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Spatio-temporal modelling of disease incidence with missing covariate values

  • R. C. HOLLAND (a1), G. JONES (a1) and J. BENSCHOP (a2)
Summary

The search for an association between disease incidence and possible risk factors using surveillance data needs to account for possible spatial and temporal correlations in underlying risk. This can be especially difficult if there are missing values for some important covariates. We present a case study to show how this problem can be overcome in a Bayesian analysis framework by adding to the usual spatio-temporal model a component for modelling the missing data.

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Copyright
Corresponding author
* Author for correspondence: Dr J. Benschop, mEpiLab, Hopkirk Research Institute, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Private Bag 11222, Palmerston North, New Zealand. (Email: j.benschop@massey.ac.nz)
References
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Epidemiology & Infection
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  • EISSN: 1469-4409
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