A deterministic Susceptible–Infected–Recovered model for studying the impact of media on epidemic dynamics

Abstract

It is important to understand how the provision of information influences individuals’ behavior and its impact on disease transmission dynamics. We formulate a simple deterministic Susceptible–Infected–Recovered (SIR) model with vital dynamics and incorporate, one at a time, four media functions used in previous studies to mimic media reporting of a disease outbreak to investigate their impact on the dynamics of an epidemic. The most sensitive model parameter for the epidemic outcome at initial disease transmission and disease prevalence are obtained through normalized forward-sensitivity analyses. Media reporting does not impact initial disease transmission but affects the effective reproduction number as the media coverage begins. Numerical results show that the epidemic will affect a large proportion of the population with no media functions. Still, the epidemic time line may be short. In contrast, the key epidemiological quantities (such as age at infection, peak magnitude, peak time, end of the epidemic, and final epidemic size) vary depending on the media function used. The choice of the media function in a pandemic is critical. The media reporting on the spread of disease during pandemics should be done with care since it could counter-intuitively lead to under or overestimating the disease outbreak.

Keywords

• Disease outbreak
• Media coverage
• Susceptible–infected–recovered
• Epidemic dynamics
• Deterministic model
• Sensitivity analysis