Forecasting Covid-19 epidemic in Isfahan using a dynamic modeling approach

Abstract

The multidimensional destructions caused by Covid-19 have been compared to that of World War II. What makes the situation even more complicated is the ambiguity regarding the duration and the final size of the pandemic. It is critical especially for the governments, healthcare systems, and economic sectors to have an estimation of the future of this disaster. Using a dynamic model, we have here simulated the epidemic in Isfahan province, Iran for the episode of Feb 14th to April 11th and also have forecasted the remaining course with three scenarios which differ in terms of the stringency of social distancing. Results of this study indicate that in a “good scenario”, the epidemic could be overcome by following a strict lockdown for some weeks. Notably, even partial restrictions in the “feasible scenario” decline hospital admissions and mortality rates by one third compared to the “bad scenario” in which no limitation is imposed. Taken together, inattention to preventive strategies will result in a dramatic increase of the medical, social, and economical burden of the outbreak.