TITLE:
An Interrupted Time Series Analysis of COVID-19 Positivity before, during and after Lockdown in Four States of India
AUTHORS:
Shailaja Tetali, Guru Rajesh Jammy, Edwin Sam Asirvatham, Bogam Ranjeeth Kumar, Lincoln Priyadarshi Choudhury
KEYWORDS:
Causality, Interrupted Time Series, COVID-19, Impact Evaluation
JOURNAL NAME:
Open Journal of Epidemiology,
Vol.11 No.1,
January
5,
2021
ABSTRACT: Objectives: The objective of this study was to examine the impact of large scale non-pharmaceutical interventions on COVID-19 pandemic. Methods: We used interrupted time series analysis (ITS), a quasi-experimental model to evaluate the effect of interventions in four states of India by comparing the COVID-19 positivity before lockdown, during lockdown and opening-up period. Results: The positivity in all the four states declined during lockdown and the trends reversed soon after the lockdown measures were relaxed as the states opened-up. The rate of reduction of positivity was significantly different between states. Between the lockdown and opening-up period, an increase in positivity was recorded in all the states with significant variation between states. Conclusion: The analysis provides conclusive evidence that the lockdown measures had a positive effect in reducing the burden of COVID-19 and establishes a causal relationship.