Predicting the infections, evolution and outcome of COVID-19 pandemic in Rwanda using SIR model

A: Background: Since the first case was reported in Rwanda on March 14, 2020, various measures have been taken to slowdown the spread of the virus. However, due to its high infection rate and lack of virus immunity to everyone, the number of infected persons have continued to increase. The rising numbers of COVID19 infections have the potential to devastate the health care system in Rwanda if the spread is not controlled. There is a need of a reliable, country-specific forecast model to help in the prediction of infections and evolution of the virus. Such a model is necessary to monitor and assess the impact of the policies taken to slowdown the spread and consequences of the COVID-19 virus B. Goal and Objectives The goal of this project is to build a prediction model which provide a picture of the predicted progress of COVID-19 in Rwanda and test the impact of limiting the contact risks under the precaution measures taken to slowdown the spread of the virus Objectives: 1. To measure the transmission rate of the virus in Rwanda and determine the basic reproduction number (R0) of COVID-19 in Rwanda; 2. To assess the recovery rate of COVID-19, estimate the number of infectives, and the cumulative morbidity of COVID-19 in subsequent periods; 3. To estimate the risk of healthcare capacity in terms of access consideration, functional requirements, location, and uncertainties associated with the spread of the virus. C. Methods · The data will be collected from two sampling sources: Sampling Source 1: The first sample will utilize the list of all COVID-19 patients and recoveries as the sampling frame. From the selected sample, the primary data will be collected and used to assess the infectivity, incubation, and recovery among different population categories. Sampling Source 2: The second sample will be selected from the list of all health facilities in Rwanda. The primary data will be collected from the selected sample and analyzed to assess the healthcare capacity and determining which health facilities are capable of receiving COVID-19 patients in case the virus continues to spread in Rwanda · Prediction model To build a mathematical prediction model of COVID-19 pandemic in Rwanda, an extended Susceptible - Infected - Removed (eSIR) model was used. While the standard SIR model assumes constant transmission rate, the extended SIR model assumes a varying rate of virus transmission from infected person to a normal person, which is due to different measures taken to slow the spread of the virus like lockdown of cities, social distancing, and others. 35 D: Expected Outcomes are: · Availing a mathematical prediction model that will be used to control the spread and the outcome of the pandemic in Rwanda specifically, · Inform on the impact assessment of preventive measures taken by the government of Rwanda in response of flattening the curve of infection, · Inform on the healthcare capacity in terms of availability of functional requirements in case the virus continues to increase in Rwanda.