Prevalence and correlates of SARS-CoV-2 seropositivity among people who inject drugs in the San Diego-Tijuana border region.

BACKGROUND: People who inject drugs may be at elevated SARS-CoV-2 risk due to their living conditions and/or exposures when seeking or using drugs. No study to date has reported upon risk factors for SARS-CoV-2 infection among people who inject drugs. METHODS AND
FINDINGS: Between October, 2020 and June, 2021, participants aged ≥18 years from San Diego, California, USA and Tijuana, Baja California, Mexico who injected drugs within the last month underwent interviews and testing for SARS-CoV-2 RNA and antibodies. Binomial regressions identified correlates of SARS-CoV-2 seropositivity.
RESULTS: Of 386 participants, SARS-CoV-2 seroprevalence was 36.3% (95% CI: 31.5%-41.1%); 92.1% had detectable IgM antibodies. Only 37.5% had previously been tested. Seroprevalence did not differ by country of residence. None tested RNA-positive. Most (89.5%) reported engaging in ≥1 protective behavior [e.g., facemasks (73.5%), social distancing (46.5%), or increasing handwashing/sanitizers (22.8%)]. In a multivariate model controlling for sex, older age, and Hispanic/Latinx/Mexican ethnicity were independently associated with SARS-CoV-2 seropositivity, as was engaging in sex work (AdjRR: 1.63; 95% CI: 1.18-2.27) and having been incarcerated in the past six months (AdjRR: 1.49; 95% CI: 0.97-2.27). Comorbidities and substance using behaviors were not associated with SARS-CoV-2 seropositivity.
CONCLUSIONS: In this community-based study of people who inject drugs in the San Diego-Tijuana border region, over one third were SARS-CoV-2 seropositive, exceeding estimates from the general population in either city. We found no evidence that substance use behaviors were associated with an elevated risk of SARS-CoV-2 infection, but observed that circumstances in the risk environment, notably sex work and incarceration, were independently associated with higher SARS-CoV-2 seroprevalence. Our findings suggest that a binational policy response to COVID-19 mitigation is warranted beyond the closure of the U.S.-Mexico border. Furthermore, decriminalizing sex work and drug use could reduce the burden of COVID-19 among people who inject drugs.

Introduction

The disproportionate burden of COVID-19 on under-represented minorities is well documented [1-3]. Substance users may also experience greater COVID-19 related morbidity and mortality. An analysis of data from the U.S. National Survey on Drug Use and Health found that those with opioid and methamphetamine use disorders were more likely to have underlying conditions identified as risk factors for COVID-19 severity and mortality [4]. A recent study found that compared to other patients, people with substance use disorders were more likely to experience breakthrough infections following COVID-19 vaccination, due at least in part to the high prevalence of comorbid conditions [5].

Data are lacking on whether people with substance use disorders are more vulnerable to acquiring and transmitting SARS-CoV-2 due to their living conditions (e.g., homelessness, incarceration) and drug-related behaviors (e.g. smoking, vaping, sharing drug paraphernalia, sex work) [6,7]. In a U.S. nation-wide study, those with substance use disorders, especially African Americans and opioid users, were at increased risk of COVID-19 [8]. However, this study could not determine whether these factors were independently associated with COVID-19 diagnosis since risk factor data were not available, and the sample was restricted to patients accessing health care. In a telephone survey of active and former drug injectors in Baltimore, Maryland, compared to former substance users, those who were actively using substances were less likely to report social distancing, which could increase their risk of acquiring SARS-CoV-2 [7]. In an online survey of adults residing in the Northeastern U.S., daily users of opioids and alcohol were less likely to adhere to COVID-19 related stay-at-home orders, and stimulant users were more likely to report having tested positive for SARS-CoV-2 [9]. There are also reports that the COVID-19 pandemic has interrupted global drug supplies as well as harm reduction and addiction treatment services, which could alter drug use patterns [10,11].

Reports in the literature of SARS-CoV-2 prevalence among people who inject drugs are sparse. In a study of needle exchange clients in Stockholm, Sweden, SARS-CoV-2 prevalence was 5.4% [12], whereas in a survey of people who inject drugs in England, Wales and Northern Ireland, 11% reported that they had tested positive for COVID-19 [13]. U.S. estimates among people who are homeless or living in shelters range from 2%-14% [14-16]. We could not identify any publications that reported risk factors for SARS-CoV-2 among people who inject drugs.

As the eighth largest city in the U.S. and the largest situated on the Mexico-US border, San Diego County, California is home to approximately 1.42 million people. Its counterpart in Baja California, Mexico is Tijuana, a city of ~1.5 million people, located twenty minutes from San Diego and located on a major drug trafficking route. In an attempt to limit SARS-CoV-2 transmission, the U.S.-Mexico border was closed to essential travel on March 21, 2020 and remained closed for the eight months duration of the study. Modeling of the SARS-CoV-2 epidemic in San Diego County suggests that prevalence was below 5% through July, 2020 then increased to approximately 20% by January, 2021 (California Department of Public Health, unpublished data). In a household study conducted in Tijuana in February 2021, SARS-CoV-2 seroprevalence was 21% [17].

Most epidemiologic research on COVID-19 has been conducted on inpatient samples and has focused on upper-income countries. We studied prevalence and correlates of SARS-CoV-2 infection in a binational community-based study of people who inject drugs residing in San Diego and Tijuana. We hypothesized a priori that residents of San Diego who had recently crossed the border to inject drugs in Tijuana and those who were homeless, traded sex or injected drugs more often would be more likely to test SARS-CoV-2 seropositive.

Materials and methods

Participants and eligibility

Data collection took place between October 28, 2020 and June 16, 2021 in San Diego and Tijuana by trained interviewers who were residents of either city, using street outreach and mobile vans.

A short screener was used to identify participants who were eligible for study participation. Eligible participants were required to be aged ≥18 or older, report injecting drugs within the last month (as evidenced through injection stigmata) and report living in San Diego County or Tijuana. We sought to enroll participants residing in San Diego who reported having crossed the border to inject drugs in Tijuana within the last two years as well as those from either city who reported not having used illicit drugs on the other side of the border.

Data collection

After screening was conducted, eligible participants provided written informed consent and underwent interviewer-administered surveys at baseline and approximately one week later to minimize participant burden. Computer assisted personal interviewing was used to minimize socially desirable responding. Interviews were conducted in person, with plexiglass dividers separating the interviewer and participant, who were both required to wear facemasks.

Survey measures

Survey items were developed based on a previous study [18], as well as the C3PNO study [19] (refer to Supplemental Materials). Measures included sociodemographics, potential COVID-19 exposures (e.g., injection and non-injection drug use, sharing injection equipment, incarceration, sex work), vulnerabilities (e.g., homelessness, cross-border, mobility, food insecurity [8,20], impact of COVID-19 on income and housing), and protective behaviors (e.g., social distancing, use of facemasks and handwashing/sanitizers). Before beginning data collection, the survey was translated into Spanish, back-translated into English, and verified for accuracy by bilingual team members. To eliminate duplicate enrollments, identifying information was collected from participants as well as photographs, which were stored separately from survey data in encrypted, password protected files. Participants were compensated $20 USD and were provided with photo ID cards embossed with the study logo and contact information. Protocols were approved by the Human Research Protections Program and Biosafety Committee at the University of California San Diego (UCSD) and the institutional review board at Xochicalco University.

Biological measures

Venous blood samples were obtained by trained phlebotomists to conduct serology for SARS-CoV-2, HIV and HCV. Pre- and post-test counseling was provided following national guidelines in the U.S. and Mexico. Rapid testing for HIV and HCV was done during the study visit, enabling participants to immediately obtain their test results. Biological samples were batched and stored at -80 degrees Celsius and shipped weekly on dry ice for SARS-CoV-2 RNA and antibody detection.

HIV and HCV serology

Rapid HIV and HCV tests were conducted by trained study staff using the Miriad® HIV/HCV Antibody InTec Rapid Anti-HCV Test (Avantor, Radnor, PA). Reactive and indeterminate tests underwent a second rapid test with Oraquick® HIV or Oraquick® HCV, respectively (Orasure, Bethlehem, PA). HIV and HCV rapid test reactive were sent for confirmatory testing at UCSD’s Center for AIDS Research (CFAR) laboratory.

SARS-CoV-2 RNA detection

Participants were instructed on how to self-collect anterior nasal swabs in the presence of study staff. Swabs which were placed in 3mL of viral transport media for temporary storage, before being shipped for testing at the UCSD CFAR laboratory. RT-PCR was conducted using a pooling approach based on the Fluxergy system® (Irvine, CA) to detect SARS-CoV-2 RNA.

SARS-CoV-2 antibody detection

Serology was conducted by Genalyte® (San Diego, CA), using their Maverick™ Multi-Antigen Serology Panel [21] that detects IgG and IgM antibodies to five SARS-CoV-2 antigens (Nucleocapsid, Spike S1-S2, Spike S1, Spike S1-RBD, Spike S2) within a multiplex format based on photonic ring resonance. A machine learning algorithm was used to call results using the Random Forest Ensemble method with 3000 decision trees [22].

Statistical analysis

SARS-CoV-2 prevalence was calculated with 95% confidence intervals (CIs) based on the Binomial distribution. Those testing indeterminate were excluded. The Cochran-Armitage test was used to assess trends in SARS-CoV-2 seroprevalence.

Characteristics of participants testing SARS-CoV-2 seropositive versus seronegative were compared using Wilcoxon Rank Sum for continuous variables and Chi-square or Fisher’s Exact tests for categorical variables. Univariate and multivariable binomial regressions with robust standard error estimation via generalized estimating equations were performed to identify factors associated with SARS-CoV-2 seropositivity. Variables attaining <10% significance were considered for inclusion in multivariable models. All potential interactions between variables in the final model were assessed. Multi-collinearity was assessed using diagnostics such as largest condition index and variance inflation factors. Although site-specific models were examined, results were presented for the overall sample since associations were generally similar. All analyses were conducted using SAS version 9.4.

Role of funding source

The funders had no involvement in the study design, collection, analysis, interpretation or writing of this report, nor the decision to submit the paper for publication.

Results

Biologic testing

Of 405 participants tested, none had detectable SARS-CoV-2 RNA. Considering serologic evidence of SARS-CoV-2 infection, 19 (4.7%) tested indeterminate and were excluded from further analysis. These participants did not differ significantly from those who were included, with the exception that those testing indeterminate were less likely to inject heroin compared to the remainder of participants (68.4% vs. 87.4%, P = 0.04). Detectable SARS-CoV-2 IgG and/or IgM antibodies were observed in 36.3% [95% confidence interval (95% CI): 31.5%-41.1%], of whom the majority had IgM (92.1%). Of the 140 testing SARS-CoV-2 seropositive, only 37.5% had previously been tested, and 26.8% reported ≥1 current symptom consistent with COVID-19. There was no significant trend in seroprevalence over time (p = 0.80).

Descriptive statistics

Of the 386 subjects included in the analysis, 63.5% lived in San Diego County. Most were male (74.1%) and Hispanic/Latinx/Mexican (71.5%). Median age was 43 (inter-quartile range [IQR: 35–51]. Over half reported that COVID-19 had adversely affected their housing or income. During the last six months, 39.1% were homeless, 8.3% were incarcerated and 12.4% traded sex (Table 1). Of the San Diego residents, 50.8% reported having crossed the border to inject drugs in Tijuana within the last six months.

Table 1

Characteristics associated with SARS-CoV-2 Sero-positivity among people who inject drugs in San Diego, California and Tijuana, Mexico.

Baseline Characteristics	SARS-CoV-2 Seropositive N = 140	SARS-CoV-2 Seronegative N = 246	Total N = 386	Univariate RR (95% CI)
Sociodemographics
Male	104(74.3%)	182(74.0%)	286(74.1%)	1.01 (0.75,1.37)
Median Age (IQR)P	45.0(37.0,53.0)	42.0(34.0,50.0)	43.0(35.0,51.0)	1.02 (1.00,1.03)¥
Hispanic/Latinx/MexicanP	111(79.3%)	165(67.1%)	276(71.5%)	1.53 (1.08,2.15)
Speaks English	98(70.0%)	185(75.2%)	283(73.3%)	0.85 (0.64,1.13)
Born in the US	61(43.6%)	129(52.4%)	190(49.2%)	0.80 (0.61,1.04)
Primary residence in San Diego	88(62.9%)	157(63.8%)	245(63.5%)	1.00 (0.96,1.04)
Highest year of school completed (IQR)	11.0(8.0,12.0)	11.0(7.0,12.0)	11.0(7.0,12.0)	0.92 (0.65,1.30)
Married or common law	25(17.9%)	49(19.9%)	74(19.2%)	1.02 (0.78,1.33)
Average monthly income <500 USD	75(53.6%)	130(52.8%)	205(53.1%)	0.97 (0.74,1.28)
Median years lived in Study Location (IQR)	30.0(10.0,45.0)	26.5(10.0,40.0)	28.0(10.0,41.0)	1.01 (1.00,1.01)¥
Potential Exposures
Homeless*	50(35.7%)	101(41.1%)	151(39.1%)	0.86 (0.65,1.14)
Incarcerated*P	16(11.5%)	16(6.5%)	32(8.3%)	1.43 (0.99,2.09)
Median # of people in household (IQR)*	2.0(1.0, 4.0)	2.0(1.0, 5.0)	2.0(1.0, 4.0)	1.00 (1.00,1.00)¥
Low/very low food security	88(78.6%)	171(80.3%)	259(79.7%)	0.93 (0.65,1.34)
Engaged in sex work*P	25(17.9%)	23(9.3%)	48(12.4%)	1.53 (1.12,2.09)
Client of sex worker*	8(5.7%)	10(4.1%)	18(4.7%)	1.24 (0.73,2.11)
Exposed to someone with COVID-19	6(5.4%)	12(5.6%)	18(5.5%)	0.97 (0.49,1.89)
Impact of Pandemic
Housing situation worse	91(65.0%)	140(56.9%)	231(59.8%)	1.25 (0.94,1.65)
Income worse	98(70.5%)	149(62.3%)	247(65.3%)	1.27 (0.94,1.71)
Substance Use
Smokes cigarettes	118(84.3%)	222(90.2%)	340(88.1%)	0.73 (0.52,1.01)
Smoked or vaped marijuana*	67(47.9%)	139(56.5%)	206(53.4%)	0.80 (0.62,1.04)
Smoked/snorted/inhaled heroin*P	32(22.9%)	73(29.7%)	105(27.2%)	0.79 (0.57,1.10)
Smoked/snorted/inhaled/vaped meth*	86(61.4%)	150(61.0%)	236(61.1%)	1.01 (0.77,1.33)
Smoked/snorted/inhaled crack/cocaine*	15(10.7%)	22(8.9%)	37(9.6%)	1.13 (0.75,1.71)
Injected heroin*	123(87.9%)	222(90.2%)	345(89.4%)	0.86 (0.58,1.27)
Injected fentanyl*	27(19.3%)	50(20.3%)	77(19.9%)	0.96 (0.68,1.34)
Median age at first injection	20.0(17.0,27.0)	19.0(17.0,25.0)	20.0(17.0,26.0)	1.01 (0.99,1.02)
#Times injected drugs per day	2.5(0.3, 4.0)	2.5(0.7, 4.0)	2.5(0.3, 4.0)	0.94 (0.87,1.02)¥
Visited shooting galleries*	12(8.6%)	19(7.7%)	31(8.0%)	1.07 (0.67,1.71)
Used hit doctor*	25(17.9%)	46(18.8%)	71(18.4%)	0.96 (0.68,1.36)
Crossed border to inject drugs*	60(42.9%)	97(39.4%)	157(40.7%)	1.09 (0.84,1.43)
Co-Morbidities
HIV-antibody positive	15(10.7%)	17(6.9%)	32(8.3%)	1.33 (0.89,1.97)
HCV-antibody positive	47(33.6%)	86(35.1%)	133(34.5%)	0.96 (0.72,1.27)
DiabetesY	5(4.5%)	10(4.7%)	15(4.6%)	0.97 (0.46,2.01)
AsthmaY	8(7.1%)	22(10.3%)	30(9.2%)	0.76 (0.41,1.40)
HypertensionY	13(11.6%)	25(11.7%)	38(11.7%)	0.99 (0.62,1.58)
Preventive Measures
Practiced social distancingY	52(46.4%)	99(46.5%)	151(46.5%)	1.00 (0.74,1.35)
Wore face maskY	85(75.9%)	154(72.3%)	239(73.5%)	1.13 (0.79,1.62)
Increased handwashing/sanitizerY	24(21.4%)	50(23.5%)	74(22.8%)	0.93 (0.64,1.34)
Stocked up on drugsY	18(16.1%)	35(16.5%)	53(16.4%)	0.98 (0.65,1.47)
Stocked up on harm reduction suppliesY	24(21.4%)	38(17.9%)	62(19.1%)	1.15 (0.81,1.65)
Stopped smoking (current smokers)YP	6(6.3%)	4(2.1%)	10(3.5%)	1.86 (1.09,3.17)
Avoided sharing drug paraphernaliaY	11(9.8%)	18(8.5%)	29(9.0%)	1.11 (0.68,1.81)
Engaged in ≥1 protective behaviorY	101(90.2%)	190(89.2%)	291(89.5%)	1.07 (0.64,1.79)
Had a prior COVID-19 testYP	42(37.5%)	63(29.6%)	105(32.3%)	1.26 (0.93,1.70)

*past 6 months

YMissing values n = 62

¥Per year increase

PP-value<0.10.

Although 89.5% reported engaging in ≥1 protective behavior [e.g., face masks (73.5%)], only 46.5% reported social distancing, 22.8% increased handwashing/hand sanitizers, and 9.0% reported avoiding sharing drug paraphernalia in the prior six months (Table 1).

Bivariate analyses

Older age and identifying as Hispanic, Latinx, or Mexican were significantly associated with SARS-CoV-2 seropositivity (Table 1). Considering potential community exposures in the past six months, those engaging in sex work were significantly more likely to test seropositive compared to those who did not (17.9% vs. 9.3%, p = 0.01, [Relative Risk (RR): 1.53; 95% CI: 1.12–2.09]. Being incarcerated was associated with marginally higher SARS-CoV-2 seropositivity (RR: 1.43; 95% CI: 0.99–2.09). We did not observe injection drug use, smoking, vaping specific drugs or any other substance use behaviors to be associated with seroprevalence, nor were any co-morbidities (i.e., HIV, HCV, Type 2 diabetes, hypertension). Protective behaviors were not significantly associated with SARS-CoV-2 serostatus, with the exception that those testing SARS-CoV-2 seropositive were more likely to report having stopped smoking in the last six months and to have had a COVID-19 test.

Multivariate analysis

In a multivariate model that controlled for sex (Table 2), each year in age was associated with a 2% increase in SARS-CoV-2 seropositivity (Adjusted relative risk (AdjRR): 1.02; 95% CI: 1.01–1.03). Identifying as Hispanic/Latinx/Mexican was also independently associated with SARS-CoV-2 seropositivity (AdjRR: 1.53; 95% CI: 1.09–2.15), as was engaging in sex work in the past six months (adjRR: 1.63; 95% CI: 1.18–2.27). Being incarcerated in the last six months remained marginally significant (AdjRR: 1.49; 95% CI: 0.97–2.27). When country of residence was forced into the model, all significant associations held except ethnicity. Excluding the nine participants who reported having received at least one COVID-19 vaccine did not appreciably change parameter estimates.

Table 2

Factors Independently associated with SARS-CoV-2 Seropositivity among people who inject drugs in San Diego, CA and Tijuana, Mexico.

Baseline Characteristics	Adjusted RR** (95% CI)
Male	1.02 (0.76, 1.37)
Age¥	1.02 (1.01, 1.03)
Hispanic/Latinx/Mexican	1.53 (1.09, 2.15)
Engaged in sex work*	1.63 (1.18, 2.27)
Incarcerated*	1.49 (0.97, 2.27)

*past 6 months

**variables in the multivariable model were adjusted for all the variables in the model.

¥ Per year increase.

Given that sex work was independently associated with SARS-CoV-2 seropositivity, we examined this subgroup more closely. Compared to non-sex workers, sex workers were just as less likely report protective behaviors but were significantly more likely to report being exposed to someone with COVID-19 (20% vs. 3.8%, p = 0.001) or to have low/very low food security (94.3% vs. 77.9% p = 0.02).

Discussion

In this community-based study of people who inject drugs in the San Diego-Tijuana border region, over one third had detectable SARS-CoV-2 antibodies, which exceeds estimates from the general population in either city [17]. This suggests that a binational policy response to COVID-19 is warranted beyond the closure of the U.S.-Mexico border. We did not observe substance use behaviors, such as smoking, vaping, or use of specific drugs such as opiates or stimulants to be associated with an elevated risk of SARS-CoV-2 infection, as others have hypothesized [9]. Instead, we observed that circumstances in the risk environment, notably sex work and incarceration, were independently associated with higher SARS-CoV-2 seroprevalence.

To our knowledge, this is the first study to show that sex work is independently associated with higher SARS-CoV-2 seroprevalence after controlling for potential confounders such as sex, age, and ethnicity. In an unpublished study in Denmark, SARS-CoV-2 seroprevalence was higher among sex workers (12.2%) than people experiencing homelessness (6.8%) or the general population (2.9%) [23], but the independent effects of these and other factors were not assessed.

Although the majority of our sample reported that COVID-19 had greatly affected their income and housing, sex workers may have faced additional hardships following the closure of the U.S.-Mexico border because of their reliance on sex tourism, and since social distancing is not possible during sexual transactions. Compared to the rest of the sample, significantly higher proportions of sex workers reported low or very low food security, and they were more likely to report having been exposed to someone with COVID-19 than others. This suggests that sex workers may have engaged in higher risk behaviors to support themselves, placing them at greater risk of SARS-CoV-2 infection. In a study of female sex workers in Kenya, sexual transactions declined during the pandemic [24] and those most reliant on sex work reported greater food insecurity, which is consistent with our findings. Among female sex workers in Nigeria, those who had knowledge about COVID-19 were significantly more likely to wear face masks, but less than half did so [25].

Despite concerns about sex workers’ vulnerability to COVID-19, few countries provide them aid [24,26]. In Thailand, the Netherlands and Japan, sex workers were included in COVID-19 government-sponsored support programs [26], but they are excluded in countries where sex work is criminalized, such as the U.S. Although sex work is quasi-legal in Tijuana’s red light district, those using drugs are less likely to obtain sex work permits and instead work outside of commercial establishments that could offer protections [27]. In an earlier study, we found that female sex workers in Tijuana who inject drugs were more vulnerable to offers of unprotected sex in exchange for more money or drugs compared to those that did not inject [28].

Our finding that recent incarceration was independently associated with SARS-CoV-2 seropositivity could reflect institutional exposures. Over-crowding was implicated in COVID-19 outbreaks in California correctional institutions [29], including those in the U.S.-Mexico border region. Mitigation included early release, halting intakes, and eliminating bail, but a recent analysis suggests that considerable potential for SARS-CoV-2 exposures persists, at least in the California prison system [29]. Similar measures have not been undertaken in Baja California. Taken together, our findings suggest that decriminalization of drug use and sex work and increasing their access to social protection programs could reduce SARS-CoV-2 risk among people who inject drugs and sex workers, as others have proposed [26,30].

SARS-CoV-2 seroprevalence did not differ by country of residence in our study, perhaps reflecting close social ties between San Diego and Tijuana communities despite the closure of the U.S.-Mexico border. In a phylogenetic analysis of SARS-CoV-2 sequences from the U.S. and Mexico, those obtained from the Mexican state of Baja California were more closely related to San Diego than to Mexico City [31]. Although one half of the San Diego residents in our study had crossed the border and injected drugs in Tijuana in the last six months, we found no evidence that cross-border mobility was associated with SARS-CoV-2 seropositivity.

Consistent with other studies, subjects who were older [8] and who identified as Hispanic, Latinx, or Mexican [2] were significantly more likely to test SARS-CoV-2 seropositive. This demonstrates that even among the lowest socioeconomic strata in the US and Mexico, ethnic disparities in SARS-CoV-2 seroprevalence persist.

Our study also found that over half of those testing SARS-CoV-2 seropositive had not been tested prior to study enrolment. These findings underscore the need to improve community outreach to provide testing, vaccines, and treatment, for example using mobile syringe exchange programs.

Limitations

Our ability to detect some associations was limited due to statistical power. Ours was a non-random sample and the cross-sectional study design precludes drawing causal inferences. Participants experiencing symptoms may have changed behaviors, such as stopped smoking or sought COVID-19 testing. Some misclassification may have also occurred since behaviors such as current and past substance use were self-reported.

Of note, none of the self-collected swabs tested positive for SARS-CoV-2 RNA. The sensitivity of the pooling approach could have been impacted by: 1) the viral load of any particular infected individual; 2) the consistency with which swabs were obtained; 3) storage, shipping, and transport conditions; or 4) of diluting out (via pooling) any viral SARS-CoV-2 RNA collected below the limit of detection. In this study, we limited our pools to ≤10 swabs, and previously validated our approach with up to 30 samples per pool where the limit of detection was estimated at 2.4 copies/μL [32]. Therefore, it is unlikely that we experienced loss of sensitivity due to pooling.

Since SARS-CoV-2 antibodies may wane over time especially among patients who are asymptomatic or mildly symptomatic [33,34], infections that occurred earlier in the epidemic may have gone undetected. However, the majority of participants testing SARS-CoV-2 seropositive had detectable IgM antibody titers, which is suggestive of recent infection [35]. Some misclassification could have occurred among those testing indeterminate who were recently infected, but these were few in number and would have tended to underestimate SARS-CoV-2 prevalence, dampening any observed associations.

Since COVID-19 vaccines did not become available to adults 18–65 years of age in San Diego County until May 15, 2021 and were not available to most adults in Tijuana until after the study period ended, we were unable to examine the impact of vaccination on SARS-CoV-2 infection. Nevertheless, among the 75 San Diego residents in our sample who were interviewed after May 15, only 9 (9.3%) reported having received at least one COVID-19 vaccine dose. In comparison, the proportion of adults aged ≥18 years who had received at least one COVID-19 vaccine dose in San Diego County through June 24, 2021 exceeded 50% [36].

Conclusions

We found that most people who inject drugs in the San Diego-Tijuana border region engaged in preventive measures to avoid SARS-CoV-2, but since over one-third had evidence of infection, a binational policy response is warranted beyond the closure of the U.S.-Mexico border. Importantly, social and structural factors in the risk environment were independently associated with SARS-CoV-2, and substance use behaviors were not, suggesting that structural interventions such as decriminalizing sex work and drug use and increasing their access to social protection programs could reduce vulnerability to SARS-CoV-2 among people who inject drugs. Since the proportion of participants who had previously been tested for SARS-CoV-2 or had received COVID-19 vaccine was very low, efforts are needed to mitigate risks and provide COVID-19 testing and vaccines this vulnerable population.

La Frontera protocol.

(DOCX)

Click here for additional data file.

La Frontera baseline and supplemental surveys.

(PDF)

Click here for additional data file.

La Frontera data set.

(SAS7BDAT)

Click here for additional data file.

Transfer Alert

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15 Oct 2021

PONE-D-21-25385Prevalence and Correlates of SARS-CoV-2 Seropositivity among People who Inject Drugs in the San Diego-Tijuana Border RegionPLOS ONE

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Reviewer #1: Yes

Reviewer #2: No

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript makes an important contribution to the COVID literature among the PWID population with high rates of sex work. One important finding is that injection drug use or other substance use behaviors were not associated with seroprevalence; rather circumstances in the risk environment, notably sex work and incarceration, were associated with significantly higher SARS-CoV-2 seroprevalence.

Several clarification and suggestions are below:

• Clarification on recruitment: The authors indicated that street-based recruiting was used between October 28, 2020 and June 16, 2021 (a period when the border was closed to essential travel). It’s unclear how recruitment was done for participants in Tijuana and “those from either city who reported not having used illicit drugs on the other side of the border”. Was all recruitment done in San Diego?

• Clarification needed on “personal interviewing” – were individuals interviewed in person during this period? Or via Zoom?

• Did the study collect identifiers in order to ascertain duplicate enrollments?

• In the limitations section, the authors reported the majority of participants had IgM; however, this is not reported in the results. Given that there were no active infections reported in the sample, it would be interesting to report how many (if any) were individuals had only IgM and not IgG as an estimate of recent infection.

• Minor: The recruitment period includes a few months where individuals may have gotten vaccinations. While most antibody tests were not designed to specifically detect antibodies as a result of vaccination, is the possible that particular antibody tests used may have yielded a false positive? This would be easily seen if the 9 individuals who reported if the participant were all positive relative to the rest of the sample. In the limitations section, the authors reported on the vaccinated portions of the sample, but not in the results. Nonetheless, the authors did report that excluding nine participants who reported having received at least one COVID-19 vaccine did not appreciably change parameter estimates in multivariable analysis.

• Minor Suggestion: Table 1 reports column %, which provide snapshot of the sample distribution. It would be interesting to more directly compare sub-groups (row%). One suggestion would be just to the univariate RR from Table 2 to Table 1.

Reviewer #2: Thank you for giving me the opportunity to review the manuscript titled “Prevalence and Correlates of SARS-CoV-2 Seropositivity among People who Inject Drugs in the San Diego- Tijuana Border Region.” This manuscript presents relevant information related to the prevalence and correlates of SARS-CoV-2 in PWID, a vulnerable population at increased risk for infection and increased morbidity and mortality. This study is innovative in terms that it provides novel information related to PWID living in an understudied region and at an increased vulnerability. However, there are some issues in this paper that limit my enthusiasm.

Introduction

Overall, this section is extremely short and does not provide the background necessary to understand why this research study exploring the prevalence and correlates of SARS-CoV-2 among people who inject drugs is necessary.

I recommend including estimates and correlates of SARS-CoV-2 obtained from earlier studies involving people with substance use disorder. I would also suggest including the limitations in earlier research studies (e.g., mostly conducted in developed countries), which would strengthen the Introduction section.

The Introduction section should highlight the fact that SARS-CoV-2 could be a serious threat to health among those people who use drugs.

There is not a lack of data on the effects of SARS-CoV-2 on people with substance use disorders. In fact, there is a growing amount of research focusing on this topic. It would be important to reframe the second sentence and specify in which specific area lacks data.

Methods

There are several aspects related to the study procedures that are ambiguous. The order of the assessments is unclear. It would be very helpful to include a paragraph describing the order of the assessments.

The inclusion criteria are unclear for participating in this study. It is presented that individuals who recently injected any drugs (within 30 days) are eligible, but also those who injected drugs in the last two years as well as those who reported not having used illicit drugs. I would recommend listing the inclusion and exclusion criteria to improve readability.

Did the participants provide written informed consent?

It would be important to cite where the questionnaire came from.

Participants self-collected nasal swabs. Were these participants trained in the use of the swabs to ensure they were collecting the biological samples correctly?

There is no description of when and by whom the SARS-CoV-2 antibody, HIV, and HCV serology tests were conducted.

Data analyses

It would be interesting to explore whether the characteristics of the participants with inconclusive SARS-CoV-2 results differ from those with positive results.

Results

I suggest some editing in this section to improve readability. It would be helpful to focus one paragraph only describing the overall sample, then another presenting the bivariate analyses, and a final one describing the multivariate analyses.

Discussion

This section provides information that would have been useful in the Introduction section to provide a background on the topic. This includes the prevalence and correlates of SARS-CoV-2.

This section presents 7 different findings obtained from the current study. It is unclear what the take home message is. I would suggest rewording and reorganizing this section to focus on the most relevant findings.

It should be noted that the reasons for these 7 different findings are not fully described.

Recent or past drug use is self-reported. This should be included as a study limitation.

Conclusions

The conclusions section does not fully mirror what is presented in the Discussion section and reads as a different paper. This last paragraph should focus on the findings related to the prevalence of SARS-CoV-2 and its correlates among PWID. The additional information is distracting.

Minor comments:

- Remove “a priori” from the sentence “We hypothesized a priori that…”

- Include the software used to conduct the data analyses

**********

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Reviewer #2: Yes: Irene Pericot-Valverde

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27 Oct 2021

Editorial Revisions

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: We have adhered to the journal’s requirements.

2. Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information.

Furthermore, please provide additional information regarding the steps taken to validate the questionnaire.

Response: We have uploaded English and Spanish versions of the baseline and supplemental survey as supporting information, and have indicated this in the text. Please note that the survey was formatted so it could be programmed into QDS (CAPI software) and the format of the surveys we are providing are not intended to be administered with pencil and paper.

The sociodemographic and behavioral components of the survey was based on previous items used in an earlier study (Proyecto El Cuete). Some of the COVID-19 questions were obtained from the CP30 study (c3pno-covid-19-survey-measures (2).pdf ). The Spanish version of the survey was back-translated into English and reviewed for accuracy. We have added these details to the text and provided citations for validated scales that were assessed in this study (e.g., food insecurity).

3. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

Response: We have made corrections so these statements now match.

4. We note that you have referenced (California Department of Public Health, unpublished data which has currently not yet been accepted for publication. Please remove this from your References and amend this to state in the body of your manuscript: (ie “California Department of Public Health [Unpublished]”) as detailed online in our guide for authors

http://journals.plos.org/plosone/s/submission-guidelines#loc-reference-style.

Response: We have removed this source from the reference list as requested.

5. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Response: No citations were retracted. The reference list is complete.

Review Comments to the Author

Reviewer #1: The manuscript makes an important contribution to the COVID literature among the PWID population with high rates of sex work. One important finding is that injection drug use or other substance use behaviors were not associated with seroprevalence; rather circumstances in the risk environment, notably sex work and incarceration, were associated with significantly higher SARS-CoV-2 seroprevalence.

Several clarification and suggestions are below:

1. Clarification on recruitment: The authors indicated that street-based recruiting was used between October 28, 2020 and June 16, 2021 (a period when the border was closed to essential travel). It’s unclear how recruitment was done for participants in Tijuana and “those from either city who reported not having used illicit drugs on the other side of the border”. Was all recruitment done in San Diego?

Response: The closure of the border did not interrupt data collection. Recruitment was done in both San Diego and Tijuana using staff who were residents of the respective cities. We have clarified this in the text.

2. Clarification needed on “personal interviewing” – were individuals interviewed in person during this period? Or via Zoom?

Response: Interviews were conducted in person. We added the following sentence to clarify:

“Interviews were conducted in person, with plexiglass dividers separating the interviewer and participant, who were both required to wear facemasks.”

3. Did the study collect identifiers in order to ascertain duplicate enrollments?

Response: Identifying information was collected as well as photographs of participants to eliminate duplicate enrolments. We added this text to the Methods.

4. In the limitations section, the authors reported the majority of participants had IgM; however, this is not reported in the results. Given that there were no active infections reported in the sample, it would be interesting to report how many (if any) were individuals had only IgM and not IgG as an estimate of recent infection.

Response: Unfortunately, Genalyte does not separate IgM and IgG serology in their reports, so we could make this information available. We report in the text that that 92% had detectable IgM antibodies.

5. Minor: The recruitment period includes a few months where individuals may have gotten vaccinations. While most antibody tests were not designed to specifically detect antibodies as a result of vaccination, is it possible that particular antibody tests used may have yielded a false positive?

Response: We consulted with the Chief Scientific Officer from Genalyte who shared that the positive predictive value for their antibody assay is 97.2%.

6. Minor Suggestion: Table 1 reports column %, which provide snapshot of the sample distribution. It would be interesting to more directly compare sub-groups (row%). One suggestion would be just to the univariate RR from Table 2 to Table 1.

Response: We have modified the tables accordingly and collapsed Tables 1 and 2.

Reviewer #2:

7. Introduction

Overall, this section is extremely short and does not provide the background necessary to understand why this research study exploring the prevalence and correlates of SARS-CoV-2 among people who inject drugs is necessary. I recommend including estimates and correlates of SARS-CoV-2 obtained from earlier studies involving people with substance use disorder.

Response: We appreciated the opportunity to expand the Introduction. As suggested, we have moved text from the Discussion reporting prevalence of SARS-CoV-2 among substance users to the Introduction. We also updated the literature review to cover research published during the three month period since our paper was prepared for submission. The introduction is now more comprehensive.

8. I would also suggest including the limitations in earlier research studies (e.g., mostly conducted in developed countries), which would strengthen the Introduction section.

Response: Thank you. We agree and added this as a limitation of the earlier studies in the Introduction.

9. The Introduction section should highlight the fact that SARS-CoV-2 could be a serious threat to health among those people who use drugs.

Response: We agree and have added this sentence to the Introduction with new accompanying references.

10. There is not a lack of data on the effects of SARS-CoV-2 on people with substance use disorders. In fact, there is a growing amount of research focusing on this topic. It would be important to reframe the second sentence and specify in which specific area lacks data.

Response. At the time our paper was submitted (early August 2021), there were few papers published on the effects of SARS-CoV-2 on people with substance use disorders. We repeated a literature review in October 2021 and revised our Introduction accordingly to include new publications that were relevant. We amended the sentence about how data are lacking as follows:

“Data is lacking about whether people with substance use disorders are more vulnerable to acquiring and transmitting SARS-CoV-2 due to their living conditions (e.g., homelessness, incarceration) and drug-related behaviors (e.g. smoking, vaping, sharing drug paraphernalia, sex work).”

Our literature review could still not identify any additional papers on risk factors for SARS-CoV-2 among persons with substance use disorders, with the exception of one paper that found that stimulant users had a higher SARS-CoV-2 prevalence. We have now clarified that this is a gap in the literature that our study attempts to fill.

11. Methods

The order of the assessments is unclear. It would be very helpful to include a paragraph describing the order of the assessments.

Response: We have clarified the order of assessments in the Methods section.

12. The inclusion criteria are unclear for participating in this study. It is presented that individuals who recently injected any drugs (within 30 days) are eligible, but also those who injected drugs in the last two years as well as those who reported not having used illicit drugs. I would recommend listing the inclusion and exclusion criteria to improve readability.

Response: We apologize for the confusion and have revised the section on eligibility to make it clearer.

13. Did the participants provide written informed consent?

Response: Yes. We have revised the sentence on informed consent to clarify that written consent was obtained.

14. It would be important to cite where the questionnaire came from.

Response: See response to #2.

15. Participants self-collected nasal swabs. Were these participants trained in the use of the swabs to ensure they were collecting the biological samples correctly?

Response: Yes. We have clarified that study participants were trained about how to collect anterior nasal swabs, which they collected in the presence of study staff.

16. There is no description of when and by whom the SARS-CoV-2 antibody, HIV, and HCV serology tests were conducted.

Response: We have clarified the timing of the tests, and indicated which were performed by study staff (i.e., rapid HIV and HCV tests) versus those that were conducted by laboratory personnel (i.e., SARS-CoV-2 antibody and RNA).

17. Data analyses

It would be interesting to explore whether the characteristics of the participants with inconclusive SARS-CoV-2 results differ from those with positive results.

Response: We compared those testing indeterminate to the remainder of the sample and found only one significant difference between these groups. We have added the following sentences to the Results section:

“Considering serologic evidence of SARS-CoV-2 infection, 19 (4.7%) tested indeterminate and were excluded from further analysis. These participants did not differ significantly from those who were included, with the exception that those testing indeterminate were less likely to inject heroin compared to the remainder of participants (68.4% vs. 87.4%, P=0.04).”

18. Results

I suggest some editing in this section to improve readability. It would be helpful to focus one paragraph only describing the overall sample, then another presenting the bivariate analyses, and a final one describing the multivariate analyses.

Response: We have re-ordered the Results section to improve readability as recommended, and have situated all of the descriptive statistics together. We also added subheadings to better organize the findings.

19. Discussion

This section provides information that would have been useful in the Introduction section to provide a background on the topic. This includes the prevalence and correlates of SARS-CoV-2.

Response: In response to Reviewer 1, we moved the text on prevalence and correlates of SARS-CoV-2 from the Discussion to the Introduction, and updated the references where needed (see response to #7).

20. This section presents 7 different findings obtained from the current study. It is unclear what the take home message is. I would suggest rewording and reorganizing this section to focus on the most relevant findings.

Response: We have taken the opportunity to re-organize the beginning of the Discussion so that the opening paragraph summarizes the main findings, as follows:

“In this community-based study of people who inject drugs in the San Diego-Tijuana border region, over one third had detectable SARS-CoV-2 antibodies, which exceeds estimates from the general population in either city. This suggests that a binational policy response to COVID-19 is warranted beyond the closure of the U.S.-Mexico border. We did not observe substance use behaviors, such as smoking, vaping, or use of specific drugs such as opiates or stimulants to be associated with an elevated risk of SARS-CoV-2 infection, as others have hypothesized. Instead, we observed that circumstances in the risk environment, notably sex work and incarceration, were associated with significantly higher SARS-CoV-2 seroprevalence.”

21. Recent or past drug use is self-reported. This should be included as a study limitation.

Response: We agree and have now specifically referred to this as a limitation.

22. Conclusions

The conclusions section does not fully mirror what is presented in the Discussion section and reads as a different paper. This last paragraph should focus on the findings related to the prevalence of SARS-CoV-2 and its correlates among PWID. The additional information is distracting.

Response: We have modified the opening paragraph of the Discussion and the Conclusions paragraph so that they are now in alignment.

23. Minor comments: Remove “a priori” from the sentence “We hypothesized a priori that…”

Response: The editor, Dr. Page, indicated in her decision letter that this sentence should remain as originally stated.

24. Include the software used to conduct the data analyses.

Response: We added a sentence at the end of the Methods section to indicate that the analysis was conducted with SAS version 9.4.

Submitted filename: PloS One response to reviewers-ss_v2.docx

Click here for additional data file.

8 Nov 2021

Prevalence and Correlates of SARS-CoV-2 Seropositivity among People who Inject Drugs in the San Diego-Tijuana Border Region

PONE-D-21-25385R1

Dear Dr. Strathdee,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Kimberly Page, PhD, MPH

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

12 Nov 2021

PONE-D-21-25385R1

Prevalence and correlates of SARS-CoV-2 seropositivity among people who inject drugs in the San Diego-Tijuana border region

Dear Dr. Strathdee:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

Dr. Kimberly Page

Academic Editor

PLOS ONE