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A systematic review and meta-analysis reveals long and dispersive incubation period of COVID-19

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ABSTRACTBackgroundThe incubation period of SARS-CoV-2 remains uncertain, which has important implications for estimating transmission potential, forecasting epidemic trends, and decision-making in prevention and control.PurposeTo estimate the central tendency and dispersion for incubation period of COVID-19 and, in turn, assess the effect of a certain length of quarantine for close contacts in active monitoring.Data SourcesPubMed, Embase, medRxiv, bioRxiv, and arXiv, searched up to April 26, 2020Study SelectionCOVID-19 studies that described either individual-level incubation period data or summarized statistics for central tendency and dispersion measures of incubation period were recruited.Data ExtractionFrom each recruited study, either individual-level incubation period data or summarized statistics for central tendency and dispersion measures were extracted, as well as population characteristics including sample size, average age, and male proportion.Data SynthesisFifty-six studies encompassing 4 095 cases were included in this meta-analysis. The estimated median incubation period for general transmissions was 5.8 days [95% confidence interval (95%CI), 5.3 to 6.2 d]. Median and dispersion were higher for SARS-CoV-2 incubation compared to other viral respiratory infections. Furthermore, about 20 in 10 000 contacts in active monitoring would develop symptoms after 14 days, or below 1 in 10 000 for young-age infections or asymptomatic transmissions.LimitationSmall sample sizes for subgroups; some data were possibly used repeatedly in different studies; limited studies for outside mainland China; non-negligible intra-study heterogeneity.ConclusionThe long, dispersive incubation period of SARS-CoV-2 contributes to the global spread of COVID-19. Yet, a 14-day quarantine period is sufficient to trace and identify symptomatic infections, which while could be justified according to a better understanding of the crucial parameters.
Title: A systematic review and meta-analysis reveals long and dispersive incubation period of COVID-19
Description:
ABSTRACTBackgroundThe incubation period of SARS-CoV-2 remains uncertain, which has important implications for estimating transmission potential, forecasting epidemic trends, and decision-making in prevention and control.
PurposeTo estimate the central tendency and dispersion for incubation period of COVID-19 and, in turn, assess the effect of a certain length of quarantine for close contacts in active monitoring.
Data SourcesPubMed, Embase, medRxiv, bioRxiv, and arXiv, searched up to April 26, 2020Study SelectionCOVID-19 studies that described either individual-level incubation period data or summarized statistics for central tendency and dispersion measures of incubation period were recruited.
Data ExtractionFrom each recruited study, either individual-level incubation period data or summarized statistics for central tendency and dispersion measures were extracted, as well as population characteristics including sample size, average age, and male proportion.
Data SynthesisFifty-six studies encompassing 4 095 cases were included in this meta-analysis.
The estimated median incubation period for general transmissions was 5.
8 days [95% confidence interval (95%CI), 5.
3 to 6.
2 d].
Median and dispersion were higher for SARS-CoV-2 incubation compared to other viral respiratory infections.
Furthermore, about 20 in 10 000 contacts in active monitoring would develop symptoms after 14 days, or below 1 in 10 000 for young-age infections or asymptomatic transmissions.
LimitationSmall sample sizes for subgroups; some data were possibly used repeatedly in different studies; limited studies for outside mainland China; non-negligible intra-study heterogeneity.
ConclusionThe long, dispersive incubation period of SARS-CoV-2 contributes to the global spread of COVID-19.
Yet, a 14-day quarantine period is sufficient to trace and identify symptomatic infections, which while could be justified according to a better understanding of the crucial parameters.

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