An equitable sanitation coverage promotes sustainability, economic prosperity, and public health protection. This study examined factors affecting sanitation coverage and the potential of selected countries across three income levels (Low-Income, Lower-Middle, and Upper-Middle Income Countries) to meet Sustainable Development Goal 6.2 by developing a Sanitation Coverage Index (SCI). Nine developing countries were selected based on the following sets of criteria: income level, population, and geographical region. Twenty years (2000–2020) of sanitation coverage data were extracted from the JMP database and visualized. The SCI was developed using the service level criteria and examined the local drivers of poor sanitation coverage. Findings show that all countries studied made good progress and have commendable current status, except Ethiopia, Rwanda, and Nigeria. Nigeria has the highest open defecation coverage and may not meet the 2030 target. The SCI result shows that Turkey, Ukraine, and China have excellent coverage (scoring: 44, 43, and 40). Brazil, Bangladesh, and DPR Korea have satisfactory performances (36, 31, and 31), while Nigeria, Rwanda, and Ethiopia recorded unsatisfactory progress (28, 27, and 16). The strongest factors influencing poor coverage include population, high socioeconomic inequalities, and socio-political challenges. Therefore, the institutionalization of minimum acceptable standards, adequate sensitization, and funding could improve sanitation coverage in the countries assessed.

  • The Sanitation Coverage Index was developed to rank countries’ performances on SDG 6.2.

  • Population density is a major driver of sanitation coverage (SC).

  • Local realities are more representative than the global outlook of income levels.

  • Socioeconomic factors, socio-political factors, and cultural norms influence SC.

  • SC can be improved with the implementation of minimum acceptable standards and sensitization.

Graphical Abstract

Graphical Abstract
Graphical Abstract

An equitable, safe, hygienic, and accessible sanitation facility is pivotal to all forms of human development (JMP, 2021). Target 2 of goal 6 for the Sustainable Development Goals (SDGs) seeks to ensure available and sustainable management of sanitation for all by the year 2030. The prime goal of SDG 6.2 is to prevent human interactions with fecal pathogens to reduce incidences of diseases. To adequately capture the progress of countries in the quest to achieve sanitation for all, sanitation coverage (the proportion of the human population with access to safe sanitation services) is assessed globally. Sanitation coverage fosters an understanding of current practices, planning, and evaluation of the effectiveness of sanitation interventions toward the global agenda on sanitation for all. Sanitation coverage is essential at the global, municipal, and local scales, as it has been connected to public health protection and morbidity reduction (Murray et al., 2012; Freeman et al., 2017). Meanwhile, the absence of an indexing tool for the traction of the actual performance of countries can undermine the deployment of required intervention for enhanced performance in pursuit of the sanitation agenda. As a solution, a robust tool is needed to quantify such an agenda. In this study, a Sanitation Coverage Index (SCI) tool will be proposed to bridge the extant gap and provide overall performance status by ranking and providing the basis for definitive actions.

Kmush et al. (2021) regressed sanitation coverage against maternal and neonatal mortality and established that the relevance of sanitation coverage to neonatal and women's health is underestimated. Hushie (2018) established that poor sanitation service delivery, lack of sense of belonging, and improper engagement of civil society organizations are major drivers of poor sanitation coverage, with negative implications for urban and community development.

In Mali, Africa, community sanitation coverage was found to have a strong correlation with child growth indicators such as height. However, household access to private safe sanitation facilities has a less strong relationship (Harris et al., 2017). This is probably because access to a safe facility in one household among several houses in a community does not guarantee environmental safety since the possibility of epidemic diseases occurring due to poor fecal management by other households is high. Munamati et al. (2017) assessed the factors responsible for the distribution of sanitation facilities in Sub-Saharan Africa (SSA), using a combination of demographic health survey and cluster variables including the World Bank indicators. The study identified income and population, facility space requirements, soil properties (soil type and depth of groundwater table), and topography (steep slopes) as the predominant factors responsible for the choice of sanitation facilities in SSA.

Several factors have been linked to poor sanitation coverage in different parts of the world, resulting in diverse contexts and assumptions. For instance, JMP's (2021) household report stated that SSA countries are seriously behind in the race toward the fulfillment of the SDG 2030 agenda due to the rapid population growth rate, without commensurable investment in sanitation infrastructures. Munamati et al. (2016) linked income level, education, and socio-political stability to countries’ abilities to achieve acceptable sanitation coverage. Low-Income Countries (LICs) have been tagged with poor sanitation coverage basically because of associable lean available resources and consequent low sanitation intervention funds (Cha et al., 2017). Studies have emphasized the necessity for more cost-efficient safe sanitation facilities aside from the conventional sewer system, with huge cost implications attributed to the high cost of construction (Öberg et al., 2020; Delaire et al., 2021). Particularly, this is essential because households will mostly choose affordable sanitation facilities based on their income level.

Despite the significant importance of sanitation coverage to global health profile and development, attention on the subject matter is significantly low. For instance, a search on the Scopus database (on June 1, 2022) for articles with the term ‘sanitation coverage’ (as a focus title) showed that just 12 articles had been published since the introduction of the SDGs in 2015. Although, a few studies such as Munamati et al. (2016, 2019) presented sanitation coverage in the context of countries with a large population that satisfied the Millennium Development Goal (MDG) access to safe sanitation services as ‘sanitation success’. Table 1 summarizes previous studies on sanitation coverage and their study focus (water, sanitation, and hygiene (WASH), countries of focus, and employed indicators. In this study, sanitation coverage is defined as the proportion of households with access to sanitation facilities based on the Joint Monitoring Program (JMP) service levels criteria developed by the United Nations.

Table 1

Bibliographic summary of past articles on sanitation coverage retrieved from Scopus database from 2000–2022.

ReferenceStudy focusVariables of focusCountry(ies)/RegionsTotal citation
Capone et al. (2022)  Ascaris transmission, fecal Soil-transmitted helminth Ascaris ova, community-coverage of latrine. Maputo, Mozambique 
Contreras et al. (2022)  Sanitation coverage, fecal contamination and child health Community sanitation coverage, E. coli, diarrheal, and acute respiratory infection. Bangladesh 
Kmush et al. (2021)  Community sanitation coverage from 1990 to 2018. Community-level women access to sanitation facility, women with neonatal mortality, small birth size, and anemia. 248 countries across the globe. 
Berendes et al. (2020)  Sanitation coverage and fecal contamination in urban open drains. Field sampling of open drains for Escherichia Coliform and community sanitation coverage levels. Accra Ghana 
Wolf et al. (2019)  Impact of WASH improvement on diarrheal incidence and sanitation coverage. Diarrheal incidence in low-middle-income countries, documented on reputable platforms (Cochrane, MEDLINE, PUB-MED, etc.). Low-Middle Income countries 29 
Syromyatnikov et al. (2019)  Water supply and sanitation coverage Big data analysis of water supply and sanitation data harvested from reputable database. Russia 
Nurul Huda et al. (2019)  Community-level sanitation coverage and fecal contamination Classify facilities as improved and unimproved. Analysis fecal coliform from children hands (6–24 months) and sentinel toy balls. Bangladesh 
Berendes et al. (2018)  Urban sanitation coverage and fecal contamination Tested soil and open drain for E. coli, adenovirus, norovirus and facility containment. Ghana 24 
Hushie (2018)  State-Civil society partnership Qualitative assessment (interview) of selected organizations partnership and sanitation. Northern Ghana 
Harris et al. (2017)  Community sanitation coverage and child growth Survey on impact of latrine coverage, community diseases transmission, and access to private sanitation facility on child growth. Mali 39 
Cha et al. (2017)  Water and sanitation coverage Performance and inequality of Opportunity Development Assistance (ODA) on sanitation and water from 1990 to 2010. Developing countries 18 
Oswald et al. (2016)  Sanitation coverage Developed model for predicting sanitation coverage from socio-demographic data Ethiopia 
Ntozini et al. (2015)  House water access and sanitation coverage Geographic Information System using Sanitation Hygiene Infant Nutrition Efficacy (SHINE) data. Zimbabwe 15 
Monney et al. (2015)  Rural sanitation coverage Qualitative data (interview and group discussion) sources to evaluate access to in-house sanitation facility. Ghana 
Munamati et al. (2015)  Sanitation performance and sanitation coverage Criticizes the JMP criteria for sanitation coverage and identified; storage, transport, treatment and disposal as missing indicators. Global 
Mazeau et al. (2013)  Sanitation coverage Identified the necessity of including shared sanitation facility into JMP service level criteria using field survey. Ghana and Uganda 10 
Zheng et al. (2013)  Sanitation coverage House survey on access and class of sanitation facilities using JMP criteria between 1994 and 2009. Bangladesh 
Oumar & Tewari (2013)  Urban drinking water and sanitation coverage Precipitation, population, urbanization, management practices of available resources. Cameroon, Egypt, Nigeria, and South Africa 
Aryal et al. (2012)  Diarrheal diseases burden, water and sanitation coverage Household survey, observation of water sources and sanitation facilities. Nepal 10 
Tumwebaze et al. (2011)  Ecological sanitation coverage Cross sectional interview on coverage of ecological sanitation and its uptake. Uganda 19 
Fry et al. (2008)  Water and sanitation Indicators affecting sanitation coverage and associated factors (legislation, gender disparities and water availability) Global 
Bollmann & Da Motta Marques (2006)  Organic carbon, phosphorus and nitrogen in low sanitation coverage area Chemical and biological oxygen demand, Total Kjedhal Nitrogen and Phosphorus content of rivers within low sanitation coverage community. Brazil 10 
ReferenceStudy focusVariables of focusCountry(ies)/RegionsTotal citation
Capone et al. (2022)  Ascaris transmission, fecal Soil-transmitted helminth Ascaris ova, community-coverage of latrine. Maputo, Mozambique 
Contreras et al. (2022)  Sanitation coverage, fecal contamination and child health Community sanitation coverage, E. coli, diarrheal, and acute respiratory infection. Bangladesh 
Kmush et al. (2021)  Community sanitation coverage from 1990 to 2018. Community-level women access to sanitation facility, women with neonatal mortality, small birth size, and anemia. 248 countries across the globe. 
Berendes et al. (2020)  Sanitation coverage and fecal contamination in urban open drains. Field sampling of open drains for Escherichia Coliform and community sanitation coverage levels. Accra Ghana 
Wolf et al. (2019)  Impact of WASH improvement on diarrheal incidence and sanitation coverage. Diarrheal incidence in low-middle-income countries, documented on reputable platforms (Cochrane, MEDLINE, PUB-MED, etc.). Low-Middle Income countries 29 
Syromyatnikov et al. (2019)  Water supply and sanitation coverage Big data analysis of water supply and sanitation data harvested from reputable database. Russia 
Nurul Huda et al. (2019)  Community-level sanitation coverage and fecal contamination Classify facilities as improved and unimproved. Analysis fecal coliform from children hands (6–24 months) and sentinel toy balls. Bangladesh 
Berendes et al. (2018)  Urban sanitation coverage and fecal contamination Tested soil and open drain for E. coli, adenovirus, norovirus and facility containment. Ghana 24 
Hushie (2018)  State-Civil society partnership Qualitative assessment (interview) of selected organizations partnership and sanitation. Northern Ghana 
Harris et al. (2017)  Community sanitation coverage and child growth Survey on impact of latrine coverage, community diseases transmission, and access to private sanitation facility on child growth. Mali 39 
Cha et al. (2017)  Water and sanitation coverage Performance and inequality of Opportunity Development Assistance (ODA) on sanitation and water from 1990 to 2010. Developing countries 18 
Oswald et al. (2016)  Sanitation coverage Developed model for predicting sanitation coverage from socio-demographic data Ethiopia 
Ntozini et al. (2015)  House water access and sanitation coverage Geographic Information System using Sanitation Hygiene Infant Nutrition Efficacy (SHINE) data. Zimbabwe 15 
Monney et al. (2015)  Rural sanitation coverage Qualitative data (interview and group discussion) sources to evaluate access to in-house sanitation facility. Ghana 
Munamati et al. (2015)  Sanitation performance and sanitation coverage Criticizes the JMP criteria for sanitation coverage and identified; storage, transport, treatment and disposal as missing indicators. Global 
Mazeau et al. (2013)  Sanitation coverage Identified the necessity of including shared sanitation facility into JMP service level criteria using field survey. Ghana and Uganda 10 
Zheng et al. (2013)  Sanitation coverage House survey on access and class of sanitation facilities using JMP criteria between 1994 and 2009. Bangladesh 
Oumar & Tewari (2013)  Urban drinking water and sanitation coverage Precipitation, population, urbanization, management practices of available resources. Cameroon, Egypt, Nigeria, and South Africa 
Aryal et al. (2012)  Diarrheal diseases burden, water and sanitation coverage Household survey, observation of water sources and sanitation facilities. Nepal 10 
Tumwebaze et al. (2011)  Ecological sanitation coverage Cross sectional interview on coverage of ecological sanitation and its uptake. Uganda 19 
Fry et al. (2008)  Water and sanitation Indicators affecting sanitation coverage and associated factors (legislation, gender disparities and water availability) Global 
Bollmann & Da Motta Marques (2006)  Organic carbon, phosphorus and nitrogen in low sanitation coverage area Chemical and biological oxygen demand, Total Kjedhal Nitrogen and Phosphorus content of rivers within low sanitation coverage community. Brazil 10 

According to the findings of Cha et al. (2017), over the last decades, the trend of inequalities in water and sanitation coverage across developing countries worldwide has not been fully addressed. Zerbo et al. (2021) extensively studied water, sanitation and hygiene coverage across all regions of SSA (central, southern, western, and eastern regions) to demystify how the regions are faring and their peculiarities. The study also discovered a correlation between diarrheal mortality and sanitation coverage in the region. However, the study had two major limitations: firstly, only 2017 data from the JMP service level database were used for the assessment, which is considered insufficient for a full understanding of the progress made by an individual country/region. Secondly, the study failed to compare the progress of SSA countries/regions with other developing countries in other continents, particularly countries within the same income group.

While the highlighted factors are strong indicators that contributed to sanitation coverage, questions on pertinent issues on the progress, current status, and feasibility of attaining the 2030 agenda by countries that are lagging behind remain unanswered. Most recent studies have not addressed internal factors responsible for poor coverage (beyond population and income levels) in those countries. In addition, those studies are yet to prove whether countries with similar income levels or geographical locations (continents) have comparable sanitation coverage levels. Additionally, the performance of all countries was reported by JMP (2021), but the report did not present a summary classification (rating) of the performance of individual countries toward attaining the SDG target. Although Sachs et al. (2022) reported an index for monitoring the performance of the countries with respect to SDG, the index presented in the study largely sums up all SDG indicators and does not portray the sanitation coverage performances of the countries. Therefore, the main aim of this study is to analyze the trend in sanitation coverage, the global and internal factors affecting sanitation coverage, and essentially to develop an SCI, for actual performance rating purposes of selected countries across three income levels and different continents. This study has been performed in a manner that is relatable and portrayed to reflect where more interventional actions are required for continuous service improvement.

This study assessed the trend, current state, and potential toward achieving the SDG 6.2 agenda. Nine countries were assessed (Brazil, Bangladesh, China, Ethiopia, Democratic People's Republic of Korea (DRP Korea), Nigeria, Rwanda, Turkey, and Ukraine) across three income levels: LICs, Lower-Middle-Income Countries (LMICs), and Upper-Middle-Income countries (UMICs), exploring the intercontinental income parity. Additionally, an index was proposed to evaluate the country's performance and pursue advances toward sanitation coverage.

While some countries have shown high development toward SDG 6, others seem to be stuck at low levels of sanitation coverage with little or no improvement. Global and internal factors that influence countries’ achievement have been discussed throughout this paper, and a sanitation index has been proposed to chase countries’ performance, based on the factors herein raised.

Health implications of poor sanitation coverage

There are varying underlying factors attributed to poor sanitation coverage across various parts of the globe, and so are the health consequences of poor sanitation coverage. Beyond diarrheal mortality, health implications of poor sanitation coverage in one country may differ from another. Yet, the indirect health implications of poor sanitation coverage and management could be broadly categorized into the following groups as discussed below.

Environmental health risks and emergent contaminants

Poor sewage treatment facilities or management could result in the introduction of various diseases into the environment, posing major environmental health threats. Such contaminants could include organic pollutants, endocrine-disrupting chemicals, micro and nano plastics, and pharmaceutical and personal care products. Endocrine-disrupting chemicals cause acute and severe damage to human health (Wee & Aris, 2017; Hadibarata et al., 2019; Imran et al., 2019; Guo et al., 2020) and trigger illnesses such as cancer, and hormonal imbalance, among others. Sanitary pads and baby wipes are made of plastic and synthetic materials (Park et al., 2019), and their indiscriminate disposal has led to their occurrence in the environment, particularly in water bodies. Detailed studies on their occurrence and toxicity have been investigated by several researchers (Bollmann et al., 2019; Picó & Barceló, 2019; Zhang et al., 2020; Li et al., 2021; Jung et al., 2021).

Although the focus of this study is not centered on wastewater treatment or environmental pollutants, it offers a comprehensive picture of the existing health concerns posed by poor sanitation management. For example, dumping effluents, sewage sludge, or slurries into the environment or a body of water can reintroduce pathogens that were not completely removed during the treatment process (Bankole et al., 2022). Leakage from septic tanks and pit latrines could contribute to groundwater pollution through leaching (Bankole et al., 2022), which has been recognized as a major sanitary risk (Oluwasanya, 2013; Oluwasanya et al., 2016; Odjegba et al., 2020a, 2020b). Currently, research is being conducted to determine the association between sanitation coverage and many of these infections. Meanwhile, Zhang et al. (2021) verified the presence of microplastics in children's feces with concentrations ten times higher than in adult feces. This demonstrates the importance of further research into the relationships between sanitation coverage, pollutants’ bioavailability, and pathogen threats.

Infectious diseases

The importance of access to basic sanitation facilities is reflected in global data on sanitation-related health concerns. Over 2 million people have died as a result of schistosomiasis, which is a neglected tropical disease (NTD), while Soil-Transmitted Helminths (STH) were responsible for around 5 million disability-adjusted lives (DALY), which is more than 1 billion people (Freeman et al., 2017). Schistosomiasis is an infectious disease caused by trematodes, parasites present in human feces (Schistosoma mansoni and Schistosoma japonicum) and urine (Schistosoma haemotobium). STH is caused by nematodes that reside in human guts and enter the environment through fecal contamination (Hotez et al., 2006).

Freeman et al. (2017) established a strong link between sanitation and health problems such as STH, stunted growth, and schistosomiasis in their systematic review and meta-analysis study on the relationship between sanitation and infectious diseases. Freeman et al. (2017) further stated that the information available to justify the implication of the sanitation ladder on infectious diseases was limited. The lack of good data on the occurrence of the aforementioned infectious diseases makes it difficult to make effective inferences. However, available global resources revealed a strong relationship between sanitation coverage and infectious diseases such as NTDs (e.g., STH, schistosomiasis, trachoma, and dengue fever).

Antimicrobial resistance

The occurrence of resistant bacteria in humans is a major public health threat (Isidro et al., 2020; Weinbren, 2020; Pham et al., 2021). Antimicrobial-resistant organisms are food- and water-borne pathogens that have the capability to resist many antibiotic drugs and biocides (WHO, 2018). AMR organisms include but are not limited to Enterobacterales (Klebsiella and Escherichia Coliform) and Arcobacter butzleri, and have been found in water bodies, as well as having an interaction with metals, microplastics, and the general environment (Isidro et al., 2020). WHO (2018) established that untreated cases of antimicrobial resistance (AMR) may be very difficult or impossible to treat.

Weinbren (2020) stated in his study that poor sanitation and water facilities could easily expose patients who seek treatment in healthcare centers to antimicrobial-resistant bacteria if facilities are shared with an infected patient. Besides, the author called for an urgent re-examination of water and sanitation methods, emphasizing that the design to curb pathogens such as cholera is ineffective against AMR. In the same context, shared sanitation facilities in households (limited and unimproved services) could expose users (neighbors) to infections such as antimicrobial-resistant bacteria. Detailed information on the possible association between sanitation coverage and AMR incidences is currently lacking. Thus, the ultimate goal of health authorities at large in terms of sanitation coverage should be geared toward safely managed facilities in order to break the chain of transmission and reduce the risk of exposure to diseases contractible through sharing of sanitation facilities.

Study area

This study focused on sanitation coverage among selected developing countries across three income groups, using their populations and geographical regions as set criteria. The selected countries from the same income group were not from the same geographical region. Since all developing countries are within one of the three income groups (LICs, LMICs, and UMICs), the three income groups were selected for the purpose of this study. Three countries were selected per income level; this was done to give a relative allowance for observation of countries from different geographical regions within an income level. The choice of three countries per group (a total of nine countries) is to ensure fair representation from different continents (at least one per continent) within the three income groups. Also, highly populous countries per region in the income groups are prioritized. The 2021 World Bank country income group classification (available at World Bank Data Help Desk) was utilized in the selection of the countries of focus in this study.

Brazil is the most populous Latin-American country in the UMIC and has shared population density with Nigeria (the most populous SSA country in Lower-Middle-Income level – LMICs). The choice of selecting China for this study was based on both its population and the possibility to identify learning points from recorded successes of other countries, considering that China is seemingly at-par with many developed countries in economic strength. Similarly, Turkey was selected for this study due to its high population (most populous European country) and classification as an UMICs.

This study considers it imperative to examine the coverage trend of a developing country outside the SSA with a moderately high population status (less than 200 million) in the LMICs group, hence, Bangladesh was chosen over India. Notably, the authors recognize the ongoing invasion in Ukraine but consider it important to acknowledge the sanitation status of the country before the invasion. The selection is also to investigate the past progress since the country is the only European/Central Asian country in the LMICs group.

DRP Korea was chosen since it is the only LIC in the East Asia/Pacific region. Ethiopia was chosen to be the most populous SSA country within the LICs group. The choice of selecting Rwanda is to understudy the trend and status of a moderately low populous SSA country in the same income group as a highly populous SSA country (Ethiopia).

Data source and analysis

Sanitation data for the selected nine countries for 20 years (2000–2020) were extracted from the JMP (WHO/UNICEF) data archive JMP (washdata.org). Individual country data based on JMP service level criteria were extracted for this study. The WHO database was chosen for this study because of the SDG indicators service ladder update and the availability of up-to-date sanitation data (2020). Notably, the integrity of JMP as the apex body for the SDG 6 global monitoring, and the assessor/evaluator of progress on the SDG 6 generally were the reasons for using their data for the purposes of this study. Also, the JMP database is an open repository, hence, users’ accessibility is not restricted, in case of future studies on sanitation coverage.

Local realities of the country with critical sanitation status and poor performance over the years were assessed using existing publications retrieved from reputable journal platforms, newspaper articles, and reports by relevant national agencies or United Nations projects, to understand disparities in accessibility and identify vulnerable groups. Service level coverage data for income groups (poorest, poor, middle, rich, and richest classes) were extracted and classified for both urban and rural coverage. Also, the relationship between diarrhea and sanitation coverage in the country was assessed using under-5 children's diarrhea mortality data and sanitation coverage data. The diarrhea mortality data were extracted from the archive of the Institute of Health Metric Evaluation (IHME) portal of Global Health Data Exchange (GBD Results Tool|GHDx(healthdata.org)). The IHME database was chosen here because of its authenticity and open-source repository nature (availability of data up to 2019).

The sanitation service level data for all countries were first grouped and sorted based on income level to run a descriptive statistical analysis using Microsoft Excel 2016 pivot chart for data visualization analysis. The trend in the sanitation coverage over the years 2000–2020 was visualized using appropriate charts. Service level data for both urban and rural areas were summarized with bars representing the years 2000, 2005, 2010, 2015, and 2020. This is to better understand coverage within MDG and SDG eras, as well as progress on access to sanitation facilities and possible effects of sanitation interventions. The diarrheal data extracted were also visualized to project the trend in mortality rate over the 19 years of the study. It is important to note that the data size was insufficient to develop a robust model that could have been used to make inferences and predict future scenarios of sanitation coverage.

Classification of sanitation facilities

Given the numerous types of sanitation facilities and the variation in their adoption by communities/municipalities across the globe, it is essential to classify facilities correctly based on their functions and effectiveness. This study used the service level classification of sanitation facilities as generally improved services, unimproved services, and open defecation. Improved sanitation facilities cut across safely managed services, basic service, and limited services, which include flush/pour flush toilets connected to sewers, septic tanks or ventilated improved latrine toilets, pit latrines with a slab, and composting toilet facilities. Following the JMP's (2021) service level classification, safely managed service includes the use of improved facilities (as listed above) that are not shared with other households and excreta are safely disposed of in situ or treated elsewhere. Basic service is the use of improved facilities that are not shared with other households, while limited service is sharing of improved facilities with another household. Unimproved sanitation facilities include hanging toilets, a pit latrine without a slab, and bucket toilet facilities. Any sort of excretion on an open surface without a sanitation facility or disposal of excreta in an open place (field, forest bushes, open water bodies, beaches, or any open place) is considered open defecation. Notably, at least basic service level is used on occasions where safely managed and basic service level data are merged (Munamati et al., 2015; JMP, 2021).

Sanitation Coverage Index

To develop the SCI, the maximum probable outcome of individual service level was first prioritized (e.g., a country could have 100% coverage of basic service or 100% coverage of unimproved services). Values were subjected to class mark classification using simple statistical classification (e.g., 0–0.4, 0.5–10.4, and 10.5–20.4). The selected range was captured to ensure explicit categorization of the country's coverage and avoid rating bias, and misapproximation of values (i.e., basic service = 10.9 compared to basic service = 10.1). Weight was assigned to each class boundary (0 = 0, and 0.5–10.4 = 1) as shown in Table 2. Also, the weight 0 was assigned to class-bound 0–0.4 (as shown in Table 2) to avoid bias, as one country could have 0.9% coverage while another could have 0% coverage.

Table 2

Sanitation coverage matrix.

Service level
O.D.UNL.M.BASS.M.
Coverage (%)Weight01234
0–0.4 
0.5–10.4 
10.5–20.4 
20.5–30.4 12 
30.5–40.4 12 16 
40.5–50.4 10 15 20 
50.5–60.4 12 18 24 
60.5–70.4 14 21 28 
70.5–80.4 16 24 32 
80.5–90.4 18 27 36 
90.5–100 10 10 20 30 40 
Classification 
Excellent Satisfactory Unsatisfactory     
40–45 30–39 <30     
Service level
O.D.UNL.M.BASS.M.
Coverage (%)Weight01234
0–0.4 
0.5–10.4 
10.5–20.4 
20.5–30.4 12 
30.5–40.4 12 16 
40.5–50.4 10 15 20 
50.5–60.4 12 18 24 
60.5–70.4 14 21 28 
70.5–80.4 16 24 32 
80.5–90.4 18 27 36 
90.5–100 10 10 20 30 40 
Classification 
Excellent Satisfactory Unsatisfactory     
40–45 30–39 <30     

Note: O.D., open defecation; UN, unimproved service; L.M., limited service; BAS, basic service; S.M., safely managed service.

Each service level was assigned a weight, prioritizing their classification (Open defecation = 0, Unimproved = 1). The weight 0 was assigned to the Open defecation service level on the premise that users have no access to a sanitation facility. The matrix of the index is presented in Table 2. To determine the SCI, the summation of the values for all service levels for the individual country was divided by the maximum probable score (45) (see Equation (1)). The maximum probable score was derived by considering the possibility of a country having values for more than one service level (e.g., 82% of safely managed = 36, 11% of basic service = 6, 4% of limited service = 2, and 3% of unimproved service = 1). Data for total sanitation coverage of the countries (from the JMP database) were used for the computation in this section.
formula
(1)

The SCI was classified into three levels (Excellent (40–45), Satisfactory (30–39), and Unsatisfactory (<30)), as shown in Table 2. The choice of classification into the three levels was in relation to the SDG criteria (at least basic service), being the minimum SDG target. The SCI score for the satisfactory level was based on the probable maximum score for a country with 100% basic service level coverage (3 × 10 = 30) as shown in Table 2. The choice of rating for ‘excellent’ was considered important to identify countries with extraordinary performance beyond the basic service level criterion, while unsatisfactory was considered to identify countries performing below the minimum SDG target (at least basic).

This section presents the results of the analysis on the sanitation coverage of the selected countries (Brazil, Bangladesh, China, Ethiopia, DRP Korea, Nigeria, Rwanda, Turkey, and Ukraine), within and across the three income levels: LICs, LMICs, and UMICs. Furthermore, the result of the SCI, in-depth analysis of the local realities, drivers, and pressures responsible for the poor performance of the country with the least performance are also discussed.

Trend in service levels coverage

Low-Income Countries

The trend of sanitation coverage in LICs is presented in Figure 1. Service levels of facility coverage among the three countries (DPR Korea, Ethiopia, and Rwanda) show the extent to which individual states are faring. The coverage of safely managed services was only recorded by Ethiopia, with a steady increase of 1% per 5 years, while both DPR Korea and Rwanda only have data for ‘at least basic service’ facilities. This shows a lack of information on the proportion of households connected to the sewer system or general sewage management practices (disposed of in situ or evacuated and treated elsewhere) by some member states.
Fig. 1

Service level coverage in urban (a) and rural LICs (b).

Fig. 1

Service level coverage in urban (a) and rural LICs (b).

Close modal

The grouping of safely managed and basic service data as ‘at least basic service’ was done by JMP (2021) and used in tracking the progress of the SDG 1.4 (Ensure everyone, i.e. all men and women, have equal rights/access to at least basic services). The combination of basic service and safely managed facilities data for Ethiopia is still low compared to the coverage of at least basic service recorded in Rwanda and DPR Korea between the two decades. Also, the percentage of citizens with access to safely managed services could not be identified which implies that either sewage management is not prioritized or there is a lack of proper data management by the two countries compared to Ethiopia.

The steady decrease (3% every 5 years) in coverage of at least basic services in Rwanda against the increase in coverage of limited services reflects that the country may be experiencing a high rate of urban informal settlements due to rural–urban migration.

The increase in coverage of limited services could also mean that houses built in urban centers in Rwanda over the past two decades embraced more shared facilities such as multiple rooms with one or two toilet facilities. Also, it could be inferred that most houses built in the urban centers within the last two decades have not prioritized the provision of basic sanitation facilities per household, despite the global and national paradigm shifts that emphasize access to basic sanitation services as a fundamental human right. Studies have evidenced that five or more households often share sanitation facilities in low-income areas, reflecting their level of poor menstrual hygiene, lack of privacy, maintenance, and sustainability (Aquaya, 2019a, 2019b, 2019c, 2019d).

Delaire et al. (2021) attributed the seriously poor urban sanitation coverage in LICs to high population of informal settlements. The survey carried out by Okurut & Charles (2014) identified high informal settlements within the capital city of Rwanda (Kigali), with a higher proportion of tenants than house owners. Furthermore, it has been stressed that demands for household sanitation improvement are mainly influenced by types of settlements and users’ income levels. The study also supported the position of Marx et al. (2013), which affirmed that tenants living in informal settlements often do not invest in improving the infrastructural standard of household facilities.

Ethiopia also recorded a steady increase but at a rather low rate for limited and unimproved facilities coverage, unlike DPR Korea which has a reduction in coverage of both services (limited and unimproved services) in place of the increased basic service, as shown in Figure 1(a). Although the sharp reduction in open defecation practices in Ethiopia reflects that progress is being made, the current status requires drastic measures to completely eradicate open defecation practices in the urban centers of the country, including Rwanda.

Rural areas of the LICs explored have a better data representation as all categories of the service levels are well captured. Rwanda has the best performance in safely managed facility coverage with a rapid coverage rate of 6% every 5 years between 2000 and 2015, and 5% in the last 5 years (Figure 1(b)). DPR Korea has the highest basic service coverage with zero percent open defecation practices in the rural areas but a decrease in safely managed facility coverage over the past two decades (23.8% in 2000 to 1.0% in 2020). Safely managed facilities are indicators of appropriate sewage management practices which promote a sustainable and healthy environment. The decrease in safely managed facilities suggests that sanitation management practices (such as sewerage treatment, decentralized treatment, or treated in situ) have been on the decline in the rural part of the country.

Also, it is very interesting to observe that rural areas in Rwanda recorded higher coverage of at least basic service level (basic service and safely managed service) than the urban areas (72.7 against 50.5%). Such progress could be attributed to the impact of the national action plans on alleviating sanitation access in rural areas, further reflecting the better impact of the plan on rural settlements than urban centers. Although the 100% coverage target by 2020 setup by the Rwanda Ministry of Infrastructure (2010) is yet to be achieved, the current status showed that implemented plans could facilitate its realization by the 2030 agenda.

The very poor rate (1% in every 5 years) in coverage of safely managed, basic, and limited services was recorded in Ethiopia (Figure 1(b)). This suggests that the rural areas of Ethiopia are seriously lagging behind in the race toward achieving SDG 6.2. The increased rate of unimproved services shows that most rural dwellers in the country use facilities such as pit latrines without a slab, hanging toilet, and bucket toilet facilities, while many people still practice open defecation. A drastic reduction has been recorded in the rate of open defecation, which can be traced to diverse sanitation interventions. The country has launched the Total Sanitation to End Open Defecation and Urination (TSEDU) in 2019, with a target to end open defecation by 2024 and meet 100% coverage of safely managed services by 2030. However, relatable improvement could not be traced from the current statistics.

Lower-Middle Income Countries

Economic growth influences development activities including global sustainable practices. Sanitation coverage in urban and rural areas of the selected LMICs (Bangladesh, Nigeria, and Ukraine) is presented in Figure 2. Ukraine has the best coverage, with a remarkable improvement over the last two decades. Despite achieving the MDG goal with a 15% increase in safely managed facilities over the basic service between 2010 and 2015, a recent increase (8%) in coverage of safely managed facilities further proves that measures taken have been effective in addressing sanitation problems. Furthermore, it could be assumed that Ukraine prioritizes sewage treatment because safely managed facilities require adequate management and treatment for the generated sewage.
Fig. 2

Service level coverage in urban (a) and rural LMICs (b).

Fig. 2

Service level coverage in urban (a) and rural LMICs (b).

Close modal

Nigeria recorded safely managed services coverage with a steady but low rate of 1% in every 5 years in the last two decades (4% in 20 years), as shown in Figure 2(b). On the other hand, urban areas in Nigeria seem to have a higher improvement rate (4.2%) over Bangladesh (1.4%) in the last 5 years, as shown in Figure 2(a). Data also show that the current status of at least basic service coverage in urban areas of Bangladesh is higher than the coverage in Nigeria (52.8% > 51.7%), Figure 2(a).

The urban coverage of limited sanitation facilities in Ukraine has been the same for the last two decades (20%). Limited service coverage in Bangladesh increased with the highest margin recorded in the last 5 years (3.8%), as shown in Figure 2(a). The near-steady increase in the limited service coverage was attributed to an increase in population density by Zheng et al. (2013). Steady decrease in limited facilities coverage has been observed in the urban areas in Nigeria over the last two decades. Bangladesh currently has higher coverage of unimproved facilities than Nigeria, although unimproved facility coverage in Bangladesh has drastically reduced in the last two decades (at 5% reduction every 5 years).

Urban parts of Nigeria have the highest coverage of open defecation practices among the LMICs assessed in this study. The Federal Government of Nigeria and UNICEF (2016) established that Nigeria has one of the highest populations of people practicing open defecation. The data presented in this study also project that the agenda ‘Making Nigeria Open-Defecation free by 2025’ may not be achieved with the current rate of open-defecation coverage. The current coverage of open defecation in urban centers in Nigeria (8.5%) reflects a high level of informal settlements (majorly urban poor) with a high population of underserviced people, which was also documented in the study of Öberg et al. (2020).

Rural sanitation coverage in Ukraine has been impressive with the eradication of unimproved facility usage and open defecation practices (Figure 2(b)). Although there is no information on safely managed facility coverage, progress recorded in Bangladesh within the last two decades, and particularly the past 5 years, is commendable for eradicating open defecation practices in rural areas. The improvement in safely managed and basic facilities coverage in Bangladesh in the last 5 years (Figure 2(b)) proves that the country is working very hard toward achieving the SDG 6.2 target. Contreras et al. (2022) studied the environmental implications of community sanitation coverage on children's health and fecal contamination using 360 rural compounds in Bangladesh. The study established a strong relationship between the community sanitation coverage and reported diarrheal cases, acute respiratory infections, and the population density of the community. Although their approach to sanitation coverage was based on access to a safely managed toilet facility (latrine) at a varying distance (50 and 100 m coverage), the authors further stated that higher coverage directly influenced the occurrence of diarrheal cases and children's health.

Relating the current coverage of unimproved and limited sanitation services to the findings of Contreras et al. (2022), it could be inferred that rural areas in Bangladesh will be negatively impacted with children's health at more risk if the current coverage is not improved. In addition, the structure of the community (compound) could be a limiting factor; a community that uses a compound structure (combination of many houses) may likely find it difficult to adopt a safely managed facility, because their ‘compound’ may usually consist of extended families, thus shared and unimproved sanitation facilities are common, due to their societal norms.

With open defecation having the highest current sanitation coverage, and a decrease in limited services coverage, rural Nigerian towns are clearly falling behind in the 2030 sanitation for all agenda. The dominance of unimproved facilities as the second most used service in rural parts of Nigeria could be attributed to a multi-dimensional problem mainly caused by poorly financed rural sanitation projects as evident in the report of UN-Global Analysis and Assessment of Sanitation and Drinking-Water (2014) and national budgets. Also, the non-adoption of technology-oriented sanitation facilities due to a lack of education and adequate knowledge of its health benefits (Seleman & Bhat, 2016), and poverty could also contribute to poor coverage. For instance, a lack of requisite knowledge of the importance of improved facilities could make rural dwellers consider the construction of pit latrine toilets cheaper and easier, compared to the conventional sewer facility (flush toilet) or improved pit latrine facility. The current status strongly indicates that Nigeria may not meet the 2030 sanitation target without drastic measures that would boost the coverage.

Upper-Middle Income Countries

The urban and rural sanitation coverage in Brazil, China, and Turkey in the past two decades is presented in Figure 3. Notably, Turkey recorded a matchless performance among the UMICs assessed, with basic and limited services being the only facilities used in the urban parts of the country from 2020. Further increase in safely managed facility coverage and eradication of the 1% unimproved services accounted for during the conclusion of the MDG goal evidences their level of commitment to the sanitation for all agenda. Hence, the country is currently considered to have achieved >99% coverage in at least basic services (safely managed plus basic service) in urban centers, placing it ahead of China.
Fig. 3

Service level coverage in urban (a) and rural UMICs (b).

Fig. 3

Service level coverage in urban (a) and rural UMICs (b).

Close modal

Although China currently has the highest coverage of safely managed facilities (Figure 3(a)), with only 2% of limited services and unimproved facilities left, Turkey took roughly 15 years to eradicate its 2% unimproved facility usage. This fact affirms the suggestion of Fuller et al. (2016) and Luh & Bartram (2016) that it is very difficult to reach unserved populations as a country moves toward achieving optimum sanitation coverage (100% at least basic service coverage). Having said that, with the accelerated rate of implementation, current economic status, and demonstrable political will, China could fast track the eradication process before 2030, thus achieving the global agenda. Urban areas in Brazil have also experienced a significant improvement in safely managing facility coverage and the eradication of open defecation practices which was captured at the inception of the SDGs in 2015.

Brazil currently has the least coverage of at least basic sanitation services among the three countries studied, as shown in Figure 3(a) and 3(b), with China slightly leading Brazil by 1.1% in urban coverage (Figure 3(a)). Brazil currently has a lower percentage of safely managed services coverage compared with China and Turkey. However, Brazil has successfully eradicated open defecation practices in urban areas. This illustrates its proper implementation of the 2019 National Basic Water and Sanitation Plan whose aim to achieve at least 85% coverage of safely managed services and eradicate unimproved facilities by the year 2023 is achievable (PLANSAB, 2019). According to Ferreira et al. (2021), the national plan fails to explicitly present the target for the rural areas in Brazil, stressing that the country's socioeconomic and cultural diversity could be a major hindrance to achieve the 2030 SDG target 6.

Rural areas in Turkey recorded an increase in safely managed facility coverage at an impressive rate. This made Turkey the best with regards to the provision of both safely managed services, and at least basic service coverage (97%), ahead of Brazil and China. Furthermore, the current status shows that Turkey is among the developing countries (UMICs) that is currently about to meet the SDG 6.2 target. This inference is based on the safely managed service coverage improvement rate (7% in every 5 years), which strongly shows that the remaining 1% each of unimproved service, limited service, and open defecation coverage could be transformed into at least service before 2030. However, the 1% proportion of people practicing open defecation in Turkey seems to be a serious concern since the value has been occurring over the past two decades.

China is also performing well in its rural sanitation coverage, by eradicating open defecation practices within the last 5 years. In addition, the rise in securely managed service coverage (approximately 66%) is impressive, demonstrating that if similar devotion is harnessed, the remaining percentage of unimproved and limited services might be transformed before the year 2030. As a result, it could be predicted that China would achieve SDG 6.2 in both rural and urban areas by 2030.

Current service level coverage in Brazil reflects the efforts made toward the implementation of several sanitation action plans that particularly in the rural settlements, have resulted in a drastic reduction in the proportion of people practicing open defecation. However, it is important that the large percentage of people using unimproved facilities (34%) and the minute proportion practicing open defecation (2%) be eradicated to ensure the realization of SDG 6.2. According to Ferreira et al. (2021), sanitation services in Brazil require more investment than water supply services, as sanitation requires more infrastructure and currently has less coverage compared to drinking water.

Among all countries assessed in this study, Nigeria, being the most populous African country with a high GDP (compared to LICs studied), currently has the worst sanitation coverage, with the highest level of open defecation practices. Therefore, further assessment of local drivers in states like Nigeria is essential to demystify the cause(s) of such poor sanitation coverage.

Drivers and pressures affecting sanitation progress in Nigeria

State agenda and the SDG

The Federal Ministry of Water Resources (FMWR), Nigeria is saddled with the responsibility to monitor the water supply and sanitation progress of Nigeria as a state, and execute all federal government projects on WASH. However, the responsibility for providing water and sanitation is carried by state and local governments (UN-GLASS, 2014). Several policies made by the federal government in the late 1990s to early 2000s, such as the Nigeria Sanitation Policy 2004, and the National Water Resources Acts 2007, which bestowed the power of monitoring and execution of WASH projects on the FMWR, addressed the issue of access and right of citizens to water and sanitation facilities. The federal government developed the water sector road map 2010, to upscale the failed attempt of a 60% target for coverage of access to safe sanitation facilities by 2007. This is to ensure that the 65% coverage target is achieved, and consequently, the MDG. However, despite all efforts and international interventions, only 28% coverage was achieved by 2012, but the value rapidly increased to 41% coverage (of the total population) in 2013 (WHO/UNICEF, 2014). The major factor that caused such a rapid increase is not clear to the authors. Conversely, an estimated population of over 100 million people still lack access to basic sanitation, while 123 out of every 1,000 children under the age of 5 years die due to diarrhea in Nigeria (UNICEF, 2013).

The effect of this poor sanitation coverage does not only affect the state's public health status, but also results in a major loss to the economy. The Water and Sanitation Program (2012) reported that Nigeria loses about $3 billion yearly (at $1 equals ₦152.8), accounting for about 1.3% of the GDP. Federal investment in the water and sanitation goals varies between different settlement classes (urban, rural, and peri-urban) and the components of the goal. For example, funding for rural community projects on sanitation was only 19% of the capital projects in 2014, with 4% of the total disproportionate funding released. Between the years 2014 and 2016, the federal government through the Federal Ministry of Environment failed to allocate funds for the sanitation sector of the country. Only 46% out of less than 0.5% of the total allocation was released in 2017, and the 0.5% allocation is grossly below the initially promised 1% of the national budget meant to be allocated (WSSCC, 2020).

Although SSA countries (including Nigeria) received several endowment funds from different bodies including the United States Agency for International Development (USAID), World Bank, and Bill and Melinda Gates Foundation (Water Easy Toilet project and Reinvent Toilet expo) (WaterAid, 2016; UNICEF, 2020), Nigeria's sanitation sector grew worse in 2018, leading to the federal government's declaration of a state of emergency on the country's WASH sector. The government further declared a 13-year National Action Plan to achieve an equitable access to WASH services in the country (World Bank, 2021). According to Kotsila & Saravanan (2017), most water and sanitation solutions do not reach those in need. Unfortunately, such is the situation in Nigeria as key indicators that could improve the current sanitation coverage, such as community sensitization, implementation of community-based projects, and increase in the funds allocation to the WASH sector remains a mirage. In addition, non-implementation of projects geared toward improving the dilapidated municipal sewage treatment infrastructures in the country is considered to influence the poor sanitation situation, which may further impede the realization of the global SDGs. Therefore, the poor sanitation coverage status in Nigeria can be attributed to a lack of political will.

Comparing the status of Nigeria's sanitation sector to a country of both high population and socio-cultural diversity like Brazil, we identified that Brazil also has some level of inequality with regard to water and sanitation investment within the country. Current sanitation coverage shows that the North and Northeastern parts of Brazil have the highest proportion of underserviced people (86.9 and 69.7%), compared to the Southeastern part (19.5%) (Painelsaneamento, 2020). Nevertheless, certain statistics confirm the huge differences in commitment and structure between Brazil and Nigeria (aside from income). In Brazil, infrastructure investment for water and sanitation is derived from four major sources: water and sanitation provider, municipality, state government, and the union. For instance, some states/municipalities in Brazil such as State of Acre (99.46%) and Para (72.89%), provide the largest portion of the funding for sanitation services in their state. While the institutional frameworks in some states/municipalities (e.g., Sao Paulo) allow service providers (industries) to invest and enhance their sanitation infrastructure. This further shows that implementation of development-oriented frameworks in Nigeria may improve the sanitation status of the country.

Local realities of sanitation coverage: equity or inequality

Despite the publicity of the SDG goals, understanding of human rights to basic facilities remains a rhetoric for the vast majority in many developing countries, and Nigeria has not been spared from this experience. Several studies have established the severe consequences of poor access to basic sanitation (Tsinda et al., 2015; Seleman & Bhat, 2016; Elimian et al., 2019; Spuhler et al., 2020; Odjegba et al., 2021; Peletz et al., 2021). The variation in the access to sanitation facilities across different settings in many developing countries has attracted studies on the marginalization of underrepresented groups, hard to reach/far to reach people, rural dwellers and particularly, the female gender. The inequality in basic facility usage in rural and urban areas is clearly observed and it has become an old tale. But the extent of inequality between the income groups in the same environment (e.g., urban poor, middle class, and urban rich) in every community deserves more attention if we really do not want to leave the vulnerable groups behind.

Demystifying the Nigerian context of the vulnerable groups, Figure 4(a) and 4(b) presents the variation in access to sanitation services by income groups in Nigeria (richer, rich, poor, and poorest), both in urban and rural areas. The urban richest have the highest population with access to a minimum of basic facilities, followed by the rich and middle class, leaving the poor and urban poorest behind. This is clearly in alignment with previous studies on the choice of sanitation technology by Munamati et al. (2017) and Armah et al. (2018). A similar trend is found in the population practicing open defecation, with the urban poorest having access to majorly unimproved services and open defecation due to lack of access to basic facilities. The United Nations Children's Fund (2019) and the study of Zerbo et al. (2021) related the poor sanitation coverage among the urban poor to the disparities in socioeconomic standards between the urban poor and urban rich, with children being the major group affected by severe consequences.
Fig. 4

Urban (a) and rural (b) sanitation coverage in Nigeria by income groups.

Fig. 4

Urban (a) and rural (b) sanitation coverage in Nigeria by income groups.

Close modal

In rural part of Nigeria, open defecation is practiced across different income groups. This could be considered as owing to a lack of adequate information on the health implications of open defecation practices and exposure to fecal contamination. This supports the findings by Munamati et al. (2016), who suggested education as the strongest factor influencing sanitation success in SSA. This relationship could be traced to the choice of facility, as well-informed individuals will always desire safe sanitation services, provided they are affordable and accessible.

Nigeria's poor sanitation status has attracted the prevalence of diarrheal incidence, with the lives of under-5 children at more risk (Vos et al., 2015; Fontoura et al., 2018). The most common enteric fecal disease is cholera, caused by Vibrio cholera. There have been several cholera outbreaks in Nigeria, right from the late 1990s till now. Elimian et al. (2019) documented past cholera outbreaks in Nigeria, and established that all measures taken by the government to eradicate cholera proved abortive. In 2018, Nigeria experienced a cholera outbreak that claimed over 800 lives. Figure 5 shows the trend of diarrheal mortality for the group of under-5 children in Nigeria between the years 2000 and 2019. This has been examined to establish the link between the country's sanitation coverage, diarrheal mortality, and its gender implications.
Fig. 5

Population of under-5 years diarrheal mortality in Nigeria.

Fig. 5

Population of under-5 years diarrheal mortality in Nigeria.

Close modal

The result from the diarrheal data (Figure 5) shows that the mortality pattern observed is similar to the trend of sanitation coverage (increase in coverage of at least basic services to decrease in diarrheal deaths, and decrease in open defecation translate to decrease in diarrheal deaths).

This trend corroborates the findings of Wolf et al. (2014), which demonstrated that improved sewer connections and use of safe water facilitate the decrease in diarrheal occurrence. The result also shows that diarrheal death occurs more in male children (under 5 years) compared to females. The major cause of this difference could also be other factors that are not captured in this study (such as proportion of male-to-female child birth). According to the study conducted by Kmush et al. (2021), poor community sanitation coverage influences diarrheal mortality, neonatal deaths, maternal anemia, and small birth sizes. Kmush et al. (2021) further stressed that improvement is mostly feasible in communities with nearly 100% coverage of basic services. Therefore, findings revealed that a high level of inequality exists at the community-level coverage, affecting the Nigerian sanitation sector with a larger underserviced population in both urban and rural areas.

Apart from the government's lack of political will to provide basic sanitation services to citizens, insecurity has caused marginalization of different parts of the country. Tyndall et al. (2020) reported the adverse effect of the activities of the Islamic insurgence group (Boko Haram) in the Northern parts of Nigeria. They emphasized that mortality, maternal, child health, and malnutrition are increasing in the region, where there are more than 2.4 million internally displaced people. Fear of being molested, kidnapped, raped, or killed has driven many people to flee for their lives, abandoning aspirations that go beyond bare necessities (Watkins, 2006).

Olarewaju (2021) further stressed that the adverse impact of insurgency includes poor healthcare workforce and food insecurity, and deprivation of access to safe WASH. He also emphasized that 50% out of the over 7.1 million people in need of humanitarian services were children. Although no study has established the link between armed conflict and sanitation coverage, the suggestion of recent findings (Eboreime & Obi, 2017; Dunn, 2018; Tyndall et al., 2020; Olarewaju, 2021) on the impact of armed conflict on healthcare status of Nigeria, coupled with the increasing statistics of internally displaced people, evidently proved that insurgency occurrences in Nigeria would affect the sanitation coverage in the country. Notably, insurgency is not limited to the northern part of Nigeria as some states in the southern part are also challenged by the Niger Delta insurgency group. Therefore, Nigeria may not be able to meet the SDG 6.2 if insurgency is not properly addressed before 2030.

The SCI result is presented in Table 3. The SCI is a true reflection of the overall performance of a country's sanitation coverage in relation to the SDG target 6.2. Turkey, Ukraine, and China recorded excellent performances in their SCI scores. Notably, Turkey has the overall best performance with a score of 44, followed by Ukraine (43) and China (40). Their performances are consistent with the sanitation coverage reported in the earlier section. This implies that current sanitation coverage in Turkey, Ukraine, and China have surpassed the satisfactory level and are well positioned to meet the 2030 SDG target 6.2.

Table 3

The SCI across income levels.

CountryCompositeClassification
Turkey 44 Excellent 
Ukraine 43 
China 40 
Brazil 36 Satisfactory 
Bangladesh 31 
DPR Korea 31 
Nigeria 28 Unsatisfactory 
Rwanda 27 
Ethiopia 16 
CountryCompositeClassification
Turkey 44 Excellent 
Ukraine 43 
China 40 
Brazil 36 Satisfactory 
Bangladesh 31 
DPR Korea 31 
Nigeria 28 Unsatisfactory 
Rwanda 27 
Ethiopia 16 

Brazil, Bangladesh, and DPR Korea recorded a satisfactory performance, in which Brazil was taking the lead with a score of 36, followed by Bangladesh (31), and DPR Korea (31). Generally, those countries are considered to be on track in fulfilling the 2030 sanitation goal. However, some levels of improvement are expected to ensure they obtain excellent status. The performance of DPR Korea was unable to be perfectly commensurate with the result discussed earlier (Figure 1(a) and 1(b)), due to their poor data representation (they only have at least basic service level data, no data for safely managed services). Thus, the current coverage of safely managed services in the country could not be concluded. This is also considered as one of the advantages of the SCI as the rating score will reflect the level of appropriate data representation by country.

In comparison, Nigeria, Rwanda, and Ethiopia recorded the worst performance, with values of 28, 27, and 16, respectively. The reason of poor performance by Rwanda based on the index is also similar to the case of DPR Korea (i.e., poor data representation). The rating of Nigeria ahead of Ethiopia despite their high coverage of open defecation is attributed to the fair coverage of safely managed services in Nigeria, against the high coverage of unimproved facilities with very low coverage of basic and safely managed services in Ethiopia.

Generally, the SCI rating reflects the general sanitation coverage across the countries, which perfectly aligns with the findings (coverage status) discussed above and efficiently summarizes their performances. Furthermore, the SCI as a tool has an added advantage as it identifies adequate data representation by countries, which would reflect the ideal current situation of the countries, thus promoting quality assurance of data. Therefore, it is believed that the SCI tool might assist governments, policymakers, stakeholders, and the general public to chase the global ranking for sanitation coverage performances and further the SDG agenda.

In general, the role of population density as a critical factor influencing sanitation coverage is obvious from the current status of Rwanda against Ethiopia (despite their being in the same region), and DPR Korea (based on rural service coverage of at least basic service). A similar pattern was observed in the coverage of studied LMICs. Ukraine (with the least population density) has better coverage compared to Nigeria and Bangladesh; while Bangladesh also performed better than Nigeria. Furthermore, the performance of Turkey against Brazil and China also showed that countries with the least population density in each group performed better than the highly populous countries. However, China was an exception with a better coverage compared to Brazil, despite its high population density of up to four times Brazil's population. Nevertheless, all studied UMICs have very good sanitation coverage, despite their high population density.

The role of geographical location (region) as an indicator for sanitation coverage is found to be negligible, particularly with Rwanda (located in SSA), which has better coverage of safely managed services than DPR Korea (located in East Asia/Pacific region) and Ethiopia (which is located in the same region – SSA). Meanwhile, highly populous SSA countries assessed in this study (Nigeria and Ethiopia) recorded poor sanitation coverage, with Nigeria being the worst (highest coverage of open defecation).

The impact of the challenges experienced with the installation of sanitation facilities such as septic tanks cannot be overlooked. According to the household survey conducted by Aquaya (2019d), most low-income residents in Nakuru, Kenya had loose soils, causing pits to collapse. Aquaya (2019d) also emphasized that most households would have preferred to install a pour flush toilet facilities'. Cases of poor land consolidation (loose soils) that cause the collapse of septic tanks and pit latrines have been reported in Rangpur, Bangladesh, Kenya (Nakuru, Malindi, and Kisimu), and Ghana (Aquaya, 2019a, 2019b, 2019c, 2019d). These recent studies further confirmed the position of Munamati et al. (2017) that soil properties are major determinants of sanitation facilities' choice/usage in SSA countries.

The comparison of service level coverage in Nigeria (an LMIC) to Lower Income Countries (DPR Korea and Rwanda) proved that income level does not necessarily translate into better sanitation coverage, particularly when necessary sustainable development plans are not effectively implemented. Despite the fact that income is a basic determinant of a country's level of growth, disparities within income groups in Nigeria proved that income levels influence sanitation coverage in a local context more than the national/country level. This aligns with the study of Luh & Bartram (2016) that compares the relationship between gross national income per-capita and the rate of change in access to sanitation services in 73 countries using a regression analysis. Their study affirmed that there is no significant relationship between the income level of a country and its progress in sanitation service accessibility.

The official development assistance (ODA) is vital in boosting the sanitation coverage of the developing countries (particularly LICs and LMICs). The importance of ODA was evident in the progress recorded by Bangladesh in the last decade. However, analysis from the study of Hopewell & Graham (2014) concluded that no significant relationship exists between sanitation coverage and ODA received by countries (developing countries, particularly in SSA). Salami et al. (2014) attributed the cause of the insignificant relationship to poor accountability, stating that ODAs received by SSA countries could not translate into better sanitation coverage due to inadequate utilization of aid such as diversion of funds to service external debts.

Beyond economic and political stability, socio-cultural perspective and religious inclination are underlying factors influencing sanitation services adoption, which in turn influence sanitation coverage. Engagement of users or local community representatives as grass-root stakeholders are important to the success of any development-oriented project. According to Dwipayanti et al. (2019), the socio-cultural perspective impacts the success of sanitation programs which also influences sanitation coverage. As further emphasized, the uptake of technology in development programs is often affected by socio-cultural beliefs, making it (socio-cultural) an integral aspect in planning a framework for sustainable sanitation and acceptable infrastructure.

Different studies have reported the impact of societal norms and cultural beliefs on sanitation services usage. For instance, Routray et al. (2015) attributed poor utilization of sanitation services provided by NGOs and the government in the coastal area of Odisha, India to socio-cultural factors such as the elaborate process of cleansing after defecation, behavioral differences, gender and marital segregations, among others. Dwipayanti et al. (2019) also found a strong relationship between sanitation practices/acceptance of services and local cultural beliefs on purity, and local values among the rural dwellers in rural Bali, Indonesia. The study also stated that in-depth studies with analysis of the role of cultural values and norms, and possible means of adoption into sanitation programs are uncommon.

Graveleau et al. (2021) studied a Community-Led Total Sanitation approach to establish the importance of the whole system and bottom-up approach to increase sanitation services coverage and eradicate cholera outbreaks in rural areas in Niger. Similarly, Geruso & Spears (2018) found that religious beliefs within a community influence the sanitation services usage and in turn child mortality. Although the impact of socio-cultural and religious perspectives on sanitation coverage/ services acceptability is common in the rural settings, the variation in global cultural and religious diversities, which differs from one location to another, makes it complex to develop a general framework that could proffer solutions to these challenges. However, the incorporation of socio-cultural and religious perspectives into future frameworks could boost sanitation coverage and ensure no one is left behind. The factors (global and local) influencing sanitation coverage are summarized in Figure 6.
Fig. 6

Factors (global and internal) influencing sanitation coverage.

Fig. 6

Factors (global and internal) influencing sanitation coverage.

Close modal

Globally, the importance of population, growth rate, urbanization, environmental factors (such as soil properties), and funding has been established, with evidence in this study. However, the big question now will be what is the best way to approach this complex problem? If the management of funds and implementation of action plans set by the government are duly followed, will this set the country on the path to provide at least basic service to all its citizens? Could the implementation of a minimum acceptable standard in each country be a way forward?

Adequate funding and implementation of projects (action plans) geared toward sustainable water and sanitation management will definitely improve the current status of countries. Meanwhile, in the face of rapid population increase and ensuing urban sprawls from urbanization in many developing countries like Nigeria (including many SSA countries), legalization (legislation and enforcement) of minimum standards for sanitation facility installation in houses and public places could be a sustainable way to go. Considering that every country has blueprints for at least urban planning, it is believed that mandating a minimum standard of at least improved sanitation facilities for all households could rapidly improve sanitation coverage (particularly eradicating open defecation) and thus facilitate the realization of SDG 6.2 in many countries. Furthermore, the implementation of such minimum standards could allow flexibilities in the selection of service types depending on the regional and societal norms. Therefore, such approaches could also address the difficulty of technology uptake in sanitation projects.

The roles of education (high literacy level) and political stability in the realization of the millennium development goals’ sanitation target in SSA countries have been demonstrated (Munamati et al., 2016). Internal factors such as cultural/societal norms, religious beliefs, illiteracy, segregation, and other socio-cultural factors can be mitigated through adequate public literacy on the importance of sanitation and hygiene practices. This is expected to have more impact in rural settings, and also improve the quality of life in the urban centers, thus reducing urban sprawl.

Although the SDG era has witnessed more global awareness, the current coverage of people practicing open defecation in urban and rural areas shows that people need to be well informed on both the proper choice of sanitation facility (what type of toilet is good and what type is not) and their benefits (beyond just health implications). Places with specific environmental factors such as poor soil consolidation can be properly sensitized on alternative sanitation facilities such as the use of surface plastic containment and communal sanitation facilities. Generally, most of the internal factors affecting sanitation coverage can be controlled with adequate sensitization, good political will, and funding.

The limitations of this study include the lack of primary data from the survey that could help us make additional inferences on the factors affecting sanitation coverage (particularly, the role of religious belief, gender and marital segregation, environmental factors, socio-political problems, among others). This is expected to elucidate the impact of each factor and help policymakers in developing frameworks that would adequately address poor sanitation coverage. Nevertheless, findings from this study could help governments and the general public make sustainable decisions and serve as a reference point for researchers to make further studies that will benefit sanitation coverage both locally and globally. Future studies are advised to include this aspect in their research.

This study assessed the trend, current status, and potential toward achieving the SDG 6.2. For this purpose, sanitation coverage in nine countries (Brazil, Bangladesh, China, DPR Korea, Ethiopia, Nigeria, Rwanda, Ukraine, and Turkey) across three income levels, and geographical regions were critically studied. Global and internal factors affecting sanitation coverage were raised, exploring income parity intercontinentally, and an SCI to classify and rank the performance of the countries was developed.

Findings from this study show that Rwanda, DPR Korea, Bangladesh, Ukraine and all UMICs studied recorded major improvement in their sanitation coverage over the last two decades. This allowed them to meet the 2030 target of the United Nations. Ethiopia recorded poor improvement with high coverage of open defecation, while Nigeria has the worst performance with highest coverage of open defecation in rural and urban areas. Although both of those countries have a fair improvement in general coverage, their pace may not translate into the realization of the SDG 6.2 by 2030.

The global factor given by the population density has the strongest influence on sanitation coverage, all low populous countries outperformed high populous countries in the same income level. Geographical peculiarities (e.g., soil properties) have more influence on sanitation coverage than geographical location/region. There was no direct relationship identified between the country's income level and sanitation coverage. Rather, disparities in income groups within the country influence sanitation coverage at the community level, which was evidenced in Nigeria. Identified drivers influencing the poor sanitation coverage in Nigeria include a high population of urban poor through high socioeconomic differences, lack of political will, and insurgency. The incidence of diarrheal mortality in the group of children under 5 years old has a similar trend with sanitation coverage in Nigeria.

Several identified internal factors affecting sanitation coverage include socioeconomic disparities, poor project implementation and monitoring, cultural and religious beliefs, gender and marital status segregation, sanitation facility design and cost implications, and insecurity. Their influence on the adoption of sanitation services, although of varying prominence, still has a bearing impact on sanitation coverage. Therefore, internal factors of a locality are considered critical in any successful sanitation development program.

The developed SCI shows that Turkey, Ukraine, and China have an excellent performance; Brazil, Bangladesh, and DPR Korea have a satisfactory performance, while Nigeria, Rwanda and Ethiopia have an unsatisfactory performance. The SCI index is considered good to perform well in ranking the country's sanitation coverage performances, with a potential of adoption for water coverage as well.

Therefore, a holistic intervention, commitment from both the government and citizens, institutional framework implementation, legislation, and enforcement of a minimum acceptable standard for sanitation services are critical to improving sanitation coverage. Adoption of eco-friendly solutions such as communal sanitation facilities and surface plastic containment are alternative sustainable solutions that can be explored in regions with environmental problems. Lastly, adequate public sensitization and funding are also urgently needed to improve sanitation coverage in countries lagging behind and facilitate the realization of SDG 6.2.

The authors (A.O.B., A.O.J., and B.E.) are grateful to TETFund and Agricultural Research and Innovation Fellowship for Africa (ARIFA), for the opportunity and support to pursue postgraduate studies in Brazil. R.B.M. is grateful to the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES), in the scope of the Program CAPES-PrInt, process number 88887.310327/2018-00 and to CNPq Grant numbers 309788/2021-8.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

All relevant data are available from an online repository or repositories. Links to the JMP data (washdata.org) and the Health data (healthdata.org) has been provided in the methodology (section 2.2).

The authors declare there is no conflict.

Aquaya
(
2019a
).
Sanitation Policies, Practices and Preferences in Rangpur, Bangladesh
.
Aquaya Institute
.
Aquaya
(
2019b
).
Sanitation Policies, Practices and Preferences in Kisumu, Kenya
.
Aquaya Institute
.
Aquaya
(
2019c
).
Sanitation Policies, Practices and Preferences in Kumasi, Ghana
.
Aquaya Institute
.
Aquaya
(
2019d
).
Sanitation Policies, Practices and Preferences in Nakuru, Kenya
.
Aquaya Institute
.
Armah
F. A.
,
Ekumah
B.
,
Yawson
D. O.
,
Odoi
J. O.
,
Afitiri
A. -R.
&
Nyieku
F. E.
(
2018
).
Access to improved water and sanitation in Sub-Saharan Africa in a quarter century
.
Heliyon
4
,
e00931
.
https://doi.org/10.1016/j.heliyon.2018.e00931
.
Aryal
K. K.
,
Joshi
H. D.
,
Dhimal
M.
,
Singh
S. P.
,
Dhakal
P.
,
Dhimal
B.
&
Bhusal
C. L.
(
2012
).
Environmental burden of diarrhoeal diseases due to unsafe water supply and poor sanitation coverage in Nepal
.
J. Nepal Health Res. Counc.
10
,
125
129
.
Bankole
A. O.
,
Oluwasanya
G.
&
Odjegba
E. E.
(
2022
).
Evaluation of groundwater suitability in the Cretaceous Abeokuta formation, Nigeria: implications for water supply and public health
.
Groundwater Sustainable Dev.
19
,
100845
.
https://doi.org/10.1016/j.gsd.2022.100845
.
Berendes
D. M.
,
Kirby
A. E.
,
Clennon
J. A.
,
Agbemabiese
C.
,
Ampofo
J. A.
,
Armah
G. E.
,
Baker
K. K.
,
Liu
P.
,
Reese
H. E.
,
Robb
K. A.
,
Wellington
N.
,
Yakubu
H.
&
Moe
C. L.
(
2018
).
Urban sanitation coverage and environmental fecal contamination: links between the household and public environments of Accra, Ghana
.
PLOS ONE
13
,
e0199304
.
https://doi.org/10.1371/journal.pone.0199304
.
Berendes
D. M.
,
de Mondesert
L.
,
Kirby
A. E.
,
Yakubu
H.
,
Adomako
L.
,
Michiel
J.
,
Raj
S.
,
Robb
K.
,
Wang
Y.
,
Doe
B.
,
Ampofo
J.
&
Moe
C. L.
(
2020
).
Variation in E. coli concentrations in open drains across neighborhoods in Accra, Ghana: the influence of onsite sanitation coverage and interconnectedness of urban environments
.
Int. J. Hyg. Environ. Health
224
,
113433
.
https://doi.org/10.1016/j.ijheh.2019.113433
.
Bollmann
H. A.
&
Da Motta Marques
D. M. L.
(
2006
).
Influence of the urban density in the relationship among carbonic organic matter, nitrogen and phosphorous in small rivers with low sanitation coverage
.
Eng. Sanitaria e Ambiental
11
,
343
352
.
https://doi.org/10.1590/s1413-41522006000400007
.
Bollmann
U. E.
,
Simon
M.
,
Vollertsen
J.
&
Bester
K.
(
2019
).
Assessment of input of organic micropollutants and microplastics into the Baltic Sea by urban waters
.
Mar. Pollut. Bull.
148
,
149
155
.
https://doi.org/10.1016/j.marpolbul.2019.07.014
.
Capone
D.
,
Barker
T.
,
Cumming
O.
,
Flemister
A.
,
Geason
R.
,
Kim
E.
,
Knee
J.
,
Linden
Y.
,
Manga
M.
,
Meldrum
M.
,
Nala
R.
,
Smith
S.
&
Brown
J.
(
2022
).
Persistent ascaris transmission is possible in urban areas even where sanitation coverage is high
.
Environ. Sci. Technol.
https://doi.org/10.1021/acs.est.2c04667
.
Cha
S.
,
Mankadi
P. M.
,
Elhag
M. S.
,
Lee
Y.
&
Jin
Y.
(
2017
).
Trends of improved water and sanitation coverage around the globe between 1990 and 2010: inequality among countries and performance of official development assistance
.
Global Health Action
10
,
1327170
.
https://doi.org/10.1080/16549716.2017.1327170
.
Contreras
J. D.
,
Islam
M.
,
Mertens
A.
,
Pickering
A. J.
,
Kwong
L. H.
,
Arnold
B. F.
,
Benjamin-Chung
J.
,
Hubbard
A. E.
,
Alam
M.
,
Sen
D.
,
Islam
S.
,
Rahman
M.
,
Unicomb
L.
,
Luby
S. P.
,
Colford
J. M.
Jr.
&
Ercumen
A.
(
2022
).
Influence of community-level sanitation coverage and population density on environmental fecal contamination and child health in a longitudinal cohort in rural Bangladesh
.
Int. J. Hyg. Environ. Health
245
.
https://doi.org/10.1016/j.ijheh.2022.114031
.
Delaire
C.
,
Peletz
R.
,
Haji
S.
,
Kones
J.
,
Samuel
E.
,
Easthope-Frazer
A.
,
Charreyron
E.
,
Wang
T.
,
Feng
A.
,
Mustafiz
R.
,
Faria
I. J.
,
Antwi-Agyei
P.
,
Donkor
E.
,
Adjei
K.
,
Monney
I.
,
Kisiangani
J.
,
MacLeod
C.
,
Mwangi
B.
&
Khush
R.
(
2021
).
How much will safe sanitation for all cost? Evidence from five cities
.
Environ. Sci. Technol.
55
,
767
777
.
https://doi.org/10.1021/acs.est.0c06348
.
Dwipayanti
N. M. U.
,
Rutherford
S.
&
Chu
C.
(
2019
).
Cultural determinants of sanitation uptake and sustainability: local values and traditional roles in rural Bali, Indonesia
.
J. Water Sanit. Hyg. Dev.
9
,
438
449
.
https://doi.org/10.2166/washdev.2019.178
.
Eboreime
E.
&
Obi
F. A.
(
2017
).
How Boko Haram is Devastating Health Services in North-East Nigeria [WWW Document]
.
The Conversation
. .
Elimian
K. O.
,
Musah
A.
,
Mezue
S.
,
Oyebanji
O.
,
Yennan
S.
,
Jinadu
A.
,
Williams
N.
,
Ogunleye
A.
,
Fall
I. S.
,
Yao
M.
,
Eteng
W. -E.
,
Abok
P.
,
Popoola
M.
,
Chukwuji
M.
,
Omar
L. H.
,
Ekeng
E.
,
Balde
T.
,
Mamadu
I.
,
Adeyemo
A.
,
Namara
G.
,
Okudo
I.
,
Alemu
W.
,
Peter
C.
&
Ihekweazu
C.
(
2019
).
Descriptive epidemiology of cholera outbreak in Nigeria, January–November, 2018: implications for the global roadmap strategy
.
BMC Public Health
19
,
1264
.
https://doi.org/10.1186/s12889-019-7559-6
.
Federal Government of Nigeria and UNICEF
(
2016
).
Making Nigeria Open Defecation Free by 2025: A National Road map
.
Federal Ministry of Water Resources
,
Nigeria
.
Ferreira
D. C.
,
Graziele
I.
,
Marques
R. C.
&
Gonçalves
J.
(
2021
).
Investment in drinking water and sanitation infrastructure and its impact on waterborne diseases dissemination: the Brazilian case
.
Sci. Total Environ.
779
,
146279
.
https://doi.org/10.1016/j.scitotenv.2021.146279
.
Fontoura
V. M.
,
Graepp-Fontoura
I.
,
Santos
F. S.
,
Neto
M. S.
,
Tavares
H. S. d. A.
,
Bezerra
M. O. L.
,
Feitosa
M. d. O.
,
Neves
A. F.
,
Morais
J. C. M. d.
&
Nascimento
L. F. C.
(
2018
).
Socio-environmental factors and diarrheal diseases in under five-year old children in the state of Tocantins, Brazil
.
PLOS ONE
13
,
e0196702
.
https://doi.org/10.1371/journal.pone.0196702
.
Freeman
M. C.
,
Garn
J. V.
,
Sclar
G. D.
,
Boisson
S.
,
Medlicott
K.
,
Alexander
K. T.
,
Penakalapati
G.
,
Anderson
D.
,
Mahtani
A. G.
,
Grimes
J. E. T.
,
Rehfuess
E. A.
&
Clasen
T. F.
(
2017
).
The impact of sanitation on infectious disease and nutritional status: a systematic review and meta-analysis
.
Int. J. Hyg. Environ. Health
220
,
928
949
.
https://doi.org/10.1016/j.ijheh.2017.05.007
.
Fry
L. M.
,
Mihelcic
J. R.
&
Watkins
D. W.
(
2008
).
Water and nonwater-related challenges of achieving global sanitation coverage
.
Environ. Sci. Technol.
42
,
4298
4304
.
https://doi.org/10.1021/es7025856
.
Fuller
J. A.
,
Goldstick
J.
,
Bartram
J.
&
Eisenberg
J. N. S.
(
2016
).
Tracking progress towards global drinking water and sanitation targets: a within and among country analysis
.
Sci. Total Environ.
541
,
857
864
.
https://doi.org/10.1016/j.scitotenv.2015.09.130
.
Geruso
M.
&
Spears
D.
(
2018
).
Neighborhood sanitation and infant mortality
.
Am. Econ. J. Appl. Econ.
10
,
125
162
.
https://doi.org/10.1257/app.20150431
.
Graveleau
J.
,
Reserva
M. E.
,
Keita
A.
,
Molinari
R.
&
Constantin De Magny
G.
(
2021
).
Influence of community-led total sanitation and water coverages in the control of cholera in Madarounfa, Niger (2018)
.
Front. Public Health
9
,
643079
.
https://doi.org/10.3389/fpubh.2021.643079
.
Guo
J. -J.
,
Huang
X. -P.
,
Xiang
L.
,
Wang
Y. -Z.
,
Li
Y. -W.
,
Li
H.
,
Cai
Q. -Y.
,
Mo
C. -H.
&
Wong
M. -H.
(
2020
).
Source, migration and toxicology of microplastics in soil
.
Environ. Int.
137
,
105263
.
Hadibarata
T.
,
Kristanti
R. A.
&
Mahmoud
A. H.
(
2019
).
Occurrence of endocrine-disrupting chemicals (EDCs) in river water and sediment of the Mahakam River
.
J. Water Health
18
,
38
47
.
https://doi.org/10.2166/wh.2019.100
.
Harris
M.
,
Alzua
M. L.
,
Osbert
N.
&
Pickering
A.
(
2017
).
Community-level sanitation coverage more strongly associated with child growth and household drinking water quality than access to a private toilet in Rural Mali
.
Environ. Sci. Technol.
51
,
7219
7227
.
https://doi.org/10.1021/acs.est.7b00178
.
Hotez
P. J.
,
Bundy
D. A. P.
,
Beegle
K.
,
Brooker
S.
&
Drake
L.
(
2006
).
Helminth infections: soil-transmitted helminth infections and schistosomiasis
.
Dis. Control Priorities Dev. Countries
,
467
482
.
Imran
M.
,
Das
K. R.
&
Naik
M. M.
(
2019
).
Co-selection of multi-antibiotic resistance in bacterial pathogens in metal and microplastic contaminated environments: an emerging health threat
.
Chemosphere
215
,
846
857
.
https://doi.org/10.1016/j.chemosphere.2018.10.114
.
Isidro
J.
,
Ferreira
S.
,
Pinto
M.
,
Domingues
F.
,
Oleastro
M.
,
Gomes
J. P.
&
Borges
V.
(
2020
).
Virulence and antibiotic resistance plasticity of Arcobacter butzleri: insights on the genomic diversity of an emerging human pathogen
.
Infect. Genet. Evol.
80
,
104213
.
https://doi.org/10.1016/j.meegid.2020.104213
.
JMP
(
2021
).
Progress on Household Drinking Water, Sanitation and Hygiene, 2000-2020
.
UNICEF DATA
,
Geneva
.
Jung
J. -W.
,
Park
J. -W.
,
Eo
S.
,
Choi
J.
,
Song
Y. K.
,
Cho
Y.
,
Hong
S. H.
&
Shim
W. J.
(
2021
).
Ecological risk assessment of microplastics in coastal, shelf, and deep sea waters with a consideration of environmentally relevant size and shape
.
Environ. Pollut.
270
,
116217
.
https://doi.org/10.1016/j.envpol.2020.116217
.
Kmush
B. L.
,
Walia
B.
,
Neupane
A.
,
Frances
C.
,
Mohamed
I. A.
,
Iqbal
M.
&
Larsen
D. A.
(
2021
).
Community-level impacts of sanitation coverage on maternal and neonatal health: a retrospective cohort of survey data
.
BMJ Global Health
6
,
e005674
.
https://doi.org/10.1136/bmjgh-2021-005674
.
Kotsila
P.
&
Saravanan
V. S.
(
2017
).
Biopolitics gone to shit? State narratives versus everyday realities of water and sanitation in the Mekong delta
.
World Dev.
93
,
374
388
.
https://doi.org/10.1016/j.worlddev.2017.01.008
.
Li
C.
,
Gan
Y.
,
Zhang
C.
,
He
H.
,
Fang
J.
,
Wang
L.
,
Wang
Y.
&
Liu
J.
(
2021
).
‘Microplastic communities’ in different environments: differences, links, and role of diversity index in source analysis
.
Water Res.
188
,
116574
.
https://doi.org/10.1016/j.watres.2020.116574
.
Luh
J.
&
Bartram
J.
(
2016
).
Drinking water and sanitation: progress in 73 countries in relation to socioeconomic indicators
.
Bull. World Health Organ.
94
,
111
121A
.
https://doi.org/10.2471/BLT.15.162974
.
Marx
B.
,
Stoker
T.
&
Suri
T.
(
2013
).
The economics of slums in the developing world
.
J. Econ. Perspect.
27
,
187
210
.
https://doi.org/10.1257/jep.27.4.187
.
Mazeau
A.
,
Tumwebaze
I. K.
,
Lüthi
C.
&
Sansom
K.
(
2013
).
Inclusion of shared sanitation in urban sanitation coverage? Evidence from Ghana and Uganda
.
Waterlines
32
,
334
348
.
https://doi.org/10.3362/1756-3488.2013.034
.
Monney
I.
,
Baffoe-Kyeremeh
A.
&
Amissah-Reynolds
P. K.
(
2015
).
Accelerating rural sanitation coverage in Ghana: what are the speed bumps impeding progress?
J. Water Sanit. Hyg. Dev.
5
,
531
543
.
https://doi.org/10.2166/washdev.2015.005
.
Munamati
M.
,
Nhapi
I.
&
Misi
S. N.
(
2015
).
Monitoring sanitation performance: unpacking the figures on sanitation coverage
.
J. Water Sanit. Hyg. Dev.
5
,
341
350
.
https://doi.org/10.2166/washdev.2015.180
.
Munamati
M.
,
Nhapi
I.
&
Misi
S.
(
2016
).
Exploring the determinants of sanitation success in Sub-Saharan Africa
.
Water Res.
103
,
435
443
.
https://doi.org/10.1016/j.watres.2016.07.030
.
Munamati
M.
,
Nhapi
I.
&
Misi
S. N.
(
2017
).
Types and distribution of improved sanitation technologies in Sub-Saharan Africa
.
J. Water Sanit. Hyg. Dev.
7
,
260
271
.
https://doi.org/10.2166/washdev.2017.123
.
Munamati
M.
,
Nhapi
I.
&
Misi
S.
(
2019
).
Exploring the sanitation success, sanitation technology and diarrhoeal mortality nexus in Sub-Saharan Africa
.
Phys. Chem. Earth Parts ABC
114
,
102795
.
https://doi.org/10.1016/j.pce.2019.08.003
.
Murray
C. J. L.
,
Vos
T.
,
Lozano
R.
,
Naghavi
M.
,
Flaxman
A. D.
,
Michaud
C.
,
Ezzati
M.
,
Shibuya
K.
,
Salomon
J. A.
,
Abdalla
S.
,
Aboyans
V.
,
Abraham
J.
,
Ackerman
I.
,
Aggarwal
R.
,
Ahn
S. Y.
,
Ali
M. K.
,
AlMazroa
M. A.
,
Alvarado
M.
,
Anderson
H. R.
,
Anderson
L. M.
,
Andrews
K. G.
,
Atkinson
C.
,
Baddour
L. M.
,
Bahalim
A. N.
,
Barker-Collo
S.
,
Barrero
L. H.
,
Bartels
D. H.
,
Basáñez
M.-G.
,
Baxter
A.
,
Bell
M. L.
,
Benjamin
E. J.
,
Bennett
D.
,
Bernabé
E.
,
Bhalla
K.
,
Bhandari
B.
,
Bikbov
B.
,
Abdulhak
A. B.
,
Birbeck
G.
,
Black
J. A.
,
Blencowe
H.
,
Blore
J. D.
,
Blyth
F.
,
Bolliger
I.
,
Bonaventure
A.
,
Boufous
S.
,
Bourne
R.
,
Boussinesq
M.
,
Braithwaite
T.
,
Brayne
C.
,
Bridgett
L.
,
Brooker
S.
,
Brooks
P.
,
Brugha
T. S.
,
Bryan-Hancock
C.
,
Bucello
C.
,
Buchbinder
R.
,
Buckle
G.
,
Budke
C. M.
,
Burch
M.
,
Burney
P.
,
Burstein
R.
,
Calabria
B.
,
Campbell
B.
,
Canter
C. E.
,
Carabin
H.
,
Carapetis
J.
,
Carmona
L.
,
Cella
C.
,
Charlson
F.
,
Chen
H.
,
Cheng
A. T.-A.
,
Chou
D.
,
Chugh
S. S.
,
Coffeng
L. E.
,
Colan
S. D.
,
Colquhoun
S.
,
Colson
K. E.
,
Condon
J.
,
Connor
M. D.
,
Cooper
L. T.
,
Corriere
M.
,
Cortinovis
M.
,
de Vaccaro
K. C.
,
Couser
W.
,
Cowie
B. C.
,
Criqui
M. H.
,
Cross
M.
,
Dabhadkar
K. C.
,
Dahiya
M.
,
Dahodwala
N.
,
Damsere-Derry
J.
,
Danaei
G.
,
Davis
A.
,
Leo
D. D.
,
Degenhardt
L.
,
Dellavalle
R.
,
Delossantos
A.
,
Denenberg
J.
,
Derrett
S.
,
Des Jarlais
D. C.
,
Dharmaratne
S. D.
,
Dherani
M.
,
Diaz-Torne
C.
,
Dolk
H.
,
Dorsey
E. R.
,
Driscoll
T.
,
Duber
H.
,
Ebel
B.
,
Edmond
K.
,
Elbaz
A.
,
Ali
S. E.
,
Erskine
H.
,
Erwin
P. J.
,
Espindola
P.
,
Ewoigbokhan
S. E.
,
Farzadfar
F.
,
Feigin
V.
,
Felson
D. T.
,
Ferrari
A.
,
Ferri
C. P.
,
Fèvre
E. M.
,
Finucane
M. M.
,
Flaxman
S.
,
Flood
L.
,
Foreman
K.
,
Forouzanfar
M. H.
,
Fowkes
F. G. R.
,
Fransen
M.
,
Freeman
M. K.
,
Gabbe
B. J.
,
Gabriel
S. E.
,
Gakidou
E.
,
Ganatra
H. A.
,
Garcia
B.
,
Gaspari
F.
,
Gillum
R. F.
,
Gmel
G.
,
Gonzalez-Medina
D.
,
Gosselin
R.
,
Grainger
R.
,
Grant
B.
,
Groeger
J.
,
Guillemin
F.
,
Gunnell
D.
,
Gupta
R.
,
Haagsma
J.
,
Hagan
H.
,
Halasa
Y. A.
,
Hall
W.
,
Haring
D.
,
Haro
J. M.
,
Harrison
J. E.
,
Havmoeller
R.
,
Hay
R. J.
,
Higashi
H.
,
Hill
C.
,
Hoen
B.
,
Hoffman
H.
,
Hotez
P. J.
,
Hoy
D.
,
Huang
J. J.
,
Ibeanusi
S. E.
,
Jacobsen
K. H.
,
James
S. L.
,
Jarvis
D.
,
Jasrasaria
R.
,
Jayaraman
S.
,
Johns
N.
,
Jonas
J. B.
,
Karthikeyan
G.
,
Kassebaum
N.
,
Kawakami
N.
,
Keren
A.
,
Khoo
J.-P.
,
King
C. H.
,
Knowlton
L. M.
,
Kobusingye
O.
,
Koranteng
A.
,
Krishnamurthi
R.
,
Laden
F.
,
Lalloo
R.
,
Laslett
L. L.
,
Lathlean
T.
,
Leasher
J. L.
,
Lee
Y. Y.
,
Leigh
J.
,
Levinson
D.
,
Lim
S. S.
,
Limb
E.
,
Lin
J. K.
,
Lipnick
M.
,
Lipshultz
S. E.
,
Liu
W.
,
Loane
M.
,
Ohno
S. L.
,
Lyons
R.
,
Mabweijano
J.
,
MacIntyre
M. F.
,
Malekzadeh
R.
,
Mallinger
L.
,
Manivannan
S.
,
Marcenes
W.
,
March
L.
,
Margolis
D. J.
,
Marks
G. B.
,
Marks
R.
,
Matsumori
A.
,
Matzopoulos
R.
,
Mayosi
B. M.
,
McAnulty
J. H.
,
McDermott
M. M.
,
McGill
N.
,
McGrath
J.
,
Medina-Mora
M. E.
,
Meltzer
M.
,
Memish
Z. A.
,
Mensah
G. A.
,
Merriman
T. R.
,
Meyer
A.-C.
,
Miglioli
V.
,
Miller
M.
,
Miller
T. R.
,
Mitchell
P. B.
,
Mock
C.
,
Mocumbi
A. O.
,
Moffitt
T. E.
,
Mokdad
A. A.
,
Monasta
L.
,
Montico
M.
,
Moradi-Lakeh
M.
,
Moran
A.
,
Morawska
L.
,
Mori
R.
,
Murdoch
M. E.
,
Mwaniki
M. K.
,
Naidoo
K.
,
Nair
M. N.
,
Naldi
L.
,
Narayan
K. M. V.
,
Nelson
P. K.
,
Nelson
R. G.
,
Nevitt
M. C.
,
Newton
C. R.
,
Nolte
S.
,
Norman
P.
,
Norman
R.
,
O'Donnell
M.
,
O'Hanlon
S.
,
Olives
C.
,
Omer
S. B.
,
Ortblad
K.
,
Osborne
R.
,
Ozgediz
D.
,
Page
A.
,
Pahari
B.
,
Pandian
J. D.
,
Rivero
A. P.
,
Patten
S. B.
,
Pearce
N.
,
Padilla
R. P.
,
Perez-Ruiz
F.
,
Perico
N.
,
Pesudovs
K.
,
Phillips
D.
,
Phillips
M. R.
,
Pierce
K.
,
Pion
S.
,
Polanczyk
G. V.
,
Polinder
S.
,
Pope
C. A.
,
Popova
S.
,
Porrini
E.
,
Pourmalek
F.
,
Prince
M.
,
Pullan
R. L.
,
Ramaiah
K. D.
,
Ranganathan
D.
,
Razavi
H.
,
Regan
M.
,
Rehm
J. T.
,
Rein
D. B.
,
Remuzzi
G.
,
Richardson
K.
,
Rivara
F. P.
,
Roberts
T.
,
Robinson
C.
,
De Leòn
F. R.
,
Ronfani
L.
,
Room
R.
,
Rosenfeld
L. C.
,
Rushton
L.
,
Sacco
R. L.
,
Saha
S.
,
Sampson
U.
,
Sanchez-Riera
L.
,
Sanman
E.
,
Schwebel
D. C.
,
Scott
J. G.
,
Segui-Gomez
M.
,
Shahraz
S.
,
Shepard
D. S.
,
Shin
H.
,
Shivakoti
R.
,
Silberberg
D.
,
Singh
D.
,
Singh
G. M.
,
Singh
J. A.
,
Singleton
J.
,
Sleet
D. A.
,
Sliwa
K.
,
Smith
E.
,
Smith
J. L.
,
Stapelberg
N. J.
,
Steer
A.
,
Steiner
T.
,
Stolk
W. A.
,
Stovner
L. J.
,
Sudfeld
C.
,
Syed
S.
,
Tamburlini
G.
,
Tavakkoli
M.
,
Taylor
H. R.
,
Taylor
J. A.
,
Taylor
W. J.
,
Thomas
B.
,
Thomson
W. M.
,
Thurston
G. D.
,
Tleyjeh
I. M.
,
Tonelli
M.
,
Towbin
J. A.
,
Truelsen
T.
,
Tsilimbaris
M. K.
,
Ubeda
C.
,
Undurraga
E. A.
,
van der Werf
M. J.
,
van Os
J.
,
Vavilala
M. S.
,
Venketasubramanian
N.
,
Wang
M.
,
Wang
W.
,
Watt
K.
,
Weatherall
D. J.
,
Weinstock
M. A.
,
Weintraub
R.
,
Weisskopf
M. G.
,
Weissman
M. M.
,
White
R. A.
,
Whiteford
H.
,
Wiebe
N.
,
Wiersma
S. T.
,
Wilkinson
J. D.
,
Williams
H. C.
,
Williams
S. R.
,
Witt
E.
,
Wolfe
F.
,
Woolf
A. D.
,
Wulf
S.
,
Yeh
P.-H.
,
Zaidi
A. K.
,
Zheng
Z.-J.
,
Zonies
D.
&
Lopez
A. D.
(
2012
).
Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010
.
The Lancet
380
,
2197
2223
.
https://doi.org/10.1016/S0140-6736(12)61689-4
.
Ntozini
R.
,
Marks
S. J.
,
Mangwadu
G.
,
Mbuya
M. N. N.
,
Gerema
G.
,
Mutasa
B.
,
Julian
T. R.
,
Schwab
K. J.
,
Humphrey
J. H.
&
Zungu
L. I.
for the Sanitation Hygiene Infant Nutrition Efficacy (SHINE) Trial Team
,
Chasekwa
,
B.
,
Helyar
,
W.
,
Phiri
,
S.
,
Garikai
,
A.
,
Meki
,
K.
,
Chimucheka
,
N.
,
Mapuranga
,
A.
,
Hoko-Sibanda
,
N.
&
Chikwavaire
,
V. F.
(
2015
).
Using geographic information systems and spatial analysis methods to assess household water access and sanitation coverage in the SHINE trial
.
Clin. Infect. Dis.
61
,
S716
S725
.
https://doi.org/10.1093/cid/civ847
.
Nurul Huda
T. M.
,
Schmidt
W. -P.
,
Pickering
A. J.
,
Unicomb
L.
,
Mahmud
Z. H.
,
Luby
S. P.
&
Biran
A.
(
2019
).
Effect of neighborhood sanitation coverage on fecal contamination of the household environment in rural Bangladesh
.
Am. J. Trop. Med. Hyg.
100
,
717
726
.
https://doi.org/10.4269/ajtmh.16-0996
.
Öberg
G.
,
Metson
G. S.
,
Kuwayama
Y.
&
Conrad
S. A.
(
2020
).
Conventional sewer systems are too time-consuming, costly and inflexible to meet the challenges of the 21st century
.
Sustainability
12
,
6518
.
https://doi.org/10.3390/su12166518
.
Odjegba
E.
,
Oluwasanya
G.
,
Idowu
O.
,
Shittu
O.
&
Brion
G.
(
2020a
).
Sustainability indices and risk analysis of drinking water systems in Southwest Nigeria
.
J. Water Supply Res. Technol.-Aqua
69
,
591
603
.
https://doi.org/10.2166/aqua.2020.002
.
Odjegba
E.
,
Oluwasanya
G.
,
Sadiq
A.
&
Brion
G.
(
2020b
).
Sustainability and risk assessment matrix (SRAM): pathway to water security
.
Water Supply
20
,
2928
2940
.
https://doi.org/10.2166/ws.2020.196
.
Odjegba
E. E.
,
Bankole
A. O.
,
Layi-Adigun
B. O.
&
Dada
V. O.
(
2021
).
Water, sanitation, and hygiene in healthcare centres: appraisal in a pandemic
.
J. Water Sanit. Hyg. Dev.
11
,
926
936
.
https://doi.org/10.2166/washdev.2021.075
.
Okurut
K.
&
Charles
K. J.
(
2014
).
Household demand for sanitation improvements in low-income informal settlements: a case of east African cities
.
Habitat Int.
44
,
332
338
.
https://doi.org/10.1016/j.habitatint.2014.07.014
.
Olarewaju
O. A.
(
2021
).
Insecurity in northern Nigeria: implications for maternal and child health
.
Clin. Epidemiol. Global Health
12
.
https://doi.org/10.1016/j.cegh.2021.100869
.
Oluwasanya
G.
(
2013
).
Qualitative risk assessment of self-supply hand-dug wells in Abeokuta, Nigeria : a water safety plan approach
.
Int. J. Water Sanit. Waste Waterlines
32
,
36
49
.
https://doi.org/10.3362/1756-3488.2013.004
.
Oluwasanya
G.
,
Sadiq
A.
&
Odjegba
E.
(
2016
).
Inventory and sanitary status of self water supply systems in Abeokuta, Nigeria
.
Niger. J. Hydrol. Sci.
4
,
215
236
.
Oswald
W. E.
,
Stewart
A. E. P.
,
Flanders
W. D.
,
Kramer
M. R.
,
Endeshaw
T.
,
Zerihun
M.
,
Melaku
B.
,
Sata
E.
,
Gessesse
D.
,
Teferi
T.
,
Tadesse
Z.
,
Guadie
B.
,
King
J. D.
,
Emerson
P. M.
,
Callahan
E. K.
,
Moe
C. L.
&
Clasen
T. F.
(
2016
).
Prediction of low community sanitation coverage using environmental and sociodemographic factors in Amhara Region, Ethiopia
.
Am. J. Trop. Med. Hyg.
95
,
709
719
.
https://doi.org/10.4269/ajtmh.15-0895
.
Oumar
S. B.
&
Tewari
D. D.
(
2013
).
The evolution of access to drinking water and sanitation coverage in urban centers of selected African countries
.
Mediterr. J. Soc. Sci.
4
,
747
762
.
https://doi.org/10.5901/mjss.2013.v4n6p747
.
Painelsaneamento
(
2020
).
Brazil Sanitation Panel [WWW Document]
. .
Park
C. J.
,
Barakat
R.
,
Ulanov
A.
,
Li
Z.
,
Lin
P. -C.
,
Chiu
K.
,
Zhou
S.
,
Perez
P.
,
Lee
J.
,
Flaws
J.
&
Ko
C. J.
(
2019
).
Sanitary pads and diapers contain higher phthalate contents than those in common commercial plastic products
.
Reprod. Toxicol.
84
,
114
121
.
https://doi.org/10.1016/j.reprotox.2019.01.005
.
Peletz
R.
,
Delaire
C.
,
Kones
J.
,
Macleod
C.
,
Samuel
E.
,
Easthope-Frazer
A.
&
Khush
R.
(
2021
).
Will households invest in safe sanitation? Results from an experimental demand trial in Nakuru, Kenya
.
Int. J. Environ. Res. Public. Health
18
.
https://doi.org/10.3390/ijerph18094462
.
Pham
D. N.
,
Clark
L.
&
Li
M.
(
2021
).
Microplastics as hubs enriching antibiotic-resistant bacteria and pathogens in municipal activated sludge
.
J. Hazard. Mater. Lett.
2
,
100014
.
https://doi.org/10.1016/j.hazl.2021.100014
.
PLANSAB
(
2019
).
Plano Nacional de Saneamento Básico
.
Ministério do Desenvolvimento Regional
,
Brasila
.
Routray
P.
,
Schmidt
W. -P.
,
Boisson
S.
,
Clasen
T.
&
Jenkins
M. W.
(
2015
).
Socio-cultural and behavioural factors constraining latrine adoption in rural coastal Odisha: an exploratory qualitative study
.
BMC Public Health
15
,
880
.
https://doi.org/10.1186/s12889-015-2206-3
.
Rwanda Ministry of Infrastructure
(
2010
).
National Policy & Strategy for Water Supply and Sanitation Services
.
Rwanda
.
Sachs
D. J.
,
Lafortune
G.
,
Kroll
C.
,
Fuller
G.
&
Woelm
F.
(
2022
).
Sustainable Development Report
.
Cambridge University press
,
Cambridge
,
UK
.
Salami
A. O.
,
Stampini
M.
,
Kamara
A. B.
,
Sullivan
C. A.
&
Namara
R.
(
2014
).
Development aid and access to water and sanitation in Sub-Saharan Africa
.
Water Int.
39
,
294
314
.
https://doi.org/10.1080/02508060.2013.876570
.
Spuhler
D.
,
Germann
V.
,
Kassa
K.
,
Ketema
A. A.
,
Sherpa
A. M.
,
Sherpa
M. G.
,
Maurer
M.
,
Lüthi
C.
&
Langergraber
G.
(
2020
).
Developing sanitation planning options: a tool for systematic consideration of novel technologies and systems
.
J. Environ. Manage.
271
,
111004
.
https://doi.org/10.1016/j.jenvman.2020.111004
.
Syromyatnikov
D. A.
,
Pyatkina
D. A.
,
Kondratenko
L. N.
,
Krivolapov
S. I.
&
Stepanova
D. I.
(
2019
).
Big data analysis for studying water supply and sanitation coverage in cities (Russia)
.
Espacios
40
(
27
),
21
35
.
Tsinda
A.
,
Abbott
P.
&
Chenoweth
J.
(
2015
).
Sanitation markets in urban informal settlements of East Africa
.
Habitat Int.
49
,
21
29
.
https://doi.org/10.1016/j.habitatint.2015.05.005
.
Tumwebaze
I. K.
,
Orach
C. G.
,
Nakayaga
J. K.
,
Karamagi
C.
,
Luethi
C.
&
Niwagaba
C.
(
2011
).
Ecological sanitation coverage and factors affecting its uptake in Kabale municipality, western Uganda
.
Int. J. Environ. Health Res.
21
,
294
305
.
https://doi.org/10.1080/09603123.2010.550036
.
Tyndall
J. A.
,
Ndiaye
K.
,
Weli
C.
,
Dejene
E.
,
Ume
N.
,
Inyang
V.
,
Okere
C.
,
Sandberg
J.
&
Waldman
R. J.
(
2020
).
The relationship between armed conflict and reproductive, maternal, newborn and child health and nutrition status and services in northeastern Nigeria: a mixed-methods case study
.
Confl. Health
14
,
75
.
https://doi.org/10.1186/s13031-020-00318-5
.
UN-Global Analysis and Assessment of Sanitation and Drinking-Water
(
2014
).
Sanitation, Drinking-Water and Hygiene Status Overview (GLASS)
.
Geneva
.
UNICEF
(
2013
).
Levels & Trends in Child Mortality. Report
.
UNICEF
(
2020
).
10 Facts About Sanitation in Nigeria [WWW Document]
.
Borgen Proj
.
Available at: https://borgenproject.org/facts-about-sanitation-in-nigeria/ (accessed 16 August 2021)
.
United Nations Children's Fund
(
2019
).
Global Framework for Urban Water, Sanitation and Hygiene
.
UNICEF
,
New York
.
Vos
T.
,
Barber
R. M.
,
Bell
B.
,
Bertozzi-Villa
A.
,
Biryukov
S.
,
Bolliger
I.
,
Charlson
F.
,
Davis
A.
,
Degenhardt
L.
,
Dicker
D.
,
Duan
L.
,
Erskine
H.
,
Feigin
V. L.
,
Ferrari
A. J.
,
Fitzmaurice
C.
,
Fleming
T.
,
Graetz
N.
,
Guinovart
C.
,
Haagsma
J.
,
Hansen
G. M.
,
Hanson
S. W.
,
Heuton
K. R.
,
Higashi
H.
,
Kassebaum
N.
,
Kyu
H.
,
Laurie
E.
,
Liang
X.
,
Lofgren
K.
,
Lozano
R.
,
MacIntyre
M. F.
,
Moradi-Lakeh
M.
,
Naghavi
M.
,
Nguyen
G.
,
Odell
S.
,
Ortblad
K.
,
Roberts
D. A.
,
Roth
G. A.
,
Sandar
L.
,
Serina
P. T.
,
Stanaway
J. D.
,
Steiner
C.
,
Thomas
B.
,
Vollset
S. E.
,
Whiteford
H.
,
Wolock
T. M.
,
Ye
P.
,
Zhou
M.
,
Ãvila
M. A.
,
Aasvang
G. M.
,
Abbafati
C.
,
Ozgoren
A. A.
,
Abd-Allah
F.
,
Aziz
M. I. A.
,
Abera
S. F.
,
Aboyans
V.
,
Abraham
J. P.
,
Abraham
B.
,
Abubakar
I.
,
Abu-Raddad
L. J.
,
Abu-Rmeileh
N. M. E.
,
Aburto
T. C.
,
Achoki
T.
,
Ackerman
I. N.
,
Adelekan
A.
,
Ademi
Z.
,
Adou
A. K.
,
Adsuar
J. C.
,
Arnlov
J.
,
Agardh
E. E.
,
Al Khabouri
M. J.
,
Alam
S. S.
,
Alasfoor
D.
,
Albittar
M. I.
,
Alegretti
M. A.
,
Aleman
A. V.
,
Alemu
Z. A.
,
Alfonso-Cristancho
R.
,
Alhabib
S.
,
Ali
R.
,
Alla
F.
,
Allebeck
P.
,
Allen
P. J.
,
AlMazroa
M. A.
,
Alsharif
U.
,
Alvarez
E.
,
Alvis-Guzman
N.
,
Ameli
O.
,
Amini
H.
,
Ammar
W.
,
Anderson
B. O.
,
Anderson
H. R.
,
Antonio
C. A. T.
,
Anwari
P.
,
Apfel
H.
,
Arsenijevic
V. S. A.
,
Artaman
A.
,
Asghar
R. J.
,
Assadi
R.
,
Atkins
L. S.
,
Atkinson
C.
,
Badawi
A.
,
Bahit
M. C.
,
Bakfalouni
T.
,
Balakrishnan
K.
,
Balalla
S.
,
Banerjee
A.
,
Barker-Collo
S. L.
,
Barquera
S.
,
Barregard
L.
,
Barrero
L. H.
,
Basu
S.
,
Basu
A.
,
Baxter
A.
,
Beardsley
J.
,
Bedi
N.
,
Beghi
E.
,
Bekele
T.
,
Bell
M. L.
,
Benjet
C.
,
Bennett
D. A.
,
Bensenor
I. M.
,
Benzian
H.
,
Bernabe
E.
,
Beyene
T. J.
,
Bhala
N.
,
Bhalla
A.
,
Bhutta
Z.
,
Bienhoff
K.
,
Bikbov
B.
,
Abdulhak
A. B.
,
Blore
J. D.
,
Blyth
F. M.
,
Bohensky
M. A.
,
Basara
B. B.
,
Borges
G.
,
Bornstein
N. M.
,
Bose
D.
,
Boufous
S.
,
Bourne
R. R.
,
Boyers
L. N.
,
Brainin
M.
,
Brauer
M.
,
Brayne
C. E. G.
,
Brazinova
A.
,
Breitborde
N. J. K.
,
Brenner
H.
,
Briggs
A. D. M.
,
Brooks
P. M.
,
Brown
J.
,
Brugha
T. S.
,
Buchbinder
R.
,
Buckle
G. C.
,
Bukhman
G.
,
Bulloch
A. G.
,
Burch
M.
,
Burnett
R.
,
Cardenas
R.
,
Cabral
N. L.
,
Campos-Nonato
I. R.
,
Campuzano
J. C.
,
Carapetis
J. R.
,
Carpenter
D. O.
,
Caso
V.
,
Castaneda-Orjuela
C. A.
,
Catala-Lopez
F.
,
Chadha
V. K.
,
Chang
J.-C.
,
Chen
H.
,
Chen
W.
,
Chiang
P. P.
,
Chimed-Ochir
O.
,
Chowdhury
R.
,
Christensen
H.
,
Christophi
C. A.
,
Chugh
S. S.
,
Cirillo
M.
,
Coggeshall
M.
,
Cohen
A.
,
Colistro
V.
,
Colquhoun
S. M.
,
Contreras
A. G.
,
Cooper
L. T.
,
Cooper
C.
,
Cooperrider
K.
,
Coresh
J.
,
Cortinovis
M.
,
Criqui
M. H.
,
Crump
J. A.
,
Cuevas-Nasu
L.
,
Dandona
R.
,
Dandona
L.
,
Dansereau
E.
,
Dantes
H. G.
,
Dargan
P. I.
,
Davey
G.
,
Davitoiu
D. V.
,
Dayama
A.
,
De La Cruz-Gongora
V.
,
De La Vega
S. F.
,
De Leo
D.
,
Del Pozo-Cruz
B.
,
Dellavalle
R. P.
,
Deribe
K.
,
Derrett
S.
,
Des Jarlais
D. C.
,
Dessalegn
M.
,
DeVeber
G. A.
,
Dharmaratne
S. D.
,
Diaz-Torne
C.
,
Ding
E. L.
,
Dokova
K.
,
Dorsey
E. R.
,
Driscoll
T. R.
,
Duber
H.
,
Durrani
A. M.
,
Edmond
K. M.
,
Ellenbogen
R. G.
,
Endres
M.
,
Ermakov
S. P.
,
Eshrati
B.
,
Esteghamati
A.
,
Estep
K.
,
Fahimi
S.
,
Farzadfar
F.
,
Fay
D. F. J.
,
Felson
D. T.
,
Fereshtehnejad
S.-M.
,
Fernandes
J. G.
,
Ferri
C. P.
,
Flaxman
A.
,
Foigt
N.
,
Foreman
K. J.
,
Fowkes
F. G. R.
,
Franklin
R. C.
,
Furst
T.
,
Futran
N. D.
,
Gabbe
B. J.
,
Gankpe
F. G.
,
Garcia-Guerra
F. A.
,
Geleijnse
J. M.
,
Gessner
B. D.
,
Gibney
K. B.
,
Gillum
R. F.
,
Ginawi
I. A.
,
Giroud
M.
,
Giussani
G.
,
Goenka
S.
,
Goginashvili
K.
,
Gona
P.
,
De Cosio
T. G.
,
Gosselin
R. A.
,
Gotay
C. C.
,
Goto
A.
,
Gouda
H. N.
,
Guerrant
R. L.
,
Gugnani
H. C.
,
Gunnell
D.
,
Gupta
R.
,
Gupta
R.
,
Gutierrez
R. A.
,
Hafezi-Nejad
N.
,
Hagan
H.
,
Halasa
Y.
,
Hamadeh
R. R.
,
Hamavid
H.
,
Hammami
M.
,
Hankey
G. J.
,
Hao
Y.
,
Harb
H. L.
,
Haro
J. M.
,
Havmoeller
R.
,
Hay
R. J.
,
Hay
S.
,
Hedayati
M. T.
,
Pi
I. B. H.
,
Heydarpour
P.
,
Hijar
M.
,
Hoek
H. W.
,
Hoffman
H. J.
,
Hornberger
J. C.
,
Hosgood
H. D.
,
Hossain
M.
,
Hotez
P. J.
,
Hoy
D. G.
,
Hsairi
M.
,
Hu
H.
,
Hu
G.
,
Huang
J. J.
,
Huang
C.
,
Huiart
L.
,
Husseini
A.
,
Iannarone
M.
,
Iburg
K. M.
,
Innos
K.
,
Inoue
M.
,
Jacobsen
K. H.
,
Jassal
S. K.
,
Jeemon
P.
,
Jensen
P. N.
,
Jha
V.
,
Jiang
G.
,
Jiang
Y.
,
Jonas
J. B.
,
Joseph
J.
,
Juel
K.
,
Kan
H.
,
Karch
A.
,
Karimkhani
C.
,
Karthikeyan
G.
,
Katz
R.
,
Kaul
A.
,
Kawakami
N.
,
Kazi
D. S.
,
Kemp
A. H.
,
Kengne
A. P.
,
Khader
Y. S.
,
Khalifa
S. E. A. H.
,
Khan
E. A.
,
Khan
G.
,
Khang
Y.-H.
,
Khonelidze
I.
,
Kieling
C.
,
Kim
D.
,
Kimokoti
R.W.
,
Kinfu
Y.
,
Kinge
J. M.
,
Kissela
B. M.
,
Kivipelto
M.
,
Knibbs
L.
,
Knudsen
A. K.
,
Kokubo
Y.
,
Kosen
S.
,
Kramer
A.
,
Kravchenko
M.
,
Krishnamurthi
R. V.
,
Krishnaswami
S.
,
Defo
B. K.
,
Bicer
B. K.
,
Kuipers
E. J.
,
Kulkarni
V. S.
,
Kumar
K.
,
Kumar
G. A.
,
Kwan
G. F.
,
Lai
T.
,
Lalloo
R.
,
Lam
H.
,
Lan
Q.
,
Lansingh
V. C.
,
Larson
H.
,
Larsson
A.
,
Lawrynowicz
A. E. B.
,
Leasher
J. L.
,
Lee
J.-T.
,
Leigh
J.
,
Leung
R.
,
Levi
M.
,
Li
B.
,
Li
Y.
,
Li
Y.
,
Liang
J.
,
Lim
S.
,
Lin
H.-H.
,
Lind
M.
,
Lindsay
M. P.
,
Lipshultz
S. E.
,
Liu
S.
,
Lloyd
B. K.
,
Ohno
S. L.
,
Logroscino
G.
,
Looker
K. J.
,
Lopez
A. D.
,
Lopez-Olmedo
N.
,
Lortet-Tieulent
J.
,
Lotufo
P. A.
,
Low
N.
,
Lucas
R. M.
,
Lunevicius
R.
,
Lyons
R. A.
,
Ma
J.
,
Ma
S.
,
MacKay
M. T.
,
Majdan
M.
,
Malekzadeh
R.
,
Mapoma
C. C.
,
Marcenes
W.
,
March
L. M.
,
Margono
C.
,
Marks
G. B.
,
Marzan
M. B.
,
Masci
J. R.
,
Mason-Jones
A. J.
,
Matzopoulos
R. G.
,
Mayosi
B. M.
,
Mazorodze
T. T.
,
McGill
N. W.
,
McGrath
J. J.
,
McKee
M.
,
McLain
A.
,
McMahon
B. J.
,
Meaney
P. A.
,
Mehndiratta
M. M.
,
Mejia-Rodriguez
F.
,
Mekonnen
W.
,
Melaku
Y. A.
,
Meltzer
M.
,
Memish
Z. A.
,
Mensah
G.
,
Meretoja
A.
,
Mhimbira
F. A.
,
Micha
R.
,
Miller
T. R.
,
Mills
E. J.
,
Mitchell
P. B.
,
Mock
C. N.
,
Moffitt
T. E.
,
Ibrahim
N. M.
,
Mohammad
K. A.
,
Mokdad
A. H.
,
Mola
G. L.
,
Monasta
L.
,
Montico
M.
,
Montine
T. J.
,
Moore
A. R.
,
Moran
A. E.
,
Morawska
L.
,
Mori
R.
,
Moschandreas
J.
,
Moturi
W. N.
,
Moyer
M.
,
Mozaffarian
D.
,
Mueller
U. O.
,
Mukaigawara
M.
,
Murdoch
M. E.
,
Murray
J.
,
Murthy
K. S.
,
Naghavi
P.
,
Nahas
Z.
,
Naheed
A.
,
Naidoo
K. S.
,
Naldi
L.
,
Nand
D.
,
Nangia
V.
,
Narayan
K. M. V.
,
Nash
D.
,
Nejjari
C.
,
Neupane
S. P.
,
Newman
L. M.
,
Newton
C. R.
,
Ng
M.
,
Ngalesoni
F. N.
,
Nhung
N. T.
,
Nisar
M. I.
,
Nolte
S.
,
Norheim
O. F.
,
Norman
R. E.
,
Norrving
B.
,
Nyakarahuka
L.
,
Oh
I. H.
,
Ohkubo
T.
,
Omer
S. B.
,
Opio
J. N.
,
Ortiz
A.
,
Pandian
J. D.
,
Panelo
C. I. A.
,
Papachristou
C.
,
Park
E.-K.
,
Parry
C. D.
,
Caicedo
A. J. P.
,
Patten
S. B.
,
Paul
V. K.
,
Pavlin
B. I.
,
Pearce
N.
,
Pedraza
L. S.
,
Pellegrini
C. A.
,
Pereira
D. M.
,
Perez-Ruiz
F. P.
,
Perico
N.
,
Pervaiz
A.
,
Pesudovs
K.
,
Peterson
C. B.
,
Petzold
M.
,
Phillips
M. R.
,
Phillips
D.
,
Phillips
B.
,
Piel
F. B.
,
Plass
D.
,
Poenaru
D.
,
Polanczyk
G. V.
,
Polinder
S.
,
Pope
C. A.
,
Popova
S.
,
Poulton
R. G.
,
Pourmalek
F.
,
Prabhakaran
D.
,
Prasad
N. M.
,
Qato
D.
,
Quistberg
D. A.
,
Rafay
A.
,
Rahimi
K.
,
Rahimi-Movaghar
V.
,
Rahman
S. U.
,
Raju
M.
,
Rakovac
I.
,
Rana
S. M.
,
Razavi
H.
,
Refaat
A.
,
Rehm
J.
,
Remuzzi
G.
,
Resnikoff
S.
,
Ribeiro
A. L.
,
Riccio
P. M.
,
Richardson
L.
,
Richardus
J. H.
,
Riederer
A. M.
,
Robinson
M.
,
Roca
A.
,
Rodriguez
A.
,
Rojas-Rueda
D.
,
Ronfani
L.
,
Rothenbacher
D.
,
Roy
N.
,
Ruhago
G. M.
,
Sabin
N.
,
Sacco
R. L.
,
Ksoreide
K.
,
Saha
S.
,
Sahathevan
R.
,
Sahraian
M. A.
,
Sampson
U.
,
Sanabria
J. R.
,
Sanchez-Riera
L.
,
Santos
I. S.
,
Satpathy
M.
,
Saunders
J. E.
,
Sawhney
M.
,
Saylan
M. I.
,
Scarborough
P.
,
Schoettker
B.
,
Schneider
I. J. C.
,
Schwebel
D. C.
,
Scott
J. G.
,
Seedat
S.
,
Sepanlou
S. G.
,
Serdar
B.
,
Servan-Mori
E. E.
,
Shackelford
K.
,
Shaheen
A.
,
Shahraz
S.
,
Levy
T. S.
,
Shangguan
S.
,
She
J.
,
Sheikhbahaei
S.
,
Shepard
D. S.
,
Shi
P.
,
Shibuya
K.
,
Shinohara
Y.
,
Shiri
R.
,
Shishani
K.
,
Shiue
I.
,
Shrime
M. G.
,
Sigfusdottir
I. D.
,
Silberberg
D. H.
,
Simard
E. P.
,
Sindi
S.
,
Singh
J. A.
,
Singh
L.
,
Skirbekk
V.
,
Sliwa
K.
,
Soljak
M.
,
Soneji
S.
,
Soshnikov
S. S.
,
Speyer
P.
,
Sposato
L. A.
,
Sreeramareddy
C. T.
,
Stoeckl
H.
,
Stathopoulou
V. K.
,
Steckling
N.
,
Stein
M. B.
,
Stein
D. J.
,
Steiner
T. J.
,
Stewart
A.
,
Stork
E.
,
Stovner
L. J.
,
Stroumpoulis
K.
,
Sturua
L.
,
Sunguya
B. F.
,
Swaroop
M.
,
Sykes
B. L.
,
Tabb
K. M.
,
Takahashi
K.
,
Tan
F.
,
Tandon
N.
,
Tanne
D.
,
Tanner
M.
,
Tavakkoli
M.
,
Taylor
H. R.
,
Te Ao
B. J.
,
Temesgen
A. M.
,
Have
M. T.
,
Tenkorang
E. Y.
,
Terkawi
A. S.
,
Theadom
A. M.
,
Thomas
E.
,
Thorne-Lyman
A. L.
,
Thrift
A. G.
,
Tleyjeh
I. M.
,
Tonelli
M.
,
Topouzis
F.
,
Towbin
J. A.
,
Toyoshima
H.
,
Traebert
J.
,
Tran
B. X.
,
Trasande
L.
,
Trillini
M.
,
Truelsen
T.
,
Trujillo
U.
,
Tsilimbaris
M.
,
Tuzcu
E. M.
,
Ukwaja
K. N.
,
Undurraga
E. A.
,
Uzun
S. B.
,
Van Brakel
W. H.
,
Van De Vijver
S.
,
Dingenen
R. V.
,
Van Gool
C. H.
,
Varakin
Y. Y.
,
Vasankari
T. J.
,
Vavilala
M. S.
,
Veerman
L. J.
,
Velasquez-Melendez
G.
,
Venketasubramanian
N.
,
Vijayakumar
L.
,
Villalpando
S.
,
Violante
F. S.
,
Vlassov
V. V.
,
Waller
S.
,
Wallin
M. T.
,
Wan
X.
,
Wang
L.
,
Wang
J.
,
Wang
Y.
,
Warouw
T. S.
,
Weichenthal
S.
,
Weiderpass
E.
,
Weintraub
R. G.
,
Werdecker
A.
,
Wessells
K. R.
,
Westerman
R.
,
Wilkinson
J. D.
,
Williams
H. C.
,
Williams
T. N.
,
Woldeyohannes
S. M.
,
Wolfe
C. D. A.
,
Wong
J. Q.
,
Wong
H.
,
Woolf
A. D.
,
Wright
J. L.
,
Wurtz
B.
,
Xu
G.
,
Yang
G.
,
Yano
Y.
,
Yenesew
M. A.
,
Yentur
G. K.
,
Yip
P.
,
Yonemoto
N.
,
Yoon
S.-J.
,
Younis
M.
,
Yu
C.
,
Kim
K. Y.
,
Zaki
M. E. S.
,
Zhang
Y.
,
Zhao
Z.
,
Zhao
Y.
,
Zhu
J.
,
Zonies
D.
,
Zunt
J. R.
,
Salomon
J. A.
&
Murray
C. J. L.
(
2015
).
Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013
.
The Lancet
386
,
743
800
.
https://doi.org/10.1016/S0140-6736(15)60692-4
.
Water and Sanitation Program
(
2012
).
Economic Impacts of Poor Sanitation in Africa
.
Nigeria
.
WaterAid
(
2016
).
Nigeria's Sanitation Crisis: 2016 World Toilet Day Nigeria Supplement
.
Watkins
K.
(
2006
).
Human Development Report 2006 - Beyond Scarcity: Power, Poverty and the Global Water Crisis (SSRN Scholarly Paper No. ID 2294691)
.
Social Science Research Network
,
Rochester, NY
.
Wee
S. Y.
&
Aris
A. Z.
(
2017
).
Endocrine disrupting compounds in drinking water supply system and human health risk implication
.
Environ. Int.
106
,
207
233
.
http://dx.doi.org/10.1016/j.envint.2017.05.004
.
WHO/UNICEF
. (
2014
).
Progress on Drinking-Water and Sanitation – 2014 Update
.
WHO/UNICEF
,
Geneva
.
Wolf
J.
,
Prüss-Ustün
A.
,
Cumming
O.
,
Bartram
J.
,
Bonjour
S.
,
Cairncross
S.
,
Clasen
T.
,
Colford
J. M.
,
Curtis
V.
,
France
J. D.
,
Fewtrell
L.
,
Freeman
M. C.
,
Gordon
B.
,
Hunter
P. R.
,
Jeandron
A.
,
Johnston
R. B.
,
Mäusezahl
D.
,
Mathers
C.
,
Neira
M.
&
Higgins
J. P. T.
(
2014
).
Systematic review: assessing the impact of drinking water and sanitation on diarrhoeal disease in low- and middle-income settings: systematic review and meta-regression
.
Trop. Med. Int. Health
19
,
928
942
.
https://doi.org/10.1111/tmi.12331
.
World Bank
(
2021
).
Nigeria: Ensuring Water, Sanitation and Hygiene for All [WWW Document]
.
World Bank
. .
World Health Organization
(
2018
).
Guidelines on Sanitation and Health
.
World Health Organization
,
Geneva
.
WSSCC
(
2020
).
Nigeria's Accountant-General Pledges Improved Funding for the WASH Sector – Nigeria [WWW Document]
. .
Zerbo
A.
,
Castro Delgado
R.
&
Arcos González
P.
(
2021
).
Water sanitation and hygiene in Sub-Saharan Africa: coverage, risks of diarrheal diseases, and urbanization
.
J. Biosaf. Biosecur.
3
,
41
45
.
https://doi.org/10.1016/j.jobb.2021.03.004
.
Zhang
J.
,
Wang
L.
,
Trasande
L.
&
Kannan
K.
(
2021
).
Occurrence of polyethylene terephthalate and polycarbonate microplastics in infant and adult feces
.
Environ. Sci. Technol. Lett.
8
,
989
994
.
https://doi.org/10.1021/acs.estlett.1c00559
.
Zheng
Y.
,
Hakim
S. A. I.
,
Nahar
Q.
,
van Agthoven
A.
&
Flanagan
S. V.
(
2013
).
Sanitation coverage in Bangladesh since the millennium: consistency matters
.
J. Water Sanit. Hyg. Dev.
3
,
240
251
.
https://doi.org/10.2166/washdev.2013.154
.
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