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fluEvidenceSynthesis: An R package for evidence synthesis based analysis of epidemiological outbreaks

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  • Edwin van Leeuwen
  • Petra Klepac
  • Dominic Thorrington
  • Richard Pebody
  • Marc Baguelin

Abstract

Public health related decisions often have to balance the cost of intervention strategies with the benefit of the reduction in disease burden. While the cost can often be inferred, forward modelling of the effect of different intervention options is complicated and disease specific. Here we introduce a package that is aimed to simplify this process. The package allows one to infer parameters using a Bayesian approach, perform forward modelling of the likely results of the proposed intervention and finally perform cost effectiveness analysis of the results. The package is based on a method previously used in the United Kingdom to inform vaccination strategies for influenza, with extensions to make it easily adaptable to other diseases and data sources.

Suggested Citation

  • Edwin van Leeuwen & Petra Klepac & Dominic Thorrington & Richard Pebody & Marc Baguelin, 2017. "fluEvidenceSynthesis: An R package for evidence synthesis based analysis of epidemiological outbreaks," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-12, November.
    • Handle: RePEc:plo:pcbi00:1005838
    DOI: 10.1371/journal.pcbi.1005838
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    References listed on IDEAS

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    1. Merl, Daniel & Johnson, Leah R. & Gramacy, Robert B. & Mangel, Marc, 2010. "amei: An R Package for the Adaptive Management of Epidemiological Interventions," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i06).
    2. Dureau, Joseph & Kalogeropoulos, Konstantinos & Baguelin, Marc, 2013. "Capturing the time-varying drivers of an epidemic using stochastic dynamical systems," LSE Research Online Documents on Economics 41749, London School of Economics and Political Science, LSE Library.
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