The Impact of China’s Lockdown Policy on the Incidence of COVID-19: An Interrupted Time Series Analysis

Background. Policy changes are often necessary to contain the detrimental impact of epidemics such as those brought about by coronavirus disease (COVID-19). In the earlier phases of the emergence of COVID-19, China was the first to impose strict restrictions on movement (lockdown) on January 23rd, 2...

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Autores principales: Mooketsi Molefi, John T. Tlhakanelo, Thabo Phologolo, Shimeles G. Hamda, Tiny Masupe, Billy Tsima, Vincent Setlhare, Yohana Mashalla, Douglas J. Wiebe
Formato: article
Lenguaje:EN
Publicado: Hindawi Limited 2021
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Acceso en línea:https://doaj.org/article/e62f56c61ba34b46a9051f731c2d0418
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Sumario:Background. Policy changes are often necessary to contain the detrimental impact of epidemics such as those brought about by coronavirus disease (COVID-19). In the earlier phases of the emergence of COVID-19, China was the first to impose strict restrictions on movement (lockdown) on January 23rd, 2020. A strategy whose effectiveness in curtailing COVID-19 was yet to be determined. We, therefore, sought to study the impact of the lockdown in reducing the incidence of COVID-19. Methods. Daily cases of COVID-19 that occurred in China which were registered between January 12th and March 30th, 2020, were extracted from the Johns Hopkins CSSE team COVID-19 ArcGIS® dashboards. Daily cases reported were used as data points in the series. Two interrupted series models were run: one with an interruption point of 23 January 2020 (model 1) and the other with a 14-day deferred interruption point of 6th February (model 2). For both models, the magnitude of change (before and after) and linear trend analyses were measured, and β-coefficients reported with 95% confidence interval (CI) for the precision. Results. Seventy-eight data points were used in the analysis. There was an 11% versus a 163% increase in daily cases in models 1 and 2, respectively, in the preintervention periods (p≤0.001). Comparing the period immediately following the intervention points to the counterfactual, there was a daily increase of 2,746% (p<0.001) versus a decline of 207% (p=0.802) in model 2. However, in both scenarios, there was a statistically significant drop in the daily cases predicted for this data and beyond when comparing the preintervention periods and postintervention periods (p<0.001). Conclusion. There was a significant decrease the COVID-19 daily cases reported in China following the institution of a lockdown, and therefore, lockdown may be used to curtail the burden of COVID-19.