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Article: Deciphering early-warning signals of SARS-CoV-2 elimination and resurgence from limited data at multiple scales

TitleDeciphering early-warning signals of SARS-CoV-2 elimination and resurgence from limited data at multiple scales
Authors
Keywordsinfectious diseases
local transmission
SARS-CoV-2 elimination
effective reproduction numbers
COVID-19
Issue Date2021
PublisherThe Royal Society. The Journal's web site is located at http://publishing.royalsociety.org/index.cfm?page=1572
Citation
Journal of the Royal Society Interface, 2021, v. 18 n. 185, p. article no. 20210569 How to Cite?
AbstractInferring the transmission potential of an infectious disease during low-incidence periods following epidemic waves is crucial for preparedness. In such periods, scarce data may hinder existing inference methods, blurring early-warning signals essential for discriminating between the likelihoods of resurgence versus elimination. Advanced insight into whether elevating caseloads (requiring swift community-wide interventions) or local elimination (allowing controls to be relaxed or refocussed on case-importation) might occur can separate decisive from ineffective policy. By generalizing and fusing recent approaches, we propose a novel early-warning framework that maximizes the information extracted from low-incidence data to robustly infer the chances of sustained local transmission or elimination in real time, at any scale of investigation (assuming sufficiently good surveillance). Applying this framework, we decipher hidden disease-transmission signals in prolonged low-incidence COVID-19 data from New Zealand, Hong Kong and Victoria, Australia. We uncover how timely interventions associate with averting resurgent waves, support official elimination declarations and evidence the effectiveness of the rapid, adaptive COVID-19 responses employed in these regions.
Persistent Identifierhttp://hdl.handle.net/10722/309359
ISSN
2023 Impact Factor: 3.7
2023 SCImago Journal Rankings: 1.101
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorParag, KV-
dc.contributor.authorCowling, BJ-
dc.contributor.authorDonnelly, CA-
dc.date.accessioned2021-12-29T02:13:59Z-
dc.date.available2021-12-29T02:13:59Z-
dc.date.issued2021-
dc.identifier.citationJournal of the Royal Society Interface, 2021, v. 18 n. 185, p. article no. 20210569-
dc.identifier.issn1742-5689-
dc.identifier.urihttp://hdl.handle.net/10722/309359-
dc.description.abstractInferring the transmission potential of an infectious disease during low-incidence periods following epidemic waves is crucial for preparedness. In such periods, scarce data may hinder existing inference methods, blurring early-warning signals essential for discriminating between the likelihoods of resurgence versus elimination. Advanced insight into whether elevating caseloads (requiring swift community-wide interventions) or local elimination (allowing controls to be relaxed or refocussed on case-importation) might occur can separate decisive from ineffective policy. By generalizing and fusing recent approaches, we propose a novel early-warning framework that maximizes the information extracted from low-incidence data to robustly infer the chances of sustained local transmission or elimination in real time, at any scale of investigation (assuming sufficiently good surveillance). Applying this framework, we decipher hidden disease-transmission signals in prolonged low-incidence COVID-19 data from New Zealand, Hong Kong and Victoria, Australia. We uncover how timely interventions associate with averting resurgent waves, support official elimination declarations and evidence the effectiveness of the rapid, adaptive COVID-19 responses employed in these regions.-
dc.languageeng-
dc.publisherThe Royal Society. The Journal's web site is located at http://publishing.royalsociety.org/index.cfm?page=1572-
dc.relation.ispartofJournal of the Royal Society Interface-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectinfectious diseases-
dc.subjectlocal transmission-
dc.subjectSARS-CoV-2 elimination-
dc.subjecteffective reproduction numbers-
dc.subjectCOVID-19-
dc.titleDeciphering early-warning signals of SARS-CoV-2 elimination and resurgence from limited data at multiple scales-
dc.typeArticle-
dc.identifier.emailCowling, BJ: bcowling@hku.hk-
dc.identifier.authorityCowling, BJ=rp01326-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1098/rsif.2021.0569-
dc.identifier.pmid34905965-
dc.identifier.pmcidPMC8672070-
dc.identifier.scopuseid_2-s2.0-85122903698-
dc.identifier.hkuros331314-
dc.identifier.volume18-
dc.identifier.issue185-
dc.identifier.spagearticle no. 20210569-
dc.identifier.epagearticle no. 20210569-
dc.identifier.isiWOS:000730112500004-
dc.publisher.placeUnited Kingdom-

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