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

Abstract

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.

Potential Impact of a Diagnostic Test for Detecting Prepatent Guinea Worm Infections in Dogs

“…The number of dogs exuding worms over time by geographic cluster (2016-2021) and by village (year 2021) are reported in Figure 1. We adapt the agent-based simulation model developed by Perini et al 15 and revised for multiple water sources by Wang et al 14 to incorporate the testing intervention. The simulation model simulates daily interactions between dogs, worms, and water sources, considering the life cycle of GW, the impact of Abate ® larvicide and weather on water infectivity, and the tethering of dogs.…”

Potential Impact of a Diagnostic Test for Detecting Prepatent Guinea Worm Infections in Dogs

“…The number of dogs exuding worms over time by geographic cluster (2016-2021) and by village (year 2021) are reported in Figure 1. We adapt the agent-based simulation model developed by Perini et al 15 and revised for multiple water sources by Wang et al 14 to incorporate the testing intervention. The simulation model simulates daily interactions between dogs, worms, and water sources, considering the life cycle of GW, the impact of Abate ® larvicide and weather on water infectivity, and the tethering of dogs.…”

“…Infectivity and weather parameter values used in this simulation model are reported in the supplemental materials. These parameters were calibrated by Perini et al 15 and Wang et al 14 based on infection data provided by GWEP and weather data from NOAA for years 2016-2018. In 2019, Chad reported an 86% increase in infected dogs and a 28% increase in villages with infected dogs compared to 2018.…”

“…In 2019, Chad reported an 86% increase in infected dogs and a 28% increase in villages with infected dogs compared to 2018. 16 When attempting to recalibrate model parameters using more recent data (i.e., 2019-2021), we find that due to high variability/spikes in dog infections during years 2019 and 2020, we can more closely simulate dog infections in year 2021 by using the original infectivity and weather parameters calibrated based on years 2016-2018 (for details on parameter calibration, see 14,15 ).…”

The Eradication of Guinea Worm Disease: A Push for Community Engagement

“…Animal sources of GWD transmission are increasingly concerning for eradication, although infections in dogs remain incompletely understood [19,20]. Identification and containment of GWD in animals are difficult because cases are confirmed only when a worm visually appears on the animal's body [18].…”