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Modelling non-linear patterns of time-varying intervention effects on recurrent events in infectious disease prevention studies.

Xiangmei MaXiangmei MaKwok Fai LamChee Fu YungPaul Milligan
Published in: Journal of biopharmaceutical statistics (2022)
Protective efficacy of vaccines and pharmaceutical products for prevention of infectious diseases usually vary over time. Information on the trajectory of the level of protection is valuable. We consider a parsimonious, non-linear and non-monotonic function for modelling time-varying intervention effects and compare it with several alternatives. The cumulative effects of multiple doses of intervention over time can be captured by an additive series of the function. We apply it to the Andersen-Gill model for analysis of recurrent time-to-event data. We re-analyze data from a trial of intermittent preventive treatment for malaria to illustrate and evaluate the method by simulation.
Keyphrases
  • infectious diseases
  • randomized controlled trial
  • electronic health record
  • study protocol
  • clinical trial
  • big data
  • machine learning
  • high intensity
  • data analysis
  • phase ii
  • open label