ArticlePLoS computational biology2013
Multiple estimates of transmissibility for the 2009 influenza pandemic based on influenza-like-illness data from small US military populations.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Model fit vs. predictive reliability: a case study of the 1978 influenza outbreak.Scientific reports · 2025Article
- Article
- Forecasting the spatial transmission of influenza in the United States.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Forecasting influenza-like illness dynamics for military populations using neural networks and social media.PloS one · 2017Article
- Novel Use of Flu Surveillance Data: Evaluating Potential of Sentinel Populations for Early Detection of Influenza Outbreaks.PloS one · 2016Article
- Prediction of Peaks of Seasonal Influenza in Military Health-Care Data.Biomedical engineering and computational biology · 2016Article
- Early Characterization of the Severity and Transmissibility of Pandemic Influenza Using Clinical Episode Data from Multiple Populations.PLoS computational biology · 2015Article
- Respiratory Infections in the U.S. Military: Recent Experience and Control.Clinical microbiology reviews · 2015Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Rapidly characterizing the amplitude and variability in transmissibility of novel human influenza strains as they emerge is a key public health priority. However, comparison of early estimates of the basic reproduction number during the 2009 pandemic were challenging because of inconsistent data sources and methods. Here, we define and analyze influenza-like-illness (ILI) case data from 2009-2010 for the 50 largest spatially distinct US military installations (military population defined by zip code, MPZ). We used publicly available data from non-military sources to show that patterns of ILI incidence in many of these MPZs closely followed the pattern of their enclosing civilian population. After characterizing the broad patterns of incidence (e.g. single-peak, double-peak), we defined a parsimonious SIR-like model with two possible values for intrinsic transmissibility across three epochs. We fitted the parameters of this model to data from all 50 MPZs, finding them to be reasonably well clustered with a median (mean) value of 1.39 (1.57) and standard deviation of 0.41. An increasing temporal trend in transmissibility ([Formula: see text], p-value: 0.013) during the period of our study was robust to the removal of high transmissibility outliers and to the removal of the smaller 20 MPZs. Our results demonstrate the utility of rapidly available - and consistent - data from multiple populations.
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Registered trials
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