The Covid-19 outbreak of 2020 has required many governments to develop mathematical-statistical models of the outbreak prevalence for policy and planning purposes. This work provides a tutorial on building a compartmental model using the Susceptibles, Exposed, Infected, Recovered and Deaths (SEIRD) model for the State of Qatar. A Bayesian framework is used to perform both parameter estimation and predictions. The use of interventions in the model attempts to quantify the impact of various government attempts to slow the spread of the virus. Predictions are also made to determine when the peak of Active Infections will occur. The talk uses the data from the Johns Hopkins Corona Virus Mapping project.
Edward Boone is a Professor of Statistics in the Department of Statistical Sciences and Operations Research at Virginia Commonwealth University.
Virtual seminar series sponsored by the Environmental Change Initiative