Analysis of the COVID-19 pandemic in Rwanda using a stochastic model

Abstract

On March 12, 2020, the WHO declared the COVID-19 pandemic, in response to widespread infections and thousands of fatalities resulting from the outbreak. Researchers worldwide have paid close attention to this pandemic. This situation has been aided by mathematical models that guide public policy. In Rwanda, this problem involves uncertainty and incomplete information, and a stochastic approach is appropriate for capturing a broad range of possible outcomes. However, many epidemiological models do not account for preventive measures using a stochastic approach to analyze COVID-19 in Rwanda. Therefore, the aim of the paper is to build and analyze a COVID-19 pandemic stochastic model with preventive measures implemented in Rwanda. A deterministic model is formulated and transformed into stochastic equations. The numerical solutions of both models were computed and compared. The stochastic model is considered to be the best to use in the Rwanda context because of the model’s fluctuations, which capture even the residuals and uncertainties. The results indicate that the pandemic could spread faster if awareness-raising strategies are not effectively implemented, and preventive actions for the pandemic are considered crucial tools for effective control and mitigation.

Keywords

• Disease free equilibrium
• pandemic disease
• compartmental model
• model parameters
• preventive measures