Secondary Logo

Journal Logo

EDITORIAL REVIEW

Fisherfolk are among groups most at risk of HIV: cross-country analysis of prevalence and numbers infected

Kissling, Esthera; Allison, Edward Ha; Seeley, Janet Aa; Russell, Stevena; Bachmann, Maxa; Musgrave, Stanley Da; Heck, Simonb

Author Information
doi: 10.1097/01.aids.0000191925.54679.94

Introduction

HIV prevalence in some fishing communities in low and middle-income countries is known to be high relative to national average seroprevalence rates [1,2]. Most of the studies supporting this claim refer to the men involved in fish-catching operations (fishermen). However, they acknowledge that the men and women who work in associated occupations such as fish trading and processing are also vulnerable, in part because they are often within the fishermen's sexual networks [3–5]. This vulnerability stems from the nature and dynamics of the fish trade and fishing lifestyle in which a number of known or hypothesized ‘risk factors’ converge.

  • Most people involved in fishing as an occupation are within the age groups (15 to 35 years) most vulnerable to sexually transmitted infections (STIs).
  • Many fishing people are mobile or migratory, so the social structures that constrain sexual behaviour in home communities may not apply in the context of fishing camps or ports.
  • Fishing is a high-risk occupation which can contribute to a culture of risk denial or risk confrontation, extending to displays of bravado and risk-taking in the social and sexual arena.
  • Fishing people are often socially marginalized and have low status, which can cause, among men, exaggerated or ‘oppositional’ forms of masculinity that challenge norms of behaviour adopted by those in ‘mainstream’ society. Masculinity in this context often includes the expectation of multiple sexual partners.
  • Alcohol use is widespread among fisherfolk in many parts of the world, to help cope with the dangers or stresses of their occupation. This further compounds vulnerability to HIV.
  • In addition, fisherfolk are vulnerable to HIV and AIDS due to inadequate prevention, treatment and mitigation measures and limited access to sexual health services more generally.

These points are summarized from a more detailed explanation and bibliography pertaining to HIV-related risk factors among fisherfolk, given in two of our earlier publications [2,6].

The occurrence of these risk factors should not be taken as characteristic of all fishing communities but it appears, through numerous government, donor agency and non-governmental organization reports as well as recent academic studies, to be widespread enough to cause concern that fishermen, female fish traders and processors and their sexual partners are at significant risk of HIV infection. This is particularly so in the Asian, African and Latin American countries with established or emerging epidemics, where over 95% of the world's 200 million fisherfolk (men and women fish catchers, processors and traders) live [3].

Thus, there is mounting evidence that fisherfolk and people living in fishing communities comprise a significant sub-population at risk. Despite this, the policy response to their vulnerability has, to date, been limited and fragmented. There is, for example, no clear targeting of fishing communities in prevention, care and mitigation guidelines issued by WHO and UNAIDS. Key national and international fisheries policies do not mention HIV and AIDS [3,7]. It was only in March 2005 that the International Labour Organisation's Governing Body was asked to consider a draft FAO/ILO/IMO ‘Fishing Vessel Safety Code and Voluntary Guidelines’ recommending that ‘those who are HIV positive, but not disabled, are not excluded from opportunities to work’ [8].

There is evidence, however, that the previous neglect of HIV in the fisheries sector is changing. Recent initiatives, like those supported by the Food and Agriculture Organisation of the United Nations (FAO) and the WorldFish Center, have started to raise awareness of HIV in the sector [3]. Urgent action is still required to increase awareness and improve the response. A first step needed was to review epidemiological evidence of the threat posed by the epidemic to fisherfolk and fishery-based livelihoods. Estimates of seroprevalence and numbers likely to be infected are critical to informing policy and planning responses to the AIDS epidemic [9]. Population-size estimates alert policy-makers to the existence and magnitude of a sub-population that may be at risk to HIV. They can guide the level and types of funding allocation towards appropriate prevention, treatment and mitigation measures, and monitoring of the effectiveness of interventions designed to reduce infection [10].

Sex workers, injecting drug users (IDUs), men who have sex with men (MSM), and people in prison are known to be at higher risk of infection, due to non-use of condoms, participation in or coercion into sex acts that have high viral transmission probabilities, and the re-use of injecting equipment. Others at higher risk are individuals in social and occupational groups in which economic and socio-cultural factors combine to foster behaviours that carry an enhanced risk of HIV infection and transmission. Such factors include frequent visits to sex-workers, impaired decision-making due to alcohol or drug abuse, masculine norms of behaviour that include expectation of multiple partners, non-use of condoms with at-risk partners, non-treatment of sexually transmitted infections and needle sharing among workmates [11]. With the exception of sex workers, the literature on HIV/AIDS usually identifies occupation-based groups at higher risk as being male-dominated, including long-distance truck drivers, military personnel and miners or, in the case of women and men, broader groups such as traders and migrant workers [12]. However there is no comparative analysis of the number of people with HIV in each of these groups.

The objective of this paper is to present estimates of the prevalence levels and numbers of people infected with HIV among fisherfolk and compare these estimates to those for other sub-populations considered at higher risk of HIV infection, to provide a basis for assessing the case for including fisherfolk among the groups meriting targeted interventions.

We reviewed the literature on HIV in fishermen (men involved in fish catching operations), fisherfolk (any persons involved in fishing and fish trading and processing) and people living in fishing communities (any person resident in a port, village or fish landing station where fishing is a prominent occupation). We also reviewed the literature on HIV prevalence in other occupational groups commonly stated as being at higher risk: sex workers, long-distance truck drivers, military personnel, miners and seafarers. Data for miners and seafarers were scarce and confined to one or two countries, so results are not reported here. The category of ‘migrant worker’ was too generic to be useful. For comparison we also attempted to locate, for countries where we had estimates for fisherfolk, the prevalence and group size for the (non-occupational) sub-populations known to be at highest risk; namely IDUs, MSM and people in prison. We also included estimates of seroprevalence in the general sexually active adult (age 15 to 49 years) population as a baseline for comparison.

Methods

We searched electronic library databases, including Medline and Embase. Search terms used for fishing community literature included HIV, Human Immunodeficiency Virus, AIDS, Acquired Immunodeficiency Syndrome, seroprevalance, fishing, fishery, fisheries, fisherman, fishermen, fisherfolk and fishers, with additional searches in French and Spanish. Relevant references cited in these articles were checked. The same procedure was carried out for the other groups at risk, substituting fishing-related search words with the appropriate key words. The websites of relevant organizations such as UNAIDS, WHO, FAO, UN Office on Drugs and Crime, and the International Centre for Prison Studies were used, as were keyword searches in Google and Scholar Google search engines. The CD-ROM “HIV/AIDS Surveillance Data Base”, produced by the US Census Bureau was used to obtain data on prevalence and population size for prisoners, IDUs and military personnel. Care was taken to find the most up-to-date and reliable information on the population sizes of the different groups.

The number of HIV-infected people in each sub-population was calculated by taking the number of people in the group and multiplying by an HIV prevalence estimate based on the most up-to-date seroprevalence data available. Given the paucity of data, inclusion criteria for the review could not be limited to studies with random sampling and high response rates so all published or reported surveys were included. Where available, the upper and lower HIV prevalence estimates were used to establish an average prevalence estimate. Confidence intervals on sub-population group size estimates were seldom available, so the values are taken as point estimates. Seroprevalence surveys as well as surveillance data reported in UN, WHO or government documents, journals or international conference presentations were included. HIV prevalence estimates from nationally-representative surveillance (hereafter referred to as ‘national estimates’) were preferentially used over surveillance estimates limited to a single location or region (‘regional estimates’), unless the latter were more than 3 years more up-to-date. If regional data were available for more than one region within a country, we provided an estimate using the lower and upper prevalence measures from the different regions.

The final selection of 10 countries reported here was based on the availability of seroprevalence data on fishermen, fisherfolk or fishing communities. In all the Asian country studies, the prevalence data were collected from fishermen, rather than fisherfolk more generally. In Africa and Honduras, the data are from surveys in fishing communities and are therefore assumed to apply to all adults living in communities where fishing is a major occupation. Data on HIV prevalence and group size for the other sub-populations at risk (truck drivers, IDUs, etc) were available for a wider set of countries. However as the focus of this paper is on fisherfolk, we did not extend the analysis to calculate number of HIV infections among these groups for all countries for which prevalence rates were available.

Although defining the boundaries of ‘risk group’ membership is always problematic, it is particularly so for some of the groups that are most frequently mentioned as at highest risk for HIV. For this reason we did not attempt to estimate the size of sex worker populations nor the number infected, because estimates of this group's size are often based on the numbers of women involved in brothel-based sex work which may be a minority, particularly where brothels are illegal. For non-brothel-based sex work, it can be difficult to define the boundaries between a sex worker and someone who engages in ‘transactional sex’ – the exchange of sexual services for goods or opportunities instead of or in addition to a monetary exchange. Transactional sex is a strategy adopted by some poor and vulnerable groups, usually women, needing access to food, shelter or work and other opportunities and so is not a distinct occupational or sub-population group. This ambiguity leads to highly uncertain estimates of the number of persons involved and there is often a very large within-group difference in prevalence associated with different forms of sex work [12]. We therefore confined the review to prevalence rate estimates for sex workers from HIV surveillance surveys reported by WHO and UNAIDS [13], and did not review primary literature nor did we attempt to estimate respective population sizes or numbers infected.

Among the non-occupational-based sub-populations at risk we were able to obtain prevalence rates and estimated group sizes for IDUs and prisoners, but not for MSM for the countries included. In many African and Asian societies the illegality and strong social stigma attached to homosexuality makes these estimates unavailable. Although drug use is also illegal, the social stigma is often less and it proved easier to estimate the numbers and prevalence for IDUs in some of the included countries. Thus IDUs and prisoners represent our known non-occupational sub-populations commonly assumed to have the highest HIV prevalence rates. All of the above groups are likely to overlap.

The sources of the data used in the estimates are presented in the following sub-sections.

General population

Prevalence estimates and risk population sizes are for adults (age 15–49 years) and based on UNAIDS data for 2003 [14].

Fishermen, fisherfolk and fishing communities

The prevalence estimate is from a single regional estimate for Democratic Republic of Congo (DRC) [15], Honduras [16], Indonesia [17], Myanmar [18], Thailand [19] and Uganda [20]. The prevalence estimate is from two or more regional rates for Brazil [21], Cambodia [18,22] and Kenya [23]. The Malaysian rate is a national estimate based on a source stating that 7.8% of all persons with a known occupation living with HIV or AIDS are fishermen [24]. Prevalence was then estimated by taking the number of fishermen with HIV as percentage of total numbers of fishermen. The above prevalence estimates are for fishermen only, with the exception of Brazil (fishermen and hunters), DRC [partners of fishermen visiting antenatal clinics (ANC)], Honduras (study carried out in a coastal community, with fishing as an important employment), Kenya (ANC clinic surveillance in fishing communities; and population-based serosurvey in fishing villages), and Uganda (population-based survey of lake-shore community, with high employment as fishermen). All data are from 1998 to the present. All fisherfolk population size estimates are for 2002 and are based on data from the UN Food and Agricultural Organization [25]. These population size estimates usually include only those employed in the fish-catching sector (fishers, mostly fishermen) and so, in cases when seroprevalence data are for a wider group (fisherfolk or fishing communities) our estimates of numbers infected are for fishermen only, based on the assumption that HIV prevalence rates of fishermen are similar to those reported for the fishing community as a whole.

Truck drivers

The prevalence estimates are from a national rate for Thailand [26] and Uganda [27]. Prevalence estimates are from a single regional rate for Brazil [28], Honduras [29] and Indonesia [17] and from two regional estimates for Myanmar [30] and Kenya [31,32]. Data from Thailand date back to 1992, data from Myanmar are from 1993, Kenyan data are from 1993–1997, data from Brazil are from 1995/1996 and Honduran data are from 1998. Indonesian data are from 2000.

The number of Kenyan truck drivers is derived from the number of trucks and lorries in Kenya in 2003 [33]. The Ugandan truck driver population size was extrapolated from the total Ugandan population, using the same proportion of Kenyan truck drivers to the total Kenyan population. For other countries (Brazil, Honduras, Indonesia, Myanmar, Thailand) the number of truck drivers was estimated by taking 5% of the total persons employed in the Major Occupational Division 7 [transport, storage and communication (TSC)] of the ‘International Standard Industrial Classification of all Economic Activities’, using LABORSTA Internet, an online database for labour statistics, maintained by the International Labour Organisation: www.ilo.org (accessed May 2005). The 5% figure is a conservative proportion, derived from data in Indonesia which was the only country we found to have figures for both the number of trucks and the number of persons employed in the TSC sector.

Military

The prevalence estimates are from national rates for Brazil [34], Honduras [35], Indonesia [36], Myanmar [37] and Thailand [34]. The Ugandan prevalence estimate is from a single regional rate [38]. The Cambodian prevalence estimate is from rates from 11 provinces [39]. Prevalence for Brazil, Indonesia, Thailand and Uganda are based on rates for military personnel, and for Honduras and Myanmar rates are for military recruits. Data from Indonesia are from 1992–1993, Ugandan data from 1995–1996 and Cambodian and Honduran data are from 1996 or 1997. Data from other countries are more recent. All at-risk population estimates are from the International Institute of Strategic Studies [40].

Prisoners

The prevalence estimate is from a national rate for Brazil [41], Indonesia [42], Malaysia [43], Myanmar [44] and Uganda [45]. The prevalence estimate is from a single regional rate for Cambodia [46], Honduras [47] and Thailand [48]. The prevalence data from Myanmar are from 1991 and Cambodian data are from 1993. All other studies are from 2001 or more recent. All risk population size estimates are from Dolan et al. [49], with the exception of Indonesia [50].

Injecting drug users

The prevalence estimate is from a national rate for Brazil [50], Indonesia [42], Kenya [51], Myanmar and Malaysia [52], and Thailand [52,53]. Information from Myanmar and Cambodia are from 1993. All other studies are from 2001 or more recent.

At-risk population sizes are derived from studies in Brazil [52], Indonesia [42], Thailand [50], Malaysia [54], Myanmar [55], and Kenya [56]. The number of injecting drug users in Kenya is an estimate of opiate users. Not all opiate users inject, so this is likely to be an overestimate.

Sex workers

UNAIDS/WHO sentinel surveillance site data were used to estimate median prevalence rates [13], except for Uganda where these data on sex-workers were not available. Data from Uganda are for sex workers in Kampala, based on the preliminary findings of the Uganda HIV/AIDS Sero-Behavourial Survey [57].

Results

From the ten low or middle-income countries in Africa, Asia and Latin America for which data were available, the estimated number of persons infected in each group and reported ranges of seroprevalence for these groups are shown in Table 1. In all cases except Brazil, HIV prevalence rates in fishermen or fishing communities is four to 14 times higher than the national average prevalence rate for adults aged 15 to 49 years. Again with the exception of Brazil (the sample for which includes hunters in the Amazon basin as well as fishermen), HIV prevalence rates among fisherfolk are higher than for both truck drivers and the military in all countries where comparative data are available and are higher than or equal to (within 1%) the seroprevalence rate for prisoners in four of the eight countries for which data were available, and those for sex workers in two of the ten countries.

Table 1
Table 1:
Estimated number of persons infected with HIV by group at risk in the ten low- or middle-income countries for which HIV prevalence data was available for fisherfolkb.

In the African countries of DRC, Kenya and Uganda the numbers of fishermen likely to be infected with HIV are higher than in any of the other groups considered. This is also the case in the Asian countries of Cambodia, Indonesia and Myanmar (although missing data reduce the value of the Cambodia comparison) and in Thailand it was surpassed only by the number of HIV-infected prisoners. In Honduras the number of people infected with HIV was also the highest among all the groups at risk; however, in Brazil, by contrast the prevalence rates among fishermen (combined with hunters) were low, so although Brazil has a large fishing population, the estimated number of infections among them were much lower than for other sub-populations. In summary, the epidemiological data support the many observations of behavioural and social factors that are thought to place many fisherfolk at high risk to HIV [2].

Discussion

Both HIV prevalences and absolute numbers of infected people were in many cases estimated to be higher among fishermen or members of fishing communities than in other sub-populations that are more usually considered to be ‘populations at higher risk’ in the HIV, public health and policy literatures (with the possible exception of sex workers for whom numbers could not be estimated; see methods section above).

Our estimates assume that prevalence survey data can be generalized to the larger fishing populations, which may be diverse in terms of mobility and socio-economic status. Prevalence figures for fishermen and fishing communities presented in the table are mostly based on regional estimates. Some study samples were not randomly selected or were small and so could be biased or unreliable. The estimates are a mixture of those pertaining to fishermen only, and those applying to people in fishing communities (not all of whom may be fisherfolk; that is, involved in fishing-related work). Study dates are also relevant as different countries are at different stages of their epidemics. Nevertheless the estimates are a cause for concern.

The results presented here have implications for the way in which the number of HIV infections is calculated. In countries with large but non-generalized epidemics, including some of the most populous Asian and Latin American countries, national HIV infection statistics submitted to UNAIDS are compiled by identifying prevalence in sub-populations at risk, estimating the sizes of these sub-populations (as we have done in this paper) and summing the resulting estimates to obtain the number of infected persons nationally [29,58]. The accuracy of estimated numbers infected with HIV nationally depends on identifying all relevant sub-populations at higher risk and including them in the calculations. Excluding estimates for fisherfolk may lead to underestimation of the size of the epidemic in countries such as Cambodia, Indonesia and Thailand, all of which have large fishing populations that have been shown to have high HIV prevalences. Indonesia along with China, India, Vietnam and Bangladesh are the five countries with the highest number of fisherfolk in the world; they account for over two-thirds of the world's 36 million fishermen (and presumably a similar proportion of the world's 200 million fisherfolk) between them. The HIV prevalence among fishermen and in fishing communities in the latter four countries are not known, although fishermen in Vietnam have been identified as being at high risk [59], and fishing communities in the Indian state of Gujarat have been identified as being at very high risk and have recently been targeted with HIV prevention efforts [60].

For Asia and Latin America, it is argued that a generalized epidemic might be averted by targeting prevention and treatment campaigns at known groups at higher risk such as sex workers and IDUs [61]. There is a danger that focusing too narrowly on these groups neglects larger sub-populations at high risk, such as fisherfolk. Such mobile populations may be a conduit for the spread of the HIV to the general population. We argue that if a generalized epidemic is to be averted in these regions, then the net of prevention efforts has to be cast wider, to include groups like fisherfolk [1].

Data limitations currently hinder concerted action to address HIV in the fisheries sector, although awareness of the scale of the problem is growing [3]. Fishing communities in less developed countries are often mobile and socially marginalized and have poor access to facilities and medicines and low uptake of available health services [6]. More specifically HIV awareness and prevention campaigns have seldom been targeted at fishing communities, in contrast to other susceptible groups of people.

Continuing policy neglect of HIV in the fisheries sector is likely to have severe health and development consequences across Africa and Asia, hindering progress towards the Millennium Development Goals. The sector sustains the livelihoods of over 200 million people and is an important contributor to gross domestic product, employment, nutrition and food security, and poverty reduction in many low and middle-income countries [3]. Necessary responses include implementing effective, cost-effective and locally appropriate methods of prevention and treatment [62,63]. Epidemiological and ethnographic research on HIV transmission within fishing communities, and between them and other populations, is also urgently needed.

Acknowledgements

This study was funded by the World Fish Center, Africa Programme. E.H.A. was supported by a secondment to the Sustainable Fisheries Livelihoods Programme, which is funded by the UK Department for International Development and implemented by the UN Food and Agriculture Organisation in partnership with 25 West African countries.

References

1. Allison EH, Seeley JA. Another group at high risk for HIV. Science 2004; 305:1104.
2. Allison EH, Seeley JA. HIV and AIDS among fisherfolk: a threat to ‘responsible fisheries’? Fish & Fisheries 2004; 5:215–234.
3. Food and Agriculture Organisation of the United Nations (FAO). Impact of HIV and AIDS on fishing communities. Rome: Sustainable Fisheries Livelihoods Programme, UN Food and Agriculture Organisation; 2005.
4. Pickering H, Okongo M, Ojwiya A, Yirrell D, Whitworth J. 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.
5. Appleton J. ‘At my age I should be sitting under that tree’: the impact of AIDS on Tanzanian lakeshore communities. Gender Dev 2000; 8:19–27.
6. Seeley JA, Allison EH. HIV/AIDS in Fishing Communities: Challenges to delivering antiretroviral therapy to vulnerable groups. AIDS Care 2005; 17:688–697.
7. International Labour Office (ILO). Safety and health in the fishing industry. Report for discussion at the Tripartite Meeting on Safety and Health in the Fishing Industry. Geneva: International Labour Office; 1999.
8. Food and Agriculture Organisation (FAO)/ILO/International Maritime Organisation. Code of safety for fishermen and fishing vessels. Geneva: FAO/ILO/IMO, Geneva; 2005. (Sections 4.2.5 and 4.12)
9. Barnett T. Editorial: the cost of an HIV/AIDS epidemic. Trop Med Int Health 2004; 9:315–317.
10. Joint United Nations Programme on HIV/AIDS (UNAIDS). Estimating the size of populations at risk for HIV. Geneva: UNAIDS; 2003.
11. Poundstone KE, Strathdee SA, Celentano DD. The social epidemiology of Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome. Epidemiol Rev 2004; 26:22–35.
12. Nagot N, Ouangre A, Ouedraogo A, Cartoux M, Huygens P, Defer MC, et al. Spectrum of commercial sex activity in Burkina Faso: classification model and risk of exposure to HIV. J Acquired Immune Defic Syndr 2002; 29:517–521.
13. UNAIDS/WHO. UNAIDS/WHO Global HIV/AIDS Online Database. Geneva: World Health Organization 2005. http://www.who.int/globalatlas/predefinedReports/default.asp [Accessed August 2005].
14. UNAIDS. UNAIDS report on the global AIDS epidemic. Geneva: UNAIDS; 2004.
15. Kambale L. Etude de la séroprévalence de l'infection par VIH dans la zone de santé de Kalemie au Nord Katanga. Kivu: Save the Children/PNLS; December 2001. http://www.kongo-kinshasa.de/dokumente/ngo/sc_vih.pdf [Accessed July 2005].
16. Sierra MA, Paredes C, Pinel R, Fernández J, Mendoza S, Meza R, et al. Estudio Seroepidemiológico de Sífilis, Hepatitis B y VIH En Población Garífuna de El Triunfo de la Cruz, Bajamar, Sambo Creek y Corozal. Honduras: Secretaria de Salud Subscretaria de Riesgos Poblacionales Departamento de Control y Prevencion de Enfermedades de Transmision Sexual, Sida y Tuberculosis; 1999. http://www.pasca.org/docs/informe_garifunas.pdf [Accessed May 2005].
17. Indonesian Centre of Disease Control and Environmental Health, 2001. In: Hugo G, editor. Population mobility and HIV/AIDS in Indonesia. New York: UNDP South East Asia HIV and Development Programme; 2001. http://www.hiv-development.org/text/publications/hugo_Chapter2.doc [Accessed May 2005].
18. Entz AT, Ruffolo VP, Chinveschakitvanich V, Soskolne V, van Griensven GJ. HIV-1 prevalence, HIV-1 subtypes and risk factors among fishermen in the Gulf of Thailand and the Andaman Sea. AIDS 2000; 14:1027–1034.
19. AIDS Cluster, Bureau of AIDS, TB and STIs Department of Diseases Control, Ministry of Public Health, Thailand. http://www.aidsthai.org/aidsenglish/situation_03.html [Accessed May 2005].
20. Kipp W, Kabwa P, Verbeck A, Fischer P, Eggert P, Buttner DW. Prevalence and risk factors of HIV-1 infection in three parishes in western Uganda. Trop Med Parasitol 1995; 46:141–146.
21. Cassano C, de Medeiros Frias LA, Valente JG. Classificação por ocupação dos casos de AIDS no Brasil – 1995 (Occupational classification of AIDS cases in Brazil, 1995). Cad Saude 2000; 16(suppl. 1):53–64.
22. Samnang P, Leng HB, Kim A, Canchola A, Moss A, Mandel JS, Page-Shafer K. HIV prevalence and risk factors among fishermen in Sihanouk Ville, Cambodia. Int J STD AIDS 2004; 15:479–483.
23. UNAIDS/WHO Epidemiological fact sheets on HIV/AIDS and sexually transmitted infections, Kenya, 2002 update Geneva: UNAIDS/UNICEF/PAHO/WHO; 2002. http://www.who.int/emc-hiv/fact_sheets/pdfs/kenya_en.pdf [Accessed May 2005].
24. Huang M. HIV/AIDS among fishers: vulnerability of their partners. Penang: The World Fish Centre; 2002.
25. FAO Fisheries Information, Data and Statistics Unit. Rome: FAO; http://www.fao.org/fi/struct/fidi.asp#EMPLOY [Accessed December 2004].
26. Podhisita C, Wawer MJ, Pramualratana A, Kanungsukkasem U, McNamara R. Multiple sexual partners and condom use among long-distance truck drivers in Thailand. AIDS Educ Prev 1996; 8:490–498.
27. Congressional Black Caucus Foundation Inc. Health. Vital Statistics. http://www.cbcfhealth.org/content/contentID/1805 [Accessed July 2005].
28. Lacerda R, Gravato N, McFarland W, Rutherford G, Iskrant K, Stall R, et al. Truck drivers in Brazil: prevalence of HIV and other sexually transmitted diseases, risk behaviour and potential for spread of infection. AIDS 1997; 11(suppl. 1):S15–S19.
29. Ramón JS, Alverenga M, Walker N, Garcia-Calleja JM, Zacarias F. Estimating HIV/AIDS prevalence in countries with low-level and concentrated epidemics: the example of Honduras. AIDS 2002; 16(suppl. 3):S18–S22.
30. Htoon MT, Lwin HH, San KO, Zan E, Thwe M. HIV/AIDS in Myanmar. AIDS 1994; 8(suppl. 2):S105–S109.
31. Baeten JM, Chohan BH, Lavreys L, Rakwar J, Ashley R, Richardson B, et al. Correlates of human herpesvirus 8 seropositivity among heterosexual men in Kenya. AIDS 2002; 16:2073–2078.
32. Rakwar J, Lvreys L, Thompson ML, Jackson D, Bwayo J, Hassanali S, et al. Cofactors for the acquisition of HIV-1 among heterosexual men: prospective cohort study of trucking company workers in Kenya. AIDS 1999; 13:607–614.
33. Alila PO, Meleckidzedeck K, Odhiambo W, Pedersen PO. Development of African freight transport – the case of Kenya. Working Paper 2005/2006. Copenhagen: DIIS; 2005. http://www.diis.dk/graphics/Publications/WP2005/pop_Development_of_African_Freight_Transport.pdf [Accessed May 2005].
34. UNAIDS. Engaging uniformed services in the fight against HIV/AIDS. Geneva: UNAIDS. http://uniformservices.unaids.org/country.asp?region=America%20and%20Caribbean&country=Brazil&menu=Country%20overview [Accessed May 2005].
35. UNAIDS/WHO. Epidemiological fact sheets on HIV/AIDS and sexually transmitted infections, 2002 update, Honduras. Geneva: UNAIDS/UNICEF/PAHO/WHO; 2002. http://www.who.int/GlobalAtlas/PDFFactory/HIV/EFS_PDFs/EFS2004_HN.pdf [Accessed May 2005].
36. Soeprapto W, Ertono S, Hudoyo H, Mascola J, Porter K, Gunawan S, et al. HIV and peacekeeping operations in Cambodia. Lancet 1995; 346:1304–1305.
37. WHO. Myanmar HIV/AIDS in Asia and the Pacific region. Geneva:WHO; 2001. http://www.who.int/hiv/strategic/en/wpraids2001.pdf [Accessed May 2005].
38. Mugyenyi P, Hom D, Loughlin A, Johnson JL, MaGrath JL, George K, et al. HIV-1 seroprevalence, incidence and risk behaviour in the Ugandan military. Presented at the XI International Conference on AIDS, Vancouver, July, 1996 [poster Mo.C.1483].
39. Ministry of Health (MOH). Cambodia (sentinel surveillance 1996). In: HIV/AIDS in Asia and the Pacific Region. Geneva: WHO; 2001. http://www.wpro.who.int/pdf/sti/aids2001/complete.pdf [Accessed May 2005].
40. International Institute for Strategic Studies. The military balance 2001–2002. Oxford: Oxford University Press; 2001.
41. Tourinho DR, Dourado I. Safe sex in the prison system in Salvador, Brazil: Is it possible? Paper presented at the XIV International Conference for AIDS, Barcelona, Spain, July 2002 [abstract TuPeD4942].
42. Ministry of Health (MOH). National Estimates process. In: Estimasi Nasional Infeksi HIV Pada Orang Dewasa Indonesia 2002. Jakarta, Indonesia: Departemen Kesehatan Republik Indonesia. Direktorat Jenderal Pemberantasan Penyakit Menular dan Penyehatan Linkungan; 2002. http://www.fhi.org/NR/rdonlyres/ezykqdtywnqpv44vkacujdl5c32a6mhzpupej5br2igcsdzektmjwiuwpv63wvm32uzoc5ixifvi6h/Reportestimation.pdf [Accessed May 2005].
43. UNODC Regional Centre for East Asia and the Pacific. Monitoring the AIDS Pandemic (MAP): Injecting drug use and HIV/AIDS in prison: presentation to UN Task Force, UNODC Regional Centre for East Asia and the Pacific, 2001. In: Dolan K, Kite B, Black E, Lowe J, Agaliotis M, MacDonald M, et al., editors. Review of injection drug users and HIV infection in prisons in developing and transitional countries. Sydney/London: UN Reference Group on HIV/AIDS Prevention and Care among IDUs in Developing and Transitional Countries; 2004.
44. Htoon MT. Myanmar AIDS prevention and control programme – quarterly report, Oct – Dec. 1991. Geneva: WHO; 1992. In: Dolan K, Kite B, Black E, Lowe J, Agaliotis M, MacDonald M, et al. editors. Review of injection drug users and HIV infection in prisons in developing and transitional countries. Sydney/London: UN Reference Group on HIV/AIDS Prevention and Care among IDUs in Developing and Transitional Countries; 2004.
45. International Centre for Prison Studies (ICPS) and Kings College London. Data provided by National Prison Administration to ICPS on http://www.kcl.ac.uk/depsta/rel/icps/home.html [Accessed August 2003]. In: Dolan K, Kite B, Black E, Lowe J, Agaliotis M, MacDonald M, et al., editors. Review of injection drug users and HIV infection in prisons in developing and transitional countries. Sydney/London: UN Reference Group on HIV/AIDS Prevention and Care among IDUs in Developing and Transitional Countries; 2004.
46. Lay KS. The HIV epidemic in Cambodia. TB & HIV 1994; 2:15.
47. Sierra MA, Paredes C, Soto R, Fernandez J, Hernandez R, Pinel R, et al. A seroepidemiological study of syphilis, hepatitis B and Human Immunodeficiency Virus among male prisoners of three cities in Honduras.XIV International AIDS Conference, Barcelona, Spain, July 2002 [abstract MoPeC3524].
48. Thaisri H, Lerwitworapong J, Vongsheree S, Sawanpanyalert P, Chadbanchachai C, Rojanawiwat A, et al. HIV infection and risk factors among Bangkok prisoners, Thailand: a prospective cohort study. BMC Infect Dis 2003; 3:25–32.
49. Dolan K, Kite B, Black E, Lowe J, Agaliotis M, MacDonald M, et al. Review of injection drug users and HIV infection in prisons in developing and transitional countries. Sydney/London: UN Reference Group on HIV/AIDS Prevention and Care among IDUs in Developing and Transitional Countries; 2004.
50. Aceijas C, Stimson GV, Hickman M, Rhodes T. Global overview of injecting drug use and HIV infection among injecting drug users. AIDS 2004; 18:2295–2303.
51. United Nations Office on Drugs and Crime. Vienna: UNODC; http://www.unodc.org/kenya/press_release_2004-07-01_1.html [Accessed May 2005].
52. UNAIDS. Progress report on the global response to the HIV/AIDS epidemic. Geneva: UNAIDS; 2003. http://www.unaids.org/ungass/en/global/ungass00_en.html [Accessed May 2005].
53. AIDS Cluster, Bureau of AIDS, TB and STIs Department of Diseases Control. Bangkok, Thailand: Ministry of Public Health; http://www.aidsthai.org/aidsenglish/situation_03.html; [Accessed May 2005].
54. WHO. Consensus report on STIs, HIV and AIDS epidemiology: Malaysia 1999. WHO, Regional Office for the West Pacific; 1999. http://www.hawaii.edu/hivandaids/Consensus_Report_on_STI,_HIV_and_AIDS_Epidemiology,_Malaysia,_April_1999.doc [Accessed May 2005].
55. United Nations Office on Drugs and Crime. Vienna: UNODC; (http://www.unodc.org/unodc/drug_demand_hiv_aids_extend.html [Accessed May 2005].
56. United Nations Office on Drugs and Crime. World Drug Report, 2004. Volume 2: statistics. Vienna: UNODC. http://www.unodc.org/pdf/WDR_2004/volume_2.pdf [Accessed May 2005].
57. Nyanzi, P. Half Kampala sex workers have HIV (report on preliminary results of the ‘Uganda HIV/AIDS Sero-behavioural Survey’, UHSHS, Kampala). The Monitor 3 May 2005.
58. Srinivasa Rao ASR. Can we obtain realistic HIV/AIDS estimates for India? J Biosci 2003; 28:367–369.
59. Trang NQ. Seafarers and HIV vulnerability: a study of fishermen and passenger boat crewmembers in Haiphong. AusAID, World Vision and Haiphong Department of Health, Vietnam, 2002: 52 pp. http://www.undp.org.vn/projects/vie98006/RSex.html [Accessed October 2003].
60. UK Department for International Development. Promoting sexual health to high-risk groups in Gujarat, UK Department for International Development, Case Studies. London: UK Department for International Development; 2005; http://www.dfid.gov.uk/casestudies/files/asia/india-condom.asp [Accessed August 2005].
61. Cohen J. Two hard-hit countries offer rare success stories. Science 2003; 301:1658.
62. Creese A, Floyd K, Alban A, Guiness L. Cost-effectiveness of HIV/AIDS interventions in Africa: a systematic review of the evidence. Lancet 2002; 359:1635–1642.
63. Jha P, Nagelkerke JD, Ngugi EN, Prasada Rao JV, Willbond B, Moses S, et al. Public health. Reducing HIV transmission in developing countries. Science 2001; 292:224–225.
Keywords:

fishing communities; fishermen; military; truck drivers; prisoners; injecting drug users; sex workers

© 2005 Lippincott Williams & Wilkins, Inc.