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Inferring epidemiological dynamics of infectious diseases using Tajima's D statistic on nucleotide sequences of pathogens

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Title: Inferring epidemiological dynamics of infectious diseases using Tajima's D statistic on nucleotide sequences of pathogens
Authors: Kim, Kiyeon Browse this author
Omori, Ryosuke Browse this author →KAKEN DB
Ito, Kimihito Browse this author →KAKEN DB
Keywords: Influenza A virus
Tajima's D
Basic reproduction number
Model based inference
Transmission dynamics
Issue Date: Dec-2017
Publisher: Elsevier
Journal Title: Epidemics
Volume: 21
Start Page: 21
End Page: 29
Publisher DOI: 10.1016/j.epidem.2017.04.004
PMID: 28552262
Abstract: The estimation of the basic reproduction number is essential to understand epidemic dynamics, and time series data of infected individuals are usually used for the estimation. However, such data are not always available. Methods to estimate the basic reproduction number using genealogy constructed from nucleotide sequences of pathogens have been proposed so far. Here, we propose a new method to estimate epidemiological parameters of outbreaks using the time series change of Tajima's D statistic on the nucleotide sequences of pathogens. To relate the time evolution of Tajima's D to the number of infected individuals, we constructed a parsimonious mathematical model describing both the transmission process of pathogens among hosts and the evolutionary process of the pathogens. As a case study we applied this method to the field data of nucleotide sequences of pandemic influenza A (H1N1) 2009 viruses collected in Argentina. The Tajima's D-based method estimated basic reproduction number to be 1.55 with 95% highest posterior density (HPD) between 1.31 and 2.05, and the date of epidemic peak to be 10th July with 95% HPD between 22nd June and 9th August. The estimated basic reproduction number was consistent with estimation by birth-death skyline plot and estimation using the time series of the number of infected individuals. These results suggested that Tajima's D statistic on nucleotide sequences of pathogens could be useful to estimate epidemiological parameters of outbreaks.
Rights: https://creativecommons.org/licenses/by/4.0/
Type: article
URI: http://hdl.handle.net/2115/76486
Appears in Collections:人獣共通感染症リサーチセンター (Research Center for Zoonosis Control) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
国際連携研究教育局 : GI-CoRE (Global Institution for Collaborative Research and Education : GI-CoRE) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

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