High HCV prevalence among drug users in Iran: Systematic review and meta-analysis of epidemiological evidence (2001 – 2012)

Abstract

Objective

Drug users, particularly drug injectors, are at elevated risk of blood-borne diseases. This study systematically reviewed the prevalence of hepatitis C virus (HCV) mono-infection and its co-infections with human immunodeficiency virus (HIV) and hepatitis B virus (HBV) in drug users in Iran.

Methods

We conducted searches in international, regional, and Iranian databases, screened documents, extracted data, generated pooled point prevalence and 95% confidence intervals (CI).

Results

Overall, 13,821 subjects (87.4% male) with an average age of 32.4 (95% CI: 31 - 33) from 24 original studies were included in the analysis. Pooled HCV prevalence (95% CI) among drug users with and without an injection history was 45% (37 – 54) and 8% (4 – 13), respectively. Pooled HCV prevalence (95% CI) among individuals with versus without a history of imprisonment and needle sharing were: 58% (39 - 77) vs. 44% (20 - 68) and 56% (41 - 71) vs. 49% (26 - 71), respectively. Prevalence (95% CI) of HCV/HIV co-infection among injectors was 11% (5 – 16).

Conclusions

HCV prevalence is high in drug users in Iran especially among those with a history of injection drug use, needle sharing, and imprisonment. Drug user-focused HCV prevention and treatment programs are imminently needed.

INTRODUCTION

To date, there are more than 150 million persons worldwide who are infected with hepatitis C virus (HCV),^{(1, 2)} a blood-borne disease causing several difficult to treat health conditions such as cirrhosis (5-20% risk in 20-30 years) and liver cancer (1-5% annual risk depending on staging of liver fibrosis and cirrhosis).^{(3, 4)} There is no effective HCV vaccine available yet. As a result, public health and behavioral interventions are the only means to prevent HCV infection, particularly among high-risk populations. People who inject drugs (PWID) are at an especially high risk of contracting HCV and other fatal blood-borne diseases, including human immunodeficiency virus (HIV) and hepatitis B virus (HBV).^(5-7)

In 2012, it was estimated that there were nearly 12.7 (95% CI: 8.9 – 22.4) million PWID worldwide.⁽⁸⁾ Access to HCV treatment for PWID has been limited due to a multitude of factors, including low HCV testing coverage and guidelines that recommend treatment only to drug-abstinent patients.⁽⁹⁾ Thus, HCV prevention and treatment among PWID remains a major public health challenge globally, especially in countries with high rates of injection drug use such as Iran.^(10-13)

The recreational use of opium smoking has been widespread for centuries in Iran. Over the past three decades, opium consumption in the country has been greatly influenced by its geographic proximity to neighboring Afghanistan, the world's largest opium producer.^{(8, 14)} In recent decades, there has been a shift in the patterns of opiate use from smoking opium to injecting heroin.⁽¹⁵⁾ According to the only national Iranian household survey, conducted in 2011, 6.2% of people aged 15-64 (nearly 3.5 million people) reported using an illicit drug in the last 12 months, 5.2% reported using an illicit opioid, and 0.5% reported using heroin.⁽¹⁶⁾ Varying sources place the number of PWID in Iran between 200,000 - 300,000, from whom nearly 100,000 reside in Tehran.^{(17, 18)}

Since 2002, to curb the blood-borne epidemic among PWID, Iran has adopted and rapidly rolled out harm reduction policies promoting opioid substitution treatment (OST), needle and syringe programs (NSP), outreach, and prison-based programs.⁽¹⁹⁾ Nevertheless, the HCV epidemic continues to pose an emerging public health threat in Iran.⁽²⁰⁾ While there have been several sporadic HCV serological surveys among PWID in the last decade, a systematic approach to assess HCV distribution and trends in various sub-populations in Iran is lacking. The objective of this study is, for the first time, to systematically compile and synthesize the epidemiologic evidence on the prevalence of HCV infection and its co-infection with HIV and HBV among drug users outside of prison in Iran. This information could assist policy makers for public health decision-making about interventions targeted at reducing the burden of HCV.

METHODS

Overview

We conducted a systematic review to identify studies reporting on the prevalence and incidence of HCV infection and its co-infections with HIV and HBV among drug-using populations in Iran. We undertook the following four steps: (1) conducted searches to identify scientific documents, (2) screened documents to identify eligible studies, (3) extracted data from included studies, and (4) organized, pooled, and analyzed data. Below, we have provided details for these steps.

Conducting searches and identifying scientific documents

This step included three components. First, we used a strategy employed in another systematic review conducted recently by our team⁽²¹⁾ to search several international (PubMed, Web of Science, CINAHL, PsycINFO), regional (IMEMR), and Iranian (Iranmedex, Iranpsych) databases. Given the scarcity of data related to Iran, we conducted a broad search using keyword combinations for geographic location (i.e., country and province names) and diseases (i.e., HCV, HIV, and HBV). We did not limit our search parameters to a specific sub-population (e.g., drug users), language, or time interval. Instead, we manually screened the retrieved documents and included all that met our eligibility criteria, as described below. For Iranian databases, we used both Persian and English keywords. Since the use of combinations of keywords was not possible for these databases, we used a single broad search term to yield a more sensitive search. We imported all citations identified through international databases to an Endnote library and removed duplicative citations.

For Iranian databases, we reviewed retrieved citations in Microsoft Word and manually entered eligible titles into the Endnote database given that the automatic export of citations to Endnote was not available for these databases. Second, we hand-searched the reference section of relevant review articles (i.e., review studies with similar eligibility criteria and scope as ours) or national program reports to identify studies with original data. Third, we contacted researchers in the field of drug use and infectious diseases in several academic and public health organizations in Iran and internationally and asked for additional reports of original data that may have been missed in our search.

Screening of scientific documents

Eligibility criteria

The objective of screening was to identify scientific documents with epidemiologic evidence on the prevalence and or incidence of HCV infection and its co-infection with HBV or HIV among drug using populations who were not in a correctional facility (including prison) or inpatient healthcare facility during or immediately before the time of the survey. We used the following five eligibility criteria in the selection of relevant studies: (1) document type, (2) study design, (3) disease area, (4) geographic setting, and (5) population. With respect to the document type, we included all scientific documents reporting original data (i.e., gathered directly by conducting surveys and laboratory tests on specimens), in the form of a peer-reviewed manuscript, progress report, abstract, technical report, or substantive scientific commentary. We excluded documents not reporting epidemiologic data (e.g., legal cases, legislation), and also not reporting original data (e.g., data simulation) or documents lacking scientific and methodological details needed for the assessment of the validity of findings (e.g., media reports). We retained documents that were self-described as “systematic reviews” or “meta-analyses” (scientific documents such as peer-reviewed manuscripts or abstracts summarizing results from a group of epidemiologic studies) for hand searching of references. We included all study designs reporting data on the prevalence and incidence of disease, including cross-sectional studies, cohort studies, and even experimental studies (e.g., randomized controlled trials) in which a biological survey was conducted to test for HCV prior to the introduction of the intervention (baseline). We excluded case reports, case series, and qualitative studies. Studies with a sample size less than 20 were considered to be underpowered and also prone to a wider range of biases due to a narrow implementation scale and thus were also excluded. For the disease area, we included studies with biological evidence on mono-infection with hepatitis C virus and/or its co-infection with hepatitis B virus or HIV. We excluded self-reported data on the above diseases. We limited our geographic scope to studies conducted within Iran and excluded studies conducted among Iranian populations residing outside of Iran. For the study population, we included studies conducted in human subjects who self-identified as current or former drug users and at the time of the study were not hospitalized or in prison (i.e., facilities under the direct supervision of the Prison Organization that may contain a mix of drug and non-drug related offenders). Studies on populations who were in short-term mandatory drug treatment and rehabilitation detention centers were included. We excluded studies in non-human subjects, blood donors, hospitalized patients (regardless of injection drug use status), dialysis patients, pregnant women, families or sexual partners of HCV/HBV patients, and populations with other chronic diseases (e.g., studies reporting HCV among people with liver cancer). We did not set any limits on study implementation or publication age.

Screening process

We screened studies in a stepwise fashion. First, one of the co-authors (SN) carefully reviewed and excluded studies that clearly did not meet our eligibility criteria solely based on the title (e.g., not related to HCV, HBV, HIV, not conducted in Iran, conducted among specific groups such as blood donors). Subsequently, at the abstract level, two co-authors (SN & AL) independently screened citations to identify eligible studies. Citations included by either of the two reviewers were promoted for full text review. At the full text level, two reviewers (SN & AL) screened studies independently and included studies that provided relevant data on the prevalence and or incidence of mono-infection with HCV, and its co-infection with HBV or HIV. Citations with disagreement went through reconciliation proofs between the two reviewers, and a third coauthor provided input as needed.

Data extraction

Two of the co-authors (SN & AL) independently extracted data from included studies using structured sheets in Microsoft Excel® and discussed disagreements with the third coauthor (MM) as indicated. We extracted data on: (1) authors (or principal investigator), (2) publication year, (3) publication type, (4) language of the publication, (5) study implementation year, (6) study setting (e.g., drug treatment clinic, drop-in center (DIC), community), (7) study scale (clinic, city, province, national), (8) study target population (including eligibility criteria and history of drug use), (9) sample size and sampling methods, (10) number of recruitment sites, (11) geographic location (urban versus rural), (12) key socioeconomic indicators (age, sex, marital status, employment status, housing status, education level), (13) outcome measurement (specimen type, laboratory test), (14) outcome including prevalence of HCV mono-infection (overall and broken down by history of incarceration, needle sharing, tattoos), and (15) prevalence of HCV co-infection with HIV or HBV

If information was missing from a study, we contacted study authors for further clarification. For research studies reported in multiple formats (i.e., technical report, peer-reviewed paper, and conference abstract) we considered the most comprehensive and accessible format and used other documents to supplement missing information. We obtained and used the original databases for secondary data analysis for Malekinejad, 2008.

Risk of Bias Assessment

We adapted and used an existing and validated risk of bias assessment tool to rate the quality of evidence included in the meta-analysis⁽²²⁾. In brief, the modified tool consisted of eight domains, three of which focused on external validity and five on internal validity of the data. The external validity domains included: 1) relevance of the target population (i.e. was the study's target population a close representation of Iranian drug users), 2) appropriateness of the sampling method (i.e. was some form of random sampling or other innovative method used to select the sample), and 3) likelihood of non-response bias (i.e. was there a high response rate or an analysis indicating that responders and non-responders were similar). The internal validity domains included: 1) directness of data collection from subjects (i.e. were the data collected directly from the subjects or by proxy), 2) acceptability of the case definition (i.e. was the case definition for HCV acceptable), 3) reliability and validity of laboratory tests (i.e. were the laboratory tests used for HCV diagnosis shown to be valid and reliable), 4) consistency of data collection methods for all subjects (i.e. were the methods employed for collecting data among different participants consistent), and 5) appropriateness of the numerator and denominator of the parameters (i.e. were the numerator and denominator used for the calculation of HCV prevalence appropriate). Two co-authors (AL & SN) independently rated studies on the eight domains, reconciled disagreements, and when needed, the third co-author (MM) provided tie-breaking decisions. Each domain was ranked as a high or low risk of bias domain. On aggregate, we used a three tier ranking system (high, moderate, low) to rank the included studies as follow: 1) high risk of bias: studies with two or more high risk of bias domains, 2) moderate risk of bias: studies with only one high risk of bias domain, and 3) low risk of bias: studies without any high risk of bias domains. For studies presenting duplicative data, we reviewed the version providing the most comprehensive and complete information allowing the appraisal of data points.

Data synthesis

We created tables in Microsoft Excel® to organize and synthesize data. We categorized studies based on self-reported drug injection behaviors of the participants. Studies in which participants reported no history of drug injection were defined as never injector (NI). Those in which subjects reported injecting drugs at least once in the year prior to the survey or the subjects self-identified as current injectors and had injection marks were defined as recent injector (RI). Finally, those studies in which participants reported some history of drug-injection but the timing of drug injection was not defined were considered as ever injector (EI). If a study had both RI and EI populations, it was categorized as an EI study. Studies reporting on a combination of NI and EI or NI and RI were listed twice and prevalence data for each population was presented separately. We calculated summary point estimates and 95% confidence intervals (CI) for HCV, HCV/HIV, and HCV/HBV weighted by inverse of variance using a random-effect meta-analysis model in Stata® Version 13 utilizing the metan command. We illustrated data in the form of forest plots for the above sub-populations wherever such data was available. We also repeated the meta-analysis on a sub-set of studies that ranked as low or moderate risk of bias studies. In circumstances where the distribution of the pooled prevalence was not normal or the pooled prevalence was close to 0 or 100 and the sample size was small, using a traditional meta-analysis command (metan command in Stata) would have resulted in CIs smaller than zero or larger than 100. To address this issue, we first transformed the prevalence and CI into the logit scale in order to generate a distribution closer to normal, and then performed meta-analyses on the transformed values. We derived overall pooled prevalence and CIs by back-transforming the estimates and CIs using the -invlogit- function. In a few cases, the CI of pooled prevalence data remained smaller than zero or larger than 100 even after using the logit transformation. For these data points, using the metaprop command in Stata, we calculated CIs for the original data using the exact binomial and score test.

RESULTS

From a total of 3401 retrieved scientific documents from our electronic searches (after de-duplication), hand-searching of review studies and reports, and contacting experts, we identified and included 32 relevant scientific documents. We contacted a total of 24 experts from whom we received responses from 11 yielding a total of 18 new documents. Four new documents sent by the research experts met our eligibility criteria and were included in the 32 documents for final assessment and potential data extraction. Fourteen other documents were eliminated because the subjects were prison inmates (Figure 1).

Figure 1. Search Results.

Number of studies identified at each step of searching, screening, and data extraction

From the final list of 32 included documents, 23 (72%) were in English^(23-45) and 9 (28%) were in Persian.^(46-54) Thirty documents were peer-reviewed articles^{(23-52, 54)} and two were technical reports.⁽⁵³⁾ From the 32 included documents, 8 reported the same data as other studies (6 duplicates and 1 triplicate); hence there were 24 original studies. The 8 duplicative studies were not included in the final meta-analysis but used to complete key information when data points were missing from the original document reporting on the same study.

Table 1 presents characteristics of the included research studies. Of the 24 original studies, 9 (37.5%) were studies on RI,^{(23-26, 32, 40, 44, 45, 53)} 10 (41.7%) were studies on EI,^{(29-31, 33, 35-37, 41, 46, 54)} and 1 (4.2%) was a study on NI.⁽⁴³⁾ Another 4 (16.7%) studies reported on both EI and NI.^{(27, 42, 47, 50)} These four studies are presented twice in Table 1, once among the EI population and a second time among the NI population. Included studies were carried out within an 11-year time span (2001 to 2012), with more than half being implemented between 2006 and 2012. With respect to the geographic location, 8 (33.3%) studies were conducted only in Tehran (the capital city),^{(24-26, 31-33, 43, 44)} 12 (50.0%) in a city other than Tehran,^{(27, 29, 30, 36, 37, 40, 42, 45-47, 50, 54)} and 4 (16.7%) in multiple cities.^{(23, 35, 41, 53)} All studies implemented cross-sectional designs and 2 applied respondent-driven sampling (RDS)^{(32, 45)} for participant recruitment. With respect to study settings, 3 (12.5%) recruited subjects from DIC,^{(23, 35, 37)} 7 (29.2%) from drug treatment clinics,^{(25, 29, 31, 33, 40, 47, 50)} 2 (8.3%) from the community,^{(36, 46)} 1(4.2%) from homes,⁽⁴²⁾ 4 (16.7%) from health facilities including voluntary HIV counseling and testing (VCT) sites,^{(27, 30, 43, 54)} 1 from a detention center (4.2%),⁽²⁶⁾ and 5 (20.8%) from a mix of settings.^{(24, 32, 44, 45, 53)} One study did not report the recruitment setting.⁽⁴¹⁾ All studies used whole blood except for one that used saliva⁽⁴⁴⁾ and one that used dried blood samples.⁽⁵³⁾

Table 1.

Characteristics of populations and studies included in systematic review

	Characteristics of Population			Characteristics of Study
Author/PI & Date	Age Mean (SE) Min-Max	% Male	Sample SES1	Study Year & Location	Scale & # Sites	Study Setting2	Biological Test3	Sampling Method	Sample Size4
Recent IDU
Alipour 2013 (English)	36.45	84%	Unmarried: 44.8% Under-educated: 74.2%	Tehran, Mashad, Shiraz (2010)	City (Multiple)	DIC	HCV: ELISA & WB HIV: ELISA & WB HBV: ELISA	Convenience	268
Amin-Esmaeili 2012 (English) Rahimi-Movaghar 2010 (English)	33.9 (+/− 9.4) 16 - 65	95.80 %	Unmarried: 70.8% Under-educated:53.4% Homelessness: 38.8% Unemployed: 64.1% Imprisonment: 70.9%	Tehran (2006)	City (Multiple)	Mixed (Drug treatment clinic, DIC, community)	HCV: ELISA HIV: ELISA & WB HBV: EIA & IEMA Well	Purposive & snowballing (community) Convenience (drug treatment centers)	904
Amini 2005 (English)	NR	NR	NR	Tehran (2002)	City (Single)	Drug treatment clinic	HCV: EIA HIV: EIA HBV: EIA	Convenience	34
Eskandarieh 2013 (English)	28.78 13 - 62	96.50%	Unmarried: 76.2% Under-educated: 70.4% Homelessness: 37.0% Unemployed: 14.8% Imprisonment: 72.7%	Tehran (2008)	City (Single)	Detention center (Shafagh)	HCV: NR HIV: ELISA & WB	Convenience	402
Malekinejad 20086 (English) Rahnama 2014 (English)	36.5 (+/− 9.2) 20 - 70	99.40%	Unmarried: 46% Under-educated: 45.7% Homelessness: 34.9% Unemployed: 45.8% Imprisonment: 83.2%	Tehran (2007)	City (Multiple)	Mixed (Hospital, DIC)	HCV: ELISA HIV: EIA HBV: NR	Respondent- driven	564
Norouzi 20116 (Persian)	35.96 (+/− 8.03) 20 - 54	95.3%	Unmarried: 29.7% Under-educated: 62.5% Homelessness: 10.4% Unemployed: 32.8%	Karaj, Isfahan, Gorgan (2011)	City (Multiple)	Mixed (Drug treatment clinic, DIC)	HCV: ELISA	Convenience	192
Ramezani 20146 (English)	Median: 33.3 17 - 58	100%	Unmarried: 67% Under-educated: 70% Unemployed: 17% Imprisonment: 73%	Arak (2012)	City (Single)	Drug treatment clinic	HCV: ELISA HIV: ELISA & WB HBV: ELISA	Convenience	100
Zamani 2007 (English)	38.3 (+/− 11.9) 15-64	97%	Unmarried: 41.1% Under-educated: 75.2% Homelessness: 32.2% Unemployed: 65.8%	Tehran (2004)	City (Multiple)	Mixed (DIC and community)	PA assays	Convenience	202
Zamani 2010 (English)	29.0 (+/− 6.6)	9 7.40%	Unmarried: 69.2% Under-educated: 54.7% Unemployed: 42.7%	Foulad-shahr (2008)	City (Multiple)	Mixed (NEP, MMT, community, DIC)	HCV: ELISA HIV: EIA HBV: NR	Respondent- driven	118
Ever IDU
Ataei 2011 (Persian)	NR	NR	N/R	Golpayegan8 (2007)	City (Multiple)	Community	HCV: ELISA	Convenience	136
Azizi 20119 (Persian)	31.82 (+/− 9.18)7	NR	Unmarried: 51% Under-educated: 66.5% Unemployed: 14.8%	Kermanshah (2008)	City (Single)	Drug treatment clinic	HCV: ELISA	Convenience	263
Honarvar 20139 (English)	32.3 (+/− 7.33) 19 - 59	98.3%	Unmarried: 70.8% Under-educated: 14.2% Unemployed: 26.6%	Shiraz (2012)	City (Multiple)	VCT	HCV: ELISA & WB HIV: ELISA & WB HBV: ELISA	Convenience	569
Fadaei Nobari 2012 (English) Fadaei Nobari 2011 (Persian)	35 (+/− 9.4) 17 - 64	NR	NR	Isfahan Province8 (2008)	Province (Multiple)	Community	HCV: ELISA	Convenience	1747
Imani 2008 (English) Imani 2006 (Persian)	31.3 (+/− 7.1) 18 - 65	98.40%	NR	Shahr-e-Kord (2004)	City (Multiple)	Drug treatment clinic	HCV: ELISA	Convenience	133
Keramat 2011 (English)	29.7 (+/− 9.5) 13 - 80	71.50%	Imprisonment: 52.5%	Hamadan (2005)	City (Single)	VCT	HCV: ELISA & WB HIV: ELISA & WB	Convenience	379
Kheirandish 2009 (English) Hosseini 2010 (English)	33.7 (+/− 10.2) 17 - 70	100%	Unmarried: 60.4% Under-educated: 81.1% Imprisonment: 75.3%	Tehran (2006)	City (Single)	Drug treatment clinic	HCV: EIA HIV: ELISA & WB	Convenience	454
Khodadadi-zadeh 20069 (Persian)	29.3 (+/− 5.3)	95.50%	NR	Rafsanjan (2003)	City (Single)	Drug treatment clinic	HCV: ELISA HIV: ELISA & WB HBV: ELISA	Convenience	180
Mirahmadizadeh 2009 (English)	33.1 (+/−8.97) 15-63	96.10%	Unmarried: 64.9%	Multiple Cities (2005)	National (Multiple)	DIC	NR	Systematic Random	1531
Mir-Nasseri 2008 (English) Mir Nasseri 2011 (English) Mir-Nasseri 2005 (Persian)	33 (+/− 8.66) 19 - 54	98%	NR	Tehran (2001)	City (Multiple)	Drug treatment clinic	HCV: ELISA HIV: NR HBV: EIA	Convenience	132
Nokhodian 2012 (English) Meshkati 2011 (Persian)	31.77 (+/− 8.51) 19 - 62	94.70%	Unmarried: 47.6% Under-educated: 19.9%6 Unemployed: 44.1%	Isfahan (2008)	Province (Multiple)	DIC	HCV: ELISA	Convenience	539
Rostami Jalilian 2006 (Persian)	27.7 (+/− 7.6) 16 - 54	NR	NR	Isfahan (2002)	City (Multiple)	VCT	HCV: ELISA	Convenience	148
Sarkari 2012 (English)	NR	66.40%	Unmarried: 39.7%	Yasuj, Gachsaran, Dehdasht, Kohgilooye Province (2009)	Province (Multiple)	NR	HCV: ELISA	Convenience	158
Sayad 20089 (English)	32.7 (+/− 12.5) 155 - 64	49.60%	Unmarried: 38.5% Under-educated: 54.7%	Kermanshah (2006)	City (Multiple)	Home-based	ELISA & WB	Systematic & cluster	1721
Never IDU
Azizi 20119 (Persian)	31.82 (+/− 9.18)7	NR	Unmarried: 51% Under-educated: 66.5% Unemployed: 14.8%	Kermanshah (2008)	City (Single)	Drug treatment clinic	HCV: ELISA	Convenience	263
Honarvar 20139 (English)	28.49 (+/− 7.72) 13 - 56	75.90%	Unmarried: 63.7% Under-educated: 11.3% Unemployed: 25.6%	Shiraz (2012)	City (Multiple)	VCT	HCV: ELISA & WB HIV: ELISA & WB HBV: ELISA	Convenience	569
Khodadadi-zadeh 20069 (Persian)	29.3 (+/− 5.3)	95.50%	NR	Rafsanjan (2003)	City (Single)	Drug treatment clinic	HCV: ELISA HIV: ELISA & WB HBV: ELISA	Convenience	180
Sayad 20089 (English)	32.7 (+/− 12.5) 155 - 64	49.60%	Unmarried: 38.5% Under-educated: 54.7%	Kermanshah (2006)	City (Multiple)	Home-based	ELISA & WB	Systematic & cluster	1721
Talaie 2007 (English)	37.9 (+/− 14.95) 16-87	91.60%	NR	Tehran (2004)	City (Single)	Health care facility	HCV: EIA HIV: EIA HBV: EIA	Convenience	214

¹SES = socioeconomic status defined by marital status, employment status, history of imprisonment, homelessness, and education level. Under-educated defined as having less than a high school diploma

²Description of various study settings: Drug treatment clinic = MMT or Drug treatment center; DIC = NEP or Harm reduction program for active drug users; Health care facility = VCT or hospital; Community = community or park or detention center (a place where drug users are detained after being arrested by police, the main detention center in Tehran is called Shafagh); home-based = conducted at home; Mixed = Two of the above categories

³EIA = Enzyme immunoassay; WB = Western blot; PA = Particle agglutination; ELISA = Enzyme-linked immunosorbent assay. WB was used for confirmation when the initial test was positive

⁴Sample size is the overall number of subjects recruited for the study

⁵Imputed data

⁶Includes unpublished data

⁷Reported age distribution is a mixture of injection drug users and non-injection drug users

⁸Mixture of urban and rural

⁹Studies reporting on both EI and NI

Table 2 presents a summary of demographic and socioeconomic characteristics of 13,821 study participants. The overall weighted mean age of participants was 32.4 (95% CI: 31-33). Among all participants, 87.4 % (95% CI: 82 – 92) were male, 53.9 % (95% CI: 47 - 60) were unmarried, 54.6% (95% CI: 42 - 66) were under-educated (defined as having lower than a high school diploma), 30.3 % (95% CI: 17 - 42) were homeless (data available only for RI), 34.1 % (95% CI: 23 - 45) were unemployed at the time or within the year prior to the study, and 71.3 % (95% CI: 63 - 79) reported ever being imprisoned.

Table 2.

Summary of demographic and socioeconomic characteristics of participants in included studies by pattern of drug injection

	Sample size	Age	Male	Unmarried	Under-educated	Homeless	Unemployed	Ever Imprisoned
	N	Mean (95%CI)	P %, (95%CI)	P %, (95%CI)	P %, (95%CI)	P %, (95%CI)	P %, (95%CI)	P %, (95%CI)
Recent IDU	2784	34.7 (32 - 37)	95.6 (93 - 97)	55.5 (43 - 67)	63.1 (54 - 71)	30.3 (17 - 42)	40.4 (23 - 57)	75.1 (68 - 82)
Ever IDU	8090	31.8 (30 - 32)	85.5 (76 - 94)	53.3 (42 - 64)	47.2 (22 - 72)	--	38.5 (12 - 44)	63.9 (41 - 86)
Any IDU (combined above)	10874	32.6 (31 - 33)	89.9 (85 - 94)	54.5 (46 - 62)	57.1 (44- 69)	--	36.8 (24 - 49)	71.3 (63 - 79)
Never IDU	2947	31.9 (29 - 34)	78.1 (54 - 100)	51.1 (33 - 68)	44.1 (10 - 77)	--	20.2 (9 - 30)	--
Overall	13821	32.4 (31 - 33)	87.4 (82 - 92)	53.9 (47 - 60)	54.6 (42 - 66)	30.3 (17 - 42)	34.1 (23 - 45)	71.3 (63 - 79)

As shown in Figure 2, the overall pooled HCV prevalence among all injection drug users (RI and EI combined) was 45% (95% CI: 37 – 54).^{(23-27, 29-33, 35-37, 40-42, 44-47, 50, 53, 54)} The HCV prevalence among RI was 53% (95% CI: 37 – 70)^{(23-26, 32, 40, 44, 45, 53)} and in EI it was 40% (95% CI: 30 – 50).^{(27, 29-31, 33, 35-37, 41, 42, 46, 47, 50, 54)} The prevalence of HCV among NI was 8% (95% CI: 4 – 13)^{(27, 42, 46, 47, 50)} (Figure 3). Among the 24 original studies, 15 (63%) studies had a high risk of bias, 7 (29%) had a moderate risk of bias, and 2 (8%) had a low risk of bias (Table 3). After excluding 15 studies with a high risk of bias, the overall pooled HCV prevalence among all injection drug users was 53% (95% CI: 38 – 68).^{(31, 33, 35, 42, 44, 45, 47, 54, 55)} The HCV prevalence among RI and EI was 65% (95% CI: 43 – 88)^{(44, 45, 55)} and 46% (95% CI: 27 – 65).^{(31, 33, 35, 42, 47, 54)} The HCV prevalence among NI was 6% (95% CI: 3 – 9).^{(42, 47)}

Figure 2. HCV prevalence in drug users who inject.

Summary estimate of HCV infection prevalence and 95% CI among people who inject drugs, by timing of injection

Figure 3. HCV prevalence in drug users who do not inject.

Summary estimate of HCV infection prevalence and 95% CI among drug users who have never injected

Table 3.

Assessment of risk bias of studies included in the systematic review

External Validity				Internal Validity
Author & Year	Relevance of target population	Appropriateness of sampling method	Likelihood of non-response bias	Directness of data collection from subjects	Acceptability of case definition	Reliability & validity of lab tests	Consistency of data collection methods for all subjects	Appropriateness of numerator & denominator of parameters	Overall risk of bias*
Alipour 2013	Low	High	High	Low	Low	Low	Low	Low	High
Amin-Esmaeili 2012
Rahimi-Movaghar 2010	Low	High	High	Low	Low	Low	Low	Low	High
Amini 2005	High	High	High	Low	Low	Low	Low	Low	High
Eskandarieh 2013	High	High	High	Low	Low	Low	Low	Low	High
Malekinejad 2008	Low	Low	Low	Low	Low	Low	Low	Low	Low
Rahnama 2014
Norouzi 2011	Low	High	High	Low	High	High	Low	Low	High
Ramezani 2014	High	High	High	Low	Low	Low	Low	Low	High
Zamani 2007	Low	High	Low	Low	Low	Low	Low	Low	Moderate
Zamani 2010	Low	Low	Low	Low	Low	Low	Low	Low	Low
Ataei 2011	Low	High	High	Low	Low	Low	Low	Low	High
Azizi 2011	High	Low	Low	Low	Low	Low	Low	Low	Moderate
Honarvar 2013	High	High	High	Low	Low	Low	Low	Low	High
Fadaei Nobari 2012	Low	High	High	Low	Low	Low	Low	Low	High
Fadaei Nobari 2011
Imani 2008	High	High	High	Low	Low	Low	Low	Low	High
Imani 2006
Keramat 2011	High	High	High	Low	Low	Low	Low	Low	High
Kheirandish 2009	Low	High	Low	Low	Low	Low	Low	Low	Moderate
Hosseini 2010
Khodadadi-zadeh 2006	High	High	High	Low	Low	Low	Low	Low	High
Mirahmadizadeh 2009	Low	Low	High	Low	Low	Low	Low	Low	Moderate
Mir-Nasseri 2008
Mir Nasseri 2011	Low	High	Low	Low	Low	Low	Low	Low	Moderate
Mir-Nasseri 2005
Nokhodian 2012	Low	High	High	Low	Low	Low	Low	Low	High
Meshkati 2011
Rostami Jalilian 2006	Low	High	Low	Low	Low	Low	Low	Low	Moderate
Sarkari 2012	Low	High	High	Low	Low	Low	Low	Low	High
Sayad 2008	Low	Low	High	Low	Low	Low	Low	Low	Moderate
Talaie 2007	High	High	Low	Low	Low	Low	Low	Low	High

^*Low: No high-risk domains, Moderate: one high-risk domain, High: two or more high-risk domains

We also examined the pooled prevalence of HCV co-infection with HIV and HBV in all injection drug users (IDU). In total 2615 individuals were tested for both HCV and HIV while 1996 individuals were tested for HCV and HBV. Prevalence of HCV/HIV and HCV/HBV co-infection among IDU were 11% (95% CI: 5 – 16)^{(24, 27, 31-33, 40, 44, 45)} and 11% (95% CI: 2 – 20),^{(24, 27, 32, 33, 40, 45)} respectively (Figure 4).

Figure 4. HCV co-infection prevalence.

Summary estimate of HCV/HIV (top) and HCV/HBV (bottom) co-infection prevalence and 95% CI by drug use pattern

With respect to the distribution of HCV infection among IDU by geographic location, pooled estimates of HCV prevalence in Tehran, cities other than Tehran, and a mix of Tehran and other cities were 55% (95% CI: 35 – 74),^{(24-26, 31, 33, 44)} 42% (95% CI: 30 – 54),^{(27, 29, 30, 32, 36, 37, 40-42, 45-47, 50, 53, 54)} and 41% (95% CI: 37 – 46),^{(23, 35)} respectively. Further, when we looked at the distribution of infection by recruitment setting, the pooled HCV prevalence was as follows: 43% (95% CI: 17 – 69) among those recruited from drug treatment clinics,^{(25, 29, 31, 33, 40, 47, 50)} 43% (95% CI: 39 - 48) among those recruited from DIC,^{(23, 35, 37)} 48% (95% CI: 32 – 63) among those recruited from healthcare facilities,^{(27, 30, 54)} 40% (95% CI: 18 – 62) among those recruited from the community,^{(26, 36, 46)} 50% (95% CI: 22 – 78) among those recruited from the home,⁽⁴²⁾ and 52% (95% CI: 27 – 77) among those recruited from a mix of settings (Figure 5).^{(24, 32, 44, 45, 53)}

Figure 5. HCV prevalence in different cities/settings.

Summary estimate of HCV infection prevalence and 95% CI among injection drug users, stratified by city (top) and study settings (bottom)

As presented in table 4, pooled HCV prevalence was higher among IDU with a history of incarceration [58% (95% CI: 39 - 77)] as compared to those without [44% (95% CI: 20 - 68)]. HCV prevalence was also higher among those IDU with a history of tattoos [72% (95% CI: 55-88)] as compared to those without [55% (95% CI: 40 – 70)]. Further, IDU who reported sharing needles in the past had higher rates of HCV [57% (41-71)] than those who reported not sharing needles [49% (26 – 71)]. The differences in these 3 categories were not considered statistically significant.

Table 4.

Reported and pooled HCV infection prevalence & 95% confidence intervals by pattern of drug injection & risk factors

ID	Male	Female	Ever Incarcerated	Never Incarcerated	Ever Shared Needle/Syringe	Never Shared Needle/Syringe	Ever Received Tattoo	Never Received Tattoo
	N, P %, (95%CI)	N, P %, (95%CI)	N, P %, (95%CI)	N, P %, (95%CI)	N, P %, (95%CI)	N, P %, (95%CI)	N, P %, (95%CI)	N, P %, (95%CI)
Recent IDU (Pooled)	1199, 44.6 (24 - 64)	81, 43.8 (30 - 57)*	1160, 62.7 (30 - 95)	379, 35.2 (5 - 84)	820, 59.9 (35 - 84)	589, 56.0 (30 - 81)	285, 71.9 (44 - 88)	566, 60.1 (41 - 78)
Alipour 2013	226, 38 (20 - 60)	42, 36 (13 - 67)	--	--	--	--	--	--
Amin-Esmaeili 2012	859, 34 (30 - 37)	36, 44 (28 - 60)	631, 42 (38 - 46)	259, 14 (10 - 19)	566, 36 (32 - 39)	325, 32 (26 - 37)	--	--
Malekinejad 2008**	--	--	443, 86 (78 - 90)	89, 82 (39 - 100)	123, 79 (56 - 93)	76, 85 (77 - 93)	183, 94 (87 - 100)	349, 75 (69 - 83)
Zamani 2007	--	--	--	--	99, 53 (43 - 63)	103, 50 (40 - 60)	84, 58 (47 - 68)	118, 47 (38 - 56)
Zamani 2010	114, 60 (51 - 69)	3, 66 (20 - 93)	86, 59 (48 - 69)	31, 64 (47 - 81)	32, 71 (56 - 87)	85, 56 (45 - 67)	18, 83 (60 - 94)	99, 56 (46 - 66)
Ever IDU (Pooled)	1875, 34.3 (21 - 47)	86, 28.5 (19 -38)*	720, 53.4 (23 - 83)	389, 35.1 (2 - 67)	399, 53.6 (30 - 76)	775, 41.7 (1 - 81)	660, 64.1 (50 - 77)	462, 48.3 (27 - 69)
Honarvar 2013	230, 40 (33 - 46)	4, 50 (1 - 98)	--	--	--	--	--	--
Imani - 2008	131, 11 (6 - 16)	2, 0 (0 - 0)	47, 17 (6 - 27)	86, 8 (2 - 13)	26, 30 (13 - 48)	107, 6 (1 - 11)	--	--
Kheirandish 2009	--	--	342, 83 (79 - 87)	112, 69 (61 - 78)	58, 84 (72 - 92)	396, 79 (75 - 83)	125, 66 (41-86)	--
Mirahmadizadeh 2009	883, 44 (41 - 47)	48, 22 (11 - 34)	--	--	--	--	--	--
Mir-Nasseri 2008	128, 28 (20 - 35)	4, 25 (4 - 69)	--	--	60, 41 (29 - 54)	--	248, 71 (66 - 77)	220, 59 (52 - 65)
Nokhodian 2012	503, 47 (43 - 51)	28, 39 (21 - 57)	331, 58 (53 - 63)	191, 28 (21 - 34)	130, 76 (68 - 83)	263, 46 (40 - 52)	287, 55 (49 - 60)	242, 37 (31 - 43)
Sayad 2008	--	--	--	--	3, 100 (100 - 100)	9, 33 (2 - 64)	--	--
Azizi 2011	--	--	--	--	122, 32 (24 - 41)	--	--	--
Overall	3074, 37.9 (28 - 46)	167, 33.6 (25 - 41)*	1880, 58.1 (39 - 77)	768, 44.2 (20 - 68)	1219, 56.5 (41 - 71)	1364, 49.1 (26 - 71)	945, 71.5 (55 - 88)	1028, 55.3 (40 - 70)

DISCUSSION

PWID are the main group affected by HCV infection worldwide.⁽⁵⁶⁾ This study examined the prevalence of HCV among drug users with and without a drug injection history. Our results showed a high prevalence of HCV infection among PWID in Iran which is consistent with world estimates of 52.0% in this population,⁽⁶⁾ but still lower than certain other countries (e.g., Bulgaria, Estonia).⁽¹⁾ Hepatitis C infection can lead to serious and deadly liver diseases such as cirrhosis and hepatocellular carcinoma. The burden of hepatitis C attributed to injection drug use is high and was estimated to be 502,000 (286,000 -891,000) disability-adjusted life years globally in 2010.⁽⁵⁷⁾ Given that HCV prevalence in Iran is consistent with world estimates, HCV likely contributes to a high burden of disease in Iran. Therefore, special emphasis must be placed on the control of hepatitis C infection among PWID in Iran.

In 2002, Iran implemented harm reduction interventions including NSP and OST primarily in response to HIV epidemics among PWID. These programs have been scaled up at the national level since 2007.⁽¹⁹⁾ Although there is ample evidence on the effectiveness of NSP and OST on the reduction of self-reported injecting risk behaviors,^(58-60) evidence regarding the effectiveness of these programs in reducing HCV incidence is inconclusive.^{(58, 59)} HCV infection is transmitted more efficiently than HIV.^(61-66) Modeling studies show that an individual who shares needles and syringes is at greatest risk for contracting hepatitis C during the first year.^{(67, 68)} In addition, the risk of becoming infected increases with injection duration.^{(69, 70)} In the Amsterdam Addiction Cohort study, the incidence of HCV infection among PWID who received both OST and high coverage NSP (i.e., sufficient number of syringes) was approximately one third lower than those who received either OST or NSP alone.⁽⁶⁰⁾ These studies suggest that a combination of harm reduction interventions need to reach PWID early on to be effective in reducing the risk of HCV transmission. This is especially applicable to Iran since the overall coverage of NSP and OST programs have remained insufficient among PWID^{(8, 71)} and many harm reduction facilities provide only one or the other.

In this study, we have also provided weighted pooled prevalence (11.3%) on HCV and HIV co-infection among PWID in Iran. A recent systematic review of 22 European countries reported a median co-infection rate of 3.9%.⁽⁷⁰⁾ HIV co-infection accelerates disease progression in chronic hepatitis C and reduces the response rate to interferon-based therapy.⁽⁷²⁾ Further, there is a higher risk of hepatotoxicity among HIV-infected patients treated with antiretroviral therapy (ART) who are co-infected with hepatitis C infection.^(73-75) Direct-acting antivirals (DAA) are equally effective in HCV patients with and without HIV co-infection and may be a better treatment choice for this population.⁽⁷⁶⁾ However the cost of treatment limits their availably in Iran. We were unable to provide pooled prevalence of HCV and HIV co-infection among drug users who had never injected drugs, because only one study reported this data on NI.

In our sample, non-injection drug users had a higher prevalence of Hepatitis C (8.2%) than the general population (<1%).⁽²⁰⁾ Some studies on hepatitis C infection among individuals with no reported history of blood transfusion and injection drug-use have proposed sexual intercourse as the possible mode of hepatitis C transmission.^{(77, 78)} We suspect that in this review, a high degree of mixing or bridging between IDUs and non-IDUs may have resulted in the high HCV prevalence. The higher than expected HCV infection among non-injection drug users may also be due to a multitude of other risk factors such as unsafe tattoo procedures, body piercings, cocaine snorting, crack-cocaine use, herpes simplex virus (HSV)-2 infection, gonorrhea, HIV infection, and high-risk sexual activity.^(78-83) Hepatitis C infection among non-injecting drug users is likely also influenced by underreporting of injection practices, as a result of the stigma attached to injection drug use, which leads to misclassification of drug users.^{(84, 85)} Further studies are warranted to determine risk factors for hepatitis C infection among non-injecting drug users. Such studies should also focus on the extent to which the stigma associated with injection drug use may deter PWID from reporting injection behaviors.

It should be noted that studies that assessed HCV prevalence in incarcerated drug users, were excluded from this review. HCV prevalence in this subpopulation might be higher than those out of prison. Nonetheless, more than 70% of drug users included in this review had a history of imprisonment in their lifetime. Although HCV prevalence was higher in those with a history of incarceration, the difference was insignificant. The Prison Organization in Iran launched small-scale programs to provide sterile needles and syringes to prisoners who inject drugs in a limited number of prisons, but these programs were not scaled.⁽¹⁹⁾ Another systematic review by our team is under way to determine the prevalence of HCV among incarcerated populations in Iran.

Sharing of injection equipment is the primary cause of HCV transmission,⁽²⁾ however, we did not find any correlation between a self-reported history of needle sharing and HCV prevalence. Because many of the included studies in our review did not report information about sharing of injection equipment other than needles, we were not able to assess this correlation. It is noteworthy that a recent meta-analysis of the factors correlated with HCV transmission in China showed no significant difference between those who shared injection equipment and those who did not.⁽⁸⁶⁾

Studies among Iranian PWID show that testing for blood-borne infectious diseases is low in this population.^{(53, 71)} Since there are multiple studies supporting successful treatment of HCV among PWID,^{(87, 88)} easy access to testing services could be an initial step towards meeting the need for hepatitis C infection treatment. In Iran, there is no publicly funded program for hepatitis C infection treatment. Besides, insurance coverage for antiviral medications and needed tests are very limited. These issues negatively affect access to antiviral treatment for affected populations, particularly people who use drugs in Iran. Treatments may also have a positive impact on preventing hepatitis C transmission. Modeling studies suggest new generation antiviral therapies could be a cost-effective and efficacious method of preventing hepatitis C transmission among affected individuals while they are in treatment and once a sustained virologic response has been achieved.^{(89, 90)}

Although studies were heterogeneous with respect to the risk of bias, the overall quality of evidence is low with only 2 out of the 24 studies qualifying as low risk of bias studies. Nevertheless, the estimated pooled prevalence of HCV among all sub populations of drug users (RI+EI, RI only, EI only, and NI) remained relatively stable (i.e., 95% confidence intervals overlapped significantly) after the 15 studies that were rated as high risk of bias were excluded from the meta-analysis. Although the prevalence remained relatively stable, this change resulted in a wider 95% CI for estimates as a result of a decrease in the included number of subjects in the model. For all drug-injecting sub-populations (RI+EI, RI, and EI), the distribution of the HCV prevalence shifted to the right (i.e., the prevalence increased), while among NI, the distribution shifted to the left (the prevalence decreased). In addition to heterogeneity with regard to the risk of bias, the included studies were also heterogeneous with respect to study setting and the characteristics of the drug using sub-populations. The wide confidence intervals around the pooled estimates generated by the random effect model reflect the uncertainty around these estimates.

Given our findings of high HCV prevalence in drug users, providing an appropriate response to hepatitis C infection within this population in Iran is warranted. Such a response would likely require urgent implementation of a multi-pronged approach consisting of a combination of preventive measures, testing services, and antiviral treatment programs among drugs users, particularly PWID. Further studies are needed to produce evidence based on target coverage and combination of harm reduction interventions to reduce hepatitis C transmission among Iranian PWID.

Highlights.

• Our search yielded 24 original studies on HCV prevalence in drug users in Iran.

• Injection drug users had a higher HCV prevalence than non-injection drug users.

• Pooled HCV prevalence in recent and ever injectors were 53% and 40%, respectively.

• Approximately 11% of injection drug users with HCV had HBV or HIV co-infection.