Sampling studies to estimate the HIV prevalence rate in female commercial sex workers

REVIEW ARTICLE

Sampling studies to estimate the HIV prevalence rate in female commercial sex workers

Ana Roberta Pati Pascom^I; Célia Landmann Szwarcwald^II; Aristides Barbosa Júnior^I

^IMonitoring and Evaluation Advisory, Brazilian Departament of STD, AIDS and Viral Hepatitis; Ministério da Saúde, Brazil

^IIHealth Information Laboratory, Health Science and Technology Information and Communication, Fundação Oswaldo Cruz, Brazil

^{Correspondence to}

ABSTRACT

INTRODUCTION: We investigated sampling methods being used to estimate the HIV prevalence rate among female commercial sex workers.

METHODS: The studies were classified according to the adequacy or not of the sample size to estimate HIV prevalence rate and according to the sampling method (probabilistic or convenience).

RESULTS: We identified 75 studies that estimated the HIV prevalence rate among female sex workers. Most of the studies employed convenience samples. The sample size was not adequate to estimate HIV prevalence rate in 35 studies.

DISCUSSION: The use of convenience sample limits statistical inference for the whole group. It was observed that there was an increase in the number of published studies since 2005, as well as in the number of studies that used probabilistic samples. This represents a large advance in the monitoring of risk behavior practices and HIV prevalence rate in this group.

Keywords: HIV, AIDS, commercial sex workers, sampling.

INTRODUCTION

The several measures being adopted to prevent HIV dissemination, both at national and international levels, are based on the natural history of the infection, the experience of AIDS-related health programs, and the results of simulations and mathematical models that seek to translate the dynamics of the disease transmission.¹

From the epidemiological point of view, it is known that there are population subgroups presenting a higher risk of HIV-infection, such as men who have sex with other men (MSM), injection drug users (IDU), and female commercial sex workers (SW), who are the most affected and have been infected on the early days of the epidemics. It is also known that sexually-transmitted diseases (STD) act as cofactors to promote disease transmission; and that sexual practices, such as multiple sex partners and irregular condom use are important determinants.²

From mathematical models' point of view, sexual relations patterns among the population subgroups constitute other important factor in the dissemination of HIV, as small alterations in the rate of contacts between the low-risk segment and the high-risk one can significantly change the dissemination of the epidemics.³

The AIDS epidemics in Brazil took place during the first years of the 80's. Throughout this period of more than 20 years, it has been shown to be a concentrated epidemics,⁴ maintaining a prevalence rate of HIV infection in the general population lower than 1% and high rates in the population subgroups that are more vulnerable to HIV infection, such as SW.⁶

The SW group size is estimated at 1% of the Brazilian female population, aged 15 to 49 years, corresponding to more than half a million women.⁷ The prevalence rate for this population group according to some studies carried out in the country, has been estimated to be always higher than that of the general female population. In the study carried out in the city of Santos, state of São Paulo, Brazil, in 1997, the prevalence rate was of 8%.⁸ In another study carried out between 2000 and 2001, with 2,712 female sex workers in some cities of Brazil, the prevalence rate was estimated at 6.1%.⁶ These studies indicate a prevalence that is approximately 15fold higher among the commercial sex workers when compared to the Brazilian female population as a whole.⁵ It is noteworthy to mention, however, that convenience samples have been used and, therefore, these results must be interpreted considering such limitation.

From the year 2005 on, the United Nations Joint Program on HIV/AIDS (UNAIDS) has emphasized the need to monitor indicators in the groups at higher risk of HIVinfection in countries with concentrated epidemics. In Brazil, current efforts are being made to carry out several studies that allow the estimation of the prevalence of HIV and other STDs and characterize the risk practices and behavior in the groups at higher risk of HIV infection, particularly SW.

The higher risk among the SW suggested by previous studies requires studies with a probabilistic sampling to attain adequate monitoring of the risk practices related to HIV-infection. Currently, obtaining representative samples of population subgroups of hard-to-reach individuals, such as commercial sex workers, is one of the biggest challenges for epidemiologic surveillance.⁹ Traditional sampling methods are inadequate to generate representative samples, considering that, to estimate solid enough parameters, it is necessary to select very large samples, which are rendered impossible due to operational and cost difficulties.¹⁰

Another challenge in carrying out home-based studies with SW is the fact that this profession is surrounded by a great deal of stigma, which leads many women to not declare themselves as such or to hide their profession from family members and friends. Additionally, many of these women do not live in permanent private homes of their own, very often residing at their workplaces, which are not included in the traditional researches.

The present study carried out a literature review of scientific articles to investigate the sampling methodologies that are being used in studies estimating the prevalence rate of HIV among SW.

METHODOLOGY

A literature review was carried out through a systematic search of scientific articles involving SW and the estimate of the HIV prevalence rate. The search for articles was conducted between October and November 2008, and was attained through the MEDLINE and PUBMED databases.

This review consisted of cross-sectional studies that: included the population group of SW; estimated the HIV prevalence rate through serological tests; and that had been published in English, Portuguese or Spanish, from 2000 to 2008. We excluded review articles, clinical trials or longitudinal studies, as well as studies that did not include the estimate of the HIV prevalence rate through serological tests.

The multiple combinations of the following keywords were used during the systematic search: "HIV"; "prevalence"; "AIDS"; "female"; "women"; "prostitution"; "CSW"; "commercial sex workers"; "sex workers"; and "SW".

The following data were collected for the systematization of the information obtained from the selected articles: year of publication; country where the study was carried out; type of sampling; whether the sampling design was considered in data analysis; sample size; and the HIV prevalence rate.

The studies were classified according to the adequacy or not of the sample size used to estimate the HIV prevalence rate. For that purpose, the estimate error for simple random samples was calculated using the following formula:

Where p = HIV prevalence rate; q = 1 -p; n = sample size; and z = 1.96, which is the value established for 95% confidence. When the error was > p/2 (half the HIV prevalence rate), the sample size was considered to be inadequate.

We also analyzed the type of sampling technique used in the study, classified as probabilistic method or convenience sampling method. Convenience samples are those in which the population elements are chosen according to their availability to participate in the study or the researcher's interest.¹³ Among the studies with convenience samples, we specifically identified the "snowball sampling". In this type of sampling, the selection of the individuals is carried out by the participants themselves, through the indication of acquaintances until the established sample size is achieved.¹⁴

In probabilistic samples, each element of the population is associated with a known selection probability and is different from zero.^13,15 Among the studies with probabilistic sampling are the conglomerate sampling and the respondent driven sampling (RDS). The conglomerate sampling is a probabilistic sampling employed very often in population surveys, in which the sampling unit is the conglomerate.^13,15 Proposed by Heckathorn¹⁶ in 1997, the RDS is a variant of chain-based sampling and, as such, assumes that hard-to-reach members of a population are better at recruiting their peers than other individuals, such as healthcare agents or researchers. Moreover, it introduces a mathematical model that allows the weighing of the sample to compensate the bias generated by the non-random selection of the seed-individuals and overrepresentation of some subgroups in the studied population.

The studies were classified regarding their quality, according to the following criteria: 1) only the sample size was adequate; 2) the study used a probabilistic sampling method; 3) the sample size was adequate and the study used a probabilistic sampling method; and 4) the sample size was adequate, the study used a probabilistic sampling method and considered the sampling design at the analysis of the study.

RESULTS

Initially, 1,197 scientific indexed articles were identified during the search at the PUBMED database, using the aforementioned keywords, of which 921 were excluded as they did not meet the established eligibility criteria. Of the remaining 276 articles, 201 were excluded due to duplicity. Thus, 75 articles were included in this review.

Table 1 presents information on the 75 articles included in the study, such as: authorship; year of publication; country where the study was carried out; sampling type; whether the sampling design was considered in data analysis; sample size and HIV prevalence rate.

Almost 50% of the selected studies (48.3%) were published after 2006, and around 25% of them were published between 2000 and 2002 (Table 2).

Although the studies were published in 31 different journals, 49.3% of them were published in four journals: Sexually Transmitted Diseases; Sexually Transmitted Infections; AIDS; and International Journal of STD & AIDS.

Regarding the country where the study was carried out, almost half of the studies were carried out in only eight countries. Most of them were carried out in China (10) and around 7% in India (5) and Vietnam (5), and 5.3% in Spain. Three studies (4%) were carried out in each of the following countries: Indonesia, Italy, Mexico and Kenya.

Considering the region where the study was carried out, 42.7% of them were carried out in the Eastern, Southern and Southeastern Asia; 26.7% in the Sub-Saharan Africa; 10.7% in Latin America; and 2.7% in Eastern Europe and Central Asia (Table 2).

Table 3 shows the results related to the sampling design and the adequacy of the sample size. A total of 84% (63) of the selected studies used convenience samples, and 8% (6) employed the snowball sampling method. It was not possible to obtain information on the type of sampling used in around 5% of the studies, as the authors had no access to the complete study text. Of eight studies that used probabilistic sampling, four used cluster sampling and three used RDS. Six studies with probabilistic sampling (75%) were carried out after 2006 and, among them, the three that used RDS. The studies that used RDS were carried out in Estonia, India and Vietnam. Two of the four studies that used cluster sampling were carried out in Vietnam.

Of the eight studies with probabilistic sampling, six had the sampling design considered at the analysis. One used a stratified sampling with proportional allocation and random selection in the strata;two used RDS and performed the analysis using the software program specific for the method (RDSAT^®); and three used cluster sampling and considered the design effect at the analysis.

It was verified that the sample size was adequate for the estimation of the HIV prevalence rate in 53.3% of the studies (Table 3). Among the 35 studies that had an inadequate sample size for the estimation of HIV prevalence rate according to the criterion used in the present study, the prevalence rate was estimated at zero (0) in 16 of them.

The classification of the studies according to the quality criterion is shown in Table 4. Almost 50% of the studies (36) did not meet any of the adopted quality criteria. In 30 studies (40.5%), only the sample size was adequate, without using the probabilistic sampling method. Three studies, published from 2005 to 2008, used probabilistic methods, but the sample size was not adequate and the study design was not considered at the analysis. Only four of the analyzed studies had an adequate sample size for the estimation of the HIV prevalence rate, used a probabilistic method of sampling and considered the sampling design of the study at the analysis.

DISCUSSION

The present study used the aforementioned keywords to identify 75 cross-sectional studies with female commercial sex workers that estimated the HIV prevalence rate. The studies supply information on 61,075 female SW and were carried out in 35 different countries, of which 10 were located in Asia. Many of the studies were published after 2006 and were concentrated in four scientific journals.

The higher risk among the female SW was observed in many of the countries where the studies reviewed here were carried out. Luchters et al,¹⁷ in their study carried out in Kenya, emphasized that, in spite of the decrease in the HIV prevalence rate observed in the female population, there was no evidence that these changes were occurring among the higher-risk populations, such as the SW. The findings of a study conducted in China equally demonstrated a higher risk among the SW, especially related to the lack of condom use and the low level of education.¹⁸ Considering the importance of this population for the control of the HIV/AIDS epidemics, in a study carried out in New Guinea, the authors pointed out that the development of specific interventions for this population subgroup is a cost-effective strategy for the control of HIV dissemination.¹⁹

This review shows that most of the studies that involved female SW used sampling techniques with non-probabilistic selection. When compared to the probabilistic samples, the convenience samples can generally be implemented more easily, faster and with fewer resources.²⁰ However, any inference to the target-population is limited and difficult to interpret, as the study sample might not be representative of the population as a whole.

In general, although most of the analyzed studies used convenience samples, a mapping of the prostitution locations was performed before the start of the study and the SW were recruited at those locations. Although this ethnographic component might have contributed to the representativeness of the population group, the probabilities of selection remain unknown, which prevents any statistical estimate or inference.^18,21 Additionally, the SW that work in locations that were not mapped in the study, were excluded from it.²²

Snowball sampling was used in 8% of the studies. In spite of its indisputable practical feasibility, several aspects prevent the statistical analysis of the data. First, as there is no maximum number of individuals that each participant can invite to the study, the estimates are biased by the individuals who belong to a larger social network,^16,23 with the final sample being strongly influenced by the initial participants.⁹ Secondly, there is a structure of dependence between the observations, which is not considered at the analysis. As discussed by Erickson,²⁴ the individuals tend to recruit people who are similar to them, an effect known as homophily. Moreover, the lack of representativeness of the sample can also be observed.²⁵

From 2005 on, there is an increase in the number of articles and studies with probabilistic sampling. This increase is probably associated with the new set of indicators, proposed in 2005, to follow the Declaration of Commitment on HIV/AIDS, established during the 26^th United Nations General Assembly Special Session - UNGASS.²⁶ In this new version, in contrast to those proposed in 2002, two distinct sets of indicators were proposed, according to the type of epidemics of the country: concentrated or generalized. For countries with epidemics classified as concentrated, the indicators aimed at the follow-up of populations at higherrisk, determined by the countries themselves, according to the characteristics of their epidemics.²⁷

Additionally, the development and the dissemination of the use of specific and probabilistic sampling methods for the study of populations that are hard to reach brought new possibilities and stimuli for researchers interested in the study of groups at higher-risk for infection HIV. Three studies that utilized probabilistic sampling methods, by using RDS, were the result of this process.^28-30 In Vietnam, this method showed to be efficient to recruit different types of SW.²⁸

It is worth mentioning, however, that probabilistic sampling methods also present important limitations. In cases of conglomerate sampling, it is difficult to have a complete list of all prostitution locations and the selection probabilities are, in general, unknown, and approximations are considered at the data analysis.^21,31-33 As for the RDS technique, as the method is still being developed, data analysis is yet quite limited, not allowing multivariate analyses, which are essential for the study of the factors associated with HIV infection.^28,34-36

Of the 75 articles analyzed in the present study, 35 presented an insufficient sample size to estimate the HIV prevalence rate with a simple random sample, which is the one that provides the lowest error among the sampling methods.¹³ In 16 articles, the prevalence rate among female SW was of 0%, which might indicate that the sample size was not large enough to detect cases of HIV infection. Nevertheless, only three of the studies discussed the possibility of the result being related to the sample size.^33,37,38

As for the quality assessment, most of the selected studies did not meet the quality criteria that would be adequate to estimate the HIV prevalence rate among the SW. In spite of the improvement in study quality in the two analyzed periods, only four studies^21,30-32 met the established criteria, i.e., having an adequate sample size, using probabilistic sampling method and considering the sampling design at data analysis.

It is also important to mention that not considering the sampling design at the analysis can lead to important errors in the estimation of parameters of interest. By ignoring the sampling design, the traditional statistical analysis, considering the assumed simple random sampling, can result in inaccuracies regarding the mean estimates, as well as for the respective variances, compromising the results, the hypothesis tests and the conclusions of the study.³⁹ In the specific case of RDS, Goel and Salganick⁴⁰ suggest design effects > 4, resulting from homophily between peers, meaning that the structure of dependence between the observations needs to be considered at data analysis.

The present literature review did not identify any Brazilian study. A further investigation at the Scielo database (www.scielo.br) disclosed three studies carried out between 2000 and 2008 in the country: one in Santa Catarina⁴¹ and two in Amazonas.^42,43 All studies used convenience samples and, according to the criterion adopted in the present article, the sample size was inadequate for the estimation of the HIV prevalence rate in all three of them.

As for the international scenario, the present review showed that some recent studies used a probabilistic sampling technique, which represents a great advance for the monitoring of risk practices and HIV prevalence rates in this population group.

Submitted on: 03/05/2010

Approved on: 03/20/2010

We declare no conflict of interest.

• 1. Cruz-Grote D. Prevention of HIV infection in developing countries. Lancet 1996; 348:1071-4.
• 2. Potts M, Anderson R, Boily MC. Slowing the spread of human immunodeficiency virus in developing countries. Lancet 1991; 338:608-13.
• 3. Boily MC, Mâsse B. Mathematical models of disease transmission: a precious tool for the study of sexually transmitted diseases. Can J Public Health 1997; 88:255-65.
• 4. Joint United Nations Programme on HIV/AIDS (UNAIDS). 2004 Report on the global AIDS epidemic [Internet]. Genebra: Joint United Nations Programme on HIV/AIDS (UNAIDS); June 2004 [cited 2009 May 12]. Available from http://www.unaids.org/bangkok2004/GAR2004_html/GAR2004_00_en.htm
• 5. Szwarcwald CL, Barbosa Júnior A, de Souza-Júnior PR et al HIV testing during pregnancy: use of secondary data to estimate 2006 test coverage and prevalence in Brazil. Braz J Infect Dis. 2008; 12:167-72.
• 6. Ministério da Saúde - Coordenação Nacional de DST e Aids (Brasil). Avaliação da efetividade das ações de prevenção dirigidas às profissionais do sexo, em três regiões brasileiras. Coleção DST/Aids - Série Estudos, Pesquisas e Avaliação nş 7. Brasília: 2004.
• 7. Szwarcwald CL, Barbosa-Júnior A, Pascom ARP, Souza-Júnior PR. Knowledge, practices and behaviors related to HIV transmission among the Brazilian population in the 15-54 years age group, 2004. AIDS 2005 19(Suppl 4):S51-S58.
• 8. Szwarcwald CL, Bastos FI, Gravato N, Lacerda R, Chequer PN, Castilho EA. The relationship of illicit drug use to use to HIV infection among commercial sex workers in the city of Santos, São Paulo, Brazil. Int J Drug Policy 1998; 9:427-36.
• 9. Magnani R, Sabin K, Saidel T, Heckathorn D. Review of sampling hard-to-reach and hidden populations for HIV surveillance. AIDS 2005; 19:S67-72.
• 10. Frank O, Snijders T. Estimating the size of hidden populations using snowball sampling. J Off Stat 1994; 10:53-67.
• 11. Joint United Nations Programme on HIV/AIDS (UN-AIDS). 2008 Report on the global AIDS epidemic [Internet]. Genebra: Joint United Nations Programme on HIV/AIDS (UNAIDS); July 2008 [cited 2009 May 1^st]. Available from http://www.unaids.org/en/KnowledgeCentre/HIVData/GlobalReport/2008/ .
• 12. U.S. Census Bureau. International Data Base [Internet]. [cited 2009 May 1^st] Available from http://www.census.gov/cgibin/ipc/idbagg
• 13. Scheaffer RL, Medenhall III W, Ott RL. Elementary Survey Sampling. USA: Duxbury Press, 1996.
• 14. Goodman L. Snowball Sampling. Annals of Mathematical Statistics 1961; 32:148-70.
• 15. Cochran, Gemmell W. Sampling Techniques. 3rd ed. USA: John Wiley & Sons, Inc, 1977.
• 16. Heckathorn DD. Respondent-driven sampling: a new approach to the study of hidden populations. Soc Probl 1997; 44:174-99.
• 17. Luchters S, Chersich MF, Rinyiru A et al Impact of five years of peer-mediated interventions on sexual behavior and sexually transmitted infections among female sex workers in Mombasa, Kenya. BMC Public Health 2008; 8:143.
• 18. Chen XS, Yin YP, Liang GJ et al Sexually transmitted infections among female sex workers in Yunnan, China. AIDS Patient Care STDS 2005; 19:853-60.
• 19. Gare J, Lupiwa T, Suarkia DL et al High prevalence of sexually transmitted infections among female sex workers in the eastern highlands province of Papua New Guinea: correlates and recommendations. Sex Transm Dis 2005; 32:466-73.
• 20. Shapiro MF, Berk ML, Berry SH et al National probability samples in studies of low-prevalence diseases -Part I: Perspectives and lessons from the HIV cost and services utilization study. Health Serv Res 1999; 34:951-68.
• 21. Tran TN, Detels R, Long HT, Van Phung L, Lan HP. HIV infection and risk characteristics among female sex workers in Hanoi, Vietnam. J Acquir Immune Defic Syndr 2005; 39:581-6.
• 22. Minh TT, Nhan DT, West GR et al Sex workers in Vietnam: how many, how risky? AIDS Educ Prev 2004; 16:389-404.
• 23. Heckathorn DD. Respondent-driven sampling II: deriving valid population estimates from chain-referral samples of hidden populations. Soc Probl 2002; 49:11-34.
• 24. Erickson BH. Some problems of inference from chain data. Sociol Methodol 1979; 10:276-302.
• 25. Bautista CT, Sanchez JL, Montano SM et al Seroprevalence of and risk factors for HIV-1 infection among female commercial sex workers in South America. Sex Transm Infect 2006; 82:311-6.
• 26. UNAIDS (Joint United Nations Programme on HIV/AIDS). 2005. Monitoring the Declaration of Commitment on HIV/AIDS: Guidelines on Constructions of Core Indicators. Geneva: UNAIDS, 2005.
• 27. Barbosa Junior A, Pascom AR, Szwarcwald CL, Dhalia CB, Monteiro L, Simão MB. Proposed UNGASS indicators and the monitoring of the AIDS epidemic in Brazil. Rev Saude Publica 2006; 40(Suppl 1):94-100.
• 28. Johnston LG, Sabin K, Mai TH, Pham TH. Assessment of respondent driven sampling for recruiting female sex workers in two Vietnamese cities: reaching the unseen sex worker. J Urban Health 2006; 83(Suppl 6):i16-28.
• 29. Uusküla A, Fischer K, Raudne R et al A study on HIV and hepatitis C virus among commercial sex workers in Tallinn. Sex Transm Infect 2008; 84:189-91.
• 30. Shahmanesh M, Cowan FM, Wayal SS, Copas A, Patel V, Mabey D. The burden and determinants of HIV and sexually transmitted infections in a population based sample of female sex workers in Goa, India. Sex Transm Infect 2009; 85:50-9.
• 31. Morison L, Weiss HA, Buvé A et al Study Group on Heterogeneity of HIV Epidemics in African Cities. Commercial sex and the spread of HIV in four cities in sub-Saharan Africa. AIDS 2001;15(Suppl 4):S61-9.
• 32. Laurent C, Seck K, Coumba N et al Prevalence of HIV and other sexually transmitted infections, and risk behaviors in unregistered sex workers in Dakar, Senegal. AIDS 2003; 17:1811-6.
• 33. Tuan NA, Fylkesnes K, Thang BD et al Human immunodeficiency virus (HIV) infection patterns and risk behaviors in different population groups and provinces in Vietnam. Bull World Health Organ 2007; 85:35-41.
• 34. Salganik MJ, Heckathorn DD. Sampling and Estimation in Hidden Populations Using Respondent-Driven Sampling. Sociol Methodol 2004; 34:193-239.
• 35. Salganik MJ. Variance estimation, design effects, and sample size calculations for respondent-driven sampling. J Urban Health 2006; 83:i98-112.
• 36. Heckathorn, Douglas D. Extensions of respondent-driven sampling: Analyzing continuous variables and controlling for differential recruitment. Sociological Methodology 2007; 37:151-208.
• 37. Hagan JE, Dulmaa N. Risk factors and prevalence of HIV and sexually transmitted infections among low-income female commercial sex workers in Mongolia. Sex Transm Dis 2007; 34:83-7.
• 38. Lau JT, Tsui HY, Ho SP. Variations in condom use by locale: a comparison of mobile Chinese female sex workers in Hong Kong and mainland China. Arch Sex Behav 2007; 36:849-59.
• 39. Szwarcwald CL, Damacena GN. Amostras complexas em inquéritos populacionais: planejamento e implicações na análise estatística dos dados. Rev bras epidemiol 2008; 11(Suppl.1):38-45.
• 40. Goel S, Salganik MJ. Respondent-driven sampling as Markov chain Monte Carlo. Stat Med 2009; 28:2202-29.
• 41. Trevisol FS, Silva MV. HIV frequency among female sex workers in Imbituba, Santa Catarina, Brazil. Braz J Infect Dis 2005; 9:500-5.
• 42. Benzaken AS, Garcia EG, Sardinha JCG, Pedrosa VL, Loblein O. Baixa prevalência de DST em profissionais do sexo no Município de Manacapuru -interior do Estado do Amazonas, Brasil. J Bras Doenças Sex Transm 2002; 14:9-12.
• 43. Benzaken AS, Sabidó M, Galban EG et al Field evaluation of the performance and testing costs of a rapid point-of-care test for syphilis in a red-light district of Manaus, Brazil. Sex Transm Infect 2008; 84:297-302.
• 44. Azim T, Islam MN, Bogaerts J et al Prevalence of HIV and syphilis among high-risk groups in Bangladesh. AIDS 2000; 14:210-1.
• 45. Ohshige K, Morio S, Mizushima S et al Cross-sectional study on risk factors of HIV among female commercial sex workers in Cambodia. Epidemiol Infect 2000; 124:143-52.
• 46. Ford K, Wirawan DN, Reed BD, Muliawan P, Sutarga M. AIDS and STD knowledge, condom use and HIV/STD infection among female sex workers in Bali, Indonesia. AIDS Care 2000; 12:523-34.
• 47. Van Den Hoek A, Yuliang F, Dukers NH et al High prevalence of syphilis and other sexually transmitted diseases among sex workers in China: potential for fast spread of HIV. AIDS 2001; 15:753-9.
• 48. Aklilu M, Messele T, Tsegaye A et al Factors associated with HIV-1 infection among sex workers of Addis Ababa, Ethiopia. AIDS 2001; 15:87-96.
• 49. Asamoah-Adu C, Khonde N, Avorkliah M et al HIV infection among sex workers in Accra: need to target new recruits entering the trade. J Acquir Immune Defic Syndr 2001; 28:358-66.
• 50. DAntuono A, Andalò F, Carlà EM, De Tommaso S. Prevalence of STDs and HIV infection among immigrant sex workers attending an STD centre in Bologna, Italy. Sex Transm Infect 2001; 77:220.
• 51. Verster A, Davoli M, Camposeragna A, Valeri C, Perucci CA. Prevalence of HIV infection and risk behavior among street prostitutes in Rome, 1997-1998. AIDS Care 2001; 13:367-72.
• 52. Ishi K, Suzuku F, Saito A, Yoshimoto S, Kubota T. Prevalence of human immunodeficiency virus, hepatitis B and hepatitis C virus antibodies and hepatitis B antigen among commercial sex workers in Japan. Infect Dis Obstet Gynecol 2001; 9:215-9.
• 53. Alary M,Mukenge-Tshibaka L,Bernier F et al Decline in the prevalence of HIV and sexually transmitted diseases among female sex workers in Cotonou, Benin, 1993-1999. AIDS 2002; 16:463-70.
• 54. Chan MK, Ho KM, Lo KK. A behavior sentinel surveillance for female sex workers in the Social Hygiene Service in Hong Kong (1999-2000). Int J STD AIDS 2002; 13:815-20.
• 55. Ghys PD, Diallo MO, Ettiègne-Traoré V et al Increase in condom use and decline in HIV and sexually transmitted diseases among female sex workers in Abidjan, Côte d'Ivoire, 1991-1998. AIDS 2002; 16:251-8.
• 56. Ford K, Wirawan DN, Reed BD, Muliawan P, Wolfe R. The Bali STD/AIDS Study: evaluation of an intervention for sex workers. Sex Transm Dis 2002; 29:50-8.
• 57. Bakare RA, Oni AA, Umar US et al Pattern of sexually transmitted diseases among commercial sex workers (CSWs) in Ibadan, Nigeria. Afr J Med Med Sci 2002; 31:243-7.
• 58. Mgone CS, Passey ME, Anang J et al Human immunodeficiency virus and other sexually transmitted infections among female sex workers in two major cities in Papua New Guinea. Sex Transm Dis 2002; 29:265-70.
• 59. Hawken MP, Melis RD, Ngombo DT et al Part time female sex workers in a suburban community in Kenya: a vulnerable hidden population. Sex Transm Infect 2002; 78:271-3.
• 60. Sopheab H, Gorbach PM, Gloyd S, Leng HB. Rural sex work in Cambodia: work characteristics, risk behaviors, HIV, and syphilis. Sex Transm Infect 2003; 79:e2.
• 61. Desai VK, Kosambiya JK, Thakor HG, Umrigar DD, Khandwala BR, Bhuyan KK. Prevalence of sexually transmitted infections and performance of STI syndromes against aetiological diagnosis, in female sex workers of red light area in Surat, India. Sex Transm Infect 2003; 79:111-5.
• 62. Davies SC, Otto B, Partohudoyo S et al Sexually transmitted infections among female sex workers in Kupang, Indonesia: searching for a screening algorithm to detect cervical gonococcal and chlamydial infections. Sex Transm Dis 2003; 30:671-9.
• 63. Miyazaki M, Babazono A, Kato M, Takagi S, Chimura H, Une H. Sexually transmitted diseases in Japanese female commercial sex workers working in massage parlors with cell baths. J Infect Chemother 2003; 9:248-53.
• 64. Behets FM, Rasolofomanana JR, Van Damme K et al Evidencebased treatment guidelines for sexually transmitted infections developed with and for female sex workers. Trop Med Int Health 2003; 8:251-8.
• 65. Xueref S, Holianjavony J, Daniel R, Kerouedan D, Fabry J, Vanhems P. The absence of HIV seropositivity contrasts with a high prevalence of markers of sexually transmitted infections among registered female sex workers in Toliary, Madagascar. Trop Med Int Health 2003; 8:60-6.
• 66. Uribe-Salas F, Conde-Glez CJ, Juárez-Figueroa L, Hernández-Castellanos A. Sociodemographic dynamics and sexually transmitted infections in female sex workers at the Mexican-Guatemalan border. Sex Transm Dis 2003; 30:266-71.
• 67. Resl V, Kumpová M, Cerná L, Novák M, Pazdiora P. Prevalence of STDs among prostitutes in Czech border areas with Germany in 1997-2001 assessed in project "Jana". Sex Transm Infect 2003; 79:E3.
• 68. Camejo MI, Mata G, Díaz M. Prevalence of hepatitis B, hepatitis C and syphilis in female sex workers in Venezuela. Rev Saude Publica 2003; 37:339-44.
• 69. Belza MJ, Clavo P, Ballesteros J et al Social and work conditions, risk behavior and prevalence of sexually transmitted diseases among female immigrant prostitutes in Madrid (Spain). Gac Sanit 2004; 18:177-83.
• 70. Belza MJ. Spanish Group for the Unlinked Anonymous Survey of HIV Seroprevalence in STD Patients. Prevalence of HIV, HTLV-I and HTLV-II among female sex workers in Spain, 2000-2001. Eur J Epidemiol 2004; 19:279-82.
• 71. Pal D, Raut DK, Das A. A study of HIV/STD infections amongst commercial sex workers in Kolkata. (India) Part-IV laboratory investigation of STD and HIV infections. J Commun Dis 2004; 36:12-6.
• 72. Nguyen AT, Nguyen TH, Pham KC et al Intravenous drug use among street-based sex workers: a high-risk behavior for HIV transmission. Sex Transm Dis 2004; 31:15-9.
• 73. Dunkle KL, Beksinska ME, Rees VH, Ballard RC, Htun Y, Wilson ML. Risk factors for HIV infection among sex workers in Johannesburg, South Africa. Int J STD AIDS 2005; 16:256-61.
• 74. Ding Y, Detels R, Zhao Z et al HIV infection and sexually transmitted diseases in female commercial sex workers in China. J Acquir Immune Defic Syndr 2005; 38:314-9.
• 75. Sarkar K, Bal B, Mukherjee R, Niyogi SK, Saha MK, Bhattacharya SK. Epidemiology of HIV infection among brothelbased sex workers in Kolkata, India. J Health Popul Nutr 2005; 23:231-5.
• 76. Jahani MR, Alavian SM, Shirzad H, Kabir A, Hajarizadeh B. Distribution and risk factors of hepatitis B, hepatitis C, and HIV infection in a female population with "illegal social behavior". Sex Transm Infect 2005; 81:185.
• 77. Cowan FM, Hargrove JW, Langhaug LF et al The appropriateness of core group interventions using presumptive periodic treatment among rural Zimbabwean women who exchange sex for gifts or money. J Acquir Immune Defic Syndr 2005; 38:202-7.
• 78. Pando MA, Berini C, Bibini M et al Prevalence of HIV and other sexually transmitted infections among female commercial sex workers in Argentina. Am J Trop Med Hyg 2006; 74:233-8.
• 79. Ruan Y, Cao X, Qian HZ et al Syphilis among female sex workers in southwestern China: potential for HIV transmission. Sex Transm Dis 2006; 33:719-23.
• 80. Papadogeorgaki H, Caroni C, Frangouli E, Flemetakis A, Katsambas A, Hadjivassiliou M. Prevalence of sexually transmitted infections in female sex workers in Athens, Greece - 2005. Eur J Dermatol 2006; 16:662-5.
• 81. Allen CF, Edwards M, Williamson LM et al Sexually transmitted infection service use and risk factors for HIV infection among female sex workers in Georgetown, Guyana. J Acquir Immune Defic Syndr 2006; 43:96-101.
• 82. Sarkar K, Bal B, Mukherjee R et al Young age is a risk factor for HIV among female sex workers - an experience from India. J Infect 2006; 53:255-9.
• 83. Cwikel JG, Lazer T, Press F, Lazer S. Sexually transmissible infections among illegal female sex workers in Israel. Sex Health 2006; 3:301-3.
• 84. Nigro L, Larocca L, Celesia BM et al Prevalence of HIV and other sexually transmitted diseases among Colombian and Dominican female sex workers living in Catania, Eastern Sicily. J Immigr Minor Health 2006; 8:319-23.
• 85. Patterson TL, Semple SJ, Fraga M et al Comparison of sexual and drug use behaviors between female sex workers in Tijuana and Ciudad Juarez, Mexico. Subst Use Misuse 2006; 41:1535-49.
• 86. Bruckova M, Bautista CT, Graham RR et al Short report: HIV infection among commercial sex workers and injecting drug users in the Czech Republic. Am J Trop Med Hyg 2006; 75:1017-20.
• 87. Pisani E, Purnomo H, Sutrisna A et al Basing policy on evidence: low HIV, STIs, and risk behavior in Dili, East Timor argue for more focused interventions. Sex Transm Infect 2006; 82:88-93.
• 88. Todd CS, Khakimov MM, Alibayeva G et al Prevalence and correlates of human immunodeficiency virus infection among female sex workers in Tashkent, Uzbekistan. Sex Transm Dis 2006; 33:496-501.
• 89. Mosoko JJ, Macauley IB, Zoungkanyi AC, Bella A, Koulla-Shiro S. Human Immunodeficiency Virus Infection and Associated Factors among Specific Population Subgroups in Cameroon. AIDS Behav 2009; 13:277-87.
• 90. Barrientos JE, Bozon M, Ortiz E, Arredondo A. HIV prevalence, AIDS knowledge, and condom use among female sex workers in Santiago, Chile. Cad Saúde Pública 2007; 23:1777-84.
• 91. Lau JT, Ho SP, Yang X, Wong E, Tsui HY, Ho KM. Prevalence of HIV and factors associated with risk behaviors among Chinese female sex workers in Hong Kong. AIDS Care 2007; 19:721-32.
• 92. Vall-Mayans M, Villa M, Saravanya M et al Sexually transmitted Chlamydia trachomatis, Neisseria gonorrhoeae, and HIV-1 infections in two at-risk populations in Barcelona: female street prostitutes and STI clinic attendees. Int J Infect Dis 2007; 11:115-22.
• 93. Enkhbold S, Tugsdelger S, Morita S, Sakamoto J, Hamajima N. HIV/AIDS related knowledge and risk behaviors among female sex workers in two major cities of Mongolia. Nagoya J Med Sci 2007; 69:157-65.
• 94. Chersich MF, Luchters SM, Malonza IM, Mwarogo P, Kingola N, Temmerman M. Heavy episodic drinking among Kenyan female sex workers is associated with unsafe sex, sexual violence and sexually transmitted infections. Int J STD AIDS 2007; 18:764-9.
• 95. Vandepitte JM, Malele F, Kivuvu DM et al HIV and other sexually transmitted infections among female sex workers in Kinshasa, Democratic Republic of Congo, in 2002. Sex Transm Dis 2007; 34:203-8.
• 96. Wang C, Hawes SE, Gaye A et al HIV prevalence, previous HIV testing, and condom use with clients and regular partners among Senegalese commercial sex workers. Sex Transm Infect 2007; 83:534-40.
• 97. Vu Thuong N, Van Nghia K, Phuc Hau T et al Impact of a community sexually transmitted infection/HIV intervention project on female sex workers in five border provinces of Vietnam. Sex Transm Infect 2007; 83:376-82.
• 98. Xu JJ, Wang N, Lu L et al HIV and STIs in clients and female sex workers in mining regions of Gejiu City, China. Sex Transm Dis 2008; 35:558-65.
• 99. Ngo TD, Laeyendecker O, Li C et al Herpes simplex virus type 2 infection among commercial sex workers in Kunming, Yunnan Province, China. Int J STD AIDS 2008; 19:694-7.
• 100. Wang H, Chen RY, Ding G et al Prevalence and predictors of HIV infection among female sex workers in Kaiyuan City, Yunnan Province, China. Int J Infect Dis 2009; 13:162-9.
• 101. Folch C, Esteve A, Sanclemente C et al Prevalence of human immunodeficiency virus, Chlamydia trachomatis, and Neisseria gonorrhoeae and risk factors for sexually transmitted infections among immigrant female sex workers in Catalonia, Spain. Sex Transm Dis 2008; 35:178-83.
• 102. Van Veen MG, Götz HM, van Leeuwen PA, Prins M, van de Laar MJ. HIV and Sexual Risk Behavior among Commercial Sex Workers in the Netherlands. Arch Sex Behav 2010; 39:714-23
• 103. Linhart Y, Shohat T, Amitai Z et al Sexually transmitted infections among brothel-based sex workers in Tel-Aviv area, Israel: high prevalence of pharyngeal gonorrhoea. Int J STD AIDS 2008; 19:656-9.
• 104. Strathdee SA, Lozada R, Semple SJ et al Characteristics of female sex workers with US clients in two Mexico-US border cities. Sex Transm Dis 2008; 35:263-8.
• 105. Imade G, Sagay A, Egah D et al Prevalence of HIV and other sexually transmissible infections in relation to lemon or lime juice douching among female sex workers in Jos, Nigeria. Sex Health 2008; 5:55-60.

Publication Dates

• Publication in this collection
  06 Oct 2010
• Date of issue
  Aug 2010

History

• Received
  05 Mar 2010
• Accepted
  20 Mar 2010