About: Estimating pre-symptomatic transmission of COVID-19: a secondary analysis using published data

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About: Estimating pre-symptomatic transmission of COVID-19: a secondary analysis using published data Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Estimating pre-symptomatic transmission of COVID-19: a secondary analysis using published data
Creator	Griffin, John More, Simon Barber, Ann Butler, Francis Byrne, Andrew Casey, Miriam Collins, Áine Hunt, Kevin Lane, Elizabeth Madden, Jamie Mcaloon, Conor O'brien, Kirsty Wall, Patrick Walsh, Kieran Mc Evoy, David
topic	covid:a77cc03d2656359b108c42c1d03214048b2eb366#this
Source	MedRxiv
abstract	Background: Understanding the extent of virus transmission that can occur before symptom onset is vital for targeting control measures against the global pandemic of COVID-19. Objective: Estimation of (1) the proportion of pre-symptomatic transmission of COVID-19 that can occur and (2) timing of transmission relative to symptom onset. Design: Secondary analysis of published data Data sources: Meta-analysis of COVID-19 incubation period and a rapid systematic review of serial interval and generation time, which are published separately. Methods: Simulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset were calculated and the proportion of pre-symptomatic transmission was estimated. Results: A total of 23 estimates of serial interval and five estimates of generation time from 17 publications were included. These came from nine different data source categories (presented here in descending order of the proportion of pre-symptomatic transmission): Hong Kong, Tianjin, pooled data from Hong Kong and Shenzhen, Singapore, Mainland China excluding Hubei, mixed sources, Shenzhen, northern Italy and Wuhan. Transmission time relative to symptom onset ranged from a mean of 2.05 days before symptom onset for Hong Kong to 1.72 days after symptom onset for Wuhan. Proportion of pre-symptomatic transmission ranged from 33.7% in Wuhan to 72.7% in Hong Kong. Based on individual estimates, transmission time relative to symptom onset ranged from mean of 2.95 days before symptom onset to 1.72 days after symptom onset and proportion of pre-symptomatic transmission ranged from 33.7% to 79.9%. Simple unweighted pooling of estimates based on serial intervals resulted in a mean time of transmission of 0.67 days before symptoms, and an estimated 56.1% of transmission occurring in the pre-symptomatic period. Conclusions: Contact rates between symptomatic infectious and susceptible people are likely to influence the proportion of pre-symptomatic transmission. There is substantial potential for pre-symptomatic transmission of COVID-19 in a range of different contexts. Our work suggests that transmission of SARS-CoV-2 is most likely in the day before symptom onset whereas estimates suggesting most pre-symptomatic transmission highlighted a mean transmission times almost 3 days before symptom onset. These findings highlight the urgent need for extremely rapid and effective case detection, contact tracing and quarantine measures if strict social distancing measures are to be eased.
has issue date	2020-05-11(xsd:dateTime)
bibo:doi	10.1101/2020.05.08.20094870
has license	medrxiv
sha1sum (hex)	a77cc03d2656359b108c42c1d03214048b2eb366
schema:url	https://doi.org/10.1101/2020.05.08.20094870
resource representing a document's title	Estimating pre-symptomatic transmission of COVID-19: a secondary analysis using published data
resource representing a document's body	covid:a77cc03d2656359b108c42c1d03214048b2eb366#body_text
is http://vocab.deri.ie/void#inDataset of	proxy:http/ns.inria.fr/covid19/a77cc03d2656359b108c42c1d03214048b2eb366
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