Dynamics of SARS-CoV-2 outbreak in the Kingdom of Saudi Arabia: A predictive model

Abstract

Background: COVID-19 is a worldwide pandemic that was first reported in China, and has spread to almost all nations. Measures of containment and control practiced by governments and authorities may benefit from prediction of the extent and peaks of spread to properly prepare to face the pandemic. Aim: The aim of the study was to predict the peak numbers of mortality, intensive care unit (ICU) admission, hospitalization, and positive cases and the time of their occurrence. Settings and Design: The study design is of a mathematical prediction model of prediction of spread of infectious disease, based on data from Saudi Arabia. Materials and Methods: We utilized a SEIR predictive model that divides the population into compartments and utilizes mathematical equations to predict the dynamics of the infection and its peak. The model exploited data from reliable sources on the Internet, and is – by design – based on certain assumptions. Statistical Analysis: Predefined mathematical equations that incorporate different parameters and assumptions were used for statistical analysis. Results: We estimated an R 0 value for our model of 2.2, and the model predicted a peak incidence of the pandemic around July 26, 2020. The peak mortality was predicted at 99,749 persons, predicted peak ICU admission of 70,246 patients, and peak hospitalization of 11,997,936 patients; all these predicted values were out of a total of predicted 14,049,104.83 COVID-19-positive cases. Conclusion: The COVID-19 pandemic in Saudi Arabia is predicted to peak by the end of July 2020, and may pose a serious burden on health-care systems already in shortage. Proper crisis management and effective resource utilization is crucial to safely overcome the pandemic, in addition to continuing control measures at least till the predicted peak time is over.