Content uploaded by Thomas Clasen
Author content
All content in this area was uploaded by Thomas Clasen on May 13, 2014
Content may be subject to copyright.
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 (Pr€uss 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 0–33% 33–66% 66–100%
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.
2© 2014 John Wiley & Sons Ltd
Tropical Medicine and International Health volume 00 no 00
A. Pr€uss-Ust€un 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: 0.14–0.74). 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 exposure–risk 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
© 2014 John Wiley & Sons Ltd 3
Tropical Medicine and International Health volume 00 no 00
A. Pr€uss-Ust€un 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 0.59–0.88) 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 0.32–1.86)
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 (0.78–1.01) 0.77 (0.64–0.92) 0.55 (0.38–0.81)
Improved source other than piped to premise 0.86 (0.72–1.03) 0.62 (0.42–0.93)
Basic piped water to premise‡0.72 (0.47–1.11)†
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
Tropical Medicine and International Health volume 00 no 00
A. Pr€uss-Ust€un 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.
© 2014 John Wiley & Sons Ltd 5
Tropical Medicine and International Health volume 00 no 00
A. Pr€uss-Ust€un 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
Tropical Medicine and International Health volume 00 no 00
A. Pr€uss-Ust€un 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 5–7, 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 (0.19–0.50) 229 316 (106 664–300 790) 17 587 (8152–23 065)
America, LMI 0.26 (0.14–0.33) 6441 (624–9748) 522 (39–801)
Eastern Mediterranean, LMI 0.36 (0.19–0.46) 50 409 (22 498–66 604) 4046 (1784–5351)
Europe, LMI 0.16 (0.10–0.26) 1676 (196–2606) 174 (19–271)
South-East Asia 0.32 (0.11–0.44) 207 773 (59 708–293 068) 10 748 (3097–15 160)
Western Pacific, LMI 0.20 (0.09–0.27) 6448 (2005–9469) 716 (198–1081)
Total LMI 0.34 (0.16–0.45) 502 061 (217 119–671 945) 33 793 (14 930–44 871)
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 (0.07–0.31) 126 294 (42 881–186 850) 9694 (3291–14 333)
America, LMI 0.09 (0.03–0.15) 2370 (774–3724) 188 (61–295)
Eastern Mediterranean, LMI 0.17 (0.06–0.26) 24 441 (8339–36 809) 1914 (651–2887)
Europe, LMI 0.03 (0.01–0.06) 352 (107–597) 36 (11–61)
South-East Asia 0.19 (0.06–0.28) 123 279 (42 116–185 426) 6376 (2177–9595)
Western Pacific, LMI 0.11 (0.04–0.17) 3709 (1171–5954) 444 (136–737)
Total LMI 0.19 (0.07–0.29) 280 443 (95 699–417 482) 18 650 (6380–27 769)
DALYs, disability-adjusted life years; PAF, population-attributable fraction; LMI, low and middle income.
© 2014 John Wiley & Sons Ltd 7
Tropical Medicine and International Health volume 00 no 00
A. Pr€uss-Ust€un 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 (0–0.61) 122 955 (0–365 911) 9411 (0–28 006)
America, HI 0.13 (0–0.45) ––
America, LMI 0.20 (0–0.60) 5026 (0–15 013) 416 (0–1243)
Eastern Mediterranean, HI 0.14 (0–0.48) ––
Eastern Mediterranean, LMI 0.21 (0–0.61) 28 699 (0–85 369) 2314 (0–6884)
Europe, HI 0.14 (0–0.48) ––
Europe, LMI 0.19 (0–0.59) 1972 (0–5975) 202 (0–611)
South-East Asia 0.20 (0–0.60) 131 519 (0–392 018) 6857 (0–20 444)
Western Pacific, HI 0.16 (0–0.50) ––
Western Pacific, LMI 0.21 (0–0.61) 6690 (0–19 891) 758 (0–2253)
Total 0.20 (0–0.60) ––
Total HI 0.14 (0–0.47) ––
Total LMI 0.20 (0–0.60) 296 860 (0–885 355) 19 958 (0–59 491)
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 (0.55–0.66) 367 605 (326 795–402 438) 0.51 (0.47–0.55) 307 493 (276 989–335 899)
America, LMI 0.46 (0.36–0.50) 11 519 (9310–13 616) 0.32 (0.28–0.34) 8125 (7101–9158)
Eastern Mediterranean, LMI 0.58 (0.47–0.66) 81 064 (65 359–94 707) 0.47 (0.40–0.53) 65 700 (55 266–75 876)
Europe, LMI 0.35 (0.28–0.46) 3564 (2462–4678) 0.19 (0.19–0.27) 1970 (1654–2280)
South-East Asia 0.56 (0.36–0.70) 363 904 (225 359–477 720) 0.45 (0.31–0.57) 291 763 (193 198–383 423)
Western Pacific, LMI 0.44 (0.31–0.54) 14 160 (10 035–18 009) 0.29 (0.23–0.33) 9429 (7519–11 242)
Total LMI 0.58 (0.48–0.65) 841 818 (699 059–963 626) 0.47 (0.40–0.53) 684 479 (580 456–780 463)
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. Pr€uss-Ust€un 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. Pr€uss-Ust€un 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.
References
Bain R, Cronk R, Bonjour S et al. (2014) Assessment of the level
of exposure to fecally contaminated drinking water in develop-
ing countries. Tropical Medicine and International Health (this
issue).
Baum R, Luh J & Bartram J (2013) Sanitation: a global estimate
of sewerage connections without treatment and the resulting
impact on MDG progress. Environmental Science & Technol-
ogy 47, 1994–2000.
Black RE, Victora CG, Walker SP et al. (2013) Maternal and
child undernutrition and overweight in low-income and mid-
dle-income countries. Lancet 382, 427–477.
Cairncross S & Feachem R (1993). Environmental Health Engi-
neering in the Tropics. An Introductory Text. John Wiley &
Sons, Chichester.
Clasen T, Mclaughlin C, Nayaar N et al. (2008) Microbiological
effectiveness and cost of disinfecting water by boiling in semi-
urban India. American Journal of Tropical Medicine &
Hygiene 79, 407–413.
Clasen T, Pr€
uss-Ust€
un A, Mathers C, Cumming O, Cairncross S
& Colford JM Jr (2014) Estimating the impact of unsafe
water, sanitation and hygiene on the global burden of disease:
evolving and alternative methods. Tropical Medicine & Inter-
national Health (this issue).
Curtis V & Cairncross S (2003) Effect of washing hands with
soap on diarrhoea risk in the community: a systematic review.
The Lancet Infectious Diseases 3, 275–281.
Dangour AD, Watson L, Cumming O et al. (2013) Interventions
to improve water quality and supply, sanitation and hygiene
practices, and their effects on the nutritional status of children.
The Cochrane Database of Systematic Reviews 8, CD009382.
Dreibelbis R, Freeman MC, Greene LE, Saboori S & Rheingans
R (2014) The impact of school water, sanitation, and hygiene
interventions on the health of younger siblings of pupils: a
cluster-randomized trial in Kenya. American Journal of Public
Health 104, e91–e97.
Emerson PM, Cairncross S, Bailey RL & Mabey DC (2000)
Review of the evidence base for the ‘F’ and ‘E’ components of
the SAFE strategy for trachoma control. Tropical Medicine &
International Health 5, 515–527.
Engell RE & Lim S (2013) Does clean water matter? An updated
meta-analysis of water supply and sanitation interventions and
diarrhoeal diseases. The Lancet 381, S44.
Esrey SA, Potash JB, Roberts L & Shiff C (1991) Effects of
improved water supply and sanitation on ascariasis, diarrhoea,
10 © 2014 John Wiley & Sons Ltd
Tropical Medicine and International Health volume 00 no 00
A. Pr€uss-Ust€un et al. Burden of disease from WASH
dracunculiasis, hookworm infection, schistosomiasis, and tra-
choma. Bulletin of the World Health Organization 69, 609–
621.
Evans B, Bartram J, Hunter P et al. (2013) Public Health and
Social Benefits of At-House Water Supplies. University of
Leeds, Leeds, UK.
Ezzati M, Lopez AD, Rodgers A, Vander Hoorn S & Murray
CJL (2002) Selected major risk factors and global and regional
burden of disease. Lancet 360, 1347–1360.
Fewtrell L, Kaufmann RB, Kay D, Enanoria W, Haller L & Col-
ford JM (2005) Water, sanitation, and hygiene interventions
to reduce diarrhoea in less developed countries: a systematic
review and meta-analysis. The Lancet Infectious Diseases 5,
42–52.
Freeman MC, Clasen T, Dreibelbis R et al. (2014a) The impact
of a school-based water supply and treatment, hygiene, and
sanitation programme on pupil diarrhoea: a cluster-random-
ized trial. Epidemiology & Infection 142, 340–351.
Freeman M, Stocks M, Cumming O et al. (2014b) Hygiene and
health: systematic review of handwashing practices worldwide
and update of health effects. Tropical Medicine and Interna-
tional Health (this issue).
Galiani S, Gonzalez-Rozada M & Schargrodsky E (2007) Water
Expansions in Shantytowns: Health and Savings. Inter-Ameri-
can Development Bank, Washington, DC.
Gunnarsdottir MJ, Gardarsson SM, Elliott M, Sigmundsdottir G
& Bartram J (2012) Benefits of water safety plans: microbiol-
ogy, compliance, and public health. Environmental Science &
Technology 46, 7782–7789.
Humphrey JH (2009) Child undernutrition, tropical enteropathy,
toilets, and handwashing. Lancet 374, 1032–1035.
Hunter PR, Ramı
´rez Toro GI & Minnigh HA (2010) Impact on
diarrhoeal illness of a community educational intervention to
improve drinking water quality in rural communities in Puerto
Rico. BMC Public Health 10, 219.
Iijima Y, Karama M, Oundo JO & Honda T (2001) Prevention
of bacterial diarrhea by pasteurization of drinking water in
Kenya. Microbiology & Immunology 45, 413–416.
Lake IR, Harrison FC, Chalmers RM et al. (2007) Case-con-
trol study of environmental and social factors influencing
cryptosporidiosis. European Journal of Epidemiology 22,
805–811.
Lim SS, Vos T, Flaxman AD et al. (2012) A comparative risk
assessment of burden of disease and injury attributable to 67
risk factors and risk factor clusters in 21 regions, 1990–2010:
a systematic analysis for the Global Burden of Disease Study
2010. The Lancet 380, 2224–2260.
Liu L, Johnson HL, Cousens S et al. (2012) Global, regional, and
national causes of child mortality: an updated systematic analysis
for 2010 with time trends since 2000. Lancet 379,2151–2161.
Lozano R, Naghavi M, Foreman K et al. (2012) Global and
regional mortality from 235 causes of death for 20 age groups
in 1990 and 2010: a systematic analysis for the Global Burden
of Disease Study 2010. Lancet 380, 2095–2128.
Mermin JH, Villar R, Carpenter J et al. (1999) A massive epi-
demic of multidrug-resistant typhoid fever in Tajikistan associ-
ated with consumption of municipal water. The Journal of
Infectious Diseases 179, 1416–1422.
Murray C & Lopez AD (1996) The Global Burden of Disease.
World Health Organization, Harvard School of Public Health,
World Bank, Geneva.
Naumova EN, Christodouleas J, Hunter PR & Syed Q (2005)
Effect of precipitation on seasonal variability in
cryptosporidiosis recorded by the North West England surveil-
lance system in 1990–1999. Journal of Water and Health 3,
185–196.
OECD (2013) Public Spending on Health and Long-Term Care:
A New Set of Projections. Organization for Economic Co-
operation and Development, Paris.
Palisade (2013) @Risk 6. http://www.palisade.com/risk
Pickering AJ & Davis J (2012) Freshwater availability and
water fetching distance affect child health in sub-Saha-
ran Africa. Environmental Science & Technology 46,
2391–2397.
Pr€
uss A, Kay D, Fewtrell L & Bartram J (2002) Estimating
the burden of disease from water, sanitation, and hygiene at
a global level. Environmental health perspectives 110,
537–542.
Pr€
uss-Ust€
un A & Corval
an C (2007) How much disease burden
can be prevented by environmental interventions? Epidemiol-
ogy 18, 167–178.
Pr€
uss-Ust€
un A, Bos R, Gore F & Bartram J (2008) Safer Water,
Better Health. World Health Organization, Geneva,
Switzerland.
Rosa G & Clasen T (2010) Estimating the scope of household
water treatment in low- and medium-income countries. The
American Journal of Tropical Medicine and Hygiene 82, 289–
300.
Rosa G, Miller L & Clasen T (2010) Microbiological effective-
ness of disinfecting water by boiling in rural Guatemala.
American Journal of Tropical Medicine & Hygiene 82, 473–
477.
Royal Scientific Society (2013) To Identify Minimum Household
Water Security Requirements for Health Protection. Royal Sci-
entific Society, Amman, Jordan.
Savovi
c J, Jones HE, Altman DG et al. (2012) Influence of
reported study design characteristics on intervention effect esti-
mates from randomized, controlled trials. Annals of Internal
Medicine 157, 429–438.
Tinker SC, Moe CL, Klein M et al. (2009) Drinking water resi-
dence time in distribution networks and emergency department
visits for gastrointestinal illness in Metro Atlanta, Georgia.
Journal of Water and Health 7, 332–343.
Tonglet R, Isu K, Mpese M, Dramaix M & Hennart P
(1992) Can improvements in water supply reduce
childhood diarrhoea? Health Policy and Planning 7,
260–268.
UNICEF (2014) Multiple Indicator Cluster Survey (MICS). Uni-
ted Nations Children’s Fund, New York. http://www.unicef.
org/statistics/index_24302.html.
USAID (2014) DHS Program. US Agency for International
Development. http://dhsprogram.com/.
© 2014 John Wiley & Sons Ltd 11
Tropical Medicine and International Health volume 00 no 00
A. Pr€uss-Ust€un et al. Burden of disease from WASH
Waddington H, Snilstveit B, White H & Fewtrell L (2009)
Water, Sanitation and Hygiene Interventions to Combat Child-
hood Diarrhoea in Developing Countries. The International
Initiative for Impact Evaluation (3ie), New Delhi, India.
WHO (2002) The World Health Report 2002 –Reducing Risks,
Promoting Healthy Life. World Health Organization, Geneva,
Switzerland.
WHO (2004) Comparative Quantification of Health Risks.
World Health Organization, Geneva.
WHO (2009) The Global Burden of Disease: 2004 Update.
World Health Organization, Geneva.
WHO (2013a) Global health observatory –data repository
[Online]. http://apps.who.int/ghodata/files/84/ghodata.html.
WHO (2013b) WHO Regional Offices [Online]. World Health
Organization, Geneva. http://www.who.int/about/regions/en/
WHO (2014) World Health Survey (WHS) [Online]. Geneva.
http://www.who.int/healthinfo/survey/en/
WHO & UNICEF (2013a) Progress on Sanitation and Drinking-
Water. 2013 Update. World Health Organization, Geneva.
WHO & UNICEF (2013b) WHO/UNICEF Joint Monitoring
Programme (JMP) for water supply and sanitation [Online].
http://www.wssinfo.org/data-estimates/introduction/.
Wolf J, Bonjour S & Pr€
uss-Ust€
un A (2013) An exploration of
multilevel modeling for estimating access to drinking-water
and sanitation. Journal of Water and Health 11,64–77.
Wolf J, Pr€
uss-Ust€
un A, Cumming O et al. (2014) Review of the
evidence relating drinking-water and sanitation to diarrhoea: a
meta-regression. Tropical Medicine and International Health
(this issue).
World Bank (2012) Country and Lending Groups, July 2012.
World Bank, Washington, DC.
Ziegelbauer K, Speich B, M€
ausezahl D, Bos R, Keiser J & Utzin-
ger J (2012) Effect of sanitation on soil-transmitted helminth
infection: systematic review and meta-analysis. PLoS Medicine
9, e1001162.
Zmirou D, Rey S & Courtois X (1995) Residual microbiological
risk after simple chlorine treatment of drinking ground water
in small community systems. European Journal of Public
Health 5,75–81.
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
Tropical Medicine and International Health volume 00 no 00
A. Pr€uss-Ust€un et al. Burden of disease from WASH