Deciphering early-warning signals of SARS-CoV-2 elimination and resurgence from limited data at multiple scales.
J R Soc Interface
; 18(185): 20210569, 2021 12.
Article
in English
| MEDLINE | ID: covidwho-1575238
ABSTRACT
Inferring 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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Communicable Diseases
/
COVID-19
Type of study:
Observational study
Limits:
Humans
Country/Region as subject:
Oceania
Language:
English
Journal:
J R Soc Interface
Year:
2021
Document Type:
Article
Affiliation country:
Rsif.2021.0569
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