Inference for infectious diseases from multivariate serological survey data

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The aim of this project is to develop new methods that will aid our understanding of how infectious diseases spread in a population, and hence improve our ability to control those diseases by vaccination. The methods to be developed will be used with serological data, that is, data obtained from blood tests. These tests determine whether a person has, or has not, been infected by one or more infections. Large studies based on such data are commonly used to plan vaccination programmes, and to monitor how successful existing vaccination programmes are at maintaining levels of immunity sufficient to prevent the occurrence of large epidemics. However, most of the methods that are currently employed to analyse serological data are used to look at each infection in isolation. The project is to develop new methods to analyse serological data on several infections at the same time. The reason why this might be fruitful is that the occurrences of different infections within the same individuals are likely to be correlated. For example, children who go to nurseries are more likely to get infected by all childhood infections that are transmitted by close contacts. The idea behind the project is to use the correlations between different infections (which can be measured using serological data) to tell us about contact patterns, how they vary between individuals, and how they vary with age. The way we propose to do this is by developing new statistical models for this type of data, based on relevant hypotheses about what might be causing the correlations to arise. The results from these models can then be used to improve our understanding of the spread of infections, for example by providing better estimates of the proportion of children that need to be vaccinated to prevent large epidemics, or by helping to identify how infections are transmitted if this is not known. The project involves a collaboration between the two applicants, who have long experience of statistical modelling of infectious diseases, and the Head of the Health Protection Agency?s Seroepidemiology Programme. So far, much data on different infections have been collected, and initial analyses have been undertaken to verify that the project?s rationale is well-founded. In this application, we seek funding for a researcher to work on the project full-time for three years under the supervision of the applicants.