Analytical insights of the effects of Non-Pharmaceutical Interventions on SRAS-CoV-2 Dynamic with Application to West African Data

Abstract

The COVID-19 pandemic was caused by the rapid spread of a new coronavirus (SARS-CoV-2) worldwide. COVID-19 pandemic mitigation measures caused significant social and economic disruption, especially in regions with weak economic and fragile healthcare systems like West Africa. Therefore, accurate knowledge of the impact of these measures on its dynamics is important in decision-making. In this study, we formulated and used a deterministic compartmental model, considering two sub-classes of susceptible individuals (S₁ and S₂), where S₁ is the population living around the epicenter of the epidemic and S₂ is the population living far from the epicenter of the epidemic. The aim was to (i) theoretically assess the impact of measures reducing the transmission rate of the disease (ψ) on the epidemic dynamics and (ii) analyze the impact of measures reducing the probability of contact between infected and susceptible individuals (detection and isolation rates, θ_ap, θ_s) on the epidemic dynamics. We determined the expressions of the basic and control reproduction numbers and studied the sensitivity and elasticity of the control reproduction number with respect to ψ, θ_ap, θ_s, and heterogeneity factor, k(S₁/S₂). Application to the COVID-19 first-wave data from West Africa revealed that the basic reproduction number was 1.85. Moreover, the results indicated that a 50% reduction in the transmission rate of COVID-19 or the detection and isolation of 10% of infected individuals per day should help to reach the peak of the epidemic. Furthermore, a 100% increase in the heterogeneity factor induces a 16% increase in the control reproduction number when θ_ap = 0.15 and a 14% increase in the control reproduction number when θ_ap = 0.6. These conclusions could help design control measures to curtail future epidemics.