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Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020

BACKGROUND: As of March 31, 2020 the ongoing COVID-19 epidemic that started in China in December 2019 is now generating local transmission around the world. The geographic heterogeneity and associated intervention strategies highlight the need to monitor in real time the transmission potential of CO...

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Autores principales: Tariq, Amna, Lee, Yiseul, Roosa, Kimberlyn, Blumberg, Seth, Yan, Ping, Ma, Stefan, Chowell, Gerardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217090/
https://www.ncbi.nlm.nih.gov/pubmed/32511436
http://dx.doi.org/10.1101/2020.02.21.20026435
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author Tariq, Amna
Lee, Yiseul
Roosa, Kimberlyn
Blumberg, Seth
Yan, Ping
Ma, Stefan
Chowell, Gerardo
author_facet Tariq, Amna
Lee, Yiseul
Roosa, Kimberlyn
Blumberg, Seth
Yan, Ping
Ma, Stefan
Chowell, Gerardo
author_sort Tariq, Amna
collection PubMed
description BACKGROUND: As of March 31, 2020 the ongoing COVID-19 epidemic that started in China in December 2019 is now generating local transmission around the world. The geographic heterogeneity and associated intervention strategies highlight the need to monitor in real time the transmission potential of COVID-19. Singapore provides a unique case example for monitoring transmission, as there have been multiple disease clusters, yet transmission remains relatively continued. METHODS: Here we estimate the effective reproduction number, R(t), of COVID-19 in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays as of March 17, 2020. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis that accounts for truncation of case counts. RESULTS: The local incidence curve displays sub-exponential growth dynamics, with the reproduction number following a declining trend and reaching an estimate at 0.7 (95% CI: 0.3, 1.0) during the first transmission wave by February 14, 2020 while the overall R based on the cluster size distribution as of March 17, 2020 was estimated at 0.6 (95% CI: 0.4, 1.02). The overall mean reporting delay was estimated at 6.4 days (95% CI: 5.8, 6.9), but it was shorter among imported cases compared to local cases (mean 4.3 vs. 7.6 days, Wilcoxon test, p<0.001). CONCLUSION: The trajectory of the reproduction number in Singapore underscores the significant effects of successful containment efforts in Singapore, but it also suggests the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission.
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spelling pubmed-72170902020-06-07 Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020 Tariq, Amna Lee, Yiseul Roosa, Kimberlyn Blumberg, Seth Yan, Ping Ma, Stefan Chowell, Gerardo medRxiv Article BACKGROUND: As of March 31, 2020 the ongoing COVID-19 epidemic that started in China in December 2019 is now generating local transmission around the world. The geographic heterogeneity and associated intervention strategies highlight the need to monitor in real time the transmission potential of COVID-19. Singapore provides a unique case example for monitoring transmission, as there have been multiple disease clusters, yet transmission remains relatively continued. METHODS: Here we estimate the effective reproduction number, R(t), of COVID-19 in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays as of March 17, 2020. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis that accounts for truncation of case counts. RESULTS: The local incidence curve displays sub-exponential growth dynamics, with the reproduction number following a declining trend and reaching an estimate at 0.7 (95% CI: 0.3, 1.0) during the first transmission wave by February 14, 2020 while the overall R based on the cluster size distribution as of March 17, 2020 was estimated at 0.6 (95% CI: 0.4, 1.02). The overall mean reporting delay was estimated at 6.4 days (95% CI: 5.8, 6.9), but it was shorter among imported cases compared to local cases (mean 4.3 vs. 7.6 days, Wilcoxon test, p<0.001). CONCLUSION: The trajectory of the reproduction number in Singapore underscores the significant effects of successful containment efforts in Singapore, but it also suggests the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission. Cold Spring Harbor Laboratory 2020-04-17 /pmc/articles/PMC7217090/ /pubmed/32511436 http://dx.doi.org/10.1101/2020.02.21.20026435 Text en http://creativecommons.org/licenses/by-nc/4.0/It is made available under a CC-BY-NC 4.0 International license (http://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Article
Tariq, Amna
Lee, Yiseul
Roosa, Kimberlyn
Blumberg, Seth
Yan, Ping
Ma, Stefan
Chowell, Gerardo
Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020
title Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020
title_full Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020
title_fullStr Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020
title_full_unstemmed Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020
title_short Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020
title_sort real-time monitoring the transmission potential of covid-19 in singapore, march 2020
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217090/
https://www.ncbi.nlm.nih.gov/pubmed/32511436
http://dx.doi.org/10.1101/2020.02.21.20026435
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