SimFI: A Transmission Agent-Based Model of Two Interacting Pathogens

Mathematical modeling has become essential in the field of infectious diseases epidemiology, particularly when it comes to studying the transmission of pathogens. However, most models simulate only one pathogen, whereas many species can circulate in the same population and impact each other's transmission dynamics. Here we present a new agent-based model, SimFI, formalizing the co-circulation of two distinct pathogens in a human population. Several between-pathogen interaction mechanisms are implemented at the individual scale, and their effects on the global transmission dynamics at the population scale are studied. The model produces independent time series of infection cases for the two pathogens, mimicking the data usually collected by infectious diseases surveillance systems. This study highlights the importance of precisely representing phenomena occurring at the individual level and the complexity of ecological interactions, thus confirming the usefulness of agent-based models to better understand between-pathogen interactions in epidemiology.