Modeling and Forecasting Trend of COVID-19 Epidemic in Iran

Ali Ahmadi; Majid Shirani; Fereydoon Rahmani

The actual trend of detecting COVID-19 cases in Iran has been increasing and is based on public behavior and government intervention. In this study, estimated are based on current trends, social distance, sampling of severe cases, hospitalization and tip of iceberg spread disease and asymptomatic, mild and moderate cases could not be calculated. Complete reliance on any type of model will lead to systematic and random error, unless modeling provides a prediction with precise and clear assumptions and inputs and outputs. Given the assumptions in Iran, the prediction of the patients on 3 April (Farvardin 15), 2020 with the three growth models of Von Bertalanffy, Gompertz, and the least squared error were estimated at 48200, 52500 and 58000, respectively. The number of deceased COVID-19 patients was also estimated to be 3600 individuals using the Von's growth model, 4200 ones by Gompertz''s model and 4850 ones according to the LSE method. If enforcement and public behavior interventions (social distance) continue with current trends, the control and reduction of the COVID-19 epidemic in Iran will be felat from late April 2020, and new cases are expected to decline from mid-April of the following Iranian new year. For prediction end of epidemic, three models of growth were used.