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The incubation period of COVID-19: A rapid systematic review and meta-analysis of observational research
Preprint
in English
| medRxiv
| ID: ppmedrxiv-20073957
ABSTRACT
BackgroundReliable estimates of the incubation period are important for decision making around the control of infectious diseases. Knowledge of the incubation period distribution can be used directly to inform decision-making or as inputs into mathematical models. ObjectivesThe aim of this study was to conduct a rapid systematic review and meta-analysis of estimates of the incubation periods of COVID-19. DesignRapid systematic review and meta-analysis of observational research Data sourcesPublications on the electronic databases PubMed, Google Scholar, MedRxiv and BioRxiv were searched. The search was not limited to peer-reviewed published data, but also included pre-print articles. Study appraisal and synthesis methodsStudies were selected for meta-analysis if they reported either the parameters and confidence intervals of the distributions fit to the data, or sufficient information to facilitate calculation of those values. The majority of studies suitable for inclusion in the final analysis modelled incubation period as a lognormal distribution. We conducted a random effects meta-analysis of the parameters of this distribution. ResultsThe incubation period distribution may be modelled with a lognormal distribution with pooled mu and sigma parameters of 1.63 (1.51, 1.75) and 0.50 (0.45, 0.55) respectively. The corresponding mean was 5.8 (5.01, 6.69 days). It should be noted that uncertainty increases towards the tail of the distribution the pooled parameter estimates resulted in a median incubation period of 5.1 (4.5, 5.8) days, whereas the 95th percentile was 11.6 (9.5, 14.2) days. Conclusions and implicationsThe choice of which parameter values are adopted will depend on how the information is used, the associated risks and the perceived consequences of decisions to be taken. These recommendations will need to be revisited once further relevant information becomes available. Finally, we present an RShiny app that facilitates updating these estimates as new data become available. ARTICLE SUMMARYO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIThis study provides a pooled estimate of the distribution of incubation periods which may be used in subsequent modelling studies or to inform decision-making C_LIO_LIThis estimate will need to be revisited as subsequent data become available. We present an RShiny app to allow the meta-analysis to be updated with new estimates C_LI
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Full text:
Available
Collection:
Preprints
Database:
medRxiv
Type of study:
Observational study
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Prognostic study
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Rct
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Review
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Systematic review
Language:
English
Year:
2020
Document type:
Preprint