Evidence map›Paper›PMID 34579681›Full record

ArticleBMC public health2021

Modeling the effect of age on quantiles of the incubation period distribution of COVID-19.

Xiaohui Liu, Lei Wang, Xiansi Ma, Jiewen Wang, Liwen Wu

Abstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiaohui Liu *School of Statistics, Jiangxi University of Finance and Economics, No.169, East Shuanggang Road, Nanchang, Jiangxi Province, 330013, China.
Lei WangNational Engineering Laboratory for Educational Big Data, Central China Normal University, NO.152 Luoyu Road, Wuhan, Hubei Province, 430079, China. leiw@mails.ccnu.edu.cn.
Xiansi MaSchool of Statistics, Jiangxi University of Finance and Economics, No.169, East Shuanggang Road, Nanchang, Jiangxi Province, 330013, China.
Jiewen WangSchool of Statistics, Jiangxi University of Finance and Economics, No.169, East Shuanggang Road, Nanchang, Jiangxi Province, 330013, China.
Liwen Wu *Department of Neurology, Hunan children's Hospital, No.86 Ziyuan Road, Changsha, Hunan Province, 410000, China.

Funding

China Postdoctoral Science Foundation 2016M600511China Postdoctoral Science Foundation 2017T100475national natural science foundation of china 11601197national natural science foundation of china 11971208national natural science foundation of china 81671297natural science foundation of jiangxi province 20192BAB201005Natural Science Foundation of Jiangxi Province (CN) 20171ACB21030
6 · The paper itself

Abstract

backgroundThe novel coronavirus SARS-CoV-2 (coronavirus disease 2019, COVID-19) has caused serious consequences on many aspects of social life throughout the world since the first case of pneumonia with unknown etiology was identified in Wuhan, Hubei province in China in December 2019. Note that the incubation period distribution is key to the prevention and control efforts of COVID-19. This study aimed to investigate the conditional distribution of the incubation period of COVID-19 given the age of infected cases and estimate its corresponding quantiles from the information of 2172 confirmed cases from 29 provinces outside Hubei in China.

methodsWe collected data on the infection dates, onset dates, and ages of the confirmed cases through February 16th, 2020. All the data were downloaded from the official websites of the health commission. As the epidemic was still ongoing at the time we collected data, the observations subject to biased sampling. To address this issue, we developed a new maximum likelihood method, which enables us to comprehensively study the effect of age on the incubation period.

resultsBased on the collected data, we found that the conditional quantiles of the incubation period distribution of COVID-19 vary by age. In detail, the high conditional quantiles of people in the middle age group are shorter than those of others while the low quantiles did not show the same differences. We estimated that the 0.95-th quantile related to people in the age group 23 ∼55 is less than 15 days.

conclusionsObserving that the conditional quantiles vary across age, we may take more precise measures for people of different ages. For example, we may consider carrying out an age-dependent quarantine duration in practice, rather than a uniform 14-days quarantine period. Remarkably, we may need to extend the current quarantine duration for people aged 0 ∼22 and over 55 because the related 0.95-th quantiles are much greater than 14 days.

Indexed as

COVID-19Infectious Disease Incubation PeriodAdolescentAdultAgedAged, 80 and overChildChild, PreschoolChinaEpidemicsHumansInfantInfant, NewbornMiddle AgedQuarantineSARS-CoV-2Biased samplingConditional quantilesCOVID-19Incubation period

Identifiers

PMID34579681
PMCPMC8474900

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.