UNSPECIFIED (2005) Modelling antigenic drift in weekly flu incidence. STATISTICS IN MEDICINE, 24 (22). pp. 3447-3461. doi:10.1002/sim.2196

Full text not available from this repository, contact author.

Request Changes to record.

Abstract

Since influenza in humans is a major public health threat, the understanding of its dynamics and evolution, and improved prediction of its epidemics are important aims. Underlying its multi-strain structure is the evolutionary process of antigenic drift whereby epitope mutations give mutant virions a selective advantage. While there is substantial understanding of the molecular mechanisms of antigenic drift, until now there has been no quantitative analysis of this process at the population level. The aim of this study is to develop a predictive model that is of a modest-enough structure to be fitted to time series data on weekly flu incidence. We observe that the rate of antigenic drift is highly non-uniform and identify several years where there have been antigenic surges where a new strain substantially increases infective pressure. The SIR-S approach adopted here can also be shown to improve forecasting in comparison to conventional methods. Copyright (C) 2005 John Wiley & Sons, Ltd.

Item Type:	Journal Article
Subjects:	Q Science > QH Natural history > QH301 Biology R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine R Medicine Q Science > QA Mathematics
Journal or Publication Title:	STATISTICS IN MEDICINE
Publisher:	JOHN WILEY & SONS LTD
ISSN:	0277-6715
Official Date:	30 November 2005
Dates:	Date Event 30 November 2005 UNSPECIFIED
Volume:	24
Number:	22
Number of Pages:	15
Page Range:	pp. 3447-3461
DOI:	10.1002/sim.2196
Publication Status:	Published

Data sourced from Thomson Reuters' Web of Knowledge

Request changes or add full text files to a record

Repository staff actions (login required)

View Item