Applying a WASH Risk Assessment Tool in a Rural South African Setting to Identify Risks and Opportunities for Climate Resilient Communities
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Study Design
2.3. Patient Data
2.4. Risk Assessment Approach
2.4.1. Hazard Scoring
2.4.2. Exposure Scoring
2.4.3. Vulnerability Scoring
2.4.4. Risk Summary
3. Results and Discussion
3.1. Hazards/Threats Classification
3.2. Exposure Scoring
3.3. Vulnerability Scoring
3.4. Study limitations
4. Managerial Insights
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Bacterial Pathogen | Source of Exposure | Symptoms/Diseases | WASH Description |
---|---|---|---|
Burkholderia Cepacia | Hygiene | Lung infections | The germs spread either by direct contact, such as kissing, or indirectly from touching objects on which germs were situated, such as doorknobs. This is known as cross-infection and can happen in social settings such as events, gatherings, or meetings. |
Enterococcus Faecalis | Hygiene | UTIs, prostatitis, intra-abdominal infection, cellulitis, wound infection | A strong association between hand hygiene method and bacterial contamination of hands has been found |
Enterococcus Faecium | Hygiene | UTIs | A strong association between hand hygiene method and bacterial contamination of hands has been found |
Enteropathogenic Escherichia Coli (EPEC) | Water, food, hygiene | diarrhea | In general, strategies for the prevention and control of the spread of EPEC should include access to safe water, good handling practices to reduce the risk of food contamination, sanitation measures, public education, and vaccination |
Non-specific pathogenic Escherichia Coli | Water, food, hygiene | Diarrhea, UTIs, respiratory illness, pneumonia | Un-speciated E. coli may not be pathogenic but, given that the laboratory records state its presence, it may be taken to represent a pathogenic strain. |
Salmonella Group | Water, food, and hygiene | Gastrointestinal illness | Some common ways in which a person can become infected with salmonella include: Eating food or drinking water that has been contaminated with animal faeces Eating food that has been handled by a food worker who has not properly washed their hands |
Shigella Flexneri | Water, hygiene | Diarrhea | Swallowing recreational water (for example, lake or river water) while swimming or drinking water that is contaminated with stool (faeces) containing the germ. |
Hazard/Threat | Present-Day Frequency and Intensity | Classification of Hazards |
---|---|---|
High temperature/heatwaves [21,22,23,24,25,26] |
| High: The Mopani District is well known for experiencing heatwaves and high temperature and adequate data exist to support this classification. |
Heavy rains/flooding [27,28,29,30,31] |
| High: The Mopani District is well known for experiencing heavy rains and flooding and adequate data exist to support this classification. |
Drier than usual/dry spells [12,32,33,34] |
| Medium: Existence of dry spells is evident but additional data for the Mopani District is needed to assign that this as high since drought also probably requires detailed consideration. |
Variable | Frequency n | Frequency % |
---|---|---|
Number of laboratory samples by WASH-related organisms (n = 3 070) | ||
Alcalgenes Faecalis Subsp faecalis | 12 | 0.4 |
Burkholderia Cepacia | 19 | 0.6 |
Enterococcus Faecalis | 642 | 21 |
Enterococcus Faecium | 108 | 6 |
Enteropathogenic Escherichia Coli | 1 | <1 |
Escherichia Coli | 2241 | 73 |
Salmonella Group | 34 | 1 |
Shigella Flexneri | 9 | 0.3 |
Shigella Group | 4 | 0.1 |
Patient age | ||
Under 5-year-olds | 308 | 10 |
5–18-year-olds | 335 | 11 |
19–65-year-olds | 2019 | 66 |
Older than 65 years | 263 | 9 |
Missing | 143 | 5 |
Patient gender | ||
Male | 923 | 30 |
Female | 2124 | 69 |
Missing | 23 | <1 |
Human Indicator | Outcome for Mopani District | Classification of Exposure |
---|---|---|
Child health | Mopani District had the second highest number of deaths due to diarrhea nationally for children aged under 5 years of age (case fatality rate of 4%) [35]. | High: Above the national target of 3%. |
Morbidity | In 2015, 15% of hospital admissions from two major hospitals in the district were diarrhea related [12]. | High: More than 15% of total admissions were due to a WASH-related illness. |
From 2015 to 2018, among 20,250 laboratory specimens, there was a 5% prevalence of WASH-related bacterial pathogens (this study). | High: 5% of laboratory specimens were associated with a WASH-related bacterial pathogen. | |
Water quality | Microbial water quality of water samples collected from Mopani standpipes had high microbial risk. Total coliform counts exceeded 100 counts/100 mL water in 29% of these samples. A similar pattern was observed for E.coli with more than 20 counts/100 mL detected in 11% of samples from standpipes [2,3,6]. | High: More than a third of households were exposed to microorganisms that can cause diseases and that may come via piped water provided by the municipality. |
Factor | Element | Question | Outcome for Mopani District | Classification of Vulnerability |
Environ-mental | Waste disposal | Is domestic waste collected and disposed of safely by municipal authorities? | Only 15% of population has refuse removed by authorities. 68% of population use their own refuse dump. | High: A large proportion of the population does not have access to formal domestic waste disposal. |
Human | Age of population | Is there a large population of very old or young people? | 40% of the population is under the age of 18 years. | Medium: Close to 50% of the population is under the age of 18 years. |
Socio-economic stability | What are the levels of employment? What are levels of income per month? # | 26% of population is employed; 50% are not economically active. 17% are unemployed. 43% of population do not earn any income; 45% earn less than ZAR 1600; 4% earn between ZAR 1600–3200; 2% earn between ZAR 3200–6400; 4% earn more than ZAR 6400. | High: There is low socio-economic stability in Mopani District. High percentages of the population do not earn any income or earn well below minimum wages. | |
Physical | Technology of WASH physical infrastructure | Which latrine types are predominantly used? Are they resilient? | 69% of population in Mopani use pit latrines. These are often poorly designed and not designed to be resilient to climate shocks. | High: Poor/basic WASH infrastructure is available. Resilience of infrastructure is low due to poor design and construction of pit latrines. |
What is the availability of water supply infrastructure? | 16% of population is without access to piped water. | High: The percentage of people without access to piped water from a tap in their home, yard or community is high (>80%). | ||
Political and institutional | Climate change policies and adaptation plans for the water supply and sanitation sectors for Mopani district | Are there any government or municipal policies/legislature on climate change and adaptation plans for water supply and sanitation sectors? | Climate change policies and adaptation plans identify the risks to sanitation and drinking water, but sanitation policies do not discuss climate change or offer recommendations on adaptation. | High: The Mopani District Municipality Climate Change Vulnerability Assessment and Response Plan identifies sanitation as an impacted sector. Projections suggest increased risk of flooding and rainfall intensities, flash floods and regional flooding, litter and debris blocking water and sanitation systems. No sanitation policy was found. |
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Kapwata, T.; Kunene, Z.; Wernecke, B.; Lange, S.; Howard, G.; Nijhawan, A.; Wright, C.Y. Applying a WASH Risk Assessment Tool in a Rural South African Setting to Identify Risks and Opportunities for Climate Resilient Communities. Int. J. Environ. Res. Public Health 2022, 19, 2664. https://doi.org/10.3390/ijerph19052664
Kapwata T, Kunene Z, Wernecke B, Lange S, Howard G, Nijhawan A, Wright CY. Applying a WASH Risk Assessment Tool in a Rural South African Setting to Identify Risks and Opportunities for Climate Resilient Communities. International Journal of Environmental Research and Public Health. 2022; 19(5):2664. https://doi.org/10.3390/ijerph19052664
Chicago/Turabian StyleKapwata, Thandi, Zamantimande Kunene, Bianca Wernecke, Samantha Lange, Guy Howard, Anisha Nijhawan, and Caradee Y. Wright. 2022. "Applying a WASH Risk Assessment Tool in a Rural South African Setting to Identify Risks and Opportunities for Climate Resilient Communities" International Journal of Environmental Research and Public Health 19, no. 5: 2664. https://doi.org/10.3390/ijerph19052664