Data, Model Documentation, and Output Supporting "Optimizing syndromic health surveillance in free ranging great apes: the case of Gombe National Park"

Syndromic surveillance is an incipient approach to early wildlife disease detection. Consequently, systematic assessments are needed for methodology validation in wildlife populations. We evaluated the sensitivity of a syndromic surveillance protocol for respiratory disease detection among chimpanzees in Gombe National Park, Tanzania. Empirical health, behavioral and demographic data were integrated with an agent-based, network model to simulate disease transmission and surveillance. Surveillance sensitivity was estimated as 66% (95% Confidence Interval: 63.1, 68.8%) and 59.5% (95% Confidence Interval: 56.5%, 62.4%) for two monitoring methods (weekly count and prevalence thresholds, respectively), but differences among calendar quarters in outbreak size and surveillance sensitivity suggest seasonal effects. We determined that a threshold weekly detection of ≥2 chimpanzees with clinical respiratory disease leading to outbreak response protocols (enhanced observation and biological sampling) is an optimal algorithm for outbreak detection in this population. Synthesis and applications: This is the first quantitative assessment of syndromic surveillance in wildlife, providing a model approach addressing disease emergence. Coupling syndromic surveillance with targeted diagnostic sampling in the midst of suspected outbreaks will provide a powerful system for detecting disease transmission and understanding population impacts. Data files include documentation of a disease simulation model, simulation data produced from the model, as well as input data used to parameterize the model.