ArticleTheoretical biology & medical modelling2007
Time variations in the transmissibility of pandemic influenza in Prussia, Germany, from 1918-19.
Article in Theoretical biology & medical modelling, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.
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Who cites it
39 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Estimates of the reproduction number for seasonal, pandemic, and zoonotic influenza: a systematic review of the literature.BMC infectious diseases · 2014Pooled it
- The serial intervals of seasonal and pandemic influenza viruses in households in Bangkok, Thailand.American journal of epidemiology · 2013Trial
- Estimating the effective reproduction number of COVID-19 from population-wide wastewater data: An application in Kagawa, Japan.Infectious Disease Modelling · 2024Article
- Approximation of the infection-age-structured SIR model by the conventional SIR model of infectious disease epidemiology.Frontiers in epidemiology · 2024Article
- Time warping between main epidemic time series in epidemiological surveillance.PLoS computational biology · 2023Article
- SARS-CoV-2 Serology Across Scales: A Framework for Unbiased Estimation of Cumulative Incidence Incorporating Antibody Kinetics and Epidemic Recency.American journal of epidemiology · 2023Article
- Learning from the past: A short term forecast method for the COVID-19 incidence curve.PLoS computational biology · 2023Article
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- Modeling COVID-19 Incidence by the Renewal Equation after Removal of Administrative Bias and Noise.Biology · 2022Article
- Computing the daily reproduction number of COVID-19 by inverting the renewal equation using a variational technique.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Modelling the SARS-CoV-2 outbreak: Assessing the usefulness of protective measures to reduce the pandemic at population level.The Science of the total environment · 2021Article
- SARS-CoV-2 serology across scales: a framework for unbiased seroprevalence estimation incorporating antibody kinetics and epidemic recency.medRxiv : the preprint server for health sciences · 2021Article
- Optimizing Spatial Allocation of COVID-19 Vaccine by Agent-Based Spatiotemporal Simulations.GeoHealth · 2021Article
- Statistical Estimation of the Reproductive Number From Case Notification Data.American journal of epidemiology · 2021Review
- Comparison of methods to Estimate Basic Reproduction Number (Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2019Article
- Impact of Public Health Responses During a Measles Outbreak in an Amish Community in Ohio: Modeling the Dynamics of Transmission.American journal of epidemiology · 2018Article
- A Bayesian inferential approach to quantify the transmission intensity of disease outbreak.Computational and mathematical methods in medicine · 2015Article
- Transmission dynamics and control of Ebola virus disease (EVD): a review.BMC medicine · 2014Review
- The R0 package: a toolbox to estimate reproduction numbers for epidemic outbreaks.BMC medical informatics and decision making · 2012Article
- Modeling rapidly disseminating infectious disease during mass gatherings.BMC medicine · 2012Review
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1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTime variations in transmission potential have rarely been examined with regard to pandemic influenza. This paper reanalyzes the temporal distribution of pandemic influenza in Prussia, Germany, from 1918-19 using the daily numbers of deaths, which totaled 8911 from 29 September 1918 to 1 February 1919, and the distribution of the time delay from onset to death in order to estimate the effective reproduction number, Rt, defined as the actual average number of secondary cases per primary case at a given time.
resultsA discrete-time branching process was applied to back-calculated incidence data, assuming three different serial intervals (i.e. 1, 3 and 5 days). The estimated reproduction numbers exhibited a clear association between the estimates and choice of serial interval; i.e. the longer the assumed serial interval, the higher the reproduction number. Moreover, the estimated reproduction numbers did not decline monotonically with time, indicating that the patterns of secondary transmission varied with time. These tendencies are consistent with the differences in estimates of the reproduction number of pandemic influenza in recent studies; high estimates probably originate from a long serial interval and a model assumption about transmission rate that takes no account of time variation and is applied to the entire epidemic curve.
conclusionThe present findings suggest that in order to offer robust assessments it is critically important to clarify in detail the natural history of a disease (e.g. including the serial interval) as well as heterogeneous patterns of transmission. In addition, given that human contact behavior probably influences transmissibility, individual countermeasures (e.g. household quarantine and mask-wearing) need to be explored to construct effective non-pharmaceutical interventions.
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