Modelling the effects of immunity on influenza transmission - implications for prevention and vaccine development

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There is uncertainty about how many people can be infected by a single person with influenza at the start of an outbreak. Some data suggest that a single generation of transmission can infect 10-20 other people. With such a rate of growth (ie 10-20 fold every 3 days) the spread of an influenza outbreak is virtually unstoppable. Other data suggest that each person with influenza infects less than 2 other people on average. With such a lower rate of growth, control would be more feasible. Our project will use data from historic and contemporary outbreaks of influenza and build mathematical models to explain the rate of growth of an influenza outbreak in terms of: 1. The proportion of people exposed to influenza who do not become ill (although there can be evidence of infection if careful studies are made). This proportion is about 33%. 2. The proportion of people who are protected from influenza by immunity, whether induced by vaccination or by past exposure to natural influenza infection (this can vary from 0% in isolated populations which have not seen influenza for many years up to 80 or 90% in urbanised populations that are exposed to influenza almost every season). 3. Different rates of contact between different people and groups of people - some may be exposed so often that their immunity is boosted regularly without them becoming severely ill; others, living in more isolated circumstances, may be rarely exposed, but when they are, they are more likely to become severely ill. 4. The effects of influenza vaccine in inducing protective immunity - it is well known that there is good protection if the vaccine is well matched to the circulating virus. 5. The effects of live virus infection in inducing (short-lived) protection against a wider range of influenza viruses. Our model results will be used to guide vaccine design and pandemic planning.