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Predicting the nature and extent of herd effects from vaccination

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  • Full or part time
    Dr H Christensen
    Prof A Finn
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

About This PhD Project

Project Description

Previously the benefit of vaccination was thought to be to the recipient only though direct protection, but increasingly the importance of herd effects – where vaccination prevents transmission of a pathogen – are being recognised. The benefits from herd effects can be far greater than through direct protection alone. At present geographical variation in vaccination uptake is rarely considered when predicting herd impact, though if there are pockets of unimmunised individuals this could have important implications for potential outbreaks and likely numbers of cases. Additionally, there is growing evidence that there is variation in the extent to which individuals may be colonised with microbes, with some healthy individuals having high numbers of potentially disease causing bacteria in their throat and nasopharynx while others having low numbers. If vaccination could reduce colonisation density, this could lead to important herd effects which are not currently being considered.

Aims & Objectives
Aim: Predict the nature and extent of herd effects from vaccination under different circumstances
- Review and analyse evidence on the variation in the density of colonisation of individuals by age/risk group and the geographical variation in UK vaccination uptake
- Develop and apply mathematical models an infection and vaccination against it (e.g. meningococcus, pneumococcus, pertussis) to predict the nature and extent of herd effects from vaccination under different circumstances

A number of studies have been published and are ongoing which assess the bacterial and viral load of potentially pathogenic microbes in the throat and nasopharynx. A literature review will be undertaken to establish the variation in density of microbes by age and for different risk groups and the possible reasons for this. Vaccination uptake rates by geographical area will be obtained and reviewed from routine data sources. Taking one or two model pathogens forward mathematical models will be developed of the infection including disease, and different vaccination strategies to control it. These will be extended to incorporate different degrees of geographical variation of vaccine uptake and colonisation in different individuals. The impact of vaccination, in terms of cases of disease averted, will be explored through application of these models under different scenarios and the sensitivity of the models to changes will be investigated.

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