Predictors of bovine Schistosoma japonicum infection in rural Sichuan, China

In China, bovines are believed to be the most common animal source of human Schistosoma japonicum infections, though little is known about what factors promote bovine infections. Because schistosomiasis is a sanitation-related, water-borne disease transmitted by many animals, we hypothesized that several environmental factors – such as the lack of improved sanitation systems, or participation in agricultural production that is water-intensive – could promote schistosomiasis infection in bovines.

This data was collected as a part of a repeat cross-sectional study conducted in rural villages in Sichuan, China from 2007 to 2016. During this time, all humans and bovines residing in participating households in the study villages were invited to participate in schistosomiasis infection surveys in 2007, 2010 and 2016. Additionally, the head of each household was asked to complete a household survey each year that contained closed-ended questions related to socioeconomic status, domestic and farm animal ownership, sanitation and water access and agricultural practices. Bovine age, type and sex were also collected at the time of the bovine infection surveys in 2007 and 2010.

Each row in the data represents a single bovine participant from a given study year. The outcome in this analysis was bovine Schistosoma japonicum infection, while predictors included village and household-level values of physical and environmental conditions hypothesized to be potentially predictive of bovine S. japonicum infection. Candidate predictors included: 1) physical/biological characteristics of bovines, 2) human sources of environmental schistosomes, 3) socio-economic indicators, 4) animal reservoirs, and 5) agricultural practices. Village-level predictors were generated from the household survey data, representing all households that participated in the household survey from a given village, even if they didn’t own bovines. Notably, the village-level variables excluded all observations from the bovine’s own household, and instead used only the data from the other households in the village. This allowed for an assessment of how the surrounding village environment impacts individual bovine infection risk, independent of the home environment, whereas the household-level variables aim to unpack the influence of the unique household environment on bovine infection status. All personal and/or identifying information – including human infection data – was removed from our datasets prior to publishing here to maintain participant privacy. Nevertheless, our entire analysis code is included in the R scripts published here, in the interest of full transparency.

The density of bovines in a village and agricultural practices were among the top predictors of bovine S. japonicum infection in all collection years. Additionally, human infection prevalence in the village, pig ownership and bovine age were found to be strong predictors of bovine infection in at least one year.