Concurrent impact evaluation of lockdown measures on COVID-19 positivity in three states of India
DOI:
https://doi.org/10.18203/2394-6040.ijcmph20204371Keywords:
India, Interrupted time series, COVID-19Abstract
Background: In response to the COVID pandemic, many preventive steps have been undertaken in the India, including lockdown measures. The objective of the study was to analyze the impact of lockdown on COVID-19 epidemic.
Methods: We used quasi-experimental interrupted time series analysis using reported data from 17 March 2020 to 14 April 2020 with effective time interruption on 3 April 2020. We used publicly available data from three states to calculate the pre and post lockdown period COVID-19 test positivity.
Results: The lockdown was able to reduce the infections cases in all three states. The trend of positivity changed to negative for Tamil Nadu and Odisha and accelerated upward in Kerala. The trend changes for positivity were statistically significant for two states (Tamil Nadu and Odisha). In comparison to counterfactual, on 13 April 2020, the predicted relative change in COVID-19 positivity was maximum for the state of Odisha (108%), followed by Tamil Nadu (85%) and Kerala (78%) respectively.
Conclusions: The lockdown measurements were observed to be effective in the three states studied. However, the quantity of change varied from state to state. Policymakers and public health scientists can consider these findings ad methodology for future action.
References
Press Information Bureau. Government of India. Update on Novel Coronavirus: one positive case reported in Kerala. 2020. Available at: https://pib.gov.in/newsite/PrintRelease.aspx?relid=197738. Accessed on 16 April 2020.
Statement on the second meeting of the International Health Regulations. Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV). 2005. Available at: https://www.who.int/news-room/detail/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov). Accessed on 16 April 2020.
Simha A, Prasad RV, Narayana S. A simple Stochastic SIR model for COVID-19 Infection Dynamics for Karnataka: Learning from Europe. arXiv. 2020. Available at: http://arxiv.org/abs/2003.11920. Accessed on 16 April 2020.
Gazette of Kerala. The Government of Kerala. Notfication: COVID-19 Notifiable Disease. 2020. Available at: http://dhs.kerala.gov.in/wp-content/uploads/2020/03/MP-Act.pdf.
Secretary Home. Government of India Communication on Lockdown. DO No. 40-3/2020-DM-I(A) 2020. Available at: https://www.mohfw.gov.in/pdf/Annexure_MHA.pd.
Secretary Home. MHA Order for extending the Lockdown Period till 3.5.2020. No-40-3/2020-DM-I(A) 2020. Available at: https://www.mha.gov.in/sites/default/files/MHA_29042020.PDF
Center for Disease Dynamics E & P. COVID-19 Modeling with IndiaSIM. 2020. Available at: https://cddep.org/covid-19/. Accessed on 30 March 2020.
Krishnakumar B, Rana S. COVID 19 in INDIA: Strategies to combat from combination threat of life and livelihood. J Microbiol Immunol Infect. 2020;53(3):389-91.
Singh R, Adhikari R. Age-structured impact of social distancing on the COVID-19 epidemic in India. arXiv. 2020;1-9.
Mandal S, Bhatnagar T, Arinaminpathy N, Agarwal A, Chowdhury A, Murhekar M, et al. Prudent public health intervention strategies to control the coronavirus disease 2019 transmission in India: A mathematical model-based approach. Indian J Med Res. 2020;151(2 and 3):190-9.
Lombardi A, Bozzi G, Mangioni D, Muscatello A, Peri AM, Taramasso L, et al. Duration of quarantine in hospitalized patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection: a question needing an answer. J Hosp Infect. 2020;105(3):404-5.
Shah K, Awasthi A, Modi B, Kundapur R, Saxena DB. Unfolding trends of COVID-19 transmission in India: Critical review of available Mathematical models. Indian J Community Heal. 2020;32(2):206-14.
The World Bank. Impact Evaluation in Practice Second Edition. Available at: https://openknowledge.worldbank.org/bitstream/handle/10986/25030/9781464807794.pdf?sequence=2&isAllowed=y. Accessed on 17 April 2020.
Lopez Bernal J, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol. 2017;348-55.
Figueiredo A, Codina A, Moreira D, Figueiredo M, Saez M, León A. Impact of lockdown on COVID-19 incidence and mortality in China: an interrupted time series study. WHO Bull. 2020. Available at: http://dx.doi.org/10.2471/BLT.20.251561. Accessed on 17 April 2020.
Government of Kerala. GoK Dashboard | COVID-19 Battle. Available at: https://dashboard.kerala.gov.in/. Accessed on 17 April 2020.
Health and Family Welfare Department G of TN. Daily Bulletin – StopCoronaTN. Available at: https://stopcorona.tn.gov.in/daily-bulletin/. Accessed on 17 April 2020.
Government of Odisha. Department of Health and Family Welfare, Odisha. Available at: https://health.odisha.gov.in/. Accessed on 17 April 2020.
Policy Analysis Using Interrupted Time Series | edX. Available at: https://www.edx.org/course/policy-analysis-using-interrupted-time-series. Accessed on 17 April 2020.
R: The R Project for Statistical Computing. 2020. Available at: https://www.r-project.org/. Accessed on 17 April 2020.
State control room Tamil Nadu. Media Bulletin. 2020.
Endo A, van Leeuwen E, Baguelin M, Kucharski AJ, Russell TW, Diamond C, et al. Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts. medRxiv. 2020;9:1-5.
Nussbaumer-Streit B, Mayr V, Dobrescu AI, Chapman A, Persad E, Klerings I, et al. Quarantine alone or in combination with other public health measures to control COVID-19: a rapid review. Cochrane database Syst Rev. 2020;4:CD013574.
Mandal S, Bhatnagar T, Arinaminpathy N, Agarwal A, Chowdhury A, Murhekar M, et al. Prudent public health intervention strategies to control the coronavirus disease 2019 transmission in India: A mathematical model-based approach. Indian J Med Res. 2020;151(2 and 3):190-9.
Chatterjee K, Chatterjee K, Kumar A, Shankar S. Healthcare impact of COVID-19 epidemic in India: A stochastic mathematical model. Med J Armed Forces India. 2020;76(2):147-55.
Pulla Bangalore P. Covid-19: India imposes lockdown for 21 days and cases rise. Available at: http://group.bmj.com/group/rights-licensing/. Accessed on 11 April 2020.
Paixão ES, Rodrigues MS, Cardim LL, Oliveira JF, Costa M da CN, et al. Impact evaluation of Zika epidemic on congenital anomalies registration in Brazil: An interrupted time series analysis. Harley D, editor. PLoS Negl Trop Dis. 2019;13(9):e0007721.
Price J, Cheek E, Lippett S, Cubbon M, Gerding DN, Sambol SP, et al. Impact of an intervention to control Clostridium difficile infection on hospital- and community-onset disease; an interrupted time series analysis. Eur Soc Clin Infect Dis. 2010;16:1297-302.
Linden A. Using forecast modelling to evaluate treatment effects in single-group interrupted time series analysis. J Eval Clin Pract. 2018;24(4):695-700.
Selvaraj S, Farooqui HH, Mehta A. Does price regulation affect atorvastatin sales in India? An impact assessment through interrupted time series analysis. BMJ Open. 2019;9(1):e024200.
NITI Ayog G of I. NITI Aayog releases “Healthy States, Progressive India” Report. Press release. 2018. Available at: http://pib.nic.in/newsite/PrintRelease.aspx?relid=176418. Accessed on 19 October 2018.
