The number of deaths due to unsafe water sources has generally decreased over time. In low-income countries, unsafe water sources are the cause of 2.3 percent of deaths as of 2021. In Chad, seven percent of deaths are due to these unsafe water resources.

The global death rate due to unsafe water access has decreased in the past decades. As of 2021, there were approximately ten deaths per 100,000 people worldwide, a considerable decrease from almost 41 deaths per 100,000 people in 1990.

There were an estimated 35.2 deaths per 100,000 people due to unsafe water sources in India in 2021. The annual number of deaths due to unsafe water sources in India has fallen by more than 80 percent since 1990. Neverthless, the death rate from this health risk was still three times above the global average in 2021. Unsafe water sources are among the leading death risk factors in India.

Sub-Saharan Africa had the highest death rate due to unsafe water worldwide in 2021, at almost ** people per 100,000. Nevertheless, this was a considerable decrease from the *** deaths for every 100,000 people recorded in the region in 1990.

Japan JP: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 0.200 Ratio in 2016. Japan JP: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 0.200 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Japan JP: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

BackgroundAccording to the most recent estimates, 842,000 deaths in low- to middle-income countries were attributable to inadequate water, sanitation and hygiene in 2012. Despite billions of dollars and decades of effort, we still lack a sound understanding of which kinds of WASH interventions are most effective in improving public health outcomes, and an important corollary–whether the right things are being measured. The World Health Organization (WHO) has made a concerted effort to compile comprehensive data on drinking water quality and sanitation in the developing world. A recent 2014 report provides information on three phenotypes (responses): Unsafe Water Deaths, Unsafe Sanitation Deaths, Unsafe Hygiene Deaths; two grouped phenotypes: Unsafe Water and Sanitation Deaths and Unsafe Water, Sanitation and Hygiene Deaths; and six explanatory variables (predictors): Improved Sanitation, Unimproved Water Source, Piped Water To Premises, Other Improved Water Source, Filtered and Bottled Water in the Household and Handwashing.Methods and FindingsRegression analyses were performed to identify statistically significant associations between these mortality responses and predictors. Good fitted-model performance required: (1) the use of population-normalized death fractions as opposed to number of deaths; (2) transformed response (logit or power); and (3) square-root predictor transformation. Given the complexity and heterogeneity of the relationships and countries being studied, these models exhibited remarkable performance and explained, for example, about 85% of the observed variance in population-normalized Unsafe Sanitation Death fraction, with a high F-statistic and highly statistically significant predictor p-values. Similar performance was found for all other responses, which was an unexpected result (the expected associations between responses and predictors–i.e., water-related with water-related, etc. did not occur). The set of statistically significant predictors remains the same across all responses. That is, Unsafe Water Source (UWS), Improved Sanitation (IS) and Filtered and Bottled Water in the Household (FBH) were the only statistically significant predictors whether the response was Unsafe Sanitation Death Fraction, Unsafe Hygiene Death Fraction or Unsafe Water Death Fraction. Moreover, the fraction of variance explained for all fitted models remained relatively high (adjusted R2 ranges from 0.7605 to 0.8533). We find that two of the statistically significant predictors–Improved Sanitation and Unimproved Water Sources–are particularly influential. We also find that some predictors (Piped Water to Premises, Other Improved Water Sources) have very little explanatory power for predicting mortality and one (Other Improved Water Sources) has a counterintuitive effect on response (Unsafe Sanitary Death Fraction increases with increases in OIWS) and one predictor (Hand Washing) to have essentially no explanatory usefulness.ConclusionsOur results suggest that a higher priority may need to be given to improved sanitation than has been the case. Nevertheless, while our focus in this paper is mortality, morbidity is a staggering consequence of inadequate water, sanitation and hygiene, and lower impact on mortality may not mean a similarly low impact on morbidity. More specifically, those predictors that we found uninfluential for predicting mortality-related responses may indeed be important when morbidity is the response.

In 2021, an estimated 800,000 deaths were attributed to unsafe water sources worldwide, a number that has fallen by 63 percent since 1990.

Chad TD: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 101.000 Ratio in 2016. Chad TD: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 101.000 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Chad TD: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

This dataset contains information on mortality rates per 100,000 people in Cambodia related to unsafe sanitation and unsafe water and unavailability of handwashing facilities. This data shows the overall mortality rate in Cambodia from 1990 to 2019.

Series Name: Mortality rate attributed to unsafe water unsafe sanitation and lack of hygiene (deaths per 100 000 population)Series Code: SH_STA_WASHRelease Version: 2021.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 3.9.2: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (exposure to unsafe Water, Sanitation and Hygiene for All (WASH) services)Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contaminationGoal 3: Ensure healthy lives and promote well-being for all at all agesFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Background: It is not known how the number of deaths due to COVID-19 compare to the number of deaths due to "unsafe water, sanitation, and handwashing" during the COVID-19 global health emergency. Methods: A dataset of deaths due to COVID-19 was downloaded from the World Health Organization. A dataset summarizing deaths due to unsafe water, sanitation, and handwashing was obtained from the Institute for Health Metrics and Evaluation (IHME).  Results indicate that COVID-19 deaths in Africa and South East Asia regions exceeded those due to unsafe water, sanitation, and hygiene. , Two raw datasets were obtained and processed.  To construct the dataset, "Estimates of  mortality due to inadequate water, sanitation, and hygiene (WASH) during the COVID-19 Global Health Emergency" raw data were downloaded from the Institute for Health Metrics and Evaluation (IHME). The raw dataset was reduced, eliminating variables. The original IHME dataset was for the year 2019. IMHE does not yet have data for 2020 or beyond. The final data contains calculations that project into 2020-2023 the estimated number of WASH-related deaths, by region. That was done by multiplying the 2019 estimated deaths by regions, by a factor of the duration of the pandemic period/the number of days in 2019, assuming a constant rate. To construct the dataset "Estimates of COVID-19  mortality, by region January 3 2020-May 5, 2023, with assumptions about undercounting" raw data were downloaded from the public WHO Coronavirus (COVID-19) Dashboard. The raw dataset contains COVID-19 mortality data by coun..., , # Data from: Priority setting for global WASH challenges in the age of wastewater-based epidemiological surveillance

A brief summary of dataset contents

Dataset #1: Estimates of mortality due to inadequate water, sanitation, and hygiene (WASH) during the COVID-19 Global Health Emergency

VARIABLES Region = The name for country groupings used by WHO
Age category = All observations have either the value 1 (<5 years) or 5 (all ages) Deaths 2019 due to unsafe WASH point estimate = The point estimate for the number of deaths due to unsafe WASH in 2019, by WHO region, by age category Deaths 2019 due to unsafe WASH upper estimate = The upper bound estimate for the number of deaths due to unsafe WASH in 2019, by WHO region, by age category Deaths 2019 due to unsafe WASH lower estimate = The lower bound estimate for the number of deaths due to unsafe WASH in 2019, by WHO region, by age category Estimated number Jan 3 2020-May 5 2023 = The estimated number of deaths ...

Sierra Leone SL: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 81.300 Ratio in 2016. Sierra Leone SL: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 81.300 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Sierra Leone SL: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sierra Leone – Table SL.World Bank: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Indicator 3.9.2Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (exposure to unsafe Water, Sanitation and Hygiene for All (WASH) services).Methodology:Incidence rate=Deaths attributable to unsafe water, sanitation, and hygiene focusing on inadequate WASH services, expressed per 100,000 population.Note:Deaths attributable to unsafe water, sanitation, and hygiene focusing on inadequate WASH services, expressed per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. The included diseases are the WASH attributable portions of diarrhea (ICD-10 code A00, A01, A03, A04, A06-A09), intestinal nematode infections (ICD-10 code B76-B77, B79) and protein-energy malnutrition (ICD-10 code E40-E46).Data Source:Ministry of Public Health - Accounts of the Planning and Statistics Authority.

Age-adjusted mortality rates for the contiguous United States in 2000–2005 were obtained from the Wide-ranging Online Data for Epidemiologic Research system of the U.S. Centers for Disease Control and Prevention (CDC) (2015). Age-adjusted mortality rates were weighted averages of the age-specific death rates, and they were used to account for different age structures among populations (Curtin and Klein 1995). The mortality rates for counties with < 10 deaths were suppressed by the CDC to protect privacy and to ensure data reliability; only counties with ≥ 10 deaths were included in the analyses. The underlying cause of mortality was specified using the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems (10th revision; ICD-10). In this study, we focused on the all-cause mortality rate (A00-R99) and on mortality rates from the three leading causes: heart disease (I00-I09, I11, I13, and I20-I51), cancer (C00-C97), and stroke (I60- I69) (Heron 2013). We excluded mortality due to external causes for all-cause mortality, as has been done in many previous studies (e.g., Pearce et al. 2010, 2011; Zanobetti and Schwartz 2009), because external causes of mortality are less likely to be related to environmental quality. We also focused on the contiguous United States because the numbers of counties with available cause-specific mortality rates were small in Hawaii and Alaska. County-level rates were available for 3,101 of the 3,109 counties in the contiguous United States (99.7%) for all-cause mortality; for 3,067 (98.6%) counties for heart disease mortality; for 3,057 (98.3%) counties for cancer mortality; and for 2,847 (91.6%) counties for stroke mortality. The EQI includes variables representing five environmental domains: air, water, land, built, and sociodemographic (2). The domain-specific indices include both beneficial and detrimental environmental factors. The air domain includes 87 variables representing criteria and hazardous air pollutants. The water domain includes 80 variables representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination. The land domain includes 26 variables representing agriculture, pesticides, contaminants, facilities, and radon. The built domain includes 14 variables representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment. The sociodemographic environment includes 12 variables representing socioeconomics and crime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Jian, Y., L. Messer, J. Jagai, K. Rappazzo, C. Gray, S. Grabich, and D. Lobdell. Associations between environmental quality and mortality in the contiguous United States 2000-2005. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(3): 355-362, (2017).

Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.

Run002—All Countries (145) No transformations—Response is USDF.

Jamaica JM: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 0.600 Ratio in 2016. Jamaica JM: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 0.600 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Jamaica JM: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jamaica – Table JM.World Bank: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Mexico MX: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 1.100 Ratio in 2016. Mexico MX: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 1.100 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Mexico MX: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Run101– all countries except DRCongo (144) No transformations–Response is USDF.

1Attack rate was not included as it was not available for the majority of outbreak reports2Other microorganisms included Salmonella spp., Small Round Structured Viruses (SRSV), Rotavirus, Yersinia enterocolitica, Streptococcus spp., Bacillus cereus and Pseudomonas aeruginosa3Unknown was not reported4Count exceeds the total number of people ill due to illness associated with multiple agentsSummary of number of illnesses and deaths by causative microorganism as reported in 293 waterborne disease outbreaks involving small drinking water systems in Canada and the United States (1970–2014).