scholarly journals Estimating the presymptomatic transmission of COVID19 using incubation period and serial interval data

2020 ◽  
Author(s):  
Weituo Zhang
Keyword(s):  
Mathematical Models ◽  
Incubation Period ◽  
Symptom Onset ◽  
Interval Data ◽  
Serial Interval ◽  
Imported Cases

AbstractWe estimated the fraction and timing of presymptomatic transmissions of COVID19 with mathematical models combining the available data of the incubation period and serial interval. We found that up to 79.7% transmissions could be presymptomatic among the imported cases in China outside Wuhan. The average timing of presymptomatic transmissions is 3.8 days (SD = 6.1) before the symptom onset, which is much earlier than previously assumed.

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 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 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 Epidemiological parameters of coronavirus disease 2019: a pooled analysis of publicly reported individual data of 1155 cases from seven countries

2020 ◽  
Author(s):  
Shujuan Ma ◽  
Jiayue Zhang ◽  
Minyan Zeng ◽  
Qingping Yun ◽  
Wei Guo ◽  
...  
Keyword(s):  
Latent Period ◽  
Incubation Period ◽  
Symptom Onset ◽  
Severe Disease ◽  
Individual Data ◽  
Robust Estimates ◽  
Upper Limit ◽  
Serial Interval ◽  
Epidemiological Parameters ◽  
Time Point

SummaryBackgroundThe outbreak of coronavirus disease 2019 (COVID-19) has been declared a pandemic by the World Health Organization, while several key epidemiological parameters of the disease remain to be clarified. This study aimed to obtain robust estimates of the incubation period, upper limit of latent period (interval between infector’s exposure and infectee’s exposure), serial interval, time point of exposure (the day of infectee’s exposure to infector relative to the latter’s symptom onset date) and basic reproduction number (R0) of COVID-19.MethodsBetween late February and early March of 2020, the individual data of laboratory confirmed cases of COVID-19 were retrieved from 10728 publicly available reports released by the health authorities of and outside China and from 1790 publications identified in PubMed and CNKI. To be eligible, a report had to contain the data that allowed for estimation of at least one parameter. As relevant data mainly came from clustering cases, the clusters for which no evidence was available to establish transmission order were all excluded to ensure accuracy of estimates. Additionally, only the cases with an exposure period spanning 3 days or less were included in the estimation of parameters involving exposure date, and a simple method for determining exposure date was adopted to ensure the error of estimates be small (< 0.3 day). Depending on specific parameters, three or four of normal, lognormal, Weibull, and gamma distributions were fitted to the datasets and the results from appropriate models were presented.FindingsIn total, 1155 cases from China, Japan, Singapore, South Korea, Vietnam, Germany and Malaysia were included for the final analysis. The mean and standard deviation were 7.44 days and 4.39 days for incubation period, 2.52 days and 3.95 days for the upper limit of latent period, 6.70 days and 5.20 days for serial interval, and −0.19 day (i.e., 0.19 day before infector’s symptom onset) and 3.32 days for time point of exposure. R0 was estimated to be 1.70 and 1.78 based on two different formulas. For 39 (6.64%) cases, the incubation periods were longer than 14 days. In 102 (43.78%) infector-infectee pairs, transmission occurred before infectors’ symptom onsets. In 27 (3.92%) infector-infectee pairs, infectees’ symptom onsets occurred before those of infectors. Stratified analysis showed that incubation period and serial interval were consistently longer for those with less severe disease and for those whose primary cases had less severe disease. Asymptomatic transmission was also observed.InterpretationThis study obtained robust estimates of several key epidemiological parameters of COVID-19. The findings support current practice of 14-day quarantine of persons with potential exposure, but also suggest that longer monitoring periods might be needed for selected groups. The estimates of serial interval, time point of exposure and latent period provide consistent evidence on pre-symptomatic transmission. This together with asymptomatic transmission and the generally longer incubation and serial interval of less severe cases suggests a high risk of long-term epidemic in the absence of appropriate control measures.FundingThis work received no funding from any source.

scholarly journals Transmission of SARS-CoV-2 before and after symptom onset: impact of nonpharmaceutical interventions in China

2020 ◽  
Author(s):  
Mary Bushman ◽  
Colin Worby ◽  
Hsiao-Han Chang ◽  
Moritz Kraemer ◽  
William P. Hanage
Keyword(s):  
Symptom Onset ◽  
Relative Frequency ◽  
Population Level ◽  
Interval Data ◽  
Contact Tracing ◽  
Serial Interval ◽  
Before And After ◽  
Primary Means ◽  
Nonpharmaceutical Interventions

AbstractNonpharmaceutical interventions, such as contact tracing and quarantine, are currently the primary means of controlling the spread of SARS-CoV-2; however, it remains uncertain which interventions are most effective at reducing transmission at the population level. Using serial interval data from before and after the rollout of nonpharmaceutical interventions in China, we estimate that the relative frequency of presymptomatic transmission increased from 34% before the rollout to 71% afterward. The shift touward earlier transmission indicates a disproportionate reduction in transmission post-symptom onset. We estimate that, following the rollout of nonpharmaceutical interventions, transmission post-symptom onset was reduced by 82% whereas presymptomatic transmission decreased by only 16%. These findings suggest that interventions which limit opportunities for transmission in the later stages of infection, such as contact tracing and isolation, may have been particularly effective at reducing transmission of SARS-CoV-2.

scholarly journals Transmission of SARS-CoV-2 before and after symptom onset: impact of nonpharmaceutical interventions in China

2021 ◽  
Author(s):  
Mary Bushman ◽  
Colin Worby ◽  
Hsiao-Han Chang ◽  
Moritz U. G. Kraemer ◽  
William P. Hanage
Keyword(s):  
Symptom Onset ◽  
Relative Frequency ◽  
Population Level ◽  
Interval Data ◽  
Contact Tracing ◽  
Serial Interval ◽  
Before And After ◽  
Primary Means ◽  
Nonpharmaceutical Interventions

AbstractNonpharmaceutical interventions, such as contact tracing and quarantine, have been the primary means of controlling the spread of SARS-CoV-2; however, it remains uncertain which interventions are most effective at reducing transmission at the population level. Using serial interval data from before and after the rollout of nonpharmaceutical interventions in China, we estimate that the relative frequency of presymptomatic transmission increased from 34% before the rollout to 71% afterward. The shift toward earlier transmission indicates a disproportionate reduction in transmission post-symptom onset. We estimate that, following the rollout of nonpharmaceutical interventions, transmission post-symptom onset was reduced by 82% whereas presymptomatic transmission decreased by only 16%. The observation that only one-third of transmission was presymptomatic at baseline, combined with the finding that NPIs reduced presymptomatic transmission by less than 20%, suggests that the overall impact of NPIs was driven in large part by reductions in transmission following symptom onset. This implies that interventions which limit opportunities for transmission in the later stages of infection, such as contact tracing and isolation, are particularly important for control of SARS-CoV-2. Interventions which specifically reduce opportunities for presymptomatic transmission, such as quarantine of asymptomatic contacts, are likely to have smaller, but non-negligible, effects on overall transmission.

scholarly journals Transmission of corona virus disease 2019 during the incubation period may lead to a quarantine loophole

2020 ◽  
Author(s):  
Wei Xia ◽  
Jiaqiang Liao ◽  
Chunhui Li ◽  
Yuanyuan Li ◽  
Xi Qian ◽  
...  
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
First Generation ◽  
Virus Disease ◽  
Demographic Characteristics ◽  
Corona Virus ◽  
Serial Interval ◽  
History Of ◽  
Exposure History ◽  
Close Contacts

AbstractBackgroundThe ongoing outbreak of novel corona virus disease 2019 (COVID-19) in Wuhan, China, is arousing international concern. This study evaluated whether and when the infected but asymptomatic cases during the incubation period could infect others.MethodsWe collected data on demographic characteristics, exposure history, and symptom onset day of the confirmed cases, which had been announced by the Chinese local authorities. We evaluated the potential of transmission during the incubation period in 50 infection clusters, including 124 cases. All the secondary cases had a history of contact with their first-generation cases prior to symptom onset.ResultsThe estimated mean incubation period for COVID-19 was 4.9 days (95% confidence interval [CI], 4.4 to 5.4) days, ranging from 0.8 to 11.1 days (2.5th to 97.5th percentile). The observed mean and standard deviation (SD) of serial interval was 4.1±3.3 days, with the 2.5th and 97.5th percentiles at −1 and 13 days. The infectious curve showed that in 73.0% of the secondary cases, their date of getting infected was before symptom onset of the first-generation cases, particularly in the last three days of the incubation period.ConclusionsThe results indicated the transmission of COVID-9 occurs among close contacts during the incubation period, which may lead to a quarantine loophole. Strong and effective countermeasures should be implemented to prevent or mitigate asymptomatic transmission during the incubation period in populations at high risk.

scholarly journals Challenges Caused by Imported Cases Abroad for the Prevention and Control of COVID-19 in China

2021 ◽  
Vol 8 ◽  
Author(s):  
Jianfei Zhu ◽  
Qingqing Zhang ◽  
Chenghui Jia ◽  
Shuonan Xu ◽  
Jie Lei ◽  
...  
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
Onset Time ◽  
Interquartile Range ◽  
Categorical Variables ◽  
Chinese Government ◽  
Asymptomatic Patients ◽  
Diagnostic Time ◽  
Imported Cases ◽  
Epidemiological Characteristics

Background: Overseas imported cases of COVID-19 continue to increase in China, so we conducted this study to review the epidemiological characteristics of these patients.Methods: From February 26 to April 4, 2020, the imported cases from abroad were enrolled in this study. The effect of prevention countermeasures in curbing the spread of COVID-19 was assessed in this study. Moreover, we defined incubation period and confirmed time as from the date of leaving the epicenter to date of symptom onset and date of final diagnosed, respectively, and the interval of symptom onset to final diagnosed time was defined as diagnostic time. Categorical variables were summarized as numbers and percentages, and the difference among the variables were analyzed.Results: For 670 cases imported from abroad, 555 were Chinese and 115 were foreigners. Apparently, confirmed cases had significantly decreased after China was compelled to temporarily suspend the entry of foreign passport holders with valid visas or residence permits; 6 days after implement of controlled measures, the daily new confirmed cases were reduced to 13 cases. Moreover, about 84.3% of patients (166/197) presented symptoms 1 week after leaving the epicenter, and notably seven patients (3.6%) had symptoms 2 weeks after leaving the epicenter. The median incubation period was 3.0 days (inter quartile range, 1.0 to 6.0), the 95th percentile was 11.6 days. Additionally, most of cases (92.9%) were detected positively of nucleic acid after symptom onset with 4 days, the median diagnostic time was 2.0 days (interquartile range, 1.0 to 3.0), and the 95th percentile of the distribution was 5.0 days. Finally, about 5.8% of patients were healthy carriers, and the median confirmed time of asymptomatic patients was 4.0 days (interquartile range, 2.0 to 9.0). The following variables might be associated with confirmed time: symptom type (P = 0.005), exported regions (P &lt; 0.001), and symptom onset time (P &lt; 0.001).Conclusions: The prevention countermeasures for imported cases implemented by the Chinese government played an indispensable role in curbing the spread of COVID-19; the time of departure from epicenter could provide an estimate of the incubation period; and a confirmed time, 2-week quarantine period might need to be prolonged, while asymptomatic patients should be closely monitored.

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 The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019

2020 ◽  
Vol 5 ◽  
pp. 58 ◽  
Author(s):  
Yang Liu ◽  
Sebastian Funk ◽  
Stefan Flasche ◽  
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
Case Finding ◽  
Mitigation Strategies ◽  
Potential Contribution ◽  
Active Case Finding ◽  
Symptomatic Infection ◽  
Active Case ◽  
Secondary Infections ◽  
Serial Interval

Background: Pre-symptomatic transmission can be a key determinant of the effectiveness of containment and mitigation strategies for infectious diseases, particularly if interventions rely on syndromic case finding. For COVID-19, infections in the absence of apparent symptoms have been reported frequently alongside circumstantial evidence for asymptomatic or pre-symptomatic transmission. We estimated the potential contribution of pre-symptomatic cases to COVID-19 transmission. Methods: Using the probability for symptom onset on a given day inferred from the incubation period, we attributed the serial interval reported from Shenzen, China, into likely pre-symptomatic and symptomatic transmission. We used the serial interval derived for cases isolated more than 6 days after symptom onset as the no active case finding scenario and the unrestricted serial interval as the active case finding scenario. We reported the estimate assuming no correlation between the incubation period and the serial interval alongside a range indicating alternative assumptions of positive and negative correlation. Results: We estimated that 23% (range accounting for correlation: 12 – 28%) of transmissions in Shenzen may have originated from pre-symptomatic infections. Through accelerated case isolation following symptom onset, this percentage increased to 46% (21 – 46%), implying that about 35% of secondary infections among symptomatic cases have been prevented. These results were robust to using reported incubation periods and serial intervals from other settings. Conclusions: Pre-symptomatic transmission may be essential to consider for containment and mitigation strategies for COVID-19.

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