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Title: Estimating the impact of influenza vaccination and antigenic drift on influenza-related morbidity and mortality in England & Wales using hidden Markov models
Author: Mann, Andrea Gail
ISNI:       0000 0004 2702 1725
Awarding Body: London School of Hygiene & Tropical Medicine
Current Institution: London School of Hygiene and Tropical Medicine (University of London)
Date of Award: 2010
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Influenza causes substantial morbidity and mortality in some influenza sea- sons, especially among the elderly. Influenza seasons dominated by circula- tion of influenza A/H3N2 virus tend to result in more morbidity and mor- tality than seasons dominated by influenza A/H1N1 or influenza B viruses. Influenza viruses undergo constant mutation, called antigenic drift, which is largely driven by host immunity. It has been shown that antigenic drift in influenza A/H3N2 virus proceeds in a punctuated, as opposed to contin- uous, fashion. A cluster of antigenically similar influenza A/H3N2 viruses appears to remain dominant for between 1 and 8 influenza seasons before being supplanted by a new cluster. Influenza seasons when a new cluster becomes dominant may result in higher morbidity and mortality than other seasons. Influenza vaccine effectiveness varies between influenza seasons be- cause of the different subtypes in circulation and the degree of antigenic match between vaccine and circulating variants. In each influenza season in recent years, over 70% of the population of England & Wales aged > 65 has been vaccinated, though the impact of this high coverage on population level morbidity and mortality is unknown. Multivariate time series models were fitted to reports of laboratory confirmed influenza, sentinel general practi- tioner (GP) consultations for influenza-like-illness, and all deaths registered to underlying pneumonia or influenza in England & Wales from 1975/76 to 2004/05. The models successfully distinguish influenza - attributable GP consultations and deaths from GP consultations and deaths that would be expected in the absence of influenza. This distinction is made jointly by the laboratory reports and the non-laboratory confirmed surveillance data. It is not possible to use the multivariate time series models to quantify the average effect of the appearance of a new cluster of influenza A/H3N2 virus variants, or vaccine impact, on influenza - attributable morbidity or mortality in the data analyzed. Reasons for this are discus
Supervisor: Whittaker, J. C. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral