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Sexually Transmitted Diseases:
doi: 10.1097/OLQ.0b013e3181a8cdcf

Assessing HIV Risk in Workplaces for Prioritizing HIV Preventive Interventions in Karnataka State, India

Halli, Shiva S. PHD*; Buzdugan, Raluca MA, BA*; Ramesh, B M. PHD*†; Gurnani, Vandana MA†; Sharma, Vivek PHD‡; Moses, Stephen MD*§; Blanchard, James F. PHD*§

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From the *Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada; †Karnataka Health Promotion Trust, Bangalore, Karnataka; ‡Population Services International, Bangalore, Karnataka; and §Department of Medical Microbiology, University of Manitoba, Winnipeg, Canada.

The authors thank for the contribution of the United States Agency for International Development, through Population Services International, for funding the study.

SSH was responsible for the overall concept of the article and wrote the first draft of the article, along with RB. BMR, VG, JFB, VS, and SM contributed to the writing of the article.

Supproted by the United States Agency for International Development, through Population Services International.

Correspondence: Shiva S. Halli, PhD, Department of Community Health Sciences, Faculty of Medicine, University of Manitoba, 750 Bannatyne Avenue, Winnipeg, Manitoba, Canada R3E 0W3. E-mail: halli@ms.umanithoba.ca.

Received for publication August 29, 2008, and accepted April 3, 2009.

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Objective: To develop a model for prioritizing economic sectors for HIV preventive intervention programs in the workplace.

Methods: This study was undertaken in Karnataka state, India. A 3-stage survey process was undertaken. In the first stage, we reviewed secondary data available from various government departments, identified industries in the private sector with large workforces, and mapped their geographical distribution. In the second stage, an initial rapid risk assessment of industrial sectors was undertaken, using key-informant interviews conducted in relation to a number of enterprises, and in consultation with stakeholders. In the third stage, we used both quantitative (polling booth survey) and qualitative methods (key informant interviews, in-depth interviews, focus group discussions) to study high-risk sectors in-depth, and assessed the need and feasibility of HIV workplace intervention programs.

Results: The highest risk sectors were found to be mining, garment/textile, sugar, construction/infrastructure, and fishing industries. Workers in all sectors had at best partial knowledge about HIV/AIDS, coupled with common misconceptions about HIV transmission. There were intersector and intrasector variations in risk and vulnerability across different geographical locations and across different categories of workers. This has implications for the design and implementation of workplace intervention programs.

Conclusions: There is tremendous scope for HIV preventive interventions in workplaces in India. Given the variation in HIV risk across economic sectors and limited available resources, there will be increased pressure to prioritize intervention efforts towards high-risk sectors. This study offers a model for rapidly assessing the risk level of economic sectors for HIV intervention programs.

Discussions on the need for HIV workplace intervention programs in Africa have been reported since the mid-1990s.1–2 Subsequently, researchers started documenting the successes and challenges of various HIV prevention and/or treatment programs conducted within workplaces in South Africa and other African countries.3–10 Nevertheless, a recent review of the existing literature on HIV/AIDS workplace intervention policies and programs in southern Africa remarked on “the underdeveloped and nascent state of the literature on workplace intervention programmes.”11 In general, there has been little discussion of the process of selection of enterprises for HIV workplace intervention programs.

The current study hypothesizes that workers in certain economic sectors are at higher risk for HIV than others. Given limited available resources, we propose that HIV intervention programs should first be implemented in enterprises in high-risk economic sectors. Previous studies have documented the selection process of occupational groups for randomized, controlled trials.12 However, studies documenting the selection process of enterprises for HIV workplace intervention programs are lacking. The current study is intended to fill this gap by proposing a model for prioritizing high-risk economic sectors in a large geographical area, i.e., the southern Indian state of Karnataka, with a total population of 55 million people.

Compared to Africa, there have been very few reported HIV workplace intervention programs in India. As elsewhere in the world,13–14 workers in the transport industry (truck drivers and their helpers) were among the first occupational groups to be considered as high-risk.15–21 Consequently, various HIV prevention programs have been implemented among this high-risk group,22–24 the largest being the Healthy Highways Project. Operation Lighthouse is another large-scale HIV prevention program that covered 12 major ports in India.25,26 Other smaller-scale HIV workplace prevention programs have been conducted among jute workers27 and tea plantation workers.28 The Indian Business Coalition on AIDS was established in 2003, out of growing concerns for the need for HIV workplace prevention programs across India, but this organization was not sustained.29

The United States Agency for International Development is supporting the Connect program, which aims to establish HIV workplace intervention programs in Karnataka. Before implementing the program, this research study was designed to assess the risk level of private economic sectors, in order to prioritize HIV workplace intervention programs. This article documents the assessment process, as a possible model that can be replicated elsewhere, for prioritizing economic sectors for HIV workplace intervention programs.

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We classified economic sectors by product (e.g., textile, construction, manufacturing), and we examined all types of industries, including primary (e.g., mining), secondary (e.g., manufacturing), and tertiary economic sectors (e.g., service). We restricted our study to the private sector, and we undertook a 3-stage process. In the first stage, we conducted a review and analysis of available secondary data, mainly from government sources, in order to identify the largest economic sectors and their geographical distribution. In the second stage, we conducted a rapid assessment of key informants in a selected number of enterprises. The assessment consisted of structured interviews with management representatives regarding workforce structure and employees’ sexual behavior. The results of the assessment were presented in a meeting with wide range of stakeholders, including company owners, labor contractors, representatives of nongovernmental organizations working on HIV/AIDS, and members of female sex worker organizations. These stakeholders, along with the research team, selected the sectors and districts for the third stage of the study.

In the third stage, an indepth investigation was conducted in a number of selected economic sectors and districts. Two to 3 industrial units were randomly selected in each sector and district, using a list of companies working in the district. For each selected unit, information about the workforce composition, sexual activity, and perceived HIV risk among workers was collected from a management representative, using a structured questionnaire. Following this initial assessment, approximately 5 key informants were identified at each site, and interviewed. Data were collected on the socio-demographic profile of the workers, the unit’s structure, sexual behavior among workers, and other HIV/AIDS-related information. The structured questionnaires and the key informant interviews helped us to identify the main layers of the unit’s workforce, distinguished according to occupation, gender, marital status, and age. In each unit, approximately 10 in-depth interviews were then conducted with workers who were selected from all of the main layers of the unit’s workforce. Following the interviews, about 6 focus group discussions (FGDs) and polling booth surveys (PBS) of 10 to 15 participants were conducted in each unit. The respondents from the FGDs and PBS were selected from each of the main identified layers of the unit under study. The PBS is a quantitative survey method used to obtain more accurate data on sensitive behavioral topics.30 It provides more anonymity than surveys using questionnaires, and is also expected to reduce social desirability bias.

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In the first stage of the study, we identified the economic sectors with the largest workforces (Table 1). Data in some sectors (e.g., agriculture, granite, mining, sugarcane and construction) might be affected by underreporting of workers, and nonreporting of daily wage labourers. All of the sectors listed in Table 1 were selected for the second stage of the study (the rapid assessment), with the exception of the sectors with predominantly “white-collar” workforces (e.g., software/IT parks, software/electronics, engineering, services) (Table 2). White-collar status was defined based on the level of education of the workers, and they were excluded because, while they might engage in risky behaviors, they were assumed to have more access to information on HIV/AIDS and preventive practices. On the basis of this premise, we focused on “blue-collar” and informal workers.

Table 1
Table 1
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Table 2
Table 2
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Once we selected the sectors for the rapid assessment, we identified the districts where most enterprises were concentrated for each sector. Certain districts were chosen purposively, based on anecdotal evidence from experts working in the HIV/AIDS field suggesting that risky sexual behavior is more common. The sectors and districts selected for the rapid assessment are shown in Table 2.

Based on the interviews conducted with key informants as part of the rapid assessment, the high-risk sectors were assessed to be the manufacturing, mining, and sugar industries. This assessment was intended to guide in the selection of the sectors and districts for the indepth study. The findings were discussed at the stakeholders meeting, and the final selection of industries was made, taking into account both the rapid assessment results and the stakeholders’ recommendations. Consequently, the garment, fishing, and construction industries were added to the 3 high-risk sectors noted above for inclusion in the indepth study. The indepth study was conducted in districts where most enterprises were concentrated for each sector, as indicated by the secondary data analysis. The sectors and districts selected for the in-depth study are presented in Table 2.

The indepth study collected both quantitative and qualitative data on the 6 economic sectors assessed as being high-risk. The PBS aimed to understand the workers’ sexual behavior and knowledge about HIV/AIDS (Table 3). The qualitative data (key informant interviews, indepth interviews, and FGDs) provided information on the socio-demographic characteristics of the workers, their risk level (sexual behavior and knowledge about HIV/AIDS), and the sector’s structural characteristics (organizational structure, seasonality of work, labor welfare measures, willingness for intervention programs), in order to assess the overall need and feasibility for HIV workplace intervention programs in each sector (Table 4).

Table 3
Table 3
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Table 4
Table 4
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Table 4
Table 4
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There were important differences in the level of HIV risk experienced by mining workers in Bellary district, depending on the occupational group. Laborers (diggers, loaders/unloaders, plantation workers) were more likely to report casual sex, while transport workers (drivers, cleaners) and other semiskilled and highly skilled workers were more likely report visiting female sex workers (FSWs). An important driving factor of the practice of casual sex seemed to be the facilitating workplace set-up (i.e., the hilly terrain, which provided venues where sex could take place in privacy). Drivers and cleaners (mostly unmarried) reported visiting FSWs in larger numbers, due to their reported surplus income and easy access to FSW sites (given their mobility). HIV workplace intervention programs would be facilitated by the small number of large companies involved in this work, but might be hindered by the fact that a large part of the workforce is migrant and seasonal.

In Gulbarga district, mining workers were generally low paid and unskilled. They often worked with their spouses in small units of 10 to 15 workers. The sexual behavior of these workers was similar to that of the unskilled mining workers in Bellary district, namely they tended to be involved mostly in casual sex. Male workers also visited FSWs (mainly the transport workers), but casual sex with neighbors was also common. The difficulty in implementing workplace intervention programs in this kind of setting is that the mining activity in Gulbarga district is very spread out, and conducted by a large number of small companies. On the other hand, once the companies are identified and the management agrees to a workplace intervention, the workers can be easily reached, as they are mainly local permanent workers.

Bagalkot district handloom and power loom workers were of both sexes, mostly married, and living with their families. These populations (married men living with families) were less prone to report risky sexual behavior compared to other groups. However, in Bagalkot it seemed that the availability of FSWs, especially of traditional caste-based sex workers,31 was an important factor, and as a result, male handloom workers reported frequently paying for sex. In addition, there was incomplete knowledge about HIV/AIDS. Although these workers are at high risk for HIV, there would likely be difficulties in implementing intervention programs among them, as handloom workers work out of their homes, and would therefore be difficult to reach in large numbers.

In Bangalore Rural district garment factories, most workers were blue-collar and reported engaging in risky sexual behavior. Many men working in these units visited FSWs, and also had casual sex with their female coworkers. What is specific to garment factories, however, is the large percentage of female workers, many of whom were unmarried and living without their families in company hostels. These women often reported sex without using condoms. There were also incidents reported of sexual harassment of women by various supervisors. Such sexual behavior patterns, coupled with inconsistent condom use and incomplete knowledge about HIV/AIDS, resulted in high risk behavior. Implementation of intervention programs should be feasible, as work is conducted through organized companies, with the majority of employees working on a permanent basis.

In sugar factories, employees worked either in the factory or the fields to cut the sugar cane. These 2 groups reported different patterns of sexual behavior. Factory workers were generally male, and many of them visited FSWs, and also reported other types of sexual partners in their vicinity. Sugar cane cutters were usually migrants who moved with their families from various places (mostly out-of-state) to cut sugar cane, and tended to have sex mostly within their community, including with casual partners or regular noncommercial partners. Sugar cane fields provide an environment where sex can be undertaken in privacy. Condom use was reported to be low with all partners, especially with wives and casual partners, but also with FSWs. The feasibility of intervention programs in the sugar sector varies, depending upon the type of workers targeted. Factory workers can be easily reached by programs, as they are permanent workers, directly supervised by the company management. However, the sugar cane cutters are hired by contractors on a seasonal temporary basis, with high turnover, making them difficult to reach.

Infrastructure/construction workers reported engaging in risky sexual behavior with FSWs, and casual sex with coworkers. However, the proportion of men visiting FSWs was lower if the work sites were situated outside of the city. Awareness about HIV and condoms was relatively low, and even if workers had partial or correct knowledge about HIV/AIDS, men still tended not to use condoms consistently during sex. While there is a need for intervention programs, their implementation might be problematic, given the large number of temporary seasonal migrant workers in this industry. Hence, contractors who provide the workforce for this sector might be helpful in reaching the workers.

Fishermen also represent a high-risk occupational group, as they reported frequent contact with FSWs, as well as casual sex with other women working in the port area. Although some of them reported using condoms with FSWs, they generally did not do so with other partners. A number of factors drive risky sexual behavior among fishermen compared to workers in other sectors. Fishermen have relatively high income, live away from their families and spouses, and spend a lot of time at sea, in partial isolation. Moreover, boats provide the private space necessary for casual sex. Among fishermen, deep-sea fishermen who go to sea for 1 to 2 weeks at a time reported visiting FSWs in larger numbers, and to be less exposed to HIV intervention programs. The main difficulty in implementing intervention programs is that fishing activities are generally undertaken by small companies owning only a few boats, with few employees. In addition, programs conducted in the port areas would need to take into account the fact that all fishermen cannot be found in the same place at the same time, as deep-sea and travel boat fishermen are at sea for many days at a time.

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The literature on HIV workplace intervention programs is relatively scarce, is generally limited to South Africa and other African states, and usually just presents the experience of various HIV prevention and/or treatment programs conducted within the workplace.3–10 The current study offers a model for prioritizing economic sectors for HIV workplace intervention programs in a large-scale setting. The HIV risk assessment process consisted of 3 stages, as detailed above. By first undertaking formative research, evidence can be used to inform the development of workplace intervention programs.

Using this process, we assessed the risk level of various private-sector, blue-collar economic sectors in Karnataka. As a result of this assessment, the mining, garment/textile, sugar, construction/infrastructure, and fishing industries were rated as sectors with high HIV risk. A study on the sexual behavior of garment/textile workers in the southern Indian state of Tamil Nadu has also documented risky behavior among such workers.32 The mining sector in South Africa is known for high HIV prevalence rates, and workplace intervention programs have been underway for many years.33–36 HIV workplace intervention programs have also been implemented in the sugar sector in Malawi37 and South Africa.38,39 Similarly, fishermen have been considered a high-risk group for HIV, based on studies from Uganda40 and Tanzania.41,42

Our study showed that workers in all sectors have at best partial knowledge about HIV/AIDS, coupled with common misconceptions about HIV transmission. Hence, a first step in future workplace interventions should be to increase the level of awareness and knowledge about HIV/AIDS. Low condom use among workers seems to be due to lack of awareness about STIs/HIV/AIDS, limited access or nonavailability of condoms in the vicinity of the workplace, and a perception that using condoms during sex reduces sexual pleasure. Any intervention program should, hence, address these issues.

In designing future interventions, it is important to take into account the intersector and intrasector variations in risk and vulnerability across different geographical locations, and across different categories of workers. This will facilitate a more efficient use of available resources. Moreover, if the workforce tends to be employed on a seasonal basis, the program should consider using mobile units instead of permanent ones.

In interpreting the findings of this study, a number of limitations should be noted. The fieldwork was conducted in the months July to August 2007, which in Karnataka represents the peak of the monsoon season. Except for the steel and garment sectors, all other sectors selected for the indepth study have large seasonal workforces that work less during the monsoon months. This seasonal and usually migrant workforce is believed to be at high risk for HIV, because of separation from family and spouse, isolation and loneliness, and a sense of anonymity that can lead to risky sexual behavior. Nevertheless, efforts were made during data collection to gather information about these workers. The sectors that were particularly affected by this issue are fishing and sugar. It should also be noted that in the organized sectors (i.e., steel and garment), in the early stages of the study, there were great difficulties in obtaining permission from management to interact with the workers, although for the most part, these barriers were eventually overcome.

In India, targeted HIV preventive intervention programs among high-risk groups such as FSWs and men who have sex with men have been scaled up significantly over the past few years. There has been increasing recognition though that there is a need to target FSWs’ clients, for which HIV workplace interventions can be a key strategy. In addition, as has been noted above, transactional sex is often practiced in many workplaces. However, workers in some economic sectors are at higher risk than in others, and where resources are limited, intervention efforts should be prioritized to those sectors. In this context, the current study offers a model for assessing the risk level of economic sectors for HIV intervention programs, which could be applied in the future in many different settings. Of course, identifying those sectors and individuals at highest risk is only the first step. To have impact in preventing HIV and other sexually transmitted infections, this formative research needs to be followed up by focused HIV preventive intervention programs, reaching both the women and the men involved in risky sexual practices in workplace settings.

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1. Jackson H. HIV/AIDS, STDs, and the workplace. AIDS STD Health Promot Exch 1995; 2:1–3.

2. London L. AIDS control and the workplace: The role of occupational health services in South Africa. Int J Health Serv 1998; 28:575–591.

3. Hope KR. Promoting behavior change in Botswana: An assessment of the peer education HIV/AIDS prevention program at the workplace. J Health Commun 2003; 8:267–281.

4. Bekele SB. Ethiopian Red Cross Society workplace HIV/AIDS intervention program [Abstract]. Int Conf AIDS 2004; 15.

5. Dickinson D. Smokescreen or opening a can of worms? Workplace HIV/AIDS peer education and social protection in South Africa African Studies 2006; 65:321–342.

6. Charalambous S, Innes C, Muirhead D, et al. Evaluation of a workplace HIV treatment programme in South Africa. AIDS 2007; 21(suppl 3):S73–S78.

7. Page-Shipp LS, Charalambous S, Roux S, et al. Attitudes to directly observed antiretroviral treatment in a workplace HIV care programme in South Africa. Sex Transm Infect 2007; 83:383–386.

8. Dahab M, Charalambous S, Hamilton R, Fielding K, Kielmann K, Churchyard GJ, et al. “That is why I stopped the ART”: Patients’ & providers’ perspectives on barriers to and enablers of HIV treatment adherence in a South African workplace programme. BMC Public Health 2008; 8:63–69.

9. Corbett EL, Dauya E, Matambo R, et al. Uptake of workplace HIV counselling and testing: A cluster-randomised trial in Zimbabwe. PLoS Medicine 2006; 3:1005–1102.

10. Corbett EL, Makamure B, Cheung YB, et al. HIV incidence during a cluster-randomised trial of two strategies providing voluntary counselling and testing at the workplace, Zimbabwe. AIDS 2007; 21:483–489.

11. Mahajan AP, Colvin M, Rudatsikira JB, et al. An overview of HIV/AIDS workplace policies and programmes in southern Africa. AIDS 2007; 21(suppl 3):S31–S39.

12. Wu Z, Rotheram-Borus MJ, Detels R, et al. Selecting at-risk populations for sexually transmitted disease/HIV intervention studies. AIDS 2007; 21(suppl 8):S81–S87.

13. Witte K, Cameron KA, Lapinski MK, et al. A theoretically based evaluation of HIV/AIDS prevention campaigns along the Trans-Africa highway in Kenya. J Health Commun 1998; 3:345–363.

14. Laukamm-Josten U, Mwizarubi BK, Outwater A, et al. Preventing HIV infection through peer education and condom promotion among truck drivers and their sexual partners in Tanzania, 1990–1993. AIDS Care 2000; 12:27–40.

15. Singh YN, Malaviya AN. Long distance truck drivers in India: HIV infection and their possible role in disseminating HIV into rural areas. Int J STD AIDS 1994; 5:137–138.

16. George S, Jacob M, John TJ, et al. A case-control analysis of risk factors in HIV transmission in South India. J Acquir Immun Defic Syndr Hum Retrovirol 1997; 14:290–293.

17. Kanjilal B, Forsythe S, Ganesh V, et al. An assessment of socio-economic impact of HIV/AIDS epidemic among truckers on Indian trucking industry [Abstract]. Int Conf AIDS 1998; 12:976.

18. Rao KS, Pilli RD, Rao AS, et al. Sexual lifestyle of long distance lorry drivers in India: Questionnaire survey. BMJ 1999; 318:162–163.

19. Gawande AV, Vasudeo ND, Zodpey SP, et al. Sexually transmitted infections in long distance truck drivers. J Commun Dis 2000; 32:212–215.

20. Bryan AD, Fisher JD, Benziger TJ. HIV prevention information, motivation, behavioral skills and behavior among truck drivers in Chennai, India. AIDS 2000; 14:756–758.

21. Manjunath JV, Thappa DM, Jaisankar TJ. Sexually transmitted diseases and sexual lifestyles of long-distance truck drivers: A clinico-epidemiologic study in south India. Int J STD AIDS 2002; 13:612–617.

22. Ahmad B. Workplace intervention in trucking industry [Abstract]. Int Conf AIDS 1998; 12:176.

23. Rao MR. Tracking the trucks. AIDS Action 1999; 44:5.

24. National AIDS Control Organization (NACO). Targeted interventions under NACP III. Operational guidelines. Volume 2. Migrants and truckers. NACO 2007.

25. United States Agency for International Development (USAID). Operational Lighthouse: National Ports Project. Available at: http://www.usaid.gov/in/our_work/activities/Health/health_lighthouse.htm.

26. Population Services International (PSI). India’s Operation Lighthouse. Breaking the mold on traditional HIV/AIDS behavior change approaches. Available at: http://www.psi.org/resources/pubs/OPL.pdf.

27. Ghosh M. Workplace intervention program—-matching intervention with needs [Abstract]. Int Conf AIDS 2004; 15.

28. Rafique EM. From the Tatas to the Indian Business Coalition on AIDS: The growth of work place initiatives on HIV/AIDS [Abstract]. Int Conf AIDS 2004; 15.

29. Rafique EM, Nanda RB. Solution exchange for the AIDS community consolidated reply. 2007. Available at: www.solutionexchange-un.net.in/en/Download-document/707-State-and-National-Level-NGO-Alliances.html.

30. Hanck SE, Blankenship KM, Irwin KS, et al. Assessment of self-reported sexual behavior and condom use among female sex workers in India using a polling box approach: A preliminary report. Sex Transm Dis 2008; 35:489–494.

31. O’Neil JD, Orchard T, Swarankar RC, et al. Dhanda, dharma and disease: Traditional sex work and HIV/AIDS in rural India. Soc Sci Med 2004; 59:851–860.

32. Reza-Paul S, Mangaimalar V, Mukherjee S, et al. A sexual behavior survey among male and female textile factory workers in Tirupur, India [Abstract]. Int Conf AIDS 2002; 14.

33. Heywood M. Mining industry enters a new era of AIDS prevention. Eye witness: South Africa. AIDS Anal Afr 1996; 6:16.

34. Campbell C. Migrancy, masculine identities and AIDS: The psychosocial context of HIV transmission on the South African gold mine. Soc Sci Med 1997; 45:273–281.

35. Campbell C, Williams B. Beyond the biomedical and behavioral: Towards an integrated approach to HIV prevention in the Southern African mining industry. Soc Sci Med 1999; 48:1625–1639.

36. Davies JR, de Bruin DG, Deysel M, et al. The SA mining industry enters the HIV/AIDS war zone. Meditari Account Res 2002; 10:25–51.

37. Kumwenda NI, Taha TE, Hoover DR, et al. Three surveys of HIV-1 prevalence and risk factors among men working at a sugar estate in Malawi. STD 2002; 29:366–371.

38. Morris CN, Wilkinson D, Stein Z, et al. A multi-sectoral committee in directing HIV/AIDS-specific interventions in the occupational setting: An example from South Africa. AIDS Patient Care and STDs 2001; 15:153–158.

39. Morris CN, Cheevers EJ. A package of care for HIV in the occupational setting in Africa: Results of a pilot intervention. AIDS Patient Care and STDs 2001; 15:633–640.

40. Pickering H, Okongo M, Ojwiya A, et al. Sexual networks in Uganda: Mixing patterns between a trading town, its rural hinterland and a nearby fishing village. Int J STD AIDS 1997; 8:495–500.

41. Balyagati D, Luhamba D, Nnko S, et al. HIV/AIDS and STD health promotion in Tanzanian fishing villages. AIDS STD Health Promot Exch 1995; 2:3–7.

42. Yahya-Malima KI, Matee MI, Evjen-Olsen B, et al. High potential of escalating HIV transmission in a low prevalence setting in rural Tanzania. BMC Public Health 2007; 7.

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