Title |
Estimation of outbreak severity and transmissibility: Influenza A(H1N1)pdm09 in households
|
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Published in |
BMC Medicine, October 2012
|
DOI | 10.1186/1741-7015-10-117 |
Pubmed ID | |
Authors |
Thomas House, Nadia Inglis, Joshua V Ross, Fay Wilson, Shakeel Suleman, Obaghe Edeghere, Gillian Smith, Babatunde Olowokure, Matt J Keeling |
Abstract |
When an outbreak of a novel pathogen occurs, some of the most pressing questions from a public-health point of view relate to its transmissibility, and the probabilities of different clinical outcomes following infection, to allow an informed response. Estimates of these quantities are often based on household data due to the high potential for transmission in this setting, but typically a rich spectrum of individual-level outcomes (from uninfected to serious illness) are simplified to binary data (infected or not). We address the added benefit from retaining the heterogeneous outcome information in the case of the 2009-10 influenza pandemic, which posed particular problems for estimation of key epidemiological characteristics due to its relatively mild nature and hence low case ascertainment rates. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 5 | 36% |
United States | 2 | 14% |
Australia | 1 | 7% |
Unknown | 6 | 43% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 43% |
Scientists | 3 | 21% |
Science communicators (journalists, bloggers, editors) | 3 | 21% |
Practitioners (doctors, other healthcare professionals) | 2 | 14% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 2% |
Kenya | 1 | 2% |
Australia | 1 | 2% |
United Kingdom | 1 | 2% |
Japan | 1 | 2% |
United States | 1 | 2% |
Unknown | 54 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 15 | 25% |
Researcher | 14 | 23% |
Student > Master | 7 | 12% |
Other | 6 | 10% |
Professor > Associate Professor | 4 | 7% |
Other | 8 | 13% |
Unknown | 6 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 15 | 25% |
Mathematics | 11 | 18% |
Agricultural and Biological Sciences | 10 | 17% |
Social Sciences | 3 | 5% |
Immunology and Microbiology | 2 | 3% |
Other | 11 | 18% |
Unknown | 8 | 13% |