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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. 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. 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. 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.

Despite global reductions in HIV incidence and mortality, the 15 UNAIDS-designated countries of Eastern Europe and Central Asia (EECA) that gained independence from the Soviet Union in 1991 constitute the only region where both continue to rise. HIV transmission in EECA is fuelled primarily by injection of opioids, with harsh criminalisation of drug use that has resulted in extraordinarily high levels of incarceration. Consequently, people who inject drugs, including those with HIV, hepatitis C virus, and tuberculosis, are concentrated within prisons. Evidence-based primary and secondary prevention of HIV using opioid agonist therapies such as methadone and buprenorphine is available in prisons in only a handful of EECA countries (methadone or buprenorphine in five countries and needle and syringe programmes in three countries), with none of them meeting recommended coverage levels. Similarly, antiretroviral therapy coverage, especially among people who inject drugs, is markedly under-scaled. Russia completely bans opioid agonist therapies and does not support needle and syringe programmes—with neither available in prisons—despite the country's high incarceration rate and having the largest burden of people with HIV who inject drugs in the region. Mathematical modelling for Ukraine suggests that high levels of incarceration in EECA countries facilitate HIV transmission among people who inject drugs, with 28–55% of all new HIV infections over the next 15 years predicted to be attributable to heightened HIV transmission risk among currently or previously incarcerated people who inject drugs. Scaling up of opioid agonist therapies within prisons and maintaining treatment after release would yield the greatest HIV transmission reduction in people who inject drugs. Additional analyses also suggest that at least 6% of all incident tuberculosis cases, and 75% of incident tuberculosis cases in people who inject drugs are due to incarceration. Interventions that reduce incarceration itself and effectively intervene with prisoners to screen, diagnose, and treat addiction and HIV, hepatitis C virus, and tuberculosis are urgently needed to stem the multiple overlapping epidemics concentrated in prisons.

Wastewater-based epidemiology can be particularly valuable at university campuses where high-resolution spatial sampling in a well-controlled context could not only provide insight into what affects campus community as well as how those inferences can be extended to a broader city/county context. In the present study, a large-scale wastewater surveillance was successfully implemented on a large university campus enabling early detection of 85% of COVID-19 cases thereby averting potential outbreaks. Wastewater-based surveillance has gained prominence and come to the forefront as a leading indicator of forecasting COVID-19 (coronavirus disease 2019) infection dynamics owing to its cost-effectiveness and its ability to inform early public health interventions. A university campus could especially benefit from wastewater surveillance, as universities are characterized by largely asymptomatic populations and are potential hot spots for transmission that necessitate frequent diagnostic testing. In this study, we employed a large-scale GIS (geographic information systems)-enabled building-level wastewater monitoring system associated with the on-campus residences of 7,614 individuals. Sixty-eight automated wastewater samplers were deployed to monitor 239 campus buildings with a focus on residential buildings. Time-weighted composite samples were collected on a daily basis and analyzed on the same day. Sample processing was streamlined significantly through automation, reducing the turnaround time by 20-fold and exceeding the scale of similar surveillance programs by 10- to 100-fold, thereby overcoming one of the biggest bottlenecks in wastewater surveillance. An automated wastewater notification system was developed to alert residents to a positive wastewater sample associated with their residence and to encourage uptake of campus-provided asymptomatic testing at no charge. This system, integrated with the rest of the “Return to Learn” program at the University of California (UC) San Diego-led to the early diagnosis of nearly 85% of all COVID-19 cases on campus. COVID-19 testing rates increased by 1.9 to 13× following wastewater notifications. Our study shows the potential for a robust, efficient wastewater surveillance system to greatly reduce infection risk as college campuses and other high-risk environments reopen. IMPORTANCE Wastewater-based epidemiology can be particularly valuable at university campuses where high-resolution spatial sampling in a well-controlled context could not only provide insight into what affects campus community as well as how those inferences can be extended to a broader city/county context. In the present study, a large-scale wastewater surveillance was successfully implemented on a large university campus enabling early detection of 85% of COVID-19 cases thereby averting potential outbreaks. The highly automated sample processing to reporting system enabled dramatic reduction in the turnaround time to 5 h (sample to result time) for 96 samples. Furthermore, miniaturization of the sample processing pipeline brought down the processing cost significantly ($13/sample). Taken together, these results show that such a system could greatly ameliorate long-term surveillance on such communities as they look to reopen. Author Video : An author video summary of this article is available.

Epidemics of COVID-19 in student populations at universities were a key concern for the 2020-2021 school year. The University of California (UC) System developed a set of recommendations to reduce campus infection rates. SARS-CoV-2 test results are summarized for the ten UC campuses during the Fall 2020 term. UC mitigation efforts included protocols for the arrival of students living on-campus students, non-pharmaceutical interventions, daily symptom monitoring, symptomatic testing, asymptomatic surveillance testing, isolation and quarantine protocols, student ambassador programs for health education, campus health and safety pledges, and lowered density of on-campus student housing. We used data from UC campuses, the UC Health-California Department of Public Health Data Modeling Consortium, and the U.S. Census to estimate the proportion of each campus' student populations that tested positive for SARS-CoV-2 and compared it to the fraction individuals aged 20-29 years who tested positive in their respective counties. SARS-CoV-2 cases in campus populations were generally low in September and October 2020, but increased in November and especially December, and were highest in early to mid-January 2021, mirroring case trajectories in their respective counties. Many students were infected during the Thanksgiving and winter holiday recesses and were detected as cases upon returning to campus. The proportion of students who tested positive for SARS-CoV-2 during Fall 2020 ranged from 1.2% to 5.2% for students living on campus and was similar to students living off campus. For most UC campuses the proportion of students testing positive was lower than that for the 20-29-year-old population in which campuses were located. The layered mitigation approach used on UC campuses, informed by public health science and augmented perhaps by a more compliant population, likely minimized campus transmission and outbreaks and limited transmission to surrounding communities. University policies that include these mitigation efforts in Fall 2020 along with SARS-CoV-2 vaccination, may alleviate some local concerns about college students returning to communities and facilitate resumption of normal campus operations and in-person instruction.

Alcohol use is a major contributor to mortality and morbidity worldwide. Uganda has a high level of alcohol use per capita. Compared to men, women are less likely to consume alcohol globally; however, women who drink have increased risks for co-occurring conditions, including depression, intimate partner violence, and HIV. This study assessed the prevalence of alcohol use and correlates of harmful alcohol use by gender and HIV status in rural Uganda. We used cross-sectional data from a study among women and men aged 15-59 residing in rural, central Uganda and accepting home-based HIV testing (Nov 2017 to Dec 2020). We estimated the prevalence of levels of alcohol use (categorized as no alcohol use (score 0), low (score 1-3 for men; 1-2 for women), medium (score 4-5 for men; 3-5 for women), high (score 6-7), and very-high (score 8-12) use with the AUDIT-C), stratified by gender and HIV status. We assessed correlates of harmful alcohol use using multivariable logistic regression models for women and men. Among 18,460 participants, 67% (95% CI: 66-67%) reported no alcohol use, 16% (95% CI: 16-17%) reported low, 5% (95% CI: 4.8-5%) reported medium, 5% (95% CI: 4-5%) reported high, and 3% (95% CI: 2.8-3) reported very high alcohol use. Compared to women, men were more likely to report alcohol use (Chi-squared p-value<0.0001). People diagnosed with HIV (both newly diagnosed and previously aware of their status prior to home-based HIV testing) were more likely to report low, medium, high, and very high alcohol use compared to those who were HIV negative (Chi-squared p-value<0.0001). Among women, those who were newly diagnosed were more likely report alcohol use, compared to those who were HIV negative. In multivariable models, being newly diagnosed with HIV (compared to HIV negative) increased the odds of harmful alcohol use among women, but not men. While alcohol use was higher among men and people living with HIV, being newly diagnosed with HIV had a stronger relationship with harmful alcohol use among women than men. More research is needed to understand how alcohol use may increase the risks of HIV acquisition among women and to identify gender-responsive services to address harmful alcohol use and increase access to HIV testing and linkage to care for women who use harmful levels of alcohol.

Background Our research focuses on local-level estimation of the effective reproductive number, which describes the transmissibility of an infectious disease and represents the average number of individuals one infectious person infects at a given time. The ability to accurately estimate the infectious disease reproductive number in geographically granular regions is critical for disaster planning and resource allocation. However, not all regions have sufficient infectious disease outcome data; this lack of data presents a significant challenge for accurate estimation. Methods To overcome this challenge, we propose a two-step approach that incorporates existing estimation procedures (EpiEstim, EpiFilter, EpiNow2) using data from geographic regions with sufficient data (step 1), into a covariate-adjusted Bayesian Integrated Nested Laplace Approximation (INLA) spatial model to predict in regions with sparse or missing data (step 2). Our flexible framework effectively allows us to implement any existing estimation procedure for in regions with coarse or entirely missing data. We perform external validation and a simulation study to evaluate the proposed method and assess its predictive performance. Results We applied our method to estimate using data from South Carolina (SC) counties and ZIP codes during the first COVID-19 wave (‘Wave 1’, June 16, 2020 – August 31, 2020) and the second wave (‘Wave 2’, December 16, 2020 – March 02, 2021). Among the three methods used in the first step, EpiNow2 yielded the highest accuracy of prediction in the regions with entirely missing data. Median county-level percentage agreement (PA) was 90.9% (Interquartile Range, IQR: 89.9–92.0%) and 92.5% (IQR: 91.6–93.4%) for Wave 1 and 2, respectively. Median zip code-level PA was 95.2% (IQR: 94.4–95.7%) and 96.5% (IQR: 95.8–97.1%) for Wave 1 and 2, respectively. Using EpiEstim, EpiFilter, and an ensemble-based approach yielded median PA ranging from 81.9 to 90.0%, 87.2-92.1%, and 88.4-90.9%, respectively, across both waves and geographic granularities. Conclusion These findings demonstrate that the proposed methodology is a useful tool for small-area estimation of , as our flexible framework yields high prediction accuracy for regions with coarse or missing data.

The advent of highly effective hepatitis C (HCV) treatments has questioned the need for a vaccine to control HCV amongst people who inject drugs (PWID). However, high treatment costs and ongoing reinfection risk suggest it could still play a role. We compared the impact of HCV vaccination amongst PWID against providing HCV treatment. Dynamic HCV vaccination and treatment models among PWID were used to determine the vaccination and treatment rates required to reduce chronic HCV prevalence or incidence in the UK over 20 or 40 years. Projections considered a low (50% protection for 5 years), moderate (70% protection for 10 years) or high (90% protection for 20 years) efficacy vaccine. Sensitivities to various parameters were examined. To halve chronic HCV prevalence over 40 years, the low, moderate and high efficacy vaccines required annual vaccination rates (coverage after 20 years) of 162 (72%), 77 (56%) and 44 (38%) per 1000 PWID, respectively. These vaccination rates were 16, 7.6 and 4.4 times greater than corresponding treatment rates. To halve prevalence over 20 years nearly doubled these vaccination rates (moderate and high efficacy vaccines only) and the vaccination-to-treatment ratio increased by 20%. For all scenarios considered, required annual vaccination rates and vaccination-to-treatment ratios were at least a third lower to reduce incidence than prevalence. Baseline HCV prevalence had little effect on the vaccine's impact on prevalence or incidence, but substantially affected the vaccination-to-treatment ratios. Behavioural risk heterogeneity only had an effect if we assumed no transitions between high and low risk states and vaccinations were targeted or if PWID were high risk for their first year. Achievable coverage levels of a low efficacy prophylactic HCV vaccine could greatly reduce HCV transmission amongst PWID. Current high treatment costs ensure vaccination could still be an important intervention option.

Prior to direct-acting antivirals (DAAs), HCV incidence rose among men who have sex with men (MSM) living with HIV infection in Germany despite high hepatitis C virus (HCV) treatment rates. We establish a HCV elimination modeling framework to evaluate whether existing treatment rates can achieve the World Health Organization (WHO) incidence target among MSM living with HIV in Germany. To evaluate progress towards HCV elimination in Germany, we adapted a previously published HCV transmission model among MSM living with diagnosed HIV. We modelled HCV incidence and prevalence until 2030 (relative to 2015) under existing treatment and DAA scale-up and explored potential impacts of disruptions in treatment and behavioral risk reduction due to the COVID-19 pandemic. Continuing current treatment rates will result in stable HCV incidence among MSM living with HIV in Germany between 2015-2030. The WHO HCV incidence target is achievable under DAA scale-up to 100% treatment combined with treatment of those previously diagnosed and untreated (at a rate of 15%/year) and would result in greater reductions with early treatment (3 vs 6 months) reducing incidence from 4.0/100person-years to 0.8/100person-years by 2030. A 12-month disruption to HCV treatment (20% reduction) and risk behaviors (25%,50%,75% reduction) during the COVID-19 pandemic would result in a 15% relative increase in total HCV incidence in 2030 compared to that expected under the status quo. HCV elimination among MSM living with HIV in Germany requires further DAA scale-up among those newly diagnosed combined with efforts to treat those previously diagnosed but untreated. Prospective monitoring will establish whether Germany is on track for HCV microelimination.

HCV direct-acting antivirals (DAAs) are produced in India at low cost. However, concerns surrounding reinfection and budgetary impact limit treatment scale-up in India. We evaluate the cost-effectiveness and budgetary impact of HCV treatment in India, including reinfection. A closed cohort Markov model of HCV disease progression, treatment, and reinfection was parameterized. We compared treatment by fibrosis stage (F2-F4 or F0-F4) to no treatment from a health care payer perspective. Costs (2017 USD$, based on India-specific data) and health utilities (in quality-adjusted life years, QALYs) were attached to each health state. We assumed DAAs with 90% sustained viral response at $900/treatment and 1%/year reinfection, varied in the sensitivity analysis from 0.1-15%. We deemed the intervention cost-effective if the incremental cost-effectiveness ratio (ICER) fell below India's per capita GDP ($1,709). We assessed the budgetary impact of treating all diagnosed individuals. HCV treatment for diagnosed F2-F4 individuals was cost-saving (net costs -$2,881 and net QALYs 3.18/person treated; negative ICER) compared to no treatment. HCV treatment remained cost-saving with reinfection rates of 15%/year. Treating all diagnosed individuals was likely cost-effective compared to delay until F2 (mean ICER $1,586/QALY gained, 67% of simulations falling under the $1,709 threshold) with 1%/year reinfection. For all scenarios, annual retesting for reinfection was more cost-effective than the current policy (one-time retest). Treating all diagnosed individuals and reinfections results in net costs of $445-1,334 million over 5 years (<0.25% of total health care expenditure over 5 years), and cost-savings within 14 years. HCV treatment was highly cost-effective in India, despite reinfection. Annual retesting for reinfection was cost-effective, supporting a policy change towards more frequent retesting. A comprehensive HCV treatment scale-up plan is warranted in India.

Injection drug use (IDU) is associated with multiple health harms. The vast majority of IDU initiation events (in which injection-naïve persons first adopt IDU) are assisted by a person who injects drugs (PWID), and as such, IDU could be considered as a dynamic behavioral transmission process. Data suggest that opioid agonist treatment (OAT) enrollment is associated with a reduced likelihood of assisting with IDU initiation. We assessed the association between recent OAT enrollment and assisting IDU initiation across several North American settings and used dynamic modeling to project the potential population-level impact of OAT scale-up within the PWID population on IDU initiation. We employed data from a prospective multicohort study of PWID in 3 settings (Vancouver, Canada [n = 1,737]; San Diego, United States [n = 346]; and Tijuana, Mexico [n = 532]) from 2014 to 2017. Site-specific modified Poisson regression models were constructed to assess the association between recent (past 6 month) OAT enrollment and history of ever having assisted an IDU initiation with recently assisting IDU initiation. Findings were then pooled using linear mixed-effects techniques. A dynamic transmission model of IDU among the general population was developed, stratified by known factors associated with assisting IDU initiation and relevant drug use behaviors. The model was parameterized to a generic North American setting (approximately 1% PWID) and used to estimate the impact of increasing OAT coverage among PWID from baseline (approximately 21%) to 40%, 50%, and 60% on annual IDU initiation incidence and corresponding PWID population size across a decade. From Vancouver, San Diego, and Tijuana, respectively, 4.5%, 5.2%, and 4.3% of participants reported recently assisting an IDU initiation, and 49.4%, 19.7%, and 2.1% reported recent enrollment in OAT. Recent OAT enrollment was significantly associated with a 45% lower likelihood of providing recent IDU initiation assistance among PWID (relative risk [RR] 0.55 [95% CI 0.36-0.84], p = 0.006) compared to those not recently on OAT. Our dynamic model predicts a baseline mean of 1,067 (2.5%-97.5% interval [95% I 490-2,082]) annual IDU initiations per 1,000,000 individuals, of which 886 (95% I 406-1,750) are assisted by PWID. Based on our observed statistical associations, our dynamic model predicts that increasing OAT coverage from approximately 21% to 40%, 50%, or 60% among PWID could reduce annual IDU initiations by 11.5% (95% I 2.4-21.7), 17.3% (95% I 5.6-29.4), and 22.8% (95% I 8.1-36.8) and reduce the PWID population size by 5.4% (95% I 0.1-12.0), 8.2% (95% I 2.2-16.9), and 10.9% (95% I 3.2-21.8) relative to baseline, respectively, in a decade. Less impact occurs when the protective effect of OAT is diminished, when a greater proportion of IDU initiations are unassisted by PWID, and when average IDU career length is longer. The study's main limitations are uncertainty in the causal pathway between OAT enrollment and assisting with IDU initiation and the use of a simplified model of IDU initiation. In addition to its known benefits on preventing HIV, hepatitis C virus (HCV), and overdose among PWID, our modeling suggests that OAT scale-up may also reduce the number of IDU initiations and PWID population size.