Series HIV and related infections in prisoners 1 Global burden ...

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www.thelancet.com Published online July 14, 2016 http://dx.doi.org/10.1016/S0140-6736(16)30466-4 1

HIV and related infections in prisoners 1

Global burden of HIV, viral hepatitis, and tuberculosis in prisoners and detaineesKate Dolan, Andrea L Wirtz, Babak Moazen, Martial Ndeffo-mbah, Alison Galvani, Stuart A Kinner, Ryan Courtney, Martin McKee, Joseph J Amon, Lisa Maher, Margaret Hellard, Chris Beyrer, Fredrick L Altice

The prison setting presents not only challenges, but also opportunities, for the prevention and treatment of HIV, viral hepatitis, and tuberculosis. We did a comprehensive literature search of data published between 2005 and 2015 to understand the global epidemiology of HIV, hepatitis C virus (HCV), hepatitis B virus (HBV), and tuberculosis in prisoners. We further modelled the contribution of imprisonment and the potential impact of prevention interventions on HIV transmission in this population. Of the estimated 10·2 million people incarcerated worldwide on any given day in 2014, we estimated that 3·8% have HIV (389 000 living with HIV), 15·1% have HCV (1 546 500), 4·8% have chronic HBV (491 500), and 2·8% have active tuberculosis (286 000). The few studies on incidence suggest that intraprison transmission is generally low, except for large-scale outbreaks. Our model indicates that decreasing the incarceration rate in people who inject drugs and providing opioid agonist therapy could reduce the burden of HIV in this population. The prevalence of HIV, HCV, HBV, and tuberculosis is higher in prison populations than in the general population, mainly because of the criminalisation of drug use and the detention of people who use drugs. The most effective way of controlling these infections in prisoners and the broader community is to reduce the incarceration of people who inject drugs.

IntroductionFrom the beginning of the AIDS epidemic in 1981, the association between HIV, tuberculosis, and prisons was apparent,1 with HIV responsible for a steep rise in tuberculosis in US prison populations.2 This is important because the prevalence of HIV in prisons in many countries is high, with one review reporting levels greater than 10% in 20 low-income and middle-income countries.3 Several factors have a role in the epidemics of HIV, tuberculosis, and related infections in prisons.4 Many individuals who are most likely to be incarcerated are at greatest risk of these infections, whether because of injection drug use for HIV and viral hepatitis or poverty and overcrowding for tuberculosis. Drug injection is common in prison inmates, ranging from 2% to 38% in Europe, 34% in Canada, and up to 55% in Australia, in stark contrast with the percentage in the general population, estimated at 0·3% in the European Union and 0·2% in Australia.5 Prisons provide many opportunities both for the spread4 and prevention of these infections.6

The situation is complicated further by the expansion of parallel prison systems for those suspected of drug use in at least 27 countries. These compulsory drug detention centres operate extrajudicially and often under the guise of drug treatment (panel 1).20 Punishment and inhumane conditions are widespread, but evidence-based treatment for drug dependence and infectious diseases is rare or non-existent.7,21 However, prisons not only pose a threat to the health of people incarcerated within them. They also pose a risk to staff and to the population at large, because detainees are not a static population, but move around the prison system and back and forth from the outside world.

The risks particularly lie at the interface between prisons and society outside. In the USA, HIV incidence is highest

in detainees who were released and re-incarcerated compared with continuously incarcerated prisoners, people who inject drugs with no history of incarceration, and men who have sex with men (MSM; panel 2).4 The period immediately after release is especially risky for receptive syringe sharing, acquisition of HIV and hepatitis C virus (HCV), and mortality.29–32 Thus, the transition between the prison and community settings represents a high-risk

Published Online July 14, 2016 http://dx.doi.org/10.1016/S0140-6736(16)30466-4

This is the first in a Series of six papers on HIV and related infections in prisoners

National Drug and Alcohol Research Centre (Prof K Dolan PhD, R Courtney PhD), and Kirby Institute (Prof L Maher PhD), University of New South Wales, Sydney, NSW, Australia; Center for Public Health and Human Rights, and Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA (A L Wirtz PhD, Prof C Beyrer MD); Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran (B Moazen MScIH); Center for Infectious Disease Modeling and Analysis (M Ndeffo-mbah PhD, Prof A Galvani PhD), and Epidemiology and Public Health (Prof F L Altice MD), Yale University, New Haven, CT, USA; Griffith Criminology Institute & Menzies Health Institute Queensland, Griffith University, Brisbane, QLD, Australia (Prof S A Kinner PhD); Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK (Prof M McKee DSc); Health and Human Rights Division, Human Rights Watch, New York, NY, USA (J J Amon PhD); and Centre for Population Health, Burnet Institute, Melbourne, VIC, Australia (Prof M Hellard PhD)

Correspondence to: Prof Kate Dolan, National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW 2052, Australia [email protected]

Key messages

• PrevalenceofHIV,HCV,HBV,andtuberculosisishigherinprison populations than in the general population, mainly because of the criminalisation of drug use and the detention of people who inject or use drugs

• WestronglysupporttheUN’s2012calltoclosecompulsory drug detention centres and expand voluntary, evidence-based treatment in the community

• Mathematicalmodellingsuggeststhatincarcerationandre-incarceration of people who inject drugs contributes to the overall HIV epidemic and a reduction in incarceration of this population will reduce the incidence of HIV

• Evidence-basedpreventionandtreatmentsuchasopioidagonist therapy and antiretroviral therapy can substantially reduce the incidence of HIV, HCV, and HBV, and reduce drug dependence in this population

• Responsestoco-infectionwithHIVandtuberculosisshouldinclude an integrated, patient-centred model of prevention and care, with systematic screening of high-risk groups and equitable access to effective treatment

• Themosteffectivewayofcontrollinginfectioninprisoners and the broader community is to reduce mass incarceration of people who inject drugs

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2 www.thelancet.com Published online July 14, 2016 http://dx.doi.org/10.1016/S0140-6736(16)30466-4

environment, especially for people with substance use disorders.31 This is important because, although an estimated 10·2 million people were incarcerated at any time in 2014, over 30 million individuals transition from prison to the community each year.33 Prisons act as incubators for tuberculosis and HIV, because they are associated with higher levels of infection than in the surrounding populations,3,34 yet many countries have parallel and vertical systems, with fragmented policy responses to these interlinked issues—prisons, HIV, viral hepatitis, and tuberculosis—and interruptions of surveillance and treatment during transitions. This Series paper encourages a coordinated response by reviewing the global epidemiology of HIV, HCV, HBV, and tuberculosis in prison populations.35,36

Disease burden in prisoners and detaineesWe did a comprehensive review of studies of prevalence and incidence data on HIV, HCV, HBV, tuberculosis, and co-infection with tuberculosis and HIV in prisoners and detainees, published between Jan 1, 2005, and Nov 30, 2015, for 196 countries in 2015 (appendix p 2, 4).37

We searched for studies with biological markers of each infection in general prisoners and in people who inject drugs, MSM, female sex workers, and transgender people, in prisons, jails, and compulsory drug detention centres.

Of 11 000 publications identified, 299 met inclusion criteria for the meta-analysis of infections (appendix p 7). These data show substantial heterogeneity in disease burden across regions (figure 1).

Global estimates of prisoners with HIV, HCV, HBV, and tuberculosis infectionOf an estimated 10·2 million people incarcerated worldwide on any given day in 2013,22 we estimated the midpoint of the number infected was 389 000 with HIV (3·8%), 1 546 500 with HCV (15·1%), 491 500 with chronic HBV infection (4·8%), and 286 000 with active tuberculosis (2·8%; appendix pp 9, 15, 20, 24).

Overall, prevalence of all infections was substantially higher in prison populations than in surrounding communities, especially where there are generalised HIV epidemics, such as in sub-Saharan Africa,38 and where there is a high prevalence of injection drug use, such as in eastern Europe and central Asia (figure 1, 2, appendix p 9).39

HIV infectionPooled estimated HIV prevalence in prisoners74 of 196 countries37 had HIV prevalence data in 2015 (200 datapoints) in prisoners (appendix p 8). The regions most affected were the two African regions (east and southern Africa and west and central Africa), which have a high prevalence in the general population, and the two European regions (eastern Europe and central Asia and west Europe), reflecting the over-representation of people who inject drugs in prison—a group with a high prevalence of HIV infection. Transmission via injection drug use also contributes to the HIV epidemic in the Middle East and north Africa and Asia Pacific regions.

While injection drug use is rare in the Caribbean and Latin America, HIV prevalence in prisoners is generally higher than in North America, possibly reflecting the concentrated epidemic of HIV in MSM40 and cocaine users in Latin America.41

Female inmates had a slightly higher prevalence of HIV than male prisoners in six regions (both African regions, Asia Pacific, both European regions, and North America) and lower than male inmates in Latin America and the Middle East and north Africa (appendix p 9). Notable differences were found in west and central Africa, where the prevalence of HIV in women was almost double that of men (13·1% vs 7·1%), and in eastern Europe and central Asia, where it was almost three times higher than in men (22·1% vs 8·5%). HIV prevalence was higher in prisoners than in the general population in eastern Europe and central Asia (4·1% vs 0·5%) and western Europe (4·6% vs 0·2%).38

Panel 1: Compulsory drug detention centres

Some 27 countries detain drug users, or suspected drug users, in compulsory drug detention centres for the purpose of treatment or rehabilitation. In east and southeast Asia, an estimated 600 000 drug users are detained in roughly 1000 (mostly government-run) centres.7 In Latin America,8,9 and sub-Saharan Africa,10–12 an unknown number of individuals are detained in hundreds of faith-based and unregulated residential treatment centres. Abuses in these facilities include being shackled to trees and starved.13 Similar unregistered treatment centres operate in central Asia.14

Detainees are typically held in forms of administrative detention, often without due legal process,assessmentofdrugdependency,orinformedconsent.Evidence-baseddrugdependency treatment such as opioid agonist therapy is rarely provided,15 while physical abuse—including torture, forced prayer, forced exercise to sweat drugs out of the body, and manual labour (sometimes forced labour)—are common.16Estimatesofdiseaseburden in compulsory drug detention centres are given in the appendix (p 31).

In Vietnam, one formerly detained child described punishment in a compulsory drug detention centre, where the staff beat him on the arm and back with a truncheon. He reported being held in a small punishment room for 3 months. Another ex-detainee served his 2-year sentence only to have it extended by 5 years with no reason given.16

In Cambodia, one former detainee reported having his head bashed against a wall until he lost consciousness.16 One child, detained in a compulsory drug detention centre in Cambodia, said he saw a doctor after he was beaten. After the doctor treated the child, the doctor told the child to not try and escape again.17 In Thailand, individuals detained in compulsory drug detention centres reported being beaten or made to roll on gravel as a punishment.18

Ex-detaineeshavelimitedornoaccesstohealthcare.InChina,oneindividualdetainedinGuangxi province reported that he was unable to continue taking his antiretroviral drugs once placed in (compulsory) detoxification. Another person, detained in Yunnan province, reported that many incarcerated people have tuberculosis and many acquire tuberculosis while incarcerated, yet there is no treatment.19

These unregulated and abusive forms of detention in the name of drug treatment do not meet minimum health or human rights standards and should be closed.

See Online for apppendix

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HIV prevalence in imprisoned people who inject drugsOf the 200 HIV datapoints, only 47 were related to people who inject drugs in 16 countries. Prevalence estimates from Iran ranged from 0·7% in 2002 to 18·2% in 2003 and fell to 2·3% in 2007. After two large outbreaks of HIV in prisons (panel 3), Iran increased opioid agonist therapy coverage from 100 to over 25 000 drug users, provided condoms and conjugal visits, and piloted six needle and syringe programmes in prisons from 2002.47,49 Australia’s HIV infection prevalence of almost zero in people who inject drugs in and out of prison can be traced back to very early introduction of community-based needle and syringe programmes in 1986, which prevented an estimated 25 000 HIV cases in people who inject drugs.58

Hepatitis C infectionPooled estimated HCV prevalence in prisoners46 of 196 countries had HCV prevalence data (171 data-points; hepatitis C antibody) in prisoners from 2005 to 201537 (appendix p 8). HCV infection in prisoners is high worldwide, exceeding 10% in six regions (figure 1, 3, appendix p 15). This finding reflects the increased infectivity and earlier HCV entry into populations of people who inject drugs compared with HIV.59

Epidemic patterns of HCV infection related to injection drug use persist in Europe. HCV prevalence estimates were high in the eastern Europe and central Asia region at 20·2% (95% CI 11·8–30·1), in west Europe at 15·5% (12·2–19·1), and in North America at 15·3% (13·1–17·7). Injection drug use is rare in the Caribbean, which probably accounts for the absence of HCV data (and possibly infection) in prison populations. In Latin America, HCV prevalence was 4·7% (3·1–6·7), also reflecting the low level of drug injection in this region. Insufficient data, particularly for female inmate populations, precluded gender comparisons of the prevalence of HCV.

HCV prevalence in imprisoned people who inject drugsOf the 171 datapoints on HCV infection, only 53 related to people who inject drugs in 19 countries. As expected, the prevalence of HCV in imprisoned people who inject drugs was high or very high, ranging from 8% to 95%, most of which were above 40% (appendix p 28). Only six countries had multiple datapoints from which trends could be surmised. With ten datapoints, Iran showed a clear reduction in prevalence from 78·3% (2001) to 43·4% (2009).49 No data were identified for HCV in people who inject drugs for either African regions or Latin America.

Hepatitis B infectionPooled estimated HBV prevalence in prisoners43 of 196 countries had HBV prevalence data (56 data-points) in prisoners from 2005 to 2015 (figure 3, appendix pp 8, 20).37 The prevalence of HBsAg in

prisoners in west and central Africa was very high at 23·5% (95% CI 19·8–27·5)—the highest burden of all four types of infection and across the nine regions. High levels of chronic HBV infection were also reported in east and southern Africa (5·7%, 95% CI 2·9–9·4) and in eastern Europe and central Asia (10·4%, 1·9–24·6). In other regions, HBV prevalence was below 5% and unsafe injection drug use and unprotected sex remain important modes of transmission.60

HBsAg prevalence in prisoners relative to the general populationThe burden of HBV in the general population is highest in sub-Saharan Africa, with a meta-analysis estimate of HBsAg prevalence at 8·8%, which was primarily attributed to vertical transmission from mother to child,

Panel 2: Mass incarceration and the HIV epidemic in the USA

The US incarceration rate of 716 per 100 000 population is almost five times the global average of 146 per 100 000.22 This translates into 2·2 million people, or almost 1% of the US population behind bars on any given day in 2013. In the 1970s, this rate was a meagre 75 per 100 000. However, the Rockefeller Drug Laws, introduced in 1973, caused the incarceration rate to increase by five times in a decade.23 Specifically designed to target heroin and crack cocaine users, these laws mandated lengthy minimum sentences for many drug offences, including the possession and sale of small quantities of drugs, which matched sentences for rape, assault, and robbery. These laws took account of previous offences and culminated in the three-strikes law (ie, three strikes and you are in for life), for minor, but multiple offences.

By 1985, drug offenders comprised one-third of all inmates in New York state. The burden of incarceration fell heavily on young black men, who were 40 times more likely to be incarcerated than their white peers, and Hispanic men, who were 30 times more likely to beimprisonedthantheirwhitepeers.NewYorkCity’sRikersIslandprisononcehadthelargest concentration of HIV-positive people in the USA.

HIV prevalence is roughly three times higher in incarcerated individuals than in the general US population.24 HIV prevalence in the state prisons of Florida, Maryland, and New York exceeds 3%, which is higher than the national prevalence of any country outside of sub-Saharan Africa.25 At least one in six HIV-positive American people passes through a correctional centre each year.23 HIV infection has been linked to a history of incarceration; however, proving the infection occurred in prison is difficult. Although cases of intraprison HIV and HBV transmission have been recorded (panel 3), evidence suggests that most HIV-positive people were infected before prison entry. For people in detention with HIV infection, treatment outcomes have been good, but retention in treatment after release is more challenging.26

The post-release period can also be especially dangerous for treatment interruptions, fatal andnon-fataloverdose,andinfectionacquisition.TheALIVEstudy27 reported that the risk of HIV transmission increases, rather than decreases, on release from prison. Incarceration plays a role in delaying recovery from drug dependence. Incarceration also has an impact on those in the community, most probably through the return of prisoners who have been released and are infectious, who have interruptions in antiretroviral treatment. The main risk behaviour for newly diagnosed, heterosexually acquired HIV infection in African-American women was having sex with a partner who had a history of incarceration.28 The approach to drug policy and the mass incarceration of drug users in the USA is counterproductive, expensive, and increases the risk of HIV treatment interruption and subsequent transmission.23

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low HBV vaccine coverage (including birth dose), and unsafe medical products and procedures.61 In Australia, the prevalence of HBsAg was 2·3% in prison and 1·0% in the community.62

HBsAg prevalence in imprisoned people who inject drugsOf the 56 HBV datapoints, 24 related to people who inject drugs in ten countries. Iran and Australia were the only countries with multiple datapoints (appendix p 28). In Iran, HBV prevalence was significantly and positively associated with the frequency and duration of imprisonment.49 Despite a reduction in the proportion of Australian prisoners reporting injection drug use, evidence of HBV infection remains high in

prison entrants, with many unaware of their infection status.62

Tuberculosis and co-infection with HIVPrevalence of active tuberculosis and co-infection with HIV in prisonersEstimates of active tuberculosis in prison populations were higher than in the general population in almost all settings, with investigators of one study, from the Dourados prison in Brazil, estimating that prevalence of tuberculosis was 40 times higher than in the general population.63

25 of 196 countries reported tuberculosis prevalence data (46 datapoints) and 17 of 196 countries prevalence data on co-infection with HIV and tuberculosis (25 data-points) in prisoners from 2005 to 2015 (figure 4, appendix pp 8, 27).37 In the three regions with the highest prevalence of HIV and viral hepatitis, active tuberculosis was also common (appendix pp 24, 27): 5·3% (95% CI 2·1–10·0) in east and southern Africa, 2·9% (2·4–3·6) in west and central Africa, and 4·9% (1·8–9·3) in eastern Europe and central Asia. In the African regions, active tuberculosis infection was associated with overcrowding, high inmate turnover, and increased frequency or duration of incarceration.64–66 Disease burden was lower in other regions, though only one study was identified in the Middle East and north Africa, two in the western European region, and none in the Caribbean.

A systematic review67 found that the incidence of tuberculosis is 23 times higher in prison populations than in the general community, and that the prevalence of drug-resistant tuberculosis is also substantially higher. Increased prevalence of HIV infection exacerbates the effect of incarceration on tuberculosis incidence, highlighting the importance of a coordinated approach to prevent and treat these two infections.34 Important for tuberculosis control in prisons is case-finding to ensure early detection and treatment, case isolation and infection control measures,

0–1·01·1–5·05·1–10·010·1–15·015·1–20·0>20·0No data meeting inclusion criteria

North America1·3% (95% CI 1·0–1·7)

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West andcentral Africa8·2% (95% CI 6·2–10·5)

Asia Pacific1·4% (95% CI 0·9–1·9)

Western Europe4·2% (95% CI 2·7–6·1)

Figure 2: Global and regional burden of HIV in prison inmates, published between 2005 and 2015

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Figure 1: Regional prevalence of HIV, hepatitis C, HBsAg, and active tuberculosis in prisoners, published between 2005 and 2015HCV=hepatitis C antibodies.

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initiation of tuberculosis treatment followed soon after by HIV treatment, and treatment of latent tuberculosis infection, especially in patients with HIV.

Studies investigating HIV and tuberculosis co-infection are of two types (appendix p 27). The first study type measures HIV and tuberculosis co-infection in all prisoners, which typically finds prevalence estimates that are less than 10% of the prison population, ranging from 1·6% (Zambia) and 5·1% (South Africa) in east and southern Africa to 0·3% (Guinea) and 8·9% (Nigeria) in west and central Africa. The figures were less than 1% in studies from Latin America and western Europe. The second type of study measures HIV prevalence in inmates with tuberculosis infection and vice versa. Studies of HIV in individuals with tuberculosis done in Africa typically report a prevalence of 40% and higher (Burkina Faso 75%, Uganda 57%, Zambia 45·8%, and South Africa 42–58%). Prevalence estimates of tuberculosis in people with HIV infection tend to be lower (Burkina Faso 20%, Ethiopia 47%, and Malaysia 17%; appendix p 27).

Incidence of HIV, HCV, HBV, and tuberculosis in prisonersFew incidence studies were found on HIV (three countries), HCV (four), HBV (two), and tuberculosis (14; appendix p 32). Spain had detailed annual HIV incidence data from 2000 to 2014 that revealed a steady decline from 0·70% to 0·04% per year over 14 years.68 A large prospective study of hepatitis C incidence in prisons in Australia reported an annual incidence of 14·1%,69 which was high compared with Scotland (0·9%),70 the USA (0·4%),71 and Spain (1·7%).72

Of the 14 countries with tuberculosis data, only seven had multiple incidence rates. Countries that had a decrease in incidence were Colombia,73,74 Argentina,75 Hong Kong,76 Macedonia,77 and Romania.78 An increase in tuberculosis cases in prison was observed in the USA (figure 5).79

The potential effect of increased incarceration on tuberculosis in Europe and central Asia was modelled.34 For each percentage point increase in incarceration rates, there was a corresponding increase in tuberculosis incidence of 0·34% (population attributable risk; 95% CI 0·10–0·58, p<0·01). Mathematical modelling of tuberculosis transmission in Ukraine further suggests that incarceration contributes to 75% of new tuberculosis infections in people who inject drugs.80

Infectious disease prevalence in key populations HIV, HCV, HBV, and tuberculosis in imprisoned MSM, female sex workers, and transgender peopleEstimates of infectious diseases in key populations who become imprisoned (eg, MSM, female sex workers, and transgender people) are less frequently reported than in people who inject drugs. In 2008, HIV prevalence in Ghana in imprisoned female sex

workers (n=73) was 11% and 8·9% in MSM (n=403).81 HIV prevalence in imprisoned MSM was 43·8% in Nigeria (n=32 in 2009), 2·6% in Iran (n=113), and 5·5–34·0% in the USA.82–90 The only study of transgender prisoners was done in Argentina, in which half of transgender prisoners (six of 11 people) were HIV positive.75 US studies provided estimates of HIV prevalence in female sex workers from 2·0% to 5·6%.89,91

Imprisoned MSM in the USA and Iran had high levels of exposure to HCV (50%)82,92 compared with imprisoned MSM in Nigeria (12·5%).83 Imprisoned MSM had high levels of HBV in Ghana (40·2%)81 and Nigeria (56·3%).83 Female sex workers in Ghana also had high levels of HBV infection at 37·0%.81

Panel 3: Outbreaks of infectious diseases in prisoners

One of the first recognised HIV outbreaks occurred in a Bangkok prison in 1988.42 The outbreak was only detected once infected inmates were released and HIV in people who inject drugs escalated from 2% to 43% over the course of several months. An investigation revealed that HIV incidence in prison was very high at 35 per 100 person-years.43,44 In Lithuania, a policy of segregation saw a prisoner who was seroconverting to HIV infection housed with individuals who were HIV negative. At least 284 prisoners were identified as infected with HIV in a few months, which doubled the number of diagnosed HIV cases in Lithuania.3,45 Two outbreaks in Russian prisons saw more than 400 (of 1824) prisoners infected in Nizhnekamsk and 260 inmates infected in the Tatarstan region in 2001.3,46 Large outbreaks have occurred in prisons in Iran and Ukraine, with hundreds of prisoners infected.47,48 Iran increased opioid agonist therapy places from 100 to over 25 000, provided condoms and conjugal visits, and piloted six needle and syringe programmes in prison from 2002.47,49 Small HIV outbreaks have even occurred in areas where prevalence was very low, such as in Australia (four prisoners) and Scotland (ten prisoners), which also had intraprison hepatitis B virus (HBV) transmission.50–52 In 2000, two Australian prisoners were caught sharing syringes and an investigation found that four inmates had acquired hepatitis C virus infection, but none had acquired HIV in prison.53

IntheUSA,Georgia’sstateprisonsystemrecordedanoutbreakofsevencasesofhepatitisBin 2000 and 2001, which were attributed to sex. 52% of 907 susceptible inmates who completed a questionnaire reported at least one risk behaviour for hepatitis B virus infection (including 48% who reported tattooing, sharing a razor [8%], having sex [4%], or injecting drugs [2%]). HBV vaccination was offered only to inmates in the dormitory where the outbreak originated, leaving over 90% of inmates potentially at risk. In the second outbreak, an audit of prison medical records revealed 41 (72%) of 57 HBV cases had occurred in prison. Routine HBV vaccination was recommended for all new prisoners.54–56

In 2006, two ex-inmates in the USA were diagnosed with tuberculosis sparking an investigation.57 Despite one inmate having prolonged symptoms and abnormal chest radiographs, he went undiagnosed while incarcerated. Of 910 exposed inmates who were tested, 53 inmates (5·8%) had newly positive tuberculin skin tests. This included 11 (of 204) new cases of tuberculosis who had been released and re-incarcerated. Of 485 prison employees tested, ten (2·1%) were identified as tuberculin skin test converters.

Although the study of the transmission of these infections prospectively in prison populations has been challenging, these outbreaks illustrate the role that prisons might play in continuing these epidemics beyond the prison wall. It is good public health policy to screen at-risk new prisoners for infectious diseases and to provide inmates with free, easy, and confidential access to prevention programmes such as opioid agonist therapy, antiretroviral therapy, condoms, and HBV vaccination to reduce the risk of outbreaks.6

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Prevalence of HIV, HCV, and HBV in compulsory drug detention centre detainees in China, Taiwan, Vietnam, and IranIn 2012, an estimated 235 000–600 0007,20 drug users were detained for compulsory drug treatment in over 1000 compulsory drug detention centres.20 While the number of compulsory drug detention centres remained the same, the numbers of drug users detained in those centres had increased by 2015. In China, HIV prevalence ranged from 0·2% to 9·5% in general detainees and was 10·3% in people who inject drugs, whereas HCV prevalence was 44% in general detainees (appendix p 31). In Taiwan, HIV prevalence was 6·9% in general detainees and 25·5% in people who inject drugs in detention. Viral hepatitis was also common with HCV prevalence estimated at 30·5% in general detainees and 89·6% in people who inject drugs; HBsAg prevalence was estimated at 16·9% in general detainees and 16·7% in people who inject drugs in detention. In Vietnam, HIV prevalence was 19·8% and

HCV prevalence was 76·9% in people who inject drugs in detention. Iran reported that 24·4% of detained people who inject drugs were HIV positive, 80% were anti-HCV antibody positive, and 5·8% were HBsAg positive (appendix p 31).

Mathematical modelling of HIV transmission and prevention in people who inject drugsWe modelled the contribution of incarceration and re-incarceration on HIV incidence in people who inject drugs and examined the effects of a reduced rate of incarceration, introduction of prison-based opioid agonist therapy followed by post-release opioid agonist therapy, and post-release antiretroviral treatment retention on HIV incidence.

In our model, the increased risk for HIV transmission was captured by behaviour change in people who inject drugs who temporarily receptively share syringes in prison and a combination of interruption of antiretroviral treatment and behaviour change in people who inject

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Figure 3: Global and regional prevalence of viral hepatitis in prison inmates, published between 2005 and 2015(A) Prevalence of HCV antibodies. (B) Prevalence of HBsAg.

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drugs who temporarily receptively share syringes during transient post-release period, which was assumed to last between 1 and 6 months (panel 4, appendix p 33). We quantified the contribution of discontinuation of antiretroviral treatment and temporary syringe sharing to cumulative HIV incidence in people who inject drugs for varying proportions of people who continue this high-risk behaviour for a transient period after release (figure 6). Antiretroviral treatment discontinuation was shown to contribute to less than 5% of cumulative HIV incidence during the epidemic, from epidemic onset to 2015 (figure 7A). This small contribution of discontinuation of antiretroviral treatment to HIV

incidence was due to the small proportion of HIV cases discontinuing antiretroviral treatment at a given time and the short duration of discontinuation.

Specifically, our results show that for people who inject drugs from communities with high HIV prevalence (over 20%), the relative contribution of antiretroviral treatment discontinuation to HIV transmission varies from 0·12% (95% credible interval [CrI] 0·02–0·62) to 0·15% (0·02–1·0), which depends on whether individuals who engage in temporary syringe sharing behaviour only do so during incarceration or continue to do so after release (figure 7A). In communities with moderate HIV prevalence (5–20%), the relative contribution of antiretroviral

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central Africa2946(95% CI 2362–3591)

Asia Pacific1173 (95% CI 712–1747)

Eastern Europe and central Asia4903 (95% CI 1846–9321)

Figure 4: Global and regional prevalence of active tuberculosis in prison inmates, published between 2005 and 2015Data are per 100 000.

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Figure 5: Incidence of tuberculosis in prisons and closed settings*Cumulativeoverthisperiod.†Averageoverthisperiod.‡Estimatedannualrisk1996–2001.

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treatment discontinuation varies from 0·10% (0·01–1·1) to 0·23% (0·03–3·3), which also depends on whether individuals who engage in temporary sharing behaviour only do so while incarcerated (figure 7A). The contribution of temporary syringe sharing to HIV transmission varies from 7·0% (0·1–41·6) to 12·0% (0·5–51·8) in communities with high HIV prevalence, and from 5·8% (0·2–31·7) to

21·1% (0·4–53·0) in communities with moderate prevalence (figure 7B). The contribution of temporary syringe sharing to HIV transmission was higher in communities with lower HIV prevalence than in communities with high HIV prevalence (figure 7B).

To identify the contribution of each model parameter to the variability of temporary syringe sharing to HIV transmission, we calculated the partial rank correlation coefficients (PRCCs), which quantify the magnitude of increase or decrease of the value of an outcome measure predicted by the model as a given input model parameter varies.99

PRCCs indicated that the effect of temporary syringe sharing increases with the rate of re-incarceration for people who inject drugs, the proportion of people who inject drugs who share syringes in prison, and the risk of HIV transmission per episode of syringe sharing (appendix p 41). Conversely, the effect of temporary syringe sharing decreases with the proportion of people who inject drugs who share syringes outside prison, the mortality rate of people who inject drugs who do not have HIV, and the proportion of people who inject drugs and have never been incarcerated (appendix p 41). Given that the rate of first incarceration in people who inject drugs was defined as a non-monotonic functional relationship between the average non-HIV mortality rate for people who inject drugs and the proportion of people who inject drugs who have never been incarcerated (appendix p 33), we deduced from the PRCC results that the rate of first incarceration has a substantial contribution to the effect of temporary syringe sharing. However, that effect could not be captured by the PRCC analysis because of the non-monotonic relationship.

We assessed the effectiveness of three interventions in reducing HIV incidence after 5 years of initial implementation: the incarceration rate of people who inject drugs, prison-based opioid agonist therapy followed by post-release retention, and prison-based opioid agonist therapy followed by post-release opioid agonist therapy combined with antiretroviral treatment retention. We showed that lowering incarceration rates (both first-time incarceration and re-incarceration) by 10–50%, corresponding to a 4·6% (95% CrI 2·6–6·6) to 25·9% (16·9–35·4) reduction of incarcerated people who inject drugs over 5 years, could potentially reduce community-wide cumulative HIV incidence in people who inject drugs by 0·9% (–0·1 to 3·6) to 7·6% (0–26·5) over a 5-year period in communities with high HIV prevalence, and by 1·1% (0·1–3·1) to 15·4% (1·4–29·9) in communities with moderate HIV prevalence (appendix p 42). We found that prison-based opioid agonist therapy followed by post-release retention in treatment during the transitory period of elevated risk behaviour could reduce cumulative HIV incidence by 1·6% (95% CrI 0·1–7·3) for a 20% coverage and by 12·0% (1·4–45·3) as an upper bound of complete (100%) coverage in communities with high HIV prevalence. In

Panel 4: Mathematical model for HIV transmission in people who inject drugs

To assess the fundamental dynamics that govern the interplay between HIV transmission in people who inject drugs in the community and in prison around the world, we developed a deterministic compartmental model of drug injection transmission of HIV in the general community and incarcerated populations (figure 6). Individuals were structured in the model according to their HIV infection history, disease progression, and antiretroviral treatment status (1=susceptible, 2=acute infection, 3=latent infection with CD4 cell count ≥350 cells per µL, 4=latent infection with CD4 cell count <350 cells per µL, 5=pre-AIDS with elevated viraemia, 6=AIDS, 7=initiated antiretroviral treatment with CD4 cell count ≥350 cells per µL, 8=initiated antiretroviral treatment with low CD4 cell count or pre-AIDS, 9=initiated antiretroviral treatment with AIDS), incarceration status (1=currently incarcerated, 2=recently released [in the past 6 months], 3=previously incarcerated, 4=never incarcerated), and drug injection risk behaviour (1=people who do not inject drugs, 2=people who inject drugs who do not share syringes, 3=people who inject drugs who share syringes, 4=people who inject drugs and share syringes temporarily). As our analysis focused on HIV epidemics in people who inject drugs, we only considered injection drug use as transmission mode. Rather than focusing on a specific setting, we considered a wide range of scenarios by stratifying the rates of HIV transmission in people who inject drugs into communities with moderate HIV prevalence in people who inject drugs (ranging from 5% to 20%), and communities with high HIV prevalence in people who inject drugs (over 20%).93 Our model accounted for the elevated frequency of needle sharing in prison as well as discontinuation of antiretroviral treatment during a transitory period after prison release.31,94–97 We parameterise our model using epidemiological and clinical data from the scientific literature about HIV infectiousness, disease progression, demographic, injection drug behaviour data on the incarcerated population, proportion of people who inject drugs, syringe sharing in and out of prison, and incarceration history in people who inject drugs and people who do not share syringes (appendix p 33). To address empirical uncertainty regarding model parameters, we used a Bayesian inference approach to fit our model to epidemiological data of HIV prevalence in people who inject drugs in and out of prisons and HIV incidence in prison.

Given the scarcity of data on the impact of this post-release behaviour change on HIV transmission, we did a sensitivity analysis to evaluate the contribution of the frequency of post-release needle sharing and percentage discontinuation of antiretroviral treatment on HIV incidence in people who inject drugs in the community and in prison. We denoted people who inject drugs who share syringes while incarcerated as temporary sharers, a proportion of whom share for a transient duration after release, but not beyond. This post-release transient period of temporary syringe sharing and antiretroviral treatment discontinuation was assumed to vary between 1 and 6 months.31,95

Finally, we used the fitted model to evaluate the impact of demand reduction programmes, such as prison-based opioid agonist therapy followed by post-release retention, reduced rates of incarceration for non-violent drug users, and antiretroviral treatment retention in care post-release for curtailing HIV incidence in people who inject drugs. Consistent with empirical studies, we assumed that people who inject drugs who continue opioid agonist therapy after incarceration have a 20% (95% CI 10–30) reduced risk of re-incarceration while they are given treatment.98

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communities with moderate HIV prevalence, the reduction in HIV incidence is predicted to vary from 3·9% (0·9–13·4) for 20% coverage to 28·5% (9·4–57·5) for complete coverage (appendix p 42). Combining opioid agonist therapy with post-release antiretroviral treatment retention could achieve a further reduction of HIV incidence ranging from 0·3% to 1·8% in communities with high HIV prevalence and from 0·7% to 4·2% in communities with moderate HIV prevalence as coverage is expanded from 20% to 100% (appendix p 42).

Our estimates of the contribution of incarceration to HIV transmission and the potential effect of interventions depends on the general HIV prevalence in communities of people who inject drugs, which varies substantially between and within countries (figure 7, appendix p 42). Our results show that prison-based opioid agonist therapy followed with post-release retention could be an effective strategy for the reduction of HIV in people who inject drugs, at least in the short term (appendix p 42). Lowering the rate of incarceration of people who inject drugs might be effective in reducing HIV transmission in addition to opioid agonist therapy. The contribution of incarceration and effectiveness of intervention were higher in communities of lower HIV prevalence, where transmission because of incarceration is most substantial relative to that in the community, compared with communities with high HIV prevalence.

Summary of findingsThis Series paper provides clear evidence that the findings, replicated in many individual studies, that higher prevalence of HIV in individuals who are detained than in the population from which they arise, is almost universal. However, it also shows that the detailed epidemiology of HIV in people who are detained varies

A HIV infection diagram B Incarceration dynamics diagram C Subpopulation and incarceration impact diagram

Susceptible

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Prison-induced riskProportion of non-sharers temporarily sharing in prison and in a 1–6 month transient post-release period

Incarceration rate for non-PWIDElevated incarceration rate for PWIDTemporal transition between sharers and non-sharers due to incarceration

Figure 6: Deterministic compartmental model of drug injection transmission of HIV in the general community and incarcerated populationsART=antiretroviral therapy. PWID=people who inject drugs.

0

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Figure 7: Contribution of antiretroviral therapy discontinuation and temporary sharers to cumulative HIV incidence in people who inject drugs(A) Contribution of ART discontinuation. (B) Contribution of temporary sharers. Contribution accounts for transmission in prison and during the transitory period of elevated risk behaviour after release from prison. Contributions were evaluated relative to the scenario of no antiretroviral therapy discontinuation or no temporary sharers, and were assessed for a varying proportion of temporary sharers who share syringes after incarceration versus those who only share syringes while incarcerated, from epidemic onset to 2015. Bars show median (middle cross line) and range of contribution estimated for different HIV epidemics modelled (error bars show upper and lower 95% credible interval). Prevalence of HIV in people who inject drugs was varied from 5–20% (moderate prevalence communities) and 20–60% (high prevalence communities).

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considerably, reflecting the disease burden, the dominant mode of transmission in the population as a whole, and the role of incarceration. In most regions of the world, HIV prevalence is higher in detained women than detained men. However, although we have shown great variation in the pattern of HIV infection in prisons, the ability to draw general conclusions is limited by the scarcity of data, with data in some regions restricted to one or a few countries. The studies that do exist are often restricted to individual prisons (even subgroups of detainees in them) and are heterogeneous in reporting quality.

There are several reasons for the scarcity of data. First, many countries with the highest disease burden have very weak systems for health research and surveillance. Second, where health systems in prisons are organisationally separate from systems serving the general population, capacity that exists in prison systems might be deployed elsewhere. Consistent with the UN’s Mandela Rules, the WHO recommends that prisoner health care be consistent with community standards of care, and under the direction of the ministry of health.100 Third, secrecy and fear of exposing human rights abuses might cause governments to be unwilling to permit studies in their prisons, or if they are done, researchers are often prohibited from published results.101,102 Compulsory drug detention centres are a particular concern. In 2012, 12 UN agencies called for their immediate closure15 and since then, international funding for compulsory drug detention centres has stopped. However, they remain in operation in several regions, although largely hidden from those undertaking HIV surveillance.7

A particular problem is the scarcity of data on women detainees, even though they comprise about 10% of prison populations, they are more likely to have a substance abuse disorder, and are less likely to receive treatment than male prisoners.103

Most studies are cross-sectional, providing only snapshots of the situation at a particular moment in time. Cross-sectional studies, however, fail to capture the dynamic nature of the prison population, because the number of individuals passing through prisons each year can be up to three times higher than the estimated prison census. This discrepancy causes an especially important gap in our knowledge, given the role that the transition in and out of prison has in interruption of both antiretroviral treatment and opioid agonist therapy, with implications for both transmission and the emergence of drug-resistant HIV and tuberculosis infections.104

So what should be done to address the problem of HIV and related infections in prisons? One obvious response is to reduce the prison population, as our model showed. Measures that can reduce the population in detention include evidence-based treatment in and out of prison. Non-violent drug offenders and especially women15 should particularly be offered treatment, as an alternative, where appropriate.105 Our model further showed that

opioid agonist therapy given in prison can reduce HIV transmission within prison and reduce post-release HIV transmission.

Other infectious diseases might also be mitigated in prison settings. Interferon-free HCV therapies using direct-acting antiviral agents are rapidly becoming available and HCV treatment as prevention strategies, particularly in the prison setting, are now feasible.106 These treatments can produce 90–95% rates of HCV eradication.107

Routine screening and vaccination for HBV in prison settings108 is likely to produce considerable savings to the broader health system through prevention of cirrhosis of the liver and hepatocellular carcinoma,109 even though only around 5% of adults infected with HBV develop chronic infection110 because of the comparatively high prevalence in prison settings. Such programmes should be linked to a wider strategy to reduce HBV infection in countries where it is prevalent, through early childhood immunisation. A safe and efficacious vaccine for HBV has existed since 1986.111

A review of the evidence base for the management of tuberculosis and HIV and tuberculosis co-infection in prisons provides a useful framework including universal drug susceptibility testing, systematic screening of contacts in high-risk groups, access to high-quality treatment, and adequate coordination.112 Other specific measures include identification, isolation, and treatment of patients who are infected with tuberculosis as early as possible. In many countries, prisoners with symptoms suggestive of tuberculosis experience long delays in obtaining a diagnosis.113 Isolation of infectious prisoners is rare; many prisoners who are isolated might not receive treatment, and conditions are frequently appalling.114

Tuberculosis treatment completion rates in prisoners are often low, exacerbated by their movement within and in and out of the prison system. Prisoners in eastern Europe are unlikely to receive adequate treatment for HIV and tuberculosis.80 A study in Uganda found a default treatment prevalence of 12% in people staying in the same prison and 53% for those transferred to another prison, and 81% of prisoners who were on treatment and released were subsequently lost to follow-up.115

Pooled estimates of HIV prevalence and incidence, collected for the purpose of this review, were used to develop and calibrate a model for people who inject drugs for HIV transmission in and out of prison. Given that our focus was the evaluation of the contribution of incarceration to injection-related HIV transmission in people who inject drugs and the potential effect of interventions on the HIV epidemic in people who inject drugs, we did not address sexual, tattoo-related, or mother-to-child transmission of HIV. Inclusion of these transmission routes would further increase the predicted effect of the interventions considered by accounting for the substantial indirect benefits to people who do not

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inject drugs. Another limitation of our modelling analysis is the fact that the model was not developed for a specific setting; rather we investigated a range of plausible scenarios. This approach resulted in large uncertainty about model parameter values and model outcomes. Additionally, our model assumed constant antiretroviral treatment coverage during the course of the epidemic, which does not capture the effect of increased antiretroviral treatment coverage on HIV transmission. However, the effect of this assumption was mitigated by using a wide range of values for antiretroviral treatment coverage. Finally, our model was restricted to inmates who inject heroin, because most research and prevention has focused on these individuals.

ConclusionWe found a consistently higher prevalence of HIV, HCV, HBV, and tuberculosis in prisoners than in the general population across all regions and especially in imprisoned people who inject drugs.38,61,116 Interventions to prevent, identify, and treat these infections in prisons are poorly implemented, particularly in low-income and middle-income countries and in populations such as people who inject drugs, where care and treatment remain challenging in community settings. Investment in surveillance infrastructure is needed to improve country-level data on the prevalence of these infections and to inform policy and programmatic responses. This is particularly important in regions where injection drug use is increasing and the burden of HIV is already high. Mass incarceration of people who inject drugs is a key driver of the ever-growing population of prisoners. Decriminalising drug use and possession or providing alternatives to imprisonment for people who use drugs, and ensuring access to opioid agonist therapy, tuberculosis treatment, and antiretroviral treatment for prisoners will reduce the burden of these infections in the world’s prison population.ContributorsKD and CB developed the manuscript concept. ALW led the comprehensive search and data extraction and did the meta-analysis. KD developed the initial draft of the manuscript. BM wrote the sections on imprisonment data. BM and ALW calculated the number of inmates with each infection. JJA wrote the Compulsory Drug Detention Centres section. LM provided a revised structure for the manuscript, edited it, and addressed reviewers’ comments. MH analysed and wrote the section on incidence data. ALW, AG, MN-m, KD, and FLA conceived of the mathematical modelling analysis, MN-m conducted the mathematical modelling, and MN-m and AG wrote the modelling section. MM wrote the section on tuberculosis data and provided the final edit. SAK wrote the section on hepatitis B data. RC wrote the section on hepatitis C data. All authors had full access to the data, reviewed and edited the manuscript, and take responsibility for its integrity and the accuracy of the analysis.

Declaration of interestsWe declare no competing interests.

AcknowledgmentsThis paper was supported by grants to the Center for Public Health and Human Rights at Johns Hopkins Bloomberg School of Public Health from the National Institute on Drug Abuse; the Open Society Foundations; the United Nations Population Fund; Mac AIDS Fund;

the Bill & Melinda Gates Foundation; and the Johns Hopkins University Center for AIDS Research, a National Institute of Health (NIH)-funded programme 1P30AI094189. KD was supported by Australia’s National Drug and Alcohol Research Centre. RC is supported by a Cancer Institute New South Wales Early Career Research Fellowship (GNT14/ECF/1–46). SAK is supported by Australian National Health and Medical Research Council (NHMRC) Senior Research Fellowship (APP1078168). LM is supported by an NHMRC Senior Research Fellowship (APP1060443). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We thank Lori Rosman, Informationist at Johns Hopkins School Medicine, who assisted with the development of the systematic review; Teresa Ping Yeh and Natalie Flath, Johns Hopkins School of Public Health, who reviewed the identified articles and extracted data for the systematic review and meta-analysis; and Mary Kumvaj, Librarian, National Drug and Alcohol Research Centre, University of New South Wales who assisted with the grey literature search. We thank colleagues at the UN Office on Drugs and Crime, the European Monitoring Centre for Drugs and Drug Addiction, WHO, Glasgow Caledonian University, Health Protection Surveillance Centre (Ireland), Luxembourg Division de l’Inspection Sanitaire, National Advisory Committee on Drugs and Alcohol (Ireland), The National AIDS Centre (Poland), Public Health Agency of Catalonia, Trimbos Instituut, The University of Texas at Austin, Brandon Marshall, Brown University School of Public Health, Anna Bowring, Burnet Institute, and The UK Collaborating Centre for WHO Health in Prisons who contributed relevant reports and articles to the comprehensive review.

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Series


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Supplementary appendixThis appendix formed part of the original submission and has been peer reviewed. We post it as supplied by the authors.

Supplement to: Dolan K, Andrea L W, Moazen B, et al. Global burden of HIV, viral hepatitis, and tuberculosis in prisoners and detainees. Lancet 2016; published online July 14. http://dx.doi.org/10.1016/S0140-6736(16)30466-4.

1

Global burden of HIV, viral hepatitis and tuberculosis among prisoners and detainees

Authors: Kate Dolan, PhD; Andrea L Wirtz, PhD; Babak Moazen, MsCIH; Alison Galvani,

PhD; Martial Ndeffo-mbah, PhD; Stuart Kinner, PhD; Ryan Courtney, PhD; Martin Mckee, DSc;

Joseph J Amon, PhD; Lisa Maher, PhD; Margaret Hellard, PhD; Chris Beyrer, MD.; Fredrick

Altice, MD

Web Supplementary Appendix

Table of Contents

A1. Comprehensive search methods and meta-analysis ................................................................................................ 2

A2. Search strategy & terms .......................................................................................................................................... 4

A3. PRISMA search diagram ........................................................................................................................................ 7

A4. Prevalence data located for HIV, HCV, HBV TB and HIV/TB co infection among prison populations, published

between 2005-2015........................................................................................................................................................ 8

A5. National and regional HIV prevalence among prison populations, published between 2005-2015 ....................... 9

A6. National and regional estimates of anti-HCV prevalence among prison populations, published between 2005-

2015 ............................................................................................................................................................................. 15

A7. National and regional prevalence of HBV among prison populations, published between 2005-2015 ................ 20

A8. National and regional prevalence of active tuberculosis, published between 2005-2015 ..................................... 24

A9. HIV/TB Co-infection among prison populations, published 2005 - 2015 ............................................................ 27

A10. Infectious disease prevalence among imprisoned people who inject drugs, published 2005-2015 ................... 28

A11. HIV and viral hepatitis among inmates in Compulsory Drug Detention Centers (CDDCs) published between

2005 - 2015 .................................................................................................................................................................. 31

A12. Incidence of HIV and viral hepatitis among prisoners, published 2005 – 201592,97,162,279,280 .............................. 32

A13. Modeling the interplay between prison and community HIV transmission among PWIDs ............................... 33

A14. Partial rank correlation coefficients (PRCCs) of model parameters. .................................................................. 41

A15. Model Results: Effect of different incarceration-based interventions on HIV incidence after 5 years. .............. 42

Web Appendix References: ......................................................................................................................................... 43

2

A1. Comprehensive search methods and meta-analysis

Our search focused on identifying recent studies that utilized biologic measures to assess prevalence and/or

incidence of HIV, HCV, HBV, TB, and co-infections among people living in prisons and other closed facilities. The

search strategy was developed in collaboration with an informationist at Johns Hopkins University. Searches

followed controlled vocabulary and keywords, which were used in combination for the concepts of HIV, HCV,

HBV, TB, prisons, jail, and compulsory drug detention. Index specific terms are provided in Web Appendix 2

(below). We searched Pubmed, Embase, CINAHL, and Criminal Justice Abstracts with Full Text to identify peer

reviewed publications that published in any language from January 1, 2005 through July 15, 2015. Identified

publications were compiled in Refworks reference manager (version 2.0, ProQuest, Ann Arbor, MI) and duplicates

were removed. Additional reports published between 2005 and 2015 by the World Health Organization and the UN

Office on Drug and Crime were identified and also included in the literature review. Identified literature was then

independently reviewed by two research assistants, with faculty oversight and final determination, for eligibility

using a title and abstract review followed by a full text review of publications with data abstraction. Supplementary

Web Appendix 3 provides the PRISMA search flow diagram.

In the instance that no data was extracted from the systematic review search for countries on either HIV, HCV,

HBV, or TB in prisons and other closed settings, the authors called for papers and reports through potential grey

literature sources and via an email request sent to experts and researchers from the UN and/or working or affiliated

with prison systems. This invitation email requested further data on either HIV, HCV, HBV or TB from each

country. Emails were sent in October-November, 2015. In the first instance we searched the prisonstudies.org

website for email contact details of the Prison/Corrective Services Department for each country. If there was an

email contact listed, they were emailed an invitation letter. Additionally, when no Prison Department or Correct

Service contact was listed on the prisonstudies.org website we searched Google to ensure a Prison/Corrective

Services contact was ascertained and sent an email for each country, whenever possible. We also searched Google

for email contacts relevant to Health Department’s in each country and sent emails to not-for-profit/NGO agencies,

where relevant in each country. At a minimum one email was sent per country with an upper limit of five emails

sent. This call for data yielded only 17 countries that provided data and this was from the Barbados, Dominican

Republic, Estonia, Ethiopia, Ireland, Japan, Latvia, Lithuania, Luxembourg, Netherlands, the Philippines, Ukraine,

United Kingdom, Catalonia, Spain, Tanzania and Zanzibar,. In addition, we received an email alert from the

Correctional Services Department in Hong Kong and the French Monitoring Center for Drugs and Drug Addiction

in France indicating that our request was receiving attention but only electronic links or bibliography to national

surveillance were provided. Data from Catalonia were excluded due to language, from Dominican Republic due to

lack of HIV and other infectious disease data.

Peer reviewed publications and reports were included if the article met all of the following criteria: original /

primary research; study of any design that included individuals living in prisons, detention facilities, correctional

facilities, jails, compulsory drug detention/rehabilitation, and forced labor camps; included biologically confirmed

HIV, HCV, HBV, and/or TB infection; were published in a peer-reviewed journal or presented as an abstract at a

scientific conference after January 1, 2005. Data from all countries and settings that were published in were included

and there were no language restrictions used during the search. The following types of studies were excluded from

the review if they include any one of the following characteristics: case studies of one patient/participant; studied of

individuals in voluntary drug treatment/ rehabilitation/detox programs; studied individuals who were formerly

prisoners but have been outside of the prison setting for some period of time; included only self-reported HIV, HCV,

HBV, or TB diagnoses with no biologic test results; or were secondary publications (reviews, commentaries).

We extracted key data from articles that were published in English, Russian, Spanish, and French and were

independently determined to be eligible for inclusion following full text review. Abstracted data were specific to

publication data (year of publication, author); study data (geographical location and setting, year(s) of conduct,

study design, sampling or recruitment method, facility type, and diagnostic method(s); and total and gender-specific

prison population prevalence and incidence for each disease of interest (total sample size (N), gender, total cases of

infection or new infections (n), reported prevalence (%), reported incidence rate, % co-infection).

Data were analysed according to infection by total population and in disaggregated form by gender and key

population sub-group. Pooled estimates were calculated to produce country (included in maps) and regional level

estimates for each infection. Analyses were conducted in Stats Direct 3 using a meta-analysis with random effects

3

that incorporates inverse double arcsine square root to calculate the pooled prevalence estimates. Given the

expected heterogeneity between studies, all meta-analyses were performed using random effects models, which

account for interstudy variation. Heterogeneity was assessed using the I2 statistic, which describes the percentage of

variation between studies that is due to heterogeneity rather than chance. Scarcity of data precluded pooled

estimates for key population subgroup, however, data for PWID was substantial enough to summarize but not pool.

We present the summarized data for PWID by country and the available data nonetheless provide insights into the

increased burden of infectious disease among imprisoned PWID (Web Appendix 10).

4

A2. Search strategy & terms

Search terms for PUBMED:

#1 HIV

HIV [MeSH] OR "Acquired Immunodeficiency Syndrome Virus"[MeSH] OR "AIDS-Related Complex"[MeSH]

OR "AIDS-Related Opportunistic Infections"[MeSH] OR "HIV Infections"[MeSH] OR "HIV

Seropositivity"[MeSH] OR "AIDS-Related Complex"[MeSH] OR "HIV Seroprevalence"[MeSH] OR "HIV-

1"[MeSH] OR "HIV-2"[MeSH] OR “human immunodeficiency virus" [tw] OR “human immune deficiency virus"

OR HIV[tw] OR “HIV/AIDS”[tw] OR “HIV-infected”[tw] OR AIDS [tw]

#2 HCV

“Hepatitis C”[MesH] OR “Hepatitis C virus” [MeSH] OR “HCV”[tw] OR “Hepatitis C”[tw] OR “liver fibrosis”[tw]

OR “viral hepatitis” [tw]

#3 HBV

“Hepatitis B”[MesH] OR “Hepatitis B virus” [MeSH] OR “HBV”[tw] OR “Hepatitis B”[tw]

#4 TB

Tuberculosis [MeSH] OR “Mycobacterium tuberculosis”[MeSH] OR “Mycobacterium tuberculosis” [tw] OR

Tuberculosis [tw] OR “TB”[MeSH] OR “MDR-TB”[tw] OR “XDR-TB”[tw] OR “Mtb”[tw]

#5 Prison

Prisons [MeSH] OR Prisoners [MeSH] OR Criminals [MesH] OR Prison* [tw] OR "Concentration Camps" [MeSH]

OR Incarcerat* [tw] OR Penitentiar* [tw] OR imprison* [tw] OR penal institute* [tw] OR Jail* [tw] OR inmate*

[tw] OR "Correctional setting" [tw] OR "Correctional settings" [tw] OR detain*[tw] OR detention* [tw] OR

"Correctional Centre" [tw] OR "Correctional Centres" [tw] OR incarcerat* [tw] OR inmate* [tw]

#6 Compulsory Drug Detention Centers

“compulsory drug detention center” [tw] “compulsory drug detention” [tw] OR “compulsory drug treatment” OR

compulsory rehabil* OR “correction center” [tw] correction* facilit* [tw] OR “re-education through labor” [tw]

“laojiaosuo”[tw] OR “long-term detention” [tw] OR labor camp* [tw]

(#1 OR #2 OR #3 OR #4) AND (#5 OR #6)

Search terms for Embase

#1 HIV

'Human immunodeficiency virus'/exp OR 'acquired immune deficiency syndrome'/exp OR 'AIDS related

complex'/exp OR ‘AIDS-Related Opportunistic Infections’ OR 'Human immunodeficiency virus infection'/exp OR

‘HIV Seropositivity’ OR ‘AIDS-Related Complex’ OR ‘HIV Seroprevalence’ OR 'Human immunodeficiency virus

1'/exp OR 'Human immunodeficiency virus 2'/exp OR 'human immune deficiency virus' OR ‘HIV’ OR ‘HIV/AIDS’

OR ‘HIV-infected’ OR ‘AIDS’

#2 HCV

'hepatitis C'/exp OR 'Hepatitis C virus'/exp OR ‘HCV’ OR (Hepatitis NEXT/1 C) OR (liver NEXT/1 fibrosis) OR

(viral NEXT/1 hepatitis)

#3 HBV

'hepatitis B'/exp OR 'Hepatitis B virus'/exp OR ‘HBV’ OR (Hepatitis NEXT/1 B)

#4 TB

'tuberculosis'/exp OR 'Mycobacterium tuberculosis'/exp OR 'drug resistant tuberculosis'/exp OR 'extensively drug

resistant tuberculosis'/exp OR (Mycobacterium NEXT/1 tuberculosis) OR ‘Tuberculosis’ OR ‘TB’ OR ‘MDR-TB’

OR ‘XDR-TB’ OR ‘Mtb’

http://www.ncbi.nlm.nih.gov/mesh/68003209

5

#5 Prison

'prison'/exp OR 'prisoner'/exp OR 'offender'/exp OR Prison* OR (Concentration NEXT/1 Camp*) OR Incarcerate*

OR Penitentiar* OR imprison* OR (penal NEXT/1 institute*) OR Jail* OR inmate* OR (Correctional AND

setting*) OR detain* OR detention* OR (Correctional AND Centre*) OR inmate*


'detention camp'/exp OR ‘compulsory drug detention’ OR ‘compulsory drug detention’ OR ‘compulsory drug

treatment’ OR (compulsory NEXT/1 rehabil*) OR (correction* AND center*) OR (correction* NEXT/1 facilit*)

OR ‘re-education through labor’ OR ‘laojiaosuo’ OR (‘long-term’ NEXT/1 detention) OR (labor NEXT/1 camp*)

(#1 OR #2 OR #3 OR #4) AND (#5 OR #6)

Search terms for CINAHL

#1 HIV

MH “Human immunodeficiency virus” OR MH “HIV-1” OR MH “AIDS Serodiagnosis” OR MH “HIV Infections”

OR MH “HIV Seropositivity” OR MH “Acquired Immunodeficiency Syndrome” OR TX “acquired immune

deficiency syndrome” OR TX “AIDS related complex” OR TX “AIDS-Related Opportunistic Infections” OR TX

“Human immunodeficiency virus infection” OR TX “HIV Seropositivity” OR TX “AIDS-Related Complex” OR

TX “HIV Seroprevalence” OR TX “Human immunodeficiency virus 1” OR TX “Human immunodeficiency virus 2”

OR TX “human immune deficiency virus” OR TX “HIV” OR TX “HIV/AIDS” OR TX “HIV-infected” OR TX

“AIDS”

#2 HCV

MH “hepatitis C” OR TX “Hepatitis C virus” OR TX “HCV” OR TX “Hepatitis C” OR TX “liver fibrosis” OR TX

“viral hepatitis”

#3 HBV

MH “hepatitis B” OR TX “Hepatitis B virus” OR TX “HBV” OR TX “Hepatitis B”

#4 TB

MH “tuberculosis” OR MH “Mycobacterium tuberculosis” OR MH “Tuberculosis, Multidrug-Resistant” OR TX

“drug resistant tuberculosis” OR TX “extensively drug resistant tuberculosis” OR TX “Mycobacterium

tuberculosis” OR TX “Tuberculosis” OR TX “TB” OR TX “MDR-TB” OR TX “XDR-TB” OR TX “Mtb”

#5 Prison

MH “Correctional Facilities” OR MH “prisoners” OR TX “Prison*” OR TX “Incarcerate*” OR TX “Penitentiary”

OR TX “Penitentiaries” OR TX “imprisonment” OR TX “penal institute*” OR TX “Jail” OR “Jails” OR TX

“inmate” OR TX “inmates” OR TX “correctional setting” OR “Correctional settings” OR TX “detain” OR TX

“detention” OR TX “detainees” OR TX Correctional Centre” OR TX “Correctional Centres”


TX “compulsory drug detention center” OR TX “compulsory drug detention” OR TX “compulsory drug treatment”

OR TX “compulsory rehabilitation” OR TX “correctional facility” OR TX “corrections facility” OR TX

“correctional facilities” OR TX “corrections facilities” OR TX “re-education through labor” OR TX “laojiaosuo”

OR TX “long-term detention” OR TX “labor camp” OR TX “labor camps”

(S1 OR S2 OR S3 OR S4) AND (S5 OR S6)

Criminal Justice Abstracts with Full Text

#1 HIV

MH “Human immunodeficiency virus” OR MH “HIV-1” OR MH “AIDS Serodiagnosis” OR MH “HIV Infections”

OR MH “HIV Seropositivity” OR MH “Acquired Immunodeficiency Syndrome” OR TX “acquired immune

deficiency syndrome” OR TX “AIDS related complex” OR TX “AIDS-Related Opportunistic Infections” OR TX

6

“Human immunodeficiency virus infection” OR TX “HIV Seropositivity” OR TX “AIDS-Related Complex” OR

TX “HIV Seroprevalence” OR TX “Human immunodeficiency virus 1” OR TX “Human immunodeficiency virus 2”

OR TX “human immune deficiency virus” OR TX “HIV” OR TX “HIV/AIDS” OR TX “HIV-infected” OR TX

“AIDS”

#2 HCV

MH “hepatitis C” OR TX “Hepatitis C virus” OR TX “HCV” OR TX “Hepatitis C” OR TX “liver fibrosis” OR TX

“viral hepatitis”

#3 HBV

MH “hepatitis B” OR TX “Hepatitis B virus” OR TX “HBV” OR TX “Hepatitis B”

#4 TB

MH “tuberculosis” OR MH “Mycobacterium tuberculosis” OR MH “Tuberculosis, Multidrug-Resistant” OR TX

“drug resistant tuberculosis” OR TX “extensively drug resistant tuberculosis” OR TX “Mycobacterium

tuberculosis” OR TX “Tuberculosis” OR TX “TB” OR TX “MDR-TB” OR TX “XDR-TB” OR TX “Mtb”

#5 Prison

MH “Correctional Facilities” OR MH “prisoners” OR TX “Prison*” OR TX “Incarcerate*” OR TX “Penitentiary”

OR TX “Penitentiaries” OR TX “imprisonment” OR TX “penal institute*” OR TX “Jail” OR “Jails” OR TX

“inmate” OR TX “inmates” OR TX “correctional setting” OR “Correctional settings” OR TX “detain” OR TX

“detention” OR TX “detainees” OR TX Correctional Centre” OR TX “Correctional Centres”


TX “compulsory drug detention center” OR TX “compulsory drug detention” OR TX “compulsory drug treatment”

OR TX “compulsory rehabilitation” OR TX “correctional facility” OR TX “corrections facility” OR TX

“correctional facilities” OR TX “corrections facilities” OR TX “re-education through labor” OR TX “laojiaosuo”

OR TX “long-term detention” OR TX “labor camp” OR TX “labor camps”

7

A3. PRISMA search diagram

Records identified through database searching

(n =11,482)

PubMed= 2324; Embase= 3,784

CINAHL=1,037; Criminal Justice=4,337

Records after duplicates removed

(n =6,943)

Title and abstracts

screened (n =6,943)

Records excluded

(n =6,046)

Full-text articles assessed

for eligibility (n=897)

Full-text articles excluded,

(n=673)

Reasons for exclusion:

no biological data;

infection only self-reported;

does not report methodology;

sample is biased/non-representative sub-group

duplicate of another publication

Studies included in

quantitative synthesis

(meta-analysis)

(n=299)

Grey literature and email

requested reports (n =75)

8

A4. Prevalence data located for HIV, HCV, HBV TB and HIV/TB co infection among prison populations,

published between 2005-2015

Infection

Total

countries or

territories

with data

Number of data points

Total

prevalence Males Females PWIDs FSW MSM TG

HIV 74 204 70 59 47 6 14 1

HCV

(antiHCV) 46 171 65 49 53 0 7 0

HBV

(HBsAg) 43 56 40 28 24 1 5 0

Active TB 25 46 19 5 0 0 0 0

HIV/TB 17 25 4 1 1 0 0 0

9

A5. National and regional HIV prevalence among prison populations, published between 2005-2015

Region / Country Imprisonment rate

(per 100,000)1

Year

collected

Total HIV

%

Male HIV

%

Female HIV

%

East and Southern Africa

Ethiopia2 129 2013 4.2 4.3 3.8

Kenya3,4

118 2008 5.6 5.6

2009 – 10 5.7

Malawi5,6

73 2011 21.7 23.0 10.0

2011 18.5 19.0 0.0

2011 41.2 41.0 42.0

NR 36.6 29.9 50.0

South Africa7-9

292 2009 25.3

2009 25.5 25.5

2011 7.2

2014 14.0

Swaziland10

289 NR 34.9

Uganda11,12

115 2008 11.0 11.0 13.0

2014 10.9

United Republic of

Tanzania13,14

69 2011 15.0

2012 6.7 5.2 14.7

Zambia15-19

125 2009 27.4 26 43.3

2010 27.4

2011 25

2011 24.1

2011 22.9

Zanzibar20

NR 2.8

Pooled East and Southern Africa

15.6% 19.1% 21.6%

(95%CI)

(11.8-19.8%) (11.7-27.8) (7.3-41.1)

I2

99.5% 97.9% 94.6%

Total Prison Population: 588,000 Total prisoners living with HIV: 92,000 (69,500 – 116,500)

Africa - West and Central

Burkina Faso21

34 2009 5 4.9 6.7

Cameroon22,23

115 2003 11.3

2009 7.8

Côte d'Ivoire24

52 2008 - 10 5.6 5.1 17.1

Democratic Republic of the

Congo25

32 2008 10.2

Ghana26-28

53 2004 5.9 5.0 15.1

2004 19.2

2012 2.3 1.5 11.8

Nigeria29-32

31 2006 8.9 8.9

2007 18.0 18.0

NR 2.4 2.2 6.3

NR 6.7

Togo33,34

64 2011 10.8 10.8

2011 4.3 4.0 14.3

10


(per 100,000)1

Year

collected

Total HIV

%

Male HIV

%

Female HIV

%

Pooled West and Central

Africa

8.2% 7.1% 13.1%

(95%CI)

(6.2-10.5) (3.9-10.9) (8.4-18.5)

I2

92.4% 91.5% 10.%


Middle East and North Africa Egypt

35 76 NR 0.0

Islamic Republic of Iran36-40

287 1991 2.8

2008 0.6

0.0

2009 0.0

2009 0.9

Israel41

256 2003 0.2

Lebanon42

120 2007 0.17 0.17

Libya43

99 2006 18.4 18.4

Morocco44

222 2004 2.0

2.0

Pooled Middle East and North Africa

1.3% 6.0% 0.8%

(95%CI)

(0.2-3.3) (1.9-34.9) (0.1-3.7)

I2

99.9% 99.7% 75.6%


Asia and Pacific

Afghanistan45

74 2012 0.5 0.5

2012 0.8 0.8

Australia46-53

151 2003 0.0

2004 1.0 0.7 0.0

2005 0.6

2006 0.0

2008 0.1

2010 0.0

2010 0.0 0.0 0.0

2013 0.0 0.0 0.0

Fiji54

174 2012 1.0

India55

33 NR 0.5

Indonesia56-58

64 2007 29.8

2007 7.2

2009 4.8

2010 2.6 1.1 6.0

Pakistan59-64

43 2006 1.0

2007 0.2

2007 2.0 2.0

2009 0.8 0.8 1.0

2009 2.0 2.1 1.2

2009 2.4 2.4 NR

Philippines65

121 2014 12.8 16.0 3.0

11


(per 100,000)1

Year

collected

Total HIV

%

Male HIV

%

Female HIV

%

Pooled Asia and Pacific

1.4% 1.4% 1.9%

(95%CI)

(0.9 - 1.9) (0.8-2.3) (0.6-4.2)

I2

94.9% 94.2% 82.6%

Total Prison Population: 3,361,500 Total prisoners living with HIV: 47,000 (30,500– 64,000)

Eastern Europe and Central Asia Armenia

66 130 NR 2.4 2.4

Azerbaijan67

236 2014 3.7 4.0 1.7

Bosnia and Herzegovina68

73 2011 0.0

Bulgaria69-71

125 2009 0.6

2010 0.8

Estonia72

216 2012 15.8 14.5 38.2

Hungary73

187 2007 0.0

Kazakhstan74

231 2007 2.0

Latvia75

239 2010 6.1

Russian Federation76

445 2014 3.0

Serbia 148 2011

3.0 4.0

The Former Yugoslav

Republic of Macedonia77

147 2011 0.0

Ukraine78-80

194 2005 24.5

2011 19.4 17.3 28.4

2011 14.0 10.0 33.0

Pooled Eastern Europe

Central Asia

4.1 8.5% 22.1%

(95%CI)

(1.4-8.0) (2.7-17.1) (8.2-40.4)

I2

99.% 98.% 93.4%

Total Prison Population: 1,287,000 Total prisoners living with HIV: 53,500 (18,000 – 103,000)

Western Europe

Finland81

57 2006 0.8 0.7 1.1

France82,83

100 2000 0.0 0.0

2010 2.0 2.0 2.6

Ireland84,85

45 2011 1.9 1.5 8.9

Northern Ireland86

87 2004 0.0

Italy 86 2001 7.5

2001 7.5 7.8 5.6

NR 3.8

Luxembourg87

112 2014 2.2

Portugal88,89

138 2005 9.9

9.9

2007 6.6 6.6

Spain90-97

136 1992 1.9 1.9

2001 19.1 19.4 16.7

2002 7.2

2008 10.8

2009 8.5

2010 11.2

2010 1.2

2014 5.8

12


(per 100,000)1

Year

collected

Total HIV

%

Male HIV

%

Female HIV

%

United Kingdom98

148 2014 0.6

Pooled Western Europe

4.2% 3.6% 5.6

(95%CI)

(2.7-6.1) (1.1-7.4) (2.2-10.4)

I2

98.5% 97.9% 90.3%


North America

Canada99,100

106 2003 2.0 2.1 1.8

2003 3.4 2.4 8.8

United States of America101-

119 698 1994 7.5

1998 4.0

4

1999 1.8

1.8

2000 0.2

2000 1.1

1.1

2000

3.0 10.7

2003 16.8

16.8

2003

1.6

2003 1.7 2.7 1.0

2003 1.3 1.3 1.4

2003 1.9

2003 1.7

2003 0.7

2003 0.3

2004 3.4 3.6 2.6

2006 0.8

2006 0.1 0.1

2006 0.11 0.11

2006 5.2 4.7 9.8

2007 2.6

2007 0.9 0.8 1.4

2008 0.8

2008 0.3

2008 0.3

2008 0.5

2008 1.5

2009 0.8

2010 1.46 1.4 1.9

2010 0.47 0.47 0.5

2011 0.6

2011 0.4

2011 1.3

2011 1.3

Pooled North America

1.3% 3.1% 3.8%

(95%CI)

(1.0-1.7) (2.2-4.1) (2.4-5.5)

I2

99.5% 99.5% 98.8%


Caribbean

13


(per 100,000)1

Year

collected

Total HIV

%

Male HIV

%

Female HIV

%

Antigua and Barbuda120

373 2004 3.0

Belize121

449 2005 4.0 4.0

Dominica120

300 2004 2.6

Grenada120

398 2004 2.2

Jamaica122

145 2006 3.3

Saint Kitts and Nevis120

607 2004 2.4

Saint Lucia120

349 2004 2.0

Saint Vincent and the

Grenadines120

387 2004 4.1

Pooled Caribbean

3.3% 4.%

(95%CI)

(2.7 - 4.0) (not pooled) No data

I2

0.1%


Latin America

Argentina123

160 2011 3.3 3.0 4.0

Bolivia124

122 2001 0.1 0.13 0.0

Brazil125-130

301 2001 4.9

2003 5.7

2004 0.3 0.3

2007 1.8

2009 6.6

2013 5.7

Colombia131

244 2010 2.1

Mexico132-134

212 2001 0.6

2010 0.7 0.7 0.7

2010 0.7

Venezuela135

174 1998 4.0

Pooled Latin America

2.3% 1.6% 1.5%

(95%CI)

(1.5-3.4%) (0.6-3.1) (0.3-3.5)

I2

98.0% 98.1% 90.2%


GLOBAL

Total prison population: 10,242,000

Global HIV prevalence among prisoners: 3.8% (3.2 – 4.5)

Total prisoners living with HIV: 389,000 (328,000 – 461,000)

Note: Published data include national level and Sub-national reports; NR: Date not reported; N/A:

Imprisonment rate not available; Estimated numbers of prisoners living with HIV are rounded to the nearest 500

Countries that did not have data meeting inclusion criteria (imprisonment rate/100,000): Albania 189;

Algeria 162; Andorra 72; Angola 106; Austria 95; Bahamas 363; Bahrain 301; Bangladesh 43; Barbados 322;

Belarus 306; Belgium 105; Benin 77; Bhutan 145; Botswana 188; Brunei Darussalam 132; Burundi 93;

Cambodia 105; Cape Verde 286; Central African Republic 16; Chad 39; Chile 246; China 119; Comoros 31;

Congo 27; Costa Rica 352; Croatia 81; Cuba 510; Cyprus 94; Czech Republic 195; Democratic People's

Republic of Korea N/A; Denmark 61; Djibouti 68; Dominican Republic 231; Ecuador 162; El Salvador 498;

Equatorial Guinea 129; Eritrea N/A; Federated States of Micronesia 127; Gabon 210; Gambia 58; Georgia 274;

Germany 76; Greece 109; Guatemala 121; Guinea 26; Guinea-Bissau 5; Guyana 259; Haiti 97; Honduras 196;

Iceland 47; Iraq 123; Japan 48; Jordan 150; Kiribati 136; Kuwait 92; Kyrgyzstan 166; Lao People's Democratic

Republic 71; Lesotho 92; Liberia 39; Lithuania 268; Madagascar 83; Malaysia 171; Maldives 341; Mali 33;

Marshall Islands 66; Mauritania 44; Mauritius 159; Mongolia 266; Montenegro 174; Mozambique 61; Myanmar

14


(per 100,000)1

Year

collected

Total HIV

%

Male HIV

%

Female HIV

%

113; Namibia 144; Nauru 140; Nepal 59; Netherlands 69; New Zealand 194; Nicaragua 171; Niger 39; Norway

71; Oman 36; Palau 343; Panama 392; Papua New Guinea 43; Paraguay 158; Peru 242; Poland 191; Qatar 53;

Republic of Korea 101; Republic of Moldova 215; Romania 143; Rwanda 434; Sao Tome and Principe 101;

Saudi Arabia 161; Senegal 57; Seychelles 799; Sierra Leone 55; Singapore 227; Slovakia 184; Slovenia 73;

Solomon Islands 56; Somalia N/A; South Sudan c.65; Sri Lanka 92; Sudan 50; Suriname 183; Sweden 55;

Switzerland 84; Syrian Arab Republic 60; Tajikistan 121; Thailand 465; Timor-Leste 50; Tonga 166; Trinidad

and Tobago 258; Tunisia 212; Turkey 222; Turkmenistan 583; Tuvalu 110; United Arab Emirates 229;

Uruguay 291; Uzbekistan 150; Vanuatu 87; Viet Nam 154; Yemen 53; Zimbabwe 145

15

A6. National and regional estimates of anti-HCV prevalence among prison populations, published between

2005-2015

Region / Country

Imprisonment

rate

(per 100,000)1

Year

collected

Total anti-HCV

%

Male anti-HCV

%

Female

anti- HCV

%

East and Southern Africa Malawi

6 73 NR 0.0

Zanzibar20

NR 4.7


1.8%

(95%CI)

(0.2 - 9.5)

I

2 93.6%

Total Prison Population: 588,000 Total anti-HCV+ prisoners: 10,500 (1,000 – 56,000)

West and Central Africa Ghana

26,27 53 2004 -2005 19.2 19.2 13.4

2004-2005 18.7

Nigeria29

31 2007 12.3 12.3

Pooled West and Central Africa 16.9% 15.9%

Not pooled

(95%CI)

(13.1-21.1) (9.9-23.1)

I2 74.60% 88.0%



35 76 NR 15.8 12.8 10.1

Islamic Republic of

Iran38,40,136-138

287 NR 15.8

2003 45.4 45.4

2009 7.4

7.4

2008-2009 4.4 4.1 7.7

2009-2010 11.7

2009-2010 7.7 8.0 6.3

Lebanon42,139

120 2007-2008 3.43 3.43

NR 3.4

Libya43

99 2006 22.9 22.9

Pooled Middle East and North Africa 11.9% 14.0% 8.0%

(95%CI)

(5.8-19.8) (5.9-24.9) (5.6-10.7)

I2 98.8% 98.8% 0.0%


Asia and Pacific

Afghanistan45

74 2012 4.6 4.6

2012 1.4 1.4

Australia46-53,140-143

151 1996 38.7

2001 0.0

2003 9.0

2004 34.0 33.0 53.0

2004-2005 41.8 39.6 59.3

2005 41.3 39.8 66.1

16

Region / Country

Imprisonment

rate

(per 100,000)1

Year

collected

Total anti-HCV

%

Male anti-HCV

%

Female

anti- HCV

%

2006 8.7

2005-2007 24.8

2008 32.0

2008-2009 31.7 28.0 45.4

2010 22.0 21.0 34.0

2010 29.8

2013 31.0 28.2 39.8

Indonesia56,57

64 2007-2009 18.6%

2007-2009 26.3%

2009 34.1%

Japan144

48 2014 0.2% 0.2% 0.2%

Pakistan59,61,63,145-147

43 2007-2008 15.2% 15.2%

2007-2008 8.7% 8.7%

2007-2012 12.32%

2008-2009 12.8%

2009-2010 13.2% 13.1% 16.0%

NR 18.4% 18.4%

Philippines65

121 2014 43.6% 56.0% 10.0%

Sri Lanka148

92 NR 6.9% 7.4%

Taiwan149

2004-2005 22.5% 22.5%

Pooled Asia and Pacific 20.6% 17.3% 29.3%

(95%CI)

(15.4-26.4) (10.1-25.9) (12.1-50.3)

I2 99.6% 99.7% 98.9%

Total Prison Population: 3,344,500 Total anti-HCV+ prisoners: 689,000 (515,500 – 883,000)

Eastern Europe and Central Asia Armenia

66 130 NR 23.8 23.8

Azerbaijan67

236 2014 38.2 41.8 10.3

Bosnia and

Herzegovina68

73 2011 14.3

Bulgaria69-71

125 2009 25.6 32.6 20.2

2010 20.4* 24.2* 14.1

NR 28.6

Croatia150

81 2005-2007 12.5 14.4 10.6

Hungary73

187 2007-2009 4.9

Kazakhstan74

231 2007 43.0

Tajikistan74

121 2007 24.3

The Former

Yugoslav Republic

of Macedonia77

147 2011 20.0

Turkey151

222 NR 0.4

Ukraine78

194 2011 60.0

17

Region / Country

Imprisonment

rate

(per 100,000)1

Year

collected

Total anti-HCV

%

Male anti-HCV

%

Female

anti- HCV

%

Pooled Eastern Europe Central Asia 20.2% 26.8% 14.1%

(95%CI)

(11.8-30.1) (16.3-38.9) (9.8-19.2)

I2 99.3% 98.1% 47.6%


Western Europe

Finland81

57 2006 45.8 43.9 52.3

France82,83,152-155

100 2003 6.9 4.8

2010 4.8 4.5 11.8

2010 5.3

2012-2013 4.7

2012-2013 6.5

Germany156

76 2002 8.6* 8.6

Ireland85

80 2011 12.9 12.3 22.2

North Ireland86

87 2004 1.1

Italy157-160

86 2000-2002 37.4 37.4

2001-2002 38.0 40.6 20.6

2006 22.4

NR 22.8

Luxembourg87

112 2014 13.4

Netherlands161

69 2010 7.4

Portugal88,89

138 2005 11.0

11.0

2008 34.4 34.4

Scotland162

143 2010-2011 19.0

Spain90,94,95,163

136 2001 38.2 38.9 31.9

2002-2004 8.2

2008 22.7

2009 26.1

2014 20.0

United Kingdom:

England & Wales164-

168

148 2006 50.0

50.0

2006-2007 12.2

12.2

2005-2008 24.2

2010-2011 11.1 11.1

NR 1.3* 1.3*

2014 8.0

Pooled Western Europe 15.5% 18.8% 24.10%

(95%CI)

(12.2-19.1) (9.6-30.2) (15.7-33.6)

I2 99.5% 99.1% 24.10%


North America

Canada100,169

106 2003 18.5 16.6 29.2

2003-2004 17.6 15.9 30.2

2004 25.2 24.8 37.6

18

Region / Country

Imprisonment

rate

(per 100,000)1

Year

collected

Total anti-HCV

%

Male anti-HCV

%

Female

anti- HCV

%

United States of

America108,114,115,170-

186

698 1994-1996 0.8* 0.3 3.7

1996-1997 40.0

40

1998-2000 24.9 23.1 40.5

1999-2000 13.0 12.0

2000-2001 2* 1.8* 2.5*

2001 23.6

2003 15.2

2004 13.7

2005 11.1

2005 23.3

2004-2006 4.3 3.2 7.6

2004-2006 8.1 7.5 9.4

2006 29.7

2006 18.9

2006 11.2 11.2

2007 12.1 11.2 15.7

2006-2008 1.0

2006-2008 22.9

2008 13.0

2008 20.9

2007-2009 16.7

2010 5.53 5.47

2010 41.1

2011 9.6

2009-2011 20.5 19.4 28.2

2010-2011 24 18

2010-2012 16.6 14.8 33.2

2012 11.9 11.8

2012 13.9

2012 18.1 16.8 31.3

2011-12 9.8

2011-12 5.6

2011-2012 3.0 3.1 2.7

2012-2013 16.4

NR 34.3 32.7 38.3


15.3% 10.6% 17.9%

(95%CI)

(13.1-17.7) (8.2-13.3) (10.0-27.4)

I2 99.9% 99.8% 99.7%


Caribbean No data identified or met inclusion criteria for the Caribbean

Latin America

19

Region / Country

Imprisonment

rate

(per 100,000)1

Year

collected

Total anti-HCV

%

Male anti-HCV

%

Female

anti- HCV

%

Argentina123

160 2010 0.8

Brazil127,128,130,187-191

301 2001 8.1

2003 8.7 8.7

2004-2005 6.4* 6.59* 4.17*

2007 5.3

2007-2008 6.1

6.1

2009 4.8 7.0 0.8

2009-2010 3.1

2010 1.0

Mexico132,134

212 2001-2002 10.0

2010 3.2

Venezuela192

174 NR 5.0 5.0

Pooled Latin America 4.7% 7.1% 3.6%

(95%CI)

(3.1-6.7) (5.8-8.6) (0.5-9.4)

I2 97.2% 0.0% 78.8%

Total Prison Population: 1,401,000 Total anti-HCV+ prisoners:: 66,000 (43,500 – 94,000)

GLOBAL


Global prevalence of anti-HCV: 15.1 (13.7-16.5)

Total anti-HCV+ prisoners: 1,546,500 (1,403,500 – 1,690,000)

Note: Published data include national level and Sub-national reports; NR: Date not reported; N/A:

Imprisonment rate not available; *juvenile; Estimated numbers of prisoners living with HCV are rounded to

the nearest 500

Countries with no anti-HCV data meeting inclusion criteria (Imprisonment rate): Albania 189; Algeria 162;

Andorra 72; Angola 106; Antigua and Barbuda 373; Austria 95; Bahamas 363; Bahrain 301; Bangladesh 43;

Barbados 322; Belarus 306; Belgium 105; Belize 449; Benin 77; Bhutan 145; Bolivia 122; Botswana 188;

Brunei Darussalam 132; Burkina Faso 34; Burundi 93; Cambodia 105; Cameroon 115; Cape Verde 286;

Central African Republic 16; Chad 39; Chile 246; China 119; Colombia 244; Comoros 31; Congo 27; Costa

Rica 352; Côte d'Ivoire 52; Cuba 510; Cyprus 94; Czech Republic 195; Democratic People's Republic of

Korea N/A; Democratic Republic of the Congo 32; Denmark 61; Djibouti 68; Dominica 300; Dominican

Republic 231; Ecuador 162; El Salvador 498; Equatorial Guinea 129; Eritrea N/A; Estonia 216; Ethiopia

129; Federated States of Micronesia 127; Fiji 174; Gabon 210; Gambia 58; Georgia 274; Greece 109;

Grenada 398; Guatemala 121; Guinea 26; Guinea-Bissau 5; Guyana 259; Haiti 97; Honduras 196; Iceland

45; India 33; Iraq 123; Israel 256; Jamaica 145; Jordan 150; Kenya 118; Kiribati 136; Kuwait 92;

Kyrgyzstan 166; Lao People's Democratic Republic 71; Latvia 239; Lesotho 92; Liberia 39; Lithuania 268;

Madagascar 83; Malaysia 171; Maldives 341; Mali 33; Marshall Islands 66; Mauritania 44; Mauritius 159;

Mongolia 266; Montenegro 174; Morocco 222; Mozambique 61; Myanmar 113; Namibia 144; Nauru 140;

Nepal 59; New Zealand 194; Nicaragua 171; Niger 39; Norway 71; Oman 36; Palau 343;Panama 392; Papua

New Guinea 61; Paraguay 158; Peru 242; Poland 191; Qatar 53; Republic of Korea 101; Republic of

Moldova 215; Romania 143; Russian Federation 445; Rwanda 434; Saint Kitts and Nevis 607; Saint Lucia

349; Saint Vincent and the Grenadines 387; Sao Tome and Principe 101; Saudi Arabia 161; Senegal 62;

Serbia 148; Seychelles 799; Sierra Leone 55; Singapore 227; Slovakia 184; Slovenia 73; Solomon Islands

56; Somalia N/A; South Africa 292; South Sudan c.65; Sudan 50; Suriname 183; Swaziland 289; Sweden

55; Switzerland 84; Syrian Arab Republic 60; Thailand 465; Timor-Leste 50; Togo 64; Tonga 166; Trinidad

and Tobago 258; Tunisia 212; Turkmenistan 583; Tuvalu 110; Uganda 115; United Arab Emirates 229;

United Republic of Tanzania 69; Uruguay 291; Uzbekistan 150; Vanuatu 87; Viet Nam 154; Yemen 53;

Zambia 125; Zimbabwe 145.

20

A7. National and regional prevalence of HBV among prison populations, published between 2005-2015

Region / Country

Imprisonment

rate

(per 100,000)1

Year

collected

anti-HBc

%

HBsAg

%

HBV (diagnostic

method unspecified)

%


Malawi6 73 NR

3.5%

Zanzibar20

NR

7.10%


5.7%

(95%CI)

(2.9-9.4)

I

2

54.9%

Total Prison Population: 588,000 Total HBsAg+ prisoners: 33,500 (17,000 – 55,000)

West and Central Africa

Burkina Faso21

34 2009

27.3

Ghana26,27

53 2004-2005

17.4

2004-2005

22.5

Nigeria29

31 2007

23.0

Pooled West and Central Africa

23.5%

(95%CI)

(19.8-27.5)

I

2

72.2%



35 76 NR 9.8

Islamic Republic of

Iran36,38,40,193-197

287

2001-2002 4.5

2003 3.0

2008-2009 0.6

2008-2009 4.1

2009 7.4 1.2

2009-2010

2.1

2009-2010

6.9

NR

6.1

Lebanon42,139

120 2007-2008

2.4

2009

1.7

Libya43

99 2006 6.9


7.9% 3.3%

(95%CI)

(6.0-10.1) (2.4-4.5)

I

2

63.2% 82.1%


Asia and Pacific

Afghanistan45

74 2012

0.06

2012

0.05

Australia46-53,57,141,143,198

151 2001 27.8

2003 11.0

21

Region / Country

Imprisonment

rate

(per 100,000)1

Year

collected

anti-HBc

%

HBsAg

%

HBV (diagnostic

method unspecified)

%

2004 20.0

2006

3.9

2005-2007

4.5

2008

26.0

2008-2009 25.5

2009

3.2

2010 19.0 2.1

2010 17.7 3.0

2010

1.6

2013 18

Indonesia56

64 2007-2009

5.3

2007-2009

1.8

2009

3.2

Japan144

48 2014

0.0

Pakistan59,63,147

43 2007-2008

5.9

2007-2008

3.5

2012

5.3

Philippines65

121 2014

6.8

Sri Lanka148

92 NR

0.25

Taiwan199

1994

21.7

Pooled Asia and Pacific

19.9% 4.4%

(95%CI)

(16.5-23.7) (1.4-9.0)

I

2

86.4% 99.1%

Total Prison Population: 3,361,500 Total HBsAg+ prisoners: 148,000 (47,000 – 302,500)

Eastern Europe and Central

Asia

Armenia66

130 NR 3.7

Azerbaijan67

236 2014

2.7

Bosnia and Herzegovina68

73 2011

1.5

Bulgaria69-71

125 2009 59.2 32.4

2010 49.9 25.3

NR 60.2

Croatia150

81 2005-2007 5.9

Hungary73

187 2007-2009

1.5

The Former Yugoslav

Republic of Macedonia77

147

2011 17.0

Turkey151

222 NR 4.8

Pooled Eastern Europe Central Asia

35.1% 10.4%

(95%CI)

(11.0-64.4) (1.9-24.6)

I

2

99.5% 99.3%


22

Region / Country

Imprisonment

rate

(per 100,000)1

Year

collected

anti-HBc

%

HBsAg

%

HBV (diagnostic

method unspecified)

%

Western Europe

Finland81

57 2006 0.5

France83,152,155

100 2000-2003

0.3

2012-2013

7.5

2012-2013

1.2

Ireland85

80 2011 0.3

N. Ireland86

87 2004 0.8

Italy157,160

86 2001-2002 52.6

NR

4.4

Luxembourg87

112 2014 2.2

Netherlands161

69 2010 8.5 1.3

Portugal89

138 2008 19.1

Spain90,92,163

136 2008

2.6

2009

2.1

2012

2.6

Switzerland200

84 NR 44.0

United Kingdom: England &

Wales98,165,166,201

148 2005-2008 13.9 2.4

2006-2007 11.4 2.6

2011

0.4

2014 1.5

Pooled Western Europe

14.8% 2.4% 1.4%

(95%CI)

(4.6-29.5%) (1.6-3.3) (1.1-1.8)

I2

99.5% 87.4% 0.5%


North America

United States of

America115,140,171,173,177,202

698 1994-1996

2.2

1996-1997 29.0

1999-2000 19.0

2000-2001 20.5

2003-2006 0.8

2007-2009

0.9

2011-12

2.7

2011-12

1.7


22.0% 1.4%

(95%CI)

(18.2-26.0) (0.3-3.1)

I

2

88.3% 95.0%



Latin America

Argentina123

160 2010

0.6

23

Region / Country

Imprisonment

rate

(per 100,000)1

Year

collected

anti-HBc

%

HBsAg

%

HBV (diagnostic

method unspecified)

%

Brazil127,128,203,204

301 2004-2005 11.1

2007

21.0

2007-2008 18.9

NR 17.9 0.5

Mexico132-134

212 2001-2002 4.4

2010 4.8

2010 3.0

Venezuela135

174 1998-2001 16.2

Pooled Latin America

11.1% 2.3%

(95%CI)

(4.3-20.5) (0.1-8.3)

I

2

99.1% 97.0%

Total Prison Population: 1,400,000 Total HBsAg+ prisoners: 32,000 ( 0 – 116,500)

GLOBAL


Global HBsAg prevalence among prisoners: 4.8 (3.2-6.8)

Total HBsAg+ prisoners: 491500 (327,500 – 696,500)

Notes: Published data include national level and Sub-national reports; NR: Date not reported; N/A: Imprisonment rate

not available; Estimated numbers of prisoners living with HBsAg are rounded to the nearest 500

Countries with no data meeting HBV inclusion criteria (imprisonment rate): Albania 189; Algeria 162; Andorra 72;

Angola 106; Antigua and Barbuda 373; Austria 95; Bahamas 363; Bahrain 301; Bangladesh 43; Barbados 322;

Belarus 306; Belgium 105; Belize 449; Benin 77; Bhutan 145; Bolivia 122; Botswana 188; Brunei Darussalam 132;

Burundi 93; Cambodia 105; Cameroon 115; Canada 106; Cape Verde 286; Central African Republic 16; Chad 39;

Chile 246; China 119; Colombia 244; Comoros 31; Congo 27; Costa Rica 352; Côte d'Ivoire 52; Cuba 510; Cyprus

94; Czech Republic 195; Democratic People's Republic of Korea N/A; Democratic Republic of the Congo 32;

Denmark 61; Djibouti 68; Dominica 300; Dominican Republic 231; Ecuador 162; El Salvador 498; Equatorial

Guinea 129; Eritrea N/A; Estonia 216; Ethiopia 129; Federated States of Micronesia 127; Fiji 174; Gabon 210;

Gambia 58; Georgia 274; Germany 76; Greece 109; Grenada 398; Guatemala 121; Guinea 26; Guinea-Bissau 5;

Guyana 259; Haiti 97; Honduras 196; Iceland 45; India 33; Iraq 123; Israel 256; Jamaica 145; Jordan 150;

Kazakhstan 231; Kenya 118; Kiribati 136; Kuwait 92; Kyrgyzstan 166; Lao People's Democratic Republic 71; Latvia

239; Lesotho 92; Liberia 39; Lithuania 268; Madagascar 83; Malaysia 171; Maldives 341; Mali 33; Marshall Islands

66; Mauritania 44; Mauritius 159; Mongolia 266; Montenegro 174; Morocco 222; Mozambique 61; Myanmar 113;

Namibia 144; Nauru 140; Nepal 59; New Zealand 194; Nicaragua 171; Niger 39; Norway 71; Oman 36; Palau 343;

Panama 392; Papua New Guinea 61; Paraguay 158; Peru 242; Poland 191; Qatar 53; Republic of Korea 101;

Republic of Moldova 215; Romania 143; Russian Federation 445; Rwanda 434; Saint Kitts and Nevis 607; Saint

Lucia 349; Saint Vincent and the Grenadines 387; Sao Tome and Principe 101; Saudi Arabia 161; Senegal 62; Serbia

148; Seychelles 799; Sierra Leone 55; Singapore 227; Slovakia 184; Slovenia 73; Solomon Islands 56; Somalia N/A;

South Africa 292; South Sudan c.65; Sudan 50; Suriname 183; Swaziland 289; Sweden 55; Syrian Arab Republic 60;

Tajikistan 121; Thailand 465; Timor-Leste 50; Togo 64; Tonga 166; Trinidad and Tobago 258; Tunisia 212;

Turkmenistan 583; Tuvalu 110; Uganda 115; Ukraine 194; United Arab Emirates 229; United Republic of Tanzania

(Mainland) 69; Uruguay 291; Uzbekistan 150; Vanuatu 87; Viet Nam 154; Yemen 53; Zambia 125; Zimbabwe 145

24

A8. National and regional prevalence of active tuberculosis, published between 2005-2015

Imprisonment

rate

(per 100,000)1

Year

collected

Total prevalence

of active TB

% or / 100,000 †

Male prevalence

active TB

% or / 100,000 †

Female

prevalence active

TB

% or / 100,000 †

Region / Country

East and Southern Africa Ethiopia

205-207 129 2008 2.0%

2008 1913/100,000

2011 1482/100,000

Malawi5,208

73 2005 0.7%

2011 2.9% 2.9%

South Africa8,209

292 2009-2010 8.8% 8.8%

2009-2010 3.5% 3.8

Uganda12

115 2008 654/100,000

Zambia16,210

125 2000-2001 22.7% 23.2% 0%

2010-2011 12.1%


5330/100,000 8886/100,000

(95%CI)

(2066 – 9998

/100,000)

(2292-19188

/100,000) Data not pooled

I2 99.10% 98.5%

Total Prison Population: 587,000 Total prisoners with active TB: 31,000 (12,500 – 59,000)


Burkina Faso21

34 2009 1.3%

Cameroon22,23

115 2003-2004 3517 /100,000

2009 3197/100,000

Guinea211

26 2009-2010 2.5% 2.5%

Nigeria30

31 2006 1.8%

Pooled West and Central Africa 2946/100,000

(95%CI)

(2362-3591

/100,000) Data not pooled No data

I2 45.6%

Total Prison Population: 201,500 Total prisoners with active TB: 6,000 (5,000 – 7,500)

Middle East and North Africa Islamic Republic of Iran

212 287 2004-2005 910/100,000 1% 0


(95%CI)

Data not pooled Data not pooled Data not pooled

I2

Asia and Pacific*

Bangladesh213,214

43 2005-2007 2227/100,0000 2.40% 0.50%

2005-2010 600 / 100,000

Hong Kong215,216

2001 1.23% 1.23%

2005 337/100000

Malaysia217

171 2012 4.9%

Pakistan59

43 2007-2008 2.2% 2.20%

Thailand218

465 2004-2005 354/100,000 1.30% 0.90%

25

Imprisonment

rate

(per 100,000)1

Year

collected

Total prevalence

of active TB

% or / 100,000 †

Male prevalence

active TB

% or / 100,000 †

Female

prevalence active

TB

% or / 100,000 †

Region / Country

Pooled Asia and Pacific 1,173/100,000 1706/100,000 831/100,000

(95%CI)

(712 – 1747

/100,000)

1027-2553

/100,000)

(504-1238

/100,000)

I2 98.4% 93.5% 0.8%

Total Prison Population: 3,361,500 Total prisoners with active TB: 40,500 (23,500 – 57,000)

Eastern Europe and Central Asia ** Bulgaria

219 125 2004-2013 769/100,000

Poland220

191 2012 1.4%

Russian Federation221,222

445 2003 12.80% 12.80%

2005-2006 14.90% 14.90%

Tajikistan223

121 2010 4.5% 4.50%

Turkey224

222 2006-2007 108/100,000 115/100,000

Ukraine79

194 2011 4.1%

Pooled Eastern Europe Central Asia 4,903/100,000 6268/100,000

(95%CI)

(1846-9321

/100,000)

(510-17730


I2 99.40% 99.5%

Total Prison Population: 1,300,000 Total prisoners with active TB: 64,000 (23,500 – 121,000)

Western Europe*

Netherlands 69 2014 20/100,000

United Kingdom 148 2014 64.3/100,000

Pooled Western Europe Data not pooled Data not pooled Data not pooled

Total Prison Population: Total prisoners with active TB:

North America*

United States of

America225

698 2003 3.2% 3.80% 1.00%


(95%CI)

Data not pooled Data not pooled Data not pooled

I2


Latin America

Argentina123

160 2010 100 / 100,000

Brazil125,226-234

301 2002 2.7% 2.70%

2003-2004 2.5%

2005 2.7% 2.70%

2005-2006 3.8%

2006 1763 / 100,000 1763/100,000

2006 2.8% 2.80%

2007-2008 4960 / 100,000

2008 1029.5 / 100,000

2008 525.7 / 100,000

2009-2013 1044 / 100,000 1044 / 100,000

26

Imprisonment

rate

(per 100,000)1

Year

collected

Total prevalence

of active TB

% or / 100,000 †

Male prevalence

active TB

% or / 100,000 †

Female

prevalence active

TB

% or / 100,000 †

Region / Country

2013 917/100,000 1.00% 0.40%

Colombia131

244 NR 1.6%

Pooled Latin America 1977/100,000 2131/100,000

(95%CI)

(1347-2726

/100,000)

(1336-3105


I2 93.3% 92.0%

Total Prison Population: 1,401,000 Total prisoners with active TB: 28,000 ( 18,000 – 38,000)

GLOBAL


Global prevalence of active TB among prisoners: 2,790/100,000

(2050-3650/100,000)

Total prisoners with active TB: 286,000 (210,000 – 374,000)

Notes: † Prevalence as reported by the publication; NR: Date not reported; N/A: Imprisonment rate not available;

Published data include national level and Sub-national reports * Latent TB reported by Australia, Malaysia, Taiwan,

Spain, Italy, U.S.; ** MDR-TB reported in Georgia; Estimated numbers of prisoners living with active TB are

rounded to the nearest 500

Countries that did not have data meeting active TB inclusion criteria (imprisonment rate): Afghanistan 74; Albania

189; Algeria 162; Andorra 72; Angola 106; Antigua and Barbuda 373; Armenia 130; Australia* 151; Austria 95;

Azerbaijan 236; Bahamas 363; Bahrain 301; Barbados 322; Belarus 306; Belgium 105; Belize 449; Benin 77; Bhutan

145; Bolivia 122; Bosnia and Herzegovina 73; Botswana 188; Brunei Darussalam 132; Burundi 93; Cambodia 105;

Canada 106; Cape Verde 286; Central African Republic 16; Chad 39; Chile 246; China 119; Comoros 31; Congo 27;

Costa Rica 352; Côte d'Ivoire 52; Croatia 81; Cuba 510; Cyprus 94; Czech Republic 195; Democratic People's

Republic of Korea N/A; Democratic Republic of the Congo 32; Denmark 61; Djibouti 68; Dominica 300; Dominican

Republic 231; Ecuador 162; Egypt 76; El Salvador 498; Equatorial Guinea 129; Eritrea N/A; Estonia 216; Federated

States of Micronesia 127; Fiji 174; Finland 57; France 100; Gabon 210; Gambia 58; Georgia** 274; Germany 76;

Ghana 53; Greece 109; Grenada 398; Guatemala 121; Guinea-Bissau 5; Guyana 259; Haiti 97; Honduras 196;

Hungary 187; Iceland 45; India 33; Indonesia 64; Iraq 123; Ireland 80; Israel 256; Italy* 86; Jamaica 145; Japan 48;

Jordan 150; Kazakhstan 231; Kenya 118; Kiribati 136; Kuwait 92; Kyrgyzstan 166; Lao People's Democratic

Republic 71; Latvia 239; Lebanon 120; Lesotho 92; Liberia 39; Libya 99; Lithuania 268; Luxembourg 112;

Madagascar 83; Maldives 341; Mali 33; Marshall Islands 66; Mauritania 44; Mauritius 159; Mexico 212; Mongolia

266; Montenegro 174; Morocco 222; Mozambique 61; Myanmar 113; Namibia 144; Nauru 140; Nepal 59; New

Zealand 194; Nicaragua 171; Niger 39; Norway 71; Oman 36; Palau 343; Panama 392; Papua New Guinea 61;

Paraguay 158; Peru 242; Philippines 121; Portugal 138; Qatar 53; Republic of Korea 101; Republic of Moldova 215;

Romania 143; Rwanda 434; Saint Kitts and Nevis 607; Saint Lucia 349; Saint Vincent and the Grenadines 387; Sao

Tome and Principe 101; Saudi Arabia 161; Senegal 62; Serbia 148; Seychelles 799; Sierra Leone 55; Singapore 227;

Slovakia 184; Slovenia 73; Solomon Islands 56; Somalia N/A; South Sudan c.65; Spain* 136; Sri Lanka 92; Sudan

50; Suriname 183; Swaziland 289; Sweden 55; Switzerland 84; Syrian Arab Republic 60; Taiwan* ; The Former

Yugoslav Republic of Macedonia 147; Timor-Leste 50; Togo 64; Tonga 166; Trinidad and Tobago 258; Tunisia 212;

Turkmenistan 583; Tuvalu 110; United Arab Emirates 229; United Kingdom: Northern Ireland 87; United Kingdom:

Scotland 143; United Republic of Tanzania 69; Uruguay 291; Uzbekistan 150; Vanuatu 87; Venezuela 174; Viet

Nam 154; Yemen 53; Zimbabwe 145

27

A9. HIV/TB Co-infection among prison populations, published 2005 - 2015

Region / Country

Year(s) of

data

collection

HIV/TB co-

infection

among total

prison sample

(%)

Total

prevalence of

TB among

HIV+

(%)

Total

prevalence of

HIV among

TB+

(%)


Ethiopia207

2011 3.6% 47.4% 34.6%

South Africa7,8,209

2009-2010 1.6% 6.6% 42.4%

2009-2010 NR 6.2% 44.1%

2009-2010 5.1% NR 58.0%

Uganda235

2011-2012 NR NR 57.0%

Zambia16

2010-2011 1.6% 6.4% 45.8%


Burkina Faso21

2009 NR 20.0% 75.0%

Cameroon22,236

2003-2004 NR NR 25.0%

2009 NR NR 10.0%

Guinea211

2009-2010 0.3% NR 11.1%

Nigeria30

2006 8.9% NR NR

Middle East and North

Africa

No data identified or met inclusion criteria for the MENA

Region

Asia and Pacific

Australia237

2001 0.1% NR 0.9%

Malaysia217

2010 NR 16.9% NR

Eastern Europe Central Asia

Russia238

2001 NR 12.2% NR

Ukraine239,240

2005-2006 NR NR 17.7%

2006 NR NR 23.7%

Western Europe

Italy241

2001-2002 0.9% 7.4% NR

North America

USA225,242

1998 NR NR 23.1%

2003 NR NR 11.3%


Latin America

Brazil226,227,230

2002 0.6% NR 14.6%

2003-2004 0.0% NR NR

2007-2008 0.3% NR 6.9%

Colombia243,244

2010-2011 0.1% NR 14.3%

2010-2012 0.2% 11.5% 4.2%

Notes: Includes national and subnational data; includes latent and active TB infection

28

A10. Infectious disease prevalence among imprisoned people who inject drugs, published 2005-2015

Country Facility Year of

collection

HIV

(%)

Anti-HCV

(%)

HBsAg

(%)

TB

(%)


Ghana26

Central Prisons 2004-2005 11.4% 49.3%

East and Southern Africa No data identified or met inclusion criteria for the East and Southern Africa

Middle East and North Africa

Iran136,194,245-256

Prison 2001-2002 NR 78.3% 1.5%

Prison 2002 0.7% 31.5%

Prison 2002 15.1% 64.8% 4.7%

Central Prison 2002-2003 18.2% 13.6%

Central Prison 2002-2003 NR 95.4%

Prison 2003 88.9%

Prison 2003 14.0% 76.0% 4.0%

Detention center 2006 NR 80.0%

Jail 2007 6.6%

Prison 2007 2.3%

Correctional

center

2008-2009 NR 50.0% 3.3%

Prison 2009 6.4%

Prison 2009 NR 41.6%

Prisons 2009 13.9%

Prison 2009-2010 4.5%

Central Prison

and Drop in

Centers

NR NR 43.4%

Asia and Pacific

Australia46,48-50,52,257-260

Prison 2004 0.8% 56.0% 27.0%

Correctional

Center

2005 NR 40.0%

Prison 2006 NR 7.6% 7.6%

Correctional

center

2005-2009 22.6%

Prison 2008-2010 47.4%

Prison 2010 0.0% 51.0% 18.8%

Reception

Prisons

2010 0.0% 18.4%

Prison 2013 0.0% 58.2% 19.0%

Prisons NR 17.0%

Prison NR 20.7%

Prison NR 29.4%

Indonesia57

Prison 2009 13.8% 50.0% 1.1%

Pakistan145

Central Prison NR 84.2%

Taiwan199,261-263

Prisons 1994 26.4%

29

Correction center 1997 59.4% 22.2%

Correctional

institution

2005-2007 42.0%

Jail 2008-2010 52.8% 91.3% 15.3%

Eastern Europe and Central Asia

Bulgaria69,71

Prison 2009 61.4%

Juvenile

correctional

facility

2010 66.7%

Croatia264

Prison 2007 0.0% 44.0% 0.5%

Western Europe

England265

Prison NR 32.6%

Germany266

Prison 1998-1999 18.0% 83.0% 53.0%*

Ireland85

Prison 2011 6.0% 41.5%

Italy157

Prisons 2001-2002 18.2% 57.1%*

Prisons 2001-2002 24.5%

North Ireland86

Prison 2004 0.0% 2.8% 2.8%

Netherlands161

2014 58.0%

Portugal88

Prisons 2005 44.4% 68.9%

Scotland162

Prison 2010-2011 53%

Spain95

Prison 2001 53.2% 92.7%

North America

Canada99,100

Prison 2003 10.2% 55.6%

Remand

Facilities

2003-2004 5.7% 54.7%

USA104,106,108,113,114,118,170,172

,181,267,268

Sentenced and

Pretrial detainees

1994-1996 20.4%

Jail and Prison

facility

1998-2000 84.9%

Jails 1998-2002 2.5%

Juvenile

Detention Center

2000-2001 35.8%

Jail 2003-2006 1.4%

Prison 2004-2006 9.4%

Jail 2006 16.9%

Correctional

facility

2007 1.0%

County

Correctional

Facility

2009-2011 0.3% 38.0%

Correctional

facility

NR 66.2%

Caribbean

Belize121

Central Prison 2005 0.0%

Latin America

Brazil126,127,187,189,191

Prison 2003 34.5% 72.7%

Prison 2007 13.8% 34.5% 51.7%*

30

Prisons 2007-2008 66.7%

Prison 2009-2010 20.6%

Prisons 2010 0.4%

Mexico132

Correctional

facility

2001-2002 66.7%

Notes: NR: Not reported; * anti-HBc

31

A11. HIV and viral hepatitis among inmates in Compulsory Drug Detention Centers (CDDCs) published between 2005 - 2015

HIV Prevalence

anti-HCV Prevalence

HBsAg

Country Location Year(s) of

data

collection

Total CDDC

prevalence

(%)

PWID

prevalence

(%)

Total CDDC

prevalence (%)

PWID

Prevalence

(%)

Total CDDC

prevalence (%)

PWID

Prevalence

(%)

China269-

272

Beijing,

Shanghai,

Guangdong

2009-2010 0.2% NR 44.0% NR NR NR

Dongguan 2008 4.% NR NR NR NR NR

Beijing 2007 5.2% 10.3% NR NR NR NR

Guangxi 2011 9.5% NR NR NR NR NR

Taiwan273

Taoyuan 2005 6.9% 25.5% 30.5% 89.6% 16.9% 16.7%

Vietnam274

Hatay 2007-08 NR 19.8% NR 76.9% NR NR

Iran193,253,2

54,275-278

Tehran 2006 NR 24.4% NR 80.0% NR 5.8%

Tehran 2001-2002 17.% 7.8% NR NR 4.5% 1.5%

Sari 2001-2003 NR NR 30.8% 77.0% NR NR

Note: CDDCs include injecting and non-injecting people who use drugs

32

A12. Incidence of HIV and viral hepatitis among prisoners, published 2005 – 201592,97,162,279,280

Australia (South Australia)

Australia (New South Wales)*

Scotland USA (Rhode Island)

Australia (New South Wales)

Scotland

Australia (Queensland)*

Spain (Barcelona)

Estonia USA (Rhode Island)

Spain

USA (Georgia)

USA (Rhode Island)

0

2000

4000

6000

8000

10000

12000

14000

16000

1999 2001 2003 2005 2007 2009 2011 2013 2015

Inci

de

nce

pe

r 1

00

,00

0 p

ers

on

ye

ars

Year

HCV

HIV

HBV

33

A13. Modeling the interplay between prison and community HIV transmission among PWIDs

Summary:

To evaluate the fundamental dynamics that govern the interplay of HIV transmission within and between prison and

community settings, we developed a model parameterized by data of incarceration history and risk behavior among

PWIDs. Rates of HIV infection among PWIDs were stratified into communities with moderate PWID HIV

prevalence, ranging from 5 to 20%, and communities with high PWID HIV prevalence, over 20%.281

To address

empirical uncertainty regarding model parameters, we used a Bayesian inference approach to fit our model to

epidemiological data of HIV prevalence among PWIDs in and out of prisons, as well as HIV incidence in prison.

We used the fitted model to quantify the contribution of post-release ART discontinuation and behavior change of

PWIDs who temporarily share syringes while incarcerated and during a transitory period on HIV incidence among

PWIDs. Furthermore, we evaluated the impact of harm reduction programs, such as opioid substitution treatment

(OST) and lower rates of incarceration for non-violent drug users, and ART retention in care post-release for

curtailing HIV incidence across a range of epidemics parameterized from different countries.

Our model accounted for the elevated frequency of needle sharing in prison as well as discontinuation of ART

during a transitory period following prison release.282-286

Given the sparsity of data regarding the impact of this post-

release behavior change on HIV transmission, we conducted a sensitivity analysis to evaluate the contribution of the

frequency of post-release needle sharing and percentage discontinuation of ART treatment on HIV incidence among

PWID within the community and prisons. We denoted as ‘temporary sharers’ PWIDs who share syringes while

incarcerated, a proportion of whom share needs a transient duration following release, but not beyond. A detailed

description of our modeling methodology, parameterization, assumptions and limitations are presented in the

following section. We limited our model to inmates who inject heroin, as the majority of research and prevention

has focused on these individuals. To assess the variability of the effectiveness of interventions in settings with

different HIV epidemics among injection drug users, we considered parameters from a range of settings with

communities of PWID.

Model Structure:

To evaluate generalized principles governing the interplay between HIV transmission among people who inject drug

(PWID) in the community and in prison around the world, we developed a deterministic compartmental model of

drug injection transmission of HIV among the general community and incarcerated populations. To determine the

posterior distributions of model parameters through a Bayesian analysis, we used a range of estimates from HIV

prevalence among PWID in the general population, HIV prevalence among PWID in prisons and overall HIV

incidence in prisons. We then used our parameterized model to quantify the relative contribution of incarceration to

HIV incidence among PWID in different communities. Additionally, we evaluated the impact on HIV transmission

of harm reduction programs (opioid substitution treatment), ART retention in care post-release, and lower rates of

incarceration for non-violent drug users.

Model Formulation:

Transmission dynamics among PWID within and between prisons and the community were modeled by differential

equations. The state variables are given by ,

h

k iX , where h is the HIV infection status and stage of progression (1 =

susceptible; 2 = acute infection; 3 = latent infection with CD4 greater than 350 cells / L ; 4 = latent infection with

CD4 less than 350 cells / L ; 5 = pre-AIDS with elevated viremia; 6 = AIDS; 7 = initiated ART with CD4> 350

cells / L ; 8 = initiated ART with low CD4 or pre-AIDS; 9= initiated ART with AIDS), i is the incarceration

status (1 = currently incarcerated, 2 = recently released (within six months), 3 = previously incarcerated, 4 = never

incarcerated), and k is injection risk behavior (1 = non-PWID, 2 = PWID who do not share syringes, 3 = PWID

who share syringes). We stratify incarcerated PWIDs who did not share syringes prior to incarceration between

permanent non-sharers and temporary sharers. Temporary sharers only share syringes in prison, consistent with the

greater proportion of PWIDs who share syringes in prison than out of prison.287-290

Hence, we add a temporary

syringe sharer group to the injection risk behavior ( 4k ). In the description that follows, a dot ( ) in the position

of these indices indicates a sum across that index. To account for a transitory elevation of injection drug risk

behavior and discontinuation of ART treatment following release from incarceration,282,285-287

we distinguish

34

between PWIDs who have been recently released within the last six months and PWIDs released further in the past

who have resumed the relatively lower risk behavior regarding injection drug use and ART treatment exhibited prior

to incarceration. 1

, 1 1 1

, , , , , ,

,

k i

k k i k i k i k k i k i k i

k i

dXR X X X

dt

(1.1)

2

, 1 2 2

, , 2 , , ,

,

( )k i

k i k i k k i k i k i

k i

dXX X X

dt

(1.2)

3

, 4 2 3 3

2 , 3 , , ,

,

(1 ( )) ( )k i hCD

k i k k i k i k i

k i

dXa t X X X

dt

(1.3)

4

, 4 3 4 4

3 , 4 , , ,

,

(1 ( )) ( )k i lCD

k i k k i k i k i

k i

dXa t X X X

dt

(1.4)

5

, 4 4 5 5

4 , 5 , , ,

,

(1 ( )) ( )k i lCD

k i k k i k i k i

k i

dXa t X X X

dt

(1.5)

6

, 5 6 6

5 , 6 , , ,

,

(1 ) ( )k i AIDS

k i k k i k i k i

k i

dXa X X X

dt

(1.6)

7

, 4 2 7 7

2 , 7 , , ,

,

( )k i hCD

k i k k i k i k i

k i

dXa X X X

dt

(1.7)

8

, 4 3 4 8 8

3 , 4 , 8 , , ,

,

( ) ( )k i lCD

i k i k i k k i k i k i

k i

dXa X X X X

dt

(1.8)

9

, 5 9 9

5 , 9 , , ,

,

( )k i AIDS

k i k k i k i k i

k i

dXa X X X

dt

(1.9)

We denote the rate of entering PWID status k as kR , which is set as to maintain a constant population size. For

k=1, 2, 3, 4, respectively, we have

9

1 1 1, 1,

6

j

j

j

R X X

,

3 9

2 , ,

2 6

(1 ) 1idu idu j

k k j k

k j

R X X

,

3 9

3 , ,

2 6

idu j

k k j k

k j

R X X

, and

3 9

2 , ,

2 6

1idu idu j

k k j k

k j

R n X X

, where

idu is the proportion of PWIDs who share syringes in the

general population. The proportion of temporary sharers is denoted as ( ) (1 )idu idu idu idu

inc , where

idu

inc is the proportion of PWIDs who share syringes while incarcerated. To prevent negative values of idu ,

idu

inc

was sampled under the condition of being greater or equal to idu . New individuals enter the model as never having

been incarcerated, with , 1k i for 4i and 0 otherwise. The background death rate unrelated to HIV for PWID

status k is denoted k . To model the impact of expanding coverage of antiretroviral therapy we incorporated

4 4( ), ( ),and ( )HCD LCD AIDSa t a t a t as the proportions of individuals with high CD4 cell count (more than 350

cells / L threshold), low CD4 cell count (less than 350 cells / L threshold), and AIDS (advanced HIV/pre-AIDS

35

stage), respectively, with incarceration status i that are initiated on treatment at that time. We assumed that ART is

initiated at CD4 count threshold of less than 350. Thus, for the base case the status quo analysis, we assumed that 4( ) 0HCDa t . For simplicity, we assumed a uniform ART initiation rate irrespective of incarceration status. The

force of infection for individuals of specific injection drug use status k , and incarceration status i is given by ,k i .

4 9, 0 2 5 6

, , , , , ,

3 7,

( )

idu

k i j j

k i acute k latent k pre aids k aids k art k

j jk

cX X X X X

X

,

where if 1i i (currently incarcerated) and *=sum of never incarcerated, recently released, and previously

incarcerated if 2,3,4i . The transmission rate of HIV per use of contaminated syringes is denoted 0

idu if the

syringe was last used by an individual infected with HIV. The relative infectiousness of individuals in HIV stage h

compared to those with latent infection is denoted h . The frequency of syringe sharing for those of incarceration

status i is denoted ,k ic , where , ,k i k i ic f and where ,k if is the frequency of injection and i is the percentage

of PWIDs sharing syringes. Given our focus on syringe sharing as the route for HIV transmission under

consideration, we set 1, 0i and 2, 0i , such that transmission occurs exclusively between sharers. This is a

conservative assumption given that a sharer could become infected from a contaminated needle from a non-sharer.

Further studies on HIV transmission among PWIDs could explore relaxing this assumption by accounting for

differential infection risk from sharers and non-sharers.

Consistent with epidemiological behavioral studies of PWIDs with a history of incarceration,282-284,291

we assumed

that a proportion idu of recently released PWIDs who shared syringes in prison but not prior to incarceration will

continue to share syringes for a transitory period following release. After this transitory period, the proportion of

PWIDs who share syringes returns to that of PWIDs who have never been incarcerated, given that PWIDs typically

resume the injection behavior they exhibited prior to incarceration.282,284

In addition, epidemiological studies have

shown that more than 40% of the incarcerated individuals on ART would have poor adherence to treatment or even

discontinue entirely within a period of the first six-months post-release.285,286,292,293

We define the movement in and out of prison through k , a transition matrix which includes the rate of first-time

incarceration that depends on PWID status,inc

kr , rate of discharge from prison that depends on PWID status,disc

kr ,

average duration of the post-release transitory period of elevated risk behavior,1 elp

kr , and rate of re-incarceration

that depends on PWID status,rinc

kr .

To assess the benefits that could be gained from expanding harm reduction measures such as opioid substitution

treatment (OST), we incorporated an intervention cofactor within the force of infection ,k i as

, ,(1 (1 ))idu idu

j i j k i , where 0j for no OST and 1j for OST. The proportion increase in intervention j

among individuals of incarceration status i is denoted ,

idu

j i and the relative decrease in the force of infection is

denoted idu

j . The relative force of infection under OST 1

idu was varied in the uncertainty analyses from 0.16 to

0.5, consistent with epidemiological studies.294-296

The mean duration of HIV infection phase h is denoted by 1 h .

Consistent with empirical studies, we assumed that PWIDs who continue OST after incarceration have a 20% (95%

CI: 10-30%) reduced risk of re-incarceration while they are under treatment.297

Baseline coverage of OST was not

explicitly modeled, but assumed to be implicitly included in epidemiological data on HIV prevalence and incidence.

Altogether, the population dynamics of incarceration at equilibrium is given by:

36

,1

inc

n nn ninc

n n

rP A

r

, ,2 ,1 ( )disc elp

n n n n nP P r r , ,3 ,1( ) ( ) ( )elp disc rinc elp

n n n n n n n nP P r r r r ,

,4 ( )inc

n n n nP r ,with ( )( )

( )( )( )

rinc elp

n n n nn disc rinc elp rinc elp disc

n n n n n n n n n

r rA

r r r r r r

,

where ,n iP is the proportion of individuals with injection drug status n ( 1n for non-PWID, and 2n for PWID)

and incarceration status i .The system of differential equations was numerically integrated in continuous time in

MATLAB 8.5® using a fourth-fifth order Runge-Kutta solver (“ode45”).

Model fitting and analysis:

To estimate posterior distributions for the model parameters governing HIV transmission, injection drug behavior

and incarceration, we using a Bayesian melding method to calibrate the model to epidemiological data of HIV

prevalence among PWIDs, HIV prevalence among incarcerated PWIDs and HIV incidence in prison.298

Data were

divided between communities with high PWID HIV prevalence that ranged from 20 to 60% and communities with

moderate PWID HIV prevalence that ranged from 5 to 20%.281,299-301

Empirical estimates of HIV prevalence among

incarcerated PWID ranged from 22 to 80%302,303

for communities with high PWID HIV prevalence and 5.7 to

28.6%106,118,304-306

for communities with moderate PWID HIV prevalence. For annual HIV incidence in prisons, we

derived a pooled estimates from the literature that ranged between 0.01 and 1.8%307,308

for communities with

moderate PWID HIV prevalence, and 0.01–4% 72,307,308

for communities with high PWID HIV prevalence. Model

parameters were randomly sampled from their prior distributions, and each parameter set sampled was then used to

simulate a HIV epidemic which was run for a randomly sampled duration between 10 to 45 years, consistent with

the range of estimates of the durations of injection drug epidemics in different settings worldwide.288

To establish

the baseline in the absence of the improvements in intervention that we are considering here, we simulated status

quo base case epidemics.

To compare model predictions with observed data, we applied a Bayesian melding approach, incorporating a

likelihood function and using all available prior information regarding model inputs to generate posterior

distributions of model parameters. We used prior distributions defined from epidemiological and clinical studies

(Tables S1-S2) for each input model parameter. The likelihood distribution was defined as

prison HIV incidence [Community PWID prev range] [Prison PWID prev range]( ) 1 1Lik Tr which is the product of a triangular

distribution (with mode: 0.1%, and ranges detailed above) for observed HIV incidence data and uniform

distributions for the observed HIV prevalence data among PWIDs in communities and HIV prevalence among

incarcerated PWIDs. The function 1[a,b]

(x) =1,if xÎ [a,b] and 0 otherwise.

To describe the Bayesian melding algorithm, we denote the simulation model (Eqs. 1.1-1.9) by M, the

epidemiological parameters (Tables S1-S2) by and the model-predicted output by ( )M . We denote the

prior distribution for each model parameter by ( )q . We denote the data by W and the associated likelihood of the

model outputs by ( ) Pr( )L W . The posterior distribution of inputs is then proportional to ( ) ( )q L . We

implemented a sample-importance-resample algorithm [32] to generate the posterior distribution. Specifically, we

first generated a set of input parameters, ( )i , by randomly sampling from the respective prior distributions i times.

We then evaluated the model using that set of parameters, ( ) ( ( ))i M i , for each run i. Next, we calculated the

corresponding likelihood for the model run. For each sample ( )j , with non-zero corresponding likelihood, the

sampling weight was

1

( ) ( ( )) ( ( ))nT

k

j L j L k

. To ensure a sufficient sample from the posterior

distributions, we set i=100,000.

37

The number of non-zero likelihood samples, nT , was 2796 for the high PWID HIV prevalence communities and

1341 for the moderate prevalence communities. To generate the posterior distribution for the inputs, we repeated

this sampling procedure 10000 times with replacement, using a probability of selection proportional to the sampling

weights. Output from the simulation resampled most frequently (i.e., the simulation that most closely fit the

empirical prevalence data) represented the estimated mode for the output parameters of interest. The 2.5th

and 97.5th

percentiles of the inputs (and the resulting model outputs) correspond to 95% credible limits.

The fitted model was used to evaluate the contribution of incarceration to HIV infection among PWIDs and the

potential impact of a range of different program interventions involving incarceration and post-incarceration harm

reduction as well as lower incarceration rates. Simulated epidemics cover a wide range of scenarios from endemic

state to slowly increasing early phase epidemic scenarios with low prevalence that are collectively applicable to

different settings (Figure S2). Interventions were assumed to be initiated in 2016, which was the latest year in model

fitting (Figure S2).

Figure S2 Sample of model simulations of HIV epidemics parameterized to correspond to a range of HIV

prevalences. This sample of 250 simulated epidemics are shown for illustration.

Given that our focus was estimation of the contribution of incarceration to injection related HIV transmission among

injection drug users and the possible impact of interventions on the HIV epidemic among PWIDs, we did not

address sexual, tattoo-related or mother-to-child transmission of HIV. As for any modeling study, we made simplify

assumptions that capture the fundamental dynamics pertinent to the objectives of our analyses without including

extraneous details. For simplicity, our model did not incorporate the dynamics of initiation and cessation of injection

drug use, such that the proportion of PWID in the population was assumed to be constant. To assess the robustness

of our model projections to this assumption, we conducted uncertainty analysis to consider the uncertainty and

variability surrounding incarceration and post-incarceration injection drug behaviors and harm reduction

interventions.

38

Table S1: HIV natural history parameters used in our HIV transmission dynamic model.

Variable Meaning (units) Prior distributions refs

Posterior distribution

Median (95% credible interval)

0

idu HIV transmission per use of shared

syringe (if last person to use was

infected)

Uniform(0.0029,0.024) 309,310

M: 0.0032 (95%CrI: 0.003 – 0.013)

H: 0.0092 (95%CrI: 0.003 – 0.013)

acute Relative infectiousness of individuals

in acute phase compared to latent

infection

Uniform(4.5,27) 311,312

M: 18.39 (95%CrI: 4.86 – 26.02)

H: 18.79 (95%CrI: 4.85 – 26.45)

latent Relative infectiousness of individuals

in latent phase compared to latent

infection

1 NA

pre aids Relative infectiousness of individuals

in pre-AIDS phase compared to latent

infection

Triangular(5,7,10) 311

M: 7.16 (95%CrI: 5.52 – 8.11)

H: 6.47 (95%CrI: 5.45 – 8.12)

aids Relative infectiousness of individuals

in AIDS phase compared to latent

infection

0 311

NA

art Relative infectiousness of virally-

suppressed individuals on ART

compared to latent infection

0.08 313

NA

21 Mean duration of acute phase

infection (months)

Triangular(1.23,2.9,6) 311

M: 5.91 (95%CrI: 1.30 – 5.79)

H: 4.88 (95%CrI: 1.35 – 5.8 )

31 Mean latent period with CD4 count

higher or equal to 350 (years)

Triangular(5.3,6.5,7.7) 314-316

M: 7.27 (95% CrI: 5.37 – 7.62)

H: 6.64 (95%CrI: 5.37 – 7.65)

41 Mean latent period with CD4 count

lower than 350 (years)

Triangular(1.7,2.5,3.3) 314-316

M: 2.83 (95%CrI: 1.75 – 3.28)

H: 2.99 (95%CrI: 1.76 – 3.27)

51 Mean duration with elevated viral load

during pre-AIDS phase (months)

Triangular(4.81,9,18) 311,315,317

M: 16.19 (95% CrI: 5.09 – 17.29)

H: 13.19 (95%CrI: 5.18 – 17.6)

61 Mean duration of AIDS before death

(months)

Triangular(6.97,10,28) 311,315

M: 10.59 (95% CrI: 7.52 – 27.37)

H: 25.17 (95%CrI: 7.56 – 27.52)

71 Mean duration of viral suppression for

individuals on ART with high CD4

(years)

Triangular(8,20,40) 288,318

M: 8.35 (95% CrI: 8.20 – 19.64)

H: 11.57 (95%CrI: 8.27 – 19.64)


individuals on ART with low CD4

(years)

Triangular(5,12,20) 288,317-319

M: 16.18 (95% CrI: 5.23 – 19.27)

H: 7.9 (95%CrI: 5.26 – 19.49)


individuals on ART with AIDS

(years)

Triangular(2,4.8,9.7) 318

M: 5.57 (95% CrI: 2.13 – 9.48)

H: 9.13 (95%CrI: 2.21 – 9.46)

rta Annual ART initiation rates for low

CD4 count and AIDS

Calibrated to have ART

coverage between 5 - 60% 320,321

M: 0.44 (95% CrI: 0.03 – 0.66)

H: 0.53 (95%CrI: 0.03 – 0.6)

39

Table S2: IDU and incarceration parameters used in our HIV transmission dynamic model.

Variable Meaning (units) Prior distribution refs



incP Proportion of incarcerated

population

Uniform(0.0015, 0.012) 322,323

M: 0.009 (95% CrI: 0.002 – 0.0117)

H: 0.007 (95%CrI: 0.002 – 0.0117)

1 Rate of exiting the model for

non-PWID

0.02* NA

2 Average non-HIV mortality rate

for PWID

Uniform(0.009,0.07) 324

M: 0.06 (95% CrI: 0.011 – 0.06)

H: 0.01 (95%CrI: 0.011 – 0.07)

iduJ Proportion of population who

are PWID

Uniform(0.002,0.052) 325

M: 0.009 (9%% CrI: 0.0027 – 0.05)

H: 0.007 (95%CrI: 0.0035 – 0.05)

idu

incJ Proportion of incarcerated who

are PWID

Uniform(0.1,0.75) 287

M: 0.18 (95% CrI: 0.12 – 0.73)

H: 0.50 (95%CrI: 0.12 – 0.73)

idu Proportion of PWID who share

syringes out of prison

Uniform(0.1,0.75)288-290,326,327

M: 0.28 (95% CrI: 0.11 – 0.40)

H: 0.72 (95%CrI: 0.19 – 0.72)

idu

inc Proportion of PWID who share

syringes in prison Max(

idu

,Uniform(0.6,0.95)) 287

M: 0.89 (95% CrI: 0.60 – 0.94)

H: 0.73 (95%CrI: 0.61 – 0.93)

iduf Number of injections per non-

incarcerated PWID annually

Uniform(107,260) 327-329

M: 120 (95% CrI: 112 – 256)

H: 190 (95%CrI:111 – 256)

idu

incf Number of injections per PWID

in prison annually

Uniform(6,100) 330,331

M: 6 (95% CrI: 7 - 79)

H: 64 (95%CrI: 11 - 97)

ART Proportion of recently released

HIV infected individuals who do

not discontinue ART during the

post-release transition

Uniform(0,0.6) 285,286,292,293

M: 0.28 (95% CrI: 0.02 – 0.58 )

H: 0.20 (95%CrI: 0.02 – 0.58)

idu Proportion of injections of

syringe-sharers that are shared

(non-incarcerated)

Uniform(0.49,0.72) 327

M: 0.51 (95% CrI: 0.5 – 0.71)

H: 0.52 (95%CrI: 0.5 – 0.71)

idu

inc Ratio of injections of syringe-

sharers that are shared (in prison

compared to non-incarcerated)

Uniform(1,2)Assumed±

M: 1.02 (95% CrI: 1.01 – 1.88)

H: 1.68 (95%CrI: 1.02 – 1.87)

iduI Proportion of PWID who has

never being incarcerated

Uniform(0.2,0.7) 299,332

M: 0.62 (95% CrI: 0.21 – 0.68)

H: 0.29 (95%CrI: 0.21 – 0.68)

11 discr Average duration of

incarceration for non-PWID

(years)

Uniform(2,10) 333,334

M: 2.52 (95% CrI: 2.15 – 9.76)

H: 4.85 (95%CrI: 2.19 – 9.85)

2 31 ,1disc discr r Average duration of

incarceration for PWID (years)

Uniform(1,4) 333,335

M: 2.28 (95% CrI: 1.06 – 3.90)

H: 2.76 (95%CrI: 1.10 – 3.92)

31 elpr Average duration of post-release

transitory period (months)

Uniform(1,6) 283,284,336,337

M: 5.92 (95% CrI: 1.18 – 5.85)

H: 3.53 (95%CrI: 1.1 – 5.85)

1

rincr Rate of re-incarceration for non-

PWID (years-1

)

Uniform(0.1,0.5) 338

M: 0.42 (95% CrI: 0.1.02 – 0.44)

H: 0.28 (95%CrI: 0.102 – 0.45)

2 3,rinc rincr r Rate of re-incarceration for

PWID (years-1

)

Uniform(0.1,3) 297,338

M: 0.23 (95% CrI: 0.104 – 1.46)

H: 0.22 (95%CrI: 0.103 – 1.48)

40

Variable Meaning (units) Prior distribution refs



2,1P Fraction of PWID who are

currently in prison 2 2

2

2 2

inc

inc

rA

r

M: 0.16 (95%CrI: 0.06 – 0.39 )

H: 0.21 (95% CrI: 0.07 – 0.49)

1

incr Rate of initial incarceration for

non-PWID 1 1,1 1 1,1 11

( ) ( )P A P A ¥

2 3,inc incr r Rate of initial incarceration for

PWID 2(1 )idu iduI I €

idu Percentage of temporary syringe

sharers who share during the

post-release transitory period

Varied from 0 to 100%

¥ 1,1 (1 )idu

incP P J . € 2,4

iduP I . * We model adult population age 20 to 70 year olds, tracking incarceration

histories of individuals over 50 years. ± Relative percentage of injections by syringe-sharers that are shared (in

prison compared to non-incarcerated) was conditioned upon the percentage of shared injections in prison being less

or equal than 100%. M = communities with moderate PWID HIV prevalence, and H = communities with high

PWID HIV prevalence.

Table S3: Posterior distribution of PWID HIV prevalence in and out of prison.

Transmission setting Temporary sharers HIV prevalence Posterior distribution


Moderate PWIDs HIV

prevalence (5 – 20%)

0% sharing during transitory

period

In prison 14.7% (95%CI: 6.9 – 22.6%)

Out of prison 12.0% (95%CI: 5.7 – 19.3%)

50% sharing during

transitory period

In prison 17.5% (95%CI: 9.0 – 26.9%)

Out of prison 13.6% (95%CI: 6.9 – 19.0%)

100% sharing during

transitory period

In prison 19.7% (95%CI: 9.6 – 27.6%)

Out of prison 17.16% (95%CI: 6.8 – 19.4%)

High PWIDs HIV

prevalence (20 – 60%)

0% sharing during transitory

period

In prison 43.5% (95%CI: 25.0 – 68.1%)

Out of prison 35.0% (95%CI: 18.4 – 56.2%)

50% sharing during

transitory period

In prison 43.7% (95%CI: 24.9 – 68.7%)

Out of prison 34.2% (95%CI: 18.0 – 56.2%)

100% sharing during

transitory period

In prison 44.7% (95%CI: 25.8 – 68.2%)

Out of prison 34.3% (96%CI: 18.3 – 55.9%)

41

A14. Partial rank correlation coefficients (PRCCs) of model parameters.

Note: A parameter was considered to be important in affecting the impact of temporary shares on HIV transmission

if |PRCC|>0.4. The figure only shows parameters for which PRCC values were statistically significant (P-value <

0.05). Specifically, the proportion of PWID who share syringes out of prison, non-HIV PWID mortality rate,

proportion of PWID who has never being incarcerated, the rate of re-incarceration for PWID, proportion of PWID

who share syringes in prison and the HIV transmission per use of shared syringe were the most impactful

parameters. 0

idu , HIV transmission per use of shared syringe (if last person to use was infected);acute , Relative

infectiousness of individuals in acute phase compared to latent infection; 21 , Mean duration of acute phase

infection; 51 , Mean duration with elevated viral load during pre-AIDS phase; 81 , Mean duration of viral

suppression for individuals on ART with low CD4; 2 , Average non-HIV mortality rate for PWID; idu ,

Proportion of PWID who share syringes out of prison; idu

inc , Proportion of PWID who share syringes in prison;

iduf , Number of injections per non-incarcerated PWID annually; idu

incf , Number of injections per PWID in prison

annually; idu , Proportion of injections of syringe-sharers that are shared (non-incarcerated);

idu

inc , Ratio of

injections of syringe-sharers that are shared (in prison compared to non-incarcerated); 21 discr , Average duration of

incarceration for PWID; 31 elpr , Average duration of post-release transitory period; 2

rincr , Rate of re-incarceration

for PWID; iduI , Proportion of PWID who has never being incarcerated.

42

A15. Model Results: Effect of different incarceration-based interventions on HIV incidence after 5 years.

Note: RPI = reduction in PWIDs incarceration rates. OST = opioid substitution treatment. For RPI, initial

incarceration and re-incarceration were instantaneously reduced at the same rate. OST was introduced during

incarceration and supplemented by follow-up after release throughout the transitory period of elevated risk. Bounds

for every scenario (A-F) reflect median and range of effect estimates for the range of HIV epidemics modelled

(whiskers are upper and lower 95% confidence interval). (A-C) effectiveness of interventions under the lower-bound

assumption that 0% of ‘temporary sharers’ share syringes post-release, (D-F) the upper-bound assumption that 100%

of ‘temporary sharers’ continue sharing syringes post-release. When OST is used in combination with ART

retention, we assumed the same coverage increase from baseline for both interventions

43

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