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Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series

Heterogeneity in individual-level transmissibility can be quantified by the dispersion parameter [Formula: see text] of the offspring distribution. Quantifying heterogeneity is important as it affects other parameter estimates, it modulates the degree of unpredictability of an epidemic, and it needs...

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Autores principales: Li, Lucy M., Grassly, Nicholas C., Fraser, Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850343/
https://www.ncbi.nlm.nih.gov/pubmed/28981709
http://dx.doi.org/10.1093/molbev/msx195
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author Li, Lucy M.
Grassly, Nicholas C.
Fraser, Christophe
author_facet Li, Lucy M.
Grassly, Nicholas C.
Fraser, Christophe
author_sort Li, Lucy M.
collection PubMed
description Heterogeneity in individual-level transmissibility can be quantified by the dispersion parameter [Formula: see text] of the offspring distribution. Quantifying heterogeneity is important as it affects other parameter estimates, it modulates the degree of unpredictability of an epidemic, and it needs to be accounted for in models of infection control. Aggregated data such as incidence time series are often not sufficiently informative to estimate [Formula: see text]. Incorporating phylogenetic analysis can help to estimate [Formula: see text] concurrently with other epidemiological parameters. We have developed an inference framework that uses particle Markov Chain Monte Carlo to estimate [Formula: see text] and other epidemiological parameters using both incidence time series and the pathogen phylogeny. Using the framework to fit a modified compartmental transmission model that includes the parameter [Formula: see text] to simulated data, we found that more accurate and less biased estimates of the reproductive number were obtained by combining epidemiological and phylogenetic analyses. However, [Formula: see text] was most accurately estimated using pathogen phylogeny alone. Accurately estimating [Formula: see text] was necessary for unbiased estimates of the reproductive number, but it did not affect the accuracy of reporting probability and epidemic start date estimates. We further demonstrated that inference was possible in the presence of phylogenetic uncertainty by sampling from the posterior distribution of phylogenies. Finally, we used the inference framework to estimate transmission parameters from epidemiological and genetic data collected during a poliovirus outbreak. Despite the large degree of phylogenetic uncertainty, we demonstrated that incorporating phylogenetic data in parameter inference improved the accuracy and precision of estimates.
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spelling pubmed-58503432018-03-23 Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series Li, Lucy M. Grassly, Nicholas C. Fraser, Christophe Mol Biol Evol Methods Heterogeneity in individual-level transmissibility can be quantified by the dispersion parameter [Formula: see text] of the offspring distribution. Quantifying heterogeneity is important as it affects other parameter estimates, it modulates the degree of unpredictability of an epidemic, and it needs to be accounted for in models of infection control. Aggregated data such as incidence time series are often not sufficiently informative to estimate [Formula: see text]. Incorporating phylogenetic analysis can help to estimate [Formula: see text] concurrently with other epidemiological parameters. We have developed an inference framework that uses particle Markov Chain Monte Carlo to estimate [Formula: see text] and other epidemiological parameters using both incidence time series and the pathogen phylogeny. Using the framework to fit a modified compartmental transmission model that includes the parameter [Formula: see text] to simulated data, we found that more accurate and less biased estimates of the reproductive number were obtained by combining epidemiological and phylogenetic analyses. However, [Formula: see text] was most accurately estimated using pathogen phylogeny alone. Accurately estimating [Formula: see text] was necessary for unbiased estimates of the reproductive number, but it did not affect the accuracy of reporting probability and epidemic start date estimates. We further demonstrated that inference was possible in the presence of phylogenetic uncertainty by sampling from the posterior distribution of phylogenies. Finally, we used the inference framework to estimate transmission parameters from epidemiological and genetic data collected during a poliovirus outbreak. Despite the large degree of phylogenetic uncertainty, we demonstrated that incorporating phylogenetic data in parameter inference improved the accuracy and precision of estimates. Oxford University Press 2017-11 2017-07-11 /pmc/articles/PMC5850343/ /pubmed/28981709 http://dx.doi.org/10.1093/molbev/msx195 Text en © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods
Li, Lucy M.
Grassly, Nicholas C.
Fraser, Christophe
Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series
title Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series
title_full Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series
title_fullStr Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series
title_full_unstemmed Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series
title_short Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series
title_sort quantifying transmission heterogeneity using both pathogen phylogenies and incidence time series
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850343/
https://www.ncbi.nlm.nih.gov/pubmed/28981709
http://dx.doi.org/10.1093/molbev/msx195
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