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. 2017 Nov 20;13(11):e1005838.
doi: 10.1371/journal.pcbi.1005838. eCollection 2017 Nov.

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

Edwin van Leeuwen  1   2 , Petra Klepac  1   3 , Dominic Thorrington  1 , Richard Pebody  1 , Marc Baguelin  1   4
Affiliations

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

Edwin van Leeuwen et al. PLoS Comput Biol. .

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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Workflow for the fluEvidenceSynthesis package.
Fig 2
Fig 2. Posterior and prior probability of R0 for different seasons and serotype H3N2.
Fig 3
Fig 3. Reduction in influenza incidence under increased vaccination of the age group between 5 and 15.
The orange colour signifies the reduction in patients classified as high risk. The blue colour is the reduction in the low risk population. The first results correspond to a scenario where 40 percent coverage is achieved, the second to a coverage of 80.
Fig 4
Fig 4. Cost effectiveness analysis showing the vaccine cost by reduction in mortality under two vaccination scenarios, taking into account uncertainty in vaccine cost, influenza incidence and death risk.
The colours represent the uncertainty around the different scenarios. The lines represent two potential thresholds: (1) for a cost of up to 1000 for each life saved both programmes are not cost effective, (2) for a cost up to 10,000 per life saved both programmes are likely to be cost effective. The parameter values used in this figure (cost of vaccine: 17 ± 2.5 and mortality risk: 0.0025 ± 0.0005) were chosen for illustrative purposes only and should not be taken as realistic values.
See this image and copyright information in PMC

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