HIV prevalence and associated risk factors among people who inject drugs in four states of central India: Findings from the 17th round of HIV sentinel surveillance

Abstract

Background

This study was conducted to assess the prevalence of HIV and its associated risk factors among people who inject drugs in the four states of Central Zone of India (Bihar, Delhi, Uttar Pradesh and Uttarakhand), based on the data collected during the 17th round of HIV Sentinel Surveillance (HSS) during January to March, 2020.

Methods

The data was used from the 17th round of HSS which was collected through a paper-based survey among participants who were identified as people who inject drugs (PWIDs), followed by blood sample collection. Random sampling method was used to identify 250 PWIDs from each sentinel site.

Results

The key demographic findings show that 60.1% of the participants were of age >=30 years and primarily urban residents (84.5%). Most participants have been tested for HIV previously (97.5%). With almost two-thirds of the participants injecting drugs daily, 89.5% of them reported to have used sterile needles each time. One-third of the participants had avoided health care services due to stigma and discrimination and they are significantly at higher odds of being HIV seropositive (1.83 times).

Conclusions

The study highlights the risk behaviour association with higher odds of being HIV seropositive were high risk occupation, sharing of needles, PWIDs on OST therapy, HIV testing and avoidance of healthcare services - due to stigma. Better programmatic approach is needed to protect the PWIDs.

Keywords

HIV AIDS high risk behaviour sexual behaviour epidemiology

Introduction

About 11 million people inject drugs globally.¹ Out of this, an estimated 0.85 million reside in India, the highest number being in Uttar Pradesh, followed by Punjab and Delhi.^2,3 The national average for estimated size of People Who Inject Drugs for recreational purposes (PWIDs) is 21 per 100,000 population. Injecting drug use practices is one of the most important drivers of HIV epidemic in India. The prevalence of HIV among PWIDs in India is 9.03% (95% CI:8.69–9.37) which is 43 times higher than the prevalence of HIV among the general population. HIV prevalence among PWIDs is significantly higher than every other high risk group in India. The most remarkable prevalence of HIV among PWIDs can be seen in northeastern states ranging from 96 per 100,000 population in Meghalaya to 850 per 100,000 population in Mizoram.⁴

Among PWIDs, HIV may be transmitted by direct route due to sharing of needles and syringes . PWIDs who share needles are at high risk of HIV transmission, the risk being 63 per 10,000 exposures.⁵ Other factors like alcohol, smoking, and inhaling drugs may also contribute to HIV transmission due to inebriation and loss of judgment. This may lead to risky sexual behaviour as well, which provides additional risk. These high-risk behaviours not only increase the risk of HIV, but also other sexually transmitted diseases and blood-borne diseases like Hepatitis B and C.

HIV Sentinel Surveillance (HSS) in India is quite extensive, a cross-sectional studies of HIV Seroprevalence and is conducted every 2 years amongst eight typologies. These typologies are women coming to antenatal clinics, prisoners, four high-risk groups (female sex workers, men who have sex with men, people who inject drugs, and hijra/transgenders), and two bridge populations (single male migrants and long-distance truckers). The present data is from the results of the 17^th round which was conducted between 1^st January to 31^st March, 2020.

PWIDs being one of the most important population for HIV in India, controlling HIV transmission among PWIDs will bring us closer to eliminating HIV by 2030.⁶ Detailed analysis of HIV-causing behaviours among PWIDs can assist the national program in forming policy decisions. Hence, this study aims to find the association of various demographic and behavioural risk factors among people who inject drugs for recreational purposes from the four states of central zone of India.

Methodology

Study design

The primary data of this study was collected through a cross-sectional study, the biennial HIV Surveillance, by a paper-based interview with the participants who were identified as people who inject drugs as per the case definition. The study was conducted under AIIMS New Delhi as the designated Regional Institute (RI-AIIMS) for the 5 states of the central zone. A total of 19 sites in four states (Bihar, Delhi, Uttarakhand and Uttar Pradesh) and mentioned in Figure 1 were covered under the central zone from which 250 samples were collected from each sentinel site, where PWIDs are registered. The data collection through a paper based tool was followed by the collection of a biological sample using Dried Blood Spot Cards, a special protein saver card where blood samples are collected using a self-retractable sterile lancet.⁷

Figure 1.

Map of India and the overall prevalence of HIV in the four states of Central India.

Study Period: The analysis was conducted in the year 2024 after the completion of the 17^th round of HSS.

Sampling frame: Each Targeted Intervention (TI)/ Non Govt. Organization (NGO) sentinel site maintained a master list of the High Risk individual (HRI) who have ever been contacted and registered at the TI. This list is maintained in an MS Excel format, and it formed the basis of the random list selection. The registered line list from each of the sentinel site was randomized at RI-AIIMS, New Delhi and a randomized list of 250 participants was sent to the site for recruitment. A trained counsellor at each of the sites recruited the participant based on the inclusion and exclusion criteria and are verified by the site-in charge. Informed consent was taken from each of the participants. All preparatory activities for the surveillance period was carried out by the State AIDS Control Societies (SACS) of each state. SACS was responsible for the overall implementation of the HSS activities in each of the sentinel sites and also the training of staff in each of the sites

A brief interview schedule that includes demographic information, HIV related risk behaviour and stigma and discrimination against health and other services utilization from government facilities was conducted which was followed by blood sample collection.

Sample size: At each sentinel site, 250 PWIDs were recruited based on the random list provided to them. Buffer lists of randomly selected eligible individuals were provided to the site in case of non-recruits above the already given random list of 250 in each site.

Inclusion and exclusion criteria

Inclusion Criteria: People who inject drugs as per the case definition, are men who are aged 18 years and above who use addictive substances or drugs for recreational or non-medical reasons through injections at least once in the last 3 months. Exclusion Criteria: Those who were already approached and administered informed consent once in the current round of surveillance and whose age and HIV results were not available in the raw data were excluded from the study.

Laboratory procedures

Dried blood spots (DBS) cards were used to collect the biological samples. DBS cards used for HSS are protein saver cards where the blood of the person is collected by finger prick method. A self-retractable single use sterile lancet of 21 Gauge was used to prick the finger of the participants and the blood drops are collected on the DBS cards. This method of bio-specimen collection was adopted due to its acceptability among the participants and being less technique-sensitive.⁸ The DBS cards were then dried as per the SOP and sent to a designated laboratory where HIV testing was conducted.

Outcome of HIV seropositivity

HIV seropositivity among people who inject drugs (PWIDs) refers to the presence of HIV-specific antibodies in their blood, indicating a confirmed HIV infection. It is determined through serological testing, enzyme-linked immunosorbent assay (ELISA) and Western blot or nucleic acid testing (NAT) was done for confirmatory test.

Quality control measures for serum samples

Although all the testing was done at a designated laboratory, external quality assurance was also done in ICMR-NARI, Pune for all the positive tested samples and 5% of the negative tested samples to maintain the quality of testing.

Quality control measures for data

Data from the physical paper-based tool were entered into the web based software and data entry was done twice by two different data entry operators and matched later for maintaining data quality at RI-AIIMS, New Delhi into the web-based strategic information management system. The entered data were sorted individually for any discordance and verified from the paper-based forms.

Statistical analysis

After downloading from the SIMS portal, the data underwent cleaning. Quantitative variables including demographics, HIV/AIDS-related testing/treatment, injecting drug use practices, sexual risk behavior, and stigma and discrimination were expressed as numbers and percentages. Unadjusted and adjusted odds ratios, along with a 95% confidence interval, were calculated using bivariate and multivariable logistic regression for the HIV seropositivity. Statistical significance was determined at p ≤ .05. All analyses were performed using Stata version 16.0 (STATA Corp.,College Station, TX, USA).

Result

A total of 5796 PWIDs were approached and out of these, 5602 participants were recruited in the study. Mean (SD) age of the participants was 33.⁹ More than half of the participants (60.1%) were of 30 years or more, whereas 17.5% were of age 18–24. The majority of the participants (74.3%) were literate but not more than primary, 12% were educated to more than primary standard and 11.3% were illiterate. The majority of the participants were reported to be residing in an urban area (85%). All demographic details are described in Table 1.

Table 1.

Distribution of PWID by category and risk behaviour.

S.N.	Variables	Category	n (%)
Background characteristic
1	Age (n = 5602)	18–24	971 (17.3)
		25–34	2469 (44.1)
		>=35	2162 (38.6)
2	Marital status (n = 5561)	Never married	2818 (50.7)
		Currently married	2181 (39.2)
		Divorced/Separated/Widower/Widow	562 (10.1)
3	Education (n = 5575)	Primary and less (<=5)	3882 (69.6)
		More than primary (>5)	1693 (30.4)
4	Residence (n = 5445)	Urban	4601 (84.5)
		Rural	844 (15.5)
5	Occupation (n = 5427)	Unskilled workers	1135 (20.9)
		Skilled workers	627 (11.6)
		Driver	555 (10.2)
		Student/Unemployed	1093 (20.1)
		Non-agriculture	732 (13.5)
		High-risk work	471 (8.7)
		Others	814 (15.0)
HIV/AIDS-related testing, treatment services uptake & HIV pre-exposure prophylaxis (PrEP)
6	Ever tested for HIV (n = 5595)	Yes	5450 (97.5)
		No	142 (2.5)
		Not aware of HIV	3 (0.1)
7	Last test done (n = 5428)	Within 3 months	1564 (28.8)
		Three months to less than 6 months	2369 (43.6)
		Six month to less than 1 year	1056 (19.5)
		More than 1 year	439 (8.1)
8	Result of last HIV test(n = 5431)	Positive	218 (4.0)
		Negative	5150 (95.1)
		Result not known	35 (0.8)
9	Aware of PrEP (n = 5314)	Yes	437 (8.2)
		No	4877 (91.8)
Injecting drug use practices & sexual behaviour and condom use practices
10	Age of first injection (n = 5314)	<15	279 (5.2)
		15–24	3154 (58.7)
		25–34	1942 (36.1)
11	Frequency of injection in last week (n = 5552)	Every day	3622 (65.2)
		More than once a week	1603 (28.9)
		Did not inject last week	327 (5.9)
12	Frequency during the last day of injection (n = 5476)	Once a day	2270 (41.5)
		More than once a day	3206 (58.6)
13	Use of new needle (n = 5476)	Yes	151 (2.7)
		No and don’t remember	5403 (97.3)
14	Sharing of used needle (n = 5554)	Yes	151 (2.7)
		No and don’t remember	5403 (97.3)
15	Injecting drugs by a regular female partner (n = 4045)	Yes	73 (1.8)
		No/ Don’t know/No response	3972 (98.2)
16	Visited other towns to get drugs (n = 5525)	Yes	2519 (45.6)
		No	3006 (54.4)
17	OST (n = 5491)	Yes	1178 (21.5)
		No/Don’t know/No response	4313 (78.6)
18	Ever had sexual intercourse (n = 5581)	Yes	3822 (68.5)
		No	1759 (31.5)
19	Condom use during last sexual intercourse	Yes	2316 (61.4)
		No	854 (22.6)
Stigma and discrimination against testing and service uptake as an PWID
19	Avoiding health care service uptake at the PWID target intervention site due to stigma and discrimination (n-5593)	Yes	1959 (35)
		No	3534 (65)
20	Avoiding HIV testing service uptake at the PWID target intervention site due to stigma and discrimination (n = 5317)	Yes	1418 (26.7)
		No	3899 (73.3)
State wise distribution
21	State	Bihar	490 (8.75)
		Delhi	750 (13.39)
		Uttar Pradesh	3891 (69.46)
		Uttarakhand	471 (8.41)

Note – Total n is different for different variable because of missing value in all variables. The missing data is less than 5% so it is unlikely to bias the results significantly.

HIV/AIDS-related testing, treatment services uptake

Majority of the participants (97.5%) reported to have been tested for HIV previously. Majority of them (92%) were tested in last 1 year. Out of these, 218 participants reported to be positive and 187 of them (86%) were reportedly on medication.

Injecting drug use practices & sexual behaviour and condom use practices

Mean (SD) age of starting of drug use was 22.78.⁷ More than half of the participants (58.68%) started injecting drugs in the age group 15–24, and 5.1% of them were under the age of 15 when they started injecting drugs for recreational purposes.

Majority of the participants (64.7%) injected drugs every day. During the last day of injection, almost half of the participants, (41.3%) have injected once a day and more than half of the participants (58.7%) have injected more than once a day.

Majority of the participants (89.5%) used a new needle during their last drug use for recreational purpose.

Very few participants (1.3%) reported that their partners also injected drugs for recreational purpose. About a quarter of the participants (21.6%) were taking oral Opioid Substitution Therapy (OST) from any health clinic or NGO/CBO Facility.

Stigma and discrimination

More than one third of participants (35%) avoided health care service uptake at the TI NGO site and more than a quarter (26%) avoided HIV testing due to fear of stigma and discrimination.

HIV seropositivity and association with various sociodemographic and behavioural variables

Out of 5602 participants tested for HIV, 6.98% (95% CI: 6.32–7.67) were seropositive.

PWIDs who engaged in high-risk occupations (such as drug dealing, scrap/garbage collection, and petty crime) had significantly greater odds (1.71 times) of testing positive for HIV compared to those who identify themselves as unskilled labour. Additionally, PWIDs who share needles had greater odds (2.66 times) of being HIV positive.

Furthermore, PWIDs who are currently undergoing opioid substitution therapy (OST) had higher odds (3.4 times) of being HIV positive compared to those not on OST. PWIDs who travelled to other towns to inject were at higher odds (1.42) of being HIV positive compared to those who do not.

The respondents who avoided healthcare services or HIV testing services had significantly higher odds (1.83 times and 2.20 times, respectively) of being HIV positive compared to those not avoiding such services.

All these correlations were found to be statistically significant. (Table 2)

Table 2.

Association of HIV seropositivity with select socio-demographic and behavioural variables.

Variable	Category	OR (95%C.I.)	p-value	AOR (95%C.I)	p-value
Age	>=35	(ref.)	0.204	(ref.)	0.068
	18–24	1.21 (0.90–1.63)	0.083	1.54 (0.96–2.46)	0.295
	25–34	1.22 (0.97–1.54)		1.20 (0.85–1.70)
Marital status	Currently married	(ref.)	0.95	(ref.)	0.241
	Divorced/Saperated/Widower/Widow	0.99 (0.8–1.23)	0.082	0.70 (0.39–1.26)	0.277
	Not married	0.69 (0.46–1.04)		1.12 (0.86–1.62)
Education	Primary and less (<=5)	(ref.)	0.007	(ref.)	0.231
	More than primary (>5)	1.34 (1.08–1.66)		1.20 (0.89–1.58)
Occupation	Unskilled	(ref.)	<0.001	(ref.)	0.119
	Skilled	2.22 (1.49–3.31)		1.52 (0.89–2.60)	0.177
	Driver		0.023	1.45 (0.84–2.50)	0.069
	Student/Unemployed	1.66 (1.07–2.58)	0.005	1.59 (0.96–2.62)	0.286
	Non-agriculture	1.69 (1.16–2.45)	0.109	1.41 (0.74–2.70)	0.029
	High-risk work		0.002	1.88 (1.06–3.34)	0.090
	Others	1.41 (0.92–2.15)	<0.001	1.52 (0.93–2.48)
		1.98 (1.28–3.08)
		2.53 (1.75–3.66)
Residence	Rural	(ref.)	<0.001	(ref.)	0.256
	Urban	2.52 (1.69–3.76)		1.39 (0.78–2.44)
Ever tested for HIV	No	(ref.)	0.057	(ref.)	0.648
	Yes	2.63 (0.97–7.16)		1.60 (0.21–12.15)
Aware of PrEP	Yes	(ref.)	0.024	(ref.)	0.151
	No	0.68 (0.48–0.95)		0.73 (0.48–1.12)
Age at first injection for recreational purposes	>=35	(ref.)	0.006	(ref.)	0.051
	15–24	3.81 (1.68–8.65)	0.111	2.60 (0.99–6.75)	0.163
	25–34	3.18 (1.39–7.29)		2.04 (0.74–5.58)
Frequency of week of injection	Every day	(ref.)		(ref.)
	More than once a week	1.34 (1.06–1.69)	0.013	1.07 (0.78–1.43)	0.654
	Did not inject last week	3.68 (2.69–5.04)	<0.001	0.97 (0.57–1.66)	0.928
Frequency during the last day of injection	Once a day	(ref.)	0.256	-	-
	More than once a day	1.13 (0.91–1.4)		-	-
Use of new needle	Yes	(ref.)	0.025	(ref.)	0.440
	No and don’t remember	1.41 (1.04–1.91)		1.21 (0.75–1.94)
Sharing of used needle	No and don’t remember	(ref.)	<0.001	(ref.)	0.003
	Yes	2.48 (1.5–3.92)		2.66 (1.40–5.04)
Injecting drugs by your regular female partner	No/No regular female partner/ Don’t know/No response	(ref.)	0.059	(ref.)	0.095
	Yes	1.9 (0.97–3.78)		2.14 (0.88–5.22)
Visited other towns to get drugs	Yes	(ref.)	0.011	(ref.)	0.019
	No	1.31 (1.65–1.62)		1.42 (1.06–1.91)
OST	No/Don’t know/No response	(ref.)	<0.001	(ref.)	<0.001
	Yes	3.7 (3.01–4.67)		3.40 (2.50–4.61)
Ever had sexual intercourse	No	(ref.)	0.67	-	-
	Yes	1.07 (0.86–1.35)		-	-
Avoid healthcare service due to stigma and discrimination	No	(ref.)	0.038	(ref.)	0.009
	Yes	0.78 (0.63–0.98)		1.83 (1.16–2.90)
Avoid HIV testing service due to stigma and discrimination	Yes	(ref.)	<0.001	(ref.)	0.011
	No	1.72 (1.31–2.26)		2.00 (1.17–3.39)

Discussion

HIV prevalence among people who inject drugs in four states of Central India was 6.98%. The observed prevalence of HIV among people who inject drugs in India is 9% (8.7–9.4). Delhi had one of the highest prevalence of HIV among people who inject drugs at 15.87%, whereas Bihar, Uttar Pradesh and Uttarakhand had a prevalence of 2.86%, 5.45% and 9.77% respectively.⁹

As per reports, 10% of all new HIV infections globally are among PWIDs.⁹ Overall prevalence of HIV among PWIDs globally is estimated to be 17·8% (10·8–24·8) and an estimated 2.8 million PWIDs are living with HIV.¹⁰ The prevalence varies significantly by the geographical region.

The participants who were engaged in high-risk work like rag picking, petty crime, drug dealing, etc. were at significantly higher odds of being HIV seropositive.

The majority of the participants were residing in urban areas and were at higher odds of being HIV seropositive compared to those residing in rural areas. This was because most of the NGOs included in the surveillance were based in urban areas. In Delhi, 99% were residing in urban areas whereas in Bihar half of the participants were from urban areas. Nationally 64% of the participants were residing in urban areas. Injection drug use was previously thought to be more common in urban areas due to accessibility and options, but recent research suggests that it may not be so.^11,12

HIV-related testing and service uptake

Most of the participants were previously tested for HIV out of which about 72% of participants were tested for HIV in the last 6 months and 20% more in the last 1 year. About 8% of participants were not tested even once in the last 1 year. Though TI NGOs encourage every registered PWIDs to get tested every 6 months,¹³ about 85% were tested in last 1 year nationally. Being unaware of the status of HIV is a threat to the population for further spread of HIV infection.

Knowledge of injecting drug practices

In this study, we found that about 14% of the participants started injecting drugs at less than 18 years of age and 5% started injecting at younger than 15 years. Almost 7% of these PWIDs were found to be HIV positive. PWIDs who start injecting at a younger age are at higher risk of being HIV positive due to the longer risk time.¹⁴ Also, younger PWIDs may be more prone to other high-risk factors due to lack of knowledge. The TI NGOs only register PWIDs who are above 18 years of age because of the ethical issues related to the POCSO act.¹⁵ Adequate policy is required to cover younger PWIDs who do not get services from TI NGOs.

It was seen that PWIDs who shared needles while injecting were at three time higher odds of being HIV seropositive.¹⁶ Needle sharing is an established and most importantly causes high HIV prevalence in PWIDs.⁵ Most of the participants were using new needles though. Syringe exchange program reportedly decreased HIV prevalence by about 50% and close to two third when combined with opioid substitution therapy.^17,18

Very few of the participants injected drug with their female partners. But those who did were at higher odds of being HIV seropositive.

Stigma and discrimination

A good proportion of PWIDs face stigma and discrimination which results in them not seeking health services at TI NGO or being tested for HIV. These PWIDs who avoid healthcare services and HIV testing services were at higher odds of being HIV positive.

Studies show that stigma plays an important role in PWIDs experiences with health service access and utilization and is associated with adverse health outcomes. This can also result in poor mental and physical health.¹⁹

Strength and limitations

Being a cross-sectional survey, temporality of associated factors could not be established. Also, most of the questions were not compulsory for the participants, hence almost all of the variables have missing data and the total is different for different variable. Social desirability bias cannot be ruled out due to the sensitive nature of questions. Data collection was done by NGO staff. There may be bias in few variables related to the TI performance like HIV testing status. Also, the study can only be generalised to PWIDs getting services at the TI/NGO and we acknowledge that these PWIDs are different from those who are not in touch with TI/NGO.

Conclusion

This study highlights the serious HIV risks faced by people who inject drugs (PWIDs). Sharing needles, working in high-risk jobs, and delaying opioid substitution therapy (OST) increase the chances of infection. Many avoid healthcare due to stigma, making the situation worse. To protect this vulnerable group, we need better harm reduction programs, including accessible needle exchanges, stigma-free healthcare, and earlier OST access. Outreach programs, especially for those who travel, can help prevent infections. Strengthening peer support and integrating harm reduction into regular healthcare services will improve treatment, reduce transmission, and support healthier lives for PWIDs”

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Shreya Jha

Nishakar Thakur

Lukram Slim

Partha Haldar

References

People who inject drugs. 2024. https://www.who.int/teams/global-hiv-hepatitis-and-stis-programmes/populations/people-who-inject-drugs

Magnitude_substance_abuse_India.pdf . 2024. https://www.lgbrimh.gov.in/resources/Addiction_Medicine/elibrary/magnitude_substance_abuse_india.pdf

NACO and ICMR-NIMS . India HIV estimates. NACO, MoHFW, GOI. Available from: https://naco.gov.in/sites/default/files/India%20HIV%20Estimates%202021%20_Fact%20Sheets__Final_Shared_24_08_2022_0.pdf. 2021.

National Control

AIDS

. Organisation. Sankalak: Status of National AIDS & STD Response. Sixth edition, 2024. New Delhi: NACO: Ministry of Health and Family Welfare, Government of India, 2024.

Pragna

Patel

Craig Borkowf

John Brooks

, et al. Estimating per-act HIV transmission risk: a systematic review. AIDS. 2014 June 19; 28(10): 1509–1519. doi:10.1097/QAD.0000000000000298.

Fast-track - Ending the AIDS epidemic by 2030. Available from: https://www.unaids.org/en/resources/documents/2014/JC2686_WAD2014report

High risk groups and bridge population . National AIDS Control organization. HSS Plus, 2021.

Malsagova

Kopylov

Stepanov

, et al. Dried blood spot in laboratory: directions and prospects. Diagn Basel Switz 2020; 10(4): 248.

National AIDS Control Organization . HRG 2021 report. https://naco.gov.in

10.

Degenhardt L

Peacock

, et al. Correction to LanGlobal prevalence of injecting drug use and sociodemographic characteristics and prevalence of HIV, HBV, and HCV in people who inject drugs: a multistage systematic review.cet Glob Health 2017. Lancet Global Health 2018; 6(1): e36.

11.

Ezell

Ompad

Walters

. How urban and rural built environments influence the health attitudes and behaviors of people who use drugs. Health Place 2021; 69: 102578.

12.

Reyes

Ahn

Thurber

, et al. Urbanization and infectious diseases: general principles, historical perspectives, and contemporary challenges. Chall Infect Dis 2012; 123–146.

13.

Revamped and revised elements of targeted intervention for HIV prevention and care continuum among core population. New Delhi. National AIDS Control Organisation; 2019. https://naco.gov.in/sites/default/files/TIStrategyDocument_25thJuly2019_Lowres.pdf

14.

Carneiro

Fuller

Doherty

, et al. HIV prevalence and risk behaviors among new initiates into injection drug use over the age of 40 years old. Drug Alcohol Depend 1999; 54(1): 83–86.

15.

. Child sexual abuse: management and prevention, and protection of children from sexual offences (POCSO) act. Indian Pediatr 2017; 54(11): 949–953. https://pubmed.ncbi.nlm.nih.gov/29217802/

16.

Solomon

Monica

Srikrishnan

, et al. The profile of injection drug users in Chennai, India: identification of risk behaviours and implications for interventions. Subst Use Misuse 2010; 45(3). https://pubmed.ncbi.nlm.nih.gov/20141452/

17.

Syringe services programs | prevent | effective interventions | HIV/AIDS | CDC. CDC. https://www.cdc.gov/hiv/effective-interventions/prevent/syringe-services-programs/index.html

18.

Yeh

Yang

Kennedy

, et al. The impact of needle and syringe exchange programs on HIV-related risk behaviors in low- and middle-income countries: a systematic review and meta-analysis examining individual- versus community-level effects. AIDS Behav 2023; 27(10): 3306–3331.

19.

Paquette

Syvertsen

Pollini

. Stigma at every turn: health services experiences among people who inject drugs. Int J Drug Pol 2018; 57: 104–110.