Is 14-Days a Sensible Quarantine Length for COVID-19? Examinations of Some Associated Issues with a Case Study of COVID-19 Incubation Times

Abstract

To confine the spread of an infectious disease, setting a sensible quarantine time is crucial. To this end, it is imperative to well understand the distribution of incubation times of the disease. Regarding the ongoing COVID-19 pandemic, 14-days is commonly taken as a quarantine time to curb the virus spread in balancing the impacts of COVID-19 on diverse aspects of the society, including public health, economy, and humanity perspectives, etc. However, setting a sensible quarantine time is not trivial and it depends on various underlying factors. In this article, we take an angle of examining the distribution of the COVID-19 incubation time using likelihoodbased methods. Our study is carried out on a dataset of 178 COVID-19 cases dated from January 20, 2020 to February 29, 2020, with the information of exposure periods and dates of symptom onset collected. To gain a good understanding of possible scenarios, we employ different models to describe incubation times of COVID-19. Our findings suggest that statistically, the 14-day quarantine time may not be long enough to control the probability of an early release of infected individuals to be small. While the size of the study data is not large enough to offer us a definitely acceptable quarantine time, and further in practice, the decision-makers may take account of other factors related to social and economic concerns to set up a practically acceptable quarantine time, our study demonstrates useful methods to determine a reasonable quarantine time from a statistical standpoint. Further, it reveals some associated complexity for fully understanding the COVID-19 incubation time distribution.

COVID-19 Activity Risk Calculator as a Gamified Public Health Intervention Tool

“…We then identify the number of active cases by subtracting the confirmed cases for a given day with the confirmed cases for the previous day and compute a 14-day aggregate for the number of active cases. We carry out 14-day aggregate due to the fact that COVID virus is active for 14 days in any specific condition 32 . We determine a range of 14-day aggregate active cases by taking the upper limit as the product of the 14-day aggregate active cases and the ratio between the confirmed cases obtained from Facebook's COVID-19 Trends and Impact Survey 33 and Johns Hopkins dataset 23 .…”

Seeing the forest and the trees: Holistic view of social distancing on the spread of COVID-19 in China

“…Instead, considering many studies suggest that COVID-19 has a 5–8 days of incubation period ( Alene et al, 2021 ; Y. Y. Cai et al, 2020 ; Cheng et al, 2021 ; Cimolai, 2021 ; Guan et al, 2020 ; Quesada et al, 2021 ; Wan, Liu, & Liu, 2021 ; Wu et al, 2022 ; L. Zhang et al, 2021 ), and in clinical practices, a 14-day extended quarantine period is often adopted in the policy sphere ( Charvadeh, Yi, Bian, & He, 2022 ), we extended our data collection period to the early May (May 6th) until one of the data entry, the Baidu migration index, is no longer available.…”

Simultaneous Confidence Band Approach for Comparison of COVID-19 Case Counts

“…The population difference is taken into account and calculated according to the information in the State of Ohio in 2019-2020. 2 The horizontal dashed line in Fig. 1 is y = − 0.227 , which is the differenced log male and female senior populations.…”

“…The proof of ( 11) is a generalization of the proof of Theorem 2.1 of [18] for the autoregressive time series based on Theorem 4 of [21], and the details are omitted. Simulation studies are performed for {y t } n t=1 generated from model (1) with constant function g = 1 and ten ARMA models: nine ARMA(1,1) and one ARMA (2,2).…”

“…Many aspects of this virus have been studied based on publicly accessible data which are updated daily from all over the world [2][3][4][5]. In particular, the effects of gender and age on COVID-19 have received a great deal of attention.…”