Mathematical modelling of the impact of COVID-19 care measures on other respiratory diseases

Abstract

INTRODUCTION: Mathematical models of infectious disease transmission allow to study different mechanisms which affect the temporal behavior. This work analyzed the impact of the decrease in transmissibility, as a result of measures of personal care adopted to reduce circulation of COVID-19, on the dynamics of influenza and respiratory syncytial virus (RSV). METHODS: A deterministic SIRS (susceptible-infected-recovered-susceptible) model with seasonal modulation was used to represent two diseases with short-term immunity and annual cycle: influenza and RSV. Changes in disease transmissibility were modeled by reducing it for two years and analyzing different scenarios. RESULTS: In this model, transmissibility reduction brings changes which sustain in the following years: very pronounced epidemic events with lengthening of the inter-outbreak interval. This effect prevails over the seasonal behavior. The scenario of 40% initial reduction in transmissibility is compatible with the behavior of influenza and RSV currently reported in Argentina. DISCUSSION: The general model proposed here, under conditions of temporary reduced transmissibility, shows an epidemiology compatible with recently reported data of influenza and RSV in Argentina. This result illustrates modeling as a useful tool to understand non-intuitive effects.