Impact of an overdose reversal program in the context of a safe consumption site in Northern Mexico.

Background: Drug overdoses are prevalent in low- and middle-income countries but are scarcely reported in the literature. We report on an opioid overdose reversal and naloxone distribution program that was instituted at the first safe consumption site in Latin America. Methods: A cross-sectional analysis of witnessed drug overdoses and naloxone distribution between 1 June 2019 and 31 May 2021 in Mexicali, Mexico. Case report forms were entered in an electronic database. Trends in overdose and naloxone distribution were described. Comparisons were made before and after the COVID-19 pandemic was declared in the city. Maps were created to represent the geographic distribution of overdose in the city. Results: During the study period 1,534 doses of naloxone were distributed throughout the community. In addition, there were 464 overdoses reported during this period, of which 4 were fatal. There was a 30% increase in reported overdoses from the period before the COVID-19 pandemic to the period after the pandemic was declared (p = 0.03). Most common substance reported included heroin (93%), sedatives (21%), methamphetamine (16%) and fentanyl (14%). Naloxone was given in 96% of cases (median 1 dose, IQR 1-2 doses) and emergency services were called in 20% of cases. Conclusions: An opioid overdose reversal program in Mexicali, Mexico was able to distribute naloxone and register drug overdoses between 2019 and 2021 as a harm reduction strategy. This adds to the growing body of literature on the impact of community-based programs on preventing fatal overdoses and the potential for implementation in low-resource settings.

COVID-19 needs no passport: the interrelationship of the COVID-19 pandemic along the U.S.-Mexico border.

OBJECTIVES: To investigate the impact of the COVID-19 pandemic along the U.S.-Mexico border region and evaluate the relationship of COVID-19 related mortality, socioeconomic status, and vaccination. METHODS: We used indirect standardization to age-adjust mortality rates and calculate standardized mortality ratios [SMR] in both countries. To examine the impact of socioeconomic factors, we calculated the Human Development Index (HDI) by county/municipality. We performed linear regression to understand the relationship between mortality, vaccination, and HDI. We used choropleth maps to visualize the trends seen in the region. RESULTS: Between January 22nd, 2020 and December 1st, 2021, surges of cases and deaths were similar in dyad cities along the U.S.-Mexico border visualizing the interconnectedness of the region. Mortality was higher in U.S. counties along the border compared to the national average (SMR 1.17, 95% CI 1.15-1.19). In Mexico, border counties had a slightly lower mortality to the national average (SMR 0.94, 95% CI 0.93-0.95). In U.S. border states, SMR was shown to negatively correlate with human development index (HDI), a socioeconomic proxy, resulting in a higher SMR in the border region compared to the rest of the counties. Conversely in Mexican border states, there was no association between SMR and HDI. Related to vaccination, U.S. counties along the border were vaccinated at a greater percentage than non-border counties and vaccination was negatively correlated with HDI. In Mexico, states along the border had a higher ratio of vaccinations per person than non-border states. CONCLUSIONS: The U.S.-Mexico border is a divide of incredible importance not only to immigration but as a region with unique social, economic, environmental, and epidemiological factors that impact disease transmission. We investigated how the COVID-19 pandemic followed trends of previously studied diseases in the corridor such as tuberculosis, HIV, and influenza H1N1. These data state how targeted intervention along the U.S.-Mexico border region is a necessity when confronting COVID-19 and have implications for future control of infectious diseases in the region.

Clinical Characteristics and Outcomes of Coronavirus Disease 2019 Patients Who Received Compassionate-Use Leronlimab.

BACKGROUND: Leronlimab, a monoclonal antibody blocker of C-C chemokine receptor type 5 originally developed to treat human immunodeficiency virus infection, was administered as an open-label compassionate-use therapeutic for coronavirus disease 2019 (COVID-19). METHODS: Twenty-three hospitalized severe/critical COVID-19 patients received 700 mg leronlimab subcutaneously, repeated after 7 days in 17 of 23 patients still hospitalized. Eighteen of 23 received other experimental treatments, including convalescent plasma, hydroxychloroquine, steroids, and/or tocilizumab. Five of 23 received leronlimab after blinded, placebo-controlled trials of remdesivir, sarilumab, selinexor, or tocilizumab. Outcomes and results were extracted from medical records. RESULTS: Mean age was 69.5 ±â€…14.9 years; 20 had significant comorbidities. At baseline, 22 were receiving supplemental oxygen (3 high flow, 7 mechanical ventilation). Blood showed markedly elevated inflammatory markers (ferritin, D-dimer, C-reactive protein) and an elevated neutrophil-to-lymphocyte ratio. By day 30 after initial dosing, 17 were recovered, 2 were still hospitalized, and 4 had died. Of the 7 intubated at baseline, 4 were fully recovered off oxygen, 2 were still hospitalized, and 1 had died. CONCLUSIONS: Leronlimab appeared safe and well tolerated. The high recovery rate suggested benefit, and those with lower inflammatory markers had better outcomes. Some, but not all, patients appeared to have dramatic clinical responses, indicating that unknown factors may determine responsiveness to leronlimab. Routine inflammatory and cell prognostic markers did not markedly change immediately after treatment, although interleukin-6 tended to fall. In some persons, C-reactive protein clearly dropped only after the second leronlimab dose, suggesting that a higher loading dose might be more effective. Future controlled trials will be informative.

Beyond the 405 and the 5: Geographic Variations and Factors Associated With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Positivity Rates in Los Angeles County.

BACKGROUND: To highlight geographic differences and the socio-structural determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) test positivity within Los Angeles County (LAC). METHODS: A geographic information system was used to integrate, map, and analyze SARS-CoV-2 testing data reported by the LAC Department of Public Health and data from the American Community Survey. Structural determinants included race/ethnicity, poverty, insurance status, education, and population and household density. We examined which factors were associated with positivity rates, using a 5% test positivity threshold, with spatial analysis and spatial regression. RESULTS: Between 1 March and 30 June 2020 there were 843 440 SARS-CoV-2 tests and 86 383 diagnoses reported, for an overall positivity rate of 10.2% within the study area. Communities with high proportions of Latino/a residents, those living below the federal poverty line, and with high household densities had higher crude positivity rates. Age- adjusted diagnosis rates were significantly associated with the proportion of Latino/as, individuals living below the poverty line, and population and household density. CONCLUSIONS: There are significant local variations in test positivity within LAC and several socio-structural determinants contribute to ongoing disparities. Public health interventions, beyond shelter in place, are needed to address and target such disparities.

Characterizing Self-Reports of Self-Identified Patient Experiences with Methadone Maintenance Treatment on an Online Community during COVID-19.

Background: The coronavirus disease (COVID-19) pandemic has impacted patients receiving methadone maintenance treatment (MMT) through opioid treatment programs (OTPs), especially because of the unique challenges of the care delivery model. Previously, documentation of patient experiences during emergencies often comes years after the fact, in part because there is a substantial data void in real-time. Methods: We extracted 308 posts that mention COVID-19 keywords on r/methadone, an online community for patients receiving MMT to share information, on Reddit occurring between January 31, 2020 and September 30, 2020. 215 of these posts self-report an impact to their MMT. Using qualitative content analysis, we characterized the impacts described in these posts and identified four emergent themes describing patients' experience of impacts to MMT during COVID-19. Results: The themes included (1) 54.4% of posts reporting impediments to accessing their methadone, (2) 28.4% reporting impediments to accessing physicial OTPs, (3) 19.5% reporting having to self-manage their care, and (4) 4.7% reporting impediments to accessing OTP providers and staff. Conclusions: Patients described unanticipated consequences to one-size-fits-all policies that are unevenly applied resulting in suboptimal dosing, increased perceived risk of acquiring COVID-19 at OTPs, and reduced interaction with OTP providers and staff. While preliminary, these results are formative for follow-up surveillance metrics for patients of OTPs as well as digitally-mediated resource needs for this online community. This study serves as a model of how social media can be employed during and after emergencies to hear the lived experiences of patients for informed emergency preparedness and response.

Increased rates of blood culture contamination during the coronavirus disease 2019 pandemic.

We observed a higher rate of blood-culture contamination during the COVID-19 pandemic at our institution compared to a prepandemic period. Given the potential implications of blood contamination in antibiotic and diagnostic test utilization as well as added cost, it is imperative to continue efforts to minimize these episodes during the pandemic.

Primary, Recall, and Decay Kinetics of SARS-CoV-2 Vaccine Antibody Responses.

Studies of two SARS-CoV-2 mRNA vaccines suggested that they yield ∼95% protection from symptomatic infection at least short-term, but important clinical questions remain. It is unclear how vaccine-induced antibody levels quantitatively compare to the wide spectrum induced by natural SARS-CoV-2 infection. Vaccine response kinetics and magnitudes in persons with prior COVID-19 compared to virus-naïve persons are not well-defined. The relative stability of vaccine-induced versus infection-induced antibody levels is unclear. We addressed these issues with longitudinal assessments of vaccinees with and without prior SARS-CoV-2 infection using quantitative enzyme-linked immunosorbent assay (ELISA) of anti-RBD antibodies. SARS-CoV-2-naïve individuals achieved levels similar to mild natural infection after the first vaccination; a second dose generated levels approaching severe natural infection. In persons with prior COVID-19, one dose boosted levels to the high end of severe natural infection even in those who never had robust responses from infection, increasing no further after the second dose. Antiviral neutralizing assessments using a spike-pseudovirus assay revealed that virus-naïve vaccinees did not develop physiologic neutralizing potency until the second dose, while previously infected persons exhibited maximal neutralization after one dose. Finally, antibodies from vaccination waned similarly to natural infection, resulting in an average of ∼90% loss within 90 days. In summary, our findings suggest that two doses are important for quantity and quality of humoral immunity in SARS-CoV-2-naïve persons, while a single dose has maximal effects in those with past infection. Antibodies from vaccination wane with kinetics very similar to that seen after mild natural infection; booster vaccinations will likely be required.

Discharge Clinical Characteristics and Post-Discharge Events in Patients with Severe COVID-19: A Descriptive Case Series.

BACKGROUND: As the SARS-CoV-2 pandemic continues, little guidance is available on clinical indicators for safely discharging patients with severe COVID-19. OBJECTIVE: To describe the clinical courses of adult patients admitted for COVID-19 and identify associations between inpatient clinical features and post-discharge need for acute care. DESIGN: Retrospective chart reviews were performed to record laboratory values, temperature, and oxygen requirements of 99 adult inpatients with COVID-19. Those variables were used to predict emergency department (ED) visit or readmission within 30 days post-discharge. PATIENTS (OR PARTICIPANTS): Age ≥ 18 years, first hospitalization for COVID-19, admitted between March 1 and May 2, 2020, at University of California, Los Angeles (UCLA) Medical Center, managed by an inpatient medicine service. MAIN MEASURES: Ferritin, C-reactive protein, lactate dehydrogenase, D-dimer, procalcitonin, white blood cell count, absolute lymphocyte count, temperature, and oxygen requirement were noted. KEY RESULTS: Of 99 patients, five required ED admission within 30 days, and another five required readmission. Fever within 24 h of discharge, oxygen requirement, and laboratory abnormalities were not associated with need for ED visit or readmission within 30 days of discharge after admission for COVID-19. CONCLUSION: Our data suggest that neither persistent fever, oxygen requirement, nor laboratory marker derangement was associated with need for acute care in the 30-day period after discharge for severe COVID-19. These findings suggest that physicians need not await the normalization of laboratory markers, resolution of fever, or discontinuation of oxygen prior to discharging a stable or improving patient with COVID-19.

Obesity and smoking as risk factors for invasive mechanical ventilation in COVID-19: A retrospective, observational cohort study.

PURPOSE: To describe the trajectory of respiratory failure in COVID-19 and explore factors associated with risk of invasive mechanical ventilation (IMV). MATERIALS AND METHODS: A retrospective, observational cohort study of 112 inpatient adults diagnosed with COVID-19 between March 12 and April 16, 2020. Data were manually extracted from electronic medical records. Multivariable and Univariable regression were used to evaluate association between baseline characteristics, initial serum markers and the outcome of IMV. RESULTS: Our cohort had median age of 61 (IQR 45-74) and was 66% male. In-hospital mortality was 6% (7/112). ICU mortality was 12.8% (6/47), and 18% (5/28) for those requiring IMV. Obesity (OR 5.82, CI 1.74-19.48), former (OR 8.06, CI 1.51-43.06) and current smoking status (OR 10.33, CI 1.43-74.67) were associated with IMV after adjusting for age, sex, and high prevalence comorbidities by multivariable analysis. Initial absolute lymphocyte count (OR 0.33, CI 0.11-0.96), procalcitonin (OR 1.27, CI 1.02-1.57), IL-6 (OR 1.17, CI 1.03-1.33), ferritin (OR 1.05, CI 1.005-1.11), LDH (OR 1.57, 95% CI 1.13-2.17) and CRP (OR 1.13, CI 1.06-1.21), were associated with IMV by univariate analysis. CONCLUSIONS: Obesity, smoking history, and elevated inflammatory markers were associated with increased need for IMV in patients with COVID-19.

Sharp decline in hospital and emergency department initiated buprenorphine for opioid use disorder during COVID-19 state of emergency in California.

The California Bridge Program supports expansion of medications for opioid use disorder (MOUD) in emergency departments (EDs) and hospital inpatient units across the state. Here, we describe the change in activity before and after the coronavirus disease 2019 (COVID-19) California statewide shutdown. Of the 70 participating hospitals regionally distributed across California, 52 report MOUD-related activity monthly. We analyzed data on outcomes of OUD care and treatment: identification of OUD, acceptance of referral, receipt of buprenorphine prescription, administration of buprenorphine, and follow-up linkage to outpatient OUD treatment, from May 2019 to April 2020. In estimating the expected number of patients who met each outcome in April 2020, we found decreases in the expected to observed number of patients across all outcomes (all p-values<0.002): 37% (from 1053 to 667) decrease in the number of patients identified with OUD, 34% (from 632 to 420) decrease in the number of patients who accepted a referral, 48% (from 521 to 272) decrease in the number of patients who were prescribed buprenorphine, 53% (from 501 to 234) decrease in the number of patients who were administered buprenorphine, and 33% (from 416 to 277) decrease in the number of patients who attended at least one follow-up visit for addiction treatment. The COVID-19 California statewide shutdown was associated with an abrupt and large decrease in the progress toward expanded access to OUD treatment.

Diagnostic yield of repeat testing for SARS-CoV-2: Experience from a large health system in Los Angeles.

OBJECTIVE: To determine the diagnostic yield of repeat testing for SARS-CoV-2. METHODS: A retrospective analysis was performed of all SARS-CoV-2 test results within the UCLA Health System between March 9th and April 29th, 2020. All patients with repeat test results were identified and those with discordant results were reviewed. RESULTS: Between March 9th and April 29th there were 10,165 SARS-CoV-2 test results, of which 630 (6.2%) were positive. Among the 904 patients with repeat test results, 808 (89.4%) were initially negative and 96 (10.6%) were initially positive. Among the 808 patients with an initial negative test, 15 (1.9%) subsequently tested positive. Eleven cases with an initial negative SARS-CoV-2 test and without a known prior positive SARS-CoV-2 test were reviewed; 6 were employed as healthcare workers and 10 were positive on the second test. CONCLUSIONS: We found a low diagnostic yield of repeat testing for SARS-CoV-2 in our health system. Repeat testing might prove useful in certain clinical scenarios, such as in healthcare workers, when symptoms develop after a negative test, and in hospitalized patients with a high clinical suspicion for COVID-19.

A machine learning algorithm to increase COVID-19 inpatient diagnostic capacity.

Worldwide, testing capacity for SARS-CoV-2 is limited and bottlenecks in the scale up of polymerase chain reaction (PCR-based testing exist. Our aim was to develop and evaluate a machine learning algorithm to diagnose COVID-19 in the inpatient setting. The algorithm was based on basic demographic and laboratory features to serve as a screening tool at hospitals where testing is scarce or unavailable. We used retrospectively collected data from the UCLA Health System in Los Angeles, California. We included all emergency room or inpatient cases receiving SARS-CoV-2 PCR testing who also had a set of ancillary laboratory features (n = 1,455) between 1 March 2020 and 24 May 2020. We tested seven machine learning models and used a combination of those models for the final diagnostic classification. In the test set (n = 392), our combined model had an area under the receiver operator curve of 0.91 (95% confidence interval 0.87-0.96). The model achieved a sensitivity of 0.93 (95% CI 0.85-0.98), specificity of 0.64 (95% CI 0.58-0.69). We found that our machine learning algorithm had excellent diagnostic metrics compared to SARS-CoV-2 PCR. This ensemble machine learning algorithm to diagnose COVID-19 has the potential to be used as a screening tool in hospital settings where PCR testing is scarce or unavailable.