Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, India
Background: People who inject drugs (PWID) account for some of the most explosive human immunodeficiency virus (HIV) and hepatitis C virus (HCV) epidemics globally. While individual drivers of infection are well understood, less is known about network factors, with minimal data beyond direct ties. M...
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
eLife Sciences Publications Ltd
2021-08-01
|
| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/69174 |
| _version_ | 1811199585851277312 |
|---|---|
| author | Steven J Clipman Shruti H Mehta Aylur K Srikrishnan Katie JC Zook Priya Duggal Shobha Mohapatra Saravanan Shanmugam Paneerselvam Nandagopal Muniratnam S Kumar Elizabeth Ogburn Gregory M Lucas Carl A Latkin Sunil S Solomon |
| author_facet | Steven J Clipman Shruti H Mehta Aylur K Srikrishnan Katie JC Zook Priya Duggal Shobha Mohapatra Saravanan Shanmugam Paneerselvam Nandagopal Muniratnam S Kumar Elizabeth Ogburn Gregory M Lucas Carl A Latkin Sunil S Solomon |
| author_sort | Steven J Clipman |
| collection | DOAJ |
| description | Background: People who inject drugs (PWID) account for some of the most explosive human immunodeficiency virus (HIV) and hepatitis C virus (HCV) epidemics globally. While individual drivers of infection are well understood, less is known about network factors, with minimal data beyond direct ties.
Methods: 2512 PWID in New Delhi, India were recruited in 2017–19 using a sociometric network design. Sampling was initiated with 10 indexes who recruited named injection partners (people who they injected with in the prior month). Each recruit then recruited their named injection partners following the same process with cross-network linkages established by biometric data. Participants responded to a survey, including information on injection venues, and provided a blood sample. Factors associated with HIV/HCV infection were identified using logistic regression.
Results: The median age was 26; 99% were male. Baseline HIV prevalence was 37.0% and 46.8% were actively infected with HCV (HCV RNA positive). The odds of prevalent HIV and active HCV infection decreased with each additional degree of separation from an infected alter (HIV AOR: 0.87; HCV AOR: 0.90) and increased among those who injected at a specific venue (HIV AOR: 1.50; HCV AOR: 1.69) independent of individual-level factors (p<0.001). In addition, sociometric factors, for example, network distance to an infected alter, were statistically significant predictors even when considering immediate egocentric ties.
Conclusions: These data demonstrate an extremely high burden of HIV and HCV infection and a highly interconnected injection and spatial network structure. Incorporating network and spatial data into the design/implementation of interventions may help interrupt transmission while improving efficiency.
Funding: National Institute on Drug Abuse and the Johns Hopkins University Center for AIDS Research. |
| first_indexed | 2024-04-12T01:51:05Z |
| format | Article |
| id | doaj.art-fd2fa27080d44f63bab48f61c728d208 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T01:51:05Z |
| publishDate | 2021-08-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-fd2fa27080d44f63bab48f61c728d2082022-12-22T03:52:57ZengeLife Sciences Publications LtdeLife2050-084X2021-08-011010.7554/eLife.69174Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, IndiaSteven J Clipman0https://orcid.org/0000-0002-2366-8420Shruti H Mehta1Aylur K Srikrishnan2Katie JC Zook3Priya Duggal4Shobha Mohapatra5Saravanan Shanmugam6Paneerselvam Nandagopal7Muniratnam S Kumar8Elizabeth Ogburn9Gregory M Lucas10Carl A Latkin11Sunil S Solomon12Department of Medicine, Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, United StatesDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United StatesYR Gaitonde Centre for AIDS Research and Education (YRGCARE), Chennai, IndiaDepartment of Medicine, Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, United StatesDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United StatesYR Gaitonde Centre for AIDS Research and Education (YRGCARE), Chennai, IndiaYR Gaitonde Centre for AIDS Research and Education (YRGCARE), Chennai, IndiaYR Gaitonde Centre for AIDS Research and Education (YRGCARE), Chennai, IndiaYR Gaitonde Centre for AIDS Research and Education (YRGCARE), Chennai, IndiaDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, United StatesDepartment of Medicine, Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, United StatesDepartment of Health, Behavior, and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, United StatesDepartment of Medicine, Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, United States; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United StatesBackground: People who inject drugs (PWID) account for some of the most explosive human immunodeficiency virus (HIV) and hepatitis C virus (HCV) epidemics globally. While individual drivers of infection are well understood, less is known about network factors, with minimal data beyond direct ties. Methods: 2512 PWID in New Delhi, India were recruited in 2017–19 using a sociometric network design. Sampling was initiated with 10 indexes who recruited named injection partners (people who they injected with in the prior month). Each recruit then recruited their named injection partners following the same process with cross-network linkages established by biometric data. Participants responded to a survey, including information on injection venues, and provided a blood sample. Factors associated with HIV/HCV infection were identified using logistic regression. Results: The median age was 26; 99% were male. Baseline HIV prevalence was 37.0% and 46.8% were actively infected with HCV (HCV RNA positive). The odds of prevalent HIV and active HCV infection decreased with each additional degree of separation from an infected alter (HIV AOR: 0.87; HCV AOR: 0.90) and increased among those who injected at a specific venue (HIV AOR: 1.50; HCV AOR: 1.69) independent of individual-level factors (p<0.001). In addition, sociometric factors, for example, network distance to an infected alter, were statistically significant predictors even when considering immediate egocentric ties. Conclusions: These data demonstrate an extremely high burden of HIV and HCV infection and a highly interconnected injection and spatial network structure. Incorporating network and spatial data into the design/implementation of interventions may help interrupt transmission while improving efficiency. Funding: National Institute on Drug Abuse and the Johns Hopkins University Center for AIDS Research.https://elifesciences.org/articles/69174people who inject drugsHIVhepatitis CtransmissionnetworksIndia |
| spellingShingle | Steven J Clipman Shruti H Mehta Aylur K Srikrishnan Katie JC Zook Priya Duggal Shobha Mohapatra Saravanan Shanmugam Paneerselvam Nandagopal Muniratnam S Kumar Elizabeth Ogburn Gregory M Lucas Carl A Latkin Sunil S Solomon Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, India eLife people who inject drugs HIV hepatitis C transmission networks India |
| title | Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, India |
| title_full | Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, India |
| title_fullStr | Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, India |
| title_full_unstemmed | Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, India |
| title_short | Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, India |
| title_sort | role of direct and indirect social and spatial ties in the diffusion of hiv and hcv among people who inject drugs a cross sectional community based network analysis in new delhi india |
| topic | people who inject drugs HIV hepatitis C transmission networks India |
| url | https://elifesciences.org/articles/69174 |
| work_keys_str_mv | AT stevenjclipman roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT shrutihmehta roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT aylurksrikrishnan roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT katiejczook roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT priyaduggal roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT shobhamohapatra roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT saravananshanmugam roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT paneerselvamnandagopal roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT muniratnamskumar roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT elizabethogburn roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT gregorymlucas roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT carlalatkin roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia AT sunilssolomon roleofdirectandindirectsocialandspatialtiesinthediffusionofhivandhcvamongpeoplewhoinjectdrugsacrosssectionalcommunitybasednetworkanalysisinnewdelhiindia |