Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022.

COVID-19 Disease surveillance Emerging clusters SaTScan Space-time pattern

Journal

Archives of public health = Archives belges de sante publique
ISSN: 0778-7367
Titre abrégé: Arch Public Health
Pays: England
ID NLM: 9208826

Informations de publication

Date de publication:
26 Jul 2022
Historique:
received: 29 04 2022
accepted: 24 06 2022
entrez: 26 7 2022
pubmed: 27 7 2022
medline: 27 7 2022
Statut: epublish

Résumé

Up to April 2022, there were six waves of infection of coronavirus disease 2019 (COVID-19) in Japan. As the outbreaks continue to grow, it is critical to detect COVID-19's clusters to allocate health resources and improve decision-making substantially. This study aimed to identify active clusters of COVID-19 in Nagasaki Prefecture and form the spatiotemporal pattern of high-risk areas in different infection periods. We used the prospective space-time scan statistic to detect emerging COVID-19 clusters and examine the relative risk in five consecutive periods from April 1, 2020 to April 7, 2022, in Nagasaki Prefecture. The densely inhabited districts (DIDs) in Nagasaki City have remained the most affected areas since December 2020. Most of the confirmed cases in the early period of each wave had a history of travelling to other prefectures. Community-level transmissions are suggested by the quick expansion of spatial clusters from urban areas to rural areas and remote islands. Moreover, outbreaks in welfare facilities and schools may lead to an emerging cluster in Nagasaki Prefecture's rural areas. This study gives an overall analysis of the transmission dynamics of the COVID-19 pandemic in Nagasaki Prefecture, based on the number of machi-level daily cases. Furthermore, the findings in different waves can serve as references for subsequent pandemic prevention and control. This method helps the health authorities track and investigate outbreaks of COVID-19 that are specific to these environments, especially in rural areas where healthcare resources are scarce.

Sections du résumé

BACKGROUND BACKGROUND
Up to April 2022, there were six waves of infection of coronavirus disease 2019 (COVID-19) in Japan. As the outbreaks continue to grow, it is critical to detect COVID-19's clusters to allocate health resources and improve decision-making substantially. This study aimed to identify active clusters of COVID-19 in Nagasaki Prefecture and form the spatiotemporal pattern of high-risk areas in different infection periods.
METHODS METHODS
We used the prospective space-time scan statistic to detect emerging COVID-19 clusters and examine the relative risk in five consecutive periods from April 1, 2020 to April 7, 2022, in Nagasaki Prefecture.
RESULTS RESULTS
The densely inhabited districts (DIDs) in Nagasaki City have remained the most affected areas since December 2020. Most of the confirmed cases in the early period of each wave had a history of travelling to other prefectures. Community-level transmissions are suggested by the quick expansion of spatial clusters from urban areas to rural areas and remote islands. Moreover, outbreaks in welfare facilities and schools may lead to an emerging cluster in Nagasaki Prefecture's rural areas.
CONCLUSIONS CONCLUSIONS
This study gives an overall analysis of the transmission dynamics of the COVID-19 pandemic in Nagasaki Prefecture, based on the number of machi-level daily cases. Furthermore, the findings in different waves can serve as references for subsequent pandemic prevention and control. This method helps the health authorities track and investigate outbreaks of COVID-19 that are specific to these environments, especially in rural areas where healthcare resources are scarce.

Identifiants

pubmed: 35883103
doi: 10.1186/s13690-022-00921-3
pii: 10.1186/s13690-022-00921-3
pmc: PMC9315091
doi:

Types de publication

Journal Article

Langues

eng

Pagination

176

Subventions

Organisme : Nagasaki Prefectural Research Project
ID : 2020FY-NIEP-Cai
Organisme : The Major Health Research Project of Fujian Province
ID : 2021ZD01001

Informations de copyright

© 2022. The Author(s).

Références

PLoS One. 2020 Jun 11;15(6):e0234292
pubmed: 32525881
Lancet. 2021 Jun 19;397(10292):2334-2335
pubmed: 34089658
J Psychiatr Res. 2021 Apr;136:296-305
pubmed: 33631655
Stat Med. 2015 Mar 30;34(7):1094-5
pubmed: 25754922
Int J Environ Res Public Health. 2020 Aug 14;17(16):
pubmed: 32824030
Vaccines (Basel). 2021 Jan 14;9(1):
pubmed: 33466675
Int J Infect Dis. 2020 Jul;96:371-375
pubmed: 32425637
Jpn J Infect Dis. 2020 Sep 24;73(5):391-393
pubmed: 32350228
Int J Environ Res Public Health. 2022 Apr 19;19(9):
pubmed: 35564325
Prog Disaster Sci. 2020 Apr;6:100090
pubmed: 34171010
BMJ Open. 2021 Feb 15;11(2):e042002
pubmed: 33589454
Ann Oncol. 2020 Jul;31(7):894-901
pubmed: 32224151
Public Health. 2020 Oct;187:157-160
pubmed: 32980782
Infect Dis Model. 2020;5:580-587
pubmed: 32844135
Int J Infect Dis. 2020 Sep;98:328-333
pubmed: 32634584
Sci Rep. 2021 Sep 23;11(1):18951
pubmed: 34556681
Transp Res Interdiscip Perspect. 2021 Mar;9:100288
pubmed: 34173482
Clin Pract. 2021 Oct 21;11(4):778-784
pubmed: 34698149
J Infect. 2022 Feb;84(2):248-288
pubmed: 34390754
Transp Res Interdiscip Perspect. 2020 Sep;7:100212
pubmed: 34173468
Cell. 2020 Nov 12;183(4):996-1012.e19
pubmed: 33010815
Spat Spatiotemporal Epidemiol. 2020 Aug;34:100354
pubmed: 32807396
Drug Discov Ther. 2022;16(1):30-36
pubmed: 35264472
BMC Infect Dis. 2017 Aug 21;17(1):578
pubmed: 28826399
J Geogr Syst. 2021;23(1):7-36
pubmed: 33716567
Am J Public Health. 1998 Sep;88(9):1377-80
pubmed: 9736881
Cities. 2022 Jan;120:103502
pubmed: 34703071
J Med Virol. 2020 Nov;92(11):2543-2550
pubmed: 32470164
Nature. 2020 Sep;585(7825):410-413
pubmed: 32365354
Biosci Trends. 2021 Mar 15;15(1):1-8
pubmed: 33518668
Lancet. 2022 Jan 29;399(10323):412-413
pubmed: 35065007
Int J Environ Res Public Health. 2020 May 31;17(11):
pubmed: 32486403
Biometrics. 2007 Mar;63(1):109-18
pubmed: 17447935
Appl Geogr. 2020 May;118:102202
pubmed: 32287518
Emerg Infect Dis. 2021 Sep;27(9):2251-2260
pubmed: 34423761
Infect Dis Poverty. 2021 Oct 7;10(1):122
pubmed: 34620243

Auteurs

Yixiao Lu (Y)

Department of Public Health, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, 852-8523, Japan.

Guoxi Cai (G)

Department of Public Health, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, 852-8523, Japan.
Public Health and Hygiene Research Department, Nagasaki Prefectural Institute of Environment and Public Health, Nagasaki, 856-0026, Japan.
Department of International Health and Medical Anthropology, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Nagasaki, 852-8523, Japan.

Zhijian Hu (Z)

Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, 350122, Fujian Province, China.

Fei He (F)

Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, 350122, Fujian Province, China. i.fei.he@fjmu.edu.cn.

Yixian Jiang (Y)

Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, 350122, Fujian Province, China.

Kiyoshi Aoyagi (K)

Department of Public Health, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, 852-8523, Japan.

Classifications MeSH