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Exposure, hazard and vulnerability all contribute to Schistosoma haematobium re-infection in northern Senegal

Citation

Lund, Andrea et al. (2021), Exposure, hazard and vulnerability all contribute to Schistosoma haematobium re-infection in northern Senegal, Dryad, Dataset, https://doi.org/10.5061/dryad.s7h44j15p

Abstract

The risk of infectious diseases, including snail-borne schistosomiasis, is determined by three interrelated components: exposure, hazard and vulnerability. For schistosomiasis, exposure occurs through behaviors involving water contact, but not without the environmental hazard of snails and parasites in the water. Socio-economic vulnerability makes it difficult to reduce exposure in the presence of hazard, because it increases reliance on hazardous activities and environments. We aimed to quantify the contributions of exposure, hazard and vulnerability to schistosome re-infection presence and intensity. We used cross-sectional parasitological data from 821 school-aged children in 13 villages along the Senegal River, survey data from 411 households where those children resided and ecological data from all 24 village water contact sites. We fit mixed-effects logistic and negative binomial regressions with indices of exposure, hazard and vulnerability as explanatory variables of Schistosoma haematobium infection, along with demographic control variables. Multi-model inference was used to determine the relative importance of each component of risk and model averaging was used to quantify associations between infection outcomes and indices of hazard, exposure and vulnerability. The most important component of S. haematobium presence was hazard (Ʃwi = 0.95), followed by vulnerability (Ʃwi = 0.91), while the most important component of S. haematobium intensity was exposure (Ʃwi = 1.00), followed by hazard (Ʃwi = 0.77). Hazard was positively associated with infection presence (OR = 1.49, 95% CI 1.12, 1.97), while exposure was positively associated with infection intensity. Our findings highlight how social (exposure and vulnerability) and environmental (hazard) processes act together to facilitate the acquisition and accumulation of schistosome infection from the environment across time and space. This approach can inform targeting of social and environmental interventions as complements to mass drug administration.

Methods

Parasitology data: S. haematobium infection in school-aged children were determined by detection of eggs in filtered urine samples. Infections were determined to be present when any eggs were detected; intensity of infection determined by number of eggs in sample.

Household survey data: Household surveys were completed in all households where children enrolled in the parasitology study lived. Relevant survey modules include (1) individual-level demopgrahic information, (2) individual-level, two-week recall of contact with surface water for six primary domestic and occupational chores requiring contact with water, (3) average freuqency of each water contact activity reported at the household level, (4) socio-economic indicators, such as reported durable assets and access to improved water and sanitation infrastructure, and (5) geographic coordinates of houseohld locations.

Body surface area interviews: Interviews with village residents at water access sites elicitied information on how much of the body typically comes into contact with water for each of six common water contact activities: (1) washing laundry, (2) washing dishes, (3) collecting water, (4) irrigated crops, (5) washing or watering livestock and (6) fishing from shore. Responses for each activity were registered on a diagram to used to measure burn size.

Ecological surveys: Exhaustive snail surveys were performed at all water access sites in all study villages with sampling stratified by three microhabitat types (emergent vegetation, non-emergent vegetation and open water/mud bottom). Microhabitats were identified using imagery from Google Earth and an unmanned aerial vehicle equipped with a camera.

Usage Notes

Individual- and household-level data have been aggregated to the village level in accordance with IRB privacy safeguards. The data needed to replicate the analysis can be made available upon request. README file with variable descriptions included as attachement. Code used to analyze data is freely available at https://github.com/andjanlund/ehv_schisto.

 

Funding

National Science Foundation, Award: 1414102

Bill and Melinda Gates Foundation, Award: OPP1114050

Office of the Vice Provost for Graduate Education, Stanford University, Award: James and Nancy Kelso Interdisciplinary Graduate Fellowship

University of Michigan, Award: Michigan Society of Fellows

Alfred P. Sloan Foundation, Award: Sloan Research Fellowship

University of Washington, Award: UW Innovation Award

National Science Foundation, Award: OCE-1829509