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Transmission onset distribution of COVID-19.
Chun, June Young; Baek, Gyuseung; Kim, Yongdai.
  • Chun JY; Department of Internal Medicine, National Cancer Center, Goyang, South Korea.
  • Baek G; Department of Statistics, Seoul National University, Seoul, South Korea.
  • Kim Y; Department of Statistics, Seoul National University, Seoul, South Korea. Electronic address: ydkim0903@gmail.com.
Int J Infect Dis ; 99: 403-407, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-695462
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
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ABSTRACT

OBJECTIVES:

The distribution of the transmission onset of COVID-19 relative to the symptom onset is a key parameter for infection control. It is often not easy to study the transmission onset time, as it is difficult to know who infected whom exactly when.

METHODS:

We inferred transmission onset time from 72 infector-infectee pairs in South Korea, either with known or inferred contact dates, utilizing the incubation period. Combining this data with known information of the infector's symptom onset, we could generate the transmission onset distribution of COVID-19, using Bayesian methods. Serial interval distribution could be automatically estimated from our data.

RESULTS:

We estimated the median transmission onset to be 1.31 days (standard deviation, 2.64 days) after symptom onset with a peak at 0.72 days before symptom onset. The pre-symptomatic transmission proportion was 37% (95% credible interval [CI], 16-52%). The median incubation period was estimated to be 2.87 days (95% CI, 2.33-3.50 days), and the median serial interval to be 3.56 days (95% CI, 2.72-4.44 days).

CONCLUSIONS:

Considering that the transmission onset distribution peaked with the symptom onset and the pre-symptomatic transmission proportion is substantial, the usual preventive measures might be too late to prevent SARS-CoV-2 transmission.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections Type of study: Prognostic study Topics: Long Covid Limits: Humans / Middle aged Country/Region as subject: Asia Language: English Journal: Int J Infect Dis Journal subject: Communicable Diseases Year: 2020 Document Type: Article Affiliation country: J.ijid.2020.07.075

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections Type of study: Prognostic study Topics: Long Covid Limits: Humans / Middle aged Country/Region as subject: Asia Language: English Journal: Int J Infect Dis Journal subject: Communicable Diseases Year: 2020 Document Type: Article Affiliation country: J.ijid.2020.07.075