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Real-time epidemic forecasting for pandemic influenza

Published online by Cambridge University Press:  24 August 2006

I. M. HALL ,
R. GANI ,
H. E. HUGHES  and
S. LEACH
I. M. HALL
Affiliation:
Microbial Risk Assessment, Health Protection Agency, Centre for Emergency Preparedness and Response, Porton Down, Wiltshire, UK
R. GANI
Affiliation:
Microbial Risk Assessment, Health Protection Agency, Centre for Emergency Preparedness and Response, Porton Down, Wiltshire, UK
H. E. HUGHES
Affiliation:
Communicable Disease Surveillance Centre (Northern Ireland), Belfast, UK
S. LEACH
Affiliation:
Microbial Risk Assessment, Health Protection Agency, Centre for Emergency Preparedness and Response, Porton Down, Wiltshire, UK
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Abstract

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The ongoing worldwide spread of the H5N1 influenza virus in birds has increased concerns of a new human influenza pandemic and a number of surveillance initiatives are planned, or are in place, to monitor the impact of a pandemic in near real-time. Using epidemiological data collected during the early stages of an outbreak, we show how the timing of the maximum prevalence of the pandemic wave, along with its amplitude and duration, might be predicted by fitting a mass-action epidemic model to the surveillance data by standard regression analysis. This method is validated by applying the model to routine data collected in the United Kingdom during the different waves of the previous three pandemics. The success of the method in forecasting historical prevalence suggests that such outbreaks conform reasonably well to the theoretical model, a factor which may be exploited in a future pandemic to update ongoing planning and response.

Type
Research Article
Information
Epidemiology & Infection , Volume 135 , Issue 3 , April 2007 , pp. 372 - 385
Copyright
2006 Cambridge University Press

Footnotes

The views and opinions expressed in this paper are those of the authors and do not necessarily reflect those of the UK Department of Health, DG SANCO or the Health Protection Agency.