Micro-level Social and Structural Syndemic of HIV Risk among Nepalese Female Sex Workers Keshab Deuba, Sarah Anderson, Anna Mia Ekström, Satish Raj Pandey, Rachana Shrestha, Deepak Kumar Karki, Gaetano Marrone Email: keshab.deuba@ki.se

Nepal: Population 31 million; low income country Background Nepal: Population 31 million; low income country Concentrated HIV epidemic. HIV prevalence in one of the key populations >5% Key populations at higher risk to HIV: People who inject drugs Sex workers Men who have sex with men/ Transgender Migrants Keshab Deuba 11/11/2018

Background Geographic heterogeneity in HIV prevalence across the country Source: National Centre for AIDS and STD Control Keshab Deuba 11/11/2018

Background: definitions Structural factors: Barriers to or facilitators of an individuals HIV prevention behavior. They may relate to physical, economic, social, policy and other aspects of the environment. Sumartojo E, AIDS. 2000;14:S3-10. Operate at the micro and macro level (i.e., immediate space, setting, and groups vs. broad social structural characteristics) of the environment. Rhodes T. Int J Drug Policy 2009 May;20(3). Keshab Deuba 11/11/2018

Background: definitions Syndemic: The idea that two or more adverse conditions interact interdependently to heighten the burden of disease in a population (M. Singer. Introduction to syndemics, 2009) Keshab Deuba 11/11/2018

Objective To assess the prevalence of HIV among female sex workers (FSWs) in Nepal To analyze the syndemic effects of micro-level social and structural factors on unprotected sex Keshab Deuba 11/11/2018

Methods Study population: women aged ≥16 years reported having been paid in cash or kind for sex with a male within the last 6 months in one of the 22 Terai Highway districts of Nepal. Analyzed 2012 surveillance survey data. Sample size: 610 Keshab Deuba 11/11/2018

Study area Keshab Deuba 11/11/2018

Methods Two-stage cluster sampling: stage 1 was the selection of clusters and stage 2 was the random selection of an equal number of participants from each selected cluster to ensure a self-weighted sample. Cluster: At least 30 sex workers in that area; those with fewer than 30 sex workers were merged with nearby locations to form a cluster. Keshab Deuba 11/11/2018

Methods Primary outcome variable: HIV prevalence, which is the percentage of female sex workers living with HIV infection. Rapid tests (Uni-Gold HIV 1/2 kits, Determine HIV 1/2 kits, and STATPAK HIV1/2 test kits) were used to detect HIV antibodies in venous blood drawn from the respondents. Keshab Deuba 11/11/2018

Methods Secondary outcome variable: Unprotected sex’ was assessed with the following question: ‘‘The last time you had sex with your client, did he use a condom?’’ Keshab Deuba 11/11/2018

Independent variables Methods Independent variables Individual level factors: age, income per week, education, length of time working as a sex worker, and days per week working as a sex worker. Frequency of alcohol use in the last 30 days Keshab Deuba 11/11/2018

Methods: Independent variables Micro-structural factors Variables used Physical   Experience of undesirable events (client refused to give money after having sex) Social Social support (number)-Sarasson et al J Soc Pers Relat 1987. Social support (satisfaction)-Sarasson et al J Soc Pers Relat 1987. Condom negotiation skills (If a client refuses to use a condom, what do you usually do?) Economic Had sex with regular and casual clients without using a condom, in order to make more money in the last 6 months Keshab Deuba 11/11/2018

Methods Syndemic index 1 (Negative conditions) 0 (Positive conditions) Client refuses to pay money   Yes 1 No Poor condom negotiation skills I still have sex with the client/only takes medication/ treatment after sex I refuse to have sex with the client/I force the client to use a condom/I explain the advantages of condoms Poor social support score number No-one ≥1 person Poor social support satisfaction score Dissatisfied Satisfied Had sex without a condom to make more money yes Keshab Deuba 11/11/2018

Methods Statistical analysis: The relative excess risk due to interaction (RERI) for binary exposures and its 95% CI, which is the standard additive interaction estimate, was calculated (VanderWeele et al 2014). The RERI was 1.97. To facilitate interpretation, the results based on the logit model were converted to the average marginal effects of syndemic conditions on unprotected sex. Keshab Deuba 11/11/2018

Results Characteristics N (%) N=610 Age 16-24 years 215 (35%)   16-24 years 215 (35%) Educational Status No formal schooling 196 (32%) Length of time working as sex worker (less than 1 year) 128 (21%) Alcohol use in the last 30 days 2-3 times a week/ Everyday 147 (24%) Income per week in NPR (median/range) 3000 (100-35000) Keshab Deuba 11/11/2018

Results Outcome variables N (%) N=610 HIV prevalence 6 (1.0%) Unprotected sex with client (yes) 149 (24%) Keshab Deuba 11/11/2018

Results Characteristics N (%) N=610 Micro- physical factors   Client refused to give money after having sex (Once or more time) 153 (25%) Micro- economic factors Had sex without condom to make more money in the past 6 months (yes) 99 (16%) Micro-social factors Able to negotiate condom use (no) 70 (12%) Keshab Deuba 11/11/2018

Results Characteristics N (%) N=610 Micro-social factors   Social support number score Nobody (poor) 60 (10%) Social support satisfaction score Dissatisfied (poor) 111 (18%) Keshab Deuba 11/11/2018

Results Other variables included in logit model- age, education, income, length of time working as sex worker and days per week working as sex worker, place of solicitation . Keshab Deuba 11/11/2018

Conclusions Interactions between two or more adverse conditions linked to physical, social, and economic environment increase the risk of unprotected sex Design and implement interventions to address poor social support, human rights violations, poor condom negotiation skills, and economic vulnerability Keshab Deuba 11/11/2018

Acknowledgement Study participants Surveillance survey-related activities were funded by The Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM) Keshab Deuba 11/11/2018