scholarly journals Serial interval of novel coronavirus (COVID-19) infections

2020 ◽  
Author(s):  
Hiroshi Nishiura ◽  
Natalie M. Linton ◽  
Andrei R. Akhmetzhanov
Keyword(s):  
Incubation Period ◽  
Credible Interval ◽  
Substantial Proportion ◽  
List Type ◽  
Illness Onset ◽  
Full Dataset ◽  
Serial Interval ◽  
Novel Coronavirus ◽  
Right Truncation ◽  
Published Research

AbstractObjectiveTo estimate the serial interval of novel coronavirus (COVID-19) from information on 28 infector-infectee pairs.MethodsWe collected dates of illness onset for primary cases (infectors) and secondary cases (infectees) from published research articles and case investigation reports. We subjectively ranked the credibility of the data and performed analyses on both the full dataset (n=28) and a subset of pairs with highest certainty in reporting (n=18). In addition, we adjusting for right truncation of the data as the epidemic is still in its growth phase.ResultsAccounting for right truncation and analyzing all pairs, we estimated the median serial interval at 4.0 days (95% credible interval [CrI]: 3.1, 4.9). Limiting our data to only the most certain pairs, the median serial interval was estimated at 4.6 days (95% CrI: 3.5, 5.9).ConclusionsThe serial interval of COVID-19 is shorter than its median incubation period. This suggests that a substantial proportion of secondary transmission may occur prior to illness onset. The COVID-19 serial interval is also shorter than the serial interval of severe acute respiratory syndrome (SARS), indicating that calculations made using the SARS serial interval may introduce bias.Highlights-The serial interval of novel coronavirus (COVID-19) infections was estimated from a total of 28 infector-infectee pairs.-The median serial interval is shorter than the median incubation period, suggesting a substantial proportion of pre-symptomatic transmission.-A short serial interval makes it difficult to trace contacts due to the rapid turnover of case generations.

scholarly journals Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data

2020 ◽  
Vol 9 (2) ◽  
pp. 538 ◽  
Author(s):  
Natalie Linton ◽  
Tetsuro Kobayashi ◽  
Yichi Yang ◽  
Katsuma Hayashi ◽  
Andrei Akhmetzhanov ◽  
...  
Keyword(s):  
Incubation Period ◽  
Case Fatality ◽  
Illness Onset ◽  
Event Date ◽  
History Of ◽  
Novel Coronavirus ◽  
Case Fatality Risk ◽  
Right Truncation ◽  
Epidemiological Characteristics ◽  
Mean Time

The geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2–14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. The mean time from illness onset to hospital admission (for treatment and/or isolation) was estimated at 3–4 days without truncation and at 5–9 days when right truncated. Based on the 95th percentile estimate of the incubation period, we recommend that the length of quarantine should be at least 14 days. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk.

scholarly journals Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data

2020 ◽  
Author(s):  
Natalie M. Linton ◽  
Tetsuro Kobayashi ◽  
Yichi Yang ◽  
Katsuma Hayashi ◽  
Andrei R. Akhmetzhanov ◽  
...  
Keyword(s):  
Incubation Period ◽  
Case Fatality ◽  
Illness Onset ◽  
Event Date ◽  
History Of ◽  
Novel Coronavirus ◽  
Case Fatality Risk ◽  
Right Truncation ◽  
Epidemiological Characteristics ◽  
Mean Time

AbstractThe geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2–14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. The mean time from illness onset to hospital admission (for treatment and/or isolation) was estimated at 3–4 days without truncation and at 5–9 days when right truncated. Based on the 95th percentile estimate of the incubation period, we recommend that the length of quarantine should be at least 14 days. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk.

scholarly journals Early Transmission Dynamics of Novel Coronavirus (COVID-19) in Nigeria

2020 ◽  
Vol 17 (9) ◽  
pp. 3054 ◽  
Author(s):  
Oyelola A. Adegboye ◽  
Adeshina I. Adekunle ◽  
Ezra Gayawan
Keyword(s):  
Doubling Time ◽  
Reproduction Number ◽  
Infected Individual ◽  
Credible Interval ◽  
World Health ◽  
Time Interval ◽  
Serial Interval ◽  
Imported Cases ◽  
Novel Coronavirus ◽  
Health Organization

On 31 December 2019, the World Health Organization (WHO) was notified of a novel coronavirus disease in China that was later named COVID-19. On 11 March 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on 27 February 2020. This study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria. We estimated the early transmissibility via time-varying reproduction number based on the Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector), and adjusted for disease importation. By 11 April 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% confidence interval (CI): 0.05–0.10) with a doubling time of 9.84 days (95% CI: 7.28–15.18). Separately for imported cases (travel-related) and local cases, the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using a three-weekly window while adjusting for imported cases. The estimated reproduction number was 4.98 (95% CrI: 2.65–8.41) at day 22 (19 March 2020), peaking at 5.61 (95% credible interval (CrI): 3.83–7.88) at day 25 (22 March 2020). The median reproduction number over the study period was 2.71 and the latest value on 11 April 2020, was 1.42 (95% CrI: 1.26–1.58). These 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.

scholarly journals Transmission onset distribution of COVID-19

2020 ◽  
Author(s):  
June Young Chun ◽  
Gyuseung Baek ◽  
Yongdai Kim
Keyword(s):  
Standard Deviation ◽  
Incubation Period ◽  
Bayesian Methods ◽  
Symptom Onset ◽  
Onset Time ◽  
Preventive Measure ◽  
Credible Interval ◽  
Serial Interval ◽  
Interval Distribution ◽  
Key Parameter

AbstractObjectivesThe distribution of the transmission onset of COVID-19 relative to the symptom onset is a key parameter for infection control. It is often not easy to study the transmission onset time, as is difficult to know who infected whom exactly when.MethodsWe inferred transmission onset time from 72 infector-infectee pairs in South Korea, either with known or inferred contact dates by means of incubation period. Combining this data with known information of infector’s symptom onset, we could generate the transmission onset distribution of COVID-19, using Bayesian methods. Serial interval distribution could be automatically estimated from our data.ResultsWe estimated the median transmission onset to be 1.31 days (standard deviation, 2.64 days) after symptom onset with peak at 0.72 days before symptom onset. The pre-symptomatic transmission proportion was 37% (95% credible interval [CI], 16–52%). The median incubation period was estimated to be 2.87 days (95% CI, 2.33–3.50 days) and the median serial interval to be 3.56 days (95% CI, 2.72–4.44 days).ConclusionsConsidering the transmission onset distribution peaked with the symptom onset and the pre-symptomatic transmission proportion is substantial, the usual preventive measure might be too late to prevent SARS-CoV-2 transmission.

scholarly journals Estimating transmission dynamics and serial interval of the first wave of COVID-19 infections under different control measures: a statistical analysis in Tunisia from February 29 to May 5, 2020

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Khouloud Talmoudi ◽  
Mouna Safer ◽  
Hejer Letaief ◽  
Aicha Hchaichi ◽  
Chahida Harizi ◽  
...  
Keyword(s):  
Credible Interval ◽  
Emerging Diseases ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Epidemic Threshold ◽  
Illness Onset ◽  
Intervention Measures ◽  
Temporal Reproduction ◽  
Serial Interval

Abstract Background Describing transmission dynamics of the outbreak and impact of intervention measures are critical to planning responses to future outbreaks and providing timely information to guide policy makers decision. We estimate serial interval (SI) and temporal reproduction number (Rt) of SARS-CoV-2 in Tunisia. Methods We collected data of investigations and contact tracing between March 1, 2020 and May 5, 2020 as well as illness onset data during the period February 29–May 5, 2020 from National Observatory of New and Emerging Diseases of Tunisia. Maximum likelihood (ML) approach is used to estimate dynamics of Rt. Results Four hundred ninety-one of infector-infectee pairs were involved, with 14.46% reported pre-symptomatic transmission. SI follows Gamma distribution with mean 5.30 days [95% Confidence Interval (CI) 4.66–5.95] and standard deviation 0.26 [95% CI 0.23–0.30]. Also, we estimated large changes in Rt in response to the combined lockdown interventions. The Rt moves from 3.18 [95% Credible Interval (CrI) 2.73–3.69] to 1.77 [95% CrI 1.49–2.08] with curfew prevention measure, and under the epidemic threshold (0.89 [95% CrI 0.84–0.94]) by national lockdown measure. Conclusions Overall, our findings highlight contribution of interventions to interrupt transmission of SARS-CoV-2 in Tunisia.

scholarly journals Estimating transmission dynamics and serial interval of the first wave of COVID-19 infections under different control measures: A statistical analysis in Tunisia from February 29 to May 5, 2020 

2020 ◽  
Author(s):  
Khouloud Talmoudi ◽  
Mouna Safer ◽  
Hejer Letaief ◽  
Aicha Hchaichi ◽  
Chahida Harizi ◽  
...  
Keyword(s):  
Credible Interval ◽  
Emerging Diseases ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Epidemic Threshold ◽  
Illness Onset ◽  
Intervention Measures ◽  
Temporal Reproduction ◽  
Serial Interval

Abstract Background: Describing transmission dynamics of the outbreak and impact of intervention measures are critical to planning responses to future outbreaks and providing timely information to guide policy makers decision. We estimate serial interval (SI) and temporal reproduction number (Rt) of SARS-CoV-2 in Tunisia. Methods: We collected data of investigations and contact tracing between March 1, 2020 and May 5, 2020 as well as illness onset data during the period February 29-May 5, 2020 from National Observatory of New and Emerging Diseases of Tunisia. Maximum likelihood (ML) approach is used to estimate dynamics of Rt. Results: 491 of infector-infectee pairs were involved, with 14.46% reported pre-symptomatic transmission. SI follows Gamma distribution with mean 5.30 days [95% Confidence Interval (CI) 4.66-5.95] and standard deviation 0.26 [95% CI 0.23-0.30]. Also, we estimated large changes in Rt in response to the combined lockdown interventions. The Rt moves from 3.18 [95% Credible Interval (CrI) 2.73-3.69] to 1.77 [95% CrI 1.49-2.08] with curfew prevention measure, and under the epidemic threshold (0.89 [95% CrI 0.84-0.94]) by national lockdown measure.Conclusions: Overall, our findings highlight contribution of interventions to interrupt transmission of SARS-CoV-2 in Tunisia.

scholarly journals Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20–28 January 2020

2020 ◽  
Vol 25 (5) ◽  
Author(s):  
Jantien A Backer ◽  
Don Klinkenberg ◽  
Jacco Wallinga
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
Credible Interval ◽  
Viral Pneumonia ◽  
Case Definitions ◽  
Travel History ◽  
The Mean ◽  
Novel Coronavirus

A novel coronavirus (2019-nCoV) is causing an outbreak of viral pneumonia that started in Wuhan, China. Using the travel history and symptom onset of 88 confirmed cases that were detected outside Wuhan in the early outbreak phase, we estimate the mean incubation period to be 6.4 days (95% credible interval: 5.6–7.7), ranging from 2.1 to 11.1 days (2.5th to 97.5th percentile). These values should help inform 2019-nCoV case definitions and appropriate quarantine durations.

scholarly journals Reconstruction of Transmission Pairs for Novel Coronavirus Disease 2019 (COVID-19) in Mainland China: Estimation of Superspreading Events, Serial Interval, and Hazard of Infection

2020 ◽  
Author(s):  
Xiao-Ke Xu ◽  
Xiao Fan Liu ◽  
Ye Wu ◽  
Sheikh Taslim Ali ◽  
Zhanwei Du ◽  
...  
Keyword(s):  
Social Relationships ◽  
Mainland China ◽  
Credible Interval ◽  
Old People ◽  
Travel History ◽  
Serial Interval ◽  
Significant Barrier ◽  
Working Age ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions

Abstract Background Knowledge on the epidemiological features and transmission patterns of novel coronavirus disease (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 1407 transmission pairs that formed 643 transmission clusters in mainland China was reconstructed from 9120 COVID-19 confirmed cases reported during 15 January–29 February 2020. Statistical model fittings were used to identify the superspreading events and estimate serial interval distributions. Age- and sex-stratified hazards of infection were estimated for household vs nonhousehold transmissions. Results There were 34 primary cases identified as superspreaders, with 5 superspreading events occurred within households. Mean and standard deviation of serial intervals were estimated as 5.0 (95% credible interval [CrI], 4.4–5.5) days 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 nonhousehold transmissions, respectively. The hazard of being infected outside of households is higher for people aged 18–64 years, whereas hazard of being infected within households is higher for young and old people. Conclusions Nonnegligible frequency of superspreading 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 nonpharmaceutical interventions to mitigate this pandemic.

scholarly journals Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions

Science ◽  
2020 ◽  
Vol 369 (6507) ◽  
pp. 1106-1109 ◽  
Author(s):  
Sheikh Taslim Ali ◽  
Lin Wang ◽  
Eric H. Y. Lau ◽  
Xiao-Ke Xu ◽  
Zhanwei Du ◽  
...  
Keyword(s):  
Mainland China ◽  
Time Estimation ◽  
Control Measures ◽  
Illness Onset ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions ◽  
The Impact ◽  
Over Time

Studies of novel coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have reported varying estimates of epidemiological parameters, including serial interval distributions—i.e., the time between illness onset in successive cases in a transmission chain—and reproduction numbers. By compiling a line-list database of transmission pairs in mainland China, we show that mean serial intervals of COVID-19 shortened substantially from 7.8 to 2.6 days within a month (9 January to 13 February 2020). This change was driven by enhanced nonpharmaceutical interventions, particularly case isolation. We also show that using real-time estimation of serial intervals allowing for variation over time provides more accurate estimates of reproduction numbers than using conventionally fixed serial interval distributions. These findings could improve our ability to assess transmission dynamics, forecast future incidence, and estimate the impact of control measures.

scholarly journals The transmissibility of novel Coronavirus in the early stages of the 2019-20 outbreak in Wuhan: Exploring initial point-source exposure sizes and durations using scenario analysis

2020 ◽  
Vol 5 ◽  
pp. 17 ◽  
Author(s):  
Sam Abbott ◽  
Joel Hellewell ◽  
James Munday ◽  
Sebastian Funk ◽  
Keyword(s):  
Point Source ◽  
Process Model ◽  
Initial Point ◽  
Credible Interval ◽  
Wholesale Market ◽  
Initial Exposure ◽  
Transmission Event ◽  
Serial Interval ◽  
Novel Coronavirus ◽  
Initial Transmission

Background: The current novel coronavirus outbreak appears to have originated from a point-source exposure event at Huanan seafood wholesale market in Wuhan, China. There is still uncertainty around the scale and duration of this exposure event. This has implications for the estimated transmissibility of the coronavirus and as such, these potential scenarios should be explored.  Methods: We used a stochastic branching process model, parameterised with available data where possible and otherwise informed by the 2002-2003 Severe Acute Respiratory Syndrome (SARS) outbreak, to simulate the Wuhan outbreak. We evaluated scenarios for the following parameters: the size, and duration of the initial transmission event, the serial interval, and the reproduction number (R0). We restricted model simulations based on the number of observed cases on the 25th of January, accepting samples that were within a 5% interval on either side of this estimate. Results: Using a pre-intervention SARS-like serial interval suggested a larger initial transmission event and a higher R0 estimate. Using a SARs-like serial interval we found that the most likely scenario produced an R0 estimate between 2-2.7 (90% credible interval (CrI)). A pre-intervention SARS-like serial interval resulted in an R0 estimate between 2-3 (90% CrI). There were other plausible scenarios with smaller events sizes and longer duration that had comparable R0 estimates. There were very few simulations that were able to reproduce the observed data when R0 was less than 1. Conclusions: Our results indicate that an R0 of less than 1 was highly unlikely unless the size of the initial exposure event was much greater than currently reported. We found that R0 estimates were comparable across scenarios with decreasing event size and increasing duration. Scenarios with a pre-intervention SARS-like serial interval resulted in a higher R0 and were equally plausible to scenarios with SARs-like serial intervals.

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