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Front. Microbiol. | doi: 10.3389/fmicb.2018.01825

Pockets of HIV Non-Infection within Highly-Infected Risk Networks in Athens, Greece

Leslie D. Williams1, Evangelia-Georgia Kostaki2, Eirini Pavlitina3,  Dimitrios Paraskevis2,  Angelos Hatzakis2, John Schneider4, Pavlo Smyrnov5,  Andria Hadjikou6, 7,  Georgios Nikolopoulos6,  Mina Psichogiou8, 9 and  Samuel R. Friedman1*
  • 1National Development and Research Institutes, United States
  • 2Department of Hygiene Epidemiology and Medical Statistics, School of Medicine, University of Athens, Greece
  • 3Transmission Reduction Intervention Project, Greece
  • 4Departments of Medicine, University of Chicago, United States
  • 5Alliance for Public Health, Ukraine
  • 6Medical School, University of Cyprus, Cyprus
  • 7European University Cyprus, Cyprus
  • 8Laiko General Hospital of Athens, Greece
  • 9National and Kapodistrian University of Athens Medical School, Greece

As part of a network study of HIV infection among people who inject drugs (PWID) and their contacts, we discovered a connected subcomponent of 29 PWID. In the context of a just-declining large epidemic outbreak, this raised a question: What explains the existence of large pockets of uninfected people? Possible explanations include “firewall effects” (Friedman et al 2001; Dombrowski et al 2017) wherein the only HIV+ people they take risks with have low viral loads; “bottleneck effects” wherein few network paths into the pocket of non-infection exist; low risk behaviors; and an impending outbreak. We tested each of these. Participants provided information on their enhanced sexual and injection networks and assisted us in recruiting network members. The largest connected component had 92 members. Data on risk behaviors in the last 6 months were collected at the individual level. Recent infection was determined by LAg (SediaTM Biosciences Corporation), data on recent seronegative tests, and viral load. HIV-RNA was quantified using Artus HI Virus-1 RG RT-PCR (Qiagen). The 29 members of the connected subcomponent of uninfected participants were connected (network distance = 1) to 17 recently-infected and 24 long-term infected participants. Fourteen (48%) of these 29 uninfected were classified as “extremely high risk” because they self-reported syringe sharing and had at least one injection partner with viral load > 100,000 copies/mL. Seventeen of the 29 uninfected were re-interviewed after six months, but none had seroconverted. These findings show the power of network research in discovering infection patterns that standard individual-level studies cannot. Theoretical development and exploratory network research studies may be needed to understand these findings and deepen our understanding of how HIV does and does not spread through communities. Finally, the methods developed here provide practical tools to study “bottleneck” and “firewall” network hypotheses in practice.

Keywords: networks, HIV transmission, non-infection, HIV risk, firewall effects, Bottleneck effects

Received: 06 May 2018; Accepted: 23 Jul 2018.

Edited by:

Tara P. Hurst, Abcam (United Kingdom), United Kingdom

Reviewed by:

Taisuke Izumi, Henry M. Jackson Foundation, United States
Ellsworth M. Campbell, Centers for Disease Control and Prevention (CDC), United States  

Copyright: © 2018 Williams, Kostaki, Pavlitina, Paraskevis, Hatzakis, Schneider, Smyrnov, Hadjikou, Nikolopoulos, Psichogiou and Friedman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Samuel R. Friedman, National Development and Research Institutes, New York, United States,