Browse
Submit Data
Databases
API
Help

Dataset Information

20 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Estimation of the serial interval of influenza.

ABSTRACT: : Estimates of the clinical-onset serial interval of human influenza infection (time between onset of symptoms in an index case and a secondary case) are used to inform public health policy and to construct mathematical models of influenza transmission. We estimate the serial interval of laboratory-confirmed influenza transmission in households.: Index cases were recruited after reporting to a primary healthcare center with symptoms. Members of their households were followed-up with repeated home visits.: Assuming a Weibull model and accounting for selection bias inherent in our field study design, we used symptom-onset times from 14 pairs of infector/infectee to estimate a mean serial interval of 3.6 days (95% confidence interval = 2.9-4.3 days), with standard deviation 1.6 days.: The household serial interval of influenza may be longer than previously estimated. Studies of the complete serial interval, based on transmission in all community contexts, are a priority.

SUBMITTER: Cowling BJ

PROVIDER: S-EPMC3057478 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Estimation of the serial interval of influenza.

Cowling Benjamin J BJ Fang Vicky J VJ Riley Steven S Malik Peiris J S JS Leung Gabriel M GM

Epidemiology (Cambridge, Mass.) 20090501 3

<h4>Background</h4>: Estimates of the clinical-onset serial interval of human influenza infection (time between onset of symptoms in an index case and a secondary case) are used to inform public health policy and to construct mathematical models of influenza transmission. We estimate the serial interval of laboratory-confirmed influenza transmission in households.<h4>Methods</h4>: Index cases were recruited after reporting to a primary healthcare center with symptoms. Members of their households ...[more]

PMID: 19279492

Similar Datasets

Estimated Incubation Period and Serial Interval for Human-to-Human Influenza A(H7N9) Virus Transmission.

Project description:We estimated the incubation period and serial interval for human-to-human-transmitted avian influenza A(H7N9) virus infection using case-patient clusters from epidemics in China during 2013-2017. The median incubation period was 4 days and serial interval 9 days. China's 10-day monitoring period for close contacts of case-patients should detect most secondary infections.

| S-EPMC6759274 | biostudies-literature

Serial binary interval ratios improve rhythm reproduction.

Project description:Musical rhythm perception is a natural human ability that involves complex cognitive processes. Rhythm refers to the organization of events in time, and musical rhythms have an underlying hierarchical metrical structure. The metrical structure induces the feeling of a beat and the extent to which a rhythm induces the feeling of a beat is referred to as its metrical strength. Binary ratios are the most frequent interval ratio in musical rhythms. Rhythms with hierarchical binary ratios are better discriminated and reproduced than rhythms with hierarchical non-binary ratios. However, it remains unclear whether a superiority of serial binary over non-binary ratios in rhythm perception and reproduction exists. In addition, how different types of serial ratios influence the metrical strength of rhythms remains to be elucidated. The present study investigated serial binary vs. non-binary ratios in a reproduction task. Rhythms formed with exclusively binary (1:2:4:8), non-binary integer (1:3:5:6), and non-integer (1:2.3:5.3:6.4) ratios were examined within a constant meter. The results showed that the 1:2:4:8 rhythm type was more accurately reproduced than the 1:3:5:6 and 1:2.3:5.3:6.4 rhythm types, and the 1:2.3:5.3:6.4 rhythm type was more accurately reproduced than the 1:3:5:6 rhythm type. Further analyses showed that reproduction performance was better predicted by the distribution pattern of event occurrences within an inter-beat interval, than by the coincidence of events with beats, or the magnitude and complexity of interval ratios. Whereas rhythm theories and empirical data emphasize the role of the coincidence of events with beats in determining metrical strength and predicting rhythm performance, the present results suggest that rhythm processing may be better understood when the distribution pattern of event occurrences is taken into account. These results provide new insights into the mechanisms underlining musical rhythm perception.

| S-EPMC3734359 | biostudies-literature

Estimation of Serial Interval and Reproduction Number to Quantify the Transmissibility of SARS-CoV-2 Omicron Variant in South Korea.

Project description:The omicron variant (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was the predominant variant in South Korea from late January 2022. In this study, we aimed to report the early estimates of the serial interval distribution and reproduction number to quantify the transmissibility of the omicron variant in South Korea between 25 November 2021 and 31 December 2021. We analyzed 427 local omicron cases and reconstructed 73 transmission pairs. We used a maximum likelihood estimation to assess serial interval distribution from transmission pair data and reproduction numbers from 74 local cases in the first local outbreak. We estimated that the mean serial interval was 3.78 (standard deviation, 0.76) days, which was significantly shorter in child infectors (3.0 days) compared to adult infectors (5.0 days) (p < 0.01). We estimated the mean reproduction number was 1.72 (95% CrI, 1.60−1.85) for the omicron variant during the first local outbreak. Strict adherence to public health measures, particularly in children, should be in place to reduce the transmission risk of the highly transmissible omicron variant in the community.

| S-EPMC8948735 | biostudies-literature

Serial interval of novel coronavirus (COVID-19) infections.

Project description:OBJECTIVE:To estimate the serial interval of novel coronavirus (COVID-19) from information on 28 infector-infectee pairs. METHODS:We 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 adjust for right truncation of the data as the epidemic is still in its growth phase. RESULTS:Accounting 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). CONCLUSIONS:The serial interval of COVID-19 is close to or 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.

| S-EPMC7128842 | biostudies-literature

Estimation of the serial interval and proportion of pre-symptomatic transmission events of COVID- 19 in Ireland using contact tracing data.

Project description:BackgroundThe serial interval is the period of time between the onset of symptoms in an infector and an infectee and is an important parameter which can impact on the estimation of the reproduction number. Whilst several parameters influencing infection transmission are expected to be consistent across populations, the serial interval can vary across and within populations over time. Therefore, local estimates are preferable for use in epidemiological models developed at a regional level. We used data collected as part of the national contact tracing process in Ireland to estimate the serial interval of SARS-CoV-2 infection in the Irish population, and to estimate the proportion of transmission events that occurred prior to the onset of symptoms.ResultsAfter data cleaning, the final dataset consisted of 471 infected close contacts from 471 primary cases. The median serial interval was 4 days, mean serial interval was 4.0 (95% confidence intervals 3.7, 4.3) days, whilst the 25th and 75th percentiles were 2 and 6 days respectively. We found that intervals were lower when the primary or secondary case were in the older age cohort (greater than 64 years). Simulating from an incubation period distribution from international literature, we estimated that 67% of transmission events had greater than 50% probability of occurring prior to the onset of symptoms in the infector.ConclusionsWhilst our analysis was based on a large sample size, data were collected for the primary purpose of interrupting transmission chains. Similar to other studies estimating the serial interval, our analysis is restricted to transmission pairs where the infector is known with some degree of certainty. Such pairs may represent more intense contacts with infected individuals than might occur in the overall population. It is therefore possible that our analysis is biased towards shorter serial intervals than the overall population.

| S-EPMC8076671 | biostudies-literature

Confidence interval estimation in R-DAS.

Project description:BackgroundRoughly 25 years ago, the United States National Institute on Drug Abuse (US NIDA) initiated the creation of public use datasets for its National Household Survey on Drug Abuse, since re-named the National Survey on Drug Use and Health (NSDUH). The Substance Abuse and Mental Health Services Administration (SAMHSA), which assumed responsibility for the survey in 1992, has continued and expanded this effort to make the survey data available to researchers. During 2012, SAMHSA created a "Restricted-Use Data Analysis System" (R-DAS) to provide researchers with the capability to create tabulations using restricted NSDUH variables not otherwise available on the public-use files.MethodsThis methods focused article is intended to help potential users of R-DAS-like online data analysis systems by (i) clarifying statistical issues involving approximation of confidence intervals (CI), (ii) providing a way to estimate CI when tabular output is suppressed with an 'error message' based on confidentiality restrictions, and (iii) showing how to make pairwise comparisons of estimates not otherwise allowed.ResultsFor illustration purposes, some empirical estimates are presented on a topic of continuing of public health concern in the US namely, extra-medical use of pain relievers (generally opioids), where the drugs are being used to get high and otherwise outside the boundaries intended by prescribing clinicians.ConclusionThe R-DAS makes it possible to derive state-level estimates of male-female and age-related differences in incidence of extra-medical prescription pain reliever (EMPPR) use, not previously reported in peer-reviewed articles, and not available without research approaches described here.

| S-EPMC6003776 | biostudies-literature

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

Project description: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.

| S-EPMC7324649 | biostudies-literature

Confidence boosts serial dependence in orientation estimation.

Project description:In the absence of external feedback, a decision maker must rely on a subjective estimate of their decision accuracy in order to appropriately guide behavior. Normative models of perceptual decision-making relate subjective estimates of internal signal quality (e.g., confidence) directly to the internal signal quality itself, thereby making it unknowable whether the subjective estimate or the underlying signal is what drives behavior. We constructed stimuli that dissociated the human observer's performance on a visual estimation task from their subjective estimates of confidence in their performance, thus violating normative principles. To understand whether confidence influences future decision-making, we examined serial dependence in observer's responses, a phenomenon whereby the estimate of a stimulus on the current trial can be biased toward the stimulus from the previous trial. We found that when decisions were made with high confidence, they conferred stronger biases upon the following trial, suggesting that confidence may enhance serial dependence. Critically, this finding was true also when confidence was experimentally dissociated from task performance, indicating that subjective confidence, independent of signal quality, can amplify serial dependence. These findings demonstrate an effect of confidence on future behavior, independent of task performance, and suggest that perceptual decisions incorporate recent history in an uncertainty-weighted manner, but where the uncertainty carried forward is a subjectively estimated and possibly suboptimal readout of objective sensory uncertainty.

| S-EPMC6690400 | biostudies-literature

Serial Interval of COVID-19 among Publicly Reported Confirmed Cases.

Project description:We estimate the distribution of serial intervals for 468 confirmed cases of coronavirus disease reported in China as of February 8, 2020. The mean interval was 3.96 days (95% CI 3.53-4.39 days), SD 4.75 days (95% CI 4.46-5.07 days); 12.6% of case reports indicated presymptomatic transmission.

| S-EPMC7258488 | biostudies-literature

Serial interval distribution of SARS-CoV-2 infection in Brazil.

Project description: Not available

| S-EPMC7454808 | biostudies-literature