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Erschienen in: BMC Medicine 1/2019

Open Access 01.12.2019 | Research article

HIV epidemiology among female sex workers and their clients in the Middle East and North Africa: systematic review, meta-analyses, and meta-regressions

Erschienen in: BMC Medicine | Ausgabe 1/2019

Abstract

Background

HIV epidemiology among female sex workers (FSWs) and their clients in the Middle East and North Africa (MENA) region is poorly understood. We addressed this gap through a comprehensive epidemiological assessment.

Methods

A systematic review of population size estimation and HIV prevalence studies was conducted and reported following PRISMA guidelines. Risk of bias (ROB) assessments were conducted for all included studies using various quality domains, as informed by Cochrane Collaboration guidelines. The pooled mean HIV prevalence was estimated using random-effects meta-analyses. Sources of heterogeneity and temporal trends were identified through meta-regressions.

Results

We identified 270 size estimation studies in FSWs and 42 in clients, and 485 HIV prevalence studies in 287,719 FSWs and 69 in 29,531 clients/proxy populations. Most studies had low ROB in multiple quality domains. The median proportion of reproductive-age women reporting current/recent sex work was 0.6% (range = 0.2–2.4%) and of men reporting currently/recently buying sex was 5.7% (range = 0.3–13.8%). HIV prevalence ranged from 0 to 70% in FSWs (median = 0.1%) and 0–34.6% in clients (median = 0.4%). The regional pooled mean HIV prevalence was 1.4% (95% CI = 1.1–1.8%) in FSWs and 0.4% (95% CI = 0.1–0.7%) in clients. Country-specific pooled prevalence was < 1% in most countries, 1–5% in North Africa and Somalia, 17.3% in South Sudan, and 17.9% in Djibouti. Meta-regressions identified strong subregional variations in prevalence. Compared to Eastern MENA, the adjusted odds ratios (AORs) ranged from 0.2 (95% CI = 0.1–0.4) in the Fertile Crescent to 45.4 (95% CI = 24.7–83.7) in the Horn of Africa. There was strong evidence for increasing prevalence post-2003; the odds increased by 15% per year (AOR = 1.15, 95% CI = 1.09–1.21). There was also a large variability in sexual and injecting risk behaviors among FSWs within and across countries. Levels of HIV testing among FSWs were generally low. The median fraction of FSWs that tested for HIV in the past 12 months was 12.1% (range = 0.9–38.0%).

Conclusions

HIV epidemics among FSWs are emerging in MENA, and some have reached stable endemic levels, although still some countries have limited epidemic dynamics. The epidemic has been growing for over a decade, with strong regionalization and heterogeneity. HIV testing levels were far below the service coverage target of “UNAIDS 2016–2021 Strategy.”
Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12916-019-1349-y) contains supplementary material, which is available to authorized users.

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Abkürzungen
AOR
Adjusted odds ratio
CHSNs
Commercial heterosexual sex networks
CI
Confidence interval
FSWs
Female sex workers
IBBSS
Integrated bio-behavioral surveillance surveys
MENA
Middle East and North Africa
MSM
Men who have sex with men
NGOs
Non-governmental organizations
PRISMA
Preferred Reporting Items for Systematic Reviews and Meta-analyses
PWID
People who inject drugs
ROB
Risk of bias
SI
Supplementary Information
SSA
Sub-Saharan Africa
STI
Sexually transmitted infection
UNAIDS
Joint United Nations Programme on HIV/AIDS
WHO
World Health Organization

Background

The Middle East and North Africa (MENA) is one of only two regions where HIV incidence and AIDS-related mortality are rising [1]. Between 2000 and 2015, the increase in the number of new infections was estimated at over a third, while that of AIDS-related deaths, at over threefold [13]. MENA has been described as “a real hole in terms of HIV/AIDS epidemiological data” [4], with unknown status and scale of epidemics in multiple countries [57].
Despite recent progress in HIV research and surveillance in MENA [8], including the conduct of integrated bio-behavioral surveillance surveys (IBBSS) [5, 9], many of these data are, at best, published in country-level reports, or never analyzed. Since 2007, the “MENA HIV/AIDS Epidemiology Synthesis Project” has maintained an active regional HIV database [6]. The first systematic syntheses of HIV data documented concentrated and emerging epidemics among men who have sex with men (MSM) [10] and people who inject drugs (PWID) [11]. The majority of these epidemics emerged within the last two decades [10, 11].
Although the size of commercial heterosexual sex networks is expected to be much larger than the risk networks of MSM and PWID [6, 7], estimates for the population proportion of female sex workers (FSWs), volume of clients they serve, and geographic and temporal trends in infection remain to be established. This evidence gap was highlighted in the latest gap report by the Joint United Nations Programme on HIV/AIDS (UNAIDS) [3], indicating “a lack of data on the burden of HIV among sex workers in the region” and stressing that “the epidemic among them is poorly understood” though “HIV in every country is expected to disproportionately affect sex workers” [3].
This study characterizes HIV epidemiology among FSWs and their clients in MENA by (1) systematically reviewing and synthesizing all available published and unpublished records documenting population size estimates, population proportions, HIV incidence, and HIV prevalence (including in proxy populations of clients such as male sexually transmitted infection (STI) clinic attendees); (2) estimating, for each population, the pooled mean HIV prevalence per country and regionally; (3) identifying the regional-level associations with prevalence, sources of heterogeneity, and temporal trends; and (4) synthesizing the key measures of sexual and injecting risk behaviors.

Methods

Search strategy and selection criteria

Evidence for population size estimate, population proportion, HIV incidence, and HIV prevalence in FSWs and clients was systematically reviewed as per Cochrane’s Collaboration guidelines [12]. Findings were reported following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [13] (checklist in Additional file 1: Table S1). MENA definition here includes 23 countries extending from Pakistan to Morocco (Additional file 1: Figure S1), based on the convention in HIV research [6, 7, 10, 11] and on World Health Organization (WHO), UNAIDS, and World Bank definitions [6]. MENA was also classified by subregion comprising Eastern MENA (Afghanistan, Iran, Pakistan), the Fertile Crescent (Egypt, Iraq, Jordan, Lebanon, Palestine, Syria), the Gulf (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen), the Horn of Africa (Djibouti, Somalia, recently independent South Sudan), and North Africa (Algeria, Libya, Morocco, Sudan, Tunisia).
Systematic searches were performed, up to July 29, 2018, on ten international-, regional-, and country-level databases; abstract archives of International AIDS Society conferences [14]; and Synthesis Project database which includes country-level and international organizations’ reports and routine data reporting [6, 7] (Additional file 1: Box S1). No language or year restrictions were used.
Titles and abstracts of unique citations were screened for relevance, and full texts of relevant/potentially relevant citations were retrieved for further screening. Any document/report including outcomes of interest based on primary data was eligible for inclusion. Case reports, case series, editorials, commentaries, and studies in populations (such as “vulnerable women”) where overlap with FSWs is implied but engagement in sex work is not explicitly indicated were excluded. Reference lists of reviews and all relevant documents were hand searched for eligible reports.
In this article, the term study refers to a specific outcome measure (population size estimate, incidence, or prevalence) in a specific population. Therefore, one report could contribute multiple studies, and one study could be published in different reports. Duplicate study results were included only once using the more detailed report.

Data extraction and synthesis

Data extraction was performed by HC and double extraction by MH, with discrepancies settled by consensus or by contacting authors. Data were extracted from full texts by native speakers (extraction list in Additional file 1: Box S2).
Population size estimates and population proportions were grouped based on being of national coverage or for specific subnational settings, and distinguishing between current FSWs/clients and history of sex work/ex-client. For FSWs, population proportion is defined as the proportion of all reproductive-age women that are engaged in sex work, that is the exchange of sex for money (sex work as a profession) [15, 16], and for clients, as the proportion of men buying sex from FSWs using money. Studies with mixed or non-representative samples (samples biased towards oversampling FSWs with no estimate adjustment) were excluded.
Due to the paucity of studies directly looking at HIV prevalence in clients of FSW, HIV prevalence studies in male STI clinic attendees, or mixed-sex samples of predominantly men (> 60%), were used as a proxy for HIV prevalence in clients of FSWs [17, 18].
Based on meta-analysis results for the pooled HIV prevalence in FSWs, epidemics were classified as concentrated (prevalence > 5%), intermediate-intensity (prevalence between 1 and 5%), and low-level (prevalence < 1%), as informed by epidemiological relevance and existing conventions [1921].
HIV incidence studies were identified and reported. Additional contextual information was extracted from FSW studies included in the review. These include age, age at sexual debut, age at sex work initiation, sex work duration, marital status, and HIV/AIDS knowledge and perception of risk, as well as behavioral measures of condom use, injecting drug use, sexual partnerships, and HIV testing.
Data were summarized using medians and ranges.

Quality assessment

Risk of bias (ROB) assessments for population size estimates/population proportions and for HIV prevalence were conducted as informed by Cochrane Collaboration guidelines [12] (criteria in Additional file 1: Table S2). Briefly, size estimation studies were classified as having “low” versus “high” ROB on each of the three domains assessing the (1) validity of sex work definition/engagement in paid sex (clear/valid definition; otherwise), (2) rigor of estimation methodology (likely-to-yield representative estimate; otherwise), and (3) response rate (≥ 60%; < 60%).
Prevalence studies were similarly classified on each of the four domains assessing the (1) validity of sex work definition/engagement in paid sex (clear/valid definition; otherwise), (2) rigor of sampling methodology (probability-based; non-probability-based), (3) response rate (≥ 60% or ≥ 60% of target sample size reached for studies using respondent-driven or time-location sampling; < 60%), and (4) type of HIV ascertainment (biological assays; self-report).
Studies with missing information for a specific domain were classified as having “unclear” ROB for that domain. Measures only extracted from routine databases were considered of unknown quality, as original reports were not available for assessing ROB, and were not included in the quality assessment. The impact of quality domains on observed prevalence was examined in meta-regression (described below).

Meta-analyses

Pooled mean HIV prevalence in FSWs and client populations were estimated using random-effects meta-analyses, by country and for the whole region. Variances were stabilized using Freeman-Tukey-type arcsine square-root transformation [22, 23]. Weighting was performed using the inverse-variance method [23, 24]. Pooling was performed using Dersimonian-Laird random-effects models to allow for sampling variation and true heterogeneity [25, 26]. Overall prevalence measures were replaced by their stratified measures where applicable.
Heterogeneity was assessed using Cochran’s Q statistic to confirm the existence of heterogeneity, I2 to estimate the magnitude of between-study variation, and prediction intervals to estimate the 95% interval of distribution of true effect sizes [26, 27].
Meta-analyses were implemented in R version 3.4.2 [28].

Meta-regression analyses

Random-effects meta-regression analyses were conducted to identify the regional-level associations with HIV prevalence in FSWs, sources of between-study heterogeneity, and temporal trend. Independent variables considered a priori were country/subregion, FSW population type, sample size, median year of data collection, sampling methodology, response rate, validity of sex work definition, and HIV ascertainment (details in Additional file 1: Table S3). The same factors (as applicable) were considered for clients’ meta-regression analyses.
To avoid the exclusion of studies with zero prevalence, an increment of 0.1 was added to the number of events in all studies to calculate the log-transformed odds, that is prevalence/(1 − prevalence), and corresponding variance [29]. Factors showing strong evidence for an association with the odds (p value ≤ 0.10) in univariable analysis were included in the multivariable analysis.
Meta-regressions were implemented in Stata/SE v.15.1 [30].

Results

Search results and scope of evidence

Figure 1 shows the study selection process. A total of 16,131 citations were identified through databases. After excluding duplicates and title and abstract screening, full texts of 336 unique citations were screened, and 87 reports were eligible for inclusion. Hand-searching of reference lists of relevant reports yielded eight additional eligible reports. Searching US Census Bureau and UNAIDS databases yielded 173 additional measures. Sixty-three detailed country-level reports, 11 of which replaced eligible articles, and 134 additional measures were further identified through Synthesis Project database. In sum, data from 147 eligible reports and 307 additional measures were included. These yielded in total 312 size estimation, 6 HIV incidence, and 554 HIV prevalence measures in FSWs and clients.
Evidence for population size and/or population proportion of FSWs was available for 12 out of 23 MENA countries (270 studies). Population size/population proportion of clients was available in 42 studies from 10 countries. All 6 HIV incidence studies were among FSWs. A total of 485 HIV prevalence studies were identified in 287,719 FSWs from 17 countries and 69 HIV prevalence studies in 29,531 clients (or proxy populations) from 10 countries. Prevalence measures in FSWs and clients contributed respectively 674 and 147 stratified measures for the meta-analyses (overall prevalence measures were replaced by their strata in meta-analyses). For all types of measures, there was a high heterogeneity in data availability across countries.

Population size estimates and population proportions of FSWs and clients

Table 1 and Additional file 1: Table S4 show the population size estimate and population proportion studies for FSWs and clients at the national and subnational levels, respectively. At the national level, the median number of current/recent FSWs (engaged in sex work in the past year) was 58,934 (range = 2218 in Djibouti to 167,501 in Pakistan), and the median population proportion (out of reproductive-age women aged 15–49 years) was 0.6% (range across studies = 0.2% in Egypt to 2.4% in Iran). The median population proportion of current/recent clients (buying sex from FSWs in the past year) based on diverse samples of general population men was 5.7% (range across studies = 0.3% in Sudan to 13.8% in Lebanon).
Table 1
Estimates of some national representation for the number and population proportion of FSWs, and the number and population proportion of clients of FSWs, in the Middle East and North Africa (MENA) reported by identified studies
 
Country
Author, year [citation]
Year(s) of data collection
Estimation methodology
Sample type
Reported size estimate
Time frame
N
Range
%*
Range*
FSWs
Egypt
Bahaa, 2010 [31]
2004–2008
Convenience sample (self-report)
Women seeking VCT testing
NR
NR
NR
0.4
NR
Jacobsen, 2014 [32]
2014
Enumeration (time-location geographical mapping)
FSWs in urban locations
Current
22,986
6460–26,792
0.24
NR
Djibouti
WHO, 2011 [33]
2009
NR
FSWs
NR
1000
NR
NR
NR
WHO, 2011 [33]
2011
Capture-recapture
FSWs
Current
2218
NR
NR
NR
Iran
WHO, 2011 [33]
2010
Network scale-up
General pop
Current
80,000
NR
NR
NR
Sharifi, 2017 [34]
2015
Multiplier unique object
FSWs
Current
19,800
10,900–38,100
0.31
0.17–0.58
Sharifi, 2017 [34]
2015
Network scale-up
General pop
Current
98,500
87,000–109,400
1.54
1.36–1.71
Sharifi, 2017 [34]
2015
Wisdom of the crowds
FSWs
Current
152,200
93,400–21,4300
2.38
1.46–3.35
Lebanon
Kahhaleh, 2009 [35]
1996
Pop-based survey (self-report)
General pop (15–49 years)
Past 12 M
NR
NR
0.54
NR
Kahhaleh, 2009 [35]
2004
Pop-based survey (self-report)
General pop (15–49 years)
Past 12 M
NR
NR
0.53
NR
Morocco
WHO, 2011 [33]
2010
NR
FSWs
Current
67,000
NR
NR
NR
Bennani, 2013 [36]
2011
Multiplier unique object
FSWs
Past 6 M
85,000
NR
NR
NR
MOH, 2013 [37]
2013
Pop-based survey (self-report)
Young women (15–24 years)
Lifetime
NR
NR
6.9
NR
MOH, 2013 [37]
2013
Pop-based survey (self-report)
Young women (15–24 years)
Current
NR
NR
2.4
NR
Pakistan
NACP, 2005 [38] (round I)
2005
Enumeration (time-location geographical mapping)
Brothel, kothikhana, home, and street-based FSWs
Current
35,050
30,300–39,800
0.78
NR
Emmanuel, 2010 [39] (round II)
2006
Enumeration (time-location geographical mapping)
Brothel, kothikhana, home, and street-based FSWs
Current
167,501
NR
0.44
NR
Emmanuel, 2013 [40, 41] (round IV)
2011–2012
Enumeration (time-location geographical mapping)
Brothel, kothikhana, home, and street-based FSWs
Current
89,178
78,778–99,592
0.72
NR
NACP, 2017 [42] (round V)
2016–2017
Enumeration (time-location geographical mapping)
Brothel, kothikhana, home, and street-based FSWs
Current
64,829
57,734–70,428
NR
NR
Sudan
AFROCENTER Group, 2005 [43]
2005
Self-report (convenience sample)
Young women
NR
NR
NR
0.4
NR
Syria
WHO, 2011 [33]
2011
NR
FSWs
Current
50,000
NR
NR
NR
Tunisia
WHO, 2011 [33]
2005
NR
FSWs
Current
NR
1000–5000
NR
NR
WHO, 2011 [33]
2009
NR
FSWs
Current
10,000
NR
NR
NR
WHO, 2011 [33]
2011
NR
FSWs
Current
25,500
NR
NR
NR
Yemen
MOH, 2010 [44]
NR
Enumeration (time-location geographical mapping)
FSWs
Current
58,934
NR
NR
1.16–2.10
Clients of FSWs
Afghanistan
Todd, 2007 [45]
2005–2006
Pop-based survey (self-report)
TB patients receiving treatment
Lifetime
NR
NR
3.57
NR
Todd, 2012 [46]
2010–2011
Pop-based survey (self-report)
Army recruits
Lifetime
NR
NR
12.5
NR
Egypt
Bahaa, 2010 [31]
2004–2008
Convenience sample (self-report)
Men seeking VCT testing
NR
NR
NR
0.9
NR
Lebanon
Kahhaleh, 2009 [35]
1996
Pop-based survey (self-report)
General pop (15–49 years)
Past 12 M
NR
NR
9.7
NR
Adib, 2002 [47]
1999
Pop-based survey (self-report)
Military conscripts
Past 12 M
NR
NR
13.84
NR
Kahhaleh, 2009 [35]
2004
Pop-based survey (self-report)
General pop (15–49 years)
Past 12 M
NR
NR
5.65
NR
Morocco
MOH, 2007 [48]
2007
Pop-based survey (self-report)
Young men (15–24 years)
Lifetime
NR
NR
35.3
NR
MOH, 2007 [48]
2007
Pop-based survey (self-report)
Young men (15–24 years)
Current
NR
NR
2
NR
MOH, 2013 [37]
2013
Pop-based survey (self-report)
Young men (15–24 years)
Lifetime
NR
NR
10.5
NR
MOH, 2013 [37]
2013
Pop-based survey (self-report)
Young men (15–24 years)
Current
NR
NR
0.3
NR
Pakistan
Mir, 2013 [49]
2007
Pop-based survey (self-report)
Urban men (16–45 years)
Lifetime
NR
NR
11.9
NR
Mir, 2013 [49]
2007
Pop-based survey (self-report)
Urban men (16–45 years)
Past 12 M
NR
NR
5.8
NR
Sudan
NACP, 2004 [50]
2004
Convenience sample (self-report)
Military personnel
NR
NR
NR
0.3
NR
AFROCENTER Group, 2005 [43]
2005
Convenience sample (self-report)
Young men
NR
NR
NR
0.5
NR
The table is sorted by year(s) of data collection
Abbreviations: FSWs female sex workers, M months, MOH Ministry of Health, NACP National AIDS Control Programme, NR not reported, Pop population, TB tuberculosis, VCT voluntary counseling and testing, WHO World Health Organization
*The decimal places of the population proportion figures are as reported in the original reports
With high heterogeneity in estimation methodology, time frame, and scope between and within countries, it was deemed not meaningful to generate country-specific or regional-pooled estimates for the size/population proportions.

HIV incidence overview

There were six incidence studies among FSWs (three from each of Somalia and Djibouti; data not shown). Three studies reported zero seroconversions [51, 52]. One study from Somalia reported a cumulative incidence of 2.6% after 6 months of follow-up [51]. The other two from Djibouti—among predominantly Ethiopian FSWs (91%)—reported a cumulative incidence of 3.4% [51] and 11.6% [51] after 3 and 9 months of follow-up, respectively. All incidence studies were conducted before the year 2000 and were limited in scale and scope.

HIV prevalence overview

HIV prevalence in FSWs ranged from 0 to 70%, with a median of 0.1% (Tables 2 and 3 and Additional file 1: Table S5). There was a high heterogeneity, with almost half of the studies (46.8%) reporting zero prevalence. The median prevalence was 0% (range = 0–14%), 2.0% (range = 0–47.1%), and 18.8% (range = 0–70%) in countries with low-level (prevalence < 1%), intermediate-intensity (prevalence 1–5%), and concentrated epidemics (prevalence > 5%), respectively (epidemic classification based on the results of meta-analyses; see below and Table 5). Ranges indicated pockets of higher HIV prevalence, even in countries with low-level and intermediate-intensity epidemics.
Table 2
HIV prevalence in FSWs in the Middle East and North Africa (MENA), as reported in studies using probability-based sampling
Country
Author, year [citation]
Year(s) of data collection
City/province
Study site
Sampling
Population
Sample size
HIV prevalence*
%
95% CI
Afghanistan
SAR AIDS HDS, 2008 [53]
2006–2007
Jalalabad
Community
TLS
FSWs
45
0
NR
SAR AIDS HDS, 2008 [53]
2006–2007
Mazar-i-Sharif
Community
TLS
FSWs
87
0
NR
NACP, 2010 [54] (round I)
2009
Kabul
Community
RDS
FSWs
368
0
NR
NACP, 2012 [55] (round II)
2012
Herat
Community
RDS
FSWs
344
0.9
NR
NACP, 2012 [55] (round II)
2012
Kabul
Community
RDS
FSWs
333
0
NR
NACP, 2012 [55] (round II)
2012
Mazar-i-Sharif
Community
RDS
FSWs
355
0
NR
Egypt
MOH, 2006 [56] (round I)
2006
Cairo
Community
Conv**
FSWs
118
0.8
NR
MOH, 2010 [57] (round II)
2010
Cairo
Community
Conv**
FSWs
200
0
NR
Iran
Navadeh, 2012 [58]
2010
Kerman
Community
RDS
FSWs
139
0
NR
Sajadi, 2013 [59] (round I)
2010
National
Facilities serving vulnerable women
MCS
FSWs
817
4.5
NR
Kazerooni, 2014 [60]
2010–2011
Shiraz
Community
RDS
FSWs
278
4.7
NR
Moaeyedi-Nia, 2016 [61]
2012–2013
Tehran
Community
RDS
FSWs
161
5
NR
Mirzazadeh, 2016 [62] (round II)
2015
National
Facilities serving vulnerable women
MCS
FSWs
1337
2.1
0.9–4.6
Karami, 2017 [63]
2016
Tehran
Community
TLS
FSWs
369
4.6
NR
Jordan
WHO, 2011 [33] (round I)
2009
National
Community
RDS
FSWs
225
0
NR
MOH, 2014 [64] (round II)
2013
Amman
Community
RDS
FSWs
358
0.6
NR
MOH, 2014 [64] (round II)
2013
Irbid
Community
RDS
FSWs
102
0
NR
MOH, 2014 [64] (round II)
2013
Zarqa
Community
RDS
FSWs
212
0.5
NR
Lebanon
Mahfoud, 2010 [65]
2007–2008
Greater Beirut
Community
RDS
FSWs
95
0
NR
Libya
Valadez, 2013 [66] (round I)
2010–2011
Tripoli
Community
RDS
FSWs
69
15.7
3.2–32.6
Morocco
MOH, 2012 [67]
2011–2012
Agadir
Community
RDS
FSWs
364
5.1
2.1–8.6
MOH, 2012 [67]
2011–2012
Fes
Community
RDS
FSWs
359
1.8
0–2.1
MOH, 2012 [67]
2011–2012
Rabat
Community
RDS
FSWs
392
0
NR
MOH, 2012 [67]
2011–12
Tanger
Community
RDS
FSWs
319
1.4
0.4–3.3
Pakistan
Bokhari, 2007 [68]
2004
Lahore
Red-light district
SyCS
FSWs
378
0.5
NR
NACP, 2005 [38] (round I)
2005
Faisalabad
Community
RDS and TLS
Kothikhana, home, and street-based FSWs
400
0
NR
NACP, 2005 [38] (round I)
2005
Hyderabad
Community
SyRS, RDS, and TLS
Brothel, kothikhana, home, and street-based FSWs
400
0
NR
NACP, 2005 [38] (round I)
2005
Karachi
Community
SyRS, RDS, and TLS
Brothel, kothikhana, home, and street-based FSWs
400
0.8
NR
NACP, 2005 [38] (round I)
2005
Lahore
Community
SyRS, RDS, and TLS
Brothel, kothikhana, home, and street-based FSWs
400
0
NR
NACP, 2005 [38] (round I)
2005
Multan
Community
Conv (take all), RDS, and TLS
Brothel, kothikhana, home, and street-based FSWs
400
0
NR
NACP, 2005 [38] (round I)
2005
Peshawar
Community
MCS
Kothikhana, home, and street-based FSWs
359
0
NR
NACP, 2005 [38] (round I)
2005
Quetta
Community
RDS and MCS
Kothikhana, home, and street-based FSWs
411
0.7
NR
NACP, 2005 [38] (round I)
2005
Sukkur
Community
RDS and TLS
Kothikhana, home, and street-based FSWs
368
0
NR
NACP, 2007 [69] (round II)
2006
Bannu
Community
SyRS and MCS
Kothikhana, home, and street-based FSWs
194
0
NR
NACP, 2007 [69] (round II)
2006
Faisalabad
Community
SyRS and MCS
Kothikhana, home, and street-based FSWs
400
0
NR
NACP, 2007 [69] (round II)
2006
Gujranwala
Community
SyRS and MCS
Kothikhana, home, and street-based FSWs
400
0
NR
NACP, 2007 [69] (round II)
2006
Hyderabad
Community
SyRS and MCS
Brothel, kothikhana, home, and street-based FSWs
398
0.3
NR
NACP, 2007 [69] (round II)
2006
Karachi
Community
SyRS and MCS
Brothel, kothikhana, home, and street-based FSWs
403
0
NR
NACP, 2007 [69] (round II)
2006
Lahore
Community
SyRS and MCS
Brothel, kothikhana, home, and street-based FSWs
425
0.02
NR
NACP, 2007 [69] (round II)
2006
Larkana
Community
SyRS and MCS
Brothel, kothikhana, home, and street-based FSWs
400
0
NR
NACP, 2007 [69] (round II)
2006
Multan
Community
SyRS and MCS
Brothel, kothikhana, home, and street-based FSWs
400
0
NR
NACP, 2007 [69] (round II)
2006
Peshawar
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
423
0
NR
NACP, 2007 [69] (round II)
2006
Quetta
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
398
0
NR
NACP, 2007 [69] (round II)
2006
Sargodha
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
400
0
NR
NACP, 2007 [69] (round II)
2006
Sukkur
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
400
0
NR
Hawkes, 2009 [70]
2007
Abbottabad
Community
RDS
FSWs
107
0
NR
Hawkes, 2009 [70]
2007
Rawalpindi
Community
RDS
FSWs
426
0
NR
Khan, 2011 [71]
2007
Lahore
Community
RDS
FSWs
730
0.7
NR
NACP, 2010 [72] (special IBBSS among FSWs)
2009
Punjab and Sindh
Community
SyRS and MCS
FSWs
2197
1.0
NR
NACP, 2012 [40] (round IV)
2012
DG Khan
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
375
0.5
0.1–1.9
NACP, 2012 [40] (round IV)
2012
Faisalabad
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
376
0
NR
NACP, 2012 [40] (round IV)
2012
Haripur
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
211
0.9
0.3–3.4
NACP, 2012 [40] (round IV)
2012
Karachi
Community
SyRS and MCS
Brothel, kothikhana, home, street-based, and other FSWs
377
1.9
0.9–3.8
NACP, 2012 [40] (round IV)
2012
Lahore
Community
SyRS and MCS
Brothel, kothikhana, home, street-based, and other FSWs
375
0.5
0.1–1.9
NACP, 2012 [40] (round IV)
2012
Larkana
Community
SyRS and MCS
Brothel, kothikhana, home, street-based, and other FSWs
375
1.9
0.9–3.8
NACP, 2012 [40] (round IV)
2012
Multan
Community
SyRS and MCS
Brothel, kothikhana, home, street-based, and other FSWs
375
0.3
0.05–1.5
NACP, 2012 [40] (round IV)
2012
Peshawar
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
367
0
NR
NACP, 2012 [40] (round IV)
2012
Quetta
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
345
0
NR
NACP, 2012 [40] (round IV)
2012
Rawalpindi
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
375
0
NR
NACP, 2012 [40] (round IV)
2012
Sargodha
Community
SyRS and MCS
Brothel, kothikhana, home, street-based, and other FSWs
345
0.3
0.05–1.6
NACP, 2012 [40] (round IV)
2012
Sukkur
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
375
0.8
0.3–2.3
NACP, 2017 [42] (round V)
2016–2017
Bahawalpur
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
351
0
NR
NACP, 2017 [42] (round V)
2016–2017
Bannu
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
196
1.5
1–4.4
NACP, 2017 [42] (round V)
2016–2017
DG Khan
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
364
0.8
0.3–2.4
NACP, 2017 [42] (round V)
2016–2017
Gujranwala
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
304
0.7
0.2–2.4
NACP, 2017 [42] (round V)
2016–2017
Gujrat
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
250
0.4
0.1–2.2
NACP, 2017 [42] (round V)
2016–2017
Hyderabad
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
364
2.2
1.1–4.3
NACP, 2017 [42] (round V)
2016–2017
Karachi
Community
SyRS and MCS
Brothel, kothikhana, home, street-based, and other FSWs
387
2.6
1.4–4.7
NACP, 2017 [42] (round V)
2016–2017
Kasur
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
364
0
NR
NACP, 2017 [42] (round V)
2016–2017
Larkana
Community
SyRS and MCS
Brothel, kothikhana, home, street-based, and other FSWs
364
4.1
2.5–6.7
NACP, 2017 [42] (round V)
2016–2017
Mirpurkhas
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
364
4.1
2.5–6.7
NACP, 2017 [42] (round V)
2016–2017
Nawabshah
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
364
3.8
2.3–6.4
NACP, 2017 [42] (round V)
2016–2017
Peshawar
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
265
3
1.5–5.8
NACP, 2017 [42] (round V)
2016–2017
Quetta
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
364
0
NR
NACP, 2017 [42] (round V)
2016–2017
Rawalpindi
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
364
0.3
0.1–1.5
NACP, 2017 [42] (round V)
2016–2017
Sheikhupura
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
363
1.7
1.1–4.9
NACP, 2017 [42] (round V)
2016–2017
Sialkot
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
193
0
NR
NACP, 2017 [42] (round V)
2016–2017
Sukkur
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
364
8.8
6.3–12.2
NACP, 2017 [42] (round V)
2016–2017
Turbat
Community
SyRS and MCS
Kothikhana, home, street-based, and other FSWs
72
0
NR
Somalia
Testa, 2008 [73] (round I)
2008
Hargeisa
Community
RDS
FSWs
237
5.2
2.5–8.5
IOM, 2017 [74] (round II)
2014
Hargeisa
Community
RDS
FSWs
96
4.8
0.2–9.3
Sudan
Elkarim, 2002 [75]
2002
National
Community
MSysRS
FSWs
367
4.4
NR
Abdelrahim, 2010 [76]
2008
Khartoum
Community
RDS
FSWs
321
0.9
0.1–2.2
NACP, 2010 [77]
2008–09
Gezira
Community
RDS
FSWs
267
0.1
NR
NACP, 2012 [78]
2011
Alshamalia
Community
RDS
FSWs
305
0.3
0–1
NACP, 2012 [78]
2011
Blue Nile
Community
RDS
FSWs
279
1.5
0–3
NACP, 2012 [78]
2011
Gadarif
Community
RDS
FSWs
282
0.6
0–1
NACP, 2012 [78]
2011
Gezira
Community
RDS
FSWs
296
0.7
0–1
NACP, 2012 [78]
2011
Kassala
Community
RDS
FSWs
288
5.0
2–8
NACP, 2012 [78]
2011
Khartoum
Community
RDS
FSWs
287
0
NR
NACP, 2012 [78]
2011
North Darfur
Community
RDS
FSWs
303
0.7
0–3
NACP, 2012 [78]
2011
North Kordofan
Community
RDS
FSWs
296
1
0–3
NACP, 2012 [78]
2011
Red Sea
Community
RDS
FSWs
293
7.7
4–12
NACP, 2012 [78]
2011
River Nile
Community
RDS
FSWs
291
0.7
0–2
NACP, 2012 [78]
2011
Sinnar
Community
RDS
FSWs
303
0.7
0–2
NACP, 2012 [78]
2011
South Darfur
Community
RDS
FSWs
299
0.2
0–1
NACP, 2012 [78]
2011
West Darfur
Community
RDS
FSWs
284
1
0–3
NACP, 2012 [78]
2011
White Nile
Community
RDS
FSWs
288
1.3
0–3
MOH, 2016 [79]
2015–2016
Juba, South Sudan
Community
RDS
FSWs
835
37.9
33.6–42.2
Tunisia
Hsairi, 2012 [80]
2009
Tunis, Sfax, and Sousse
Community
RDS
Street-based FSWs
703
0.4
NR
Hsairi, 2012 [80]
2011
Tunis
Community
TLS
Street-based FSWs
357
0.6
0–1.3
Hsairi, 2012 [80]
2011
Sfax
Community
TLS
Street-based FSWs
284
0
NR
Hsairi, 2012 [80]
2011
Sousse
Community
TLS
Street-based FSWs
347
1.2
0.02–2.3
Yemen
Stulhofer, 2008 [81] (round I)
2008
Aden
Community
RDS
FSWs
244
1.3
0–2.9
MOH, 2014 [82] (round I)
2010–2011
Hodeida
Community
RDS
FSWs
301
0
NR
The table is sorted by year(s) of data collection
Abbreviations: CI confidence interval, Conv convenience, FSWs female sex workers, IBBSS integrated bio-behavioral surveillance survey, IOM International Organization for Migration, MCS multistage cluster sampling, MOH Ministry of Health, MSyRS multistage systematic random sampling, NACP National AIDS Control Programme, NR not reported, RDS respondent-driven sampling, SAR AIDS HDS South Asia Region AIDS Human Development Sector, SyCS systematic cluster sampling, SyRS systematic random sampling, TLS time-location sampling, WHO World Health Organization
*The decimal places of the prevalence figures are as reported in the original reports, but prevalence figures with more than one decimal places were rounded to one decimal place, with the exception of those below 0.1%. Most studies did not report the 95% CIs associated with prevalence
**Integrated bio-behavioral surveillance survey with sampling initially planned as respondent-driven but ended up being a convenience for logistical reasons
Table 3
HIV prevalence in FSWs in the Middle East and North Africa (MENA), as reported in studies using non-probability sampling
Country
Author, year [citation]
Year(s) of data collection
City/province
Study site
Sampling
Population
Sample size
HIV prevalence*
%
95% CI
Afghanistan
Todd, 2010 [83]
2006–2008
Jalalabad, Kabul, and Mazar-i-Sharif
Community and NGO
Conv
FSWs
520
0.2
0.01–1.1
Djibouti
Rodier, 1993 [84]
1987
Djibouti
STI clinic
Conv
Street-based FSWs
66
4.6
NR
Rodier, 1993 [84]
1987
Djibouti
STI clinic
Conv
Bar hostesses
221
1.4
NR
Constantine, 1992 [52]
1988
Djibouti
NR
Conv
FSWs
33
18.2
NR
Rodier, 1993 [84]
1988
Djibouti
STI clinic
Conv
Street-based FSWs
78
9.0
NR
Rodier, 1993 [84]
1988
Djibouti
STI clinic
Conv
Bar hostesses
255
2.7
NR
Rodier, 1993 [84]
1990
Djibouti
STI clinic
Conv
Street-based FSWs
116
41.7
NR
Rodier, 1993 [84]
1990
Djibouti
STI clinic
Conv
Bar hostesses
180
5.0
NR
Couzineau, 1991 [85]
1991
Djibouti
STI clinic
Conv
Street-based FSWs
300
43
NR
Couzineau, 1991 [85]
1991
Djibouti
STI clinic
Conv
Bar girls
397
13.1
NR
Rodier, 1993 [84]
1991
Djibouti
STI clinic and residences
Conv
Street-based FSWs
292
36.0
NR
Rodier, 1993 [84]
1991
Djibouti
STI clinic and residences
Conv
Bar hostesses
360
15.3
NR
Philippon, 1997 [86]
1995
Djibouti
STI clinic
Conv
Street-based FSWs
176
49
NR
Marcelin, 2002 [87]
1998–1999
Djibouti
STI clinics
Conv
Street-based FSWs
43
70
NR
Marcelin, 2002 [87]
1998–1999
Djibouti
STI clinics
Conv
FSWs working in luxury bars
123
7
NR
Egypt
Sheba, 1988 [88]
1986–1987
Multiple cities
NR
Conv
FSWs
87
0
NR
Watts, 1993 [89]
1986–1990
Urban areas
Medical facilities
Conv
FSWs
349
0
NR
Kabbash, 2012 [90]
2009–2010
Greater Cairo
Community
Conv
FSWs
431
0
NR
Iran
Jahani, 2005 [91]
2002
NR
Detainment center/prison
Conv
FSWs detained by the police
149
0
NR
Kassaian, 2012 [92]
2009–2010
Isfahan
Prison, drop-in centers, and community
Conv
FSWs
91
0
NR
Taghizadeh, 2015 [93]
2014
Sari, Mazandaran
Drop-in center
Conv
FSWs at a drop-in center
184
4
NR
Asadi-Ali, 2018 [94]
2015
Northern Iran
Counseling center, drop-in center, and community
Conv
FSWs
133
1.5
NR
Lebanon
Naman, 1989 [95]
1985–1987
NR
NR
Conv
FSWs
291
0.3
NR
Morocco
MOH, 2008 [96]
2007
Agadir, Rabat/Sale, Tanger
NGO clinic
Conv
FSWs presenting for consultation
141
1.4
0.1–2.5
Pakistan
Iqbal, 1996 [97]
1987–1994
Lahore
Hospital
Conv
FSWs
21
0
NR
Baqi, 1998 [98]
1993–1994
Karachi
VCT
Conv
FSWs in red-light district
77
0
NR
Anwar, 1998 [99]
NR
Lahore
NR
NR
FSWs
103
1.9
NR
Bokhari, 2007 [68]
2004
Karachi
Community
Snowball
FSWs in red-light district
421
0
NR
Shah, 2004 [100]
2004
Hyderabad
Community
Conv
FSWs
157
0
NR
Shah, 2004 [101]
2004
Sindh
Sentinel surveillance
Conv
FSWs
163
1.2
NR
Akhtar, 2008 [102]
2007
Faisalabad
Community
NR
FSWs
246
0
NR
Raza, 2015 [103]
2014
Rawalpindi
Clinics
Conv
FSWs
NR
0
NR
Somalia
Jama, 1987 [104]
1985–1986
Mogadishu
Camp
Conv
FSWs attending health education program
85
0
NR
Burans, 1990 [105]
NR
Mogadishu
NR
Conv
FSWs
89
0
NR
Scott, 1991 [106]
1989
Merka, Kismayu
NR
Conv
FSWs
57
0
NR
Corwin, 1991 [107]
1990
Chismayu, Merca, Mogadishu
NR
Conv
FSWs
302
3
NR
Jama Ahmed, 1991 [51]
1991
Mogadishu
PHC
Conv
FSWs
155
0.6
NR
Sudan
Burans, 1990 [108]
1987
Port Sudan
NR
Conv
FSWs
203
0
NR
McCarthy, 1995 [109]
NR
Juba, South Sudan
NR
Conv
FSWs
50
16
NR
Tunisia
Bchir, 1988 [110]
1987
Sousse
NR
Conv
FSWs
42
0
NR
Hassen, 2003 [111]
NR
Sousse
PHC
Conv
Legal FSWs
51
0
NR
Znazen, 2010 [112]
2007
Tunis, Sousse, and Gabes
Medical facilities
Conv
Legal FSWs undergoing routine testing
183
0
NR
The table is sorted by year(s) of data collection or year of publication if the year of data collection was not reported
Abbreviations: CI confidence interval, Conv convenience, FSWs female sex workers, MOH Ministry of Health, NGO non-governmental organization, NR not reported, PHC primary healthcare centers, STI sexually transmitted infection, VCT voluntary counseling and testing
*The decimal places of the prevalence figures are as reported in the original reports, but prevalence figures with more than one decimal places were rounded to one decimal place, with the exception of those below 0.1%. Most studies did not report the 95% CIs associated with prevalence
In clients/male STI clinic attendees, HIV prevalence ranged from 0 to 34.6%, with a median of 0.4% (Table 4). Studies also showed high heterogeneity with 37.7% reporting zero prevalence. The median prevalence was 0% (range = 0–1.1%), 0.6% (range = 0–9.6%), and 7.4% (range = 0.8–34.6%) in countries with low-level, intermediate-intensity, and concentrated epidemics, respectively. Ranges indicated pockets of higher HIV prevalence in countries with intermediate-intensity epidemics.
Table 4
HIV prevalence in clients of FSWs (or proxy populations of clients of FSWs such as male STI clinic attendees) in the Middle East and North Africa (MENA)
Country
Author, year [citation]
Year(s) of data collection
City/province
Study site
Sampling
Population
Sample size
HIV prev*
Sexual contacts
%
95% CI
Algeria
MOH, 2009 [113]
2004
Oran
Sent. surv.
Conv
STI clinic attendees
41
4.9
NR
NR
MOH, 2009 [113]
2004
Tamanrasset
Sent. surv.
Conv
STI clinic attendees
105
0
0
NR
MOH, 2009 [113]
2004
Tizi-Ouzou
Sent. surv.
Conv
STI clinic attendees
11
9.1
NR
NR
MOH, 2009 [113]
2007
National
Sent. surv.
Conv
STI clinic attendees
571
3.3
NR
NR
Djibouti
Rodier, 1993 [84]
1987
Djibouti
STI clinic
Conv
STI clinic attendees
252
0.8
NR
NR
Rodier, 1993 [84]
1988
Djibouti
STI clinic
Conv
STI clinic attendees
249
0.8
NR
NR
Fox, 1989 [114]
NR
NR
NR
Conv
Clients of FSWs
105
1.0
NR
Clients of FSWs
Rodier, 1993 [84]
1990
Djibouti
STI clinic
Conv
STI clinic attendees
106
1.9
NR
NR
OMS, 2001 [115]
1990
NR
STI clinic
Conv
STI clinic attendees
NR
2.2
NR
NR
Rodier, 1993 [84]
1991
Djibouti
STI clinic
Conv
STI clinic attendees
193
10.4
NR
NR
OMS, 2001 [115]
1991
NR
STI clinic
Conv
STI clinic attendees
NR
9.2
NR
NR
MOH, 1993 [116]
1992
NR
Sent. surv.
Conv
STI clinic attendees
NR
11.6
NR
NR
MOH, 1993 [116]
1993
NR
Sent. surv.
Conv
STI clinic attendees
411
14.4
NR
NR
MOH, 2002 [117]
2001–2002
Djibouti
STI clinic
Conv
STI clinic attendees
237
34.6
NR
NR
Bortolotti, 2007 [6, 118]
2006
Djibouti
STI clinic
Conv
STI clinic attendees
72
5.6
1.5–13.6
NR
Egypt
Sheba, 1988 [88]
1986–1987
Multiple cities
STI clinic
Conv
STI clinic attendees
302
0
NR
NR
Sadek, 1991 [119]
1987–1988
Cairo
STI clinic
Conv
STI clinic attendees
140
0.7
NR
NR
Sadek, 1991 [119]
1989–1990
Cairo
STI clinic
Conv
STI clinic attendees
125
0.8
NR
NR
Fox, 1994 [120]
1993
Alexandria
STI clinic
Conv
STI clinic attendees
200
0
NR
NR
Fox, 1994 [120]
1993
Cairo
STI clinic
Conv
STI clinic attendees
300
0.3
NR
NR
Saleh, 2000 [121]
1998–2000
Alexandria
STI clinic
Conv
STI clinic attendees
295
0
NR
NR
Kuwait
NAP, 1999 [122]
1984–1998
Sabah, Kuwait
STI clinic
Conv
STI clinic attendees
3097
0.02
NR
NR
Murzi, 1989 [123]
1988
Kuwait
STI clinic
Conv
STI clinic attendees
305
0
NR
NR
Al-Owaish, 2000 [124]
1996–1997
Kuwait
STI clinic
SyRS
STI clinic attendees (Kuwaiti)
617
0
NR
23% reported contact with FSWs, 1% with MSWs, 35% with girlfriend, 12% with a mix of the above
Al-Owaish, 2000 [124]
1996–1997
Kuwait
STI clinic
SyRS
STI clinic attendees (non-Kuwaiti)
1367
0
NR
61% reported contact with FSWs, 0.5% with MSWs, 28.5% with girlfriend, 3% with a mix of the above
Al-Owaish, 2002 [125]
2002
Kuwait
STI clinic
Conv
STI clinic attendees (non-Kuwaiti)
599
0
NR
NR
Al-Mutairi, 2007 [126]
2003–2004
Kuwait
STI clinic
Conv
STI clinic attendees (predom. men)
520
0
NR
79% reported contact with FSWs
Morocco
Heikel, 1999 [127]
1992–1996
Casablanca
STI clinic
Conv
STI clinic attendees
1131
0.9
NR
NR
Manhart, 1996 [128]
1996
Agadir, Tanger, and Marrakech
STI clinic
Conv
STI clinic attendees
223
1.4
NR
NR
Alami, 2002 [129]
2001
Rabat, Sale, Beni Mellal, and Marrakech
Sent. surv.
Conv
STI clinic attendees
422
0
NR
70.7% reported new sexual partner, 47% multiple sexual partners in the past 3 months
MOH, 2001 [130]
2001
Marrakech, Beni Mellal, and Rabat, Sale
Sent. surv.
Conv
STI clinic attendees
422
0
NR
NR
Khattabi, 2005 [131]
2004
National
Sent. surv.
Conv
STI clinic attendees
NR
0.4
NR
NR
MOH, 2013 [132]
2006
National
Sent. surv.
Conv
STI clinic attendees
1180
0.2
NR
NR
MOH, 2013 [132]
2007
National
Sent. surv.
Conv
STI clinic attendees
986
0.4
NR
NR
MOH, 2013 [132]
2008
National
Sent. surv.
Conv
STI clinic attendees
1237
0.5
NR
NR
MOH, 2013 [132]
2009
National
Sent. surv.
Conv
STI clinic attendees
1103
0.3
NR
NR
MOH, 2013 [132]
2010
National
Sent. surv.
Conv
STI clinic attendees
1181
0.7
NR
NR
MOH, 2013 [133]
2011
Fes, Meknes, and Laayoune Boujdour
VCT
Conv
STI clinic attendees
88
2.3
NR
NR
MOH, 2013 [132]
2012
National
Sent. surv.
Conv
STI clinic attendees
1070
0.3
NR
NR
MOH, 2013 [133]
2012
National
VCT and STI clinic
Conv
STI clinic attendees
1297
0.4
NR
NR
Pakistan
Mujeeb, 1993 [134]
NR
Karachi
STI clinic
Conv
STI clinic attendees
32
0
NR
NR
Memon, 1997 [135]
1994–1995
Hyderabad
STI clinic
Conv
STI clinic attendees (predom. men)
50
0
NR
NR
NAP, 1996 [136]
1995
Karachi
STI clinic
Conv
STI clinic attendees (predom. men)
402
0
NR
NR
NAP, 1996 [136]
1995
Lahore
STI clinic
Conv
STI clinic attendees (predom. men)
295
0
NR
NR
Rehan, 2003 [137]
1999
Karachi
STI clinic
Conv
STI clinic attendees
138
0
NR
43% reported contact with FSWs, 12% with casual heterosexual contact, 11.6% with MSM, 18.4% reported bisexuality
Rehan, 2003 [137]
1999
Lahore
STI clinic
Conv
STI clinic attendees
148
0
NR
NR
Rehan, 2003 [137]
1999
Peshawar
STI clinic
Conv
STI clinic attendees
93
1.1
NR
NR
Rehan, 2003 [137]
1999
Quetta
STI clinic
Conv
STI clinic attendees
86
0
NR
NR
Bhutto, 2011 [138]
2000–2009
Larkana
STI clinic
Conv
STI clinic attendees
4288
0.06
NR
83% reported a history of contact with FSWs
Bokhari, 2007 [68]
2004
Karachi
Trucking agencies
SRS
Truck driver clients of FSWs
120
0
NR
Subsample including only clients of FSWs
Razvi, 2014 [139]
2010–2014
Abbottabad
STI clinic
Conv
STI clinic attendees
465
1.1
NR
8% refused to answer, 70% of the rest reported contact with FSWs, 21% with MSM, 7.5% with married women
NAP, 2012 [140]
2011
Balochistan
Mines
SRS
Mine workers clients of FSWs
381
0
NR
Subsample including only men reporting contact with FSWs at last sex
Somalia
Ismail, 1990 [141]
1986
Mogadishu
STI clinic
Conv
STI clinic attendees
101
0
NR
54% reported contact with FSWs
Scott, 1991 [106]
1989
Mogadishu
STI clinic
Conv
STI clinic attendees
50
0
NR
NR
Burans, 1990 [105]
NR
Mogadishu
NR
Conv
STI clinic attendees (80% soldiers)
45
0
NR
40% reported contact with FSWs
Corwin, 1991 [107]
1990
Chismayu, Merca, and Mogadishu
NR
Conv
Partners of FSWs
26
0
NR
Partners of FSWs
Duffy, 1999 [142]
1999
Hargeisa
Sent. surv.
Conv
STI clinic attendees
106
0.9
NR
NR
WHO, 2005 [143]
2004
Bossasso
Sent. surv.
Conv
STI clinic attendees
78
1.3
NR
NR
WHO, 2005 [143]
2004
Hargeisa
Sent. surv.
Conv
STI clinic attendees
52
9.6
NR
NR
WHO, 2005 [143]
2004
Mogadishu
Sent. surv.
Conv
STI clinic attendees
46
4.4
NR
NR
UNHCR, 2007 [144]
2006–2007
Dadaab refugee camp
STI clinic
Conv
STI clinic attendees
199
0.5
NR
NR
Ismail, 2007 [145]
2007
Hargeisa
STI clinic
Conv
STI clinic attendees
108
7.4
NR
NR
NAP, 2010 [146]
2007
Puntland
Sent. surv.
Conv
STI clinic attendees
NR
1.5
NR
NR
Sudan
McCarthy, 1989 [147]
1987
Port Sudan and Suakin
NR
Conv
Clients of FSWs
157
0
NR
Subsample including only clients of FSWs
McCarthy, 1989 [148]
1987–1988
Gederef, Port Sudan, Kassala, Omdurman, and Juba
Outpatient military clinics
Conv
Soldiers clients of FSWs
398
2.5
NR
Subsample including only soldiers reporting a history of contact with FSWs
McCarthy, 1995 [109]
NR
Juba, South Sudan
STI clinics
Conv
STI clinic attendees clients of FSWs
37
13.5
NR
Subsample including only men reporting contact with FSWs in the past 10 years
US Cens. Bureau, 2017 [149]
2004
Khartoum
Sent. surv.
Conv
STI clinic attendees
72
1.4
NR
NR
US Cens. Bureau, 2017 [149]
2004
Red Sea
Sent. surv.
Conv
STI clinic attendees
164
1.8
NR
NR
Yemen
Abdol-Quauder, 1993 [150]
1992
Sanaa
STI clinic
Conv
STI clinic attendees
30
0
NR
NR
The table is sorted by year(s) of data collection or year of publication if the year of data collection was not reported
Abbreviations: Cens Census, CI confidence interval, Conv convenience, FSWs female sex workers, MENA HIV ESP MENA HIV/AIDS Epidemiology Synthesis Project, MOH Ministry of Health, NAP National AIDS Program, NR not reported, OMS Organisation Mondiale de la Sante, Predom. predominantly, Prev prevalence, Sent. surv. sentinel surveillance, SRS simple random sampling, STI sexually transmitted infection, SyRS systematic random sampling, UNHCR United Nations Higher Commission for Refugees, VCT voluntary counseling and testing, WHO World Health Organization
*The decimal places of the prevalence figures are as reported in the original reports, but prevalence figures with more than one decimal places were rounded to one decimal place, with the exception of those below 0.1%. Most studies did not report the 95% CIs associated with prevalence

Quality assessment

Additional file 1: Tables S6-S9 show the summarized and study-specific quality assessments for the size estimation and HIV prevalence studies in FSWs and clients. Almost all size estimation studies used clear/valid sex work definitions, and > 70% used rigorous size estimation methodologies. Similarly, > 70% of prevalence studies in FSWs used clear/valid sex work definitions and probability-based sampling for participants’ recruitment. Meanwhile, > 85% of prevalence studies in clients used convenience sampling.
Overall, studies were of reasonable quality. The majority of size estimation studies in FSWs and clients had low ROB on ≥ 2 quality domains (94.4% and 82.1%, respectively), and none had high ROB on ≥ 2 domains. Similarly, 85.0% of prevalence studies in FSWs and 39.4% of studies in clients had low ROB on ≥ 2 domains (studies among STI clinic attendees mostly used convenience sampling, and few reported on contact with FSWs), while 0.7% and 6.1% had high ROB on ≥ 2 domains, respectively.

Pooled mean HIV prevalence

The pooled mean HIV prevalence for the MENA region was 1.4% (95% confidence interval (CI) = 1.1–1.8%) in FSWs and 0.4% (95% CI = 0.1–0.7%) in clients (Table 5). A difference was observed between the median prevalence and the pooled mean prevalence due to the high clustering of prevalence measures close to zero.
Table 5
Results of meta-analyses on studies reporting HIV prevalence in FSWs and their clients (or proxy populations of clients such as male STI clinic attendees) in the Middle East and North Africa (MENA) by epidemic type
  
Country
Studies (N)
Samples
HIV prevalence
Pooled mean HIV prevalence**
Heterogeneity measures
Tested
HIV positive
Median* (%)
Range* (%)
%
95% CI
Q (p value)
I2‡ (%; 95% CI)
Prediction interval£ (95%)
FSWs
Low-level
Afghanistan
9
3578
7
0
0–0.90
0.03
0.00–0.18
7.59 (p = 0.4744)
0.0 (0.0–62.9)
0.00–0.22
Bahrain
1
724
6
0.83
0.83¥
0.30–1.80
Egypt
33
7222
16
0
0–1.49
0.03
0.00–0.14
36.26 (p = 0.2765)
12.8 (0.0–43.4)
0.00–0.34
Iran
32
17,277
211
0.02
0–14.00
0.99
0.34–1.88
569.63 (p < 0.0001)
94.6 (93.2–95.6)
0.00–8.84
Iraq
29
15,852
1
0
0–0.07
0.00
0.00–0.00
6.24 (p = 1.0000)
0.0 (0.0–0.0)
0.00–0.00
Jordan
7
1024
4
0
0–1.33
0.00
0.00–0.31
3.43 (p = 0.7537)
0.0 (0.0–48.9)
0.00–0.48
Lebanon
11
11,589
12
0.07
0–2.40
0.00
0.00–0.07
18.82 (p = 0.0426)
46.9 (0.0–73.6)
0.00–0.33
Pakistan
81
26,678
217
0
0–8.80
0.35
0.18–0.57
368.57 (p < 0.0001)
78.3 (73.3–82.3)
0.00–3.06
Syria
56
97,071
12
0
0–0.20
0.00
0.00–0.00
32.37 (p = 0.9936)
0.0 (0.0–0.0)
0.00–0.00
Tunisia
53
22,224
59
0
0–2.30
0.02
0.00–0.11
124.81 (p < 0.0001)
58.3 (43.6–69.2)
0.00–0.89
Yemen
10
1767
34
0.25
0–7.00
0.82
0.00–2.91
63.01 (p < 0.0001)
85.7 (75.6–91.7)
0.00–11.67
Intermediate-intensity
Algeria
33
4241
179
2.00
0–20.00
2.39
1.02–4.15
215.22 (p < 0.0001)
85.1 (80.1–88.9)
0.00–15.05
Libya
4
1249
28
8.43
1.08–18.18
4.86
0.81–11.37
34.41 (p < 0.0001)
91.3 (80.8–96.0)
0.00–47.09
Morocco
200
40,507
804
1.07
0–52.90
1.11
0.83–1.41
851.66 (p < 0.0001)
76.6 (73.3–79.6)
0.00–5.98
Somalia
17
2015
57
0.35
0–47.06
1.64
0.42–3.39
61.50 (p < 0.0001)
74.0 (57.7–83.8)
0.00–10.24
Sudan
22
7207
128
0.95
0–7.70
1.30
0.76–1.96
98.06 (p < 0.0001)
78.6 (68.1–85.6)
0.00–5.26
Concentrated
Djibouti
68
22,028
4618
18.75
0–70.00
17.89
13.62–22.60
5127.36 (p < 0.0001)
98.7 (98.6–98.8)
0.00–63.91
South Sudan
8
5466
1108
18.50
2.82–37.90
17.32
8.66–28.14
554.81 (p < 0.0001)
98.7 (98.3–99.1)
0.00–61.99
All countries
674
287,719
7501
0.26
0–70.00
1.44
1.14–1.76
24,605.29 (p < 0.0001)
97.3 (97.2–97.4)
0.00–16.49
Clients of FSWs
Low-level
Egypt
6
1362
3
0.17
0–0.80
0.09
0.00–0.42
4.82 (p = 0.4386)
0.0 (0.0–73.7)
0.00–0.60
Kuwait
6
6505
1
0
0–0.02
0.00
0.00–0.04
0.36 (p = 0.9963)
0.0 (0.0–0.0)
0.00–0.07
Pakistan
12
6498
9
0
0–1.10
0.00
0.00–0.10
14.93 (p = 0.1857)
26.3 (0.0–62.6)
0.00–0.42
Yemen
1
30
0
0
0.00¥
0.00–11.57
Intermediate-intensity
Algeria
7
728
22
7.29
0–25.80
3.51
0.32–8.90
39.79 (p < 0.0001)
84.9 (70.8–92.2)
0.00–27.63
Morocco
84
10,348
47
0
0–8.00
0.00
0.00–0.05
76.30 (p = 0.6854)
0.0 (0.0–19.9)
0.00–0.05
Somalia
11
1010
21
0.94
0–9.62
1.38
0.25–3.11
25.74 (p = 0.0041)
61.1 (25.0–79.9)
0.00–8.46
Sudan
4
791
14
1.61
0–2.51
1.22
0.16–2.97
7.02 (p = 0.0711)
57.3 (0.0–85.8)
0.00–11.65
Concentrated
Djibouti
15
2222
217
2.20
0–34.60
5.36
1.53–10.81
244.98 (p < 0.0001)
94.3 (92.0–95.9)
0.00–35.23
South Sudan
1
37
5
13.5
13.5¥
4.54–28.77
All countries
147
29,531
339
0
0–34.60
0.38
0.14–0.71
977.96 (p < 0.0001)
85.1 (82.9–87.0)
0.00–6.60
Abbreviations: CI confidence interval, FSWs female sex workers
*These medians and ranges are calculated on the stratified HIV prevalence measures
**Missing sample sizes for measures (or their strata) were imputed using median sample size calculated from studies with available information. Analyses excluding these studies had no impact on study findings
Q—the Cochran’s Q statistic is a measure assessing the existence of heterogeneity in effect size (here, HIV prevalence) across studies
I2—a measure assessing the magnitude of between-study variation that is due to the differences in effect size (here, HIV prevalence) across studies rather than chance
£Prediction interval—a measure estimating the 95% interval of the distribution of true effect sizes (here, HIV prevalence)
Based on results of meta-analyses for FSWs, countries were classified as having low-level HIV epidemic (prevalence < 1%), intermediate-intensity HIV epidemic (prevalence 1–5%), and concentrated HIV epidemic (prevalence > 5%)
¥Point estimate as only one study was available
Before 2011, South Sudan was part of Sudan, and thus, earlier measures from Sudan were based on studies that may have included participants from both Sudan and South Sudan
In FSWs, the national-level pooled mean prevalence was 0 or < 1% in most countries (low-level epidemics); between 1 and 5% (intermediate-intensity epidemics) in Algeria, Libya, Morocco, Somalia, and Sudan; and > 5% (concentrated epidemics) in Djibouti (17.9%, 95% CI = 13.6–22.6%) and South Sudan (17.3%, 95% CI = 8.7–28.1%).
In clients/male STI clinic attendees, the national-level pooled mean prevalence was mostly 0 or < 1%. However, high prevalence was estimated in Djibouti (5.4%, 95% CI = 1.5–10.8%) and South Sudan (13.5%, 95% CI = 4.5–28.8%).
There was evidence for the heterogeneity in effect size (prevalence) in meta-analyses. p value for Cochran’s Q statistic was mostly < 0.0001, prediction intervals were wide, and I2 was often > 50% indicating that most between-study variability is due to the true differences in prevalence across studies rather than chance.

Associations with prevalence, sources of between-study heterogeneity, and temporal trend

Univariable meta-regressions for FSWs demonstrated strong evidence for an association with odds for subregion, population type, sample size, year of data collection, and response rate (Table 6). Meanwhile, there was poor evidence for an association with sampling methodology, validity of sex work definition, and HIV ascertainment, which were hence dismissed from inclusion in the multivariable model. Most variability in odds was explained by subregion (adjusted R2 = 39.8%).
Table 6
Results of meta-regression analyses to identify associations with HIV prevalence, sources of between-study heterogeneity, and trend in HIV prevalence in FSWs in the Middle East and North Africa (MENA)
Variables
 
Studies
Samples
Univariable analyses
Multivariable analysis
Total N
Total N
OR (95% CI)
LR test p value
Variance explained R (%)
AOR (95% CI)
p value
LR test p value¥
Country/subregion*
         
 Eastern MENA
Afghanistan, Iran, Pakistan
122
47,533
1.00
< 0.001
39.80
1.00
 
< 0.001
 Fertile Crescent
Egypt, Iraq, Jordan, Lebanon, Syria
136
132,758
0.17 (0.10–0.27)
  
0.21 (0.12–0.36)
< 0.001
 
 Bahrain and Yemen
Bahrain and Yemen
11
2491
2.60 (0.78–8.67)
  
1.77 (0.52–6.01)
0.357
 
 Horn of Africa
Djibouti, Somalia, South Sudan
93
29,509
33.45 (19.77–56.58)
  
45.43 (24.66–83.68)
< 0.001
 
 North Africa
Algeria, Libya, Morocco, Sudan, Tunisia
312
75,428
3.14 (2.09–4.72)
  
2.90 (1.80–4.68)
< 0.001
 
Population type
Street-based, venue-based, and other FSWs
619
220,363
1.00
0.002
1.29
1.00
 
0.163
Bar girls
55
67,356
0.33 (0.17–0.67)
  
0.66 (0.37–1.18)
0.163
 
Total sample size of tested FSWs
< 100 participants
75
4008
1.00
0.001
1.54
1.00
 
< 0.001
≥ 100 participants
599
283,711
0.36 (0.20–0.65)
  
0.35 (0.21–0.56)
< 0.001
 
Median year of data collection**
< 1993
104
36,038
1.00
0.001
1.96
1.00
 
0.005
1993–2002
169
98,221
0.31 (0.17–0.56)
  
1.18 (0.71–1.95)
0.522
 
≥ 2003
401
153,460
0.57 (0.33–0.97)
  
2.03 (1.24–3.33)
0.005
 
Sampling methodology
Non-probability sampling
570
254,072
1.00
0.217
0.08
Probability-based sampling
104
33,647
0.72 (0.42–1.21)
  
Response rate
≥ 60%
96
31,161
1.00
0.043
0.64
1.00
 
0.544
< 60%/unclear
62
14,102
2.76 (1.24–6.13)
  
1.17 (0.60–2.27)
0.645
 
Not applicable
516
242,456
1.37 (0.80–2.37)
  
1.33 (0.79–2.23)
0.279
 
Validity of sex work definition
Clear and valid definition
117
36,431
1.00
0.161
0.25
Poorly defined/unclear
41
8832
2.35 (0.96–5.73)
  
Not applicable
516
242,456
1.15 (0.70–1.90)
  
HIV ascertainment
Biological assays
157
44,894
1.00
0.786
0
Self-report, unclear, and not applicable
517
242,825
0.94 (0.60–1.47)
  
Abbreviations: AOR adjusted odds ratio, CI confidence interval, FSWs female sex workers, LR likelihood ratio, OR odds ratio
*Countries were grouped based on geography and similarity in HIV prevalence levels. Given the large fraction of studies with zero HIV prevalence, particularly in the Fertile Crescent, an increment of 0.1 was added to a number of events in all studies when generating log odds, and Eastern MENA was thus used also as a statistically better reference. While this choice of increment was arbitrary, other increments yielded the same findings, though some of the effect sizes changed in scale
**Year grouping was driven by independent evidence identifying the emergence of HIV epidemics among both men who have sex with men [10] and people who inject drugs [11] in multiple MENA countries around 2003. Missing values for year of data collection (only six stratified measures) were imputed using data for year of publication adjusted by the median difference between year of publication and median year of data collection (for studies with complete information)
A large fraction of studies did not separate the different forms of female sex workers, and thus it was not possible to analyze these as separate categories
Measures extracted only from routine databases with no reports describing the study methodology were not included in the ROB assessment
Predictors with p value ≤ 0.1 were considered as showing strong evidence for an association with (prevalence) odds and were hence included in the multivariable analysis
£Adjusted R2 in the final multivariable model = 49.21%
¥Predictors with p value ≤ 0.1 in the multivariable model were considered as showing strong evidence for an association with (prevalence) odds
Multivariable analysis indicated strong subregional differences and explained 49.2% of the variation (Table 6). Compared to Eastern MENA, the adjusted odds ratio (AOR) ranged from 0.2 (95% CI = 0.1–0.4) for the Fertile Crescent to 45.4 (95% CI = 24.7–83.7) for the Horn of Africa. Studies with a larger sample size (≥ 100) showed lower odds (AOR = 0.4, 95% CI = 0.2–0.6).
Compared with studies with data collection pre-1993, studies conducted after 2003 showed strong evidence for higher odds (AOR = 2.0, 95% CI = 1.2–3.3). Notably, the trend of increasing odds was evident only after controlling for the strong confounding effect of the subregion. The trend for each subregion was also overall increasing, though the strength of evidence varied across subregions (not shown). Including the year of data collection as a linear term, instead of a categorical variable, using only post-2003 data indicated strong evidence for increasing HIV odds (AOR = 1.15, 95% CI = 1.09–1.21, p < 0.0001; not shown). No association was found with the population type or response rate.
Meta-regression analyses for clients demonstrated similar results to those of FSWs, but with wider CIs considering the smaller number of prevalence studies (Additional file 1: Table S10). There was evidence that subregion was associated with HIV odds in clients, but no evidence that sample size or year of data collection explained the between-study heterogeneity.

Sex work context and sexual and injecting risk behaviors

For the detailed sex work context and behavioral measures, we provide here (for brevity) only a high-level summary of key measures.

Sex work context

Across studies, the mean age of FSWs ranged from 19.5 to 37.4, with a median of 27.8 years. Mean age at sexual debut ranged from 14.0 to 22.5 years (median = 17.5), and mean age at sex work initiation ranged from 17.5 to 27.5 years (median = 22.7). Mean duration of sex work ranged from 0.7 to 14.3 years (median = 5.5). A median of 28.0% (range = 0.9–76.6%) of FSWs were single, 30.1% (range = 0–65.5%) were divorced, and 7.0% (range = 0–27.2%) were widowed.

Reported condom use

There was high heterogeneity in reported condom use among FSWs by sexual partnership type and across and within countries (Additional file 1: Table S11). Condom use at last sex with clients ranged from 1.2 to 94.8% (median = 44.0%). Consistent condom use with clients ranged from 0 to 95.2% (median = 26.3%) among all FSWs and from 38.2 to 45.3% (median = 42.3%) among FSWs reporting condom use with clients.
Median condom use at last sex with regular clients was 55.9% (range = 25.5–92.0%) and that with one-time clients was 58.3% (range = 28.5–96.0%). Less condom use at last sex was found with non-paying partners (median = 22.0%, range = 4.9–78.3%). There was also variability in condom use at last anal sex (range = 0–86.5%), though low levels were generally reported (median = 18.5%).
The median fraction of FSWs who reported having a condom at the time of study interview was 12.5% (range = 0–66.1%).

Clients and partners

Studies varied immensely in types of measures reporting data on clients and partners. Some reported a mean number of regular/non-regular clients, but over various time frames. Others reported different distributions for the number of clients (and by client type), also over various time frames. Summarizing the evidence was therefore challenging, given the large type of measure variability.
This being said, the mean number of clients in the past month ranged from 4.4 to 114.0, with a median of 34.0 clients. Median fraction of FSWs reporting (during the past month) < 5 clients, 5–9 clients, and 10+ clients was 28.5%, 28.1%, and 19.1%, respectively. FSWs were equally likely to report regular and one-time clients during the past month (medians = 80.0% and 81.0%, ranges = 54.3–92.4% and 59.2–97.5%, respectively).
FSWs reported a distribution of sex acts in the past week, with a median of 41.2% reporting 1–2 acts, 32.0% reporting 3–4 acts, and 12.9% reporting 5+ acts. Anal sex with clients in the past month was reported by a median of 8.0% (range = 2.3–100%).
Median fraction of FSWs that are married/cohabiting was 45.3% (range = 0–99.6%), while that of FSWs reporting non-paying partners was 48.5% (range = 6.8–86.2%). The mean number of non-paying partners in the past month ranged between 1 and 3, with about two thirds reporting only one partner.
Only few studies investigated group sex: 7.7% [90] of FSWs reported ever engaging in group sex, 6.2% [68] and 12.9% [68] reported group sex in the past month, and 10.0% [58] in the past week.

Injecting risk behavior, sex with PWID, and substance use

There was a large variability in injecting risk behavior and substance use among FSWs, but the highest levels of injecting drug use were reported in Iran and Pakistan (Additional file 1: Table S12). Median of current/recent injecting drug use was 2.1% (range = 0–26.6%), but the majority of studies were from Pakistan. Studies in Iran reported a history of injecting drug use in the range of 6.1–18.0% (median of 13.6%) among all FSWs and range of 16.4–25.5% (median of 22.3%) among only ever/active drug users. A history of injecting drug use was reported by < 1% (median) of all FSWs (range = 0%–11.8%) in the rest of MENA countries.
Fraction of FSWs reporting current/recent sex with PWID ranged from 0.5 to 13.6% within Afghanistan and 0–54.9% within Pakistan, with medians of 5.2% and 5.6%, respectively. Sex with PWID was reported at 23.6% [93] among FSWs in Iran.
Close to a third of FSWs reported ever using drugs (median = 27.0%, range = 1.7–90.7%). A median of 8.9% reported current/recent drug use (range = 0.6–59.0%). Any substance use before/during sex was reported by 37.8% (median, range = 1.0–88.1%). Alcohol use before/during sex was reported by 44.1% (median, range = 3.0–70.7%).

Knowledge of HIV/AIDS and perception of risk

Knowledge of HIV/AIDS was generally high among FSWs across MENA (Additional file 1: Table S13). Vast majority of FSWs ever heard of HIV (median = 81.9%, range = 25.4–100%) and were aware of sexual (median = 72.0%, range = 50.8–94.9%) and injecting (median = 88.7%, range = 11.5–99.6%) modes of transmission, but to a lesser extent of condoms as a prevention method (median = 51.6%, range = 14.1–89.8%)—condoms were more perceived as a contraception method. Levels of knowledge, however, varied often substantially within the same country.
Overall, FSWs did not perceive themselves at high risk of HIV acquisition (Additional file 1: Table S14). Perception of HIV risk was reported as at-risk (median = 34.6%, range = 22.8–48.5), low-risk (median = 18.3%, range = 7.1–46.9), medium-risk (median = 16.4%, range = 5.3–36.1), and high-risk (median = 14.4%, range = 5.9–32.0).

HIV testing

HIV testing among FSWs varied across countries, but was generally low, with a median fraction of 17.6% (range = 4.0–99.4%) ever tested for HIV (Additional file 1: Table S15). Only a median of 12.1% (range = 0.9–38.0%) of all FSWs tested for HIV in the past 12 months, and nearly two thirds of those who ever tested did so in the past 12 months (median = 59.2%, range = 33.3–82.0%). Majority of FSWs who ever tested were aware of their status (median = 91.9%, range = 60.0–99.0%).

Discussion

Through an extensive, systematic, and comprehensive assessment of HIV epidemiology among FSWs and clients, including data presented in the scientific literature for the first time, we found that HIV epidemics among FSWs have already emerged in MENA, and some appear to have reached their peak. Based on a synthesis and triangulation of evidence from studies on a total of 300,000 FSWs and 30,000 clients, a strong regionalization of epidemics has been identified. In Djibouti and South Sudan, the HIV epidemic is concentrated with a prevalence of ~ 20% in FSWs. In Algeria, Libya, Morocco, Somalia, and Sudan, the epidemic is of intermediate-intensity (prevalence 1–5%). Strikingly, in the remaining countries with available data, the prevalence is < 1%, and most often zero.
A key finding is that HIV prevalence in FSWs has been (overall) growing steadily since 2003. This is the same time in which independent evidence has identified the emergence of major epidemics among both PWID [11] and MSM [10] in MENA. It is probable that the epidemics among these key populations have been bridged to FSWs. An example is Pakistan, where the prevalence among FSWs was < 1% in almost all cities in three consecutive IBBSS rounds between 2005 and 2012 [38, 40, 69]. However, prevalence ranging from 1.5 to 8.8% was documented in half of the cities in the latest round in 2016–2017 [42]. These emerging epidemics among FSWs were preceded by large and growing epidemics first among PWID [11] and then among MSM [10, 11].
Some of the FSW epidemics, particularly those in Djibouti and South Sudan, emerged much earlier, most likely by late 1980s [6], mainly affected by geographic proximity and stronger population links to sub-Saharan Africa (SSA) [6]. Djibouti is a port country and the major trade route for Ethiopia and a station for large international military bases [6, 151]. The majority of FSWs operating in Djibouti are Ethiopians catering to the Ethiopian truck drivers transporting shipments from the Djibouti port [8486]. South Sudan is socio-culturally part of SSA, with a major fraction of FSWs coming from Uganda, Congo, and Kenya [79]. In these MENA countries, HIV in commercial heterosexual sex networks (CHSNs) is well-established and epidemics are concentrated—though at levels lower than the hyper-endemic epidemics observed in SSA [152].
Unlike the epidemics among PWID and MSM [10, 11], the FSW epidemics have been overall growing rather slowly, with the prevalence being mostly < 5%. Strikingly, a considerable fraction of countries still do not appear to have much HIV transmission in CHSNs, with consistently very low prevalence, quite often even at zero level—46.8% of studies in FSWs reported zero prevalence, and 7 out of 18 countries had a pooled mean prevalence of zero or nearly zero. One explanation for the observed low HIV prevalence could be that HIV has not yet been effectively introduced into CHSNs—it took decades for HIV to be effectively introduced into PWID [11] and MSM [10] networks. Another possible factor pertains to the structure of CHSNs, characterized apparently by low connectivity [6, 153, 154], which reduces the risk of HIV being introduced, or efficiently/sustainably transmitted. Unlike PWID and MSM, FSWs are also exposed to HIV mainly through their clients, who have a lower risk of exposure to HIV than themselves, thus possibly contributing to slower epidemic growth [6].
Other factors may also contribute to explaining the observed low HIV prevalence. The synthesized evidence suggests a lower risk environment for FSWs in MENA, compared to other regions. The reported number of clients is rather low at a median of 34 per month, at the lower end of global range [155158]. Close to half of commercial sex acts are protected through condom use, with no difference between regular and one-time clients, despite noted variability across and within countries. HIV/AIDS knowledge also varies, but is generally substantial, with the majority of FSWs being aware of sexual and injecting modes of transmission, and over half are aware of condoms as a prevention method. Injecting drug use and sex with PWID is low in most countries, except for countries in Eastern MENA, notably Afghanistan, Iran, and Pakistan. Serological markers for hepatitis C virus (a marker of injecting risk) [159161] are also low in FSWs, assessed at a median of 1.1% (range = 0–9.9%, not shown), with the highest measures reported in Iran [61, 162]. These relatively lower levels of risk behavior than other regions [163165] stand in contrast to what has been observed in PWID and MSM in MENA [10, 11].
Importantly, with the efficacy of 60% in randomized clinical trials [166169], male circumcision, which is essentially at universal coverage across MENA [170], may have also slowed, or even substantially reduced HIV transmission in CHSNs leading to the observed low HIV prevalence [171]. Incidentally, the two most affected countries—South Sudan and Djibouti—are nearly the only two major settings where male circumcision is at low coverage in MENA, either nationally, as is the case for South Sudan [170], or among clients of FSWs, as is the case for Ethiopian truckers and international military personnel stationed in Djibouti [151, 170]. Though HIV prevalence will probably continue to increase among FSWs and clients, the high levels of male circumcision coupled with lower levels of risk behavior may prevent significant epidemics, as seen elsewhere [172174], from materializing in CHSNs in multiple MENA countries.
HIV prevalence in FSWs in few countries, particularly in Eastern MENA, may not necessarily reflect heterosexual as much as iatrogenic exposures through injecting drug use. Specifically, in Iran and Pakistan, countries with large HIV epidemics among PWID [11], a considerable fraction of FSWs report current/recent/history (14% in Iran and 2% in Pakistan) of injecting drug use. High prevalence of sex work is also reported in women engaging in injecting drug use [93, 175, 176]. Current/recent/history of sex with PWID is also common (24% in Iran and 6% in Pakistan). The overlap between these key populations suggests a potential for HIV to be bridged from PWID networks to CHSNs, as seem to have occurred in Pakistan recently [42, 177, 178].
Population proportion of current/recent FSWs ranged from 0.2 to 2.4% across studies with a median of 0.6%, while that of current/recent clients ranged from 0.3 to 13.8% with a median of 5.7%, both on the lower end of global range [179, 180]. Though these population proportions may seem small, the size of CHSNs is much larger than that of PWID and MSM [10, 11, 181]. This suggests that CHSNs could be a main driver of HIV incidence in many countries despite the low HIV prevalence in FSWs. An example is Morocco where the mode of transmission analyses estimated that over half of HIV incidence is driven by CHSNs, despite an HIV prevalence of only ~ 2% in FSWs [182184]. The role of CHSNs is even more significant in countries with concentrated epidemics. In Djibouti, for example, the large HIV epidemic among FSWs was mirrored shortly after by a rapid rise in prevalence among clients (as proxied by male STI clinic attendees; Table 4), leading eventually to a prevalence > 1% in pregnant women [6].
HIV response to the epidemic in CHSNs in MENA continues to be weak and limited in scope and scale [185]. Criminality [151, 185] and stigma [186188] associated with sex work persist as barriers to surveillance and targeted programming [189191], leading even to the resistance to acknowledge the existence of sex work [192]. These challenges are compounded by the diverse typologies and increased mobility of FSWs [41, 70, 151]. Across MENA, only 18% of FSWs reported ever testing for HIV, and fewer (12%) reported testing in the past 12 months, far below the 90% service coverage target of “UNAIDS 2016–2021 Strategy” [193]. Programs, including healthcare provision, where they exist, are nearly always implemented by non-governmental organizations (NGOs), who often lack the resources or legal coverage to deliver comprehensive prevention interventions [6, 185].
There are, however, notable exceptions. Morocco has established an evidence-informed national strategy and rapidly scaled up provision of comprehensive services for at-risk populations, including outreach peer education programs as well as testing and case management services [183, 185]. Voluntary counseling and testing centers were established nationwide, with FSWs estimated to constitute about a quarter of attendees in 2007 [183, 194]. Findings of the 2011–2012 IBBSS indicated that over a third of FSWs ever tested for HIV, the vast majority of whom were aware of their status [67]. Condom use at last sex also increased from 37% in 2003 to a median of 50% in 2011 (Additional file 1: Table S11). Morocco’s success has been grounded on a strong multisectorial response where NGOs, in partnership with the government, play a leading role in implementing interventions [185]. In Iran, the large expansion of harm reduction services, including the first women-operated services in MENA [11], is a promising step for targeting FSWs most at risk.
This study is limited by gaps in evidence. Epidemic status among FSWs remains unknown in six countries, as no data were identified. Others (Bahrain and Libya) also had limited data to warrant a meaningful characterization of the epidemic. The high heterogeneity of epidemics within countries suggests that caution is needed when interpreting data without a representative national coverage. For instance, while concentrated epidemics among FSWs are documented in southern Morocco [67, 195] and southern Algeria [113, 196198], these do not appear to be representative of FSWs at the national level [42, 67, 74, 78, 81, 82, 113, 195199]. Hidden epidemics or outbreaks may also exist in specific geographies within the country, but not necessarily elsewhere. Data varied over time with high quality and volume of evidence available mostly post-2000, thanks to the expansion and funding of IBBSS studies. While the pooled prevalence estimates were meant to provide a summary of the relative standing of MENA countries in the HIV epidemic, the large between-study heterogeneity suggests that caution is warranted when interpreting these estimates. Studies in clients of FSWs/proxy populations remain limited with wide variability in evidence availability across MENA.
A considerable fraction of studies used convenience sampling, although meta-regression indicated no difference in the prevalence by sampling methodology. This may be explained by FSWs being more “visible” [151, 200] compared to PWID [11] and MSM [10]. A sizable fraction of studies was from routine data reporting with no sufficient documentation of study methodology. However, most of these country-level program data were presumably based on rigorous case definitions following WHO guidelines [6]. There is also a possibility that a fraction of studies may have enrolled women without a strict and valid definition for sex work, yet meta-regression findings showed no effect for the validity of sex work definition on HIV prevalence. There was also no evidence that other study-specific quality domains, including HIV ascertainment method and response rate, had an effect on prevalence. A considerable fraction of studies reported zero prevalence, thus an increment of 0.1 was added to a number of events to be able to conduct the meta-regressions. While this choice of increment was arbitrary, other increments yielded the same findings, though some of the effect sizes changed in scale. There was evidence for a small-study effect in meta-regression suggesting potential publication bias towards studies reporting higher prevalence.

Conclusions

HIV epidemics among FSWs are emerging in MENA, with some already established. The epidemic has been growing steadily in recent years, with strong regionalization and heterogeneity. A contributing factor to epidemic growth appears to be the epidemics that emerged among PWID [11] and MSM [10] nearly two decades ago. Strikingly, a large fraction of countries still do not appear to have any significant epidemic dynamics in CHSNs. These findings demonstrate the need for expanding surveillance systems, including the conduct of repeated IBBSS studies with national coverage to monitor HIV prevalence trends and to detect the emergence of epidemics. There is also a pressing need for mapping and size estimation studies to delineate the diverse typologies of sex work and to ensure evidence-informed response with adequate coverage of interventions.
Achieving “UNAIDS 2016–2021 Strategy” [193] service coverage targets entails reaching out to the increasingly dispersed FSW population [41, 70, 151]. Building on Morocco’s success, this would be best achieved through NGOs leading the provision of comprehensive interventions, with governmental support, even if discrete. Extending harm reduction services to women PWID is also critical to curb HIV burden in FSWs most at risk, specifically in Eastern MENA. The window of opportunity for detecting epidemics at their nascence, and for controlling incidence in CHSNs, should not be missed.

Acknowledgements

The authors would like to thank Dr. Sara L. Thomas for her guidance in devising the search strategy. The authors would also like to thank Ms. Adona Canlas for her assistance in locating full texts of articles and Ms. Sarwat Mahmud for her help in generating the Middle East and North Africa regional map. The publication of this article was funded by the Qatar National Library.
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Competing interests

The authors declare that they have no competing interests.
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Metadaten
Titel
HIV epidemiology among female sex workers and their clients in the Middle East and North Africa: systematic review, meta-analyses, and meta-regressions
Publikationsdatum
01.12.2019
Erschienen in
BMC Medicine / Ausgabe 1/2019
Elektronische ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-019-1349-y

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