Perspectives of modeling COVID-19 transmission via integral equations

Abstract

The ongoing COVID-19 pandemic has become a major threat to the entire globe. In order to properly place controlling strategies on each level of transmission, researchers, scientists and mathematicians use different approaches to model it. Compartment models such as SIR, SEIR are the center of attention in many models. General concern on integral equation models in disease transmission is considerably low due to the intuitive temptation of modeling in terms of rate of change of a phenomenon. This study expresses possibilities of modeling COVID-19 context in terms of integrals since accumulation effect can be observed in several influencing factors. Both Volterra and Fredholm integral equations can be used to model this, since these influences can accumulate within constant, variable or fixed intervals. While causative factors which consist of cross-references in different platforms can be modeled by degenerated kernels, difference kernels accommodate causative factors with time delay.