SISDH: A Model Based on SMAs and SIRs for the Simulation of the Evolution of COVID-19 in Cameroon

Abstract

This paper presents a model to simulate the evolution of COVID-19 in the Cameroonian context. The presented model SISDH stands for Susceptible, Infected, Severe, Died, and Healed is made up of the mixture of a Multi-Agent System (SMA) and a SIR (Susceptible, Infected, Recovered)-based model, and mainly addresses the problem of modelling the evolution of pandemics with a high transmission rate. Multi-agent systems are used to design the SIR model’s entities, namely the habitants of the region subject to the study. The experimentation carried out showed that the combination of the two concepts favours rapid decision-making. For example, the requirement to wear a mask or strict adherence to social distancing reduces the risk of spread. The application of these tough measures had theoretically leveled down the spreading of the epidemic. Besides the lowering of the number of cases when strict measures were applied, we also highlighted a significant reduction of deaths and severe illness which is a concomitant result of the lockdown. On the other hand, our experiments revealed a peak of infections a few steps after the beginning when no restrictions are made for barrier measures. The peak is followed by a sudden decrease in infection which might convey immunity of the population.