A model to estimate the impact of changes in MMR vaccine uptake on inequalities in measles susceptibility in Scotland

Napier, G. , Lee, D. , Robertson, C., Lawson, A. and Pollock, K. G. (2016) A model to estimate the impact of changes in MMR vaccine uptake on inequalities in measles susceptibility in Scotland. Statistical Methods in Medical Research, 25(4), pp. 1185-1200. (doi: 10.1177/0962280216660420) (PMID:27566772)

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An article published in 1998 by Andrew Wakefield in The Lancet (volume 351, pages 637–641) led to concerns surrounding the safety of the measles, mumps and rubella vaccine, by associating it with an increased risk of autism. The paper was later retracted after multiple epidemiological studies failed to find any association, but a substantial decrease in UK vaccination rates was observed in the years following publication. This paper proposes a novel spatio-temporal Bayesian hierarchical model with accompanying software (the R package CARBayesST) to simultaneously address three key epidemiological questions about vaccination rates: (i) what impact did the controversy have on the overall temporal trend in vaccination rates in Scotland; (ii) did the magnitude of the spatial inequality in measles susceptibility in Scotland increase due to the measles, mumps and rubella vaccination scare; and (iii) are there any covariate effects, such as deprivation, that impacted on measles susceptibility in Scotland. The efficacy of the model is tested by simulation, before being applied to measles susceptibility data in Scotland among a series of cohorts of children who were aged 2.5–4.5, in September of the years 1998 to 2014.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Lee, Professor Duncan and Napier, Dr Gary
Authors: Napier, G., Lee, D., Robertson, C., Lawson, A., and Pollock, K. G.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Statistical Methods in Medical Research
ISSN (Online):1477-0334
Published Online:26 August 2016

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
647701A flexible class of Bayesian spatio-temporal models for cluster detection, trend estimation and forecasting of disease risk.Duncan LeeMedical Research Council (MRC)MR/L022184/1M&S - STATISTICS