1. 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

2. 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

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

4. 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

5. 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

6. 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

7. 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 surveillance survey data.
Sample size: 610
Keshab Deuba
11/11/2018

8. Study area
Keshab Deuba
11/11/2018

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. 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 ( )
Keshab Deuba
11/11/2018

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

18. 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

19. 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

20. 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

21. 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

22. 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