Hindawi
Interdisciplinary Perspectives on Infectious Diseases
Volume 2022, Article ID 2544481, 12 pages
https://doi.org/10.1155/2022/2544481
Research Article
Behavioural Risk for HIV, Hepatitis B, and Hepatitis C
Infections among a Population of Drug Users and Injectors across
Four Regions in Ghana
Chris Guure ,1 Sharren Margaret Obiri-Yeboah Laryea,1 Samuel Dery,1
Carlota Baptista da Silva,2 Comfort Asamoah-Adu,3 Stephen Ayisi-Addo,4
Maria-Goretti Loglo,5 Adamu Mohammed,6 and Kwasi Torpey7
1Department of Biostatistics, School of Public Health, University of Ghana, Legon, Accra, Ghana
2International Consultant, Harm Reduction and Key Population Expert, Lisbon, Portugal
3West Africa Program to Combat AIDS, Accra, Ghana
4National AIDS/STI Control Programme, Ghana Health Service, Accra, Ghana
5International Drug Policy Consortium, East Legon, Accra, Ghana
6West Africa Behavioural Health Addictions and Recovery Management, Accra, Ghana
7Department of Population Family and Reproductive Health School of Public Health, University of Ghana, Legon, Accra, Ghana
Correspondence should be addressed to Chris Guure; cbguure@ug.edu.gh
Received 25 June 2022; Accepted 13 August 2022; Published 1 September 2022
Academic Editor: Massimiliano Lanzafame
Copyright © 2022 Chris Guure et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background. Blood borne infections such as HIV, Hepatitis B (HBV), and Hepatitis C (HCV) are of great importance to
governments and their implementing partners, especially among people who use drugs (PWUD) and people who inject drugs
(PWID). Prevalence and determinants of HIV, HBV, and HCV among PWUD and PWID in Ghana are not well established, the
signi‹cance of this study. Method. is assessment was a cross-sectional study implemented via the respondent driven sampling
approach. A team of community advisory boards that comprised former users, current users, and civil society organizations were
constituted to help in the implementation of the study. e study was conducted in four regions in Ghana. e assessment was
based on a representation of populations of PWID and PWUD from the four regions. EŽorts were made by the team to ensure
adequate representation of women where feasible. A quantitative questionnaire was developed and used to obtain information on
the respondents’ sociodemographics, sexual behavior, substance use, and biological characteristics. e prevalence of HIV, HBV,
and HCV among PWID and PWUD was determined using blood samples. First response and oral quick test for con‹rmation of
HIV positivity were carried out, while SD bioline was used to test for the presence of HBV and HBC. Data were analyzed using the
Bayesian generalized linear model via the binomial family of distributions under the logit link function with weak Cauchy and
Normal distribution as prior. Results. A total of 323 PWUD and PWID participants were interviewed across four regions of
Ghana. e overall median age of the respondents was 36 (28, 43) years. e prevalence of HIV, HBV, and HCV infection in the
study was 2.5%, 4.6%, and 5.9%, respectively.e prevalence of HIV, HBV, and HCV among drug users was 2.5% (95% CI: 0.7%–
4.2%), 4.1% (95% CI: 1.8%–6.2%), and 6.7% (95% CI: 3.9%–9.4%), respectively. Most drug injectors and users started using and
injecting drugs at ages less than 20 years and between 20 and 29 years, respectively. Drug users who identi‹ed themselves as part of
the general population were 66% less likely to be tested HIV positive (POR 0.34, CrI: 0.12–0.81) compared to sex workers. Part
time employment respondents had ‹vefold odds (POR 5.50, CrI: 1.20–16.16) of being HBV positive as against full-time
employment. Conclusion. Most of the injectors and users started drugs at an early age. Drug users and injectors are at higher risk of
these infections because of associated risky sexual behaviors and risky injection practices. Harm reduction programs to help
addicts who are willing to quit the practice are recommended.
2 Interdisciplinary Perspectives on Infectious Diseases
1. Background overexposure to drug injections being performed by others,
leading to their altered views and reducedmoral standards of
Blood-borne infections such as HIV, Hepatitis B, and C are the inappropriate nature of drug injection [19].
of great significance to public health experts [1]. (ese Despite the perceived benefits of drug use and injection
diseases have rapidly gained grounds among drug users and by those who practice it, it poses a great deal of risk and
drug injectors, increasing their contribution to the global effect, not only to those who engage in them but also to the
burden of these diseases [2–6]). Globally, 11,180,000 people communities in which they reside. Such effects include
inject drugs, and in the year 2018, there was a 30% increase in motor accidents, violence, health risks, toxicity and poi-
drug users from the previous decade to an estimated 270 soning from excessive doses, financial constraints in seeking
million. As of 2020, more than 35 million drug users ex- healthcare to managing adverse health outcomes, effects on
perienced substance use disorders. With the advent of the social norms and values, reduced effectiveness and efficiency
COVID-19 pandemic, fallouts in the global economy have at work, increased crime rates, as well as deaths [20, 21].
led to joblessness, contributing to the increased numbers of It has been advocated that to facilitate the prevention or
drug users [6, 7]. Moreover, the COVID-19 impact on in- reduction in the spread of HIV, HBV, and HCV infection
ternational commerce and drug scarcity has led to the in- from drug use and injection, harm reduction programs,
creased cost of drugs and loss of drug purity, hence, the including needle and syringes, opium substitution therapy,
increase in more detrimental drug use patterns such as the and vaccination programs should be encouraged as well as
use of synthetic drugs and drug injection [7]. Among drug the effects of sharing injection paraphernalia [22, 23]. (e
injectors worldwide, the prevalence of HIV, hepatitis B, and objective of this study was to provide an overview of the
C in the year 2021 were 12%, 8.7%, and 50%, respectively, prevalence of HIV, HCV, and HBV and their corresponding
with the ages of drug injectors spanning from 12 to 65 years. determinants among a population of drug users and in-
Other studies also suggest a significantly higher prevalence jectors in Ghana.
of HIV and hepatitis C among drug users compared to the
general population, although injection drug users are at
more risk of contracting these blood-borne infections, in- 2. Methods
cluding hepatitis B, as opposed to drug users [8, 9]. (is is 2.1. Stakeholders’ andConsultativeMeetings. (e study team
usually because of the high communal use of injection ac- organized meetings with relevant stakeholders across four
cessories such as cotton, cookers, water, and needles [10, 11]. (Greater Accra, Ashanti, Western, and Northern) selected
Among noninjecting drug users, the risk of HIV, hepatitis B, regions and constituted a committee advisory group to help
and C is mainly due to the link between drug use and risky in the successful implementation of the study. From these
sexual behaviour [12]. consultative meetings, communities were selected from each
Africa is home to about 950,000 drug injectors. Out of of the regions and included in the assessment.
this number, HIV, hepatitis B, and C infected drug injectors
were 10.9%, 6.8%, and 19.9% of the population of drug
injectors [7]. In Ghana, most drug users are of a low so- 2.2. Study Design, Data Collection, and Sample Size
cioeconomic class and usually combine drugs such as Determination. (is assessment was a cross-sectional sur-
marijuana, cocaine, and heroin (which are normally smoked vey of PWID and PWUD from four (4) regions in Ghana,
than injected) [13]. In 2013, it was found that the prevalence ensuring adequate representation of the diverse categories of
of HIV among drug injectors (4%) in Ghana was found to be drug users and injectors population across the regions.
lower than the global figure (10%) in 2013. (e few who Communities within regions where the study was carried
injected drugs were shunned by the local community of drug out were selected purposively with the help of the com-
users as it was seen as a foreign practice. It is speculated that munity advisory group. A quantitative questionnaire was
drug injectors acquired the habit when they traveled outside used to solicit information from the respondents and in-
the country [13]. A 2021 study conducted in Ghana, how- cluded questions on sociodemographic, sexual behaviour,
ever, indicates a recent surge in injection drug users within substance use, and biological characteristics. Furthermore,
the country, with subsequent increases in the prevalence of the prevalence of HIV, HBV, and HCV among PWID and
HIV, hepatitis B, and C [14]. PWUD was determined using blood samples. Before the
People use and inject drugs for many reasons, and in- tests were conducted, participants were first taken through
terestingly, one drug could be used by different people for counseling about the relevance or importance of the test and
several purposes [15]. Inferring from Cox & Klinger, 1988, the potential implications if the results of the test were
individuals choose knowingly or unknowingly based on positive. After counseling, blood samples (30uL) were taken
their expected perceived benefits or harm, whether they will for each of the tests. For the HIV test, the Laboratory
engage in substance use or not [16]. In general, people use Technicians used three different types of tests, that is, first
drugs to boost their energy, to help them deal with rest- response followed by oral quick and then SD bioline as a
lessness and sluggishness, to aid their feeling of acceptability confirmation test of positivity. For both hepatitis B and C,
among their peers, and also to deal with the loss [17, 18]. they used SD bioline. All those who were confirmed positive
Some of the reasons for drug use include homelessness, for any of the three viruses were again counseled and re-
unemployment, peer pressure, working in close contact with ferred to a clinic for treatment if he/she was already not
drugs at their place of work, and familiarity from enrolled. All data collectors were trained in data collection
Interdisciplinary Perspectives on Infectious Diseases 3
procedures for conducting quantitative data, maintaining which was computed via the Laplace-Metropolis approxi-
confidentiality, and appropriately handling and storage of mation and the posterior probabilities. (e prior that was
data. (e modified Cochran’s formula that incorporates the used for the prevalence of HIV as an outcome were Gaussian
design effect, stratification, and nonresponse rate were used (0, 5) for the logistic distribution constant and Gaussian (0,
to calculate the sample size for the study.(e total number of 0.5) for the model coefficients. (ose for the prevalence of
participants (sample size) required for the study was 303, HCV were Gaussian (0, 10) for constant and Gaussian (0,
based on a two-tail hypothesis with an alpha level of 5%. 2.5) for the coefficient, while the prevalence of HCV was
Cauchy (0, 0.5) and Cauchy (0, 2.5). During the running of
2.3. Sampling Approach (Respondent Driven Sampling). the model, 2 chains were specified with 12500 simulations, a
Respondent-driven sampling (RDS) was used to enroll the thinning of 10, and a burn-in of 2500. Convergence diag-
PWUD and PWID population in the study. In using the RDS nostics were carried out using trace plots, autocorrelation
approach, the study team, via key informants and the plots, histograms, as well as the Gelman–Rubin convergence
Community Advisory Board members, identified seeds, and rule (Rc< 1.1). All analyses were adjusted for weight. Sta-
these seeds were recruited or selected from the target tistical analyses were completed using StataCorp. 2021. Stata
population. (e seeds that were selected were interviewed, 17 Base Reference Manual (College Station, TX: Stata Press).
and they formed wave zero (0) of the sample selection. (e
seeds were recruited, taking into cognizance PWUD, PWID, 3. Results
and female respondents. All selected seeds were given three (e study engaged drug users and injectors (323) from the
sets of coupons. (ey were trained at the center on how to Greater Accra, Ashanti, Western, and Northern regions of
administer the coupons to persons within their social net- Ghana. (e median age of the participants was 37.0 (IQR:
work who were either PWIDs or PWUDs and then refer 28–44) years. (e median ages at which respondents started
them to the study location. (is recruitment approach then to use and inject drugs were 20.0 (IQR: 18.0–26.0) years and
turned into “waves.” (e first set of participants who were 22.0 (IQR 18.0–30.0) years, respectively. (e percentages of
referred to the study staff then became the first recruits. males and females in the study were 86.1% and 13.9%, re-
(ese first recruits were also trained, and three coupons were spectively. Most of the respondents were JHS leavers
given to each and asked to recruit their peers. Each cycle of (39.7%), followed by those who had at least a Senior Sec-
recruitment and participation added an additional sampling ondary education or higher qualification, with the least
wave. (ose who successfully participated in the study were (2.3%) of participants who do not have any form of formal
paid for transportation. (e transportation cost was nec- education. Participants who were single and never married
essary because all those who were recruited had traveled to were 57.0%, and those who had either separated, divorced, or
the study venue to participate. All referred participants were widowed were 15.5%, with the rest being married. (irty-
screened for eligibility. four percent lived with their sexual partners, and only 0.7%
of participants were men who slept with men (Table 1).
2.4. Data Analysis. Analysis was conducted using Stata
version 17 and RDSAT version 7.1.46 software. RDSAT 3.1. Prevalence of HIV, HBV, and HCV among Users and
software was used to calculate individual data weights. Injectors. (e overall prevalence of HIV, HBV, and HCV
Analysis of the quantitative data was done descriptively and infection in the study was 2.5%, 4.6%, and 5.9%, respectively.
presented in the form of medians and proportions (per- (e prevalence of HIV, HBV, and HCV among drug users
centages). Inferential analysis was carried out using a was 2.5% (95% CI: 0.7%–4.2%), 4.1% (95% CI: 1.8%–6.2%)
Bayesian generalized linear model via the binomial family of and 6.7% (95% CI: 3.9%–9.4%) respectively. (ere was no
distributions under the logit link function between the statistically significant difference between the prevalence of
outcomes, prevalence of HIV, hepatitis B, and hepatitis C, HIV and HBV among noninjectors compared to injectors.
and the predictors; socioeconomic, demographic, and sexual For HCV, however, there was a statistically significant in-
behaviors. All variables that showed a significant relation- creased prevalence among noninjectors versus injectors
ship with the outcomes of interest and variables that have 6.7% and 0.1% (p� 0.002), respectively. By their gender, the
been reported to be significant predictors of their corre- prevalence of HIV was highest among females (12.3%) as
sponding outcomes in the literature were entered and used opposed to males (0.5%). Age was associated (p� 0.031) with
to obtain the adjusted posterior odds ratios (OR) and their the prevalence of the hepatitis B virus. We observed that
credible intervals (CrIs). All regression model parameters 11.9% of participants had both HBV and HCV, but there
were assigned relatively informative priors following the were no coinfections among HIV, HBV, and HCV.
normal and Cauchy distributions with different parameter
values. Several sensitivity analyses via specifications (six
models) of different priors were established and fitted for 3.2. Substance Use. Most drug users started using drugs
each outcome and its corresponding predictor variables. (e between the ages of 20 and 29 years (37.8%), 35.5% started
six models for each outcome based on the assessment of the using drugs before the age of 20 years. Respondents who
sensitivity of the prior were compared and the best model started injecting drugs at an age of less than 20 years were
was selected for final analysis using Bayesian deviance in- (29.6%) years (Table 1). Approximately, 30% of drug users
formation criteria, Bayes factor, the marginal likelihood, used their drugs three times a day and 53.9% did so 4 or
4 Interdisciplinary Perspectives on Infectious Diseases
Table 1: Distribution of respondents’ (drug users and injectors) characteristics according to their HIV, HCV, and HBV status.
Unweighted Weighted HIV HCV HBV
323 (100) n(%) 323 (100) n(%) n(%) n(%) n(%)
Factor % % %
Age of participant, median (IQR) 36 (28, 43) 37 (28, 44) 39 (28, 43) 44 (34, 54) 40 (32, 50)
Age group of participants
19–29 years 91 (28.2) 90 (27.7) 30.3 17.0 13.7
30–39 years 112 (34.7) 113 (35.1) 24.5 29.0 32.7
40–49 years 75 (23.2) 71 (22.1) 45.3 21.3 21.6
>49 years 42 (13.0) 47 (14.6) 0.0 32.7 25.5
Nonresponse 3 (0.9) 2 (0.5) 0.0 0.0 6.5
Highest level of education
Never attended school 7 (2.2) 7 (2.3) 14.0 5.2 9.8
Primary 75 (23.2) 81 (25.0) 15.1 39.4 23.5
JHS/middle school 132 (40.9) 128 (39.7) 29.1 31.0 34.0
SHS/SSS/Voc./Tech. 91 (28.2) 96 (29.7) 41.8 18.4 21.6
Tertiary 18 (5.6) 11 (3.4) 0.0 5 .9 11.1
Employment status
Employed full-time 125 (38.7) 116 (36.0) 36.1 49.8 13.7
Employed part-time 64 (19.8) 78 (24.1) 30.1 23.6 55.0
Full-time student 3 (0.9) 2 (0.6) 0.0 0.0 0.0
Retired 2 (0.6) 2 (0.7) 0.0 0.0 0.0
Unemployed 129 (39.9) 125 (38.6) 33.8 26.6 31.4
Marital status
Single, never married 196 (60.7) 184 (57.0) 78.0 62.5 52.3
Married 85 (26.3) 89 (27.4) 3.5 22.6 21.6
Separated/divorced 17 (5.3) 24 (7.5) 18.6 15.0 19.6
Widowed 25 (7.7) 26 (8.0) 0.0 0.0 6.5
Currently living with sexual partner
Yes 118 (36.5) 110 (34.1) 32.6 15.6 39.2
No 205 (63.5) 213 (65.9) 67.4 84.4 60.8
Monthly income
Less than 200 GHC 70 (21.7) 66 (20.3) 36.1 11.2 27.5
200 to 500 GHC 78 (24.2) 77 (23.8) 39.4 41.7 29.4
500 to 1000 GHC 79 (24.5) 84 (26.0) 0.0 28.6 7.8
1000 to 2000 GHC 59 (18.3) 60 (18.7) 17.5 18.6 11.8
Above 2000 GHC 23 (7.1) 21 (6.5) 7.0 0.0 15.7
Don’t know 6 (1.9) 8 (2.5) 0.0 0.0 7.8
Refuse to answer 8 (2.5) 7 (2.2) 0.0 0.0 0.0
How respondents identify self
SW 15 (4.6) 13 (3.9) 29.1 0.0 0.0
MSM 2 (0.6) 2 (0.7) 0.0 0.0 0.0
General population 303 (93.8) 305(94.4) 70.9 100.0 100.0
Refuse to answer 3 (0.9) 3 (1.1) 0.0 0.00 0.0
Age at start of using of drugs, median (IQR) 20 (18, 25) 20 (18, 26) 16, 28 22, 33 17, 24
Age group at start of using drugs
<15 years 14 (4.3) 14 (4.4) 0.0 0.0 0.0
15–19 years 107 (33.1) 100 (31.1) 37.3 17.9 40.0
20–24 years 82 (25.4) 83 (25.8) 15.1 21.1 13.7
25–29 years 40 (12.4) 39 (12.0) 30.1 26.8 9.8
>30 years 51 (15.8) 55 (16.9) 17.5 28.3 7.7
Non-response 29 (9.0) 32 (9.7) 0.0 6.0 38.6
Age at start of injecting drugs, median (IQR) 23.5 (19, 30) 22 (18, 30) 16, 16 20, 20 20, 35
Age group at start of injecting drugs
<15 years 3 (5.8) 3 (5.6) 0.0 0.0 0.0
15–19 years 12 (23.1) 12 (23.9) 100.0 0.0 0.0
20–24 years 12 (23.1) 13 (25.0) 0.0 100.0 40.0
25–29 years 11 (21.2) 9 (16.6) 0.0 0.0 0.0
>30 years 14 (26.9) 15 (28.9) 0.0 0.0 50.0
Interdisciplinary Perspectives on Infectious Diseases 5
Table 1: Continued.
Unweighted Weighted HIV HCV HBV
323 (100) n(%) 323 (100) n(%) n(%) n(%) n(%)
Regions
Greater accra 108 (33.4) 134 (41.5) 37.1 94.1 41.2
Ashanti 90 (27.9) 76 (23.5) 45.4 0.0 16.3
Western 86 (26.6) 93 (28.8) 17.47 6.0 39.2
Northern 39 (12.1) 20 (6.1) 00.00 0.0 3.3
more times per day. About 91% and 70.9% of the respon- odds (70%) among respondents who have completed Junior
dents had, respectively, used and injected drugs within the High or Middle school as against those who never attended
last 7 days of the study (Table 2). school of being infected with HBV (POR� 0.30, CrI:
Of all respondents, 14.0% were drug injectors and 2.7% 0.07–0.84). For HBV infection, a fivefold higher
had used or injected drugs while in prison. Majority (82.1%) (POR� 5.50, CrI: 1.20–16.16) statistically significant rela-
of drug injectors were introduced to injecting drugs by their tionship was observed among respondents who are
friends and acquaintances. Respondents who engaged in employed on a part-time base compared to those employed
both “snorting, inhaling or swallowing” and “smoking” the full time and participants who operate within the Ashanti
drugs were 16.0% (p< 0.001) , and those who engaged in region (POR� 0.16, CrI: 0.01–0.57) as against their Greater
both “smoking” and “injecting” the drugs were 7.7% Accra counterparts, Table 5.
(p< 0.001) (Table 3).
4. Discussion
3.3. Sources of Substances Used by Users and Injectors.
Drug injectors in the study sourced their syringes mainly from Given the change in global and national priorities following
“pharmacy or chemical shops or stores” (57.4%) and “phar- the onset of the Coronavirus disease (COVID-19), pandemic
macy workers or drug vendors” (20.7%). More than 69.0% of attention has been duly shifted from already existing issues
drug injectors reused their needles and the main reasons were to the imminent matter at hand [24,25]. Among such de-
because of their perceived high cost (29.9%) and the difficulty ferred issues is that morbidities such as HIV, HBV, andHCV
in accessing needles (26.9%). A large proportion of injectors existing among drug users and injectors [26–28]. Drug use
(67.4%) never shared needles with another person. However, and injection and their consequences on health have been an
12.7% shared their needles half of the time, and 7.8% shared issue of public health concern for a long time [29,30]. (is
their needles very frequently (Table 4). study successfully engaged PWUD and PWID, who willingly
and effectively contributed to the findings through their
responses and referrals. (is is the first study to be con-
3.4.WomenWhoUse and InjectDrugs. More than half of the ducted in four regions across the three ecological zones to
women in the study, 62.2% (28/45), were less than 30 years. examine the prevalence and determinants of HIV, HBV, and
A higher percentage of women were single (69.9% (31/45)) HCV among PWUD and PWID in Ghana.
and separated (20.1% (9/45)). More than 90.0% (42/45) of Most of the respondents in this study were males.
female drug users had at least primary education, and 62.2% However, recent studies suggested ever-increasing numbers
(28/45) were unemployed. Only 2.6% (1/45) of women in the of female drug users, thus closing the gender gap between
study injected a drug (heroin), but 54.7% (25/45) used two or male and female drug users and injectors [31,32]. According
more drugs together (Table 1). Sixty-six percent (30/45) of to Strashny, there was a significantly higher proportion of
females in the study lived with a sexual partner, 45.4% (20/ males than females engaged in substance use within early
45) had ever received or given money, goods, or gifts in adolescence compared to the almost similar proportion of
exchange for sex, and 28.9% (13/45) had ever received or male to female ratio after 24 years of age [32].(ere is a need
given drugs in exchange for sex. About 22% (10/45) had for more attention to be given to gender differences related
suffered physical or sexual violence in the last 6 months. to the dynamics and effects of substance use, given the
increasing participation of women [32–34].
3.5. Factors InfluencingHIV,HBV,andHCVInfection. In the Most drug users and injectors were initiated into practice
adjusted model, respondents aged 40 years and above have by their friends, acquaintances, and relatives, which is similar
52% lower posterior odds (POR� 0.48, CrI: 0.18–0.98) of to other findings [35]. Commonly used drugs by first-time
being infected with HIV when compared to respondents in drug users in this study includedmarijuana, crack, and heroin.
the age group of 19–29 years. Being a Junior High or Middle Findings available suggest similar drugs in addition to
School graduate significantly protected the respondents methamphetamine, tobacco, cannabis, and others [31, 32, 36].
(59%) from being HIV infected (POR� 0.41, CrI: 0.14–0.97). It was interesting to note that most drug users and injectors
Belonging to the general population, compared to being a engaged in the practice at least once daily, although some
sex worker, has a statistically significant negative relation- respondents went as far as four or more times in a day. (is is
ship (66%) with being tested HIV positive or infected similar to other findings suggesting that users and injectors use
(POR� 0.34, CrI: 0.12–0.81). (ere were lower posterior and inject more drugs on a daily basis [31, 37, 38].
6 Interdisciplinary Perspectives on Infectious Diseases
Table 2: Distribution of respondents’ who use drugs for HIV, hepatitis B, and C infection.
Unweighted Weighted HIV HCV HBV
n (%) n (%) n(%) n (%) n (%)
Factor 323 (100) 323 (100) 8 (100) 19 (100.0) 15(100.0)
Age group at start of using drugs
<15 years 14 (4.3) 14 (4.4) 0 0 0
15–19 years 107 (33.1) 100 (31.1) 37.28 17.89 33.99
20–24 years 82 (25.4) 83 (25.8) 15.14 21.11 13.73
25–29 years 40 (12.4) 38 (12.0) 30.11 26.78 9.8
>30 years 51 (15.8) 54 (16.9) 17.47 28.27 3.92
Drug used at first time(M)
Cocaine 27 (8.4) 22 (7.0) 29.12 0 0
Crack 33 (10.2) 38 (11.9) 38.44 28.27 17.65
Heroin 44 (13.6) 56 (17.4) 0 19.84 3.92
Marijuana 158 (48.9) 155 (48.2) 32.44 32.55 54.25
Campucheas (heroin mixed with marijuana 1 (0.3) 1 (0.3) 0 0 6.54
Cocktail (marijuana + heroin) 7 (2.2) 7 (2.1) 0 13.39 0
Tramadol 25 (7.7) 13 (4.1) 0 0 0
Alcohol 2 (0.6) 2 (0.9) 0 0 0
Cigarette 3 (0.9) 3 (1.0) 0 0 0
Prescription drugs 2 (0.6) 1 (0.5) 0 0 0
Refused to answer 21 (6.5) 21 (6.7) 0 5.95 17.65
Ever changed from one drug to the other
Yes 246 (76.2) 239 (74.2) 51.08 58.34 82.35
No 56 (17.3) 61 (19.2) 48.92 35.71 0
Nonresponse 21 (6.5) 21 (6.7) 0 5.95 17.65
What did it change to?
Cocaine 76 (30.9) 88 (35.8) 31.93 15.79 34.13
Crack 57 (23.2) 52 (21.5) 0 0 0
Heroin 64 (26.0) 71 (29.2) 45.26 84.21 57.14
Marijuana 10 (4.1) 9 (3.9) 0 0 0
Cocktail 3 (1.2) 2 (0.6) 0 0 0
Crystal meth/methamphetamine 6 (2.4) 3 (1.2) 0 0 4.76
Tramadol 18 (7.3) 13 (5.2) 22.81 0 1.59
Pethidine 3 (1.2) 2 (0.8) 0 0 2.38
Opiates 3 (1.2) 1 (0.4) 0 0 0
Prescription drugs 6 (2.4) 4 (1.5) 0 0 0
Last time drug was used
Within the last 7 days 299 (92.6) 295 (91.5) 100 94.05 100
More than 7 days to 1 month 3 (0.9) 2 (0.6) 0 0 0
More than 1 month up to 6 months 4 (1.2) 4 (1.1) 0 0 0
More than 6 up and to 12 months 1 (0.3) 1 (0.3) 0 0 0
More than 12 months 16 (5.0) 21 (6.5) 0 5.95 0
Number of times per day drug is used 8 (2.7) 5 (1.6) 0 0 0
1 time/day 39 (12.9) 43 (14.2) 13.98 30.06 18.25
2 times/day 92 (30.5) 92 (30.3) 8.15 48.81 32.54
3 times/day 54 (17.9) 53 (17.4) 31.45 17.18 7.94
4+ times/day
>4 times/day 109 (36.1) 110 (36.5) 46.42 3.95 41.27
Commonly use two or more drugs together
No 214 (66.3) 209 (64.7) 63.89 73.22 53.59
Yes 80 (24.8) 83 (25.8) 36.11 20.83 28.76
No response 29 (9.0) 31 (9.5) 0 5.95 17.65
Most of the study participants never shared their in- needles. Other reasons include unavailability at the time of
jection needles or syringes. However, they reused their own injection, peer pressure, and difficulty to walk about due to
needles after they were sourced from pharmacies or drug police disturbances [29].
dealers. (e majority of drug injectors (93.0% and 62.0%) Women who used and injected drugs in the study were
hardly shared their needles although they mostly reused mostly single and educated but unemployed.(is is consistent
them [35, 38–40].(e reuse of needles may be because of the with already existing literature, where it is stated that only
inability of injectors to either purchase or have access to 22.8% of female drug users were in some form of full or part-
Interdisciplinary Perspectives on Infectious Diseases 7
Table 3: Unweighted and weighted characteristics of respondents by variable type according to people who inject drugs.
Unweighted Weighted
n (%) n (%)
Factor 52 (100) 52 (100)
Age group at start of injecting drugs
<15 years 12 (23.1) 3 (5.6)
15–19 years 12 (23.1) 12 (23.9)
20–24 years 11 (21.2) 13 (25.0)
25–29 years 14 (26.9) 9 (16.6)
>30 years 12 (23.1) 15 (28.9)
Person who introduced injecting
A relative or family member 3 (5.9) 4 (8.3)
A person you use drugs with 4 (7.8) 3 (5.7)
A friend/an acquaintance 42 (82.4) 42 (82.1)
A stranger 1 (2.0) 1 (2.6)
Others 1 (2.0) 1 (1.3)
Drug injected at first time(M)
Cocaine 22 (42.3) 27 (51.1)
Crack 9 (17.3) 5 (10.1)
Heroin 8 (15.4) 11 (21.0)
Marijuana 1 (2.0) 0 (0.9)
Crystal meth/methamphetamine 1 (2.0) 0 (0.6)
Tramad 6 (11.5) 4.6 (8.9)
Pethidine 6 (11.5) 4 (8.2)
Ever changed from one injecting drug to the other
Yes 16 (31.4) 13 (25.8)
No 34 (66.7) 36 (69.9)
Nonresponse 1 (2.0) 2 (4.3)
What did it change to?
Cocaine 7 (43.8) 8 (52.7)
Crack 4 (25.0) 3 (16.9)
Heroin 2 (12.5) 2 (10.9)
Crystal meth/methamphetamine 1 (6.3) 1 (6.2)
Other 2 (12.5) 2 (13.2)
Last time injected drugs
Within the last 7 days 37 (71.2) 37 (70.9)
More than 7 days to 1 month 4 (7.7) 3 (6.1)
More than 1 month up to 6 months 5 (9.6) 4 (6.8)
More than 6 up and to 12 months 2 (3.9) 3 (6.5)
More than 12 months 4 (7.7) 5 (9.8)
Commonly injected drugs
Cocaine 23 (45.1) 28 (55.2)
Crack 9 (17.7) 6 (12.4)
Heroin 7 (13.7) 8 (14.9)
Crystal meth/methamphetamine 1 (2.0) 0 (0.7)
Tramadol 6 (11.7) 5 (9.1)
Pethidine 4 (7.8) 3 (6.9)
Other 1 (2.0) 0 (0.9)
Number of times per day drug is injected
1 time/day 14 (27.5) 0 (27.6)
2 times/day 13 (25.5) 13 (25.2)
3 times/day 9 (17.7) 9 (17.5)
4+ times/day 15 (29.4) 15 (29.8)
Commonly use two or more drugs together
No 31 (67.4) 32 (69.6)
Yes 15 (32.6) 14 (30.4)
time employment [41]. (e only woman injector in this study conforms to a study where males have an early debut of drug
commonly injected heroin, which is contrary to a study where use and injection as against females [42]. Close to half of the
women were more likely to inject antianxiety medications and women in the study had ever exchanged sex for goods or
methamphetamine [41] and was initiated at 16.0 years. (is drugs. Previous studies indicated that women traded sex for
8 Interdisciplinary Perspectives on Infectious Diseases
Table 4: Unweighted and weighted characteristics of respondents by variable type according to people who inject drugs.
Unweighted Weighted
n (%) n (%)
Factor 52 52
Source of needles/syringes in the last 6months
Pharmacy/chemist/drug store/store/another store 29 (61.7) 27 (57.4)
Market place or street vendor 2 (4.3) 1 (2.7)
Pharmacy worker or drug vendor 8 (17.0) 10 (20.7)
Sex partner, friend, acquaintance, relative 3 (6.4) 2 (5.3)
Drug dealer or other drug users 4 (8.5) 4 (9.0)
Don’t know 1 (2.1) 2 (4.9)
Sterile needles and syringes available when needed
Yes 44 (86.3) 41 (80.6)
No 5 (9.8) 5 (10.8)
Don’t know 2 (3.9) 4 (8.7)
Pays for the needles
Yes 44 (88.0) 46 (92.4)
No 6 (12.0) 4 (7.6)
Pay to be injected
Yes 16 (31.4) 18 (35.5)
No 35 (68.6) 33 (64.5)
How often is a new sterile needle used in the last 6months
Never 2 (3.9) 2 (3.8)
Rarely 5 (9.8) 5 (9.0)
Half of the time 6 (11.8) 6 (12.0)
Most of the time 9 (17.7) 7 (14.7)
Always 29 (56.9) 31 (60.5)
Reasons for not using a new needle or syringe always
Not available 2 (9.1) 2 (8.9)
Difficult to find 6 (27.3) 6 (26.9)
Expensive 7 (31.8) 7 (30.0)
Peer pressured to share 3 (13.6) 5 (20.9)
I reuse my own needle 4 (18.2) 3 (13.4)
When you inject, do you do it: alone, or with a friend, drugs dealer, assistant drug dealer
Alone 25 (49.0) 27 (52.5)
A friend 19 (37.3) 18 (35.1)
Drugs dealer 5 (9.8) 4 (8.5)
Assistant drug dealer 1 (2.0) 1 (1.3)
Don’t know 1 (2.0) 1 (2.6)
In the last 6 months, how often did you use needles that someone else had already injected with
Never 38 (74.5) 34 (67.4)
Rarely 2 (3.9) 3 (6.5)
Half of the time 6 (11.8) 6 (12.7)
Most of the time 3 (5.9) 4 (7.8)
Always 6 (11.7) 1 (1.3)
Don’t know 1 (2.0) 2 (4.3)
Shared needle with other person in the past 6months
Not shared 26 (57.8) 23 (52.2)
Shared 13 (28.9) 14 (31.6)
Refused to answer 6 (13.3) 7 (16.2)
Shared an instrument with another person in the past 6months
Not shared 24 (54.6) 22 (50.0)
Shared 20 (45.5) 22 (50.0)
Venue or location drug is commonly injected
Own house 13 (26.5) 15 (30.6)
House of someone else 3 (6.1) 4 (7.3)
House of dealer 3 (6.1) 3 (6.2)
Abandoned building 2 (4.1) 2 (4.3)
Street (ghetto) 24 (49.0) 23 (46.2)
Other places 4 (8.2) 3 (5.5)
Interdisciplinary Perspectives on Infectious Diseases 9
Table 4: Continued.
Unweighted Weighted
n (%) n (%)
How often are needle/syringe reused before thrown out
Very often 13 (25.5) 12 (23.9)
Often 7 (13.7) 8 (15.0)
Not so often 13 (25.5) 15 (29.9)
Never 18 (35.3) 16 (31.3)
Table 5: Crude and adjusted posterior medians (odds ratios) and their credible intervals for the prevalence of HIV, HCV, and HBV.
Crude HIV Crude HCV Crude HBV Adjusted HIV Adjusted HCV Adjusted HBV
Factor
Age group of participants
19–29 years 1.00 1.00 1.00 1.00 1.00 1.00
30–39 years 0.97 (0.30–2.29) 0.99(0.35–2.19) 1.65 (0.37–4.86) 0.83 (0.25–1.95) 1.05 (0.36–2.32) 1.26 (0.28–3.73)
40+ years 0.95 (0.31–2.28) 1.27(0.47–2.73) 1.59 (0.36–4.60) 0.48 (0.18–0.98) 1.17 (0.40–2.69) 1.84 (0.37–5.63)
Highest level of education
Never attended school 1.00 1.00 1.00 (1.00 1.00 1.00
Primary 1.19 (0.37–2.92) 1.59(0.53–3.72) 0.65 (0.71–2.59) 1.12 (0.46–2.28) 1.55 (0.51–3.64) 0.52 (0.79–1.82)
JHS/middle school 0.68 (0.20–1.74) 0.68(0.21–1.58) 0.67 (0.09–2.46) 0.41 (0.14–0.97) 0.69 (0.22–1.62) 0.30 (0.07–0.84)
Secondary school or
higher 0.94 (0.29–2.28) 0.78(0.26–1.91) 1.21 (0.17–4.42) 0.67 (0.24–1.53) 0.79 (0.26–1.86) 1.52 (0.29–4.83)
Employment status
Employed full-time 1.00 1.00 1.00 1.00 1.00 1.00
Employed part-time 1.16 (0.35–2.88) 1.38(0.49–3.04) 3.85(1.39–10.08) 1.25 (0.40–3.09) 1.36 (0.49–2.97)
5.50
(1.20–16.16)
Unemployed 1.13 (0.37–2.61) 0.69(0.25–1.49) 1.22 (0.27–3.69) 1.03 (0.36–2.32) 0.67 (0.24–1.44) 2.13 (0.47–5.99)
Marital status
Single, never married 1.05 (0.34–2.63) 1.20(0.44–2.73) 1.11 (0.24–3.53) 0.82 (0.31–1.84) 1.09 (0.41–2.37) 2.38 (0.49–7.66)
Married 0.74 (0.19–1.92) 1.32(0.43–3.18) 0.97 (0.15–3.30) 0.53 (0.15–1.27) 0.82 (0.23–2.05) 2.10 (0.39–7.07)
Separated/divorced/
Widowed 1.00 1.00 1.00 1.00 1.00 1.00
Currently living with sexual
partner
Yes 1.00 1.00 1.00 1.00 1.00 1.00
No 0.04(0.01–0.07) 1.77(0.71–3.93) 0.57 (0.17–1.38) 0.99 (0.36–2.24) 1.75 (0.67–3.92) 0.54 (0.14–1.29)
How respondents identify
self
SW 1.00 1.00 1.00 1.00 1.00 1.00
MSM — — — — — —
General population 0.38 (0.11–1.02) — — 0.34(0.12–0.81) — —
Injecting drugs
Yes 0.94(0.25–2.37) 0.71(0.21–1.68) 1.77(0.36–4.80) 1.23(0.33–3.28) 0.70(0.20–1.73) 1.47(0.18–5.29)
No 1.00 1.00 1.00 1.00 1.00 1.00
Age group at start of using
drugs
Less than or equal to 19
years 0.96 (0.29–2.28) 0.71(0.24–1.62) 1.24 (0.22–4.06) 0.47 (0.17–1.06) 1.43 (0.53–3.15) 2.09 (0.41–6.82)
20–29 years 1.36 (0.42–3.37) 1.07(0.39–2.39) 1.30 (0.23–4.28) 0.76 (0.32–1.52) 1.57 (0.49–3.76) 1.99 (0.28–7.22)
30+ years 1.00 1.00 1.00 1.00 1.00 1.00
Regions
Greater accra 1.00 3.37(1.26–7.57) 1.00 1.00 1.00 1.00
Ashanti 1.35 (0.44–3.14) — 0.80 (0.25–1.81) 2.02 (0.70–4.5) — 0.16 (0.01–0.57)
Western 0.91 (0.28–2.19) — 1.45 (0.49–3.23) 1.67 (0.56–4.13) — 2.02 (0.55–5.13)
Northern — 1.00 1.26 (0.18–0.78) — — 0.83 (0.55–5.13)
10 Interdisciplinary Perspectives on Infectious Diseases
money or drugs or had received drugs for their first injection should be encouraged, in addition to interventions
as a gift and thereafter mostly engaged in sexual relations with that can help curb such practices of risky sexual
their partners before or after drug injection [42, 43]. behavior.
More women had HIV in the study compared to their (3) Rehabilitation programs to help people with sub-
male counterparts is found in the literature that HIV is stance use disorder who are willing to quit the
generally higher among women. (is may be exacerbated practice.
due to sexual abuse [30, 42]. In a related study, women had
more multiple sexual partners as compared to men [44]. 5. Conclusion
Other reasons include gender inequalities such as decent
employment for men than women, lower literacy levels, and Findings from this study suggest that most drug users and
women’s restricted opportunity to have some level of control injectors had a reasonable level of education and fair level of
over resources. It was further stated that when women were employment. Most were not married, but a third lived with
less financially empowered, they happened to rely more on their sexual partners. (e majority of respondents belonged
their male partners for survival, thus being at their mercy. to the general population, where they were not sex workers
(ese women may have even lacked the skills to negotiate or men who slept with men. Commonly used and injected
safe sex due to their early sexual debut, which predisposes drugs included heroin, crack, cocaine, and tramadol, and
them to such infections at an early stage [45–48]. More men these were used or injected daily from one to more than four
than women were found to be infected with hepatitis B and times a day. (ey were mostly introduced by friends, rel-
C viruses.(is is similar to other findings, where hepatitis, in atives, and acquaintances. Education, literacy, and not being
general, is higher in men than women [49–51]. a member of a key population protected respondents from
Age was a significant predictor of HIV. (e higher the HIV, hepatitis B, and C infections.
age, the less likely one was to be infected with HIV. (is
was contrary to other findings suggesting that the higher
the age, the higher probability of HIV infection [3]. Ed- Data Availability
ucation significantly predicted HIV and HBV status in this (e datasets generated and/or analyzed during the current
study. (is was confirmed by studies where significant study are not publicly available but are available from the
associations were found between having less than high corresponding author on request.
school education and being more likely to have HIV and
HBV [3, 10]. Other studies also confirmed the positive
effects of education on HIV status. (ey argue that the Ethical Approval
more individuals obtain education, the more aware they (e study received ethics approval from the University of
become of risky behaviors and their consequences. More Ghana College of Health Sciences Institutional Review
educated individuals were more likely to protect them- Board (CHS-Et/M.6 – p4.8/2020–2021). All data presented
selves since they were more knowledgeable of precau- are from people who provided written informed consent to
tionary measures against these diseases [52–54]. (ere was participate in the study. All participants were informed of
a significantly lower prevalence of HIV among people who the risks and benefits of their participation in the study,
were identified to be in the general population. (ose who their rights as study participants (e.g., the ability to stop
reported as sex workers or men who have sex with men had the interview at any time), how their information will be
higher odds of being HIV positive. (e rate of infection safeguarded, and how risks to participation will be min-
among sex workers and men who have sex with men imized. (e study was conducted in accordance with the
(MSM) was very alarming, given the number of sexual Declaration of Helsinki, and all methods were performed
partners involved and the risky sexual behavior [3, 55–58]. in accordance with the relevant guidelines and regulations.
Employment status was another significant predictor of (e consent also provided contact information in case
HBV status. (ose who were employed part-time were five participants have any future questions or wish to follow up
times more likely than those who were employed full-time with researchers.
to be infected with HBV. A past study, on the contrary,
reported that most respondents who were unemployed Conflicts of Interest
experienced blood-borne infections of which hepatitis B
was a part [10]. (e authors declare that they have no competing interests.
Authors’ Contributions
4.1. Recommendations
(1) Full harm reduction programs, including NSP and CG contributed to conceptualization, resources, project
OST, should be intensified among drug injectors to administration, methodology, investigation, data curation,
help reduce their chances of needle sharing and formal analysis, validation, visualization, writing the original
reuse. draft, and review & editing. SMOY contributed to meth-
odology, data curation, formal analysis, writing the original
(2) Continuous awareness and education on the po- draft, and review & editing. SD, CBdS, CAA, SAA, MGL,
tential for risky sexual behaviors among drug users AM AND KT contributed to resources, project
Interdisciplinary Perspectives on Infectious Diseases 11
administration, methodology, investigation, validation, vi- [13] L. Bird, Domestic Drug Consumption in Ghana|Global Ini-
sualization, writing the review & editing, and supervision. tiative [Internet], https://globalinitiative.net/analysis/drug-
policy-ghana/.
[14] L. J. Messersmith, R. Adjei, J. Beard et al., “High levels of used
Acknowledgments syringe use and unsafe sex among people who inject drugs in
(e authors express their sincere thanks to the research Kumasi, Ghana: an urgent call for a comprehensive harm
assistants, counselors, laboratory technicians, and partici- reduction approach,”Harm Reduct J, vol. 18, no. 1, p. 62, 2021.[15] A. Boys, J. Marsden, and J. Strang, “Understanding reasons for
pants including people who use or inject drugs for providing drug use amongst young people: a functional perspective,”
invaluable information for this research. (e Global Fund/ Health Education Research, vol. 16, no. 4, pp. 457–469, 2001.
West African Program to Combat AIDS funded this work, [16] W. M. Cox and E. Klinger, “A motivational model of alcohol
but the funders did not play a role in the design, conduct, or use,” Journal of Abnormal Psychology, vol. 97, no. 2,
analysis of the study. pp. 168–180, 1988.
[17] J. Bjornestad,M. Veseth, H. Berg et al., “Reports of the benefits
References of drug use from individuals with substance use disorders,”
Psychotherapy Research, vol. 30, no. 6, pp. 718–727, 2019.
[1] E. M. Beltrami, I. T. Williams, C. N. Shapiro, and [18] Y. M. Terry-Mcelrath, P. M. O’malley, and L. D. Johnston,
M. E. Chamberland, “Risk and management of blood-borne “Reasons for drug use among american youth by consump-
infections in health care workers,” Clinical Microbiology tion level, gender, and race/ethnicity: 1976-2005,” Journal of
Review, vol. 13, no. 3, pp. 385–407, 2000 Jul. Drug Issues, vol. 39, no. 3, pp. 677–713, 2009.
[2] S. Lokpo, M. Dakorah, and G. K. Norgbe, “(e burden and [19] A. Guise, D. Horyniak, J. Melo, R. McNeil, and D. Werb, “(e
trend of blood-borne pathogens among asymptomatic adult experience of initiating injection drug use and its social
population in Akwatia: a retrospective study at the St. dominic context: a qualitative systematic review and thematic syn-
Hospital,” Ghana Journal Trop Med [Internet], https://www. thesis,” Addiction, vol. 112, no. 12, pp. 2098–2111, 2017.
hindawi.com/journals/jtm/2017/3452513/, 2017. [20] K. A. Mack, C. M. Jones, and M. F. Ballesteros, “Illicit drug
[3] Y. Cai, Z. Dai, S. Wen, and R. Bhandari, “Risk factors as- use, illicit drug use disorders, and drug overdose deaths in
sociated with infection of blood-borne virus among people metropolitan and nonmetropolitan areas—United States,”
who used methamphetamine,” BMC Infect Dis, p. 742, 2020. American Journal of Transplant, vol. 17, no. 12, pp. 3241–3252,
[4] T. D. Ritchwood, H. Ford, J. DeCoster, M. Sutton, and 2017.
J. E. Lochman, “Risky sexual behavior and substance use [21] A. T. McLellan, “Substance misuse and substance use dis-
among adolescents: a meta-analysis,” Children and Youth orders: why do they matter in healthcare?” Trans Am Clin
Services Review, vol. 52, pp. 74–88, 2015. Climatol Assoc, vol. 128, pp. 112–130, 2017.
[5] P. N. Gona, C. M. Gona, S. Ballout et al., “Burden and changes [22] H. Belani, T. Chorba, F. Fletcher, and K. Hennessey, “Inte-
in HIV/AIDS morbidity and mortality in Southern Africa grated prevention services for HIV infection, viral hepatitis,
development community countries, 1990-2017,” BMC Public sexually transmitted diseases, and tuberculosis for persons
Health, vol. 20, no. 1, p. 867, 2020. who use drugs illicitly: summary guidance,” Morb Mortal
[6] D. Lavanchy, “Hepatitis B virus epidemiology, disease burden, Wkly Rep Recomm Reports, vol. 61, no. 5, 2012.
treatment, and current and emerging prevention and control [23] L. Y. Hwang, C. Z. Grimes, T. Q. Tran et al., “Accelerated
measures,” Journal of Viral Hepatitis, vol. 11, no. 2, hepatitis B vaccination schedule among drug users: a ran-
pp. 97–107, 2004. domized controlled trial,” J Infect Dis, vol. 202, no. 10,
[7] “UNODC world drug report 2020: global drug use rising;
while COVID-19 has far reaching impact on global drug pp. 1500–1509, 2010.[24] R. Fenner and T. Cernev, “(e implications of the Covid-19
markets [Internet],” https://www.unodc.org/unodc/press/
releases/2020/June/media-advisory---global-launch-of-the- pandemic for delivering the sustainable development goals,”
2020-world-drug-report.html. Futures, vol. 128, Article ID 102726, 2021.
[8] Y. P. Bao and Z. M. Liu, “Systematic review of HIV and HCV [25] M. Reid, Q. Abdool-Karim, E. Geng, and E. Goosby, “How
infection among drug users in China,” International Journal will COVID-19 transform global health post-pandemic? de-
of STD AIDS, vol. 20, no. 6, pp. 399–405, 2009. fining research and investment opportunities and priorities,”
[9] A. B. Kelly, T. J. Evans-Whipp, R. Smith et al., “A longitudinal PLoS Med, no. 3, Article ID e1003564, 2021.
study of the association of adolescent polydrug use, alcohol [26] J. Grebely, M. Cerdá, and T. Rhodes, “COVID-19 and the
use and high school non-completion,” Addiction, vol. 110, health of people who use drugs: what is and what could be?”
no. 4, pp. 627–635, 2015. International Journal of Drug Policy, vol. 83, Article ID
[10] R. Abadie, M. Welch-Lazoritz, C. Gelpi-Acosta, J. C. Reyes, 102958, 2020.
and K. Dombrowski, “Understanding differences in HIV/ [27] T. I. Vasylyeva, P. Smyrnov, S. Strathdee, and S. R. Friedman,
HCV prevalence according to differentiated risk behaviors in “Challenges posed by COVID-19 to people who inject drugs
a sample of PWID in rural Puerto Rico,” Harm Reduction and lessons from other outbreaks,” Journal of the Interna-
Journal, vol. 13, no. 1, p. 10, 2016. tional AIDS Society, vol. 23, no. 7, Article ID e25583, 2020.
[11] N. J. Kim, H. Jin, W. McFarland, and H. F. Raymond, “Trends [28] M. Whitfield, H. Reed, J. Webster, and V. Hope, “(e impact
in sources and sharing of needles among people who inject of COVID-19 restrictions on needle and syringe programme
drugs, San Francisco, 2005–2012,” International Journal of provision and coverage in England,” International Journal of
Drug Policy, vol. 26, no. 12, pp. 1238–1243, 2015. Drug Policy, vol. 83, Article ID 102851, 2020.
[12] N. El-Bassel, S. Shaw, A. Dasgupta, and S. Strathdee, “Drug [29] H. B. de Carvalho, F. Mesquita, E. Massad et al., “HIV and
use as a driver of HIV risks: re-emerging and emerging is- infections of similar transmission patterns in a drug injectors
sues,” Curr Opin HIV AIDS, vol. 9, no. 2, 2013. community of Santos, Brazil,” Journal of Acquired Immune
12 Interdisciplinary Perspectives on Infectious Diseases
Deficiency Syndromes and Human Retrovirology, vol. 12, no. 1, adults and children in an HIV cohort from a,” Infect Dis Rep,
pp. 84–92, 1996. vol. 4, no. 1, pp. 66–70, 2012.
[30] D. C. Des Jarlais, S. R. Friedman, T. Perlis et al., “Risk behavior [45] T. Girum, A. Wasie, K. Lentiro, E. Muktar, T. Shumbej, and
and HIV infection among new drug injectors in the era of M. Difer, “Gender disparity in epidemiological trend of HIV/
AIDS in New York City,” Journal of Acquired Immune De- AIDS infection and treatment in Ethiopia,” Arch Public Heal,
ficiency Syndromes and Human Retrovirology, vol. 20, no. 1, no. 1, p. 76, 2018.
pp. 67–72, 1999. [46] M. A. Magadi, “Understanding the gender disparity in HIV
[31] S. Darke, S. Kaye, andM. Torok, “Age-related patterns of drug infection across countries in sub-Saharan Africa: evidence
use initiation among polydrug using regular psychostimulant from the demographic and health surveys,” Sociology of
users,” Drug and Alcohol Review, vol. 31, no. 6, pp. 784–789, Health & Illness, vol. 33, no. 4, pp. 522–539, 2011.
2012. [47] S. Patra, “Socio-cultural correlates and risky sexual behaviour
[32] A. Strashny, “Age of substance use initiation among treatment influencing prevalence of HIV/AIDS and STIs in Uganda: a
admissions aged 18 to 30,” 2016, https://europepmc.org/ gender perspective,” Cogent Social Sciences, vol. 2, no. 1,
article/nbk/nbk384841. Article ID 1166472, 2016.
[33] R. Lal, K. Deb, and S. Kedia, “Substance use in women: current [48] D. Sia, Y. Onadja, M. Hajizadeh, S. J. Heymann, T. F. Brewer,
status and future directions,” Indian Journal Psychiatry, and A. Nandi, “What explains gender inequalities in HIV/
vol. 57, no. 6, p. 275, 2015. AIDS prevalence in sub-Saharan Africa? evidence from the
[34] R. K. McHugh, V. R. Votaw, D. E. Sugarman, and demographic and health surveys,” BMC Public Health, vol. 16,
S. F. Greenfield, “Sex and gender differences in substance use no. 1, pp. 1136–1218, 2016.
disorders,” Clinical Psychology Review, vol. 66, pp. 12–23, [49] J. K. Iyer, M. Kalra, A. Kaul, M. E. Payton, and R. Kaul,
2018. “Estrogen receptor expression in chronic hepatitis C and
[35] M. Noroozi, A. Mirzazadeh, A. Noroozi, and Y. Mehrabi, hepatocellular carcinoma pathogenesis,” World Journal of
“Client-level coverage of needle and syringe program and Gastroenterology, vol. 23, no. 37, pp. 6802–6816, 2017.
high-risk injection behaviors: a case study of people who [50] S. H. Wang, P. J. Chen, and S. H. Yeh, “Gender disparity in
inject drugs in Kermanshah, Iran,” Addict Heal, vol. 7, 2015. chronic hepatitis B: mechanisms of sex hormones,” Journal
[36] S. Zhang, S. Wu, Q. Wu, D. W. Durkin, and F. F. Marsiglia, Gastroenterol Hepatol, vol. 30, no. 8, pp.1237–1245, 2015 Aug 1.
“Adolescent drug use initiation and transition into other [51] W. C. Liu and Q. Y. Liu, “Molecular mechanisms of gender
drugs: a retrospective longitudinal examination across race/ disparity in hepatitis B virus-associated hepatocellular car-
ethnicity,” Addictive Behaviors, vol. 113, pp. 106679–114603, cinoma,” World Journal of Gastroenterology, vol. 20, p. 6252,
2021. 2014.
[37] A. E. Rudolph, N. D. Crawford, D. C. Ompad, E. O. Benjamin, [52] E. K. Kamgaing, S. M. Rogombe, A. M. L. Mikolo et al.,
R. J. Stern, and C. M. Fuller, “Comparison of injection drug “Management and development of newborns from mothers
users accessing syringes from pharmacies, syringe exchange carrying hbsag at the el rapha polyclinic in libreville, Gabon,”
programs, and other syringe sources to inform targeted HIV Open Journal of Pediatrics, vol. 11, no. 03, pp. 468–478, 2021.
prevention and intervention strategies,” Journal of the [53] T. S. Mwamwenda, “Journal of AIDS and HIV Research HIV/
American Pharmacists Association, vol. 50, no. 2, pp. 140–147, AIDS knowledge of high school adolescents in Kenya,” J AIDS
2010. HIV Res, vol. 5, no. 12, pp. 472–478, 2013.
[38] K. Suohu, C. Humtsoe, N. Saggurti, S. Sabarwal, [54] H. Rindermann and G. Meisenberg, “Relevance of education
B. Mahapatra, and M. Kermode, “Understanding the asso- and intelligence at the national level for health: the case of
ciation between injecting and sexual risk behaviors of HIV and AIDS,” Intelligence, vol. 37, no. 4, pp. 383–395, 2009.
injecting drug users in Manipur and Nagaland, India,” Harm [55] C. Beyrer, P. Sullivan, J. Sanchez et al., “(e increase in global
Reduction Journal, p. 40, 2012. HIV epidemics in MSM,” Aids, vol. 27, no. 17, pp. 2665–2678,
[39] S. S. H. Nazari, A. Hajebi, M. Noroozi et al., “(e effect of on- 2013.
site and outreach-based needle and syringe programs in [56] C. Beyrer, A. L. Crago, L. G. Bekker et al., “An action agenda
people who inject drugs in Kermanshah, Iran,” International for HIV and sex workers,” Ee Lancet, vol. 385, no. 9964,
Journal of Drug Policy, vol. 27, pp. 127–131, 2016. pp. 287–301, 2015.
[40] A. V. Rivera, J. DeCuir, N. D. Crawford, S. Amesty, and [57] H. Shang and L. Zhang, “MSM and HIV-1 infection in
C. F. Lewis, “Internalized stigma and sterile syringe use China,” National Science Review, vol. 2, no. 4, pp. 388–391,
among people who inject drugs in New York City, 2015.
2010–2012,” Drug and Alcohol Dependence, vol. 144, [58] K. Shannon, S. A. Strathdee, S. M. Goldenberg et al., “Global
pp. 259–264, 2014. epidemiology of HIV among female sex workers: influence of
[41] M. Staton, G. Ciciurkaite, J. Havens et al., “Correlates of structural determinants,” Ee Lancet, vol. 385, no. 9962,
injection drug use among rural appalachian women,” Ee pp. 55–71, 2015.
Journal of Rural Health, vol. 34, no. 1, pp. 31–41, 2018 Dec 1.
[42] D. C. Ompad, R. M. Ikeda, N. Shah et al., “Childhood sexual
abuse and age at initiation of injection drug use,” American
Journal of Public Health, vol. 95, no. 4, pp. 703–709, 2005.
[43] A. M. Young, N. Larian, and J. R. Havens, “Gender differences
in circumstances surrounding first injection experience of
rural injection drug users in the United States,” Drug and
Alcohol Dependence, vol. 134, pp. 401–405, 2014.
[44] G. Alvarez-Uria, M. Midde, R. Pakam, and P. Naik, “Gender
differences, routes of transmission, socio-demographic
characteristics and prevalence of HIV related infections of