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Health Promot Perspect. 2022;12(2): 192-199.
doi: 10.34172/hpp.2022.24
PMID: 36276422
PMCID: PMC9508386
Scopus ID: 85147776295
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Original Article

A problem of self-isolation in Japan: The relationship between self-isolation and COVID-19 community case

Nam Xuan Ha 1,2 ORCID logo, Truong Le-Van 2,3 ORCID logo, Nguyen Hai Nam 2,4,5 ORCID logo, Akshay Raut 2,6 ORCID logo, Joseph Varney 2,7 ORCID logo, Nguyen Tien Huy 2,8* ORCID logo

1 Hue University of Medicine and Pharmacy, Hue University, Hue City, Vietnam
2 Online Research Club (http://www.onlineresearchclub.org), Nagasaki, Japan
3 Traditional Medicine Hospital of Ministry of Public Security, Hanoi, Vietnam
4 Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
5 Global Clinical Scholars Research Training Program, Harvard Medical School, Boston, Massachusetts, USA
6 St. George’s Hospital, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai 400001, India
7 American University of the Caribbean, School of Medicine, Sint Maarten, Sint Maarten
8 School of Tropical Diseases and Global Health, Nagasaki University, 1-12-4 Sakamoto, Nagasaki 852-8523, Japan
*Corresponding Author: Corresponding Author: Nguyen Tien Huy, Email: , Email: tienhuy@nagasatienhuy@nagasaki-u.ac.jpki-u.ac.jp

Abstract

Background: The Japanese government advised mild or asymptomatic coronavirus disease-2019 (COVID-19) cases to self-isolate at home, while more severe individuals were treated at health posts. Poor compliance with self-isolation could be a potential reason for the new outbreak. Our study aimed to find out the correlation between the rising new cases of COVID-19 and home-based patients in Japan.

Methods: A secondary data analysis study was conducted with the data from COVID-19- involved databases collected from Johns Hopkins University, Japanese Ministry of Health, Labour and Welfare, and Community Mobility Reports of Google. New community cases, stringency index, number of tests, and active cases were analyzed. Using a linear regression model, an independent variable was utilized for a given date to predict the future number of community cases.

Results: Research results show that outpatient cases, the stringency, and Google Mobility Trend were all significantly associated with the number of COVID-19 community cases from the sixth day to the ninth day. The model predicting community cases on the eighth day (R2=0.8906) was the most appropriate showing outpatients, residential index, grocery and pharmacy index, retail and recreation index, and workplaces index were positively related (β1=24.2, 95% CI: 20.3– 26.3, P<0.0001; β2=277.7, 95% CI: 171.8–408.2, P<0.0001; β3=112.4, 95% CI: 79.8–158.3, P<0.0001; β4=73.1, 95% CI: 53- 04.4, P<0.0001; β5=57.2, 95% CI: 25.2–96.8, P=0.001, respectively). In contrast, inpatients, park index, and adjusted stringency index were negatively related to the number of community cases (β6=-2.8, 95% CI: -3.9 – -1.6, P<0.0001; β7=-33, 95% CI: -43.6 – -27, P<0.0001; β8=-14.4, 95% CI: -20.1– -12, P<0.0001, respectively).

Conclusion: Outpatient cases and indexes of Community Mobility Reports were associated with COVID-19 community cases.

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Submitted: 04 Feb 2022
Revision: 10 Apr 2022
Accepted: 15 Apr 2022
ePublished: 20 Aug 2022
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