Modelling infectious disease transmission with complex exposure pattern and sparse outcome data Academic Article uri icon

abstract

  • We present a regression modelling framework to analyse infectious disease transmission during a time period where extensive exposure data are available, but where the outcome data are sparse. A latent variable model is used for each exposure time, allowing a straight-forward accumulation of risk for a collection of exposures for which outcome data are available. We describe an analysis of HIV infection from blood products among a cohort of haemophiliacs in Ireland between 1980 and 1985. The analysis provides estimates of the time pattern and batch effects; we show how analytical complexity such as smoothly varying coefficients or random coefficient models can be accommodated by the model. Finally, we discuss other problems where the model is applicable.

authors

  • Reilly, Marie
  • Salim, Agus
  • Lawlor, Emer
  • Smith, Owen
  • Temperley, Ian
  • Pawitan, Yudi

publication date

  • October 15, 2004