Abstract

Phylogenetic trees can be used to infer the processes that generated them. Here, we introduce a model, the Bayesian birth–death skyline plot, which explicitly estimates the rate of transmission, recovery, and sampling and thus allows inference of the effective reproductive number directly from genetic data. Our method allows these parameters to vary through time in a piecewise fashion and is implemented within the B EAST 2 software framework. The method is a powerful alternative to the existing coalescent skyline plot, providing insight into the differing roles of incidence and prevalence in an epidemic. We apply this method to data from the United Kingdom HIV-1 epidemic and Egyptian hepatitis C virus (HCV) epidemic. The analysis reveals temporal changes of the effective reproductive number that highlight the effect of past public health interventions.

Keywords

SkylineCoalescent theoryPlot (graphics)Hepatitis C virusBasic reproduction numberVirologyHuman immunodeficiency virus (HIV)InferenceBiologyComputer scienceDemographyGeographyPhylogenetic treeStatisticsData miningMedicineGeneticsArtificial intelligenceMathematicsVirusEnvironmental healthPopulation

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Publication Info

Year
2012
Type
article
Volume
110
Issue
1
Pages
228-233
Citations
618
Access
Closed

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Tanja Stadler, Denise Kühnert, Sebastian Bonhoeffer et al. (2012). Birth–death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV). Proceedings of the National Academy of Sciences , 110 (1) , 228-233. https://doi.org/10.1073/pnas.1207965110

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DOI
10.1073/pnas.1207965110