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 (Preprint) (2022)
Background: Global transmission from imported cases to domestic cluster infections is often the origin of local community-acquired outbreaks when facing emerging SARS-CoV-2 variants.
Objective: We aimed to develop new surveillance metrics for alerting emerging community-acquired outbreaks arising from new strains by monitoring the risk of small domestic cluster infections originating from few imported cases of emerging variants.
Methods: We used Taiwanese COVID-19 weekly data on imported cases, domestic cluster infections, and community-acquired outbreaks. The study period included the D614G strain in February 2020, the Alpha and Delta variants of concern (VOCs) in 2021, and the Omicron BA.1 and BA.2 VOCs in April 2022. The number of cases arising from domestic cluster infection caused by imported cases (Dci/Imc) per week was used as the SARS-CoV-2 strain-dependent surveillance metric for alerting local community-acquired outbreaks. Its upper 95% credible interval was used as the alert threshold for guiding the rapid preparedness of containment measures, including nonpharmaceutical interventions (NPIs), testing, and vaccination. The 2 metrics were estimated by using the Bayesian Monte Carlo Markov Chain method underpinning the directed acyclic graphic diagram constructed by the extra-Poisson (random-effect) regression model. The proposed model was also used to assess the most likely week lag of imported cases prior to the current week of domestic cluster infections.
Results: A 1-week lag of imported cases prior to the current week of domestic cluster infections was considered optimal. Both metrics of Dci/Imc and the alert threshold varied with SARS-CoV-2 variants and available containment measures. The estimates were 9.54% and 12.59%, respectively, for D614G and increased to 14.14% and 25.10%, respectively, for the Alpha VOC when only NPIs and testing were available. The corresponding figures were 10.01% and 13.32% for the Delta VOC, but reduced to 4.29% and 5.19% for the Omicron VOC when NPIs, testing, and vaccination were available. The rapid preparedness of containment measures guided by the estimated metrics accounted for the lack of community-acquired outbreaks during the D614G period, the early Alpha VOC period, the Delta VOC period, and the Omicron VOC period between BA.1 and BA.2. In contrast, community-acquired outbreaks of the Alpha VOC in mid-May 2021, Omicron BA.1 VOC in January 2022, and Omicron BA.2 VOC from April 2022 onwards, were indicative of the failure to prepare containment measures guided by the alert threshold.
Conclusions: We developed new surveillance metrics for estimating the risk of domestic cluster infections with increasing imported cases and its alert threshold for community-acquired infections varying with emerging SARS-CoV-2 strains and the availability of containment measures. The use of new surveillance metrics is important in the rapid preparedness of containment measures for averting large-scale community-acquired outbreaks arising from emerging imported SARS-CoV-2 variants.
CitationYen AM-F, Chen TH-H, Chang W-J, Lin T-Y, Jen GH-H, Hsu C-Y, Wang S-T, Dang H, Chen SL-S 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 (Preprint). JMIR Public Health and Surveillance.
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KeywordsCOVID-19; imported case; surveillance metric; early detection; community-acquired outbreak
ANZSRC Fields of Research42 - Health sciences::4202 - Epidemiology::420202 - Disease surveillance
42 - Health sciences::4202 - Epidemiology::420207 - Major global burdens of disease
42 - Health sciences::4203 - Health services and systems::420310 - Health surveillance
42 - Health sciences::4206 - Public health
RightsAll rights reserved unless otherwise stated
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