The Impact of China's Lockdown Policy on the Incidence of COVID-19: An Interrupted Time Series Analysis.
Journal
BioMed research international
ISSN: 2314-6141
Titre abrégé: Biomed Res Int
Pays: United States
ID NLM: 101600173
Informations de publication
Date de publication:
2021
2021
Historique:
received:
09
06
2021
accepted:
28
09
2021
entrez:
1
11
2021
pubmed:
2
11
2021
medline:
9
11
2021
Statut:
epublish
Résumé
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. 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 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 ( 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.
Sections du résumé
BACKGROUND
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
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
RESULTS
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 (
CONCLUSION
CONCLUSIONS
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.
Identifiants
pubmed: 34722775
doi: 10.1155/2021/9498029
pmc: PMC8553467
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
9498029Informations de copyright
Copyright © 2021 Mooketsi Molefi et al.
Déclaration de conflit d'intérêts
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Références
Yale J Biol Med. 2021 Mar 31;94(1):13-21
pubmed: 33795979
N Engl J Med. 2020 Feb 20;382(8):727-733
pubmed: 31978945
Quant Biol. 2020 Mar 11;:1-9
pubmed: 32219006
Indian J Pediatr. 2020 Apr;87(4):281-286
pubmed: 32166607
Lancet. 2020 Feb 29;395(10225):689-697
pubmed: 32014114
J Epidemiol Glob Health. 2020 Mar;10(1):1-3
pubmed: 32175703
Risk Manag Healthc Policy. 2020 Sep 23;13:1695-1700
pubmed: 33061703
Prev Chronic Dis. 2015 Jun 25;12:E101
pubmed: 26111157
J Travel Med. 2020 May 18;27(3):
pubmed: 32181488
Lancet. 2020 Feb 15;395(10223):507-513
pubmed: 32007143
JAMA. 2020 May 12;323(18):1843-1844
pubmed: 32159775
Nature. 2020 Mar;579(7798):265-269
pubmed: 32015508
Pathogens. 2020 Mar 04;9(3):
pubmed: 32143502
Acad Pediatr. 2013 Nov-Dec;13(6 Suppl):S38-44
pubmed: 24268083