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Estimating Risks to the Public Health

  • Rose Baker
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 70)

Abstract

Risks to public health arise from infectious disease, exposure to toxic substances such as asbestos, environmental insults, and from lifestyle risks such as smoking. The risk assessment that must precede healthcare interventions or legislation requires probabilistic, statistical and computational methodologies. The introduction to this chapter discusses how our perception of the risks to public health is changing, and identifies some trends in the methodologies used for risk analysis. Risk assessment is largely characterised by likelihood-based statistical inference, using point-process models of disease intensity as a function of position in space and time. Conditional likelihoods such as Cox’s partial likelihood and matched-pairs logistic regression are widely used to eliminate confounding variables. Two examples of the use of such conditional likelihoods are given. In the first, new tests for the space-time clustering of cases characteristic of infectious disease are derived and exemplified. In a second application of conditional likelihood, some research on risks of Shigella infection to schoolchildren arising at school or from playmates is presented. The original content of this chapter is two new tests of space-time clustering, and a case-study using an unusual conditional likelihood.

Key words

Epidemiology Risk Likelihood Knox test Shigella 

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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • Rose Baker
    • 1
  1. 1.Centre for Operational Research and Applied StatisticsUniversity of Salford SalfordUK

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