Next Article in Journal
Experimental Infection Using Mouse-Adapted Influenza B Virus in a Mouse Model
Previous Article in Journal
Unveiling the Hidden Rules of Spherical Viruses Using Point Arrays
Previous Article in Special Issue
Molecular Epidemiology of the HIV-1 Subtype B Sub-Epidemic in Bulgaria
Open AccessArticle

Phylodynamics Helps to Evaluate the Impact of an HIV Prevention Intervention

1
Department of Zoology, University of Oxford, OX1 3SY Oxford, UK
2
New College, University of Oxford, OX1 3BN Oxford, UK
3
Alliance for Public Health, Kyiv 03150, Ukraine
4
Division of Community Health Sciences, University of Illinois at Chicago School of Public Health, Chicago, IL 60612, USA
5
State Institution “The L.V. Gromashevsky Institute of Epidemiology and Infectious Diseases of NAMS of Ukraine”, Kyiv 03038, Ukraine
6
Medical School, University of Cyprus, Nicosia 1678, Cyprus
7
Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 157 72 Athens, Greece
8
Department of Medicine, University of Chicago, Chicago, IL 60637, USA
9
Department of Medicine, University of California San Diego, San Diego, CA 92093, USA
10
Department of Population Health, New York University, New York, NY 10003, USA
*
Author to whom correspondence should be addressed.
Viruses 2020, 12(4), 469; https://doi.org/10.3390/v12040469
Received: 30 January 2020 / Revised: 2 April 2020 / Accepted: 15 April 2020 / Published: 20 April 2020
(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)
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 (Re) 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 Re were similar in Odessa and Kyiv before the initiation of TRIP; Re started to decline in 2013 and is now below Re = 1 in Odessa (Re = 0.4, 95%HPD 0.06–0.75), but not in Kyiv (Re = 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. View Full-Text
Keywords: HIV; phylodynamics; birth-death model; prevention; intervention HIV; phylodynamics; birth-death model; prevention; intervention
Show Figures

Figure 1

MDPI and ACS Style

Vasylyeva, T.I.; Zarebski, A.; Smyrnov, P.; Williams, L.D.; Korobchuk, A.; Liulchuk, M.; Zadorozhna, V.; Nikolopoulos, G.; Paraskevis, D.; Schneider, J.; Skaathun, B.; Hatzakis, A.; Pybus, O.G.; Friedman, S.R. Phylodynamics Helps to Evaluate the Impact of an HIV Prevention Intervention. Viruses 2020, 12, 469.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop