Examining time‐dependent effects of water, sanitation, and hygiene (WASH) interventions using an agent‐based model

Urban Water Access and Use in the Kivus: Evaluating Behavioural Outcomes Following an Integrated WASH Intervention in Goma and Bukavu, Democratic Republic of Congo

Increasing the availability and reliability of community water sources is a primary pathway through which many water supply interventions aim to achieve health gains in communities with limited access to water. While previous studies in rural settings have shown that greater access to water is associated both with increased overall consumption of water and use of water for hygiene related activities, there is limited evidence from urban environments. Using data collected from 1253 households during the evaluation of a community water supply governance and hygiene promotion intervention in the cities of Goma and Bukavu, Democratic Republic of Congo, we conducted a secondary analysis to determine the impact of these interventions on household water collection and use habits. Using multiple and logistic regression models we compared differences in outcomes of interest between households in quartiers with and without the intervention. Outcomes of interest included litres per capita day (lpcd) of water brought to the household, lpcd used at the household, and lpcd used for hygiene-related activities. Results demonstrated that intervention households were more likely to use community tapstands than households located in comparison quartiers and collected on average 16.3 lpcd of water, compared with 13.5 lpcd among comparison households (adj. coef: 3.2, 95 CI: 0.84 to 5.53, p = 0.008). However, reported usage of water in the household for domestic purposes was lower among intervention households (8.2 lpcd) when compared with comparison households (9.4 lpcd) (adj. coef: -1.11, 95 CI: -2.29 to 0.07), p = 0.066) and there was no difference between study groups in the amount of water allocated to hygiene activities. These results show that in this setting, implementation of a water supply governance and hygiene promotion intervention was associated with a modest increase in the amount of water being bought to the household, but that this did not translate into an increase in either overall per capita consumption of water or the per capita amount of water being allocated to hygiene related activities.

Molecular Epidemiology of Human Cryptosporidiosis in Low- and Middle-Income Countries

Cryptosporidiosis is one of the most important causes of moderate to severe diarrhea and diarrhea-related mortality in children under 2 years of age in low- and middle-income countries. In recent decades, genotyping and subtyping tools have been used in epidemiological studies of human cryptosporidiosis. Results of these studies suggest that higher genetic diversity of Cryptosporidium spp. is present in humans in these countries at both species and subtype levels and that anthroponotic transmission plays a major role in human cryptosporidiosis. Cryptosporidium hominis is the most common Cryptosporidium species in humans in almost all the low- and middle-income countries examined, with five subtype families (namely, Ia, Ib, Id, Ie, and If) being commonly found in most regions. In addition, most Cryptosporidium parvum infections in these areas are caused by the anthroponotic IIc subtype family rather than the zoonotic IIa subtype family. There is geographic segregation in Cryptosporidium hominis subtypes, as revealed by multilocus subtyping. Concurrent and sequential infections with different Cryptosporidium species and subtypes are common, as immunity against reinfection and cross protection against different Cryptosporidium species are partial. Differences in clinical presentations have been observed among Cryptosporidium species and C. hominis subtypes. These observations suggest that WASH (water, sanitation, and hygiene)-based interventions should be implemented to prevent and control human cryptosporidiosis in low- and middle-income countries.

A cyberGIS approach to spatiotemporally explicit uncertainty and global sensitivity analysis for agent-based modeling of vector-borne disease transmission

While agent-based models (ABMs) provide an effective means for investigating complex interactions between heterogeneous agents and their environment, they may hinder an improved understanding of phenomena being modeled due to inherent challenges associated with uncertainty in model parameters. This study uses uncertainty analysis and global sensitivity analysis (UA-GSA) to examine the effects of such uncertainty on model outputs. The statistics used in UA-GSA, however, are likely to be affected by the modifiable areal unit problem (MAUP). Therefore, to examine the scale varying-effects of model inputs, UA-GSA needs to be performed at multiple spatiotemporal scales. Unfortunately, performing comprehensive UA-GSA comes with considerable computational cost. In this paper, our cyberGIS-enabled spatiotemporally explicit UA-GSA approach helps to not only resolve the computational burden, but also to measure dynamic associations between model inputs and outputs. A set of computational and modeling experiments shows that input factors have scale-dependent impacts on modeling output variability. In other words, most of the input factors have relatively large impacts in a certain region, but may not influence outcomes in other regions. Furthermore, our spatiotemporally explicit UA-GSA approach sheds light on the effects of input factors on modeling outcomes that are particularly spatially and temporally clustered, such as the occurrence of communicable disease transmission.