Evaluating the Effect of Macro-Level Health Policies on Novel Coronavirus (COVID-19) Epidemic Control in Iran

This study aimed to evaluate the effect of macro-level health policies on COVID-19 outbreak control in Iran This was a descriptive-analytical study of the applied time series performed on April 19, 2020 The effect of four macro-health interventions, including reducing overcrowding, social distancing, limitation of high-risk economic activities, and active case detection, was examined The Vector auto-regression (VAR) was used to investigate the effect of the interventions The augmented Dickey-Fuller test (ADF) was used to ensure the time stability of the time series and the existence of a unit-root To analyzing data and estimation VAR models, STATA software was used P of less than 0 1 was considered significant The increase in the number of cases with two days’ lag had a positive and significant effect on increasing the number of new cases of the COVID-19 (C=0 176, P=0 097) Adopting an overcrowding reduction policy with both 2-day lags (c=0 095, P=0 066) and 4-day lags (c=0 314, P=0 000) had a negative and significant effect on increasing the number of new cases of the COVID-19 Our study showed that overcrowding reduction and new COVID-19 case detection could play an effective role in controlling the epidemic of COVID-19 in Iran It seems that the best advice is to stay home and use strategies to identify more patients © 2021 Tehran University of Medical Sciences All rights reserved Acta Med Iran 2021;59(1):44-49 © 2021 Tehran University of Medical Sciences