How would Widespread Community Transmission of Covid-19 in Sri Lanka look like? A Population-based Simulation

Abstract

Abstract Widespread community transmission of Covid-19 can overwhelm the capacity of health systems; Sri Lanka is no exception. We simulated the widespread community transmission of Covid-19 in Sri Lanka, using the Susceptibility, Infected and Removed (SIR) model through the Penn State University CHIME Model incorporated to ArcGIS Pro, by introducing one case of Covid-19 to the current population in each of the 26 health districts and running the model for 365 days. The simulation revealed that the number of patients requiring admissions, ICU care, and mechanical ventilation would peak at 1942, 583, and 388 per day, respectively, around 213 days from the onset. The cumulative number of cases needing admission, ICU care, and ventilation will be 245,916, 73,775, and 49,183 after 365 days. Colombo and Gampaha districts will report the highest number of daily total numbers of hospitalized cases over 1680. Health authorities can use the results of such simulations to prepare to face the worst-case scenarios of the Covid-19 outbreak to minimize morbidity and mortality. Keywords: Covid-19, Community Transmission, SIR Model, CHIME, Outbreak, Simulation, Prediction