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. Author manuscript; available in PMC: 2016 Jun 1.
Published in final edited form as: Drug Alcohol Depend. 2015 Mar 19;151:68–75. doi: 10.1016/j.drugalcdep.2015.02.034

Burden of substance use disorders, mental illness, and correlates of infectious diseases among soon-to-be released prisoners in Azerbaijan

Lyuba Azbel a, Jeffrey A Wickersham a, Martin P Wegman a, Maxim Polonsky a, Murad Suleymanov b, Rafik Ismayilov c, Sergey Dvoryak d, Signe Rotberga e, Frederick L Altice a,f,*
PMCID: PMC4447560  NIHMSID: NIHMS673700  PMID: 25861943

Abstract

Background

Despite low HIV prevalence in the South Caucasus region, transmission is volatile. Little data are available from this region about addiction and infectious diseases among prisoners who transition back to communities.

Methods

A nation-wide randomly sampled biobehavioral health survey was conducted in 13 non-specialty Azerbaijani prisons among soon-to-be-released prisoners. After informed consent, participants underwent standardized health assessment surveys and testing for HIV, hepatitis B and C, and syphilis.

Results

Of the 510 participants (mean age = 38.2 years), 11.4% were female, and 31.9% reported pre-incarceration drug injection, primarily of heroin. Prevalence of HCV (38.2%), HIV (3.7%), syphilis (3.7%), and HBV (2.7%) was high. Among the 19 HIV-infected inmates, 14 (73.7%) were aware of their HIV status, 12 (63.2%) were receiving antiretroviral therapy (ART), and 5 (26.3%) had CD4 < 350 cells/mL (4 of these were on ART). While drug injection was the most significant independent correlate of HCV (AOR = 12.9; p = 0.001) and a significant correlate of HIV (AOR = 8.2; p = 0.001), both unprotected sex (AOR = 3.31; p = 0.049) and working in Russia/Ukraine (AOR = 4.58; p = 0.008) were also correlated with HIV.

Conclusion

HIV and HCV epidemics are concentrated among people who inject drugs (PWIDs) in Azerbaijan, and magnified among prisoners. A transitioning HIV epidemic is emerging from migration from high endemic countries and heterosexual risk. The high diagnostic rate and ART coverage among Azerbaijani prisoners provides new evidence that HIV treatment as prevention in former Soviet Union (FSU) countries is attainable, and provides new insights for HCV diagnosis and treatment as new medications become available. Within prison evidence-based addiction treatments with linkage to community care are urgently needed.

Keywords: Prisons, Azerbaijan, Substance abuse, HIV/AIDS, Hepatitis C virus, Opioid substitution therapy

1. Introduction

The Southern Caucuses, countries of the former Soviet Union (FSU) that includes Azerbaijan, Armenia, and Georgia, have low HIV prevalence (<0.3%), with HIV concentrated among most-at-risk groups (Joint United Nations Programme on HIV/AIDS (UNAIDS), 2014). Whereas HIV incidence is decreasing globally, the prevalence has increased 35-fold since 2000 in the Southern Caucuses (574–19,100 estimated cases in the region; (UNAIDS, 2012; Kvitsinadze et al., 2010). In Azerbaijan, adult HIV prevalence is 0.2%, primarily concentrated among people who inject drugs (PWIDs; Kvitsinadze et al., 2010). HIV prevalence among PWIDs ranges from 19% to 24% (Cook and Kanaef, 2008). Recent data, however, suggest emerging new cases among commercial sex workers (CSWs), heterosexual men and women, and migratory populations, indicating bridges to the general population through sexual contact (Ministry of Health of the Republic of Azerbaijan, 2014). Many of the vestiges of FSU infrastructure and drug-related policies persist in Azerbaijan, leaving it vulnerable to a volatile HIV epidemic in the absence of adequately scaled HIV prevention.

Prisons have long been sentinel sites for identifying emerging HIV epidemics because the individual and structural factors associated with HIV transmission (e.g., PWIDs, sexually transmitted infections (STIs), mental illness, homelessness, proscriptive drug policies) are concentrated among individuals who cycle through the criminal justice system (CJS; Altice et al., 2005, 1998; Flanigan et al., 2010; Springer and Altice, 2005). In Azerbaijan, 72% of people living with HIV/AIDS (PLWHA) have a history of imprisonment (United Nations Office on Drugs and Crime, 2010). Azerbaijan’s CJS, however, has not been harnessed to implement evidence-based interventions (EBIs) like opioid substitution therapy (OST) for treating substance use disorders (SUDs). OST prevents HIV transmission for at-risk individuals (Gowing et al., 2008) and improves HIV treatment outcomes for PLWHA (Altice et al., 2010b; Dutta et al., 2013; Kerr et al., 2004). OST, however, is highly restricted in the general population and unavailable in prisons (Vagenas et al., 2013), although the scale up has been under consideration for more than five years (United Nations Office on Drugs and Crime, 2010). We therefore conducted an extensive, nationally representative bio-behavioral survey of soon-to-be-released prisoners in Azerbaijan in order to identify their burden of disease, with a specific focus on inter-related factors that might foreshadow an emerging epidemic in a low HIV prevalence FSU country.

2. Methods

A nationally representative, bio-behavioral survey assessing health status, addiction and infectious diseases (HIV, hepatitis C, hepatitis B, and syphilis) was conducted in 13 prisons in Azerbaijan from February to May 2014.

2.1. Setting

Azerbaijan ranks 17th (413 prisoners per 100,000 population) globally in incarceration rate (Walmsley, 2014). Azerbaijan’s Penitentiary Service and its Prison Health Department (both under the Ministry of Justice) oversee the CJS and prisoner health in Azerbaijan, respectively. Pretrial detention and prison facilities are concentrated primarily in the capital, Baku. Inmates are housed in facilities of varying security levels, based on the severity of the crime committed, and women are housed separately from men. The Penitentiary Service includes 24 facilities housing ~18,000 inmates including 15 high-, medium-, and -mixed security prisons, two specialty prisons, three pre-trial detention centers (SIZO), one prison for women, one prison for juveniles, and two inpatient treatment units.

2.2. Selection of prisons and recruitment of participants

We sampled adult prisoners (18 years or older) within six months of release in the 16 non-specialized facilities that comprise 83.4% of Azerbaijan’s prisoners using a stratified random sampling scheme (Hunt and Tyrell, 2001), previously devised for FSU countries (Azbel et al., 2013); hospital and specialty prisons were excluded, as were juvenile and SIZO facilities (did not meet eligibility criteria of ≥18 years or being soon-to-be-released, respectively). Three medium security facilities were excluded (one of them was because it opened just before the study was completed).

From an estimated 1,037 inmates in non-specialized facilities meeting eligibility criteria, we aimed to enroll 50% for our study, proportional to the number of prisoners within six months of release in each facility. Since women comprise only 2.2% of the overall prisoner population, they were oversampled to ensure adequate comparisons. The number enrolled from each facility is outlined in Fig. 1 and reflects the estimated proportion of prisoners in that type of facility six months pre-release based on the total number of prisoners in each facility.

Fig. 1.

Fig. 1

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Key: NP = number in prison population; N6 = number released in 6 months (18 months for women); NR = randomly chosen for consent; NE = number that gave consent; ♂ = male; ♀ = female. Reasons for non-participation: Already knew their health status (N = 7); cannot give blood (N = 7); did not provide a reason (N = 5); transferred to high security isolation unit (N = 4); felt too sick (N = 2).

The Ministry of Justice provided lists of all eligible prisoners in the selected facilities. Experienced research assistants (RAs) from a local NGO that works with prisoners underwent extensive training on study methods and confidentiality procedures. RAs used a random assignment chart to select participants who were informed by prison staff that they were randomly chosen for a voluntary and anonymous health study. Meetings between RAs and prisoners occurred in a private room on a one-by-one basis, in the absence of prison staff, where study details were discussed, followed by pre-test counseling for consented participants. Prisoners were informed that participation or continuation in the study would remain confidential and not influence status in any way. Prison staff was not informed about study participation or study results. After signed informed consent, she/he was assigned an anonymous personal identification number linked to her/his biobehavioral data. If not, her/his reason for non-participation was recorded without personal identifiers. Overall, 25 (4.7%) refused participation, with reasons provided in Fig. 1.

2.3. Data collection

Data collection occurred over three days using a previously described protocol (Azbel et al., 2013). Participants completed a self-administered behavioral interview using Audio-Computer-Assisted Self Survey Instruments (ACASI) on touch-screen laptop computers. ACASI enables anonymity, minimizes social desirability and reporting bias (Ghanem et al., 2005) and facilitates ethical principles of conducting research with prisoners. Participants were given the option to choose between English, Russian, or Azerbaijani versions of the instruments that had been translated and back-translated, according to standardized methods (Ware et al., 1995). Although adult literacy rate in Azerbaijan is 99.8%, survey questions were provided in written form and read aloud in a private room for those who did not have sufficient reading comprehension. All laptops included only the survey and no additional programs, files, or internet capability.

Participants then underwent phlebotomy, with specimen labeling including only the participant’s anonymous identification number. Serological tests were performed using commercially available quantitative chemiluminescent microparticle immunoassay (CMIA) Architect™ Combo for HIV-1/HIV-2 (specificity: 99.50%; sensitivity: 100%; Abbott Laboratories Tokyo, Japan), for hepatitis B surface antigen (specificity: 99.94%; sensitivity: 99.80%), for hepatitis C antibody (specificity: 99.60%; sensitivity: 99.10%), and for active syphilis Treponema pallidum antibody (specificity: 99.50%; sensitivity: 99.0). Initially positive HIV tests were confirmed with the Bio-Rad New Lav Blot 1 Western Blot (Bio-rad Laboratories, France). If both HIV tests were seropositive, reflex CD4T lymphocyte count assessment using the HumaCount CD4 was performed.

On the third day, participants reviewed their confidential HIV (including CD4), hepatitis B and C, and syphilis test results and underwent post-test counseling. They were offered voluntary referral to prison medical staff, received post-release referrals to care in the community, and were provided with a package of post-release resources. Though each participant was offered hygienic products totaling $10 USD for participation, most indicated their primary reason for participation was to receive the health assessment.

2.4. Variables and data analysis

Self-reported survey included: (1) socio-demographic characteristics; (2) imprisonment and detention history; (3) health-related quality of life (HRQoL) measured continuously using the Medical Outcomes Survey SF-36 (Ware and Sherbourne, 1992); (4) major depression symptoms defined dichotomously with a score ≥11 on the 10-item Clinical Epidemiological Survey of Depression CES-D 10 (Saunders et al., 1993) (5) alcohol use disorders defined by a score of ≥8 (men) or ≥4 (women) on the Alcohol Use Disorders Inventory Test (WHO AUDIT; Saunders et al., 1993); (6) sexual and drug risk behaviors; (7) anxiety measured using the Zung anxiety scale with a score ≥45 meeting criteria (Zung, 1971); (8) past and current history of chronic illnesses; (9) social support measured continuously using a standardized scale (Eaton et al., 2004); (10) substance use history assessed using items adapted from the Addiction Severity Index (McLellan et al., 2006, 1992); and goals for re-entry and likelihood of recidivism.

To avoid response bias and repercussions from prison officials, substance use and sexual risk behaviors were limited exclusively to six months prior to participants’ arrest. Substance use was defined as having used one or more of the following substances before arrest: barbiturates, illegal opioids, sedatives, cocaine, hallucinogens, or amphetamines. Polysubstance use was defined as having used two or more of the aforementioned substances in the same period. Participants were asked about the route of administration of each substance. Sexual risk behaviors included vaginal or anal intercourse without a condom with men and/or women in the six months prior to incarceration.

Statistical analyses were performed using SPSS (version 19.0). The t-test and χ2 for categorical and continuous variables were used. Bivariate and multivariate logistic regression analyses were performed to determine the independent correlates of HIV and hepatitis C infection. If correlates were significant at the bivariate level (p < 0.05), they were included in the multivariate logistic regression. Variables in the final model were checked for multicollinearity using the Variation Inflation Factor (VIF). Tolerance values in the final model were high (>0.90) and all VIF values were low (<1.30). Drug injection and sex without a condom were included in lieu of other sex and drug risk variables because they are most directly associated with HIV transmission and resulted in best goodness-of-fit. Variables that remained in the model were tested for interactions with each other. Goodness-of-fit for the final logistic regression was measured using the Aikake Information Criterion (AIC). To account for the stratified sampling design, and thereby ensure that study results were reflective of the entire soon-to-be-released prison population at the targeted facilities in Azerbaijan, model estimates were adjusted using weights calculated using the number of prisoners within six months of release in each facility (N6 in Fig. 1).

2.5. Ethics statement

Institutional Review Boards at the Ukrainian Institute on Public Health Policy and Yale University approved the study. Further safety assurances were provided by the Office for Human Research Protections (OHRP) in accordance with 45 CFR 46.305(c) “Prisoner Research Certification” requirements.

3. Results

3.1. Sociodemographic characteristics

The final sample (N = 510) represents 59% of all Azerbaijan’s soon-to-be-released prisoners in the selected facilities and 49% of all soon-to-be-released prisoners. As planned per our sampling strategy, high and medium security prisons each represent about 40% and mixed security prisons represent 10% of the 862 soon-to-be-released prisoners in the selected facilities. Similarly, women were over-sampled and account for about 10% of the sample (N = 58). About a third (N = 171) of the total sample were recidivists (i.e., previously imprisoned).

Table 1 presents the basic characteristics of the sample. The mean age was 38.2 years and the sample had been incarcerated, on average, for 3.3 years. More than half earned less than $5 USD daily (the international poverty rate) prior to their current incarceration, compared to 16% in the general population (The World Bank, 2014).

Table 1.

Characteristics of the study sample of prisoners (N = 510).

N (%)a
Demographics
Mean age, years (range) 38.2 (21–63)
Gender
 Male 452 (88.6)
 Female 58 (11.4)
Azerbaijani ethnicity 462 (90.6)
Criminal justice history
 Recidivists 171 (33.5)
 Mean number of previous incarcerations for recidivists (S.D.) 1.6 (0.7)
 Mean current incarceration duration, years (S.D.) 3.3 (2.6)
 Mean time before community release, months (S.D.) 4.0 (2.4)
Socioeconomic indicators
In a relationship
 Yes 278 (54.5)
 No 220 (43.1)
Completed high school 188 (36.9)
Below poverty line 270 (52.9)
Mental health
Mean CES-D score (S.D.) 7.16 (3.73)
Major depression 128 (25.1)
Mild to severe anxiety levels 24 (4.7)
Social support scale score (S.D.) 3.1 (1.2)
Health-related Quality of Life (SF-36)
 Mean physical composite score (S.D.) 49.0 (4.3)
 Mean mental composite score (S.D.) 35.9 (6.2)
HIV
HIV infected 19 (3.7)
Mean CD4 count, cells/mL (N = 19) 392.5
 CD4 > 350 14 (73.7)
 CD4 ≤350 5 (26.3)
Currently prescribed antiretroviral therapy 12 (63.2)
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Key: S.D. = standard deviation; CES-D = 10-item Clinical Epidemiological Scale for Depression.

a

Percent of those reporting.

3.2. Prevalence of infectious diseases and chronic illness

Fig. 2 shows the results of serological testing stratified by gender. Hepatitis C (N = 195, 38.2%) was most prevalent, followed by HIV (N = 19, 3.7%) and syphilis (N = 19, 3.7%), and hepatitis B (N = 14, 2.7%). All infectious diseases were significantly more prevalent among men. Nearly three-quarters (14 of 19) of the HIV-infected participants were aware of their HIV status prior to this study. The mean CD4 count was 392.5 cells/mL and 12 HIV-infected participants (63.2%) were currently prescribed antiretroviral therapy (ART). The mean CD4 count of those already aware and unaware of being HIV-infected was not significant (390.7 vs 397.6 cells/mL), but most aware patients were on ART.

Fig. 2.

Fig. 2

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Prevalence of infectious diseases. (N = 510).

Respondents were asked if a doctor had ever informed them that they had certain chronic conditions. Most commonly, they had been told they had depression (33%), hypertension (26%), and a heart condition (22%).

3.3. Substance use disorders and mental illness

One-quarter met symptomatic criteria for major depression and 4.7% met criteria for moderate to severe anxiety. On a social support scale ranging from 1 to 5, with 5 representing maximum social support, the mean score was 3.1.

Fig. 3 depicts the prevalence of SUDs with drug administration route for the 30 days before incarceration. Overall, 38.1% met criteria for having a SUD, highest being opioid (32.5%) and lowest being alcohol use disorders (10.2%); 7.5% had used at least two substances, meeting criteria for polysubstance use. The overwhelming majority (76%) of those who had used any substance had used only one substance—all but two of whom had used opioids. There was evidence of concurrent lifetime dependencies: 60% of opioid users had an alcohol use disorder and 58% of opioid users had used amphetamines.

Fig. 3.

Fig. 3

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Prevalence of substance use disorders (N = 510).

3.4. Sex and drug risk behaviors

Nearly one-third of individuals (31.9%) reported having ever injected drugs. In the 30 days prior to their arrest and incarceration, 39.8% (N = 64) of injectors reported reusing injection equipment (a needle, syringe, or container) that had been used by someone else. Men were much more likely to have ever injected drugs (153 men vs 8 women) and 5.6% of those who had ever injected had used a syringe surrogate (e.g., ballpoint pen). Only 12 injectors (7.4%) reported receiving needles from a needle/syringe program (NSP) and only two injectors (one male and one female, both of whom stated they had been “satisfied” with the program) had ever been enrolled in community-based OST; however, 25% of PWIDs stated that they would like to be enrolled in OST, but only 13.4% agreed that OST should be available in the prison setting.

More than a third of the respondents (N = 166, 36.7%) reported having had sex without a condom in the 30 days prior to their arrest and incarceration. Of the male respondents, 17 had had unprotected anal sex with other men (approximately 10% of the total sampled males who had had sex without a condom); and two out of these 17 males were HIV positive. Four of the male respondents reported that they had engaged in unprotected sex with a partner they knew was HIV-positive. Women respondents were significantly (22% vs 4%; p < 0.001) more likely to engage in transactional sex than men.

3.5. Correlates of HIV and hepatitis C infection

Table 2 presents the bivariate and multivariate analyses of the correlates of HIV infection. The final model found previous STI diagnosis (sexual risk) and drug injection as the most significant correlates of HIV infection among prisoners. Additional sexual risks that were independently associated with HIV included unprotected anal or vaginal sex. Two other factors were associated with HIV, including meeting criteria for an anxiety disorder and having worked in Russia or Ukraine.

Table 2.

Correlates of HIV infection among soon-to-be-released prisoners in Azerbaijan (N = 510).

Covariate N (%)a Bivariate analysis
Multivariate analysis
Unadjusted Odds Ratio 95% C.I. p-Value Adjusted Odds Ratio 95% C.I. p-value
>36 years old 279 (54.8) 1.31 0.50–3.43 0.590 – – –
≤36 years old 230 (45.2) Ref – –
Recidivist 339 (66.5) 1.46 0.58–3.71 0.422 – – –
First time offender 171 (33.5) Ref – –
Completed high school 188 (36.9) 3.36 0.97–11.68 0.057 – – –
Income below poverty line 269 (52.7) 0.53 0.20–1.39 0.196 – – –
Major depression 129 (26.0) 1.35 0.50–3.63 0.551 – – –
Anxiety disorder 24 (4.8) 4.35 1.17–16.20 0.028* 4.62* 1.1–19.9* 0.040*
Hazardous drinking 52 (10.4) 2.46 0.79–7.73 0.122 – – –
Have worked abroad (in Russia or Ukraine) 64 (12.9) 3.62 1.31–10.01 0.013* 4.58* 1.5–14.1* 0.008*
Told by a doctor they had a sexually transmitted infection 30 (6.0) 4.59 1.23–17.15 0.023* 10.42* 2.1–51.4* 0.004*
Has partner 278 (54.5) 2.85 1.06–7.62 0.037* – – –
Use in 30 days before incarceration
Any substance use 154 (31.0) 2.63 1.05–6.61 0.040* – – –
Amphetamine use 2 (0.4) 0.00 0.00 0.999 – – –
Opioid use 151 (30.0) 3.05 1.18–7.89 0.021* – – –
Sedatives use 13 (2.6) 0.00 0.00 0.999 – – –
Multiple-substance use 38 (7.5) 1.40 0.18–10.8 0.750 – – –
Lifetime use
Injected drugs 161 (31.9) 5.94 2.08–17.0 0.001* 8.24* 2.4–28.4* 0.001*
Any substance use 169 (35.7) 4.15 1.55–11.14 0.005* – – –
Risk behavior
Reused syringe, container or needle 65 (13.1) 4.71 1.76–12.64 0.002* – – –
Sex without condom 50 (9.8) 3.76 0.51–6.78 0.009* 3.77* 1.1–12.5* 0.031*
Given money or drugs for sex 27 (5.4) 5.21 1.60–17.00 0.006* 1.80 0.5–7.0 0.080
Sex without condom under influence of drugs 50 (9.8) 3.39 1.02–11.26 0.047* – – –
Tattoo from non-professional 138 (73.8) 1.37 0.53–3.53 0.514 – – –
Akaike Information Criterion (AIC) 277.8
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a

Percent of those reporting.

*

Significant difference, defined as p ≤0.05.

Table 3 presents the correlates of hepatitis C infection. Similar to the correlates for HIV, a history of injecting drugs was a significant independent correlate of HCV infection (p < 0.001), associated with >12-fold odds of infection. Consistent with this, sharing injection equipment portends nearly a five-fold increased likelihood (p = 0.006) of having HCV infection. When controlling for other variables, meeting criteria for an alcohol use disorder or major depression, and female gender all emerge as independently associated with HCV; receiving a tattoo from a non-professional and prison recidivism did not emerge as significant in the final model.

Table 3.

Correlates of HCV infection among soon-to-be-released Azerbaijani prisoners (N = 510).

Covariate N (%)a Bivariate analysis
Multivariate analysis
Unadjusted Odds Ratio 95% C.I. p-value Adjusted Odds Ratio 95% C.I. p-value
Male 452 (88.6) 6.23 2.62–14.80 <0.001* 9.78* 2.4–39.7* 0.001*
Female 58 (11.4) Ref – – Ref – –
Recidivist 339 (66.5) 1.84 1.27–2.68 0.001* 0.76 0.44–1.31 0.315
First time offender 171 (33.5) Ref – – Ref – –
Completed high school 188 (36.9) 0.529 0.82–1.73 0.196 – – –
Have worked abroad (in Russia or Ukraine) 64 (12.9) 1.10 0.64–1.87 0.736
Income below poverty line 269 (52.7) 0.881 0.61–1.27 0.493 – – –
Major depression 129 (26.0) 2.47 1.75–4.00 <0.001* 2.04* 1.15–3.60* 0.014*
Anxiety disorder 24 (4.8) 2.33 1.02–5.37 0.046* 0.49 0.14–1.69 0.257
Alcohol use disorder 2 (10.2) 4.42 2.35–8.32 <0.001* 3.33* 1.46–7.59* 0.004*
Use in 30 days before incarceration
Any substance use 154 (31.0) 13.91 8.75–22.11 <0.001* – – –
Amphetamine use 2 (0.4) 1.60 0.10–25.75 0.740 – – –
Opioid use 151 (30.0) 15.69 9.74–25.26 <0.001* – – –
Sedatives use 13 (2.6) 3.72 1.13–12.26 0.031* – – –
Reused syringe, container or needle 65 (13.1) 26.62 10.44–67.83 <0.001* 4.79* 1.57–14.61* 0.006*
Multiple-substance use 38 (7.5) 0.38 0.19–0.74 0.004* – – –
Lifetime use
Injected drugs 161 (31.9) 20.63 12.68–33.57 <0.001* 12.85* 7.09–23.29* <0.001*
Any substance use 169 (35.7) 16.96 10.61–27.13 <0.001* – – –
Tattoo from non-professional 138 (73.8) 1.97 1.36–2.86 <0.001* 1.33 0.81–2.18 0.264
Akaike Information Criterion (AIC) 436.6
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*

Significant difference, defined as p ≤0.05.

a

Percent of those reporting.

4. Discussion

This prison-based biosurveillance study is the first in Azerbaijan—a country with a low HIV prevalence concentrated among PWIDs. The prevalence of infectious diseases, HIV risk behaviors, and SUDs in our sample is high. For example, HIV prevalence is 18.5-fold greater among prisoners than found in the community (3.7% vs 0.2%). Our results are consistent with a concentrated HIV epidemic among PWIDs in Azerbaijani prisoners, similar to those in other FSU countries. At the same time, these data provide early evidence of the independent influence of sexual risks on HIV infection. Additionally, there are insights that other drivers of HIV in Azerbaijan are contributing to a growing epidemic, including migration to and from high HIV endemic countries (i.e., Russia and Ukraine) as well as having underlying mental illness.

The data presented in this study, showing an HIV prevalence 50% greater than previously reported (WHO/UNAIDS/UNICEF, 2010), portends concerns of a more volatile, transitioning HIV epidemic. Indeed, the findings correspond closely with the burgeoning heterosexual HIV transmission pathway in Azerbaijan through which almost a quarter of new HIV cases are contracted (Kvitsinadze et al., 2010). For example, a previous diagnosis of a STI raised the odds of HIV infection by a factor of 10 in our sample, and 14 of the 19 cases of diagnosed syphilis were unaware of being infected. Prior unprotected sex was a strong correlate of HIV infection, and almost a quarter of women (21.6%) engaged in unprotected transactional sex, potentially facilitating the spread of HIV and other STIs. These findings are especially alarming given the major STI epidemic currently underway in FSU countries (Borisenko et al., 1999; Uuskula et al., 2010).

While systematic approaches to address the co-occurring HIV and substance abuse epidemics in Central Asia are currently limited (Vagenas et al., 2013), these data from Azerbaijan provide some of the first evidence that HIV Treatment as Prevention (TasP) goals are attainable in prison settings within a FSU country. Unlike in Ukraine where <50% knew their HIV status and almost none were on ART (Azbel et al., 2014), nearly three-quarters of HIV-infected prisoners t knew their status and 63.2% were receiving ART. This performance was likely facilitated by a 2006 scale-up of ART in prisons, and is corroborated by an evaluation which found prisoners comprised 25.3% (N = 238) of the 941 PLWHA receiving ART in Azerbaijan in 2011 (Gadirova and Alakbarov, 2011). Despite this optimism, there is still room for improved HIV detection, linkage to care, and deployment of evidence-based continuity to care interventions post-release (Thompson et al., 2012).

While ART coverage is relatively high in Azerbaijan, scale-up of effective HIV prevention strategies like OST and NSPs is far below even low target levels (Vickerman et al., 2014). In our sample, only two and 12 inmates had ever utilized OST or NSPs, respectively. One potential solution to enhance HIV prevention and treatment is to introduce OST for prisoners with opioid use disorders and maintain it post-release (Haig, 2003; Kinlock et al., 2009; Wickersham et al., 2013a, 2013b). Despite OST having been introduced in Azerbaijan as a pilot project in 2004, the program has not been expanded and is not available within prisons with only 137 people receiving OST in 2013 (Ministry of Health of the Republic of Azerbaijan, 2014). Recent modeling from FSU countries like Azerbaijan where the HIV prevalence among PWIDs is low suggest that OST and NSP coverage can remain as low as 23–34% in order to curtail the HIV epidemic (Vickerman et al., 2014).

The extraordinarily high HCV prevalence in prisoners, primarily associated with drug injection, has important implications for HCV treatment. The first critical step of the HCV treatment cascade, diagnosis, is relatively poor (30.2%) and will require expanded HCV testing. The long duration of incarceration is certainly sufficient to treat patients with interferon-based therapies, but these treatments are unduly long, are associated with numerous adverse side effects, and have relatively low cure rates (Berenguer et al., 2009). Newer well-tolerated, highly efficacious direct-acting antivirals are currently inaccessible in Azerbaijan, as in many low- and middle-income countries due to price constraints. Evidence of significantly reduced pricing is emerging, however, including availability of generic medications (Hill et al., 2014). Moreover, these data suggest that there are over 7,000 prisoners infected with HCV and treatment would require monumental efforts, but could potentially be achieved within the structured prison setting. Without treatment, 330 HCV-infected prisoners would be released without treatment within the next six months and, in the absence of evidence-based harm reduction programs, will continue to fuel HCV transmission.

Our data also provide a glimpse into the role of migration between Azerbaijan and FSU countries of Russia and Ukraine, with our finding of migration as an independent contributor to the Azerbaijani HIV epidemic. Earlier data suggest that international long distance truck drivers, many of whom inject drugs, have high HIV prevalence (Botros et al., 2009). Their drug use persists when in Azerbaijan, resulting in incarceration. An estimated 500,000 Azerbaijanis seeking employment opportunities in Russia (Paul, 2014), which has one of the world’s fastest growing HIV epidemics (Degenhardt et al., 2013; UNAIDS, 2012; Kazatchkine, 2014; Zabransky et al., 2014). This migration from high to lower endemic countries, in the setting of drug injection, presents a potential bridge that fuels community transmission and should present an opportunity for targeted interventions.

Despite the many important findings from this study, the cross-sectional study design has inherent limitations. Although our study successfully describes correlates of infectious diseases, it provides no insight as to the temporal or causal nature of the observed relationships. In addition, observational studies are vulnerable to confounding such that some of the correlations reported herein cannot be substantiated (i.e., correlation between HIV and anxiety or hepatitis C and depression) and best elucidated with longitudinal designs. Moreover, recall bias from remote pre-incarceration events and/or under reporting bias about potentially stigmatizing conditions and HIV risk behaviors limit interpretation. Clearly, further analyses to disentangle possible mediating and moderating relationship among the variables, as well as longitudinal designs that would allow establishing causality are warranted.

The dearth of evidence-based harm reduction programs (OST and NSPs) in Azerbaijani communities and prisons generates a high-risk injection environment furthering HIV transmission, which is compounded in the setting of high-risk sex, drug use, and the presence of STIs. Though incarceration itself should be replaced where possible with non-custodial alternatives like community-based evidence-based treatment with OST, prisons still present a seminal platform for the prevention, detection, and treatment of diseases in this vulnerable population, which is otherwise largely missed by existing community treatment and prevention services. The HIV epidemic in Azerbaijan is still low enough that scaling up ART, OST and NSPs to as low as 25–35% would be sufficient to contain and even reduce HIV incidence. Despite this, the prison setting in Azerbaijan has not been fully harnessed to implement evidence-based interventions, which would significantly improve the health, not only of inmates, but also of their community contacts. Since the transition to the community is critical to ending the cycle of relapse and recidivism, efforts must be concentrated on the time before release to establish comprehensive harm reduction and treatment programs with linkage to community care.

Acknowledgments

Role of funding source 

This research received funding from the National Institute on Drug Abuse for research (R01 DA029910, Altice, PI and R01 DA033679), career development (K24 DA017072 for Altice and K01 DA038529 for Wickersham). This work was also supported in part by the Doris Duke Charitable Foundation through a grant supporting the Doris Duke International Clinical Research Fellows Program at Yale University School of Medicine. Wegman is a Doris Duke International Clinical Research Fellow.

Footnotes

Contributors 

FLA and JAW conceived and designed the study along with SD and LA, analyzed the data with LA and revised the manuscript in association with SD, MP, and MW. LA was responsible for performing the experiments along with JAW and wrote the manuscript together with MW and MP.

Conflict of interest

No conflict declared.

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