Estimation of the incubation period of COVID-19 in Vietnam

Long V Bui; Ha T Nguyen; Hagai Levine; Ha N Nguyen; Thu-Anh Nguyen; Thuy P Nguyen; Truong T Nguyen; Toan T T Do; Ngoc T Pham; My Hanh Bui

doi:10.1371/journal.pone.0243889

. 2020 Dec 23;15(12):e0243889. doi: 10.1371/journal.pone.0243889

Estimation of the incubation period of COVID-19 in Vietnam

Long V Bui ^1,^*, Ha T Nguyen ², Hagai Levine ³, Ha N Nguyen ⁴, Thu-Anh Nguyen ^5,⁶, Thuy P Nguyen ⁷, Truong T Nguyen ⁸, Toan T T Do ⁹, Ngoc T Pham ¹⁰, My Hanh Bui ^9,¹¹

Editor: Ka Chun Chong¹²

¹Center for Research - Consulting and Support of Community Heath, Hanoi, Vietnam

²108 Military Central Hospital, Hanoi, Vietnam

³The Braun School of Public Health and Community Medicine, Hadassah - Hebrew University, Jerusalem, Israel

⁴People’s Police Academy, Hanoi, Vietnam

⁵Woolcock Institute of Medical Research, Hanoi, Vietnam

⁶Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia

⁷Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia

⁸Ministry of Science and Technology, Hanoi, Vietnam

⁹Hanoi Medical University, Hanoi, Vietnam

¹⁰198 Hospital, Hanoi, Vietnam

¹¹Hanoi Medical University Hospital, Hanoi, Vietnam

¹²The Chinese University of Hong Kong, HONG KONG

Competing Interests: The authors have declared that no competing interests exist.

^✉

* E-mail: buimyhanh@hmu.edu.vn

Roles

Long V Bui: Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

Ha T Nguyen: Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing

Hagai Levine: Formal analysis, Methodology, Software, Visualization, Writing – original draft

Ha N Nguyen: Formal analysis, Investigation, Methodology, Resources, Software, Visualization, Writing – original draft

Thu-Anh Nguyen: Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization

Thuy P Nguyen: Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft

Truong T Nguyen: Data curation, Formal analysis, Methodology, Resources, Software, Visualization, Writing – original draft

Toan T T Do: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft

Ngoc T Pham: Conceptualization, Formal analysis, Investigation, Methodology, Resources, Software, Writing – original draft

My Hanh Bui: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

Ka Chun Chong: Editor

PMCID: PMC7757798 PMID: 33362233

Abstract

Objective

To estimate the incubation period of Vietnamese confirmed COVID-19 cases.

Methods

Only confirmed COVID-19 cases who are Vietnamese and locally infected with available data on date of symptom onset and clearly defined window of possible SARS-CoV-2 exposure were included. We used three parametric forms with Hamiltonian Monte Carlo method for Bayesian Inference to estimate incubation period for Vietnamese COVID-19 cases. Leave-one-out Information Criterion was used to assess the performance of three models.

Results

A total of 19 cases identified from 23 Jan 2020 to 13 April 2020 was included in our analysis. Average incubation periods estimated using different distribution model ranged from 6.0 days to 6.4 days with the Weibull distribution demonstrated the best fit to the data. The estimated mean of incubation period using Weibull distribution model was 6.4 days (95% credible interval (CrI): 4.89–8.5), standard deviation (SD) was 3.05 (95%CrI 3.05–5.30), median was 5.6, ranges from 1.35 to 13.04 days (2.5th to 97.5th percentiles). Extreme estimation of incubation periods is within 14 days from possible infection.

Conclusion

This analysis provides evidence for an average incubation period for COVID-19 of approximately 6.4 days. Our findings support existing guidelines for 14 days of quarantine of persons potentially exposed to SARS-CoV-2. Although for extreme cases, the quarantine period should be extended up to three weeks.

Introduction

COVID-19 caused by SAR-CoV-2 has been declared a global pandemic by WHO on March 11 2020 [1]. As a newly emerged disease, little have we known about the incubation period for COVID-19, for which patients have no clinical symptom but some infected persons can be contagious [2]. Understanding the distribution of incubation period is important to estimate the potential spreading of the SARS-CoV-2, and to determine an optimal duration of quarantine. The incubation period is identified by the interval time between exposure to source of an infectious disease and the onset of the first clinical symptoms. As the incubation period is known, we would be able to model the current and future of the pandemic scale, and to evaluate the effectiveness of intervention strategies, therefore, would be able to act swiftly several intensive public health strategies for infectious diseases [3].

Since the first COVID-19 case found in Vietnam on 23 January 2020, as of 13 April 2020, there are 265 confirmed cases all over the country. Of those, two-thirds of the patients have recovered, and no death has been reported. The pandemic situation in Vietnam is significantly different from that in other countries. Vietnam has implemented strong measures against the SARS-CoV-2 transmission at an early stage. However, the country has limited resources, hence understanding the time of intensive monitoring will be beneficial to plan for effective measures to minimize the risk for hidden SARS-CoV-2 infection. While estimations of incubation period of SARS-CoV-2 have been conducted elsewhere in the world [4–13], there is no estimation of this parameter using data from Vietnam, instead, efforts were only focusing on describing pattern of COVID-19 pandemic in Vietnam [14–16]. This study aims to estimate the incubation period of Vietnamese confirmed COVID-19 cases.

Methods

Data sources and collection

We used secondary data that publicly available from Viet Nam Ministry of Health (MoH). According to the report flow of the Ministry of Health and National Steering Committee for COVID-19 response, information of all laboratory-confirmed COVID-19 cases in Vietnam, which include patient number, travelling history, contact tracing and clusters, date of laboratory-confirmed, date of assertion, date and status of discharge was collected by the local centers for disease control and hospitals where patients were being admitted. The information then was reported daily to the Ministry of Health and officially made publicly available on the website http://ncov.moh.gov.vn [16]. Additionally, the clusters of COVID-19 in a northern province of Vietnam have been described by Thanh et al. [17]. Two researchers independently reviewed the full text of each case report of confirmed COVID-19 cases in Vietnam from 23 January 2020 to 13 April 2020, and entered data into a standardized case reporting form to establish a database for this study. Any discrepancies in data extraction were resolved by discussion between two researchers and facilitated by a third researcher to reach consensus. Previous studies also used the same approach to generate data sources for analysis [15, 16].

To assure the reliability of analysis, we selected only confirmed COVID-19 cases who are Vietnamese and locally infected with available data on date of symptom onset (including fever, cough, and shortness of breath) and clearly defined window of possible SARS-CoV-2 exposure. This window period is defined as the date range between the earliest possible exposure, which is the first contact with confirmed cases and the latest exposure, which is the most recent contact with confirmed cases in the clusters.

Statistical analysis

We assumed that the moment of infection occurred between the interval of possible SARS-CoV-2 exposure. The distribution of incubation period was estimated using maximum likelihood where the likelihood function of each case in the dataset was a single interval-censored by three parametric forms with Hamiltonian Monte Carlo method for Bayesian Inference: Weibull distribution, the Gamma distribution and the Lognormal distribution. Non-informative positive prior for the parameters of the three distributions were specified. Leave-one-out Information Criterion (LooIC) was used to assess the performance of three models. The differences of LooIC larger than two were considered as statistically significant [18]. Mean, median and posterior Credible Interval (CI) for each distribution were also estimated. Statistical analysis was conducted by rstan [19] in R 3.6.4 [20]. Data for analysis and R codes are available on public repository https://github.com/longbui/Covid19IncubVN.

Ethical statement

Research only aims to protect and improve the quality of treatment, not for any purpose. All details about patients’ information is confidential, therefore the Institutional Review Board and requirement for informed consent was waived.

Results

From 23 Jan 2020 to 13 Apr 2020, a total of 265 positive-confirmed SARS-CoV-2 was reported in Vietnam. Of those, 38.5% were locally infected, 58.2% were female. The mean age was 36 years old, median age was 31 years old. There were 19 confirmed COVID-19 cases found between 23 January to 13 April 2020, who met the inclusion criteria. These include being Vietnamese nationality, locally infected with SARS-CoV-2, and had completed epidemiological data on exposure interval and date of symptom onset. Of those, 7 were male and 12 were female. The mean age was 38.47, median age was 37 (interquartile range: 25–50). There was no statistical difference in mean age and sex distribution between sub-group for analysis and the entire group (p<0.05).

Average incubation periods estimated using different distribution model ranged from 6.0 days to 6.4 days (Table 1). According to the LooIc of proposed models, the Weibull distribution demonstrated the best fit to the data. The estimated mean of the incubation period using Weibull distribution model was 6.4 days (95% CI 4.89–8.5), the standard deviation (SD) was 3.05 (95%CI 3.05–5.30). The Gamma distribution model fitted significantly poorer than the Weibull model. The estimated mean of the incubation period of this model was 6.07 days (95% CI: 4.64–8.00), with the SD of 2.90 days (95% CI 1.91–4.80), The lognormal distribution showed the poorest fit to the data, the incubation period was estimated to be 6.4 (95% CI 4.6–10.2).

Table 1. Mean and SD of the estimated incubation period for confirmed Vietnamese COVID-19 cases between 23 Jan 2020 to 13 Apr 2020.

Distribution	Mean (days)		SD (days)		LooIC
Distribution	Estimate	95% CI	Estimate	95% CI	LooIC
Weibull	6.4	4.9–8.5	3.0	2.0–5.4	103.9
Gamma	6.1	4.7–8.0	2.9	1.9–4.8	106.2
Lognormal	6.4	4.6–10.2	5.8	3.5–11.2	106.7

Open in a new tab

Estimation of median of incubation period using different models are presented in Table 2. Fig 1 shows the estimation distribution of incubation periods using Weibull model, with estimated median of 6.1 days, ranging from 1.4 to 13.0 days (2.5^th to 97.5^th percentiles). Detail estimated possible moment of infection with Weibull distribution is illustrated in Fig 2. The results suggest a large variation in incubation periods among patients but it was most likely to fall in the period within 14 days of infection.

Table 2. Percentiles of the estimated incubation period for confirmed Vietnamese COVID-19 cases between 23 Jan 2020 to 13 Apr 2020 with Weibull, Gamma and Lognormal distribution.

Percentiles	Incubation period distribution (days)
	Weibull		Gamma		Lognormal
	Estimate	95% CI	Estimate	95% CI	Estimate	95% CI
2.5^th	1.4	0.4–2.7	1.8	0.7–33.0	1.5	0.6–2.5
5^th	1.9	0.7–3.4	1.0	2.2–3.4	1.8	2.0–3.5
50^th	6.1	4.4–8.0	5.6	4.2–7.3	5.2	3.6–7.3
95^th	11.9	9.10–12.0	11.5	8.6–16.7	14.9	9.7–30.2
97.5^th	13.0	9.1–20.7	13.0	9.6–19.4	18.2	11.3–40.8
99^th	14.4	10.6–24.0	14.7	10.7–22.8	23.0	14.4–58.0

Open in a new tab

Fig 2 — (Cases were numbered by the order of official assertion of confirmed cases on the website of the Ministry of Health of Vietnam).

Discussion

We estimated the incubation period of Vietnamese confirmed COVID-19 cases from public reported data with three parametric models, including Weibull, Gamma and Lognornal distribution. The Weibull distribution proved to be best fit to the data. Our estimation results are similar or higher than most results from published literature (Table 3). Our estimation of 6.4 days for mean incubation period is similar to the estimation of Backer et al. [4]. The estimated mean in our study is higher in comparison with that of other studies, which ranged from 3 to 5.6 days [5–8, 10]. Our estimation is shorter than several studies. Leung et al. [9] estimated incubation periods of 7.2 days among local residents of Wuhan. Studies of Kong [11], Tindale et al. [12] and Qin et al. [13] estimated incubation periods around 8–9 days. When comparing the estimated median and its range with other study, we saw a similar trend where our estimations are similar or higher than most studies where median estimation was available [4, 5, 7, 8]. Nonetheless, extreme estimation of incubation periods (95^th or 97.5^th percentiles) in studies are well within 14 days from possible infection [4, 5, 7–13].

Table 3. Comparison of estimated incubation periods for SARS-COV-2.

Author	Distribution	N	Mean and/or median (days) with 95%CI	Plausible range (days) with 95%CI
Our study	Weibull	19	Mean 6.4 (4.9–8.2)	1.4–13.0 (2.5^th to 97.5^th percentile)
Our study	Weibull	19	Median 6.1 (4.4–8.0)	1.4–13.0 (2.5^th to 97.5^th percentile)
Backer et al. [8]	Weibull	88	Mean 6.4 (5.6–7.7)	2.1–11.1 days (2.5 to 97.5 percentile)
Backer et al. [8]	Weibull	88	Median 6.4 (5.5–7.5)	2.1–11.1 days (2.5 to 97.5 percentile)
Lauer et al. [7]	Lognormal	181	Median 5.2 (4.4–6.0)	2.2–11.5 (2.5^th to 97.5^th percentile)
Linton et al. [12]	Lognormal	58 (excluding Wuhan residents)	Non-truncated	95^th percentile for non- truncated data: 10.6 (8.5–14.1)
			Mean 5.0 (4.2–6.0),
			Median 4.3 (3.5–5.1)
			Right-truncated	95^th percentile for right-truncated: 12.3 (9.1–19.8)
			Mean 5.6 (4.4–7.4)
			Median 4.6 (3.7–5.7)
	Lognormal	152 (including Wuhan residents)	Nontruncated:	95^th percentile for non-truncated data 10.8 (95% CI: 9.3–12.9)
	Lognormal	152 (including Wuhan residents)	Mean 5.6 (5.0–6.3), Median 5.0 (95%: 5.0–6.3)
Li et al. [11]	Lognormal	10	Mean 5.2 (4.1–7.0),	95^th percentile”12.5 (9.2–18)
Leung [13]	Weibull	175 (Travelers to Hubei)	Mean 1.8 (1.0–2.7)	95^th percentile 3.2 (1.0–3.8)
Leung [13]	Weibull	175 (Non-travelers)	Mean 7.2 (7.1–8.4)	95^th percentile 14.6 (12.1–17.1)
Jiang et al. [9]		50	Mean 4.9 (4.4–5.5)
Lee et al. [10]	Lognormal	47	Median 3 (0.6–8.2)
Kong [11]		136	Mean 8.5 (7.8–9.2)
Kong [11]		136	Median 8.3 (7.6–9.0)
Tindale et al. [12]			Mean 5.99 (95%CI 4.97, 7.14)
			Median 5.32
			Tianjin
			Mean 8.68 (7.72, 9.7)
			Median 8.06;
Qin et al. [13]		1211	Mean 8·62 (95% CI: 8·02–9·28),
Qin et al. [13]		1211	median 8·13 days (7·37–8·91),

Open in a new tab

The estimated mean of incubation period for 19 Vietnamese confirmed COVID-19 cases using Weibull distribution model is higher than that of SARS in Hong Kong and Beijing [21] and in MERS [15, 16, 22, 23]. Hence, mathematical models of COVID-19 should not be fitted with incubation period of MERS or SARS.

The variation of incubation period of SARS-CoV-2 could be explained by the differences on the strains of the virus, the biological variations of population and the control measures of certain country. It is suggested that any interpretation of results on incubation time of SARS‐CoV‐2 is strongly dependent on the selected data sources [9]. In Vietnam, the key COVID-19 control strategy has focused on active case finding, early testing, treating and strictly isolating cases, which has been considered as effective in finding people with SARS-CoV-2 positive and providing treatment prior to clinical symptoms presentation [16]. It is also a possible circumstance that people with suggestive symptoms of respiratory diseases may take drugs before seeking diagnosis and treatment.

In this study, the plausible range of incubation period estimated using the Weibull distribution supports the importance to isolate confirmed and suspected cases, and close contacts for 14 days after exposure. However, we recommend the policy makers to consider the upper bound of this range (97.5th percentile 13.0, CI 10.6–20.7). Prior studies also suggested that the incubation period in some cases can be up to 24 days [24]. As such, the quarantine period should be extended up to three weeks.

Our study has several strengths, including being the first effort to estimate SAR-CoV-2 incubation period using data from Vietnamese locally transmitted cases. We also used 3 different models for estimation and identified the model that best fitted with our data. However, there are potential limitations in our study. First, not all confirmed COVID-19 cases have completed epidemiological data on exposure interval and date of symptom onset available on public government reports. Second, the number of patients included in the analysis is small, possibly explaining the wider range of estimated incubation period. In addition, the study could not analyze the differences in incubation period between age groups or gender due to small sample size. The large variation in incubation periods in our study can also be attributed by variations in exposure period and uncertainties in the date of infection. These highlight the need for data standardization for further studies on COVID-19 and the importance of publishing data for the scientific and public health community [9].

This study may contribute to the effort of COVID-19 control effort in Vietnam and elsewhere by providing an informed estimate of the incubation period. This is a key variable needed for modelling the spread of SARS-CoV-2, for informed decision-making throughout the pandemic. Similar methodology could be used to estimate the incubation period for other countries and diseases.

Data Availability

Data of all confirmed COVID-19 cases in Vietnam were made publicly available on the official website of Ministry of Health of Vietnam (ncov.moh.gov.vn) Data for analysis and R codes are available on public repository https://github.com/longbui/Covid19IncubVN.

Funding Statement

The authors received no specific funding for this work.

References

1.Coronavirus (COVID-19) events as they happen [Internet]. [cited 2020 Oct 13]. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-happen
2.Organization WH. Coronavirus disease 2019 (COVID-19): situation report, 73. World Health Organization; 2020 Apr p. 13 p.
3.Nishiura H. Early efforts in modeling the incubation period of infectious diseases with an acute course of illness. Emerging Themes in Epidemiology. 2007. May 11;4(1):2 10.1186/1742-7622-4-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Backer JA, Klinkenberg D, Wallinga J. Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20–28 January 2020. Eurosurveillance. 2020. February 6;25(5):2000062 10.2807/1560-7917.ES.2020.25.5.2000062 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Linton NM, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov AR, Jung S, et al. Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data. Journal of Clinical Medicine. 2020. February;9(2):538 10.3390/jcm9020538 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Jiang X, Rayner S, Luo M-H. Does SARS-CoV-2 has a longer incubation period than SARS and MERS? J Med Virol. 2020;92(5):476–8. 10.1002/jmv.25708 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, et al. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine [Internet]. 2020. March 10 [cited 2020 Apr 18]; 10.7326/M20-0504 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. New England Journal of Medicine. 2020. March 26;382(13):1199–207. 10.1056/NEJMoa2001316 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Leung C. The difference in the incubation period of 2019 novel coronavirus (SARS-CoV-2) infection between travelers to Hubei and non-travelers: The need of a longer quarantine period. Infect Control Hosp Epidemiol. 1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Lee H, Kim K, Choi K, Hong S, Son H, Ryu S. Incubation period of the coronavirus disease 2019 (COVID-19) in Busan, South Korea. Journal of Infection and Chemotherapy. 2020. September 1;26(9):1011–3. 10.1016/j.jiac.2020.06.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Kong T. Longer incubation period of coronavirus disease 2019 (COVID‐19) in older adults. Aging Med (Milton) [Internet]. 2020 May 22 [cited 2020 Oct 13]; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7280705/ [DOI] [PMC free article] [PubMed]
12.Tindale LC, Stockdale JE, Coombe M, Garlock ES, Lau WYV, Saraswat M, et al. Evidence for transmission of COVID-19 prior to symptom onset. eLife [Internet]. [cited 2020 Oct 13];9 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7386904/ 10.7554/eLife.57149 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Qin J, You C, Lin Q, Hu T, Yu S, Zhou X-H. Estimation of incubation period distribution of COVID-19 using disease onset forward time: a novel cross-sectional and forward follow-up study. medRxiv [Internet]. 2020. March 10 [cited 2020 Oct 13]; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217033/ [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Hoang VM, Hoang HH, Khuong QL, La NQ, Tran TTH. Describing the pattern of the COVID-19 epidemic in Vietnam. Global Health Action. 2020. October 15;13(1):1776526 10.1080/16549716.2020.1776526 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Nguyen THD, Vu DC. Summary of the COVID-19 outbreak in Vietnam–Lessons and suggestions. Travel Med Infect Dis [Internet]. 2020. April 2 [cited 2020 Oct 15]; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146658/ [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Pham QT, Rabaa MA, Duong HL, Dang QT, Tran DQ, Quach H-L, et al. The first 100 days of SARS-CoV-2 control in Vietnam. Clin Infect Dis [Internet]. [cited 2020 Oct 15]; https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa1130/5879764 32738143 [Google Scholar]
17.Thanh HN, Van TN, Thu HNT, Van BN, Thanh BD, Thu HPT, et al. Outbreak investigation for COVID-19 in northern Vietnam. The Lancet Infectious Diseases [Internet]. 2020. March 4 [cited 2020 Apr 19];0(0). Available from: https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30159-6/abstract [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Vehtari A, Gelman A, Gabry J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat Comput. 2017. September 1;27(5):1413–32. [Google Scholar]
19.Stan Development Team. RStan: the R interface to Stan [Internet]. 2020. http://mc-stan.org/
20.R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2020. https://www.R-project.org/ [Google Scholar]
21.Lau EH, Hsiung CA, Cowling BJ, Chen C-H, Ho L-M, Tsang T, et al. A comparative epidemiologic analysis of SARS in Hong Kong, Beijing and Taiwan. BMC Infectious Diseases. 2010. March 6;10(1):50. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Assiri A, McGeer A, Perl TM, Price CS, Al Rabeeah AA, Cummings DAT, et al. Hospital Outbreak of Middle East Respiratory Syndrome Coronavirus [Internet]. 10.1056/NEJMoa1306742. Massachusetts Medical Society; 2013 [cited 2020 Apr 19]. https://www.nejm.org/doi/10.1056/NEJMoa1306742?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dwww.ncbi.nlm.nih.gov [DOI] [PMC free article] [PubMed]
23.Cauchemez S, Fraser C, Van Kerkhove MD, Donnelly CA, Riley S, Rambaut A, et al. Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility. Lancet Infect Dis. 2014. January;14(1):50–6. 10.1016/S1473-3099(13)70304-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Guan W, Ni Z, Hu Y, Liang W, Ou C, He J, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. New England Journal of Medicine. 2020. February 28;0(0):null. [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0243889.r001

Decision Letter 0

Ka Chun Chong

25 Aug 2020

PONE-D-20-14137

Estimation of the incubation period of SARS-CoV-2 in Vietnam

PLOS ONE

Dear Dr. Bui,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Oct 09 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Ka Chun Chong

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Whilst you may use any professional scientific editing service of your choice, PLOS has partnered with both American Journal Experts (AJE) and Editage to provide discounted services to PLOS authors. Both organizations have experience helping authors meet PLOS guidelines and can provide language editing, translation, manuscript formatting, and figure formatting to ensure your manuscript meets our submission guidelines. To take advantage of our partnership with AJE, visit the AJE website (http://learn.aje.com/plos/) for a 15% discount off AJE services. To take advantage of our partnership with Editage, visit the Editage website (www.editage.com) and enter referral code PLOSEDIT for a 15% discount off Editage services. If the PLOS editorial team finds any language issues in text that either AJE or Editage has edited, the service provider will re-edit the text for free.

Upon resubmission, please provide the following:

The name of the colleague or the details of the professional service that edited your manuscript
A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file)
A clean copy of the edited manuscript (uploaded as the new *manuscript* file)

Additional Editor Comments :

As there are a number of studies related with an estimation of the incubation period, a review of the estimates in the literature is required.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript is well written and has a practical implications for addressing the COVID-19 response in Vietnam. The authors use small number of confirmed cases to estimate the incubation period and I have some comments for this manuscript.

Minor comments

1. The analyses were highly dependent on the epidemiological investigations for each case. Please describe the process of the data generation such as epidemiological investigations briefly to show the validity of the data such as the date of exposure and illness onset.

2. The author compared the incubation period in other studies using the data from China. Can you please add the other studies using the data from out of china? For example, Korea (Lee H et al. Journal of Infection and Chemotherapy 2020), France (Slje H, hal-pasteur.achieve 2020), etc).

3. Please provide more detail of the limitation of this study, particularly on the small sample size to analyse.

Reviewer #2: The authors estimated the incubation period of Vietnamese confirmed COVID-19 cases from a subsample of 19 of the 102 locally infected cases for the period 23 Jan to 13 Apr 2020. My review comments are:

1. How representative is the subsample? Data on age range and sex of the subsample was mentioned in the article, but not for the parent sample of 102 patients. Were their age/sex data comparable?

2. The authors attributed the large variation in incubation periods in their study to small sample size, but can these be contributed also by variations in exposure period and uncertainties in the date of infection (Figure 2)?

Kong T-K. Longer incubation period of coronavirus disease 2019 (COVID-19) in older adults. Aging Medicine 2020;3:102-109.

Qin J, You C, Lin Q, Hu T, Yu S, Zhou X-H. Estimation of incubation period distribution of COVID-19 using disease onset forward time: a novel cross-sectional and forward follow-up study. Sci Adv. 2020. https://advances.sciencemag.org/content/early/2020/08/07/sciadv.abc1202

Tindale LC, Stockdale JE, Coombe M, et al. Evidence for transmission of COVID-19 prior to symptom onset. eLife 2020;9:e57149. https://doi.org/10.7554/eLife.57149

4. The authors recommended the quarantine period should be extended up to three weeks based on their study finding of 97.5th percentile 13.0, CI 10.6–20.7. But would they also comment on the wide CI of 10.6-20.7 and the reason for the uncertainty?

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Dec 23;15(12):e0243889. doi: 10.1371/journal.pone.0243889.r002

Author response to Decision Letter 0

20 Oct 2020

Dear Reviewer,

Thank you for your helpful comments. We have revised our paper accordingly and feel that your comments helped clarify and improve our paper. Please find our response (in blue) to reviewer’s specific comments (in black) below.

Reviewer #1:

Response: Thank you for your comment. I have added details on the data generation: According to the report flow of the Ministry of Health and National Steering Committee for COVID-19 response, information of all laboratory-confirmed COVID-19 cases in Vietnam, which include patient number, travelling history, contact tracing and clusters, date of laboratory-confirmed, date of assertion, date and status of discharge was collected by the local centers for disease control and hospitals where patients were being admitted. The information then was reported daily to the Ministry of Health and officially made publicly available on the website httpp://ncov.moh.gov.vn.

This method was also used by several articles on COVID-19 in Vietnam, which were cited in our manuscript.

Reponse: Thank you very much. We have added relevant citation as you suggested. We did not cite Slje H, hal-pasteur.achieve 2020 because the article did not estimate the incubation period of COVID-19 in France, instead, the author used the incubation period of 5 days in a deterministic compartmental model stratified by age to describe the transmission of SARSCoV-2 in the French population.

3. Please provide more detail of the limitation of this study, particularly on the small sample size to analyse.

Response: Thank you very much. We have added “In addition, the study could not analyze the differences in incubation period between age groups due to small sample size”.

Reviewer #2:

1. How representative is the subsample? Data on age range and sex of the subsample was mentioned in the article, but not for the parent sample of 102 patients. Were their age/sex data comparable?

Response: Thank you very much for your comment. We have added some lines that compare the age/sex of subgroup to the parent sample. “There was no statistical difference in mean age and sex distribution between sub-group for analysis and the entire group (p<0.05).”

Response: Thank you very much. We’ve added this issue in the limitations: “The large variation in incubation periods in our study can also be attributed by variations in exposure period and uncertainties in the date of infection”.

3. The authors commented that “Only one study by Leung [13] estimated longer incubation periods than our estimation”. But there are three other studies that gave estimates of longer mean incubation periods of COVID-19 in the order of 8 days: Kong T-K. Longer incubation period of coronavirus disease 2019 (COVID-19) in older adults. Aging Medicine 2020;3:102-109.

Response: Thank you very much. We have added relevant citation as you suggested. We did not cite (Slje H, hal-pasteur.achieve 2020) because the article did not estimate the incubation period of COVID-19 in France, instead, the author used the incubation period of 5 days in a deterministic compartmental model stratified by age to describe the transmission of SARSCoV-2 in the French population.

Response: Thank you very much. We’ve added one reference, suggesting that the incubation period of CVOID-19 may be up to 24 days “Prior studies also suggested that the incubation period in some cases can be up to 24 days [24]”.

Thank you again for your constructive manuscript, that absolutely improve our manuscript.

We hope reviewers take our revised version into your consideration.

We look forward to hearing positive feedback from you.

Sincerely Yours

Bui My Hanh

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(17KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0243889.r003

Decision Letter 1

Ka Chun Chong

12 Nov 2020

PONE-D-20-14137R1

Estimation of the incubation period of COVID-19 in Vietnam

PLOS ONE

Dear Dr. Bui,

==============================

ACADEMIC EDITOR: Please address the remaining comments.

==============================

Please submit your revised manuscript by Dec 27 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Ka Chun Chong

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: The authors reflect all of the comments in the revised manuscript; The readibility is improved and looks better.

Reviewer #2: My review comments have been addressed and the manuscript is acceptable for publication after correction of one error and a typo:

Line 157 error: Lee et al [10] should not be quoted as a study showing longer incubation period than the authors' study finding, because the median incubation period of Lee et al [10] is shorter at 3 days. It can nevertheless be quoted under Line 155 together with other studies showing shorter incubation period compared with the authors' finding.

Line 112 typo: "of those" is duplicated.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

PLoS One. 2020 Dec 23;15(12):e0243889. doi: 10.1371/journal.pone.0243889.r004

Author response to Decision Letter 1

17 Nov 2020

Dear Reviewers,

Thank you for your helpful comments. We have revised our paper accordingly and feel that your comments helped clarify and improve our paper. Please find our response to reviewer’s specific comments below.

Reviewer #1:

The authors reflect all of the comments in the revised manuscript; The readibility is improved and looks better.

Response: Thank you for your comment.

Reviewer #2:

My review comments have been addressed and the manuscript is acceptable for publication after correction of one error and a typo:

Line 112 typo: "of those" is duplicated.

Response: Thank you for your comment. We have deleted the duplicated “of those”. We have moved the reference of Lee et al. to studies estimating shorter incubation time than ours and revised the range of shorter estimation from 3 – 5.6 days.

We have made overall editing to the manuscript to make sure all typos and wordings are correct.

Thank you again for your constructive manuscript, that absolutely improve our manuscript.

We hope reviewers take our revised version into your consideration.

We look forward to hearing positive feedback from you.

Sincerely Yours

Bui My Hanh

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(14.1KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0243889.r005

Decision Letter 2

Ka Chun Chong

1 Dec 2020

Estimation of the incubation period of COVID-19 in Vietnam

PONE-D-20-14137R2

Dear Dr. Bui,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Ka Chun Chong

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0243889.r006

Acceptance letter

Ka Chun Chong

10 Dec 2020

PONE-D-20-14137R2

Estimation of the incubation period of COVID-19 in Vietnam

Dear Dr. Bui:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ka Chun Chong

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(17KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(14.1KB, docx)}

Data Availability Statement

[pone.0243889.ref001] 1.Coronavirus (COVID-19) events as they happen [Internet]. [cited 2020 Oct 13]. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-happen

[pone.0243889.ref002] 2.Organization WH. Coronavirus disease 2019 (COVID-19): situation report, 73. World Health Organization; 2020 Apr p. 13 p.

[pone.0243889.ref003] 3.Nishiura H. Early efforts in modeling the incubation period of infectious diseases with an acute course of illness. Emerging Themes in Epidemiology. 2007. May 11;4(1):2 10.1186/1742-7622-4-2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref004] 4.Backer JA, Klinkenberg D, Wallinga J. Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20–28 January 2020. Eurosurveillance. 2020. February 6;25(5):2000062 10.2807/1560-7917.ES.2020.25.5.2000062 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref005] 5.Linton NM, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov AR, Jung S, et al. Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data. Journal of Clinical Medicine. 2020. February;9(2):538 10.3390/jcm9020538 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref006] 6.Jiang X, Rayner S, Luo M-H. Does SARS-CoV-2 has a longer incubation period than SARS and MERS? J Med Virol. 2020;92(5):476–8. 10.1002/jmv.25708 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref007] 7.Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, et al. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine [Internet]. 2020. March 10 [cited 2020 Apr 18]; 10.7326/M20-0504 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref008] 8.Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. New England Journal of Medicine. 2020. March 26;382(13):1199–207. 10.1056/NEJMoa2001316 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref009] 9.Leung C. The difference in the incubation period of 2019 novel coronavirus (SARS-CoV-2) infection between travelers to Hubei and non-travelers: The need of a longer quarantine period. Infect Control Hosp Epidemiol. 1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref010] 10.Lee H, Kim K, Choi K, Hong S, Son H, Ryu S. Incubation period of the coronavirus disease 2019 (COVID-19) in Busan, South Korea. Journal of Infection and Chemotherapy. 2020. September 1;26(9):1011–3. 10.1016/j.jiac.2020.06.018 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref011] 11.Kong T. Longer incubation period of coronavirus disease 2019 (COVID‐19) in older adults. Aging Med (Milton) [Internet]. 2020 May 22 [cited 2020 Oct 13]; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7280705/ [DOI] [PMC free article] [PubMed]

[pone.0243889.ref012] 12.Tindale LC, Stockdale JE, Coombe M, Garlock ES, Lau WYV, Saraswat M, et al. Evidence for transmission of COVID-19 prior to symptom onset. eLife [Internet]. [cited 2020 Oct 13];9 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7386904/ 10.7554/eLife.57149 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref013] 13.Qin J, You C, Lin Q, Hu T, Yu S, Zhou X-H. Estimation of incubation period distribution of COVID-19 using disease onset forward time: a novel cross-sectional and forward follow-up study. medRxiv [Internet]. 2020. March 10 [cited 2020 Oct 13]; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217033/ [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref014] 14.Hoang VM, Hoang HH, Khuong QL, La NQ, Tran TTH. Describing the pattern of the COVID-19 epidemic in Vietnam. Global Health Action. 2020. October 15;13(1):1776526 10.1080/16549716.2020.1776526 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref015] 15.Nguyen THD, Vu DC. Summary of the COVID-19 outbreak in Vietnam–Lessons and suggestions. Travel Med Infect Dis [Internet]. 2020. April 2 [cited 2020 Oct 15]; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146658/ [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref016] 16.Pham QT, Rabaa MA, Duong HL, Dang QT, Tran DQ, Quach H-L, et al. The first 100 days of SARS-CoV-2 control in Vietnam. Clin Infect Dis [Internet]. [cited 2020 Oct 15]; https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa1130/5879764 32738143 [Google Scholar]

[pone.0243889.ref017] 17.Thanh HN, Van TN, Thu HNT, Van BN, Thanh BD, Thu HPT, et al. Outbreak investigation for COVID-19 in northern Vietnam. The Lancet Infectious Diseases [Internet]. 2020. March 4 [cited 2020 Apr 19];0(0). Available from: https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30159-6/abstract [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref018] 18.Vehtari A, Gelman A, Gabry J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat Comput. 2017. September 1;27(5):1413–32. [Google Scholar]

[pone.0243889.ref019] 19.Stan Development Team. RStan: the R interface to Stan [Internet]. 2020. http://mc-stan.org/

[pone.0243889.ref020] 20.R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2020. https://www.R-project.org/ [Google Scholar]

[pone.0243889.ref021] 21.Lau EH, Hsiung CA, Cowling BJ, Chen C-H, Ho L-M, Tsang T, et al. A comparative epidemiologic analysis of SARS in Hong Kong, Beijing and Taiwan. BMC Infectious Diseases. 2010. March 6;10(1):50. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref022] 22.Assiri A, McGeer A, Perl TM, Price CS, Al Rabeeah AA, Cummings DAT, et al. Hospital Outbreak of Middle East Respiratory Syndrome Coronavirus [Internet]. 10.1056/NEJMoa1306742. Massachusetts Medical Society; 2013 [cited 2020 Apr 19]. https://www.nejm.org/doi/10.1056/NEJMoa1306742?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dwww.ncbi.nlm.nih.gov [DOI] [PMC free article] [PubMed]

[pone.0243889.ref023] 23.Cauchemez S, Fraser C, Van Kerkhove MD, Donnelly CA, Riley S, Rambaut A, et al. Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility. Lancet Infect Dis. 2014. January;14(1):50–6. 10.1016/S1473-3099(13)70304-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0243889.ref024] 24.Guan W, Ni Z, Hu Y, Liang W, Ou C, He J, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. New England Journal of Medicine. 2020. February 28;0(0):null. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Estimation of the incubation period of COVID-19 in Vietnam

Long V Bui

Ha T Nguyen

Hagai Levine

Ha N Nguyen

Thu-Anh Nguyen

Thuy P Nguyen

Truong T Nguyen

Toan T T Do

Ngoc T Pham

My Hanh Bui

Roles

Abstract

Objective

Methods

Results

Conclusion

Introduction

Methods

Data sources and collection

Statistical analysis

Ethical statement

Results

Table 1. Mean and SD of the estimated incubation period for confirmed Vietnamese COVID-19 cases between 23 Jan 2020 to 13 Apr 2020.

Table 2. Percentiles of the estimated incubation period for confirmed Vietnamese COVID-19 cases between 23 Jan 2020 to 13 Apr 2020 with Weibull, Gamma and Lognormal distribution.

Fig 1. The cumulative density function of the estimated Weibull distribution for incubation period of Vietnamese confirmed COVID-19 cases from 23 Jan 2020 to 13 Apr 2020.

Fig 2. Estimated possible moment of infection of Vietnamese confirmed COVID-19 cases from 23 Jan 2020 to 13 Apr 2020 with Weibull distribution.

Discussion

Table 3. Comparison of estimated incubation periods for SARS-COV-2.

Data Availability

Funding Statement

References

Decision Letter 0

Ka Chun Chong

Roles

Author response to Decision Letter 0

Decision Letter 1

Ka Chun Chong

Roles

Author response to Decision Letter 1

Decision Letter 2

Ka Chun Chong

Roles

Acceptance letter

Ka Chun Chong

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases