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Quantifying transmission dynamics of acute hepatitis C virus infections in a heterogeneous population using sequence datause asterix (*) to get italics
Gonche Danesh, Victor Virlogeux, Christophe Ramière, Caroline Charre, Laurent Cotte, Samuel AlizonPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
2020
<p>Opioid substitution and syringes exchange programs have drastically reduced hepatitis C virus (HCV) spread in France but HCV sexual transmission in men having sex with men (MSM) has recently arisen as a significant public health concern. The fact that the virus is transmitting in a heterogeneous population, with "new" and "classical" hosts, makes prevalence and incidence rates poorly informative. However, additional insights can be gained by analyzing virus phylogenies inferred from dated genetic sequence data. By combining a phylodynamics approach based on Approximate Bayesian Computation (ABC) and an original transmission model, we estimate key epidemiological parameters of an ongoing HCV epidemic among MSMs in Lyon (France). We show that this new epidemic is largely independent of the 'classical' HCV epidemics and that its doubling time is ten times lower (0.44 years versus 4.37 years). These results have practical implications for HCV control and illustrate the additional information provided by virus genomics in public health.</p>
https://zenodo.org/record/4314714#.X9IjLoZCdhEYou should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://
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hepatitis C virus; Epidemiology; phylodynamics; men having sex with men; transmission; heterogeneity; treatment; Approximate Bayesian Computation; doubling times
NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).
Evolutionary Epidemiology, Phylogenetics / Phylogenomics
e.g. John Doe john@doe.com
No need for them to be recommenders of PCIEvolBiol. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct
e.g. John Doe john@doe.com
2019-07-11 13:37:23
David Rasmussen