Abstract
Introduction: From the start of COVID-19 pandemic governments have been taking many decisions to control the outbreak. The impact of these decisions and policy changes on the outbreak is required to be analyzed.Objective: This article aims to investigate the impact of interventions implemented by the Government of Pakistan on the recent outbreak of novel-coronavirus. It provides the changes in the behavior of the outbreak on the implementation of two different types of interventions.Material and Method: An interrupted time-series (ITS) Poisson regression model on the ratio of cases to tests conducted for COVID-19 to regional level data of Pakistan is implemented, after checking the over-dispersion and autocorrelation problems. Selecting the level and slope change models, the effects of interventions, and the comparison of the selected models was also made. To examine future behavior of the pandemic the new cases of COVID-19, after 30 days, 60 days, and 90 days was also predicted.Result and Discussions: The estimated changes in positive ratio due to first and second interventions were reported 21.1% and 46.7% respectively for Pakistan. The country-wide COVID-19 cases predicted assuming full lockdown show an increasing trend i.e. 18,404, 37,288, and 75,545 after 30, 60, and 90 days, respectively. Assuming the partial lockdown the COVID-19 cases in the country might again reach the spike. However, 1,428, 1,004, and 706 cases are predicted under smart lockdown after 30, 60, and 90 days, respectively.Funding Statement: None.Declaration of Interests: None.
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