A Mathematical Model for Analyzing the Spread of Coronavirus in Nigeria, Including Population Migration Factors

Abstract

This study presents a mathematical model analyzing COVID-19 spread in Nigeria, incorporating population migration and asymptomatic cases. Expanding on the traditional SEIR (Susceptible-Exposed-Infectious-Recovered) model, it uses nonlinear ordinary differential equations to track the dynamics of different population groups. Key parameters, including transmission, immigration, emigration, and death rates, were estimated using data from the Nigeria Centre for Disease Control (NCDC) and fitted with the Nelder-Mead method. Simulations reveal a basic reproduction number (R₀) of 0.0095, indicating a high risk of secondary infections. The model shows that symptomatic infections peaked around 20 days before declining, while recovery rates continued to rise. The study emphasizes the importance of adhering to COVID-19 precautions and controlling population migration to mitigate the pandemic's impact. The findings offer valuable insights for effective disease control strategies in Nigeria.