<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vasylyeva, T. I.</style></author><author><style face="normal" font="default" size="100%">Zarebski, A.</style></author><author><style face="normal" font="default" size="100%">Smyrnov, P.</style></author><author><style face="normal" font="default" size="100%">Williams, L. D.</style></author><author><style face="normal" font="default" size="100%">Korobchuk, A.</style></author><author><style face="normal" font="default" size="100%">Liulchuk, M.</style></author><author><style face="normal" font="default" size="100%">Zadorozhna, V.</style></author><author><style face="normal" font="default" size="100%">Nikolopoulos, G.</style></author><author><style face="normal" font="default" size="100%">Paraskevis, D</style></author><author><style face="normal" font="default" size="100%">Schneider, J.</style></author><author><style face="normal" font="default" size="100%">Skaathun, B.</style></author><author><style face="normal" font="default" size="100%">Pybus, O. G.</style></author><author><style face="normal" font="default" size="100%">Friedman, S. R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phylodynamics Helps to Evaluate the Impact of an HIV Prevention Intervention</style></title><secondary-title><style face="normal" font="default" size="100%">VirusesVirusesViruses</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Viruses</style></alt-title><short-title><style face="normal" font="default" size="100%">VirusesViruses</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">*birth-death model</style></keyword><keyword><style  face="normal" font="default" size="100%">*Hiv</style></keyword><keyword><style  face="normal" font="default" size="100%">*intervention</style></keyword><keyword><style  face="normal" font="default" size="100%">*phylodynamics</style></keyword><keyword><style  face="normal" font="default" size="100%">*prevention</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr 20</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">4</style></number><edition><style face="normal" font="default" size="100%">2020/04/25</style></edition><volume><style face="normal" font="default" size="100%">12</style></volume><isbn><style face="normal" font="default" size="100%">1999-4915</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Assessment of the long-term population-level effects of HIV interventions is an ongoing public health challenge. Following the implementation of a Transmission Reduction Intervention Project (TRIP) in Odessa, Ukraine, in 2013-2016, we obtained HIV pol gene sequences and used phylogenetics to identify HIV transmission clusters. We further applied the birth-death skyline model to the sequences from Odessa (n = 275) and Kyiv (n = 92) in order to estimate changes in the epidemic's effective reproductive number (R(e)) and rate of becoming uninfectious (δ). We identified 12 transmission clusters in Odessa; phylogenetic clustering was correlated with younger age and higher average viral load at the time of sampling. Estimated R(e) were similar in Odessa and Kyiv before the initiation of TRIP; R(e) started to decline in 2013 and is now below R(e) = 1 in Odessa (R(e) = 0.4, 95%HPD 0.06-0.75), but not in Kyiv (R(e) = 2.3, 95%HPD 0.2-5.4). Similarly, estimates of δ increased in Odessa after the initiation of TRIP. Given that both cities shared the same HIV prevention programs in 2013-2019, apart from TRIP, the observed changes in transmission parameters are likely attributable to the TRIP intervention. We propose that molecular epidemiology analysis can be used as a post-intervention effectiveness assessment tool.</style></abstract><accession-num><style face="normal" font="default" size="100%">32326127</style></accession-num><notes><style face="normal" font="default" size="100%">1999-4915Vasylyeva, Tetyana IZarebski, AlexanderSmyrnov, PavloWilliams, Leslie DKorobchuk, AniaLiulchuk, MariiaZadorozhna, ViktoriiaNikolopoulos, GeorgiosParaskevis, DimitriosSchneider, JohnSkaathun, BrittPybus, Oliver GFriedman, Samuel RDP1 DA034989/DA/NIDA NIH HHS/United StatesP30 AI036214/NH/NIH HHS/United StatesR01AI136056/NH/NIH HHS/United StatesJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov'tViruses. 2020 Apr 20;12(4):469. doi: 10.3390/v12040469.</style></notes><custom2><style face="normal" font="default" size="100%">PMC7232463</style></custom2><auth-address><style face="normal" font="default" size="100%">Department of Zoology, University of Oxford, OX1 3SY Oxford, UK.New College, University of Oxford, OX1 3BN Oxford, UK.Alliance for Public Health, Kyiv 03150, Ukraine.Division of Community Health Sciences, University of Illinois at Chicago School of Public Health, Chicago, IL 60612, USA.State Institution &quot;The L.V. Gromashevsky Institute of Epidemiology and Infectious Diseases of NAMS of Ukraine&quot;, Kyiv 03038, Ukraine.Medical School, University of Cyprus, Nicosia 1678, Cyprus.Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 157 72 Athens, Greece.Department of Medicine, University of Chicago, Chicago, IL 60637, USA.Department of Medicine, University of California San Diego, San Diego, CA 92093, USA.Department of Population Health, New York University, New York, NY 10003, USA.</style></auth-address><remote-database-provider><style face="normal" font="default" size="100%">NLM</style></remote-database-provider></record></records></xml>