This paper is in the following e-collection/theme issue:

Surveillance Systems (462) JMIR Theme Issue: COVID-19 Special Issue (2452) Innovative Methods in Public Health and Surveillance (332) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Infectious Diseases (non-STD/STI) (1575) Outbreak and Pandemic Preparedness and Management (1727)

Published on in Vol 8, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40866, first published .
New Surveillance Metrics for Alerting Community-Acquired Outbreaks of Emerging SARS-CoV-2 Variants Using Imported Case Data: Bayesian Markov Chain Monte Carlo Approach

New Surveillance Metrics for Alerting Community-Acquired Outbreaks of Emerging SARS-CoV-2 Variants Using Imported Case Data: Bayesian Markov Chain Monte Carlo Approach

New Surveillance Metrics for Alerting Community-Acquired Outbreaks of Emerging SARS-CoV-2 Variants Using Imported Case Data: Bayesian Markov Chain Monte Carlo Approach

Authors of this article:

Amy Ming-Fang Yen1 Author Orcid Image ;   Tony Hsiu-Hsi Chen2 Author Orcid Image ;   Wei-Jung Chang2 Author Orcid Image ;   Ting-Yu Lin2 Author Orcid Image ;   Grace Hsiao-Hsuan Jen1 Author Orcid Image ;   Chen-Yang Hsu2, 3 Author Orcid Image ;   Sen-Te Wang4, 5 Author Orcid Image ;   Huong Dang6 Author Orcid Image ;   Sam Li-Sheng Chen1, 7 Author Orcid Image
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