tetano
Editor, Senior Moderator
Viruses
. 2023 Feb 6;15(2):456.
doi: 10.3390/v15020456.
Identifying High-Risk Events for COVID-19 Transmission: Estimating the Risk of Clustering Using Nationwide Data
Minami Ueda[SUP] 1 [/SUP], Katsuma Hayashi[SUP] 1 [/SUP], Hiroshi Nishiura[SUP] 1 [/SUP]
Affiliations
Abstract
The transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to be overdispersed, meaning that only a fraction of infected cases contributes to super-spreading. While cluster interventions are an effective measure for controlling pandemics due to the viruses' overdispersed nature, a quantitative assessment of the risk of clustering has yet to be sufficiently presented. Using systematically collected cluster surveillance data for coronavirus disease 2019 (COVID-19) from June 2020 to June 2021 in Japan, we estimated the activity-dependent risk of clustering in 23 establishment types. The analysis indicated that elderly care facilities, welfare facilities for people with disabilities, and hospitals had the highest risk of clustering, with 4.65 (95% confidence interval [CI]: 4.43-4.87), 2.99 (2.59-3.46), and 2.00 (1.88-2.12) cluster reports per million event users, respectively. Risks in educational settings were higher overall among older age groups, potentially being affected by activities with close and uncontrollable contact during extracurricular hours. In dining settings, drinking and singing increased the risk by 10- to 70-fold compared with regular eating settings. The comprehensive analysis of the COVID-19 cluster records provides an additional scientific basis for the design of customized interventions.
Keywords: contact tracing; disease outbreak; epidemiology; observational study; risk assessment; severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
. 2023 Feb 6;15(2):456.
doi: 10.3390/v15020456.
Identifying High-Risk Events for COVID-19 Transmission: Estimating the Risk of Clustering Using Nationwide Data
Minami Ueda[SUP] 1 [/SUP], Katsuma Hayashi[SUP] 1 [/SUP], Hiroshi Nishiura[SUP] 1 [/SUP]
Affiliations
- PMID: 36851670
- PMCID: PMC9967753
- DOI: 10.3390/v15020456
Abstract
The transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to be overdispersed, meaning that only a fraction of infected cases contributes to super-spreading. While cluster interventions are an effective measure for controlling pandemics due to the viruses' overdispersed nature, a quantitative assessment of the risk of clustering has yet to be sufficiently presented. Using systematically collected cluster surveillance data for coronavirus disease 2019 (COVID-19) from June 2020 to June 2021 in Japan, we estimated the activity-dependent risk of clustering in 23 establishment types. The analysis indicated that elderly care facilities, welfare facilities for people with disabilities, and hospitals had the highest risk of clustering, with 4.65 (95% confidence interval [CI]: 4.43-4.87), 2.99 (2.59-3.46), and 2.00 (1.88-2.12) cluster reports per million event users, respectively. Risks in educational settings were higher overall among older age groups, potentially being affected by activities with close and uncontrollable contact during extracurricular hours. In dining settings, drinking and singing increased the risk by 10- to 70-fold compared with regular eating settings. The comprehensive analysis of the COVID-19 cluster records provides an additional scientific basis for the design of customized interventions.
Keywords: contact tracing; disease outbreak; epidemiology; observational study; risk assessment; severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).