Estimating the Impact of Asymptomatic Carriers on the spread of Infectious Diseases: An interaction-based Model

Abstract

Epidemiological models are commonly used to predict and describe the spread of a viral outbreak among a population. Many such models use differential equations and transition rates to predict the growth dynamics of the infectious and exposed groups with a greater population. These methods do not distinguish between infectious individuals. In this paper, we propose a new model that includes asymptomatic carriers while holding constant many of the transition rates and assumptions of the classical models. Seeking to replicate realistic outbreak scenarios, we introduce a way to estimate the reproduction number R0 of epidemics and apply these estimations to our model. Our results replicate those described in similar research papers, showing that a small proportion of asymptomatic carriers can be responsible for a majority of the transmissions. We propose possible extensions to our model, underlining the impactful applications it may have on healthcare management and public safety policymaking.