Seasonality of drinking water sources and the impact of drinking water source on enteric infections among children in Limpopo, South Africa

Nguyen, Kathy; Operario, Darwin J.; Nyathi, Mzwakhe E.; Hill, Courtney L.; Smith, James A.; Guerrant, Richard L.; Samie, Amidou; Dillingham, Rebecca; Bessong, Pascal; McQuade, Elizabeth T Rogawski

doi:10.1016/j.ijheh.2020.113640

Cited by 27 publications

(17 citation statements)

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“…We attempted to control for seasonality using a simplified definition of wet and dry seasons (Wright et al 2012). Our finding that the wet season was associated with any E. coli contamination at the PoU in the fully adjusted models supports the findings of a systematic review (Kostyla et al 2015) and more recent studies examining seasonality (Kumpel et al 2017;Nguyen et al 2021) or the impact of rainfall on water quality (Kirby et al 2016). Integration of water quality testing in largescale longitudinal surveys may offer insights into the dynamics of water quality at a national scale.…”

Section: Discussionsupporting

confidence: 67%

See 1 more Smart Citation

Monitoring Drinking Water Quality in Nationally Representative Household Surveys in Low- and Middle-Income Countries: Cross-Sectional Analysis of 27 Multiple Indicator Cluster Surveys 2014–2020

Bain

Johnston

Khan

et al. 2021

Environ Health Perspect

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Background: The 2030 Sustainable Development Goals (SDGs) set an ambitious new benchmark for safely managed drinking water services (SMDWs), but many countries lack national data on the availability and quality of drinking water. Objectives: We quantified the availability and microbiological quality of drinking water, monitored SMDWs, and examined risk factors for Escherichia coli ( E. coli ) contamination in 27 low-and middle-income countries (LMICs). Methods: A new water quality module for household surveys was implemented in 27 Multiple Indicator Cluster Surveys. Teams used portable equipment to measure E. coli at the point of collection (PoC, ) and at the point of use (PoU, ) and asked respondents about the availability and accessibility of drinking water. Households were classified as having SMDW services if they used an improved water source that was free of E. coli contamination at PoC, accessible on premises, and available when needed. Compliance with individual SMDW criteria was also assessed. Modified Poisson regression was used to explore household and community risk factors for E. coli contamination. Results: E. coli was commonly detected at the PoC (range 16–90%) and was more likely at the PoU (range 19–99%). On average, 84% of households used an improved drinking water source, and 31% met all of the SMDW criteria. E. coli contamination was the primary reason SMDW criteria were not met (15 of 27 countries). The prevalence of E. coli in PoC samples was lower among households using improved water sources [ ; 95% confidence interval (CI): 0.64, 0.85] but not for households with water accessible on premises ( ; 95% CI: 0.94, 1.05) or available when needed ( ; 95% CI: 0.88, 1.02). E. coli contamination of PoU samples was less common for households in the richest vs. poorest wealth quintile ( ; 95% CI: 0.55, 0.88) and in communities with high ( ) improved sanitation coverage ( ; 95% CI: 0.90, 0.97). Livestock ownership ( ; 95% CI: 1.04, 1.13), rural vs. urban residence ( ; 95% CI: 1.04, 1.16), and wet vs. dry season sampling ( ; 95% CI: 1.01, 1.15) were positively associated with contamination at the PoU. Discussion: Cross-sectional water quality data can be collected in household surveys and can be used to assess inequalities in service levels, to track the SDG indicator of SMDWs, and to examine risk factors for contamination. There is an urgent need for better risk management to reduce widespread exposure to fecal contamination through drinking water services in LMICs. ...

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Section: Discussionsupporting

confidence: 67%

“…2015 ) and more recent studies examining seasonality ( Kumpel et al. 2017 ; Nguyen et al. 2021 ) or the impact of rainfall on water quality ( Kirby et al.…”

Section: Discussionmentioning

confidence: 99%

Monitoring Drinking Water Quality in Nationally Representative Household Surveys in Low- and Middle-Income Countries: Cross-Sectional Analysis of 27 Multiple Indicator Cluster Surveys 2014–2020

Bain

Johnston

Khan

et al. 2021

Environ Health Perspect

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“…This is similar to the findings from a study conducted at Port Harcourt where less than 1% had access to public water supply [26]. This contrasts with significantly high proportions of households in studies conducted in Tanzania and South Africa which rely on public water supply [30,31]. The differences observed in the systems of water supply could be due to variations in the study area with different water policies and varying degrees of implementation of the policies.…”

Section: Discussionsupporting

confidence: 79%

The effects of seasonal variations on household water security and burden of diarrheal diseases among under 5 children in an urban community, Southwest Nigeria

2022

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Background Household water security encompasses water-related factors that pose threats to public health at the household level. It presents a reliable access to water in sufficient quantity and quality towards meeting basic human needs. This study assessed the dynamics of seasonal variations in household water security and the association between household water security and diarrheal disease across dry and wet seasons in an urban settlement in Southwest Nigeria. Methods A panel study design was employed to study 180 households selected using a multistage sampling technique. The selected households were studied during dry and rainy seasons. Household water security was assessed through the application of the all or none principle to 9 indicators associated with household water security. The intensity of water insecurity was also assessed using the nine indicators. The higher the number of indicators a household failed, the higher the intensity of household water insecurity. The association between the intensity of household water insecurity and the burden of diarrheal disease across the seasons was assessed using the Mantel-Haenszel test. Results No household was water-secure in both dry and rainy seasons; however, the intensity of insecurity was more pronounced during the dry season compared with the rainy season. Ninety households (52.0%), had water insecurity intensity scores above fifty percentiles during the dry season while 21 (12.1%) households had a water insecurity score above the 50th percentile during raining season, p < 0.001. The burden of diarrheal disease was significantly higher among households with a water insecurity intensity score above the 50th percentile, 9 (8.1%) compared to households with a water insecurity intensity score below the 50th percentile 7 (3.0%), p = 0.034. There was no statistically significant association between the intensity of water insecurity and diarrheal disease burden across the dry and rainy seasons, p = 0.218. Conclusion The high burden of household water insecurity deserves concerted efforts from all concerned stakeholders, a panacea to an important health threat in the developing world.

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“…For example, studies revealed that seasonal flooding broke water pumps, inundated wells, and damaged both water storage and water treatment systems (Kelly et al, 2018; Kujinga et al, 2014). Seasonality also negatively affected municipal water supplies' intermittency and reliability (Mason, 2015; Molden et al, 2016; Nguyen et al, 2021; Nnaji et al, 2013). Wells ran dry during dry cycles (Makame & Kangalawe, 2018; Malley et al, 2009; Uzomah & Scholz, 2002) and also collapsed on themselves in the rainy season (Uzomah & Scholz, 2002).…”

Section: Discussionmentioning

confidence: 99%

Climate and hydrological seasonal effects on household water insecurity: A systematic review

et al. 2022

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Household water insecurity (HWI) can have far‐reaching consequences for human health and well‐being, yet little is known about how environmental seasonality contributes to HWI variation. Using a systematic literature review, we examined the following questions: (1) How does environmental seasonality affect HWI? and (2) How do the effects vary over time? We also highlighted strategic areas for future research. We conducted the search using Scopus, Web of Science, PubMed, ProQuest, and EBSCO Academic Search Complete, with an end search date of February 3, 2021; only English‐language studies were included. Articles were included in the review if analysis studied seasonal temperature, precipitation, or freshwater variation and individual or household experiences with household water adequacy, water reliability, water affordability, or water safety. Bias was evaluated via hand assessment, and articles of poor quality were excluded. Studies that focused on extreme weather events or water insecurity at community or watershed levels were omitted. We identified 67 articles, the majority of which were cross‐sectional (n = 46, 68.7%). Among longitudinal studies (n = 21, 31.3%), only one used a quantitative HWI scale, while the rest relied on proxies (n = 20, 95.2%). Our review also revealed literature gaps related to unequal coverage of freshwater ecosystem habitat types and forms of environmental seasonality. There is a need for more attention to extreme climate events, such as a prolonged multiyear drought. With changing climate expected to exacerbate weather patterns with serious implications, especially for vulnerable populations, understanding seasonality in HWI is important for crafting sustainable engineering and policy responses to water insecurity. This article is categorized under: Water and Life > Nature of Freshwater Ecosystems Science of Water > Water and Environmental Change Engineering Water > Sustainable Engineering of Water

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Seasonality of drinking water sources and the impact of drinking water source on enteric infections among children in Limpopo, South Africa

Cited by 27 publications

References 35 publications

Monitoring Drinking Water Quality in Nationally Representative Household Surveys in Low- and Middle-Income Countries: Cross-Sectional Analysis of 27 Multiple Indicator Cluster Surveys 2014–2020

Monitoring Drinking Water Quality in Nationally Representative Household Surveys in Low- and Middle-Income Countries: Cross-Sectional Analysis of 27 Multiple Indicator Cluster Surveys 2014–2020

The effects of seasonal variations on household water security and burden of diarrheal diseases among under 5 children in an urban community, Southwest Nigeria

Climate and hydrological seasonal effects on household water insecurity: A systematic review

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