Intersecting Structural Vulnerabilities and Health Risks: A Quantitative Epidemiological Study of HIV and STI Burden Among African Migrant Male Sex Workers in Italy " BSGH 027
GamjiRabiuAbu-Ba’are1,2,3Email
OsmanWumpiniShamrock1Email
SamiraShirzaeiNichols5Email
DelaliHenryDakpui1Email
MubarikSenaSaaka1Email
GiovanniZardini6
DonaldsonConserve7EmailEmail
LaRonE.Nelson8
1Behavioral, Sexual, and Global Health Lab, School of NursingUniversity of Rochester Medical CenterRochesterNew YorkUnited States
2Department of Public Health SciencesUniversity of Rochester Medical CenterRochesterNew YorkUnited States
3Center for Interdisciplinary Research on AIDS, School of Public HealthYale UniversityNew Haven, ConnecticutUnited States
4
A
A
A
School of Nusring and Health SciencesUniversity of Maimi
5Department of Computer Information Systems & Analytics, College of BusinessUniversity of Central ArkansasArkansasUnited States
6Pink RefugeesCity of VeronaVeronaItaly
7Milken Institute School Of Public Health, George Washinton UniversityWashintonDCUnite States
8School of NursingYale UniversityWest HavenUSA
Gamji Rabiu Abu-Ba’are1,2,3 Osman Wumpini Shamrock1, Samira Shirzaei Nichols5, Delali Henry Dakpui1, Mubarik Sena Saaka1, Giovanni Zardini6, Donaldson Conserve7, LaRon E. Nelson8
1. Behavioral, Sexual, and Global Health Lab, School of Nursing, University of Rochester Medical Center, Rochester, New York, United States
2. Department of Public Health Sciences, University of Rochester Medical Center, Rochester, New York, United States
3. Center for Interdisciplinary Research on AIDS, School of Public Health, Yale University, New Haven, Connecticut, United States
4. University of Maimi, School of Nusring and Health Sciences
5. Department of Computer Information Systems & Analytics, College of Business, University of Central Arkansas, Arkansas, United States
6. Pink Refugees, City of Verona, Verona, Italy
7. Milken Institute School Of Public Health, George Washinton University, Washinton, DC, Unite States
8. School of Nursing, Yale University, West Haven, USA
E-mail addresses of authors:
GRA: gamjirabiu_abubaare@urmc.rochester.edu
OWS: oshamro1@binghamton.edu
SSN: sshirzaei@uca.edu
HDD: henrydelali5@gmail.com
MSS: ismubarik@gmail.com
DC: dconservejr@gwu.edu
LEN: laron.nelson@yale.edu
Abstract
African migrant male sex workers (AMMSWs) remain underrepresented in Europe’s HIV and STI prevention research. This sequential mixed-methods study examined the prevalence and determinants of HIV and sexually transmitted infections (STIs) among 150 AMMSWs in Verona and Turin, Italy. Guided by the structural vulnerability framework, quantitative data were collected via a REDCap mobile survey and analyzed using descriptive statistics, chi-square tests, and Firth’s penalized logistic regression to identify structural and behavioral correlates of HIV and STI testing outcomes.
Among participants, 46.1% who had ever tested for HIV reported a positive result, and 36.0% tested positive for an STI. Firth regression revealed that self-medication as a primary source of care was significantly associated with higher odds of testing HIV negative (AOR = 3.84, 95% CI: 1.26–13.46, p = 0.017). Greater distance to healthcare facilities (≥ 6 km) predicted lower odds of HIV negativity (AOR = 0.41, p = 0.076). For STI outcomes, identifying as gay (AOR = 2.50, 95% CI: 1.08–5.94, p = 0.033) and awareness of HIV/STI services (AOR = 2.29, p = 0.072) were protective, whereas immigration-related healthcare challenges were linked to increased STI positivity (AOR = 0.48, p = 0.071).
A
These results underscore how intersecting structural and behavioral factors, including geographic inaccessibility, stigma, and migration-related barriers, shape health inequities among AMMSWs. Interventions must expand culturally competent, community-led testing, PrEP access, and legal reforms to address the structural drivers sustaining HIV/STI vulnerability.
Keywords:
HIV prevalence
STI burden
African migrant male sex workers
Italy
structural vulnerability
stigma
healthcare access
A
A
A
A
Introduction
The HIV epidemic remains a significant global health problem 1–20. In 2014, the Joint United Nations Program on HIV and AIDS (UNAIDS,2014) set the 90–90–90 targets as part of the Fast-Track strategy towards ending the epidemic by 2030, with 90% of people living with HIV knowing their status, 90% of those aware of their status on antiretroviral therapy (ART), and 90% of people on ART achieving viral suppression 21,22. Recent global indicators are proving this target unachievable22. It is estimated that by 2039, people living with HIV will be peaked at 44.4 million23. This prediction is evident from the intense focus of greater efforts and resources on heterosexual individuals8–18,24. Neglecting a significant key population such as sex workers with its unique sub-groupings (migrant sex workers, male sex workers, sexual minority sex workers 25–28. There is limited data on HIV prevalence and program coverage among high-risk subgroups of sex workers, including those who inject drugs, male and transgender sex workers, street-based and migrant sex workers13,15,17,18,29–31.
Among Africans who migrate to Europe, the main route to the North is via Spain and Italy31,32. Immigrants come to Italy as asylum seekers, legal immigrants, refugees, and irregular arrivals33–36. Given the understudied nature of AMMSW, it is essential to note that men and transgender men are involved in the sex industry across every European country 31,32.
The prevalence of HIV/AIDS and other STIs among AMMSWs in Italy suggests a critical public health concern37–40. Studies have shown the overall HIV prevalence among male sex workers in Italy is significantly influenced by their migrant status, with African migrants often facing barriers to healthcare access, stigma, and discrimination 31,32 In 2014, the estimated HIV prevalence among male sex workers in Italy was approximately 15.7% for migrant populations, compared to 40% among native Italian men who have sex with men (MSM)41. The increased vulnerability of AMMSWs can be attributed to a combination of factors, including limited access to preventive services, lack of awareness regarding HIV transmission, and socio-economic pressures that compel them into high-risk behaviors (HIV and Migration, 2020). It is already established how socio-economic factors such as poverty and lack of housing, among others, compel AMMSW's to engage in riskier sexual behaviors to survive in a new country. For instance, research has also found vast differences in income and rates of HIV among MSWs42–44, further highlighting the diverse experiences and situations relevant to this population. Research has also shown that physical positioning, based on masculine norms, top (insertive/dominant) or bottom (receptive/submissive) plays some part in determining what MSWs charge their clients42,44. Migrant MSM from sub-Saharan Africa (SSA) and other regions outside Europe are highly vulnerable to HIV. According to the European HIV/AIDS surveillance data from 2021, MSM and migrants accounted for, respectively, 40.0% and 42.0% of new HIV diagnoses in the European Economic Area (EEA)45.
When comparing HIV rates among AMMSWs to other key populations in Italy, significant disparities emerge46,47. For instance, the general population in Italy has an estimated HIV prevalence of around 0.2%, which starkly contrasts with the rates observed in key populations such as MSM and female sex workers (FSW)48. Among Italian MSM, the prevalence is reported to be as high as 9.6%, while FSWs exhibit a prevalence rate of approximately 2.5% 41.
A comparative analysis reveals that while AMMSWs face a high prevalence rate of 15.7%, this is lower than that of native Italian MSM but significantly higher than the general population49,50. This analysis suggests that while migrant male sex workers are at risk, they are not the most affected group when compared to native MSM51,52. However, it is essential to recognize that different sociocultural contexts and healthcare access dynamics shape the experiences of these groups.
Furthermore, studies show that HIV incidence rates among heterosexual migrants are alarmingly high46,48. Studies have revealed an HIV incidence rate of up to 64.6% among foreign-born heterosexual individuals compared to 38.4% among native Italians 41. These findings highlight a broader trend where migrant populations, regardless of gender or sexual orientation, experience disproportionately higher rates of HIV infection compared to their Italian counterparts46,53. Interestingly, data on both HIV infection prevalence and incidence may be underestimated due to people's inadequate perception of risk, availability to testing and access to diagnostic services5,24.
Sex workers have historically being stigmatized with male sex workers receiving double stigma, for being a sex worker and the other for homosexuality 31,32. Research has shown that among male sex workers, experiencing stigma is positively associated with anxiety, depression, suicidal ideation, substance use, reduced use of health services, and engagement in HIV-related risk behaviour 31,32. This finding increases the urgency with which more data should be gotten for key populations like MSW, MMSW's and specifically AMMSW's to aid in HIV and STI prevention. Interventions addressing stigma in the context of sex work are therefore critical for addressing the HIV burden faced by sex workers54.
As of the time of writing this paper no reliable data currently exists on the prevalence of HIV and other STIs among AMMSWs in Italy. However, available data focuses on undocumented migrant populations46 and other specific high-risk groups, including female sex workers55–59, migrant transgender women who are sex workers60, and patients with STIs61,62. To address this gap, the present study aims to assess the prevalence of HIV and STIs among AMMSWs in Italy and explore associated factors such as risk behaviors, access to healthcare, and HIV/STI testing practices.
In this study, the structural vulnerability framework was employed conceptually to frame the interrelated social, behavioral, and structural determinants shaping HIV/STI vulnerability. However, the framework was not applied as a statistical or analytic model to measure structural determinants’ interactions quantitatively.
This study aimed to quantify HIV and STI prevalence among AMMSWs in Italy and identify structural and behavioral determinants of infection.
Methodology
Research Design
This study employed a sequential exploratory mixed-methods design grounded in the structural vulnerability framework. The quantitative component assessed the clustering of HIV and STI infections alongside social and structural determinants (e.g., stigma, health insurance, distance to care), while the qualitative component (not presented here) was designed to contextualize how these structurally-driven health conditions manifest in lived experience. The theoretical framework guided variable selection, measurement, and integration by emphasizing the interdependence between biological and social processes. The structural vulnerability framework was applied conceptually to inform the study design and variable relationships, but not as an analytic model. No statistical interaction indices or terms were computed; instead, the framework provided a conceptual structure for understanding how co-occurring social and structural conditions may jointly influence health outcomes.
Participants and Setting
A
A total of 150 participants were recruited for the study. The study was conducted in partnership with Circolo Pink (Pink Refugees), a community-based nonprofit organization with established access to the target population in Italy. Data collection took place in secure, private spaces within Circolo Pink's offices in Verona and at a sister institution in Turin, both in Northern Italy. Eligible participants were those who met the following inclusion criteria: (1) refugee status from a Sub-Saharan African country, (2) current residency in Italy, (3) age 18 years or older, (4) fluency in English or Italian, (5) self-identification as a sex worker, and (6) engagement in sex work within the past six months.
Sampling and Data Collection Procedures
Given the hidden nature of AMMSWs, we employed a purposive sampling technique63, combining respondent-driven sampling64 and snowball recruitment strategy65 through Pink Refugees to effectively reach and recruit eligible participants. Two trained peer-research assistants, who were AMMSWs, facilitated recruitment by identifying and engaging their peers. We used RedCap, a secure mobile survey platform, to collect quantitative data. Data were collected using REDCap (Research Electronic Data Capture), a secure mobile-based platform designed for efficient and confidential data collection.
Data Analysis
Descriptive statistics were used to summarize participants' sociodemographic characteristics. Categorical variables were reported as frequencies and percentages, while continuous variables were presented as means with standard deviations or medians with interquartile ranges, depending on the distribution. Chi-square tests were initially performed to assess associations between HIV testing behavior, HIV status, STI status, and selected independent variables. Variables showing statistical significance at p < 0.05 in bivariate analyses were subsequently included in Firth’s penalized logistic regression to examine factors associated with HIV and STI testing outcomes. This method provides bias-reduced parameter estimates in logistic regression, particularly suitable for small or moderate sample sizes and for data with sparse categories or quasi-complete separation. Traditional maximum likelihood estimation (MLE) can produce inflated standard errors or fail to converge when cell counts are small; therefore, Firth’s approach was chosen to ensure stable and finite estimates of adjusted odds ratios (AORs) and 95% confidence intervals (CIs).
Separate models were estimated for HIV and STI outcomes. In both models, the dependent variable was binary and coded as 1 = tested negative and 0 = tested positive, allowing interpretation of higher AORs as factors associated with increased odds of testing negative (protective effects). Predictors included structural and behavioral covariates such as distance to healthcare facility, health insurance, stigma or discrimination experiences, primary source of care, awareness of HIV/STI services, alcohol and illicit drug use, and willingness to use healthcare services.
Variables were operationalized as follows:
• Healthcare access challenge was measured as a binary variable (Yes/No) indicating whether participants experienced difficulty obtaining medical services due to financial, linguistic, or documentation-related barriers.
• Immigration-related restriction was coded from self-reports of legal precarity, asylum-pending status, or fear of deportation, limiting healthcare access.
• Clustering of socially and structurally-driven health conditions was computed as the co-occurrence of two or more of the following: HIV/STI infection, substance use, and self-reported healthcare discrimination.
Multivariable Firth logistic regression models were conducted to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for factors associated with HIV and STI prevalence. Key predictors included health insurance status, distance to healthcare facilities, stigma or discrimination, substance use, and awareness of HIV/STI services.
A
A
A
A
Funding
The funding for this project came from the National Institute of Mental Health through award P30MH062294 and was managed by the Center for Interdisciplinary Research on AIDS at Yale School of Public Health. The opinions in this work are those of the authors and do not necessarily reflect the views of the Center for Interdisciplinary Research on AIDS at Yale, the National Institute of Mental Health, or the National Institutes of Health.
Table 1
Sociodemographic Characteristics of Respondents
Variable
Frequency (n = 150)
Percent (%)
Age
Mean (30.63) Std (5.86) Range (30) Min-Max (18–48)
Young Adult (18–24)
21
14.0
Adult (25+)
129
86.0
Gender Identity (n = 150)
  
Man
145
96.7
Transgender
3
2.0
Education (n = 150)
  
Primary or less
111
74.0
Secondary or more
39
26.0
Marital Status (n = 150)
  
Unmarried
97
64.7
Married
53
35.3
Number of Children (n = 150)
  
No children
80
53.3
One or more children
70
46.7
Religious Affiliation (n = 150)
  
No religion
25
16.7
Belong to a religion
125
83.3
Rank of Religiosity (n = 150)
  
Not religious
15
10.0
Religious
135
90.0
Length of Stay in Italy (n = 150)
  
A year or less
63
42.0
More than a year
87
58.0
Sexual Orientation (n = 150)
  
Gay
106
70.7
Bisexual
44
29.3
Sex Role (n = 150)
  
Top
63
42.0
Bottom
28
18.7
Versatile (Verse)
59
39.3
Any other job apart from sex work (n = 150)
  
Yes
32
21.3
No
118
78.7
STI/HIV Prevalence and Testing Behaviors
Table 2
STI/HIV Prevalence and Testing Behaviors
Category
Subcategory
Percentage
Count (n)
HIV Testing
Ever Tested
59.3%
89
HIV Testing
Never Tested
40.7%
61
HIV Test Results
Negative
53.9%
48
HIV Test Results
Positive
46.1%
41
STI Testing
Ever Tested
70.0%
105
STI Testing
Never Tested
30.0%
45
HIV Self-Testing
Awareness
44.7%
67
HIV Self-Testing
Uptake (of those aware)
47.7%
32
Table 3
HIV/STI Prevalence among Study Participants (n = 150)
HIV/STI Status
Frequency (n)
Percentages (%)
HIV Positive
41
46.07
Syphilis
14
9.33
Gonorrhoea
18
12.00
Chlamydia
4
2.67
Herpes (HSV-1 and HSV-2)
2
1.33
Human Papillomavirus (HPV)
3
2.00
Hepatitis B
14
9.33
Hepatitis C
6
4.00
Anal Warts
8
5.33
Bivariate Analysis of Factors Associated with HIV Testing among AMMSWs
Table 4
Chi-square Analysis of Factors Associated with HIV Testing among AMMSWs
 
Self-reported HIV Testing (n = 150)
  
Variable
Never Tested (n = 61)
Negative (n = 48)
Positive (n = 41)
χ²
p-value
Age
   
1.80
0.408
Young Adult (18–24)
8.5 (6)
6.7 (9)
5.7 (6)
  
Adult (25+)
52.5 (55)
41.3 (39)
35.3 (35)
  
Education
   
7.76
0.021
Primary or less
45.1 (38)
35.5 (38)
30.3 (35)
  
Secondary or more
15.9 (23)
12.5 (10)
10.7 (6)
  
Marital Status
   
15.39
< 0.001
Single
39.4 (29)
31.0 (40)
26.5 (28)
  
Married
21.6 (32)
17.0 (8)
14.5 (13)
  
Number of Children
   
14.89
0.001
No children
32.5 (21)
25.6 (31)
21.9 (28)
  
One or more children
28.5 (40)
22.4 (17)
19.1 (13)
  
Religion Affiliation
   
1.43
0.490
No religion
10.2 (10)
8.0 (6)
6.8 (3)
  
Belong to a religion
50.8 (51)
40.0 (42)
34.2 (32)
  
Length of Stay in Italy
   
17.50
< 0.001
A year or less
25.6 (14)
20.2 (23)
17.2 (26)
  
More than a year
35.4 (47)
27.8 (25)
23.8 (15)
  
Sexual Orientation
   
6.65
0.036
Gay
43.1 (50)
33.9 (29)
29.0 (27)
  
Bisexual
17.9 (11)
14.1 (19)
12.0 (14)
  
Distance to Healthcare Facility (Km)
   
25.73
< 0.001
1–5 km
29.7 (43)
23.4 (22)
20.0 (8)
  
6 km or more
31.3 (18)
24.6 (26)
21.0 (33)
  
Healthcare frequency
   
4.87
0.088
Never
11.8 (17)
9.3 (6)
7.9 (6)
  
Regular
49.2 (44)
38.7 (42)
33.1 (35)
  
Health Insurance Status
   
27.62
< 0.001
Yes
23.2 (37)
18.2 (16)
15.6 (4)
  
No
37.8 (24)
29.8 (32)
25.4 (37)
  
Healthcare access challenge (Because of Immigration status)
   
11.49
0.003
Yes
24.8 (16)
19.5 (28)
16.7 (17)
  
No
36.2 (45)
28.5 (20)
24.3 (24)
  
Experienced stigma/ discrimination at the hospital
   
14.26
0.001
Yes
17.1 (10)
13.4 (23)
11.5 (9)
  
No
43.9 (51)
34.6 (25)
29.5 (32)
  
Primary source of care when you are sick
   
7.32
0.026
Self-medicate
16.3 (17)
12.8 (18)
10.9 (5)
  
Pharmacy/clinic/Hospital
44.7 (44)
35.2 (30)
30.1 (36)
  
Do you know where to go for STI/HIV testing and care?
   
7.84
0.020
Yes
37.8 (42)
29.8 (33)
25.4 (18)
  
No
23.2 (19)
18.2 (15)
15.6 (23)
  
Alcohol Use
   
13.09
0.001
Non-users
49.6 (54)
39.0 (31)
33.3 (37)
  
Users
11.4 (7)
9.0 (17)
7.7 (4)
  
Illicit drug Use
   
8.90
0.012
Non-users
47.2 (51)
37.1 (30)
31.7 (35)
  
Users
13.8 (10)
10.9 (18)
6.0 (6)
  
Sex Role
   
7.25
0.123
Top
25.6 (22)
20.2 (20)
17.2 (21)
  
Bottom
11.4 (12)
9.0 (13)
7.7 (3)
  
Versatile (Verse)
24.0 (27)
18.9 (15)
16.1 (17)
  
Any other job apart from sex work
   
1.50
0.472
Yes
13.0 (10)
10.2 (12)
8.7 (10)
  
No
48.0 (51)
37.8 (36)
32.3 (31)
  
Tested for STI
   
10.07
0.007
Never tested
18.3 (27)
14.4 (9)
12.3 (9)
  
Ever tested
42.7 (34)
33.6 (39)
28.7 (32)
  
Transactional Condom-less sex
   
0.55
0.759
Yes
31.7 (31)
25.0 (27)
21.3 (20)
  
No
29.3 (30)
23.0 (21)
19.7 (21)
  
Number of clients daily
   
3.13
0.209
1–4
42.7 (45)
33.6 (29)
28.7 (31)
  
5 or more
18.3 (16)
14.4 (19)
12.3 (10)
  
Aware of partner's sexual history/STI status before sex
   
17.14
< 0.001
Yes
20.7 (32)
16.3 (13)
13.9 (6)
  
No
40.3 (29)
31.7 (35)
27.1 (35)
  
No. of clients in past 2 months (Men)
   
2.71
0.258
Less than 20
33.3 (38)
26.2 (25)
22.4 (19)
  
20 or more
27.7 (23)
21.8 (23)
18.6 (22)
  
*Values shown as Expected (Observed). χ² = Chi-square statistic. Significant at p-value < 0.05.
Bivariate Analysis of Factors Associated with HIV Prevalence among AMMSWs
Table 5
Factors associated with HIV Prevalence among AMMSW
 
Self-reported HIV Status (n = 89)
  
Variable
Negative (n = 48)
Positive (n = 41)
χ²
p-value
Age
  
0.27
0.605
Young Adult (18–24)
8.1 (9)
6.9 (6)
  
Adult (25+)
39.9 (39)
34.1 (35)
  
Education
  
0.58
0.448
Primary or less
39.4 (38)
33.6 (35)
  
Secondary or more
8.6 (10)
7.4 (6)
  
Marital Status
  
2.77
0.096
Unmarried
36.7 (40)
31.3 (28)
  
Married
11.3 (8)
9.7 (13)
  
Number of Children
  
0.14
0.712
No children
31.8 (31)
27.2 (28)
  
One or more children
16.2 (17)
13.8 (13)
  
Religion Affiliation
  
1.41
0.235
No religion
8.1 (6)
6.9 (9)
  
Belong to a religion
39.9 (42)
34.1 (32)
  
Length of Stay in Italy
  
2.15
0.143
A year or less
26.4 (23)
22.6 (26)
  
More than a year
21.6 (25)
18.4 (15)
  
Sexual Orientation
  
0.28
0.597
Gay
30.2 (29)
25.8 (27)
  
Bisexual
17.8 (19)
15.2 (14)
  
Distance to Healthcare Facility (Km)
  
6.86
0.009
1–5 km
16.2 (22)
13.8 (8)
  
6 km or more
31.8 (26)
27.2 (33)
  
Healthcare frequency
  
0.09
0.769
Never
6.5 (6)
5.5 (6)
  
Regular
41.5 (42)
35.5 (35)
  
Health Insurance Status
  
7.06
0.008
Yes
10.8 (16)
9.2 (4)
  
No
37.2 (32)
31.8 (37)
  
Healthcare access challenge (Immigration status)
  
2.52
0.113
Yes
24.3 (28)
20.7 (17)
  
No
23.7 (20)
20.3 (24)
  
Experienced stigma or discrimination at the hospital
  
6.47
0.011
Yes
17.3 (23)
14.7 (9)
  
No
30.7 (25)
26.3 (32)
  
Primary source of care when you are sick
  
7.39
0.007
Self-medicate
12.4 (18)
10.6 (5)
  
Pharmacy/clinic/Hospital
35.6 (30)
30.4 (36)
  
Do you know where to go for STI/HIV testing and care?
  
5.58
0.018
Yes
27.5 (33)
23.5 (18)
  
No
20.5 (15)
17.5 (23)
  
Alcohol Use
  
8.08
0.004
Non-users
36.7 (31)
31.3 (37)
  
Users
11.3 (17)
9.7 (4)
  
Illicit drug Use
  
5.87
0.015
Non-users
35.1 (30)
29.9 (35)
  
Users
12.9 (18)
11.1 (6)
  
Sex Role
  
5.89
0.053
Top
22.1 (20)
18.9 (21)
  
Bottom
8.6 (13)
7.4 (3)
  
Versatile (Verse)
17.3 (15)
14.7 (17)
  
Any other job apart from sex work
  
0.01
0.947
Yes
11.9 (12)
10.1 (10)
  
No
36.1 (36)
30.9 (31)
  
Tested for STI
  
0.14
0.708
Never tested
9.7 (9)
8.3 (9)
  
Ever tested
38.3 (39)
32.7 (32)
  
Transactional Condom-less sex
  
0.50
0.482
Yes
25.3 (27)
21.7 (20)
  
No
22.7 (21)
19.3 (21)
  
Number of clients daily
  
2.32
0.127
1–4
32.4 (29)
27.6 (31)
  
5 or more
15.6 (19)
13.4 (10)
  
Aware of partner's sexual history/STI status before sex
  
2.04
0.153
Yes
10.2 (13)
8.8 (6)
  
No
37.8 (35)
32.2 (35)
  
No. of clients in past 2 months (Men)
  
0.29
0.589
Less than 20
23.7 (25)
20.3 (19)
  
20 or more
24.3 (23)
20.7 (22)
  
*Values shown as Expected (Observed). χ² = Chi-square statistic. Significant at p-value < 0.05.
Multivariable Analysis (Firth Logistic Regression) for HIV Prevalence among AMMSWs
A multivariable Firth logistic regression model was fitted to identify predictors of testing HIV negative among participants. The outcome variable was coded as 1 = tested negative and 0 = tested positive. Table 6 presents adjusted odds ratios (AORs), 95% confidence intervals (CIs), and p-values for each predictor.
Table 6
Factors associated with HIV testing outcomes
Variable
AOR
95% CI
p-value
Distance to healthcare facility (Farther ≥ 6 km)
0.41
0.15–1.10
0.076
Has health insurance (Yes)
1.57
0.42–6.38
0.503
Experienced stigma or discrimination (Yes)
2.01
0.68–6.23
0.210
Primary source of care: Self-medicate
3.84
1.26–13.46
0.017
Aware of HIV/STI services (Yes)
0.84
0.29–2.45
0.747
Alcohol use (Yes)
0.49
0.11–1.94
0.305
Illicit drug use (Yes)
1.73
0.40–8.38
0.468
Willing to use HIV services (Yes)
2.62
0.88–8.09
0.083
With “tested negative” as the reference outcome (1 = negative, 0 = positive):
• Participants whose primary source of care was self-medication had significantly higher odds of being HIV negative (AOR = 3.84, 95% CI: 1.26–13.46, p = 0.017), indicating a protective association.
• Participants who were willing to use HIV services (AOR = 2.62, p = 0.083) and those who experienced stigma or discrimination (AOR = 2.01, p = 0.210) also had higher odds of being HIV negative, though not statistically significant.
• Conversely, living farther (≥ 6 km) from a healthcare facility was associated with lower odds of being HIV negative (AOR = 0.41, p = 0.076), suggesting higher vulnerability to HIV positivity.
• No significant associations were observed for health insurance, awareness of HIV/STI services, alcohol use, or illicit drug use.
Factors Associated with STI Prevalence Among Male Sex Workers in Italy
The bivariate analysis examined associations between various sociodemographic, behavioral, and healthcare-related factors and the prevalence of sexually transmitted infections (STIs) among 150 male sex workers (MSWs) in Italy. Table 7 summarizes the results.
Several variables demonstrated statistically significant associations with STI status: Marital Status (χ² = 8.36, p = 0.004, number of children (χ² = 4.02, p = 0.045), length of stay in Italy ((χ² = 3.80, p = 0.051), sexual orientation (χ² = 7.10, p = 0.008), healthcare access challenges due to immigration status (χ² = 4.83, p = 0.028), knowledge of where to go for STI/HIV testing and care (χ² = 5.13, p = 0.023), history of STI testing (χ² = 9.75, p = 0.002), transactional condom-less sex (χ² = 6.66, p = 0.010), awareness of partners' sexual history and sti status before sex (χ² = 5.32, p = 0.021), awareness of prep (χ² = 13.57, p < 0.001).
In contrast, several variables did not show statistically significant associations with STI prevalence. These include age, education level, religious affiliation, length of stay in Italy, distance to healthcare facility, healthcare frequency, health insurance status, experience of stigma at healthcare facilities, primary source of care, alcohol use, illicit drug use, sex role, engagement in other jobs, awareness and willingness to use HIV self-testing kits, Number of clients daily or over the past two months, ever use and willingness to use PrEP, and healthcare-seeking behaviors.
Table 7
Factors associated with STI Prevalence among MSW
 
STI Status (n = 142)
  
Variable
Negative (n = 91)
Positive (n = 51)
χ²
p-value
Age
  
0.52
0.473
Young Adult (18–24)
13.9 (12)
7.5 (9)
  
Adult (25+)
77.5 (79)
43.5 (42)
  
Education
  
2.47
0.116
Primary or less
66.0 (62)
37.0 (41)
  
Secondary or more
25.0 (29)
14.0 (10)
  
Marital Status
  
9.20
0.002
Unmarried
58.3 (50)
32.7 (41)
  
Married
32.7 (41)
18.3 (10)
  
Number of Children
  
4.00
0.045
No children
48.7 (43)
27.3 (33)
  
One or more children
42.3 (48)
23.7 (18)
  
Religion Affiliation
  
3.34
0.068
No religion
16.0 (20)
9.0 (5)
  
Belong to a religion
75.0 (71)
42.0 (46)
  
Length of Stay in Italy
  
4.25
0.039
A year or less
37.8 (32)
21.2 (27)
  
More than a year
53.2 (59)
29.8 (24)
  
Sexual Orientation
  
8.81
0.003
Gay
65.4 (73)
36.6 (29)
  
Bisexual
25.6 (18)
14.4 (22)
  
Distance to Healthcare Facility (Km)
  
0.81
0.367
1–5 km
43.6 (41)
24.4 (27)
  
6 km or more
47.4 (50)
26.6 (24)
  
Healthcare frequency
  
2.20
0.138
Never
18.6 (22)
10.4 (7)
  
Regular
72.4 (69)
40.6 (44)
  
Health Insurance Status
  
0.88
0.348
Yes
34.6 (32)
19.4 (22)
  
No
56.4 (59)
31.6 (29)
  
Healthcare access challenge (because of Immigration status)
  
6.77
0.009
Yes
35.2 (28)
19.8 (27)
  
No
55.8 (63)
31.2 (24)
  
Experienced stigma/discrimination at hospital
  
1.60
0.206
Yes
26.3 (23)
14.7 (18)
  
No
64.7 (68)
36.3 (33)
  
Primary source of care
  
3.37
0.066
Self-medicate
24.4 (29)
13.6 (9)
  
Pharmacy/Clinic/Hospital
66.6 (62)
37.4 (42)
  
Knowledge of STI/HIV testing and care
  
4.76
0.029
Yes
57.0 (51)
32.0 (38)
  
No
34.0 (40)
19.0 (13)
  
Alcohol Use
  
0.40
0.561
Non-users
73.7 (75)
41.3 (40)
  
Users
17.3 (16)
9.7 (11)
  
Illicit drug Use
  
3.01
0.083
Non-users
73.1 (77)
40.9 (37)
  
Users
17.9 (14)
10.1 (14)
  
Sex Role
  
1.12
0.571
Top
38.5 (40)
21.5 (20)
  
Bottom
16.7 (18)
9.3 (8)
  
Versatile
35.9 (33)
20.1 (23)
  
Tested for STI
  
11.86
0.001
Never tested
28.8 (38)
16.2 (7)
  
Ever tested
62.2 (53)
34.8 (44)
  
Transactional Condom-less sex
  
6.75
0.009
Yes
47.4 (40)
26.6 (34)
  
No
43.6 (51)
24.4 (17)
  
Number of clients daily
  
0.54
0.463
1–4
64.1 (66)
35.9 (34)
  
5 or more
26.9 (25)
15.1 (17)
  
Aware of partner's sexual history/STI status
  
5.32
0.021
Yes
30.8 (37)
17.2 (11)
  
No
60.2 (54)
33.8 (40)
  
No. of clients in past 2 months (Men)
  
0.05
0.818
Less than 20
49.3 (50)
27.7 (27)
  
20 or more
41.7 (41)
23.3 (24)
  
*Values shown as Expected (Observed). χ² = Chi-square statistic. Significant at p-value < 0.05.
Multivariate analysis (Firth Logistic Regression) for STI Testing Outcome
A multivariable Firth’s penalized logistic regression model was used to identify factors associated with testing STI negative among participants. The outcome variable was coded as 1 = tested STI negative and 0 = tested STI positive. Table 8 presents adjusted odds ratios (AORs), 95% confidence intervals (CIs), and p-values for each predictor.
Table 8
Factors associated with STI testing outcomes
Variable
AOR
95% CI
p-value
Marital status (Single)
0.64
0.25–1.61
0.338
Number of children (One or more)
0.93
0.37–2.29
0.879
Length of stay in Italy (More than 1 year)
1.46
0.63–3.39
0.372
Sexual orientation (Gay)
2.50
1.08–5.94
0.033
Immigration-related healthcare challenge (Yes)
0.48
0.21–1.06
0.071
Awareness of HIV/STI services (Yes)
2.29
0.93–5.99
0.072
Condom use during anal sex (Yes)
0.80
0.26–2.35
0.686
Aware of partner’s STI history (Yes)
2.09
0.82–5.51
0.123
Participants who identified as gay had significantly higher odds of testing STI negative compared to those identifying as bisexual (AOR = 2.50, 95% CI: 1.08–5.94, p = 0.033).
Although not statistically significant, greater odds of testing negative were also observed among those who were aware of HIV/STI services (AOR = 2.29, p = 0.072) and those aware
of their partner’s STI history (AOR = 2.09, p = 0.123).
Conversely, participants reporting immigration-related challenges had lower odds of testing STI negative (AOR = 0.48, p = 0.071), indicating potential increased vulnerability to STI positivity. No significant associations were found for marital status, number of children, length of stay in Italy, or condom use.
These bias-reduced estimates refine the bivariate results, revealing that structural and behavioral factors jointly influence HIV and STI outcomes among African migrant male sex workers in Italy.
Discussion
Conceptually informed by the structural vulnerability framework, but not analytically modeled as such, this study interprets the interlinkages between HIV/STI outcomes and structural vulnerabilities through a theoretical lens rather than a formal statistical framework. The coexistence of infectious diseases, stigma, and limited healthcare access exemplifies a process shaped by social determinants of health, in which structural and behavioral conditions interact to magnify risk. Quantitative evidence, such as the association between lack of insurance and HIV positivity, illustrates the structural determinants underlying the observed health inequities, while behavioral factors (e.g., substance use, condomless sex) reflect reinforcing mechanisms that sustain disease clustering.
This study also offers one of the first comprehensive epidemiologic profiles of HIV and STI prevalence among AMMSWs in Italy, highlighting a structurally-driven health burden shaped by structural, behavioral, and sociocultural vulnerabilities, with nearly half (46.07%) of participants who had ever tested for HIV self-reporting a positive status, substantially higher than Italy's national average of < 1%. These findings underscore an urgent public health crisis that has been largely invisible in European surveillance data 46,66,67.
Our findings align with broader regional and global literature identifying male sex workers, particularly those who are migrants, as a critically underserved and highly vulnerable key population for HIV and other STIs68–70. The intersection of migration status, engagement in sex work, and minoritized sexual orientation converge to amplify health risks and restrict access to prevention and care services60,71,72. This study empirically demonstrates how these intersectional disadvantages materialize in heightened disease prevalence and constrained healthcare access; a trend echoed in cross-European analyses.
Health system-related barriers emerged as significant correlates of HIV positivity. Participants without health insurance, those living more than six kilometers from a health facility, and those who reported immigration-related healthcare access challenges were significantly more likely to report HIV infection. These findings confirm prior evidence that spatial and financial barriers compromise timely HIV testing, diagnosis, and care engagement, particularly among migrant and undocumented populations73–75.
Further, experiences of stigma and discrimination within healthcare settings were associated with higher HIV prevalence. This finding corroborates robust evidence from European and global studies showing that enacted and anticipated stigma suppresses health-seeking behaviors and delays diagnosis and treatment 76–78 Stigma undermines individual engagement with health services and perpetuates population-level transmission by impeding prevention cascades77,79,80.
Interestingly, frequent engagement with formal healthcare services, typically considered a protective factor, was associated with HIV positivity. This finding likely reflects reverse causality, whereby individuals diagnosed with HIV are more routinely engaged in care for ART monitoring and comorbidity management81,82. These findings highlight the need to distinguish between antecedent risk factors and post-diagnosis behaviors when interpreting healthcare utilization data in cross-sectional analyses.
Behavioral correlates, including substance use, further compounded the risk. Consistent with prior studies83,84 both alcohol and illicit drug use were positively associated with HIV prevalence. Substance use has been linked to impaired judgment, reduced condom use, and engagement in high-risk transactional sex85,86. The high co-occurrence of these risk factors reinforces the need for integrated harm reduction and HIV prevention programming tailored to the lived realities of AMMSWs.
Moreover, a lack of awareness about where to access HIV/STI testing and care was significantly associated with HIV positivity, suggesting that informational barriers are as consequential as structural ones. This finding aligns with European research highlighting the importance of health literacy and service awareness for timely testing and prevention87,88. Public health interventions must, therefore, prioritize culturally and linguistically accessible communication strategies to raise awareness and normalize care-seeking among migrant sex workers.
Beyond HIV, this study revealed high burdens of rectal gonorrhea (12%), syphilis (9.33%), and hepatitis B (9.33%), with several structural and behavioral factors shaping STI risk. Notably, STI positivity was significantly higher among participants reporting condomless transactional sex, aligning with prior findings that financial pressures and client coercion often override safer sex intentions among sex workers89,90.
Marital and parental status also emerged as significant correlates of STI prevalence. Unmarried individuals and those without children exhibited higher STI rates, suggesting that social connectedness and perceived responsibility may exert a protective effect. This finding is consistent with the broader literature on protective social structures among migrant populations91–93 Similarly, bisexual men had disproportionately high STI prevalence, a pattern also observed in prior research likely due to dual stigma, lower healthcare engagement, and limited inclusion in MSM- or heterosexual-specific interventions.
The recency of migration also predicted the STI burden. Individuals who had resided in Italy for less than one year were significantly more likely to report an STI, echoing findings from other European studies indicating that recent migrants face intensified barriers to healthcare due to legal, linguistic, and economic constraints72,94 These data stress the importance of early and targeted outreach to newly arrived migrants engaged in sex work.
Interestingly, participants who had never tested for STIs were less likely to report infection, though this likely reflects underdiagnosis rather than actual absence of disease. Diagnostic bias is a well-documented challenge in epidemiologic studies, particularly among hard-to-reach and under-tested populations95,96. The high observed prevalence among testers underscores the critical need for expanded routine screening to improve case identification and linkage to care.
Lack of knowledge about sexual partners' STI history also correlated with higher STI prevalence, reinforcing existing evidence that limited partner communication in transactional encounters increases transmission risk97–99. Interventions must consider strategies to promote safer sex negotiation, even within the constrained agency contexts that characterize much of sex work.
Collectively, these findings expose glaring gaps in Italy's current HIV/STI prevention architecture for AMMSWs and other migrant sex workers. There is an urgent need for multilevel, culturally responsive, and community-driven interventions. Mobile clinics, peer-led testing initiatives, and digital platforms offering confidential information and appointment scheduling can mitigate geographic and structural barriers. Legal and policy reforms, including decriminalization of sex work and guarantees of healthcare access for undocumented migrants are necessary to dismantle the structural violence embedded in current systems. Expansion of PrEP access, HIV self-testing distribution, and structural determinants informed screening (e.g., combined HIV/STI/HBV testing) through trusted community organizations may significantly reduce new infections in this population.
Limitations
While the structural vulnerability framework provides a valuable approach for interpreting the interrelated health and social phenomena observed in this study, the cross-sectional design restricts the ability to assess temporal or causal relationships among variables. The associations identified between structural vulnerabilities and HIV/STI outcomes should therefore be interpreted as correlational rather than causal. Future longitudinal or mixed-methods research could better capture how changes in migration status, healthcare access, or social stigma influence structurally-driven health dynamics over time.
Additionally, the social determinants of health framework was applied conceptually rather than analytically; thus, the findings illustrate patterns consistent with socially and structurally-driven health processes but do not statistically test for interaction effects among health and social variables. The framework guided the study's conceptual framing, variable selection, and interpretation of overlapping vulnerabilities, but no formal modeling indices or analytic interaction terms were conducted. This theoretical application provides valuable insights into how social and structural inequities interact with health outcomes, even without formal statistical modeling of these interactions.
Reliance on self-reported data for sensitive behaviors such as condom use, substance use, and HIV/STI status introduces potential recall and social desirability biases, which may have led to underreporting or misclassification of risk exposures. Although purposive and respondent-driven sampling was appropriate for reaching a hidden and stigmatized population, the resulting sample may not fully represent all AMMSWs in Italy, particularly those operating outside urban centers or unaffiliated with community-based organizations.
Moreover, the exclusion of non-English and non-Italian speakers and the focus on cisgender male participants may limit the generalizability of findings to transgender, non-binary, or linguistically isolated subgroups. Finally, the absence of biomarker verification prevented confirmation of self-reported HIV/STI results, potentially affecting prevalence estimates.
Despite these limitations, the study provides a rare and critical epidemiological perspective on a severely understudied population. It quantifies the structurally-driven health burden among AMMSWs and lays the groundwork for future longitudinal and intervention studies aimed at dismantling the structural inequities that sustain overlapping epidemics of infection, stigma, and exclusion.
Conclusion
Guided by the structural vulnerability framework, this study demonstrates that the HIV and STI burden among AMMSWs in Italy extends far beyond biomedical vulnerability. It reflects the convergence of social, behavioral, and structural determinants that reinforce one another within contexts of exclusion and precarity.
In this study, the social determinants of health were considered as complementary contextual factors shaping exposure and access. The framework provided a lens for interpreting how intersecting structural factors, such as stigma, legal precarity, migration-related barriers, and limited healthcare access, compound HIV and STI risk. However, no formal statistical modeling or syndemic interaction terms were applied. Thus, while the findings reveal patterns consistent with structurally-driven health processes, they do not constitute empirical tests of interactions among social determinants of health. Instead, the study contributes a conceptual and descriptive understanding of how overlapping vulnerabilities shape health disparities within this marginalized population.
The findings provide critical epidemiological evidence on a population that remains largely invisible in national surveillance systems and underserved by public health programming. The alarmingly high prevalence of HIV and other STIs, particularly syphilis, rectal gonorrhea, and hepatitis B, illustrates a landscape shaped by the structural and social determinants of health, with overlapping behavioral, structural, and sociopolitical vulnerabilities. Structural barriers such as lack of health insurance, geographic inaccessibility, and immigration-related restrictions were strongly associated with infection, underscoring the importance of addressing the broader social determinants of health. Behavioral factors, including substance use and condomless transactional sex, further compounded individual-level risk, while informational inequities limited knowledge of testing sites and partners’ sexual health, exacerbating vulnerability. These behavioral patterns operate within the broader structural vulnerabilities described above, reflecting how individual choices are constrained by systemic barriers.
Collectively, these findings highlight the need for public health strategies that move beyond disease-specific and biomedical models. Effective responses must be community-informed, rights-based, and intersectional, integrating prevention, care, and structural reform. Expanding access to HIV self-testing, pre-exposure prophylaxis (PrEP), and screening informed by the structural vulnerability framework through peer-led networks, mobile outreach, and culturally competent providers is essential. Equally important are legal and policy reforms that decriminalize sex work, safeguard migrant rights, and combat stigma within healthcare systems.
By centering the lived realities of AMMSWs, this study contributes to a growing body of evidence calling for equity-driven, justice-oriented approaches to HIV and STI prevention. Targeted investment in this key population is both a public health imperative and a matter of human rights. Future research should build upon this foundation through longitudinal and intervention studies that operationalize the social determinants of health framework analytically, testing the interaction effects of co-occurring social, structural, and health conditions to develop scalable, sustainable, and dignified solutions for one of Europe’s most marginalized communities.
Contributions
Conceptualization (GRA, DC, LN), methodology (GRA, DC), investigation (GRA, OWS, HDD, SSN), formal analysis (OWS, HDD, SN), data curation (HDD, SSN, MS), visualization (SSN, HDD), project administration (OWS, GRA), funding acquisition (GRA, LN), writing – original draft (OWS, HDD), writing – review & editing (OWS, SN, HDD, MS, GRA, LN, DC), supervision (GRA).
Ethical Approval
A
The study received ethical clearance from the University of Rochester Institutional Review Board (IRB# STUDY00007858) and the National Ethics Committee for Clinical Trials, Italian Ministry of Health (Approval Code: AOO-ISS − 04/07/2023–0031228).
A
All participants provided written informed consent before participation. The study adhered strictly to Italian regulations regarding protecting and anonymously handling sensitive data, particularly for vulnerable and marginalized populations.
Results
Consistent with the social determinants of health framework, results indicate the simultaneous presence and interaction of multiple health and social conditions. High HIV and STI prevalence co-occurred with behavioral and structural stressors such as substance use, healthcare inaccessibility, and discrimination, reflecting a structurally-driven health pattern rather than discrete or independent risk factors.
Sociodemographic Characteristics of Respondents
A total of 150 male sex workers participated in the study, with a mean age of 30.63 years (SD = 5.9, Range = 30) and an average age at which they commenced sex work being 23.3 years (SD = 4.6). Most respondents were adults aged 25 and above (86%) and identified as men (96.7%), with only 2.0% identifying as transgender. A majority had primary education or less (74.0%), while 26.0% had secondary education or more. Single participants (64.7%) and 53.3% had no children. Most participants (83.3%) reported belonging to a religion, 90.0% described themselves as religious. Most participants (87.3%) were refugees, and 57.3% originated from Nigeria. Table 1 represents the descriptive statistics of this population.
Table 2 summarizes the HIV Testing behavior: 59.33% (n = 89) had ever tested for HIV, while 40.7% (n = 61) had never tested. Among those who tested, 53.9% (n = 48) received a negative result, and 46.07% (n = 41) tested positive. STI Testing: 70.0% (n = 105) had ever tested for an STI, while 30.0% (n = 45) had never tested. HIV Self-Testing Awareness and Uptake: 44.7% (n = 67) had heard of HIV self-testing kits, but only 47.7% (n = 32) of them had ever used one. The HIV/STI Prevalence among Study Participants is shown in Table 3.
Table 4 presents results from a chi-square analysis exploring the association between various sociodemographic, behavioral, and health-related factors and HIV testing behavior outcomes among 150 AMMSWs in Italy. Statistically significant associations (p < 0.05) were observed across several factors; Educational level (χ² = 7.76, p = 0.021), marital status (χ² = 15.39, p < 0.001), Number of Children (χ² = 14.89, p = 0.001), Length of Stay in Italy (χ² = 17.49, p < 0.001), Sexual Orientation (χ² = 6.65, p = 0.036), Distance to Healthcare Facility (χ² = 25.73, p < 0.001), Health Insurance status (χ² = 27.62, p < 0.001), Healthcare access challenge (χ² = 11.49, p = 0.003), Experience of stigma/ discrimination at the hospital (χ² = 14.26, p = 0.001), Primary source of care (χ² = 7.32, p = 0.026), knowledge of where to go for STI/HIV testing and care (χ² = 7.84, p = 0.020), alcohol use (χ² = 13.09, p = 0.001). Illicit drug use χ² = 8.90, p = 0.012), Tested for STI (χ² = 10.07, p = 0.007), and willingness to use an HIV self-testing kit (χ² = 10.93, p = 0.004), Awareness of partners' sexual history (17.14, p = p < 0.001), PrEP Awareness (χ² = 24.58, p < 0.001).
Factors such as age (χ² = 1.79, p = 0.408), religion affiliation (χ² = 1.43, p = 0.490), healthcare frequency (χ² = 4.87, p = 0.088), sex role (χ² = 7.25, p = 0.123), other job apart from sex work (χ² = 1.50, p = 0.472), transactional Condom-less sex (χ² = 0.55, p = 0.759), awareness of HIV self-testing kit (χ² = 0.32, p = 0.853), Number of clients daily (χ² = 3.1266, p = 0.209), Ever used PrEP (χ² = 2.37, p = 0.306), willingness to use PrEP (χ² = 2.16, p = 0.340) and Number of male client in past 2month (χ² = 2.71, p = 0.258) were not statistically significant at the 0.05 level.
Table 5 presents the results of a chi-square test examining associations between sociodemographic factors, healthcare access, testing behavior, sex work-related characteristics, and HIV Prevalence among AMMSWs.
Factors significantly associated with HIV prevalence among AMMSWs included distance to a healthcare facility (χ² = 6.86, p = 0.009), health insurance status (χ² = 7.06, p = 0.008), experience of stigma or discrimination (χ² = 6.47, p = 0.011), primary source of care (χ² = 7.39, p = 0.007), knowledge of where to access STI/HIV testing and care (χ² = 5.58, p = 0.018), alcohol use (χ² = 8.08, p = 0.004). Illicit drug use (χ² = 5.87, p = 0.015), sex role (χ² = 5.89, p = 0.053), and willingness to use an HIV self-testing kit (χ² = 10.41, p = 0.001)
Other factors such as age, education level, marital status, Number of children, religious affiliation, length of stay in Italy, sexual orientation, healthcare frequency, healthcare access challenges, Tested for ST, transactional Condom-less sex, awareness of HIV self-testing kit, Number of clients daily, Awareness of partners' sexual history and STI status before sex, PrEP awareness, ever used PrEP, willingness to use PrEP and Number of clients in past 2 months (Men) were not statistically significant at the 0.05 significance level, although some approached significance and may warrant further exploration in multivariate analyses.
References
1.
World Health Organization (2024) Global HIV Programme.
2.
World Health Organization (2024) HIV Data and Statistics
3.
World Health Organization (2016) Guidelines on HIV Self-Testing and Partner Notification: Supplement to Consolidated Guidelines on HIV Testing Services
4.
Ferrand R, Lowe S, Whande B et al (2010) Survey of children accessing HIV services in a high prevalence setting: time for adolescents to count? Bull World Health Organ 88(6). 10.2471/blt.09.066126
5.
Abu-Ba’are GR, Shamrock OW, Agbemedu GRK, Dakpui HD (2024) How will I know the results if I self-test at home? – At-home HIV self-testing vs. at-clinic HIV testing preference among trans-women in Ghana’s Slums. BSGH-015. Preprint posted online July 2. 10.21203/rs.3.rs-4659823/v1
6.
Abu-Ba’are GR, Shamrock OW, Rodriguez D, Agbemedu GRK, Nelson LE (2024) Adolescent HIV prevent and care framework: A global scoping review protocol- BSGH 006. PLoS ONE 19(8):e0289994. https://doi.org/10.1371/journal.pone.0289994
7.
Boyd DT, Martinez O, Mammadli T, Shamrock OW, Abu-Ba’are GR, Dyer TV (2024) Intersecting Epidemics: Examining the Impact of Internalized Homophobia and Depression Symptoms on HIV Testing Through a Suicide Syndemic Among Young Black Men Who Have Sex with Men. J Racial Ethn Health Disparities Published online Oct 30. 10.1007/s40615-024-02225-4
8.
Shamrock OW, Abu-Ba’are GR, Zigah EY et al (2024) Community stigma, victimization, and coping strategies among gay, bisexual, and other cis-gender men who have sex with men in slum communities in Ghana. BSGH-003. BMC Public Health 24(1):966. 10.1186/s12889-024-18242-1
9.
Zigah EY, Abu-Ba’are GR, Shamrock OW et al (2023) For my safety and wellbeing, I always travel to seek health care in a distant facility—the role of place and stigma in HIV testing decisions among GBMSM – BSGH 002. Health Place 83:103076. 10.1016/j.healthplace.2023.103076
10.
Shamrock OW, Guure C, Reeves J et al A qualitative study of the ecology of stigma experiences-An application of the ecological model to stigma experiences of trans-women from Ghana. BSGH019. Published online 2024.
11.
Abu-Ba’are GR, Torpey K, Nelson L et al Adaptation and feasibility of Many Men Many Voices (3MV), an HIV prevention intervention to reduce intersectional stigma and increase HIVST among YSMM residing in Ghanaian slums–A clustered pre-post pilot trial protocol. Published online 2024.
12.
Abu-Ba’are GR, Shamrock OW, Apreku A et al (2023) Awareness and Willingness to use Condoms and Preexposure Prophylaxis among Gay, Bisexual, and Other Cisgendered Men who Have sex with men in Slum Communities in Ghana. BSGH-004. J Int Association Providers AIDS Care (JIAPAC) 22:23259582231209650. 10.1177/23259582231209649
13.
Shamrock OW, Guure C, Reeves J et al (2024) A qualitative study of the ecology of stigma experiences - An application of the ecological model to stigma experiences of trans-women from Ghana. BSGH019. Published online August 21. 10.21203/rs.3.rs-4945585/v1
14.
Shamrock OW, Abu-Ba’are GR, Zigah EY et al Family rejection of non-hetero sexuality–Sexual orientation and behavior anonymity among sexual minority men in slum communities-BSGH 001. PLOS Global Public Health 3: e0001659 doi:101371/journal.pgph0001659. Published online December 1, 2023
15.
Shamrock OW, Abu-Ba’are GR, Hosseini FS et al (2024) Characterization of HIV Peer Support Based on The Dennis Peer Support Model - Accounts from Transwomen in Ghana, BSHG-018. Published online Dec 31. 10.21203/rs.3.rs-5730804/v1
16.
Abu-Ba’are GR, Torpey K, Guure C et al Status-neutral community-based multilevel intervention to address intersectional stigma and discrimination, and increase HIV testing, PrEP, and ART uptake among YGBMSM in Ghanaian Slums: A clustered randomized control trial protocol. Published online 2024.
17.
Dakpui HD, Shamrock OW, Aidoo-Frimpong G et al A qualitative description of HIV testing and healthcare experiences among trans women in Ghanaian urban slums BSGH-011. Published online 2024. https://doi.org/10.21203/rs.3.rs-4390892/v1
18.
Shamrock OW, Dakpui HD, Agbemedu GRK et al I’m scared of the nurses telling other people I am a transwoman: Disclosure and nondisclosure of gender identity among trans women in Ghana’s urban slums–BSGH010. Published online 2024.
19.
Reeves JM, Zigah EY, Shamrock OW et al (2023) Investigating the impact of stigma, accessibility and confidentiality on STI/STD/HIV self-testing among college students in the USA: protocol for a scoping review. BMJ Open 13(2). 10.1136/bmjopen-2022-069574
20.
Abu-Ba’are GR, Shamrock OW, Zigah EY et al (2024) Qualitative description of interpersonal HIV stigma and motivations for HIV testing among gays, bisexuals, and men who have sex with men in Ghana’s slums—BSGH-005. PLoS ONE 19(6):e0289905. 10.1371/journal.pone.0289905
21.
UNAIDS UNAIDS Goal 90-90-90: An ambitious treatment target to help end the AIDS epidemic. Http://WwwUnaidsOrg/Sites/Default/Files/Media_Asset/90-90-90_En_0Pdf. Published online 2014
22.
Dikobe W, Okui L, Akolo C et al (2020) Progress and challenges towards reaching 90-90-90 targets among key populations in Botswana. J Int AIDS Soc 23(SUPPL 4). 10.1002/jia2.25547
23.
Institute for Health Metrics and Evaluation Q&A: Sub-Saharan Africa has achieved great declines in HIV. https://www.healthdata.org/news-events/newsroom/videos/qa-sub-saharan-africa-has-achieved-great-declines-hiv#:~:text=So%2C%20what%20we%27re%20seeing,declines%20to%2043.4%20in%202050
24.
Zigah EY, Abu-Ba’are GR, Shamrock OW et al (2023) For my safety and wellbeing, I always travel to seek health care in a distant facility—the role of place and stigma in HIV testing decisions among GBMSM – BSGH 002. Health Place 83:103076. 10.1016/j.healthplace.2023.103076
25.
Platt L, Grenfell P, Fletcher A et al (2013) Systematic review examining differences in HIV, sexually transmitted infections and health-related harms between migrant and non-migrant female sex workers. Sex Transm Infect 89(4). 10.1136/sextrans-2012-050491
26.
Rocha-Jiménez T, Morales‐Miranda S, Fernández‐Casanueva C, Brouwer KC, Goldenberg SM (2018) Stigma and unmet sexual and reproductive health needs among international migrant sex workers at the Mexico–Guatemala border. Int J Gynecol Obstet 143(1):37–43. 10.1002/ijgo.12441
27.
Clatts MC, Goldsamt LA, Giang LM, Quc Bo L, Yu G, Colby D (2016) Sexually transmissible infection and HIV prevention and treatment for young male sex workers in Vietnam: Findings from the SHEATH intervention. Sex Health 13(6):575–581. 10.1071/SH16051
28.
Belza MJ (2005) Risk of HIV infection among male sex workers in Spain. Sex Transm Infect 81(1). 10.1136/sti.2003.008649
29.
Platt L, Grenfell P, Meiksin R et al (2018) Associations between sex work laws and sex workers’ health: A systematic review and meta-analysis of quantitative and qualitative studies. PLoS Med 15(12). 10.1371/journal.pmed.1002680
30.
Abu-Ba’are GR, Zigah EY, Shamrock OW et al Qualitative description of interpersonal HIV stigma and motivations for HIV testing among gays, bisexuals, and men who have sex with men in Ghana’s slums - BSGH-005. medRxiv. Published online January 1, 2023:2023.07.29.23293357. 10.1101/2023.07.29.23293357
31.
Abu-Ba’are GR, Nichols SS, Hosseini FS et al (2025) Bridging Gaps in HIV Prevention: A Machine Learning-Enhanced Mixed-Methods Study on PrEP Awareness and Willingness Among Refugee Male Sex Workers from Sub-Saharan Africa in Italy. Preprint posted online April 18. 10.21203/rs.3.rs-6416303/v1
32.
Abu-Ba’are GR, Dakpui HD, Saaka MS, Gyamerah E, Guure C, Nelson LE (2025) Stigma, privacy concerns, sexual behaviors, and testing history shape willingness to use HIV self-testing among African refugee male sex workers in Italy – A mixed method study - BGSH-023. Preprint posted online April 14. 10.21203/rs.3.rs-6421791/v1
33.
Dakpui HD, Abu-Ba’are GR, Saaka MS, Boyd D, Harris O, Zardini G, Yes (2025) I Saw It at a Client’s House: Factors Associated with Oral HIV Self-Testing Awareness Among African Refugee Male Sex Workers in Italy—A Mixed-Methods Study- BGSH-022. Preprint posted online April 9. 10.21203/rs.3.rs-6383201/v1
34.
Abu-Ba’are GR, Dakpui HD, Saaka MS, Gyamerah E, Guure C, Nelson LE (2025) Stigma, privacy concerns, sexual behaviors, and testing history shape willingness to use HIV self-testing among African refugee male sex workers in Italy – A mixed method study - BGSH-023. Preprint posted online April 14. 10.21203/rs.3.rs-6421791/v1
35.
Abu-Ba’are GR, Nichols SS, Hosseini FS et al (2025) Bridging Gaps in HIV Prevention: A Machine Learning-Enhanced Mixed-Methods Study on PrEP Awareness and Willingness Among Refugee Male Sex Workers from Sub-Saharan Africa in Italy. Preprint posted online April 18. 10.21203/rs.3.rs-6416303/v1
36.
Nichols SS, Abu-Ba’are GR, Rigo C et al (2025) Substance Use and HIV Risk in a Syndemic Context: Vulnerabilities Among African Refugee Sex Workers in Italy. Preprint posted online Oct 21. 10.21203/rs.3.rs-7882022/v1
37.
Nichols SS, Abu-Ba’are GR, Rigo C et al Substance Use and HIV Risk in a Syndemic Context: Vulnerabilities Among African Refugee Sex Workers in Italy. Preprint posted online 2025. 10.21203/rs.3.rs-7882022/v1
38.
Abu-Ba’are GR, Nichols SS, Hosseini FS et al Bridging Gaps in HIV Prevention: A Machine Learning-Enhanced Mixed-Methods Study on PrEP Awareness and Willingness Among Refugee Male Sex Workers from Sub-Saharan Africa in Italy. Preprint posted online 2025. 10.21203/rs.3.rs-6416303/v1
39.
Dakpui HD, Abu-Ba’are GR, Saaka MS, Boyd D, Harris O, Zardini G, Yes I Saw It at a Client’s House: Factors Associated with Oral HIV Self-Testing Awareness Among African Refugee Male Sex Workers in Italy—A Mixed-Methods Study- BGSH-022. Preprint posted online 2025. 10.21203/rs.3.rs-6383201/v1
40.
Abu-Ba’are GR, Dakpui HD, Saaka MS, Gyamerah E, Guure C, Nelson LE Stigma, privacy concerns, sexual behaviors, and testing history shape willingness to use HIV self-testing among African refugee male sex workers in Italy – A mixed method study - BGSH-023. Preprint posted online 2025. 10.21203/rs.3.rs-6421791/v1
41.
The Global Fund. HIV and migration profiles. https://hivandmigration.com/countries/italy/
42.
Minichiello V, Scott J, Callander D (2015) A new public health context to understand male sex work. BMC Public Health 15(1). 10.1186/s12889-015-1498-7
43.
Baral S, Sifakis F, Cleghorn F, Beyrer C (2007) Elevated risk for HIV infection among men who have sex with men in low- and middle-income countries 2000–2006: A systematic review. PLoS Med 4(12). 10.1371/journal.pmed.0040339
44.
Logan TD (2010) Personal characteristics, sexual behaviors, and male sex work: A quantitative approach. Am Sociol Rev 75(5). 10.1177/0003122410379581
45.
Shobowale O, Schmidt AJ, Meireles P et al (2024) Determinants of HIV Testing Among Migrant Men Who Have Sex With Men from Sub-Saharan Africa and Other Regions Residing in 10 European Countries. AIDS Behav 28(2):488–506. 10.1007/s10461-023-04239-1
46.
Pezzoli MC, El Hamad I, Scarcella C et al (2009) HIV infection among illegal migrants, Italy, 2004–2007. Emerg Infect Dis 15(11). 10.3201/eid1511.090908
47.
Regine V, Pugliese L, Suligoi B (2024) SC-37 HIV infection among migrants present in Italy from 2012 to 2022: incidence and characteristics. Sex Transm Infect 100(Suppl 1):A108. 10.1136/sextrans-ICAR-2024.98
48.
European Centre for Disease Prevention and Control (2023) HIV/AIDS Surveillance in Europe 2023
49.
European Centre for Disease Prevention and Control (2024) HIV and migrants in the EU/EEA. HIV and Migrants in the EU/EEA. Monitoring Implementation of the Dublin Declaration on Partnership to Fight HIV/AIDS in Europe and Central Asia: 2024 Progress Report
50.
UNAIDS, Italy HIV, Country Profile (2022). Https://Www.Unaids.Org/En/Regionscountries/Countries/Italy
51.
National Institute of Health (Istituto Superiore di Sanità). HIV Surveillance in Italy: Epidemiological Report 2021. Rome: ISS, Https ://Www.Epicentro.Iss.It/En/Hiv-Surveillance
52.
Lelouvier B, Servant F, Delobel P, Courtney M, Elbaz M, Amar J (2017) Identification by highly sensitive 16S metagenomic sequencing of an unusual case of polymicrobial bacteremia. J Infect 75(3):278–280. 10.1016/j.jinf.2017.05.005
53.
HIV and Migration. HIV epidemiology and migrant populations in Italy. https://hivandmigration.org/country/italy
54.
Becker ML, Bhattacharjee P, Blanchard JF et al (2018) Vulnerabilities at First Sex and Their Association With Lifetime Gender-Based Violence and HIV Prevalence Among Adolescent Girls and Young Women Engaged in Sex Work, Transactional Sex, and Casual Sex in Kenya. JAIDS J Acquir Immune Defic Syndr 79(3):296–304. 10.1097/QAI.0000000000001826
55.
Laga M, Alary M, Behets F et al (1994) Condom promotion, sexually transmitted diseases treatment, and declining incidence of HIV-1 infection in female Zairian sex workers. Lancet 344(8917). 10.1016/S0140-6736(94)93005-8
56.
Schofield WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39:1
57.
Mantell JE, Franks J, Lahuerta M et al (2021) Life in the Balance: Young Female Sex Workers in Kenya Weigh the Risks of COVID-19 and HIV. AIDS Behav 25(5). 10.1007/s10461-020-03140-5
58.
McBride B, Janushev T (2021) Criminalisation, health, and labour rights among im/migrant sex workers globally. In: Sex Work, Health, and Human Rights: Global Inequities, Challenges, and Opportunities for Action. 10.1007/978-3-030-64171-9_9
59.
Rael CT, Sheinfil A, Hampanda K, Carballo-Diéguez A, Norcini Pala A, Brown W (2017) Examining the Unique Characteristics of a Non-Probability Sample of Undocumented Female Sex Workers with Dependent Children: The Case of Haitians in the Dominican Republic. Sex Cult 21(3). 10.1007/s12119-017-9412-3
60.
Lagi F, Gatteschi C, Tilli M et al (2024) Facilitators and barriers in HIV testing and continuum of care among migrant transgender women who are sex workers residing in Florence, Italy. Int J Transgend Health 25(2). 10.1080/26895269.2023.2209072
61.
Sebo P, Jackson Y, Haller DM, Gaspoz JM, Wolff H (2011) Sexual and reproductive health behaviors of undocumented migrants in Geneva: A cross sectional study. J Immigr Minor Health 13(3). 10.1007/s10903-010-9367-z
62.
Donisi A, Colpani A, Zauli B et al (2023) Sexually Transmitted Infections Prevalence and Cascade of Care among Undocumented Sex Workers: A Twenty-Year-Long Experience. Life 13(3). 10.3390/life13030606
63.
Etikan I (2016) Comparison of Convenience Sampling and Purposive Sampling. Am J Theoretical Appl Stat 5(1). 10.11648/j.ajtas.20160501.11
64.
Zhao J, Cai R, Chen L et al (2015) A Comparison Between Respondent-Driven Sampling and Time-Location Sampling Among Men Who Have Sex with Men in Shenzhen, China. Arch Sex Behav 44(7). 10.1007/s10508-014-0350-y
65.
Rao A, Stahlman S, Hargreaves J et al (2017) JMIR Public Health Surveill 3(4):e72. 10.2196/publichealth.8116. Sampling Key Populations for HIV Surveillance: Results From Eight Cross-Sectional Studies Using Respondent-Driven Sampling and Venue-Based Snowball Sampling
66.
Giuliani M, Suligoi B, Affronti M et al (2004) Differences between Nonnational and Indigenous Patients with Sexually Transmitted Infections in Italy and Insight into the Control of Sexually Transmitted Infections. Sex Transm Dis 31(2). 10.1097/01.OLQ.0000109975.74152.29
67.
Zoboli F, Martinelli D, Di Stefano M et al (2017) Correlation between knowledge on transmission and prevention of HIV/STI and proficiency in condom use among male migrants from Africa and Middle East evaluated by a Condom Use Skills score using a wooden penile model. BMC Res Notes 10(1):216. 10.1186/s13104-017-2520-1
68.
Weine S, Bahromov M, Loue S, Owens L (2013) HIV Sexual Risk Behaviors and Multilevel Determinants Among Male Labor Migrants from Tajikistan. J Immigr Minor Health 15(4):700–710. 10.1007/s10903-012-9718-z
69.
Abdulkader RS, Goswami K, Rai SK, Misra P, Kant S (2015) HIV-Risk Behavior among the Male Migrant Factory Workers in a North Indian City. Indian J Community Med 40(2). 10.4103/0970-0218.153874
70.
Verhaegh-Haasnoot A, Dukers-Muijrers NHTM, Hoebe CJPA (2015) High burden of STI and HIV in male sex workers working as internet escorts for men in an observational study: a hidden key population compared with female sex workers and other men who have sex with men. BMC Infect Dis 15(1):291. 10.1186/s12879-015-1045-2
71.
Logie CH, James Ll, Tharao W, Loutfy MR (2011) HIV, gender, race, sexual orientation, and sex work: A qualitative study of intersectional stigma experienced by HIV-positive women in Ontario, Canada. PLoS Med 8(11). 10.1371/journal.pmed.1001124
72.
Mellini L, Poglia Mileti F, Tadorian M (2024) Migrants facing intersectional vulnerability to HIV and AIDS in Switzerland: an exploratory study. Cult Health Sex 26(10):1350–1364. 10.1080/13691058.2024.2319335
73.
Arora AK, Ortiz-Paredes D, Engler K et al (2021) Barriers and Facilitators Affecting the HIV Care Cascade for Migrant People Living with HIV in Organization for Economic Co-Operation and Development Countries: A Systematic Mixed Studies Review. AIDS Patient Care STDS 35(8):288–307. 10.1089/apc.2021.0079
74.
Lyons N, Bhagwandeen B, Edwards J (2023) Examining the Correlates of HIV Testing for Venezuelan Migrants in Trinidad. Int J Environ Res Public Health 20(3). 10.3390/ijerph20032148
75.
Yao J, Agadjanian V, Murray AT (2014) Spatial and social inequities in HIV testing utilization in the context of rapid scale-up of HIV/AIDS services in rural Mozambique. Health Place 28. 10.1016/j.healthplace.2014.04.007
76.
Moore S, Jones M, Smith JC et al (2019) Homonegativity Experienced over the Life Course by Young Black Gay, Bisexual and Other Men Who Have Sex with Men (YB-GBMSM) Living with HIV in Atlanta, Georgia. AIDS Behav 23(S3):266–275. 10.1007/s10461-019-02658-7
77.
Earnshaw VA, Chaudoir SR (2009) From conceptualizing to measuring HIV stigma: A review of HIV stigma mechanism measures. AIDS Behav 13(6). 10.1007/s10461-009-9593-3
78.
Katz IT, Ryu AE, Onuegbu AG et al (2013) Impact of HIV-related stigma on treatment adherence: systematic review and meta-synthesis. J Int AIDS Soc 16(3 Suppl 2). 10.7448/ias.16.3.18640
79.
Churcher S (2013) Stigma related to HIV and AIDS as a barrier to accessing health care in Thailand: a review of recent literature. WHO South East Asia J Public Health 2(1). 10.4103/2224-3151.115829
80.
Nyblade L, Stockton MA, Giger K et al (2019) Stigma in health facilities: Why it matters and how we can change it. BMC Med 17(1):1–15. 10.1186/S12916-019-1256-2/TABLES/4
81.
SoleimanvandiAzar N, Karimi SE, Ahmadi S, Irandoost SF, Amirkafi A, Azimi A (2023) Exploring the determinants of health service utilization among people living with HIV: a qualitative study in Iran. BMC Health Serv Res 23(1). 10.1186/s12913-023-10321-0
82.
Hojilla JC, Santiago-Rodriguez EI, Sterling S et al (2021) HIV Stigma and Its Associations with Longitudinal Health Outcomes Among Persons Living with HIV with a History of Unhealthy Alcohol Use. AIDS Behav 25(1). 10.1007/s10461-020-02963-6
83.
Fisher JC, Bang H, Kapiga SH (2007) The association between HIV infection and alcohol use: A systematic review and meta-analysis of African studies. Sex Transm Dis 34(11). 10.1097/OLQ.0b013e318067b4fd
84.
Cardoso FH (2012) Children and drug law reform. Int J Drug Policy 23(1):1–2. 10.1016/j.drugpo.2011.10.004
85.
Patrick ME, O’Malley PM, Johnston LD, Terry-McElrath YM, Schulenberg JE (2012) HIV/AIDS Risk Behaviors and Substance Use by Young Adults in the United States. Prev Sci 13(5). 10.1007/s11121-012-0279-0
86.
Stokes ML, Abram KM, Aaby DA et al (2023) Substance Use Disorders and HIV/AIDS Risk Behaviors in Youth After Juvenile Detention: A 16-Year Longitudinal Study. J Adolesc Health 73(4). 10.1016/j.jadohealth.2023.05.015
87.
Blondell SJ, Kitter B, Griffin MP, Durham J (2015) Barriers and Facilitators to HIV Testing in Migrants in High-Income Countries: A Systematic Review. AIDS Behav 19(11):2012–2024. 10.1007/s10461-015-1095-x
88.
Martinez Martinez V, Ormel H, Op de Coul ELM (2024) Barriers and enablers that influence the uptake of HIV testing among heterosexual migrants in the Netherlands. PLoS ONE 19(10):e0311114. 10.1371/journal.pone.0311114
89.
Wamoyi J, Stobeanau K, Bobrova N, Abramsky T, Watts C (2016) Transactional sex and risk for HIV infection in sub-Saharan Africa: A systematic review and meta-analysis: A. J Int AIDS Soc 19(1). 10.7448/IAS.19.1.20992
90.
Cohen SE, Vittinghoff E, Bacon O et al (2015) High interest in preexposure prophylaxis among men who have sex with men at risk for HIV infection: Baseline data from the US PrEP demonstration project. J Acquir Immune Defic Syndr 68. 10.1097/QAI.0000000000000479
91.
Giorgio M, Townsend L, Zembe Y et al (2016) Social support, sexual violence, and transactional sex among female transnational migrants to South Africa. Am J Public Health 106(6). 10.2105/AJPH.2016.303107
92.
Alcouffe L, Huber F, Creton PM et al (2022) Sexual vulnerability of migrant women in the multicultural context of French Guiana: A societal issue. Front Public Health 10. 10.3389/fpubh.2022.934049
93.
Chiao CY, Li HS (1974) [Observation on the effect of camptothecin-dimethyl sulfoxide solution on psoriasis]. Zhonghua Yi Xue Za Zhi 4:208–210
94.
Platteau T, De Baetselier I, Van Mieghem H et al (2022) Sexually Transmitted Infections and Associated Risk Factors Among Male Clients of Sex Workers: A Cross-Sectional Pilot Project in Antwerp, Belgium. Front Reproductive Health 4. 10.3389/frph.2022.837102
95.
Hunter MK, Singareddy C, Mundt KA (2024) Framing diagnostic error: an epidemiological perspective. Front Public Health 12. 10.3389/fpubh.2024.1479750
96.
Bailey ZD, Krieger N, Agénor M, Graves J, Linos N, Bassett MT (2017) Structural racism and health inequities in the USA: evidence and interventions. Lancet 389(10077). 10.1016/S0140-6736(17)30569-X
97.
Adrian Parra C, Stuardo Ávila V, Contreras Hernández P et al (2024) Structural and intermediary determinants in sexual health care access in migrant populations: a scoping review. Public Health 227. 10.1016/j.puhe.2023.11.031
98.
Lassi ZS, Damabi NM, Begum M, Avery JC, Meherali S (2025) Breaking the silence: Addressing sexual health challenges among migrant and refugee women. Women’s Health 21. 10.1177/17455057251331263
99.
Lassi ZS, Damabi NM, Begum M, Avery JC, Meherali S (2025) Breaking the silence: Addressing sexual health challenges among migrant and refugee women. Womens Health (Lond) 21:17455057251331264. 10.1177/17455057251331263
Yes
Total words in MS: 6885
Total words in Title: 25
Total words in Abstract: 212
Total Keyword count: 7
Total Images in MS: 0
Total Tables in MS: 8
Total Reference count: 99