scholarly journals Estimation of incubation period and serial interval of COVID-19: analysis of 178 cases and 131 transmission chains in Hubei province, China

2020 ◽  
Vol 148 ◽  
Author(s):  
Lin Yang ◽  
Jingyi Dai ◽  
Jun Zhao ◽  
Yunfu Wang ◽  
Pingji Deng ◽  
...  
Keyword(s):  
Incubation Period ◽  
Failure Time ◽  
Age Groups ◽  
Hubei Province ◽  
Interval Censoring ◽  
Contact Tracing ◽  
Considerable Proportion ◽  
Outbreak Period ◽  
Serial Interval ◽  
Incubation Periods

Abstract A novel coronavirus disease, designated as COVID-19, has become a pandemic worldwide. This study aims to estimate the incubation period and serial interval of COVID-19. We collected contact tracing data in a municipality in Hubei province during a full outbreak period. The date of infection and infector–infectee pairs were inferred from the history of travel in Wuhan or exposed to confirmed cases. The incubation periods and serial intervals were estimated using parametric accelerated failure time models, accounting for interval censoring of the exposures. Our estimated median incubation period of COVID-19 is 5.4 days (bootstrapped 95% confidence interval (CI) 4.8–6.0), and the 2.5th and 97.5th percentiles are 1 and 15 days, respectively; while the estimated serial interval of COVID-19 falls within the range of −4 to 13 days with 95% confidence and has a median of 4.6 days (95% CI 3.7–5.5). Ninety-five per cent of symptomatic cases showed symptoms by 13.7 days (95% CI 12.5–14.9). The incubation periods and serial intervals were not significantly different between male and female, and among age groups. Our results suggest a considerable proportion of secondary transmission occurred prior to symptom onset. And the current practice of 14-day quarantine period in many regions is reasonable.

scholarly journals Subcritical Transmission in the Early Stage of COVID-19 in Korea

2021 ◽  
Vol 18 (3) ◽  
pp. 1265
Author(s):  
Yong Sul Won ◽  
Jong-Hoon Kim ◽  
Chi Young Ahn ◽  
Hyojung Lee
Keyword(s):  
Incubation Period ◽  
Early Stage ◽  
Probability Distributions ◽  
Likelihood Estimation ◽  
Contact Tracing ◽  
Statistical Characterization ◽  
Serial Interval ◽  
Imported Cases ◽  
The Mean ◽  
Reporting Delays

While the coronavirus disease 2019 (COVID-19) outbreak has been ongoing in Korea since January 2020, there were limited transmissions during the early stages of the outbreak. In the present study, we aimed to provide a statistical characterization of COVID-19 transmissions that led to this small outbreak. We collated the individual data of the first 28 confirmed cases reported from 20 January to 10 February 2020. We estimated key epidemiological parameters such as reporting delay (i.e., time from symptom onset to confirmation), incubation period, and serial interval by fitting probability distributions to the data based on the maximum likelihood estimation. We also estimated the basic reproduction number (R0) using the renewal equation, which allows for the transmissibility to differ between imported and locally transmitted cases. There were 16 imported and 12 locally transmitted cases, and secondary transmissions per case were higher for the imported cases than the locally transmitted cases (nine vs. three cases). The mean reporting delays were estimated to be 6.76 days (95% CI: 4.53, 9.28) and 2.57 days (95% CI: 1.57, 4.23) for imported and locally transmitted cases, respectively. The mean incubation period was estimated to be 5.53 days (95% CI: 3.98, 8.09) and was shorter than the mean serial interval of 6.45 days (95% CI: 4.32, 9.65). The R0 was estimated to be 0.40 (95% CI: 0.16, 0.99), accounting for the local and imported cases. The fewer secondary cases and shorter reporting delays for the locally transmitted cases suggest that contact tracing of imported cases was effective at reducing further transmissions, which helped to keep R0 below one and the overall transmissions small.

scholarly journals Evolving epidemiology of novel coronavirus diseases 2019 and possible interruption of local transmission outside Hubei Province in China: a descriptive and modeling study

2020 ◽  
Author(s):  
Juanjuan Zhang ◽  
Maria Litvinova ◽  
Wei Wang ◽  
Yan Wang ◽  
Xiaowei Deng ◽  
...  
Keyword(s):  
Age Groups ◽  
Mainland China ◽  
The Elderly ◽  
Hubei Province ◽  
Epidemic Threshold ◽  
Epidemic Dynamics ◽  
Serial Interval ◽  
The Mean ◽  
Novel Coronavirus ◽  
Local Transmission

AbstractBackgroundThe COVID-19 epidemic originated in Wuhan City of Hubei Province in December 2019 and has spread throughout China. Understanding the fast evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.MethodsWe collected individual information on 8,579 laboratory-confirmed cases from official publically sources reported outside Hubei in mainland China, as of February 17, 2020. We estimated the temporal variation of the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.ResultsThe median age of the cases was 44 years, with an increasing of cases in younger age groups and the elderly as the epidemic progressed. The delay from symptom onset to hospital admission decreased from 4.4 days (95%CI: 0.0-14.0) until January 27 to 2.6 days (0.0-9.0) from January 28 to February 17. The mean incubation period was estimated at 5.2 days (1.8-12.4) and the mean serial interval at 5.1 days (1.3-11.6). The epidemic dynamics in provinces outside Hubei was highly variable, but consistently included a mix of case importations and local transmission. We estimate that the epidemic was self-sustained for less than three weeks with Rt reaching peaks between 1.40 (1.04-1.85) in Shenzhen City of Guangdong Province and 2.17 (1.69-2.76) in Shandong Province. In all the analyzed locations (n=10) Rt was estimated to be below the epidemic threshold since the end of January.ConclusionOur findings suggest that the strict containment measures and movement restrictions in place may contribute to the interruption of local COVID-19 transmission outside Hubei Province. The shorter serial interval estimated here implies that transmissibility is not as high as initial estimates suggested.

scholarly journals Estimating the generation interval for COVID-19 based on symptom onset data

2020 ◽  
Author(s):  
Ganyani Tapiwa ◽  
Kremer Cécile ◽  
Chen Dongxuan ◽  
Torneri Andrea ◽  
Faes Christel ◽  
...  
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
Contact Tracing ◽  
Transmission Network ◽  
Generation Interval ◽  
Period Distribution ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Modelling Studies ◽  
Interval Distribution

AbstractBackgroundEstimating key infectious disease parameters from the COVID-19 outbreak is quintessential for modelling studies and guiding intervention strategies. Whereas different estimates for the incubation period distribution and the serial interval distribution have been reported, estimates of the generation interval for COVID-19 have not been provided.MethodsWe used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates we obtained the proportions pre-symptomatic transmission and reproduction numbers.ResultsThe mean generation interval was 5.20 (95%CI 3.78-6.78) days for Singapore and 3.95 (95%CI 3.01-4.91) days for Tianjin, China when relying on a previously reported incubation period with mean 5.2 and SD 2.8 days. The proportion of pre-symptomatic transmission was 48% (95%CI 32-67%) for Singapore and 62% (95%CI 50-76%) for Tianjin, China. Estimates of the reproduction number based on the generation interval distribution were slightly higher than those based on the serial interval distribution.ConclusionsEstimating generation and serial interval distributions from outbreak data requires careful investigation of the underlying transmission network. Detailed contact tracing information is essential for correctly estimating these quantities.

scholarly journals Transmission interval estimates suggest pre-symptomatic spread of COVID-19

2020 ◽  
Author(s):  
Lauren C. Tindale ◽  
Michelle Coombe ◽  
Jessica E. Stockdale ◽  
Emma S. Garlock ◽  
Wing Yin Venus Lau ◽  
...  
Keyword(s):  
Incubation Period ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Interval Estimates ◽  
Secondary Infections ◽  
Serial Interval ◽  
Incubation Periods ◽  
Key Variables ◽  
The Mean ◽  
Interval Distribution

AbstractBackgroundAs the COVID-19 epidemic is spreading, incoming data allows us to quantify values of key variables that determine the transmission and the effort required to control the epidemic. We determine the incubation period and serial interval distribution for transmission clusters in Singapore and in Tianjin. We infer the basic reproduction number and identify the extent of pre-symptomatic transmission.MethodsWe collected outbreak information from Singapore and Tianjin, China, reported from Jan.19-Feb.26 and Jan.21-Feb.27, respectively. We estimated incubation periods and serial intervals in both populations.ResultsThe mean incubation period was 7.1 (6.13, 8.25) days for Singapore and 9 (7.92, 10.2) days for Tianjin. Both datasets had shorter incubation periods for earlier-occurring cases. The mean serial interval was 4.56 (2.69, 6.42) days for Singapore and 4.22 (3.43, 5.01) for Tianjin. We inferred that early in the outbreaks, infection was transmitted on average 2.55 and 2.89 days before symptom onset (Singapore, Tianjin). The estimated basic reproduction number for Singapore was 1.97 (1.45, 2.48) secondary cases per infective; for Tianjin it was 1.87 (1.65, 2.09) secondary cases per infective.ConclusionsEstimated serial intervals are shorter than incubation periods in both Singapore and Tianjin, suggesting that pre-symptomatic transmission is occurring. Shorter serial intervals lead to lower estimates of R0, which suggest that half of all secondary infections should be prevented to control spread.

scholarly journals Evidence for transmission of COVID-19 prior to symptom onset

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Lauren C Tindale ◽  
Jessica E Stockdale ◽  
Michelle Coombe ◽  
Emma S Garlock ◽  
Wing Yin Venus Lau ◽  
...  
Keyword(s):  
Public Health ◽  
Symptom Onset ◽  
Contact Tracing ◽  
Health Measures ◽  
Serial Interval ◽  
Incubation Periods ◽  
The Mean

We collated contact tracing data from COVID-19 clusters in Singapore and Tianjin, China and estimated the extent of pre-symptomatic transmission by estimating incubation periods and serial intervals. The mean incubation periods accounting for intermediate cases were 4.91 days (95%CI 4.35, 5.69) and 7.54 (95%CI 6.76, 8.56) days for Singapore and Tianjin, respectively. The mean serial interval was 4.17 (95%CI 2.44, 5.89) and 4.31 (95%CI 2.91, 5.72) days (Singapore, Tianjin). The serial intervals are shorter than incubation periods, suggesting that pre-symptomatic transmission may occur in a large proportion of transmission events (0.4–0.5 in Singapore and 0.6–0.8 in Tianjin, in our analysis with intermediate cases, and more without intermediates). Given the evidence for pre-symptomatic transmission, it is vital that even individuals who appear healthy abide by public health measures to control COVID-19.

scholarly journals Pre-symptomatic transmission of SARS-CoV-2 infection: a secondary analysis using published data

2020 ◽  
Author(s):  
Miriam Casey ◽  
John Griffin ◽  
Conor G. McAloon ◽  
Andrew W. Byrne ◽  
Jamie M Madden ◽  
...  
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
Generation Time ◽  
Secondary Analysis ◽  
Data Sources ◽  
Transmission Time ◽  
Contact Tracing ◽  
Published Data ◽  
List Type ◽  
Serial Interval

AbstractObjectiveTo estimate the proportion of pre-symptomatic transmission of SARS-CoV-2 infection that can occur and timing of transmission relative to symptom onset.Setting/designSecondary analysis of international published data.Data sourcesMeta-analysis of COVID-19 incubation period and a rapid systematic review of serial interval and generation time, which are published separately.ParticipantsStudies were selected for analysis if they had transparent methods and data sources and they provided enough information to simulate full distributions of serial interval or generation time. Twenty-three estimates of serial interval and five of generation time from 17 publications were included.MethodsSimulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset were calculated and the proportion of pre-symptomatic transmission was estimated.Outcome measuresTransmission time of SARS-CoV-2 relative to symptom onset and proportion of pre-symptomatic transmission.ResultsTransmission time ranged from a mean of 2.91 (95% CI: 3.18-2.64) days before symptom onset to 1.20 (0.86-1.55) days after symptom onset. Unweighted pooling of estimates of transmission time based on serial interval resulted in a mean of 0.60 days before symptom onset (3.01 days before to 1.81 days after). Proportion of pre-symptomatic transmission ranged from 42.8% (39.8%-45.9%) to 80.6% (78.1%-83.0%). The proportion of pre-symptomatic transmission from pooled estimates was 56.4% (34.9%-78.0%).ConclusionsWhilst contact rates between symptomatic infectious and susceptible people are likely to influence the proportion of pre-symptomatic transmission, there is substantial potential for pre-symptomatic transmission of SARS-CoV-2 in a range of different contexts. Our work suggests that transmission is most likely in the day before symptom onset whereas estimates suggesting most pre-symptomatic transmission highlighted mean transmission times almost three days before symptom onset. This highlights the need for rapid case detection, contact tracing and quarantine.Strengths and weaknesses of this studyWe estimate the extent and variation of pre-symptomatic transmission of SARS-CoV-2 infection across a range of contexts. This provides important information for development and targeting of control policies and for the parameterisation of transmission models.This is a secondary analysis using simulations based on published data, some of which is in pre-print form and not yet peer-reviewed. There is overlap in the contact tracing data that informed some of our source publications. We partially address this by summarising data at source location level as well as at study level.Populations where symptomatic people are rapidly isolated are likely have relatively more pre-symptomatic transmission. This should be borne in mind whilst interpreting our results, but does not affect our finding that there is substantial potential for pre-symptomatic transmission of SARS-CoV-2 infection.A strength of our approach is that it builds an understanding of pre-symptomatic transmission from a range of estimates in the literature, facilitates discussion for the drivers of variation between them, and highlights the consistent message that consideration of pre-symptomatic transmission is critical for COVID-19 control policy.

scholarly journals Estimating the distribution of the incubation period of 2019 novel coronavirus (COVID-19) infection between travelers to Hubei, China and non-travelers

2020 ◽  
Author(s):  
Char Leung
Keyword(s):  
Incubation Period ◽  
Clinical Data ◽  
Hubei Province ◽  
The Novel ◽  
Travel History ◽  
Health Authorities ◽  
Incubation Periods ◽  
The Media ◽  
Novel Coronavirus ◽  
The Individual

AbstractObjectivesAmid the continuing spread of the novel coronavirus (COVID-19), the incubation period of COVID-19 should be regularly re-assessed as more information is available upon the increase in reported cases. The present work estimated the distribution of incubation periods of patients infected in and outside Hubei province of China.MethodsClinical data were collected from the individual cases reported by the media as they were not fully available on the official pages of the Chinese health authorities. MLE was used to estimate the distributions of the incubation period.ResultsIt was found that the incubation period of patients with no travel history to Hubei was longer and more volatile.ConclusionIt is recommended that the duration of quarantine should be extended to at least 3 weeks.

scholarly journals Presymptomatic transmission of SARS-CoV-2 infection: a secondary analysis using published data

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e041240
Author(s):  
Miriam Casey-Bryars ◽  
John Griffin ◽  
Conor McAloon ◽  
Andrew Byrne ◽  
Jamie Madden ◽  
...  
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
Generation Time ◽  
Meta Analysis ◽  
Secondary Analysis ◽  
Transmission Time ◽  
Contact Tracing ◽  
Rapid Review ◽  
Published Data ◽  
Serial Interval

ObjectiveTo estimate the proportion of presymptomatic transmission of SARS-CoV-2 infection that can occur, and the timing of transmission relative to symptom onset.Setting/designSecondary analysis of international published data.Data sourcesMeta-analysis of COVID-19 incubation period and a rapid review of serial interval and generation time, which are published separately.ParticipantsData from China, the Islamic Republic of Iran, Italy, Republic of Korea, Singapore and Vietnam from December 2019 to May 2020.MethodsSimulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset, and the proportion of presymptomatic transmission, were estimated.Outcome measuresTransmission time of SARS-CoV-2 relative to symptom onset and proportion of presymptomatic transmission.ResultsBased on 18 serial interval/generation time estimates from 15 papers, mean transmission time relative to symptom onset ranged from −2.6 (95% CI −3.0 to –2.1) days before infector symptom onset to 1.4 (95% CI 1.0 to 1.8) days after symptom onset. The proportion of presymptomatic transmission ranged from 45.9% (95% CI 42.9% to 49.0%) to 69.1% (95% CI 66.2% to 71.9%).ConclusionsThere is substantial potential for presymptomatic transmission of SARS-CoV-2 across a range of different contexts. This highlights the need for rapid case detection, contact tracing and quarantine. The transmission patterns that we report reflect the combination of biological infectiousness and transmission opportunities which vary according to context.

scholarly journals Incubation period and serial interval of Covid-19 in a chain of infections in Bahia Blanca (Argentina)

2020 ◽  
Author(s):  
Valentina Viego ◽  
Milva Geri ◽  
Juan Castiglia ◽  
Ezequiel Jouglard
Keyword(s):  
Incubation Period ◽  
Missing Values ◽  
Close Contact ◽  
Point Estimation ◽  
Right Censoring ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Illness Onset ◽  
Serial Interval ◽  
The Mean

AbstractObjectiveTo estimate the incubation period and the serial interval of Covid-19 from a sample of symptomatic patients in Bahia Blanca city.MethodsWe collected dates of illness onset for primary cases (infectors) and secondary cases (infectees) for the first 18 secondary patients infected with SARS-Cov-2 in Bahia Blanca (Argentina). We ranked the fiability of the data depending upon certainty about the identification of the infector and the date of exposition to infector.The sample has some missing values. In the case of incubation, as 3 patients were infected by other household members, we only have 15 observations with an observed date of exposition. For the estimation of serial interval, one patient became ill from close contact with an asymptomatic infectious. Also, estimations of both the incubation period and the serial interval were carried using the full sample and a subsample with higher certainty about the transmissor and date of exposition. By the time the dataset was prepared all infectors were recovered so estimations do need to take into account right censoring.ResultsThe mean incubation period for symptomatic patients is 7.9 days (95% CI: 4.6, 11.1) considering the sample of 15 cases patients and 7.5 days (95% CI: 4.1, 10.9) if the sample is restricted to the most certain cases (n=12). The median is 6.1 (95% CI: 4.1, 9.2) and 5.8 (95% CI: 3.6, 9.3) respectively. Moreover, 97.5% of symptomatic cases will develop symptoms afert 13.6 days from exposition (95% CI 10.7, 16.5).The point estimation for the mean serial interval is 6.8 days (95% CI: 4.0-9.6). Considering only the most certain pairs, the mean serial interval is estimated at 5.5 days (95% CI: 2.8, 8.1). The estimated median serial intervals were 5.2 (95% CI: 3.0, 8.1) and 4.1 (95% CI: 2.0, 6.9) days respectively.ConclusionsEvidence from Bahia Blanca (Argentina) suggests that the median and mean serial interval of Covid-19 is shorter than the incubation period. This suggests that a pre-symptomatic transmission is not negligible. Comparisons with foreign estimates show that incubation period and serial interval could be longer in Bahia Blanca city than in other regions. That poses a signal of opportunity to attain more timely contact tracing and effective isolation.HighlightsWe estimate the incubation period in a sample of 15 symptomatic patients with Covid-19 in Bahia Blanca city (Argentina).We estimate the serial interval for Covid-19 infections in a sample of 17 infector-infectee pairs detected in Bahia Blanca city (Argentina).The median serial interval is lower to the median incubation period, suggesting a transmission is taking place also during the pre-symptomatic phase.The incubation period and serial interval of Covid-19 in Bahía Blanca city seem to take more days than in Asian regions. This finding slows down the pace of health assistance to patients (conditional to public interventions).Longer serial intervals help in tracing contacts and show relative slow turnover of case generations. At the same time, if symptoms take longer time to emerge, long serial intervals may also increase the reproductive number if contact tracing and effective isolation measures are placed untimely.

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