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Burden of disease from inadequate water, sanitation and hygiene in low- and middle-income settings: A retrospective analysis of data from 145 countries

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  • Rollins School of Public Health, Emory University

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Objective To estimate the burden of diarrhoeal diseases from exposure to inadequate water, sanitation and hand hygiene in low- and middle-income settings and provide an overview of the impact on other diseases.Methods For estimating the impact of water, sanitation and hygiene on diarrhoea, we selected exposure levels with both sufficient global exposure data and a matching exposure-risk relationship. Global exposure data were estimated for the year 2012, and risk estimates were taken from the most recent systematic analyses. We estimated attributable deaths and disability-adjusted life years (DALYs) by country, age and sex for inadequate water, sanitation and hand hygiene separately, and as a cluster of risk factors. Uncertainty estimates were computed on the basis of uncertainty surrounding exposure estimates and relative risks.ResultsIn 2012, 502 000 diarrhoea deaths were estimated to be caused by inadequate drinking water and 280 000 deaths by inadequate sanitation. The most likely estimate of disease burden from inadequate hand hygiene amounts to 297 000 deaths. In total, 842 000 million diarrhoea deaths are estimated to be caused by this cluster of risk factors, which amounts to 1.5% of the total disease burden and 58% of diarrhoeal diseases. In children under 5 years old, 361 000 deaths could be prevented, representing 5.5% of deaths in that age group.Conclusions This estimate confirms the importance of improving water and sanitation in low- and middle-income settings for the prevention of diarrhoeal disease burden. It also underscores the need for better data on exposure and risk reductions that can be achieved with provision of reliable piped water, community sewage with treatment and hand hygiene.
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Burden of disease from inadequate water, sanitation and
hygiene in low- and middle-income settings: a retrospective
analysis of data from 145 countries
Annette Pr
uss-Ust
un
1
, Jamie Bartram
2
, Thomas Clasen
3
, John M. Colford Jr
4
, Oliver Cumming
5
, Valerie
Curtis
5
, Sophie Bonjour
1
, Alan D. Dangour
5
, Jennifer De France
1
, Lorna Fewtrell
6
, Matthew C. Freeman
3
,
Bruce Gordon
1
, Paul R. Hunter
7,8
, Richard B. Johnston
1,9
, Colin Mathers
10
, Daniel M
ausezahl
11,12
, Kate
Medlicott
1
, Maria Neira
1
, Meredith Stocks
3
, Jennyfer Wolf
1,11,12
and Sandy Cairncross
5
1Department of Public Health and Environment, World Health Organization, Geneva, Switzerland
2Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
3Rollins School of Public Health, Emory University, Atlanta, GA, USA
4School of Public Health, University of California, Berkeley, Berkeley, CA, USA
5London School of Hygiene and Tropical Medicine, London, UK
6Centre for Research into Environment and Health, Aberystwyth University, Aberystwyth, UK
7Norwich Medical School, University of East Anglia, Norwich, UK
8Department of Environmental Health, Tshware University of Technology, Pretoria, South Africa
9EAWAG, Swiss Federal Institute of Aquatic Science and Technology, D
ubendorf, Switzerland
10 Department of Health Statistics and Information Systems, World Health Organization, Geneva, Switzerland
11 Swiss Tropical and Public Health Institute, Basel, Switzerland
12 University of Basel, Basel, Switzerland
Abstract objective To estimate the burden of diarrhoeal diseases from exposure to inadequate water,
sanitation and hand hygiene in low- and middle-income settings and provide an overview of the
impact on other diseases.
methods For estimating the impact of water, sanitation and hygiene on diarrhoea, we selected
exposure levels with both sufficient global exposure data and a matching exposure-risk relationship.
Global exposure data were estimated for the year 2012, and risk estimates were taken from the most
recent systematic analyses. We estimated attributable deaths and disability-adjusted life years
(DALYs) by country, age and sex for inadequate water, sanitation and hand hygiene separately, and
as a cluster of risk factors. Uncertainty estimates were computed on the basis of uncertainty
surrounding exposure estimates and relative risks.
results In 2012, 502 000 diarrhoea deaths were estimated to be caused by inadequate drinking
water and 280 000 deaths by inadequate sanitation. The most likely estimate of disease burden from
inadequate hand hygiene amounts to 297 000 deaths. In total, 842 000 diarrhoea deaths are
estimated to be caused by this cluster of risk factors, which amounts to 1.5% of the total disease
burden and 58% of diarrhoeal diseases. In children under 5 years old, 361 000 deaths could be
prevented, representing 5.5% of deaths in that age group.
conclusions This estimate confirms the importance of improving water and sanitation in low- and
middle-income settings for the prevention of diarrhoeal disease burden. It also underscores the need
for better data on exposure and risk reductions that can be achieved with provision of reliable piped
water, community sewage with treatment and hand hygiene.
keywords burden of disease, diarrhoea, water, sanitation, hygiene
Introduction
Information on the burden of disease, its causes and pre-
vention is fundamental to health policy. Among other
things, an improved understanding of the disease burden
and the relative contribution of key risks points towards
opportunities for preventive action in a context of
increasing healthcare costs (OECD 2013).
In recognition of the value of this information, several
comprehensive disease burden studies, focusing mainly on
© 2014 John Wiley & Sons Ltd 1
Tropical Medicine and International Health doi:10.1111/tmi.12329
volume 00 no 00
diarrhoeal diseases, have been undertaken in recent dec-
ades (Murray & Lopez 1996; WHO 2002, 2004, 2009;
Pr
uss-Ust
un et al. 2008; Lim et al. 2012). These report
important changes in the roles of various risk factors
(Clasen et al. 2014).
Inadequate drinking water, sanitation and hygiene
(WASH) are important risk factors, particularly in low-
income settings. In 2011, an estimated 768 million peo-
ple relied on ‘unimproved’ water supplies (as defined by
the WHO/UNICEF Joint Monitoring Program for Water
and Sanitation JMP), which are thought to have high
levels of pathogen contamination (WHO & UNICEF
2013a). Many more use sources that are classified as
‘improved’ but are still unsafe for consumption (Bain
et al. 2014). More than 2.5 billion people lack access to
an improved sanitation facility (WHO & UNICEF
2013a). Inadequate hand hygiene practices have been
estimated to affect 80% of the population globally (Free-
man et al. 2014b).
The health risks from inadequate WASH have been
documented previously (Esrey et al. 1991; Fewtrell et al.
2005; Waddington et al. 2009). However, the unpub-
lished review on which the 2010 Global Burden of Dis-
ease (GBD) study is based (Lim et al. 2012) departed
from earlier reviews by finding no additional benefit from
further improvements such as higher water quality or
continuous piped supply over the exposure defined as
using ‘other improved water supplies’ (Engell & Lim
2013). A more recent systematic review, however, is lar-
gely consistent with previous evidence (Wolf et al. 2014).
Estimating the impact of WASH on diarrhoeal diseases
has commonly been assessed with comparative risk
assessment methods (Ezzati et al. 2002; WHO 2004; Lim
et al. 2012), although other methods such as population
intervention models could also be considered (Clasen
et al. 2014). Other diseases cannot currently be estimated
with such methods due to insufficient evidence and
require alternative approaches. As these would require
considerable additional assessments and analyses, they
are not analysed in detail in this article.
Accrual of substantive recent evidence, as well as
trends in the total diarrhoea burden, justifies the revision
of methods and estimates of the burden of diarrhoeal
disease associated with inadequate WASH. While the
estimate presented focuses mainly on low- and middle-
income settings, the approach used can accommodate a
wider range of settings. An overview of previous findings
on the impacts of WASH on other diseases than
diarrhoea is also provided.
Methods
Framework for estimation
For the purpose of this assessment, we defined WASH to
include the following transmission pathways: (i) ingestion
of water for example diarrhoea, arsenicosis, fluorosis;
(ii) lack of water linked to inadequate personal hygiene
for example diarrhoea, trachoma, scabies; (iii) poor per-
sonal, domestic or agricultural hygiene for example
diarrhoea, Japanese encephalitis; (iv) contact with water
for example schistosomiasis; (v) vectors proliferating in
water for example malaria; and (vi) contaminated
water systems for example legionellosis (Pruss et al.
2002). The impact of WASH on most diseases cannot be
precisely estimated, because of insufficient information on
global exposures of concern or lack of widely applicable
risk estimates matching the exposures. Table 1 provides
Table 1 Diseases related to water, sanitation and hygiene
Disease outcomes and range of the fraction of disease globally attributable to WASH*
Contribution of WASH not
quantified at global level 033% 3366% 66100%
Hepatitis A, E, F
Legionellosis
Scabies
Arsenicosis
Fluorosis
Methaemoglobinaemia
Onchocerciasis Lymphatic filariasis
Malaria
Undernutrition and its consequences
Drowning
Ascariasis
Hookworm
Trichuriasis
Dengue
Schistosomiasis
Japanese encephalitis
Trachoma
WASH, water, sanitation and hygiene.
Includes diseases other than diarrhoea.
Adapted from: Pr
uss-Ust
un and Corval
an (2007), Pr
uss-Ust
un et al. (2008).
*Estimates based on previous assessments combining systematic literature reviews with expert opinion.
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A. Pruss-Ustun et al. Burden of disease from WASH
an overview of main diseases related to WASH and previ-
ously estimated attributable fractions by disease. An over-
view of previous results is provided in the Discussion
section.
The burden of diarrhoea associated with inadequate
WASH can, however, be estimated using comparative risk
assessment methods (Ezzati et al. 2002; WHO 2004; Lim
et al. 2012) and is addressed in detail in this article. This
approach estimates the proportional reduction in disease
or death that would occur if exposures were reduced to an
alternative baseline level bearing a minimum risk (also
referred to as theoretical minimum risk), while other con-
ditions remain unchanged. It is derived from the propor-
tion of people exposed to the conditions of interest and the
relative risk of disease related to the exposure.
Proportion of the population exposed and relative risk
values were specified by level of exposure, age group and
sex. Estimates were calculated for the 145 low- and mid-
dle-income countries (WHO Member States with income
levels defined by the World Bank for 2012), which were
then grouped into the six WHO Regions (WHO 2013b,
Supporting Information). The estimation was performed
for the year 2012 (WHO 2013a).
Selection of exposure-risk pairs for diarrhoeal disease
Water. Exposure levels were selected according to the
availability of exposure data and corresponding expo-
sure-risk information (Wolf et al. 2013, 2014) and
included the following: (i) using an unimproved water
source; (ii) using an improved water source other than
piped to premises; (iii) using basic piped water on pre-
mises (improved source); and (iv) using a water filter or
boiling water in the household (on water from an unim-
proved or improved source).
As piped water on premises is often intermittent and of
suboptimal quality, the risks associated with having
access to a ‘basic’ piped water supply in most settings of
low- and middle-income countries are not equal to zero.
A single study (meeting the criteria for the systematic
review Wolf et al. 2014) was identified which could
inform this estimate of risk (i.e. by demonstrating the
effect of improving water quality through the better oper-
ation of an existing piped water system in a context rele-
vant to a low- or middle-income country). This study
(Hunter et al. 2010) showed a significant and large
reduction in diarrhoea and had an effect size of 0.32
(95% CI: 0.140.74). This evidence is also supported by
information from disease outbreaks resulting from
contaminated piped water (Mermin et al. 1999) and by
interventions to further improve water supply systems in
developed countries (Gunnarsdottir et al. 2012).
However, given that only one study is currently available
on the improvement beyond piped water to premises, a
conservative approach was taken and the next best expo-
sure level was used as the counterfactual (i.e. baseline)
exposure (which consists of using a filter to treat water at
household level Wolf et al. 2014). Household water fil-
tering is therefore used as a proxy for further improve-
ment beyond currently available improved water sources.
It has been documented that lower water use (Cairn-
cross & Feachem 1993; Royal Scientific Society 2013)
and increasing distance to a water source (Tonglet et al.
1992; Galiani et al. 2007; Pickering & Davis 2012;
Evans et al. 2013) have been associated with an increased
risk of diarrhoea. The number of studies identified, how-
ever, was not sufficient to derive a pooled estimate. To
account for this, in the current analysis, people living at
distances greater than a 30-min round trip from their
water source were assumed to have unimproved water.
Among assessed household water treatment methods,
after adjusting for bias introduced through non-blinding
of study participants, only use of a filter showed signifi-
cant reductions in diarrhoeal disease morbidity; the effect
of other methods, such as solar disinfection and chlorina-
tion, became non-significant after adjusting for bias (Wolf
et al. 2014). Boiling of drinking water is a widespread
practice in certain areas (Rosa & Clasen 2010), and
while boiling may be an effective water treatment, recon-
tamination has been reported (Clasen et al. 2008; Rosa
et al. 2010). Only one study, however, has reported on
the health effect of this practice (Iijima et al. 2001) and,
for the purposes of this analysis, people who boil their
drinking water have been classified with those who filter
their water. Safe storage was assumed for all households
filtering or boiling their water as information on recon-
tamination was not available. Households filtering or
boiling their water, with subsequent safe storage, repre-
sent the minimum risk group in this analysis.
The exposure levels for inadequate drinking water,
used in this analysis, along with additional levels of expo-
sure to water with improved quality or quantity that are
not currently supported by sufficient epidemiological evi-
dence, are shown in Figure 1. This approach can accom-
modate further exposure levels when supported by
sufficient evidence. The exposurerisk relationships (taken
from Wolf et al. 2014) are summarised in Table 2.
Sanitation. The only exposure levels for inadequate sani-
tation with both globally representative exposure data and
sufficient evidence for its effect on diarrhoea were the use
of an improved or unimproved sanitation facility (as
defined by JMP WHO & UNICEF 2013b). Evidence
based on two studies suggests that further reduction in
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A. Pruss-Ustun et al. Burden of disease from WASH
diarrhoea morbidity can be achieved with sewer connec-
tions in urban settings (although it should be noted that
potential adverse impacts of untreated sewage on receiving
communities have not been well studied). As the evidence
for sewer connection was limited, it was not retained for
the current diarrhoeal disease burden estimates. The over-
all effect for access to an improved sanitation facility on
reduction in diarrhoea morbidity used was 28% (RR 0.72,
95% CI 0.590.88) from Wolf et al. (2014).
Hygiene. An updated review of the evidence linking inter-
ventions of the promotion of hand hygiene with soap and
diarrhoea morbidity (Freeman et al. 2014b) showed a
40% reduction in diarrhoea (RR 0.60, 95% CI 0.53
0.68). When correcting for bias due to non-blinding in
studies using subjective health outcomes (Savovi
cet al.
2012), this estimate changes to 0.77 (95% CI 0.321.86)
and becomes non-significant. It should be noted, however,
that this bias correction is based on a wide array of medical
Legend: Direct, sufficient evidence Indirect comparison
Insufficient epidemiological evidence
Exposure levels used for estimation of disease burden
COMMUNITY LEVEL HOUSEHOLD LEVEL
Unimproved water source
(or a round trip of 30 min
or more required
Improved other than piped
to premise source
(within 30 min)
Basic Piped water to premise,
non-continuous/sub-optimal
quality
Piped water source,
continuous/higher quality
Household water
treatment using
filters or boiling
Sanitary
/water
safety
plan
Figure 1 Exposure levels and associated risks for drinking water-related burden of disease estimates.
Table 2 Effect sizes used for estimating diarrhoeal disease burden estimates from inadequate drinking water
Baseline water
Outcome water
Improved source
other than piped to premise Basic piped water to premise
Filter and safe storage
in the household*
Unimproved source 0.89 (0.781.01) 0.77 (0.640.92) 0.55 (0.380.81)
Improved source other than piped to premise 0.86 (0.721.03) 0.62 (0.420.93)
Basic piped water to premise0.72 (0.471.11)
Not all steps of this body of evidence may be significant; however, risk estimates of the overall chain of improvements in water and
sanitation are significant.
Adapted from: Wolf et al. (2014); Figures constitute relative risks (and 95% confidence intervals).
*Estimate for filtering water in the household also used for boiling water.
Obtained through indirect comparison with improved non-piped or community water source in the meta-regression.
possibly non-continuous, and/or of sub-optimal quality.
4© 2014 John Wiley & Sons Ltd
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A. Pruss-Ustun et al. Burden of disease from WASH
interventions, which may be of limited applicability to this
type of intervention. A 23% reduction in diarrhoeal dis-
ease risk remains the best estimate of the effect of hand-
washing promotion.
Estimation of the proportion of people exposed
We drew on the definitions of the use of improved
water sources, piped water to premises and improved
sanitation of the JMP (WHO & UNICEF 2013b).
Exposure by country was estimated by multilevel mod-
elling as previously described (Wolf et al. 2013) based
on over 1400 data points from national and interna-
tional household surveys and censuses reported by JMP
(WHO & UNICEF 2013b). Households with a travel
time to the water source >30 min were deducted from
improved sources at community level. We applied a lin-
ear two-level model with a logit transformation of the
dependant variable (use of improved water source,
improved sanitation or piped water to premises) to
obtain estimates for the year 2012 (Wolf et al. 2013).
The model also used a cubic spline transformation of
the main predictor (time) and WHO region (WHO
2013b) as covariates, as well as a random intercept and
slope by country.
Travel time of >30 min was reported by 178 household
surveys [Demographic Health Surveys (USAID 2014),
Multiple Indicator Cluster Surveys (UNICEF 2014),
World Health Surveys (WHO 2014)] from 79 countries
and was estimated for the year 2012 using a similar but
simplified approach with a linear two-level model, with
time and region as covariates and a random intercept and
slope by country.
The proportion of country populations practising water
treatment in the household was estimated using data
from 78 household surveys [Demographic Health Surveys
(USAID 2014), Multiple Indicator Cluster Surveys (UNI-
CEF 2014), World Health Surveys (WHO 2014)] from
68 countries containing information on reported house-
hold water treatment (including chlorination, boiling, fil-
tering, solar disinfection and others). A similar modelling
approach as for travel time >30 min was used to obtain
the proportion of households boiling or filtering their
drinking water for the year 2012, with the difference that
it did not use a random slope at country level. For coun-
tries with no information, the regional mean trend was
taken as the best estimate.
Based on a review of water quality (Bain et al. 2014),
no significant proportion of households in low- and mid-
dle-income settings are currently assumed to benefit from
regulated and fully functional piped water supply
systems.
The hand-washing prevalence, based on 75 observa-
tions, was taken from the systematic review reported by
Freeman et al. (2014b).
Population-attributable fractions of diarrhoeal disease for
individual risk factor and for the cluster
For each risk factor, the population-attributable
fraction (PAF) was estimated by comparing current
exposure distributions to a counterfactual distribution,
for each exposure level, sex and age group, and by
country:
PAF ¼Pn
i¼1piðRRi1Þ
Pn
i¼1piðRRi1Þþ1ð1Þ
where p
i
and RR
i
are the proportion of the exposed
population and the relative risk at exposure level i,
respectively, and nis the total number of exposure lev-
els.
Exposure to inadequate WASH is related by similar
mechanisms and policy interventions. The following for-
mula has been proposed for the estimation of burden
attributable to a cluster of risk factors (Lim et al.
2012):
PAF ¼1YR
r¼1ð1PAFrÞð2Þ
where ris the individual risk factor and Rthe total num-
ber of risk factors accounted for in the cluster. This for-
mula assumes that risk factors are independent. This
assumption is likely to be an oversimplification for
WASH as, for instance, handwashing promotion is unli-
kely to be effective if water quantity is limited. However,
this approach has been applied in the assessment for ease
of interpretation of the results, and in the absence of a
more suitable approach.
Estimation of burden of diarrhoeal disease
The burden of disease attributable to each risk factor
(AB), or to the cluster of risk factors, in deaths or disabil-
ity-adjusted life years (DALYs), was obtained by multi-
plying the PAFs by the total burden of disease of
diarrhoea (B):
AB ¼PAF Bð3Þ
The PAFs were applied equally to burden of disease in
deaths and DALYs, and we assumed that the case fatality
related to WASH was the same as the mean case fatality
of diarrhoeal diseases.
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A. Pruss-Ustun et al. Burden of disease from WASH
Uncertainty estimates
To estimate uncertainty intervals, we developed a Monte
Carlo simulation of the results with 5000 draws of the
exposure distribution, and of the relative risks. As lower
and upper uncertainty estimates, we used the 2.5 and
97.5 percentiles of the attributable fractions, attributable
deaths and DALYs resulting from the Monte Carlo analy-
sis (Palisade 2013).
Results
The worldwide distribution of exposure and the resulting
attributable deaths and DALYs from diarrhoeal disease
associated with inadequate WASH practices were esti-
mated for the year 2012.
Exposure estimates
In low- and middle-income countries, it was found that
in 31% of households people report boiling or filtering
their water; 31% of households use piped water to pre-
mises; 27% use a non-piped or community water source;
12% use only an unimproved water source and do not
filter or boil their water; and on the sanitation side, 58%
of households were estimated to use an improved sanita-
tion facility, respectively.
Handwashing after using a sanitation facility or con-
tact with faecal material is practised by 19% of people
worldwide (based on observation data), with a mean of
14% in low- and middle-income countries, and 43% in
high-income countries (Freeman et al. 2014b). The esti-
mated regional distribution of exposure is presented in
Table 3 (drinking water) and Table 4 (sanitation and
hygiene); more detail by country is provided in the Sup-
porting Information.
Estimates of the burden of diarrhoeal disease
The resulting burden of diarrhoea, in low- and middle-
income countries, linked to these exposures amounts to
502 000 deaths associated with inadequate water and
280 000 deaths due to inadequate sanitation from a total
of 1.50 million diarrhoeal deaths in the year 2012.
In addition, it was estimated that 297 000 deaths could
be prevented by the promotion of hand hygiene, although
this estimate is based on an effect size which is not statis-
tically significant. The estimate without adjusting for
non-blinding would be 539 000 deaths.
Together (using Equation 2), the deaths attributable to
inadequate water and sanitation amount to 685 000.
Adding (bias-adjusted) inadequate hand hygiene increases
this estimate to 842 000 deaths, which represents 1.5%
Table 3 Distribution of the population to exposure levels of drinking water, by region, for 2012
Region
Use of piped water on
premises
Use of non-piped or
community sources
Use of unimproved water
sources
Total*
Proportion of total population by region
Filtering/boiling in the household Without With Without With Without With
Sub-Saharan Africa 0.16 0.03 0.36 0.04 0.38 0.04 1.00
America, LMI 0.58 0.30 0.05 0.01 0.05 0.01 1.00
Eastern Mediterranean, LMI 0.54 0.04 0.25 0.01 0.15 0.01 1.00
Europe, LMI 0.54 0.27 0.10 0.05 0.03 0.02 1.00
South-East Asia 0.16 0.09 0.48 0.14 0.09 0.04 1.00
Western Pacific, LMI 0.31 0.35 0.13 0.14 0.04 0.04 1.00
Total LMI 0.31 0.18 0.27 0.09 0.12 0.03 1.00
LMI, low and middle income.
*The total may not equal the sum of numbers displayed in the rows due to rounding error.
6© 2014 John Wiley & Sons Ltd
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A. Pruss-Ustun et al. Burden of disease from WASH
of the global disease burden in 2012. A regional sum-
mary of attributable deaths and DALYs for each of the
risk factors is provided in Tables 57, and the cluster
data are shown in Table 8. Detail by country can be
found in the Supporting Information.
Among children under 5 years, 361 000 deaths could
have been prevented through reduction of these risks in
low- and middle-income settings, representing 5.5% of
the total burden of disease in this age group.
Discussion
These estimates of the burden of diarrhoea attributable
to inadequate WASH are lower than previous estimates
coordinated by WHO (WHO 2009) and higher than the
recent estimate of the 2010 GBD study (Lim et al.
2012). There is strong evidence that the number of
deaths due to diarrhoeal disease has dropped consider-
ably since 2004 (WHO 2009; Liu et al. 2012; Lozano
et al. 2012) due to a combination of improved manage-
ment of diarrhoeal disease (especially the use of oral
rehydration therapy) and better access to water and san-
itation. This is in line with the lower burden of diarrho-
eal disease estimates in both the 2010 GBD study and
the current work. The larger burden of diarrhoeal dis-
ease found in this study, compared with the 2010 GBD
study, can be explained by the different counterfactuals
used, the consideration in this study of disease burden
due to poor hand hygiene and to the adjustments made
to account for bias resulting from the lack of blinding
Table 4 Distribution of the population to exposure levels of san-
itation and hygiene, by region, for 2012
Region
Access to improved
sanitation facility
Prevalence of
handwashing
after contact with
excreta
Proportion of total population
Sub-Saharan Africa 0.35 0.14
America, HI 0.49
America, LMI 0.83 0.16
Eastern
Mediterranean, HI
0.44
Eastern
Mediterranean, LMI
0.68 0.14
Europe, HI 0.44
Europe, LMI 0.87 0.15
South-East Asia 0.47 0.17
Western Pacific, HI 0.43
Western Pacific, LMI 0.64 0.13
Total 0.19
Total HI 0.43
Total LMI 0.58 0.14
LMI, low and middle income; HI, high income; , not estimated.
Table 5 Diarrhoea burden attributable to inadequate water by region, 2012
Region PAF (95% CI) Deaths (95% CI) DALYs (in 1000s) (95% CI)
Sub-Saharan Africa 0.38 (0.190.50) 229 316 (106 664300 790) 17 587 (815223 065)
America, LMI 0.26 (0.140.33) 6441 (6249748) 522 (39801)
Eastern Mediterranean, LMI 0.36 (0.190.46) 50 409 (22 49866 604) 4046 (17845351)
Europe, LMI 0.16 (0.100.26) 1676 (1962606) 174 (19271)
South-East Asia 0.32 (0.110.44) 207 773 (59 708293 068) 10 748 (309715 160)
Western Pacific, LMI 0.20 (0.090.27) 6448 (20059469) 716 (1981081)
Total LMI 0.34 (0.160.45) 502 061 (217 119671 945) 33 793 (14 93044 871)
DALYs, disability-adjusted life years; PAF, population-attributable fraction; LMI, low and middle income.
Table 6 Diarrhoea burden attributable to inadequate sanitation by region, 2012
Region PAF (95% CI) Deaths (95% CI) DALYs (in 1000s) (95% CI)
Sub-Saharan Africa 0.21 (0.070.31) 126 294 (42 881186 850) 9694 (329114 333)
America, LMI 0.09 (0.030.15) 2370 (7743724) 188 (61295)
Eastern Mediterranean, LMI 0.17 (0.060.26) 24 441 (833936 809) 1914 (6512887)
Europe, LMI 0.03 (0.010.06) 352 (107597) 36 (1161)
South-East Asia 0.19 (0.060.28) 123 279 (42 116185 426) 6376 (21779595)
Western Pacific, LMI 0.11 (0.040.17) 3709 (11715954) 444 (136737)
Total LMI 0.19 (0.070.29) 280 443 (95 699417 482) 18 650 (638027 769)
DALYs, disability-adjusted life years; PAF, population-attributable fraction; LMI, low and middle income.
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A. Pruss-Ustun et al. Burden of disease from WASH
in studies on different household water treatment
interventions.
The estimate of diarrhoeal disease burden attributable
to inadequate WASH practices is limited by the underly-
ing evidence, which remains scarce for the transition
between an improved water source and a functional and
regulated water supply system. The evidence is also lim-
ited on sanitation; in particular, there is a dearth of infor-
mation on wastewater and excreta management from
improved facilities and the impact this has on down-
stream communities when it is disposed of, untreated, to
the environment. In addition, a conservative effect size
was chosen for the impact of hand hygiene on diarrhoea,
based on figures adjusted for possible bias (Freeman et al.
2014b). This approach is, thus, more conservative than
previous estimates (Curtis & Cairncross 2003).
Exposure data are limited in terms of representative
measures of water quality. Handwashing prevalence has
not yet been widely assessed, although studies have
shown surprisingly little variation across countries and
population groups within income groups (Freeman et al.
2014b). Surveys reporting the use of household water
treatment options have shown some over-reporting. This
would, however, have led to an underestimation of diar-
rhoeal disease burden in this analysis as households
reported as filtering or boiling their water were assigned
as having no risk related to inadequate WASH.
Certain potentially relevant exposure/exposure-risk
pairs cannot yet be considered. These include, for exam-
ple, incomplete community sanitation (i.e. incomplete
community coverage) meaning that contact with excreta
may persist within the community. Another example con-
sists in improved sanitation facilities without treatment,
which are likely to result in exposure of receiving com-
munities to untreated sewage and could affect 22% of
the global population (Baum et al. 2013). Also, this
assessment is limited to non-outbreak situations.
The global assessment of exposure to faecal contamina-
tion through drinking water (Bain et al. 2014) has high-
lighted that piped water supplies in the American,
Table 7 Diarrhoea burden attributable to inadequate hand hygiene by region, 2012
Region PAF (95% CI) Deaths (95% CI) DALYs (in 1000s) (95% CI)
Sub-Saharan Africa 0.20 (00.61) 122 955 (0365 911) 9411 (028 006)
America, HI 0.13 (00.45) ––
America, LMI 0.20 (00.60) 5026 (015 013) 416 (01243)
Eastern Mediterranean, HI 0.14 (00.48) ––
Eastern Mediterranean, LMI 0.21 (00.61) 28 699 (085 369) 2314 (06884)
Europe, HI 0.14 (00.48) ––
Europe, LMI 0.19 (00.59) 1972 (05975) 202 (0611)
South-East Asia 0.20 (00.60) 131 519 (0392 018) 6857 (020 444)
Western Pacific, HI 0.16 (00.50) ––
Western Pacific, LMI 0.21 (00.61) 6690 (019 891) 758 (02253)
Total 0.20 (00.60) ––
Total HI 0.14 (00.47) ––
Total LMI 0.20 (00.60) 296 860 (0885 355) 19 958 (059 491)
DALYs, disability-adjusted life years; PAF, population-attributable fraction; LMI, low and middle income; HI, high income; , not esti-
mated.
Table 8 Diarrhoea deaths attributable to the cluster of inadequate water, and inadequate sanitation and hand hygiene
Region
Inadequate water, sanitation and hand hygiene Inadequate water and sanitation
PAF (95% CI) Deaths (95% CI) PAF (95% CI) Deaths (95% CI)
Sub-Saharan Africa 0.61 (0.550.66) 367 605 (326 795402 438) 0.51 (0.470.55) 307 493 (276 989335 899)
America, LMI 0.46 (0.360.50) 11 519 (931013 616) 0.32 (0.280.34) 8125 (71019158)
Eastern Mediterranean, LMI 0.58 (0.470.66) 81 064 (65 35994 707) 0.47 (0.400.53) 65 700 (55 26675 876)
Europe, LMI 0.35 (0.280.46) 3564 (24624678) 0.19 (0.190.27) 1970 (16542280)
South-East Asia 0.56 (0.360.70) 363 904 (225 359477 720) 0.45 (0.310.57) 291 763 (193 198383 423)
Western Pacific, LMI 0.44 (0.310.54) 14 160 (10 03518 009) 0.29 (0.230.33) 9429 (751911 242)
Total LMI 0.58 (0.480.65) 841 818 (699 059963 626) 0.47 (0.400.53) 684 479 (580 456780 463)
PAF, population-attributable fraction; LMI, low and middle income.
8© 2014 John Wiley & Sons Ltd
Tropical Medicine and International Health volume 00 no 00
A. Pruss-Ustun et al. Burden of disease from WASH
European and Western Pacific low- and middle-income
regions show particularly low contamination in urban
areas, with <10% of investigated samples faecally con-
taminated. The relative risks from the meta-regression
(Wolf et al. 2014) may overrate the risks of water
sources with such low proportions of contamination, as
they have been relatively poorly investigated in the under-
lying epidemiological literature. If assuming that urban
piped supplies in those regions carry no increased risk for
diarrhoea, the total diarrhoea burden from inadequate
water sources would have decreased from 502 000 to
497 000 deaths in 2012, with 2800 fewer deaths in the
American region, 700 fewer deaths in the European
region and 1500 fewer deaths in the Western Pacific
region, respectively. The contamination of piped water in
those regions may, however, have been underestimated
because (i) studies tend to take place in formal urban
areas and especially in capital cities, (ii) the assessment
reported the per cent of samples containing contamina-
tion rather than compliance with WHO guidelines, and
(iii) the focus was on water quality at the source and not
stored at home or sampled just before consumption (Bain
et al. 2014).
The current estimation has focused on diarrhoeal dis-
eases and has not re-analysed the impact on other dis-
eases, which have been linked to inadequate WASH,
including soil-transmitted helminth infections (Zieg-
elbauer et al. 2012), vector-borne diseases (Emerson
et al. 2000), environmental enteropathy (Humphrey
2009). Furthermore, improved WASH has been shown
to significantly reduce undernutrition (Dangour et al.
2013), a major cause of mortality in children under
5 years of age (Black et al. 2013). Previous estimates,
based on literature reviews combined with expert opin-
ion, have, however, attempted to provide quantitative
estimates of other diseases than diarrhoea, with the fol-
lowing results: In 2004, 881 000 deaths were attributed
to water supply, sanitation and hygiene, mainly through
the effect on undernutrition and its consequences, but
also from schistosomiasis and lymphatic filariasis. The
impacts of water resource management, mainly on
malaria but also dengue and Japanese encephalitis, were
estimated to amount to 557 000 deaths in the same
year. Finally, safer water environments could have pre-
vented 244 000 deaths from drowning, globally (Pr
uss-
Ust
un & Corval
an 2007; Pr
uss-Ust
un et al. 2008).
Although these figures would require an update, they
indicate that the impacts of WASH on other diseases
combined are likely to be even higher than those on
diarrhoea.
The estimation of diarrhoeal disease burden relies on
proxies such as access to water and sanitation facilities
rather than water quality, water quantity or behaviours
associated with these facilities (such as consistent or
exclusive use by individuals) which are also a determining
factor in characterising actual exposure. They were
selected because of the available exposure information
and their best match in the latest findings on risk esti-
mates from the epidemiological literature. Greater preci-
sion of estimates is expected with better assessment of
these more proximal risks and their population expo-
sures. In addition, in common with a number of other
disease burden estimates (Lim et al. 2012), the estimate is
based on risk estimates for morbidity rather than mortal-
ity.
Due to these limitations, it is unlikely that this estimate
accounts for the full health benefits in diarrhoea reduc-
tion that could be achieved by improvements in WASH.
By relying on evidence of interventions that have often
only achieved limited or partial compliance, this disease
burden reflects reduction in diarrhoea that can be
achieved with currently documented interventions in low-
and middle-income countries. It is unlikely that the esti-
mate accounts for the full reduction in burden that could
be achieved by well-functioning water supply or sewage
systems. For example, this estimate does not reflect health
benefits that may be achieved through improvements fol-
lowing the implementation of management systems such
as water safety plans (Gunnarsdottir et al. 2012), a pro-
active, comprehensive approach to managing risks
throughout the water supply system. In addition, the esti-
mates do not account for the potential impact of
improvements to institutional settings, such as health cen-
tres and schools, and where studies have shown impact
on other age groups (Dreibelbis et al. 2014; Freeman
et al. 2014a).
Through the reassessment of the evidence linking
drinking water to diarrhoea using a more scaled
approach (Wolf et al. 2014), it has been possible to
develop an estimate that takes account of the reduction
in risks when further improving water quality or quantity
over what is currently defined as an ‘improved source’,
which was not carried out in more basic assessments
(Lim et al. 2012). Indeed, improved water sources have
been shown to carry important contamination and risks
to a significant share of the population (Bain et al.
2014).
The separate assessment of the risks of WASH is not
ideal, as those risk factors are likely to have linkages in
terms of both exposure and effects on diarrhoeal risk.
This choice was made, however, to facilitate policy inter-
pretation, and because of the availability of factor-specific
data sets. Nevertheless, the validity of some of these
aspects, such as joint interventions, has been assessed in
© 2014 John Wiley & Sons Ltd 9
Tropical Medicine and International Health volume 00 no 00
A. Pruss-Ustun et al. Burden of disease from WASH
the meta-regression (Wolf et al. 2014) by testing the sig-
nificance of covariates.
It is acknowledged that this assessment does not
account for a number of relevant exposures including
access to a continuous supply of safe piped water, com-
munity sewerage which prevents exposure to untreated
wastewater or excreta (rather than focusing on house-
hold exposure alone) evidence in this area is still lim-
ited. The counterfactual for the current assessment
corresponds to currently achievable options that have
been documented in developing countries and does not
yet take into account the improvements that could be
made beyond such a status. Although this assessment is
limited to low- and middle-income settings, it is
acknowledged that health risks exist even in apparently
well-managed drinking water systems in developed
countries (Zmirou et al. 1995; Naumova et al. 2005;
Lake et al. 2007; Tinker et al. 2009), and further
improvements have been shown to reduce health risks
(Gunnarsdottir et al. 2012). This assessment does, how-
ever, act as a step towards a more comprehensive
future estimate.
Conclusion
This updated estimate of the diarrhoeal disease burden
due to inadequate WASH has made use of a meta-regres-
sion approach to the evidence, based on specific informa-
tion of baseline and outcome situation for each relevant
study. This approach has resulted in a more refined esti-
mate of disease burden according to exposure specifici-
ties. It can accommodate further consolidation as
evidence accrues. It confirms the important role of the
provision of safe water, adequate sanitation and hygiene
promotion to protect health. Previous finding indicating
an important impact of WASH on other diseases than
diarrhoea further strengthens these findings.
Acknowledgements and disclaimer
The study was partially funded by the United Kingdom
Department for International Development (DFID). The
funder had no role in study design, data collection and
analysis, decision to publish or preparation of the manu-
script. Some authors are staff members of the World Health
Organization (WHO) or other institutions. The authors
alone are responsible for the views expressed in this publica-
tion, which do not necessarily represent the views, decisions
or policies of the WHO, the UK DFID or other institutions.
This article should not be reproduced for use in association
with the promotion of commercial products, services or any
legal entity. The WHO does not endorse any specific
organisation or products. Any reproduction of this article
cannot include the use of the WHO logo.
Conflict of interest
Thomas Clasen has participated in research and consult-
ing services supported by Unilever and Vestergaard-
Frandsen, which manufacture and sell household or other
point of use water filtration devices.
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Supporting Information
Additional Supporting Information may be found in the
online version of this article:
Table S1. Deaths attributable to inadequate water,
sanitation, and hygiene by low- and middle-income coun-
triesa for the year 2012.
Table S2. Deaths attributable to the combined inade-
quate water and sanitation, and to the combined inade-
quate water, sanitation and hygiene by low- and middle-
income countrya, for the year 2012.
Corresponding Author Annette Pr
uss-Ust
un, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland.
E-mail: pruessa@who.int
12 © 2014 John Wiley & Sons Ltd
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A. Pruss-Ustun et al. Burden of disease from WASH

Supplementary resource (1)

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Objective Across Africa, the impact of COVID-19 continues to be acutely felt. This includes Malawi, where a key component of health service delivery to mitigate against COVID-19 are the primary healthcare facilities, strategically placed throughout districts to offer primary and maternal healthcare. These facilities have limited infrastructure and capacity but are the most accessible and play a crucial role in responding to the COVID-19 pandemic. This study assessed health facility preparedness for COVID-19 and the impact of the pandemic on health service delivery and frontline workers. Setting Primary and maternal healthcare in Blantyre District, Malawi. Participants We conducted regular visits to 31 healthcare facilities and a series of telephone-based qualitative interviews with frontline workers (n=81 with 38 participants) between August 2020 and May 2021. Results Despite significant financial and infrastructural constraints, health centres continued to remain open. The majority of frontline health workers received training and access to preventative COVID-19 materials. Nevertheless, we found disruptions to key services and a reduction in clients attending facilities. Key barriers to implementing COVID-19 prevention measures included periodic shortages of resources (soap, hand sanitiser, water, masks and staff). Frontline workers reported challenges in managing physical distancing and in handling suspected COVID-19 cases. We found discrepancies between reported behaviour and practice, particularly with consistent use of masks, despite being provided. Frontline workers felt COVID-19 had negatively impacted their lives. They experienced fatigue and stress due to heavy workloads, stigma in the community and worries about becoming infected with and transmitting COVID-19. Conclusion Resource (human and material) inadequacy shaped the health facility capacity for support and response to COVID-19, and frontline workers may require psychosocial support to manage the impacts of the COVID-19 pandemic.
... They reported that globally, almost 10% of the burden of disease was attributed to unsafe water, inadequate sanitation, and poor hygiene. It is estimated that consumption of unsafe water is responsible for over 500,000 deaths annually due to diarrheal disease globally (Prüss-Ustün et al., 2014). For example, Bisung and Elliot (2014) reported that 1.4 million children's deaths each year were caused by diarrheal diseases and 88% were attributable to unsafe water, inadequate sanitation and insufficient hygiene. ...
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Although progress has been made to accelerate access to safe drinking water globally, it is estimated that over 800 million people still lack access to safe water, and have to rely on unsafe and often contaminated water sources. With a population of 50 million, 40% of Kenyans rely on unimproved water sources, including ponds, shallow wells and rivers. Consumption of unsafe water is responsible for over 500,000 deaths annually due to diarrheal disease. Approximately one-third of boreholes with hand pumps fail within five years of construction, interrupting water service that force users to revert to alternative, potentially unprotected, sources. Modelled data suggest that this may undermine any health benefits provided by the water system. The goal for this study was to analyse the seasonality of water use and management of community-based water projects in urban slum settlements. A case of Spring Valley Centre Water Project of Kayole Slums in Nairobi County, Kenya, was studied. A simple linear regression was used, with relationships fitted between the data and time series steps. The observed data over time (time series data) was used to construct three components of a time series-trend, seasonality and the random component. The analysis of the monthly revenue from water sales at the kiosk, over a study period of 2013 to 2020, indicated that the activities peak once a year and drop to a low once in the year. The earlier years (2013 to 2015) could, however, be seen to have annual revenue from water sales at the kiosk varying at a lower rate compared to the latter years of 2015 to 2019. These findings of seasonality in revenues require water management committees to consider planning for continuous functionality and sustainability, while creating awareness against relapse to consumption of water from contaminated sources.
... Furthermore, the growth of doubts about the quality of water from drinking fountains is actively manifested among schoolchildren themselves [34]. However, the school environment has a particular impact: for example, when thirsty after physical activity, students may well neglect recommendations and own beliefs and drink contaminated water [35]. Therefore, the risks of rising levels of water pollution in schools should not be solved by finding alternative sources of water. ...
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The WHO/UNICEF Joint Monitoring Program (JMP) for Water Supply, Sanitation and Hygiene (WASH) produces global estimates of the real situation of access to water, sanitation and hygiene services, and sanitation and hygiene in households, educational institutes and health care facilities; however it is lacking data on schools in Kazakhstan. Thus, the aim of this research was to assess access to WASH in schools of urban area in Kazakhstan. The study was conducted in seven schools of Central Kazakhstan during the COVID-19 pandemic and restrictive measures. Three data collection methods were used: a questionnaire for administrative staff, a questionnaire for parents and observation. Parents of offline study pupils (only second and third grades due to the pandemic) were included in the survey. Students had access to in-building toilets in all schools connected to the centralized sewer. The number of school toilets varied from 7 (KAZ200085) to 61 (KAZ200089). The average amount of toilets was 28.08 ± 16.97. Only two out of seven schools complied with the requirements of Kazakhstan national sanitary standards for the ratio of school toilets to the number of students. From the questionnaire with the school administrations, it was defined that the primary source of drinking water was the public water supply. All schools regularly disinfect and check the water supply system. At the same time, the results also revealed discrepancies in the answers between administration and parents (2.6% of parents showed that their children have rare access to drinking water), and insufficient monitoring of implementation of WASH services. This study also confirmed that the full provision of access to water and water services in the structure of educational institutions solves several SDG targets.
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A mix of secondary and primary research was conducted to examine the hypothesis that access to an at-house water supply will deliver significantly greater health, social and economic benefits than those derived from a shared public water supply. The research was carried out by a team from the University of Leeds, University of North Carolina, University of East Anglia, the London School of Hygiene and Tropical Medicine and University College London, and was based on a mix of literature review and field-base case studies. Fieldwork was carried out in three countries; Ghana, South Africa and Vietnam and used a mix of data collection methods, specifically a three-part household questionnaire, which included anthropometric measures and the measurement of water collection journeys, natural group discussions, and contextual checklists. The headline conclusion from the research is that at-home water supply has significant, measurable benefits when compared with shared water supply outside the home provided that the service provided is reliable enough to ensure access to adequate quantities of water when required. Reliable at-home water supply results in higher volumes of water consumed, greater practice of key hygiene behaviours, a reduction in musculo-skeletal impacts associated with carrying water from outside the home, and improved water quality. This suggests a logical policy shift towards the promotion of reliable household access as the international benchmark for water supply.
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The 2010 global burden of disease (GBD) study represents the latest effort to estimate the global burden of disease and injuries and the associated risk factors. Like previous GBD studies, this latest iteration reflects a continuing evolution in methods, scope and evidence base. Since the first GBD Study in 1990, the burden of diarrhoeal disease and the burden attributable to inadequate water and sanitation have fallen dramatically. While this is consistent with trends in communicable disease and child mortality, the change in attributable risk is also due to new interpretations of the epidemiological evidence from studies of interventions to improve water quality. To provide context for a series of companion papers proposing alternative assumptions and methods concerning the disease burden and risks from inadequate water, sanitation and hygiene, we summarise evolving methods over previous GBD studies. We also describe an alternative approach using population intervention modelling. We conclude by emphasising the important role of GBD studies and the need to ensure that policy on interventions such as water and sanitation be grounded on methods that are transparent, peer-reviewed and widely accepted.