Modeling the Complexities of Water, Hygiene, and Health in Limpopo Province, South Africa

Abstract

Researchers have long studied the causes and prevention strategies of poor household water quality and early childhood diarrhea using intervention-control trials. Although the results of such trails can lead to useful information, they do not capture the complexity of this natural/engineered/social system. We report on the development of an agent-based model (ABM) to study such a system in Limpopo, South Africa. The study is based on four years of field data collection to accurately capture essential elements of the communities and their water contamination chain. An extensive analysis of those elements explored behaviors including water collection and treatment frequency as well as biofilm buildup in water storage containers, source water quality, and water container types. Results indicate that interventions must be optimally implemented in order to see significant reductions in early childhood diarrhea (ECD). Household boiling frequency, source water quality, water container type and the biofilm layer contribution were deemed to have significant impacts on ECD. Furthermore, concurrently implemented highly effective interventions were shown to reduce diarrhea rates to very low levels even when other, less important practices were sub-optimal. This technique can be used by a variety of stakeholders when designing interventions to reduce ECD incidences in similar settings.

Modeling the Complexities of Water, Hygiene and Health in Limpopo, South Africa

“…This result is highly consistent with the 46% found by . Other studies that Although our ABM is well tested (Mellor et al , 2012a), is consistent with previously reported results and produces logical conclusions, there are a few notable limitations.…”

“…• E↵ects of measured declines in microbial e↵ectiveness over time answer open questions in the literature (Lantagne et al , 2006) and also demonstrates the adaptability of the ABM described previously (Mellor et al , 2012a) to understand the complexities of disparate interventions.…”

“…Although, since samples were only taken monthly, it is unclear if the measurements represent true seasonal variation or sampling error. These facts indicated that there may be opportunities for improvements and dispersion of best-practices within communities and that human behaviors may have a significant e↵ect on drinking water quality (Mellor et al , 2012a).…”

“…In addition, two major meta-analyses found that hygiene, sanitation and point-of-use water treatment devices were more e↵ective in preventing diarrhea than community water source protection (Fewtrell et al , 2005;Clasen et al , 2007). Others have used complex systems approaches show that human behavior has a large impact on household water quality (Mellor et al , 2012a).…”

Time series investigation of changes in seasonality of acute diarrhea hospitalizations before and after rotavirus vaccine in Southern Brazil

“…Considering this is a hot month, probably the hospitalizations that occur in February are also due to other diarrheic diseases. On the other hand, the relationship between climate and diarrheic diseases is complex due to the large number of confounding variables 11,23,24 , the means of transmission 25 that can affect the disease rates, and the fact that diarrhea can be caused by multiple pathogens 26,27 . The limitations related to the data discussed in Masukawa et al 4 are also inherent to this research.…”