Incorporating temporal distribution of population-level viral load enables real-time estimation of COVID-19 transmission.
Nat Commun
; 13(1): 1155, 2022 03 03.
Article
in English
| MEDLINE | ID: covidwho-1730286
ABSTRACT
Many locations around the world have used real-time estimates of the time-varying effective reproductive number ([Formula see text]) of COVID-19 to provide evidence of transmission intensity to inform control strategies. Estimates of [Formula see text] are typically based on statistical models applied to case counts and typically suffer lags of more than a week because of the latent period and reporting delays. Noting that viral loads tend to decline over time since illness onset, analysis of the distribution of viral loads among confirmed cases can provide insights into epidemic trajectory. Here, we analyzed viral load data on confirmed cases during two local epidemics in Hong Kong, identifying a strong correlation between temporal changes in the distribution of viral loads (measured by RT-qPCR cycle threshold values) and estimates of [Formula see text] based on case counts. We demonstrate that cycle threshold values could be used to improve real-time [Formula see text] estimation, enabling more timely tracking of epidemic dynamics.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Viral Load
/
SARS-CoV-2
/
COVID-19
/
Epidemiological Models
Type of study:
Observational study
Limits:
Humans
Country/Region as subject:
Asia
Language:
English
Journal:
Nat Commun
Journal subject:
Biology
/
Science
Year:
2022
Document Type:
Article
Affiliation country:
S41467-022-28812-9
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