality in Ethiopia. Strategies to address neonatal survival require a multifaceted approach that encompasses health-related and other measures. Addressing short birth interval and preventing early pregnancy must be considered as interventions. Programs must improve the coverage of TTI and prevention of hypothermia for winter births should be given greater emphasis. Strategies to improve neonatal survival must address inequalities in neonatal mortality by women's education and region.
  • Article
    Full-text available
    Child mortality estimates from complete birth histories from Demographic and Health Surveys (DHS) surveys and similar surveys are a chief source of data used to track Millennium Development Goal 4, which aims for a reduction of under-five mortality by two-thirds between 1990 and 2015. Based on the expected sample sizes when the DHS program commenced, the estimates are usually based on 5-y time periods. Recent surveys have had larger sample sizes than early surveys, and here we aimed to explore the benefits of using shorter time periods than 5 y for estimation. We also explore the benefit of changing the estimation procedure from being based on years before the survey, i.e., measured with reference to the date of the interview for each woman, to being based on calendar years. Jackknife variance estimation was used to calculate standard errors for 207 DHS surveys in order to explore to what extent the large samples in recent surveys can be used to produce estimates based on 1-, 2-, 3-, 4-, and 5-y periods. We also recalculated the estimates for the surveys into calendar-year-based estimates. We demonstrate that estimation for 1-y periods is indeed possible for many recent surveys. The reduction in bias achieved using 1-y periods and calendar-year-based estimation is worthwhile in some cases. In particular, it allows tracking of the effects of particular events such as droughts, epidemics, or conflict on child mortality in a way not possible with previous estimation procedures. Recommendations to use estimation for short time periods when possible and to use calendar-year-based estimation were adopted in the United Nations 2011 estimates of child mortality.
  • Article
    Full-text available
    LiST is implemented in Spectrum, a modular computer program designed to examine the impact of interventions on health outcomes. A typical LiST application uses three other modules in Spectrum addressing demography, family planning and HIV/AIDS. The demographic module projects the population by single age and sex over time and uses LiST calculations of the mortality rates by age group to calculate the number of deaths. The family planning module uses the proximate determinants of fertility framework to calculate the effects of increasing contraceptive use on the total fertility rate and, thus, the number of births. The HIV/AIDS module calculates the consequences of HIV epidemic trends on child mortality and the effects of programs to prevent mother-to-child transmission of HIV, cotrimoxazole prophylaxis and anti-retroviral treatment on the number of AIDS deaths. These modules provide LiST with estimates of the number of children and number of deaths by single age as they are affected by changes in fertility through family planning and interventions to prevent the transmission of HIV or delay AIDS death. Integrating LiST within the existing Spectrum system of planning models expands the scope of LiST to include the effects of demographic change, family planning and HIV interventions.
  • Article
    Full-text available
    The Lives Saved Tool (LiST) is a computer-based model that estimates the impact of increasing coverage of interventions on maternal, neonatal and child mortality. The model has its origins in earlier work from the Lancet Series papers that looked at estimating the impact of increasing coverage of proven interventions on child mortality [1] and neonatal mortality [2] as well as the impact of interventions related to nutrition and nutritional status of mothers and children [3]. During the past four years, LiST has been developed into a free, publically available software tool that has been used by programs or organizations to estimate the impact of scaling up different interventions and thereby help in the health planning process [4-6]. The development of LiST is closely linked to the work of the Child Health Epidemiology Reference Group (CHERG) of WHO and UNICEF. The CHERG provides technical inputs to the assumptions and procedures used in the model and also guides the on-going development of the model. As part of this process, this journal issue, along with a previous supplement [7], is being published to ensure that the methods and assumptions in the model are peer reviewed and made publicly available for comments, criticism and feedback. In addition to the fact that the model now includes 75 interventions, LiST also continues to expand in terms of the scope of the program, including two major functionality additions in the current version. First, the new version of LiST estimates the impact of interventions on stillbirths. Second, the new version of LiST allows users the ability to add future interventions, thereby judging the impact of these interventions in conjunction with existing interventions. For example, one could put in a vaccine for malaria, set the efficacy of the vaccine and then estimate the impact that this vaccine would have on malaria deaths with or without the scale up of an existing malaria intervention, such as insecticide-treated nets or indoor residual spraying. More details about the Lives Saved Tool, (LiST) including documentation, training materials, and background information is available at http://www.jhsph.edu/IIP. This supplement includes 35 articles, the majority of which present reviews and meta-analyses that are used to estimate the effectiveness of interventions. In addition there are several articles that either look at the possible impact of future interventions or deal with methodological issues related to the Lives Saved Tool. The effectiveness review articles in the supplement are organized into three broad categories. First, there are seven papers that focus on the impact of interventions on the risk of stillbirth for pregnant women, an output new to LiST. The second section has nine articles that look at the impact of interventions related to maternal, neonatal and child mortality. These articles expand the number of interventions for which effectiveness estimates are available from the previous supplement and also, in the case of rotavirus vaccine, provide an updated estimate of effectiveness based on new trial data. The third section of the supplement contains nine reviews of nutritional interventions. Previous versions of LiST have used estimates of effectiveness drawn from the Lancet Maternal and Child Undernutrition Series [3], but the papers presented here provide new, updated reviews of the effectiveness of nutrition-related interventions. The six papers contained in the fourth section of the issue estimate the potential impact of emerging interventions against pneumonia and meningitis utilizing a modified CHRNI methodology [8]. In the past, LiST had a large, but defined set of interventions in the model. Because the interventions discussed in this section are not proven interventions, they are not included in LiST. The most recent version of LiST, however, allows users to enter new or future interventions into the LiST model and then see what additional impact these new interventions would have in conjunction with existing interventions.
  • Article
    Evaluation of large-scale programmes and initiatives aimed at improvement of health in countries of low and middle income needs a new approach. Traditional designs, which compare areas with and without a given programme, are no longer relevant at a time when many programmes are being scaled up in virtually every district in the world. We propose an evolution in evaluation design, a national platform approach that: uses the district as the unit of design and analysis; is based on continuous monitoring of different levels of indicators; gathers additional data before, during, and after the period to be assessed by multiple methods; uses several analytical techniques to deal with various data gaps and biases; and includes interim and summative evaluation analyses. This new approach will promote country ownership, transparency, and donor coordination while providing a rigorous comparison of the cost-effectiveness of different scale-up approaches.
  • Article
    Full-text available
    Abstract Background In 2005, a nationwide survey estimated that 6.5% of households in Ethiopia owned an insecticide-treated net (ITN), 17% of households had been sprayed with insecticide, and 4% of children under five years of age with a fever were taking an anti-malarial drug. Similar to other sub-Saharan African countries scaling-up malaria interventions, the Government of Ethiopia set an ambitious national goal in 2005 to (i) provide 100% ITN coverage in malarious areas, with a mean of two ITNs per household; (ii) to scale-up indoor residual spraying of households with insecticide (IRS) to cover 30% of households targeted for IRS; and (iii) scale-up the provision of case management with rapid diagnostic tests (RDTs) and artemisinin-based combination therapy (ACT), particularly at the peripheral level. Methods A nationally representative malaria indicator survey (MIS) was conducted in Ethiopia between September and December 2007 to determine parasite and anaemia prevalence in the population at risk and to assess coverage, use and access to scaled-up malaria prevention and control interventions. The survey used a two-stage random cluster sample of 7,621 households in 319 census enumeration areas. A total of 32,380 people participated in the survey. Data was collected using standardized Roll Back Malaria Monitoring and Evaluation Reference Group MIS household and women's questionnaires, which were adapted to the local context. Results Data presented is for households in malarious areas, which according to the Ethiopian Federal Ministry of Health are defined as being located