TY - JOUR
T1 - Reconstruction of Transmission Pairs for novel Coronavirus Disease 2019 (COVID-19) in mainland China
T2 - Estimation of Super-spreading Events, Serial Interval, and Hazard of Infection
AU - Xu, Xiao-Ke
AU - Liu, Xiao-Fan
AU - Wu, Ye
AU - Ali, Sheikh Taslim
AU - Du, Zhanwei
AU - Bosetti, Paolo
AU - Lau, Eric H. Y.
AU - Cowling, Benjamin J.
AU - Wang, Lin
PY - 2020/12/15
Y1 - 2020/12/15
N2 - Background. Knowledge on the epidemiological features and transmission patterns of COVID-19 is accumulating. Detailed line-list data with household settings can advance the understanding of COVID-19 transmission dynamics.Methods. A unique database with detailed demographic characteristics, travel history, social relationships, and epidemiological timelines for 1,407 transmission pairs that formed 643 transmission clusters in mainland China was reconstructed from 9,120 COVID-19 confirmed cases reported during January 15 - February 29, 2020. Statistical model fittings were used to identify the super-spreaders and estimate serial interval distributions. Age and gender-stratified hazard of infection were estimated for household versus non-household transmissions.Results. There were 34 primary cases identified as super-spreaders, with 5 super-spreading events occurred within households. Mean and standard deviation of serial intervals were estimated as 5.0 (95% CrI: 4.4, 5.5) and 5.2 (95% CrI: 4.9, 5.7) days for household transmissions and 5.2 (95% CrI: 4.6, 5.8) and 5.3 (95% CrI: 4.9, 5.7) days for non-household transmissions, respectively. Hazard of being infected outside of households is higher for age between 18 and 64 years, whereas hazard of being infected within households is higher for young and old people.Conclusions. Non-negligible frequency of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of working age indicate a significant barrier to the identification and management of COVID-19 cases, which requires enhanced non-pharmaceutical interventions to mitigate this pandemic.
AB - Background. Knowledge on the epidemiological features and transmission patterns of COVID-19 is accumulating. Detailed line-list data with household settings can advance the understanding of COVID-19 transmission dynamics.Methods. A unique database with detailed demographic characteristics, travel history, social relationships, and epidemiological timelines for 1,407 transmission pairs that formed 643 transmission clusters in mainland China was reconstructed from 9,120 COVID-19 confirmed cases reported during January 15 - February 29, 2020. Statistical model fittings were used to identify the super-spreaders and estimate serial interval distributions. Age and gender-stratified hazard of infection were estimated for household versus non-household transmissions.Results. There were 34 primary cases identified as super-spreaders, with 5 super-spreading events occurred within households. Mean and standard deviation of serial intervals were estimated as 5.0 (95% CrI: 4.4, 5.5) and 5.2 (95% CrI: 4.9, 5.7) days for household transmissions and 5.2 (95% CrI: 4.6, 5.8) and 5.3 (95% CrI: 4.9, 5.7) days for non-household transmissions, respectively. Hazard of being infected outside of households is higher for age between 18 and 64 years, whereas hazard of being infected within households is higher for young and old people.Conclusions. Non-negligible frequency of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of working age indicate a significant barrier to the identification and management of COVID-19 cases, which requires enhanced non-pharmaceutical interventions to mitigate this pandemic.
KW - COVID-19
KW - transmission
KW - super-spreading event
KW - serial interval
KW - hazard of infection
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85099153349&origin=recordpage
U2 - 10.1093/cid/ciaa790
DO - 10.1093/cid/ciaa790
M3 - RGC 21 - Publication in refereed journal
C2 - 32556265
SN - 1058-4838
VL - 71
SP - 3163
EP - 3167
JO - Clinical Infectious Diseases
JF - Clinical Infectious Diseases
IS - 12
ER -