Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London.
The tracking and projection of emerging epidemics is hindered by the disconnect between apparent epidemic dynamics, discernible from noisy and incomplete surveillance data, and the underlying, imperfectly observed, system. Behavior changes compound this, altering both true dynamics and reporting pat...
Main Authors: | Birrell, P, Ketsetzis, G, Gay, N, Cooper, B, Presanis, A, Harris, R, Charlett, A, Zhang, X, White, P, Pebody, R, De Angelis, D |
---|---|
Format: | Journal article |
Language: | English |
Published: |
2011
|
Similar Items
-
The early transmission dynamics of H1N1pdm influenza in the United Kingdom
by: Ghani, A, et al.
Published: (2010) -
The severity of pandemic H1N1 influenza in the United States, from April to July 2009: A Bayesian Analysis
by: Presanis, A, et al.
Published: (2009) -
Estimating age-stratified influenza-associated invasive pneumococcal disease in England: a time-series model based on population surveillance data
by: Chiavenna, C, et al.
Published: (2019) -
The survival of influenza A(H1N1)pdm09 virus on 4 household surfaces.
by: Oxford, J, et al.
Published: (2014) -
The severity of pandemic H1N1 influenza in the United States, April - July 2009
by: Presanis, A, et al.
Published: (2009)