Identifying High-Risk Events for COVID-19 Transmission: Estimating the Risk of Clustering Using Nationwide Data
Abstract
:1. Introduction
2. Materials and Methods
2.1. Cluster Surveillance Data
2.2. Event Frequency and Users
2.3. Estimating the Risk of Clustering
2.4. Sensitivity Analysis on the Estimates
2.5. Simulation-Based Bias Assessment
2.6. Evaluation on the Consistency of Reporting througout the Study Period
3. Results
3.1. Activity-Dependent Cluster Infection Risk Index
3.2. Rate Ratios of Activity-Dependent Risk
3.3. Sensitivity Analysis of the Risk Index and RR
3.4. Simulation-Based Bias Assessment
3.5. Evaluation on the Consistency of Reporting throughout the Study Period
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Category | Establishment Type | Definition of an Event | Type of Users | [Users] | [Days] | [Facilities] | [Hours] |
---|---|---|---|---|---|---|---|
Recreational facilities | Theater | Attend a performance | Audiences | 341.2 | 46,986 | 3.0 | |
Eating and drinking establishments with Karaoke facility | Visit stores/facilities | Users | 110.4 | 395.0 | 25,108 | 2.6 | |
Sports facility | 30.8 | 268.0 | 71,271 | 1.5 | |||
Beauty salon/Barber | 6.4 | 327.0 | 371,688 | 1.0 | |||
Welfare facility | Welfare facility for persons with disabilities | Stay for a night | Residents, Users | 27.5 | 395.0 | 5636 | 16.0 |
Elderly care facility | 32.2 | 395.0 | 28,352 | 16.0 | |||
Child welfare facility | 66.8 | 268.0 | 44,616 | 11.0 | |||
Health institute | Hospital | Stay for a night | Inpatients | 165.8 | 395.0 | 8300 | 16.0 |
Clinic | Visit a doctor | Outpatients | 41.1 | 323.0 | 102,616 | 0.5 | |
Dental clinic | 19.7 | 326.0 | 68,500 | 1.0 | |||
Eating and drinking establishment | Restaurant | Visit stores | Users | 127.4 | 323.0 | 1,279,784 | 1.0 |
Alcohol serving eating and drinking establishment | 42.9 | 323.0 | 264,359 | 2.0 | |||
Serviced entertaining bars and escort clubs | 57.0 | 323.0 | 61,857 | 2.0 | |||
Educational institution | University | Attend for a day | Students | 3667.4 | 187.0 | 795 | 5.0 |
High school | 634.4 | 237.0 | 4874 | 8.0 | |||
Middle school | 316.6 | 237.0 | 10,142 | 8.0 | |||
Elementary school | 322.7 | 237.0 | 19,525 | 7.0 | |||
Kindergarten | 111.2 | 237.0 | 9698 | 5.0 | |||
Cram school | 122.8 | 124.7 | 46,734 | 1.5 | |||
Public office and enterprises | Police station | Work for a day | Staffs | 246.2 | 268.0 | 1204 | 8.0 |
Local government office | 474.1 | 268.0 | 1971 | 8.0 | |||
Fire station | 68.2 | 268.0 | 2445 | 8.0 | |||
Workplace | 10.6 | 268.0 | 5,340,783 | 7.8 |
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Ueda, M.; Hayashi, K.; Nishiura, H. Identifying High-Risk Events for COVID-19 Transmission: Estimating the Risk of Clustering Using Nationwide Data. Viruses 2023, 15, 456. https://doi.org/10.3390/v15020456
Ueda M, Hayashi K, Nishiura H. Identifying High-Risk Events for COVID-19 Transmission: Estimating the Risk of Clustering Using Nationwide Data. Viruses. 2023; 15(2):456. https://doi.org/10.3390/v15020456
Chicago/Turabian StyleUeda, Minami, Katsuma Hayashi, and Hiroshi Nishiura. 2023. "Identifying High-Risk Events for COVID-19 Transmission: Estimating the Risk of Clustering Using Nationwide Data" Viruses 15, no. 2: 456. https://doi.org/10.3390/v15020456