Agent-Based Simulation for Seasonal Guinea Worm Disease in Chad Dogs

The campaign to eradicate dracunculiasis (Guinea worm [GW] disease) and its causative pathogen Dracunculus medinensis (GW) in Chad is challenged by infections in domestic dogs, which far outnumber the dwindling number of human infections. We present an agent-based simulation that models transmission of GW between a shared water source and a large population of dogs. The simulation incorporates various potential factors driving the infections including external factors and two currently used interventions, namely, tethering and larvicide water treatments. By defining and estimating infectivity parameters and seasonality factors, we test the simulation model on scenarios where seasonal patterns of dog infections could be driven by the parasite's life cycle alone or with environmental factors (e.g., temperature and rainfall) that could also affect human or dog behaviors (e.g., fishing versus farming seasons). We show that the best-fitting model includes external factors in addition to the pathogen's life cycle. From the simulation, we estimate that the basic reproductive number, R ₀, is approximately 2.0; our results also show that an infected dog can transmit the infection to 3.6 other dogs, on average, during the month of peak infectivity (April). The simulation results shed light on the transmission dynamics of GWs to dogs and lay the groundwork for reducing the number of infections and eventually interrupting transmission of GW.