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.
