Evaluation of location tracking methods to understand human-wildlife contact and pathogen spillover risks

Background Most emerging infectious diseases originate in wildlife populations. As demonstrated by the 2013–2016 Ebola epidemic in West Africa, pathogen spillover from zoonotic reservoirs can have devastating public health impacts. Contact between humans and wildlife reservoirs determines spillover risk, but these interactions remain poorly understood. Despite advancements in technology, there are significant challenges to collecting fine-scale human movement data in remote areas to assess contact with wildlife. We aimed to evaluate available methods for collecting these data, and we applied the findings to identify an optimal method for a case study on pathogen spillover from bats in rural communities of Macenta, Republic of Guinea. Methods We reviewed existing methods for collecting location data from humans. Among available options, we identified two location tracking methods as candidates for deployment in our case study: 1) a mobile device with the GPSLogger application and 2) a custom-designed wristwatch with geolocation technology. The accuracy of these methods was assessed under varying levels of canopy cover. Battery life and user experience were tested in a pilot usability study. Testing was conducted in remote, forested regions of Macenta, Guinea and Malaysian Borneo, which are areas with repeated zoonotic spillover events. Results Overall, the watch’s mean measurement error was 14.7 metres (range 2.4–33.5), but the mobile device performed substantially worse with a mean error of 119.2 metres (range 1.5-1215.5). The battery of the watches powered location tracking for at least seven days, while the mobile devices lasted two days. Participants reported that the watches were more comfortable to carry. We demonstrated the utility of these devices in quantifying individual heterogeneities in space use and identifying areas and populations with high risk for human-wildlife contact. Conclusion The custom-designed watch enabled collection of detailed spatial information on human movement in remote, forested regions, with direct value in our case study in Guinea. However, mobile devices may be more accessible and suitable in contexts with high mobile phone usage and service coverage. Further research is needed to integrate these movement data with ecological and demographic data to understand how environment and human behaviour shape the dynamics of disease emergence.