Modeling spillover dynamics: understanding emerging pathogens of public health concern

Abstract

ABSTRACTThe emergence of infectious diseases with pandemic potential is a major public health threat worldwide. According to the World Health Organization, around 60% of the reported emerging infectious diseases are zoonoses and have been triggered by spillover events. Although the dynamics of spillover events are not yet well understood, mathematical modeling has the potential to characterize the highly complex interactions among pathogens, wildlife, humans, and the environment where they coexist. In this work, motivated by discussions on the introductory phase of SARS-CoV-2 towards a pandemic scenario, we address the so far unexplored the emergence of novel infectious agents. Aiming at gaining insights into the dynamics of spillover events and the final outcome of an eventual disease outbreak in a population, we propose a continuous time stochastic modeling framework to describe a cross-species disease transmission by coupling the dynamics of animal reservoirs and human hosts. A complete analysis of the system is conducted, followed by numerical experiments where we investigate different scenarios of spillover events. Applied to the emergence of SARS-CoV-2 and monkeypox viruses, our results provide insights into the emergence of new infectious diseases able to cause not only local outbreaks but eventually explosive epidemics towards a pandemic.