Understanding Out-Migration Among Female Sex Workers in South India

Banandur, Pradeep MD*†; Ramanaik, Satyanarayana MSW*; Manhart, Lisa E. PhD; Buzdugan, Raluca PhD§; Mahapatra, Bidhubhushan MPhil; Isac, Shajy PhD*; Halli, Shiva S. PhD; Washington, Reynold G. MD, DNB**; Moses, Stephen MD, MPH; Blanchard, James F. PhD

Sexually Transmitted Diseases:
doi: 10.1097/OLQ.0b013e3182641d90
Original Study

Background: Migrant sex workers are known to be vulnerable to HIV. There is substantial female sex worker (FSW) mobility between the borders of Maharashtra and Karnataka, but little programming emphasis on migrant FSWs in India. We sought to understand the individual/cultural, structural, and contextual determinants of migration among FSWs from Karnataka.

Methods: A cross-sectional face-to-face interview of 1567 FSWs from 142 villages in 3 districts of northern Karnataka, India was conducted from January to June 2008. Villages having 10+ FSWs, a large number of whom were migrant, were selected following mapping of FSWs. Multinomial logistic regression was conducted to identify characteristics associated with migrant (travelled for ≥2 weeks outside the district past year) and mobile (travelled for <2 weeks outside the district past year) FSWs; adjusting for age and district.

Results: Compared with nonmigrants, migrant FSWs were more likely to be brothel than street based (Adjusted Odds Ratio (AOR): 5.7; 95% confidence interval: 1.6–20.0), have higher income from sex work (Adjusted Odds Ratio (AOR): 42.2; 12.6–142.1), speak >2 languages (AOR: 5.6; 2.6–12.0), have more clients (AORper client: 2.9; 1.2–7.2), and have more sex acts per day (AORper sex act: 3.5; 1.3–9.3). Mobile FSWs had higher income from sex work (AOR: 13.2; 3.9–44.6) relative to nonmigrants, but not as strongly as for migrant FSWs.

Conclusion: Out-migration of FSWs in Karnataka was strongly tied to sex work characteristics; thus, the structure inherent in sex work should be capitalized on when developing HIV preventive interventions. The important role of FSWs in HIV epidemics, coupled with the potential for rapid spread of HIV with migration, requires the most effective interventions possible for mobile and migrant FSWs.

In Brief

This study analyzes the factors affecting out-migration 1 among female sex workers Bagalkot, Belgaum and Bijapur districts in Karnataka south India.

Author Information

From the *Karnataka Health Promotion Trust, Bangalore, India; †Department of Community Medicine, Rajarajeswari Medical College and Hospital, Bangalore, India; ‡University of Washington, Seattle, WA; §Department of Infection and Population Health, University College London, London, United Kingdom; ¶Population Council, New Delhi, India; ∥University of Manitoba, Winnipeg, MB, Canada; and **St. John’s Research Institute, Bangalore, India

The authors would like to thank all the field and data entry staff for collecting and compiling the data, as well as the study participants in Belgaum, Bagalkot and Bijapur districts, the program staff of Karnataka Health promotion trust and the sex work collectives of the 3 districts.

Conflict of interest and sources of funding: Supported by grants from the World Bank, United States Agency for International Development (USAID), Canadian International Development Agency and Canadian Institutes of Health Research (to J.F.B.); by the Indian Council of Medical Research (to R.W.). Support for this study was provided by the Bill & Melinda Gates Foundation. The data analysis component of this study was supported by NIH research grant D43 TW000007, funded by the Fogarty International Center. All other authors declare no conflict of Interest.

The views expressed in this paper are solely those of the authors and do not necessarily reflect the official views of the Bill & Melinda Gates Foundation or the Fogarty International Center.

Correspondence: Pradeep Banandur, MD, Department of Community Medicine, Rajarajeswari Medical College and Hospital, Bangalore 560074, India. E-mail: doctorpradeepbs@gmail.com.

Received for publication December 23, 2011, and accepted June 5, 2012.

Article Outline

Approximately 2.5 million people live with HIV/AIDS in India.1 Heterosexual contact is the most common mode of transmission.2 Prevalence is highest in 4 southern Indian states,3,4 one of which is Karnataka. Unlike other places in India, the HIV prevalence in rural north Karnataka (3.6%) is higher than in urban areas (2.4%)5 because of a largely home-based rural sex work environment and the presence of traditional sex workers called Devadasis (popularly known as “Temple dancers”6,7) in the northern districts of Bagalkot, Belgaum, and Bijapur.7 This may also sustain and amplify the HIV epidemic independent of urban sexual networks. A substantial proportion of FSWs in Karnataka are mobile, both within and between states.8

Migration is an important risk factor in HIV transmission.9,10 Mobile populations have higher HIV rates than residents, independent of the HIV prevalence at their site of origin or destination.10–17 Extensive migration can expand HIV epidemics geographically by bridging high-risk sexual networks in multiple locations.8 Furthermore, mobile FSWs are more vulnerable to HIV because of inconsistent access to preventive program services,10,18 and less able to adapt and negotiate safer sex practices given their lack of influence with those controlling the sex work environment. They may have clients who are less familiar to them and therefore might be unable to negotiate condom use, all of which are compounded by language barriers.10

Given the high HIV prevalences and the role of sex work in the local transmission dynamics in the 4 southern states of India, the India AIDS initiative (Avahan) of the Bill & Melinda Gates Foundation began a focused HIV prevention programme among FSWs in 2003. In Karnataka, the Karnataka State AIDS Prevention Society and the University of Manitoba partnered through the Karnataka Health Promotion Trust (KHPT) to implement these activities. Programs in Karnataka generally focus on resident FSWs with little programming emphasis on mobile FSWs.8,18 The exception is the KHPT intervention (“Corridors” programme), which also focuses on FSWs who migrate from the districts of Belgaum, Bagalkot, and Bijapur to the neighboring state of Maharashtra.

In this context, understanding the mobility and migration of FSWs in high prevalence areas is crucial for a comprehensive understanding of HIV transmission dynamics and designing effective interventions. A large community-based cohort study titled “PAYANA” (meaning “travel” or “migration” in Sanskrit), is being funded by the Bill & Melinda Gates Foundation and conducted by KHPT and the University of Manitoba. PAYANA’s goal is to increase knowledge about migration patterns of rural FSWs and the impact of this migration on HIV risk, vulnerability, and transmission dynamics in the northern Karnataka districts of Bagalkot, Bijapur, and Belgaum. The conceptual underpinning of the PAYANA cohort study relates to the interaction between individual, social, and environmental factors that determine HIV risk, which relates to specific high-risk sexual behaviors, and vulnerability, which is composed of those factors that either facilitate or inhibit the ability to adopt safer sexual behaviors. A broad conceptual framework under which the PAYANA study was conducted is depicted in Figure 1. This construct recognizes that FSWs are frequently not the decision makers about risk reduction behaviors such as partner reduction, condom usage, or use of health services. Instead, those who control the environment such as pimps, brokers, madams, etc. as well as sex clients, exert direct and indirect influence on the latitude for decision making by FSWs. The situation is more complicated for mobile FSWs, as they move in different environments, with varying levels of control and support. Furthermore, their mobility renders them less reachable by outreach and education programs designed to support individual knowledge and skills in behavior change strategies. Using baseline data from the PAYANA cohort study, we sought to explore the associations between different mobility patterns and the individual, sociodemographic, and sex work characteristics that affect out-migration among FSWs in northern Karnataka.

Back to Top | Article Outline


We analyzed baseline data, collected between January and July 2008, from the PAYANA cohort.

Back to Top | Article Outline

The 3 districts were selected based on their historically high HIV prevalences (>3.0% in antenatal women) and the history of FSW migration from their rural areas to districts in nearby Maharashtra.19 Initially, comprehensive rural mapping of sex work locations was performed, generating the sampling frame for a 2-stage sampling process, which first selected villages and then migrant and nonmigrant FSWs in the selected villages. A migrant FSW was defined as having been outside the district or state for sex work in the past year for at least 1 period of >2 weeks. Nonmigrant FSWs were defined as not having been outside the district or state for sex work in the past year. The main PAYANA study collected information on migration, mobility, and HIV vulnerability in sampled migrant and nonmigrant FSWs at baseline, and at 3, 9, 15, and 21 months following.

Back to Top | Article Outline

Teams of community consultants, field researchers, program outreach workers, and peer educators visited each village in the 3 districts and gathered information on commercial sex work primarily through key informant interviews. Information collected included total number of FSWs (currently living in the village, usually in the village, and out of the village), client volume, sources of clients, and general mobility patterns.

Based on this, the talukas (subdistricts) with the highest proportion of migrant FSWs were selected (n ≥ 15 talukas). From these, 142 villages with the largest number of migrant FSWs were selected. After selecting the villages, mapping was repeated to validate the sampling frame. On validation, villages that had no identified FSWs were replaced with nearby villages with >10 FSWs. All migrant FSWs in each village were selected. For nonmigrant FSWs, a target proportionate to the size estimate of nonmigrant FSW population was set in each taluka. Peer community researchers (former or current FSWs working in an ongoing community sex work intervention known to the FSWs in a particular village) identified all FSWs.

After obtaining written informed consent, qualified field investigators administered a pen and paper questionnaire. Ethical approval was obtained from the institutional review boards of St John’s Medical College and Hospital, Bangalore, India, and the University of Manitoba, Winnipeg, Canada for the cohort study, and from the University of Washington, United States for the current analyses.

Back to Top | Article Outline
Analytic Methods

Our primary dependent variable was migration status in the past year, categorized as migrant, mobile, and nonmigrant. During protocol development, we had planned to compare only migrant and nonmigrant FSWs. However, after data collection, we identified 2 separate groups of FSW who moved for sex work (migrant and mobile), and they differed substantially from each other and from nonmigrant FSWs. Along with migrants and nonmigrants, this third group of mobile FSWs is potentially important in the dynamics of HIV transmission. We assessed the relationship between migration status and individual, sociodemographic, and sex work characteristics. Individual factors included age, residence, literacy, languages, and reason for entering sex work. Sociodemographic factors included marital status, schooling, household size, number of living children, children supported financially, and monthly household income. A sex worker’s household was considered as the place where her family lived in her native village (e.g., husband/lover, children, parents, and/or siblings living under one roof), not the place where she engaged in sex work. Sex work characteristics included age at sex work debut, duration in sex work, main place of solicitation, client demand, source of clients, type of clients/partners, number of sexual acts per day, income from sex work, condom use with different clients, and history of arrest for sex work. The main place of solicitation and main place for entertaining clients were categorized into home (any house or rented room), brothel (brothel, lodge, and dhaba, which are small restaurants and rest stops along highways), street, and other. A nonpaying partner was defined as a regular or primary partner who did not pay for sex. A new client was a paying client for the first time. An occasional client was a paying client who came irregularly or was not known to the FSW.

Statistical analyses were undertaken using StataIC 10.1 (Stata Corporation, College Station, TX). Descriptive analysis tested the association of individual, sociodemographic, and sex work characteristics mentioned earlier in the text, with migration status using Pearson χ2 test for categorical variables and Wilcoxon rank sum test for continuous variables. Multivariate analyses used multinomial logistic regression to identify characteristics independently associated with migration status. Age, languages spoken, marital status, and district of origin were considered primary exposure variables. All factors associated with migration status and at least 1 primary exposure variable were assessed as potential confounders. Only those characteristics that changed the risk estimates of one or more primary exposure variable(s) by >10% were retained in the final model. In the case of multiple variables representing similar concepts (e.g., number of living children and number of dependent children; monthly household income; and monthly income from sex work), we selected only the characteristic thought to best represent the overall concept. History of police arrest was excluded from the multivariate analysis, given the high proportion of nonresponses.

Back to Top | Article Outline


Sample Distribution

During the data collection period (January–July 2008), 1567 FSWs were interviewed. The majority was from Bagalkot (55.8%); followed by Belgaum (28.1%) and Bijapur (16.1%) (Table 1). Among these, 730 (46.5%) were nonmigrant, 645 (41.2%) were migrant, and 192 (12.3%) were mobile FSWs. Nearly half of the FSWs from Bagalkot (49.3%) to Bijapur (41.3%), and only a quarter from Belgaum were migrant. Approximately 50% of FSWs from Belgaum were nonmigrants. Among all FSWs approached, only 13 (0.8%) refused participation.

Back to Top | Article Outline
Individual and Sociodemographic Factors

Overall, FSWs differed significantly on most individual and sociodemographic characteristics (Table 1). The majority of FSWs was illiterate (80.7%) and Devadasi (73.8%), and most had practiced sex work for at least 5 years (52.3%). However, mobile FSWs were less often illiterate (65.1%) and Devadasi (43.8%) than either nonmigrant or migrant FSWs (80.7% and 85.4% illiterate and 72.8% and 83.9% Devadasi, respectively). Migrant FSWs were younger and generally spoke 2 or more languages. In contrast, mobile FSWs were older, more often from Belgaum and mostly spoke only one language.

Most FSWs reported at least 4 members in their household (81.9% overall), although migrant FSWs had larger families (24% had ≥9 members). Most entered sex work to meet their family’s financial needs (46.4% overall) or through the Devadasi tradition (45.4% overall), with the exception of mobile FSWs who most often cited their family’s financial needs. Migrant FSWs reported more often having no children (41.1%) and had a higher monthly household income (median Rs. 6000) than nonmigrant (median Rs. 2700) and mobile (median Rs. 3000) FSWs.

Back to Top | Article Outline
Sex Work Characteristics

FSWs differed significantly on all assessed sex work characteristics (Table 2). Migrant FSWs were younger at sex work debut, earned more money from sex work (median Rs. 5000/mo), and were less likely to have any other source of income compared with nonmigrant and mobile FSWs. They mostly solicited and entertained clients in brothels, and a majority reported having ≥3 clients and ≥3 sexual acts per day. In contrast, mobile FSWs were older when they started sex work than either nonmigrant or migrant FSWs, reported no primary place of solicitation, and clients mostly came on their own (61.5%); most entertained clients at brothels (56.3%) or at home (38%). Half of mobile FSWs reported ≤2 clients/day, and 60.4% reported ≥3 sexual acts/day. Nonmigrant FSWs earned less from sex work (44.0% earned Rs. <1000/mo), had other sources of income (71.8%), mostly entertained clients at home (>80%), and had fewer clients and fewer sexual acts/day compared with migrant and mobile FSWs. The majority of nonmigrants (79.0%) and mobile FSWs (60.4%) contributed all their income to their households.

All migrant FSWs practiced sex work outside their district/state but usually did not do so in their native village (87.6%). Only one-third of nonmigrant FSWs (31.5%) and only half of mobile FSWs (47.9%) had practised sex work outside the district or state. Mobile FSWs practiced sex work both within and outside their district, and nearly all had plans to travel within their native district (96.4%). More migrant FSWs reported using condoms every time they had sex with paying clients (99.2%) than did mobile (91.2%) and nonmigrant (84.8%) FSWs. More non-migrant FSWs reported having sex with nonpaying partners (65.5%) than either migrant (18.6%) or mobile FSWs (13.0%).

Back to Top | Article Outline
Multivariate Analyses

Adjusting for age, and district compared with nonmigrant FSWs, migrant FSWs were significantly more likely to be brothel than street based (Adjusted Odds Ratio [AOR]: 5.7; 95% confidence interval [CI]: 1.6–20.0), have higher income from sex work (AOR: 42.2; 95% CI: 12.6–142.1), speak >2 languages (AOR: 5.6%; 95% CI: 2.6–12.0), and have more clients (AORper client: 2.9; 95% CI: 1.2–7.2) and sex acts/day (AORper sex act: 3.5; 95% CI: 1.3–9.3). They were significantly less likely to have a source of income other than sex work (AOR: 0.3, 95% CI: 0.2–0.6) (Table 3). Mobile FSWs were characterized by higher monthly income from sex work (AOR: 13.2; 95% CI: 3.9–44.6) relative to nonmigrants, but not as strongly as for migrant FSWs. Mobile FSWs also reported more sex acts/day (AORper sex act: 5.3; 95% CI: 2.9–9.5) and were less likely to be Devadasi (AOR: 0.2; 95% CI: 0.1–0.4).

Back to Top | Article Outline


Most migrant FSWs in the 3 districts of northern Karnataka were Devadasi, illiterate, and they had been in sex work for >5 years, similar to other FSWs in the region.4,5,8,20 Brothel-based sex work, higher income from sex work, speaking >2 languages, having more clients, and more sex acts/day were characteristics of a migrant FSW, whereas mobile FSWs were characterized by having moderate income from sex work but a relatively large number of sexual acts/day.

Our original hypothesis that migrant FSWs are more vulnerable to HIV and other social vulnerabilities at their place of destination, due to being less embedded in the social structure, is true for mobile FSWs. However, we found that migrant FSWs were involved in very structured sex work. They primarily solicited and entertained clients in brothels and practiced sex work in the same place without intentions to practice in other places within the district. In contrast, mobile FSWs reported no preference for a place of solicitation and practiced sex work both within and outside the district. Thus, mobile FSWs may “bridge” local and nonlocal networks; this corresponds with results from another study suggesting high mobility and short duration of stay are risk markers for HIV among FSWs.21

Of the 7 FSW characteristics independently associated with migration, 5 were related to sex work (place of solicitation, sex work income, client demand, sexual acts/day, and source of income other than sex work); 1 was sociodemographic (marital/devadasi status), and one was individual (number of languages spoken). The sex work characteristics may actually be consequences of FSW migration. Migrant FSWs are mainly organized around brothels which provide a favorable environment for soliciting clients and sex work in destinations. Brothels also ensure client flow since the clients are aware of the constant availability of FSWs in brothels. We hypothesize that women migrate to access a greater number of clients where there is a greater demand for sex work. Clients attending brothels may have more money to spend, and the brothel setup may make it easier to have many clients. Alternatively, FSWs might migrate to places where sex work is more efficient and more lucrative. Although migrant FSWs contributed a lower proportion of their earnings to their household income than mobile and nonmigrant FSWs, the actual amount contributed was greater than that contributed by nonmigrant and mobile FSWs, suggesting greater economic success among migrant FSWs and contributing to the large confidence interval observed in the study. Migrant FSWs speaking more languages compared with nonmigrants and mobile FSWs might also be an adaptation to the local situation rather than being a factor leading to migration.

One-third of nonmigrant FSWs reported having migrated outside the district early in their sex work career. Over time, migrant FSWs might come back to settle in their native villages, contributing to the local HIV transmission dynamics If they acquired HIV while they were outside. These returned sex workers may influence young Devadasis, through their networks, to migrate to places outside which are safe and lucrative. It is likely that young FSWs migrate in order to make money and as the client demand reduces overtime, they either return to their native villages or stay on in their destinations to become brothel madams. These migrant devadasi FSWs might influence others from their place of origin to migrate and join them. Devadasis were mainly nonmigrants or migrants but less likely to be mobile FSWs, suggesting that the structure of residential and migrant sex work is more suited to the Devadasi system.

Although not considered a factor influencing migration, condom use is an important aspect of an FSW’s risk for HIV infection. Interestingly, condom usage across partner type was highest among migrant FSWs compared with nonmigrant and mobile FSWs. This may be because HIV intervention programs at sex work destinations focus on condom promotion and condom social marketing. Additionally, there may be some social desirability bias in reporting condom use, with those working in structured settings like brothels feeling pressure to report high condom use. The high prevalence of HIV among young FSWs,4 suggests that they typically acquire HIV infection during the early years of sex work. Young FSWs early in their sex work careers may be more likely to forego condom usage to earn more money, making them more vulnerable to HIV/STIs. Furthermore, when FSWs initially migrate, their clients might be less familiar to them, either individually or from a socio-cultural perspective, and therefore FSWs might be less empowered to negotiate condom use early in their sex work careers. Unfortunately, due to sampling at villages rather than at destinations, we were unable to explore condom use patterns among younger, newer FSWs (only 3% had been involved in sex work for <2 years).

We believe that the high-response rate in our study was because of the involvement of peer community researchers who identified and established rapport with potential participants. The ongoing Corridors program also likely provided conducive environment for study participation. Previous studies evaluating factors influencing migration among established sex workers22,23 have either used convenience sampling, with small sample sizes or were qualitative in nature.7,12 The rigorous community-based sampling, the high response rates, and the quantitative analyses used are strengths of our study. However, there are some limitations. Characteristics of urban FSWs may differ from those we identified here among FSWs in a rural setting, studies among urban FSWs are required. Given the small numbers of new FSWs in our study population, these results cannot be generalized to FSWs who have had <2 years experience in sex work. Furthermore, the cross-sectional nature of this study cannot assess temporal sequence, and thus we cannot conclude that factors identified as being independently associated with migration are causes or results of migration.

Out-migration of FSWs in South India was strongly tied to sex work characteristics. The important role that FSWs play in heterosexual HIV epidemics, coupled with the potential for the rapid spread of HIV with migration, call for developing the most effective interventions for mobile and migrant FSWs capitalizing on the structures inherent in sex work. Additionally, interventions focusing on current migrant FSWs may reduce HIV vulnerability among future migrant FSWs. Information on common destinations and patterns of movement among migrant and mobile FSWs would help position service delivery. These data, in combination with additional longitudinal studies designed to understand the determinants of migration and mobility, and factors influencing timing and destination for migration, are essential to appropriately design, implement and refine HIV interventions focusing for migrant and mobile FSWs.

Back to Top | Article Outline


1. National AIDS Control Organisation. HIV sentinel surveillance and HIV estimation, 2006. In: Ministry of Health and Family Welfare. 2007: 1–16.
2. Joint United Nations Programme on HIV/AIDS (UNAIDS). Report on Global AIDS Epidemic. Geneva, Switzerland: UNAIDS, 2006.
3. Moses S, Ramesh BM, Nagelkerke NJ, et al.. Impact of an intensive HIV prevention programme for female sex workers on HIV prevalence among antenatal clinic attenders in Karnataka state, south India: an ecological analysis. AIDS 2008; 22 (suppl 5): S101–S108.
4. Ramesh BM, Moses S, Washington R, et al.. Determinants of HIV prevalence among female sex workers in four south Indian states: analysis of cross-sectional surveys in twenty-three districts. AIDS 2008; 22 (suppl 5): S35–S44.
5. Becker ML, Ramesh BM, Washington RG, et al.. Prevalence and determinants of HIV infection in South India: A heterogeneous, rural epidemic. AIDS (London, England) 2007; 21: 739–747.
6. O’Neil J, Orchard T, Swarankar RC, et al.. Dhandha, dharma and disease: Traditional sex work and HIV/AIDS in rural India. Soc Sci Med 2004; 59: 851–860.
7. Orchard TR. Girl, woman, lover, mother: Towards a new understanding of child prostitution among young Devadasis in rural Karnataka, India. Soc Sci Med 2007; 64: 2379–2390.
8. Blanchard JF, O’Neil J, Ramesh BM, et al.. Understanding the social and cultural contexts of female sex workers in Karnataka, India: Implications for prevention of HIV infection. J Infect Dis 2005; 191 (suppl 1): S139–S146.
9. Quinn TC, Overbaugh J. HIV/AIDS in women: An expanding epidemic. Science (New York, NY) 2005; 308: 1582–1583.
10. Webber G. The impact of migration on HIV prevention for women: Constructing a conceptual framework. Health Care Women Int 2007; 28: 712–730.
11. Decosas J, Adrien A. Migration and HIV. AIDS (London, England) 1997; 11 (suppl A): S77–S84.
12. Brewer TH, Hasbun J, Ryan CA, et al.. Migration, ethnicity and environment: HIV risk factors for women on the sugar cane plantations of the Dominican Republic. AIDS (London, England) 1998; 12: 1879–1887.
13. Bronfman MN, Leyva R, Negroni MJ, et al.. Mobile populations and HIV/AIDS in Central America and Mexico: Research for action. AIDS (London, England) 2002; 16 (suppl 3): S42–S49.
14. Broring G, Van Duifhuizen R. Mobility and the spread of HIV/AIDS: A challenge to health promotion. AIDS Health Promot Exch 1993; 1: 1–3.
15. Coast E. Local understandings of, and responses to, HIV: Rural-urban migrants in Tanzania. Soc Sci Med 2006; 63: 1000–1010.
16. Ford K, Chamrathrithirong A. Sexual partners and condom use of migrant workers in Thailand. AIDS Behav 2007; 11: 905–914.
17. Gras MJ, van Benthem BH, Coutinho RA, et al.. Determinants of high-risk sexual behavior among immigrant groups in Amsterdam: Implications for interventions. J Acquir Immune Defic Syndr 2001; 28: 166–172.
18. Quinn TC. Population migration and the spread of types 1 and 2 human immunodeficiency viruses. Proc Natl Acad Sci USA 1994; 91: 2407–2414.
19. India-Canada Collaborative HIV/AIDS Project Bangalore, Population Research Center, JSS Institute of Economic Research. Baseline Survey of Female Commercial Sex Workers in Karnataka. Workshop on Mapping of Female Commercial Sex Work in Karnataka. Dharwad, Karnataka: India-Canada HIV/AIDS Project, Bangalore and Population Research Center, JSS Institute of Economic Research, 2002.
20. 20. Ramesh BM, Washington R, Mondal S, et al. Sex work typology and risk of HIV in female sex workers: Findings from an integrated biological and behavioral assessment in the Southern Indian state of Karnataka. In: XVI International AIDS Conference, 2006, Toronto, ON, Canada.
21. Saggurti N, Jain AK, Sebastian MP, et al.. Indicators of mobility, socio-economic vulnerabilities and HIV risk behaviours among mobile female sex workers in India. AIDS Behav 2011; 16: 952–959.
22. Surratt H. Sex work in the Caribbean Basin: Patterns of substance use and HIV risk among migrant sex workers in the US Virgin Islands. AIDS Care 2007; 19: 1274–1282.
23. Wang B, Li X, Stanton B, et al.. Gender differences in HIV-related perceptions, sexual risk behaviors, and history of sexually transmitted diseases among Chinese migrants visiting public sexually transmitted disease clinics. AIDS Patient Care STDS 2007; 21: 57–68.
© Copyright 2012 American Sexually Transmitted Diseases Association