Abstract
Urbanization increases human mobility in ways that can alter the transmission of classically rural, vector-borne diseases like schistosomiasis. The impact of human mobility on individual-level Schistosoma risk is poorly characterized. Travel outside endemic areas may protect against infection by reducing exposure opportunities, whereas travel to other endemic regions may increase risk. Using detailed monthly travel- and water-contact surveys from 27 rural communities in Sichuan, China, in 2008, we aimed to describe human mobility and to identify mobility-related predictors of S. japonicum infection. Candidate predictors included timing, frequency, distance, duration, and purpose of recent travel as well as water-contact measures. Random forests machine learning was used to detect key predictors of individual infection status. Logistic regression was used to assess the strength and direction of associations. Key mobility-related predictors include frequent travel and travel during July-both associated with decreased probability of infection and less time engaged in risky water-contact behavior, suggesting travel may remove opportunities for schistosome exposure. The importance of July travel and July water contact suggests a high-risk window for cercarial exposure. The frequency and timing of human movement out of endemic areas should be considered when assessing potential drivers of rural infectious diseases.