Estimating the effective reproduction number for pandemic influenza from notification data made publicly available in real time: A multi-country analysis for influenza A/H1N1v 2009

Hens, Niel; Ranst, Marc Van; Aerts, Marc; Robesyn, Emmanuel; Damme, Pierre Van; Beutels, Philippe

doi:10.1016/j.vaccine.2010.05.010

Cited by 35 publications

(32 citation statements)

References 19 publications

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“…Overall, the estimates at the community level (town, region or country) varied between 1·1 and 3·1, with a median value of 1·6. In the Netherlands, as in other European countries (except the UK), the reproduction number was smaller than 1 ( R = 0·5) in the period considered 32,37 . The largest estimate ( R = 3·3) was obtained from the analysis of a school outbreak 22 .…”

Section: Resultsmentioning

confidence: 83%

Transmission parameters of the A/H1N1 (2009) influenza virus pandemic: a review

Boëlle

Ansart

Cori

et al. 2011

Influenza Resp Viruses

141

104

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Please cite this paper as: Boëlle P‐Y et al. (2011) Transmission parameters of the A/H1N1 (2009) influenza virus pandemic: a review. Influenza and Other Respiratory Viruses 5(5), 306–316. Background The new influenza virus A/H1N1 (2009), identified in mid‐2009, rapidly spread over the world. Estimating the transmissibility of this new virus was a public health priority. Methods We reviewed all studies presenting estimates of the serial interval or generation time and the reproduction number of the A/H1N1 (2009) virus infection. Results Thirteen studies documented the serial interval from household or close‐contact studies, with overall mean 3 days (95% CI: 2·4, 3·6); taking into account tertiary transmission reduced this estimate to 2·6 days. Model‐based estimates were more variable, from 1·9 to 6 days. Twenty‐four studies reported reproduction numbers for community‐based epidemics at the town or country level. The range was 1·2–3·1, with larger estimates reported at the beginning of the pandemic. Accounting for under‐reporting in the early period of the pandemic and limiting variation because of the choice of the generation time interval, the reproduction number was between 1·2 and 2·3 with median 1·5. Discussion The serial interval of A/H1N1 (2009) flu was typically short, with mean value similar to the seasonal flu. The estimates of the reproduction number were more variable. Compared with past influenza pandemics, the median reproduction number was similar (1968) or slightly smaller (1889, 1918, 1957).

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Section: Resultsmentioning

confidence: 83%

Transmission parameters of the A/H1N1 (2009) influenza virus pandemic: a review

Boëlle

Ansart

Cori

et al. 2011

Influenza Resp Viruses

141

104

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“…By applying the proposed uncertainty bound of final size to influenza (H1N1-2009), we have also shown that all the seroepidemiological studies published to date did not necessarily indicate an overestimation of prediction based on R = 1.40, and moreover, all the observed final sizes did not reveal significant deviation from prediction with the lower limit R = 1.15. Published seroepidemiological studies agree that the upper bound R = 1.90 (and thus, other published estimates of R >2 [29], [30]) was likely an overestimation [39]. One may still speculate that R = 1.40 may well be an overestimation (because all of the observed final sizes were smaller than 51.1%), but the sample sizes of published seroepidemiological studies turned out to be too small to answer this question.…”

Section: Discussionmentioning

confidence: 92%

“…Following the earliest studies in Mexico [8], [28], the estimation of R was conducted using the early epidemic growth data in different locations across the world (yielding published estimates in 2009 [29]–[38], some reassessed [39]). The estimated R , in different epidemic settings and subpopulations, ranged from “less than 1” [40] to greater than 2 [28], [29], [35].…”

Section: Methodsmentioning

confidence: 99%

Did Modeling Overestimate the Transmission Potential of Pandemic (H1N1-2009)? Sample Size Estimation for Post-Epidemic Seroepidemiological Studies

2011

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BackgroundSeroepidemiological studies before and after the epidemic wave of H1N1-2009 are useful for estimating population attack rates with a potential to validate early estimates of the reproduction number, R, in modeling studies.Methodology/Principal FindingsSince the final epidemic size, the proportion of individuals in a population who become infected during an epidemic, is not the result of a binomial sampling process because infection events are not independent of each other, we propose the use of an asymptotic distribution of the final size to compute approximate 95% confidence intervals of the observed final size. This allows the comparison of the observed final sizes against predictions based on the modeling study (R = 1.15, 1.40 and 1.90), which also yields simple formulae for determining sample sizes for future seroepidemiological studies. We examine a total of eleven published seroepidemiological studies of H1N1-2009 that took place after observing the peak incidence in a number of countries. Observed seropositive proportions in six studies appear to be smaller than that predicted from R = 1.40; four of the six studies sampled serum less than one month after the reported peak incidence. The comparison of the observed final sizes against R = 1.15 and 1.90 reveals that all eleven studies appear not to be significantly deviating from the prediction with R = 1.15, but final sizes in nine studies indicate overestimation if the value R = 1.90 is used.ConclusionsSample sizes of published seroepidemiological studies were too small to assess the validity of model predictions except when R = 1.90 was used. We recommend the use of the proposed approach in determining the sample size of post-epidemic seroepidemiological studies, calculating the 95% confidence interval of observed final size, and conducting relevant hypothesis testing instead of the use of methods that rely on a binomial proportion.

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“…Later, Hens et al . used a hybrid version of these two methods. Their method was based on the epidemic renewal process while accounting for underreporting in a likelihood framework.…”

Section: Introductionmentioning

confidence: 99%

“…This term refers to the delay between the time of interest, for example, the true infection time or the symptom onset time, and the reported time. Delay in reporting can be the result of a long diagnosis process, limited capacity for admissions in hospitals , or working hours . For instance, it is not unlikely that, because of a restriction of working hours, no data are reported during weekends and consequently an unusually large number of cases are reported at the beginning of the week.…”

Section: Introductionmentioning

confidence: 99%

On the estimation of the reproduction number based on misreported epidemic data

Azmon

Faes

Hens

2013

Statistics in Medicine

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Epidemic data often suffer from underreporting and delay in reporting. In this paper, we investigated the impact of delays and underreporting on estimates of reproduction number. We used a thinned version of the epidemic renewal equation to describe the epidemic process while accounting for the underlying reporting system. Assuming a constant reporting parameter, we used different delay patterns to represent the delay structure in our model. Instead of assuming a fixed delay distribution, we estimated the delay parameters while assuming a smooth function for the reproduction number over time. In order to estimate the parameters, we used a Bayesian semiparametric approach with penalized splines, allowing both flexibility and exact inference provided by MCMC. To show the performance of our method, we performed different simulation studies. We conducted sensitivity analyses to investigate the impact of misspecification of the delay pattern and the impact of assuming nonconstant reporting parameters on the estimates of the reproduction numbers. We showed that, whenever available, additional information about time-dependent underreporting can be taken into account. As an application of our method, we analyzed confirmed daily A(H1N1) v2009 cases made publicly available by the World Health Organization for Mexico and the USA.

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Estimating the effective reproduction number for pandemic influenza from notification data made publicly available in real time: A multi-country analysis for influenza A/H1N1v 2009

Cited by 35 publications

References 19 publications

Transmission parameters of the A/H1N1 (2009) influenza virus pandemic: a review

Transmission parameters of the A/H1N1 (2009) influenza virus pandemic: a review

Did Modeling Overestimate the Transmission Potential of Pandemic (H1N1-2009)? Sample Size Estimation for Post-Epidemic Seroepidemiological Studies

On the estimation of the reproduction number based on misreported epidemic data

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