Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs

被引:1
作者
Buchanan, Ashley L. [1 ]
Katenka, Natallia [2 ]
Lee, Youjin [3 ]
Wu, Jing [2 ]
Pantavou, Katerina [4 ]
Friedman, Samuel R. [5 ]
Halloran, M. Elizabeth [6 ,7 ]
Marshall, Brandon D. L. [8 ]
Forastiere, Laura [9 ]
Nikolopoulos, Georgios K. [4 ]
机构
[1] Univ Rhode Isl, Dept Pharm Practice, Kingston, RI 02881 USA
[2] Univ Rhode Isl, Dept Comp Sci & Stat, Kingston, RI 02881 USA
[3] Brown Univ, Dept Biostat, Providence, RI 02912 USA
[4] Univ Cyprus, Med Sch, CY-1678 Nicosia, Cyprus
[5] NYU, Dept Populat Hlth, New York, NY 10016 USA
[6] Fred Hutchinson Canc Ctr, Vaccine & Infect Dis Div, Seattle, WA 98109 USA
[7] Univ Washington, Dept Biostat, Seattle, WA 98195 USA
[8] Brown Univ Sch Publ Hlth, Dept Epidemiol, Providence, RI 02912 USA
[9] Yale Sch Publ Hlth, Dept Biostat, New Haven, CT 06520 USA
来源
PATHOGENS | 2023年 / 12卷 / 02期
基金
美国国家卫生研究院;
关键词
spillover effects; networks; people who use; inject drugs; human immunodeficiency virus; DRIVEN SAMPLING DATA; HIV RISK BEHAVIORS; SOCIAL NETWORK; CAUSAL INFERENCE; INJECT DRUGS; NEW-YORK; OPIOID USERS; RANDOMIZATION; INTERVENTION; TRANSMISSION;
D O I
10.3390/pathogens12020326
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Human Immunodeficiency Virus (HIV) interventions among people who use drugs (PWUD) often have spillover, also known as interference or dissemination, which occurs when one participant's exposure affects another participant's outcome. PWUD are often members of networks defined by social, sexual, and drug-use partnerships and their receipt of interventions can affect other members in their network. For example, HIV interventions with possible spillover include educational training about HIV risk reduction, pre-exposure prophylaxis, or treatment as prevention. In turn, intervention effects frequently depend on the network structure, and intervention coverage levels and spillover can occur even if not measured in a study, possibly resulting in an underestimation of intervention effects. Recent methodological approaches were developed to assess spillover in the context of network-based studies. This tutorial provides an overview of different study designs for network-based studies and related methodological approaches for assessing spillover in each design. We also provide an overview of other important methodological issues in network studies, including causal influence in networks and missing data. Finally, we highlight applications of different designs and methods from studies of PWUD and conclude with an illustrative example from the Transmission Reduction Intervention Project (TRIP) in Athens, Greece.
引用
收藏
页数:28
相关论文
共 163 条
  • [1] Treatment of medical, psychiatric, and substance-use comorbidities in people infected with HIV who use drugs
    Altice, Frederick L.
    Kamarulzaman, Adeeba
    Soriano, Vincent V.
    Schechter, Mauro
    Friedland, Gerald H.
    [J]. LANCET, 2010, 376 (9738) : 367 - 387
  • [2] A p* primer:: logit models for social networks
    Anderson, CJ
    Wasserman, S
    Crouch, B
    [J]. SOCIAL NETWORKS, 1999, 21 (01) : 37 - 66
  • [3] ESTIMATING AVERAGE CAUSAL EFFECTS UNDER GENERAL INTERFERENCE, WITH APPLICATION TO A SOCIAL NETWORK EXPERIMENT
    Aronow, Peter M.
    Samii, Cyrus
    [J]. ANNALS OF APPLIED STATISTICS, 2017, 11 (04) : 1912 - 1947
  • [4] Exact p-Values for Network Interference
    Athey, Susan
    Eckles, Dean
    Imbens, Guido W.
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2018, 113 (521) : 230 - 240
  • [5] Barkley BG., STABILIZED IPW ESTIM
  • [6] CAUSAL INFERENCE FROM OBSERVATIONAL STUDIES WITH CLUSTERED INTERFERENCE, WITH APPLICATION TO A CHOLERA VACCINE STUDY
    Barkley, Brian G.
    Hudgens, Michael G.
    Clemens, John D.
    Ali, Mohammad
    Emch, Michael E.
    [J]. ANNALS OF APPLIED STATISTICS, 2020, 14 (03) : 1432 - 1448
  • [7] Randomization tests of causal effects under interference
    Basse, G. W.
    Feller, A.
    Toulis, P.
    [J]. BIOMETRIKA, 2019, 106 (02) : 487 - 494
  • [8] Analyzing Two-Stage Experiments in the Presence of Interference
    Basse, Guillaume
    Feller, Avi
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2018, 113 (521) : 41 - 55
  • [9] Correcting for differential recruitment in respondent-driven sampling data using ego-network information
    Beaudry, Isabelle S.
    Gile, Krista J.
    [J]. ELECTRONIC JOURNAL OF STATISTICS, 2020, 14 (02): : 2678 - 2713
  • [10] A review of network simulation models of hepatitis C virus and HIV among people who inject drugs
    Bellerose, Meghan
    Zhu, Lin
    Hagan, Liesl M.
    Thompson, William W.
    Randall, Liisa M.
    Malyuta, Yelena
    Salomon, Joshua A.
    Linas, Benjamin P.
    [J]. INTERNATIONAL JOURNAL OF DRUG POLICY, 2021, 88