An Interrupted Time Series Analysis of COVID-19 Positivity before, during and after Lockdown in Four States of India

Shailaja Tetali,Lincoln Priyadarshi Choudhury,Edwin Sam Asirvatham,Bogam Ranjeeth Kumar,Guru Rajesh Jammy

doi:10.4236/ojepi.2021.111005

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.

Highlights

India’s first few cases of COVID-19 were detected in Kerala by the end of January 2020
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
With a steady increase in the number of Influenza-Like Illness (ILIs) and Severe Acute Respiratory Infection (SARI) turning positive for COVID-19, the Government of India advised the States to invoke the provisions of Section 2 of the Epidemic Diseases Act 1897, to enable imposing restrictions like school and theatre closures, and banning large gatherings [1] [2]

Summary

Introduction

India’s first few cases of COVID-19 were detected in Kerala by the end of January 2020. 2020, assumed an immediate effect on infectious people becoming less infective; Davies et al, 2020, assumed a differential contact because of preferential self-isolation among people with clinical features; while Mandal et al, 2020, assumed the transmission dynamics in India to be similar to Japan and South Korea, considering half of the symptomatic cases to be quarantined within three days of developing symptoms [8] [9] [10] These assumptions provided much-needed possible scenarios of epidemic forecasting, they did not offer conclusive evidence regarding non pharmaceutical interventions. Our analysis examines the impact of lockdown as a policy intervention on COVID 19 positivity in four states of India

Objectives

Methods

Results

Conclusion