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.
【초록키워드】 COVID-19, coronavirus disease, lockdown, Epidemics, Intervention, Policy, China, Effectiveness, change, Analysis, detrimental, Precision, 95% confidence interval, Registered, postintervention, significant decrease, Daily, Result, predicted, occurred, reported, linear, were used, reducing, magnitude, increase in, statistically significant, were measured, curtail, incidence of COVID-19, Johns Hopkin, preintervention, 【제목키워드】 Policy, China, Impact, time, Interrupted, Sery,