Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Jul 8, 2022
Date Accepted: Oct 18, 2022
Date Submitted to PubMed: Oct 20, 2022
New Surveillance Metrics for Alerting Community-acquired Outbreak of the Emerging SARS-CoV-2 Variants Using Imported Cases: A Bayesian Markov Chain Monte Carlo (MCMC) Approach
ABSTRACT
Background:
Global transmission from imported cases to domestic cluster infection is often the main route for the resultant community-acquired outbreaks facing the emerging SARS-CoV-2 variants.
Objective:
This study aimed to demonstrate a new surveillance model for forestalling community-acquired outbreak through the monitoring of small domestic cluster infection transmitted through imported cases.
Methods:
We used Taiwanese COVID-19 epidemic data from D614G to Omicron periods to illustrate such an importation-cluster-community infection surveillance model by estimating the increased risk of domestic cluster infection per one imported case for providing alert thresholds of community-acquired infection.
Results:
There was no community-acquired outbreak due to effective containment measures guided by the alert threshold of the proposed surveillance model during 614DG and Delta period. However, there were a large-scale community-acquired outbreak of Alpha VOC in mid-May 2021. During the Omicron period, even with 77% coverage rate of vaccination that may substantially reduce the risk of domestic cluster infection through imported cases, the surveillance of imported cases still found the observed cases exceeding the alert threshold, say 5.2%, around late Mar 2022, due to the waning immunity of vaccine.
Conclusions:
The proposed importation-cluster-community infection surveillance model can be used as a global vigilance mode for forestalling large-scale community-acquired outbreak of the emerging SARS-CoV-2 VOCs.
Citation
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