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

Abstract

Background The 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. Methods We 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. Results Based 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. Conclusions Observing 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.

Hypothesis Test on a Mixture Forward-Incubation-Time Epidemic Model With Application to COVID-19 Outbreak

“…Accurate estimation of the incubation-period distribution, or incubation distribution, is crucial (especially in regions where the epidemic is severe) for determining the length of appropriate quarantine periods for suspected individuals. In the literature, estimating incubation distributions has attracted much attention (Sartwell, 1950;Kalbfleisch and Lawless, 1989;Struthers and Farewell, 1989;Kalbfleisch and Lawless, 1991;Farewell et al, 2005;Wilkening, 2008), while studies for COVID-19 are still ongoing; see Backer et al (2020), Guan et al (2020), Lauer et al (2020), Li et al (2020), Linton et al (2020), Liu et al (2021), Qin et al (2020), Rahman et al (2020), Wang et al (2020b), and Liu et al (2022), among others. The current results are based mostly on clinical experience or empirical statistical analysis of contact-tracing data, but such data may be inaccurate because of the patient's recall bias or the interviewer's personal judgment on the possible date of exposure rather than the actual date.…”