Telemedicine's Impact on Diabetes Care during the COVID-19 Pandemic: A Cohort Study in a Large Integrated Healthcare System (preprint)

Introduction: To examine if patients exposed to primary care telemedicine (telephone or video) early in the COVID-19 pandemic had higher rates of downstream HbA1c measurement and improved HbA1c levels in the second year of the pandemic. Research Design and Methods In a cohort of 242, 848 Kaiser Permanente Northern California patients with diabetes, we examined associations between early-pandemic patient-initiated telemedicine visit and downstream HbA1c monitoring and results during the second year of the pandemic. Results Adjusted HbA1c measurement rates were significantly higher among patients with telemedicine exposure in the early-pandemic prior year than those with no visits in the prior year (91.0% testing for patients with video visits, 90.5% for telephone visits, visits, 86.7% for no visits, p < 0.05). Among those with HbA1c measured, the rates of having an HbA1c < 8% in the second year of the COVID-19 pandemic were also statistically significantly higher among patients with telemedicine exposure in the early-pandemic prior year than those with no visits in the prior year (68.5% with HbA1c< 8% for video visits, 67.3% for telephone visits, 66.6% for no visits, p < 0.05). Conclusions Access to telephone and video telemedicine throughout the early COVID-19 pandemic was associated with patients' continued engagement in recommended diabetes care. Although our study analyzed telemedicine use during a pandemic, telemedicine visits may continue to support ongoing health care access and positive clinical outcomes.

Comprehensive Forecasting of California's Energy Consumption: A Multi-Source and Sectoral Analysis Using ARIMA and ARIMAX Models (preprint)

California's significant role as the second-largest consumer of energy in the United States underscores the importance of accurate energy consumption predictions. With a thriving industrial sector, a burgeoning population, and ambitious environmental goals, the state's energy landscape is dynamic and complex. This paper presents a comprehensive analysis of California's energy consumption trends and provides detailed forecasting models for different energy sources and sectors. The study leverages ARIMA and ARIMAX models, considering both historical consumption data and exogenous variables. We address the unique challenges posed by the COVID-19 pandemic and the limited data for 2022, highlighting the resilience of these models in the face of uncertainty. Our analysis reveals that while fossil fuels continue to dominate California's energy landscape, renewable energy sources, particularly solar and biomass, are experiencing substantial growth. Hydroelectric power, while sensitive to precipitation, remains a significant contributor to renewable energy consumption. Furthermore, we anticipate ongoing efforts to reduce fossil fuel consumption. The forecasts for energy consumption by sector suggest continued growth in the commercial and residential sectors, reflecting California's expanding economy and population. In contrast, the industrial sector is expected to experience more moderate changes, while the transportation sector remains the largest energy consumer.

The Effect of COVID-19 Public Health Measures On Mental Health in California (preprint)

California was the first state to implement statewide public health measures, including lockdowns and curfews, to mitigate the transmission of SARS-CoV-2. The implementation of these public health measures may have had unintended consequences related to mental health for persons in California. This study is a retrospective review of electronic health records of patients who sought care in the University of California Health System to examine changes in mental health status during the pandemic. Data were extracted prior to the pandemic (March-October 2019) and during the pandemic (March-October 2020). Weekly values of new mental health disorders were extracted and further classified based on age. Paired t-tests were performed to test for differences in the occurrence of each mental health disorder for each age group. A two-way ANOVA was performed to assess for between-group differences. When compared with pre-pandemic diagnoses, persons aged 26-35 had the greatest increase in mental health diagnoses overall during the pandemic, specifically for anxiety, bipolar disorder, depression, mood disturbance, and psychosis. The mental health of persons age 25-35 were more affected than any other age group.

Longitudinal sequencing and variant detection of SARS-CoV-2 across Southern California wastewater from April 2020 - August 2021 (preprint)

Wastewater based epidemiology (WBE) is a useful method to detect pathogen prevalence and may serve to effectively monitor diseases at a broad scale. WBE has been used throughout the COVID-19 pandemic to track localized and population-level disease burden through the quantification of SARS-CoV-2 RNA present in wastewater. Aside from case load estimation, WBE is being used to assay viral genomic diversity and the emergence of potential SARS-CoV-2 variants. Here, we present a study in which we sequenced RNA extracted from sewage influent samples obtained from eight wastewater treatment plants representing 16 million people in Southern California over April 2020 - August 2021. We sequenced SARS-CoV-2 with two methods: Illumina Respiratory Virus Enrichment and metatranscriptomic sequencing (N = 269), and QIAseq SARS-CoV-2 tiled amplicon sequencing (N = 95). We were able to classify SARS-CoV-2 reads into lineages and sublineages that approximated several named variants across a full year, and we identified a diversity of single nucleotide variants (SNVs) of which many are putatively novel SNVs, and SNVs of unknown potential function and prevalence. Through our retrospective study, we also show that several sublineages of SARS-CoV-2 were detected in wastewater up to several months before clinical detection, which may assist in the prediction of future Variants of Concern. Lastly, we show that sublineage diversity was similar between wastewater treatment plants across Southern California, and that diversity changed by sampling month indicating that WBE is effective across megaregions. As the COVID-19 pandemic moves to new phases, and additional SARS-CoV-2 variants emerge, the ongoing monitoring of wastewater is important to understand local and population-level dynamics of the virus. Our study shows the potential of WBE to detect SARS-CoV-2 variants throughout Southern Californias wastewater and track the diversity of viral SNVs and strains in urban and suburban locations. These results will aid in our ability to monitor the evolutionary potential of SARS-CoV-2 and help understand circulating SNVs to further combat COVID-19.

The 249RWMD spike protein insertion in Omicron BQ.1 subvariant compensates the 24LPP and 69HV deletions and may cause severe disease than BF.7 and XBB.1 subvariants (preprint)

Alarming antibody evasion properties were documented for new BF, BQ and XBB Omicron subvariants. Most immune-drugs were inactive neutralizing those COVID-19 subvariants and viral titers were exceptionally low as compared to deadly B.1.1.7, B.1.617.2 and B.1.1.529 variants with D614G, N501Y and L452R mutations in spike. The 91% nucleotides changes in spike protein of BQ.1 were resulted in AA changes whereas only 52% nucleotides changes resulted in AAs changes in ORF1ab. The N460K and K444T mutations in BQ.1 may be important driving force for immune-escape similar to F486S and N480K mutations in BA.2.75 subvariant and related XBB.1 subvariant. Further, the R346T mutation as found in BA.4.6 and BF.7, was regained in BQ.1.1 and BA.2.75.2 to enhance immune escape and infectivity (> 80%). The L452R and F486V mutations in spike were main drivers of Omicron BA.2 conversion to BA.4 and BA.5 in presence of 69HV deletion. Whereas 24LPP spike deletion and 3675SGF ORF1ab protein deletion were found in all Omicron viruses including BQ.1 and XBB.1. Interestingly, we found about 211 COVID-19 sequences with four amino acids (249RWMD) insertion near the RBD domain of Omicron viruses similar to 215EPE three amino acids insertion in Omicron BA.1 variant. Such sequences first detected in California and extended to Florida, Washington and Michigan as well as other adjoining US states. An one amino acid deletion (140Y) in spike was also found in BA.4.6, BQ.1.5, BQ.1.8, BQ.1.14, BQ.1.1.5, XBB.1 as well as related AZ.3, BU.1, BW.1, CR.2, CP.1 and CQ.1 subvariants but was not detected in BA.2.75, BF.7, XBD, BQ.1, BQ.1.1, BQ.1.2, BQ.1.6, BQ.1.10, BQ.1.12, BQ.1.16, BQ.1.19, BQ.1.22, BQ.1.1.1, BQ.1.1.4, BQ.1.1.12 and related BK.1, BN.1, BM.1.1.1, BR.2, BU.1, CA.1, CD.2, CH.1.1 subvariants. Thus, BQ.1 insertion was compensated the other deletions and would be more infectious than BA.2.75, BF.7 and XBB.1 subvariants even there was a 26nt deletion in the 3’-UTR. The spike protein R341T one amino acid change in BQ.1.1 and BQ.1.1.1 might be important but no 249RWMD insertion.

Bayesian sequential approach to monitor COVID-19 variants through positivity rate from wastewate (preprint)

Trends in COVID-19 infection have changed throughout the pandemic due to myriad factors, including changes in transmission driven by social behavior, vaccine development and uptake, mutations in the virus genome, and public health policies. Mass testing was an essential control measure for curtailing the burden of COVID-19 and monitoring the magnitude of the pandemic during its multiple phases. However, as the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementing vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 tests reduced the demand for mass severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. This paper proposes a sequential Bayesian approach to estimate the COVID-19 positivity rate (PR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. PR estimates are used to compute thresholds for WW data using the CDC thresholds for low, substantial, and high transmission. The effective reproductive number estimates are calculated using PR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring the COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. The proposed modeling framework was applied to the City of Davis and the campus of the University of California Davis.

Wastewater monitoring of SARS-CoV-2 RNA at K-12 schools: Comparison to pooled clinical testing data (preprint)

Background. Wastewater measurements of SARS-CoV-2 RNA have been extensively used to supplement clinical data on COVID-19. Most examples in the literature that describe wastewater monitoring for SARS-CoV-2 RNA use samples from wastewater treatment plants and individual buildings that serve as the primary residence of community members. However, wastewater surveillance can be an attractive supplement to clinical testing in K-12 schools where individuals only spend a portion of their time but interact with others in close proximity, increasing risk of potential transmission of disease. Methods. Wastewater samples were collected from two K-12 schools in California and divided into solid and liquid fractions to be processed for detection of SARS-CoV-2. The resulting detection rate in each wastewater fraction was compared to each other and the detection rate in pooled clinical specimens. Results. Most wastewater samples were positive for SARS-CoV-2 RNA when clinical testing was positive (75% for solid samples and 100% for liquid samples). Wastewater samples continued to test positive for SARS-CoV-2 RNA when clinical testing was negative or in absence of clinical testing (83% for both solid and liquid samples), indicating presence of infected individuals in the schools. Wastewater solids had a higher concentration of SARS-CoV-2 than wastewater liquids on an equivalent mass basis by three orders of magnitude.

Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States (preprint)

The rapid spread of the numerous outbreaks of the coronavirus disease 2019 (COVID-19) pandemic has fueled interest in mathematical models designed to understand and predict infectious disease spread, with the ultimate goal of contributing to the decision-making of public health authorities. Here, we propose a computational pipeline that dynamically parameterizes a modified SEIRD (Susceptible-Exposed-InfectedRecovered-Deceased) model using standard daily series of COVID-19 cases and deaths, along with isolated estimates of population-level seroprevalence. We test our pipeline in five heavily impacted states of the US (New York, California, Florida, Illinois, and Texas) between March and August 2020, considering two scenarios with different calibration time horizons to assess the update in model performance as new epidemiologic data becomes available. Our results show a median normalized root mean squared error (NRMSE) of 2.38% and 4.28% in calibrating cumulative cases and deaths in the first scenario, and 2.41% and 2.30% when new data is assimilated in the second scenario, respectively. Then, two-week (four-week) forecasts of the calibrated model resulted in median NRMSE of cumulative cases and deaths of 5.85% and 4.68% (8.60% and 17.94%) in the first scenario, and 1.86% and 1.93% (2.21% and 1.45%) in the second. Additionally, we show that our method provides significantly more accurate predictions of cases and deaths than a constant parameterization in the second scenario (p < 0.05). Thus, we posit that our methodology is a promising approach to analyze the dynamics of infectious disease outbreaks, and that our forecasts could contribute to designing effective pandemic-arresting public health policies.

Learning on Health Fairness and Environmental Justice via Interactive Visualization (preprint)

This paper introduces an interactive visualization interface with a machine learning consensus analysis that enables the researchers to explore the impact of atmospheric and socioeconomic factors on COVID-19 clinical severity by employing multiple Recurrent Graph Neural Networks. We designed and implemented a visualization interface that leverages coordinated multi-views to support exploratory and predictive analysis of hospitalizations and other socio-geographic variables at multiple dimensions, simultaneously. By harnessing the strength of geometric deep learning, we build a consensus machine learning model to include knowledge from county-level records and investigate the complex interrelationships between global infectious disease, environment, and social justice. Additionally, we make use of unique NASA satellite-based observations which are not broadly used in the context of climate justice applications. Our current interactive interface focus on three US states (California, Pennsylvania, and Texas) to demonstrate its scientific value and presented three case studies to make qualitative evaluations.

Assessing the accuracy of California county level COVID-19 hospitalization forecasts to inform public policy decision making (preprint)

The COVID-19 pandemic has highlighted the role of infectious disease forecasting in informing public policy. However, significant barriers remain for effectively linking infectious disease forecasts to public health decision making, including a lack of model validation. Forecasting model performance and accuracy should be evaluated retrospectively to understand under which conditions models were reliable and could be improved in the future. Using archived forecasts from the California Department of Public Health's California COVID Assessment Tool (https://calcat.covid19.ca.gov/cacovidmodels/), we compared how well different forecasting models predicted COVID-19 hospitalization census across California counties and regions during periods of Alpha, Delta, and Omicron variant predominance. Based on mean absolute error estimates, forecasting models had variable performance across counties and through time. When accounting for model availability across counties and dates, some individual models performed consistently better than the ensemble model, but model rankings still differed across counties. Local transmission trends, variant prevalence, and county population size were informative predictors for determining which model performed best for a given county based on a random forest classification analysis. Overall, the ensemble model performed worse in less populous counties, in part because of fewer model contributors in these locations. Ensemble model predictions could be improved by incorporating geographic heterogeneity in model coverage and performance. Consistency in model reporting and improved model validation can strengthen the role of infectious disease forecasting in real-time public health decision making.

Changes in Fentanyl Distribution in California (preprint)

Abstract Background: Fentanyl is a synthetic opioid that is commonly given as a medication to alleviate pain. This drug can be administered through multiple routes hence making it easy to exploit at high rates. Due to the flexibility in which it can be taken it increases the ease of both access and use. The purpose of this study was to analyze trends in the distribution of fentanyl and its formulations across Medicaid enrollees in California and among the 3 - digit registrant zip codes in California over the period of pre-pandemic (2018 - 2019) to the early stages of the COVID -19 pandemic (2020). Methods: Using the Automated Reports and Consolidated Ordering System (ARCOS) the distribution of fentanyl across California was compiled from 2018 to 2020. Utilizing ARCOS the number of individuals within the source population who lived in one of California's many zip codes was observed. To analyze the fentanyl distribution trend we used Google Sheets GraphPad Prism (Version 9.3.0 [463]) and Microsoft 365 Excel. These were helpful to organize the Medicaid ARCOS data, and as well as to create graphs. The Medicaid database was used to compile the number of fentanyl formulations prescribed from 2018 to 2020 across California. Results: The analyses from both databases provided insight into the difference in fentanyl distribution in California from the years 2018 to 2020. After looking further into the many 3 - digit registrant zip codes as well as Medicaid enrollees it was found that there was a decrease in the distribution of fentanyl and its formulations. Additionally it was found that the distribution of fentanyl as a medication by business activities also decreased from 2018 to 2020. Conclusion: The results indicate that there was more fentanyl being distributed and prescribed before the pandemic (2018 - 2019). On the other hand, when we considered the effects of the pandemic during 2020 there was quite a drastic decrease in the amount of fentanyl being prescribed and distributed to those living in California and those enrolled in Medicaid.

COVID-19 vaccine antibody response is associated with side-effects, chronic health conditions, and vaccine type in a large Northern California cohort (preprint)

As vaccines have become available for COVID-19, it is important to understand factors that may impact response. The objective of this study is to describe vaccine response in a well-characterized Northern California cohort, including differences in side-effects and antibody response by vaccine type, sex, and age, as well as describe responses in subjects with pre-existing health conditions that are known risk factors for more severe COVID-19 infection. From July 2020 to March 2021, ~5,500 adults from the East Bay Area in Northern California were followed as part of a longitudinal cohort study. Comprehensive questionnaire data and biospecimens for COVID-19 antibody testing were collected at multiple time-points. All subjects were at least 18 years of age and members of the East-Bay COVID-19 cohort who answered questionnaires related to vaccination status and side-effects at two time-points. Three vaccines, Moderna (2 doses), Pfizer-BioNTech (2 doses), and Johnson & Johnson (single dose), were examined as exposures. Additionally, pre-existing health conditions were assessed. The main outcomes of interest were anti-SARS-CoV-2 Spike antibody response (measured by S/C ratio in the Ortho VITROS assay) and self-reporting of 11 potential vaccine side effects. When comparing both doses of the Moderna vaccine to respective doses of Pfizer-BioNTech, participants receiving the Moderna vaccine had higher odds of many reported side-effects. The same was true comparing the single-dose Johnson & Johnson vaccine to dose 2 of the Pfizer-BioNTech vaccine. The antibody S/C ratio also increased with each additional side-effect after the second dose. S/C ratios after vaccination were lower in participants aged 65 and older, and higher in females. At all vaccination timepoints, Moderna vaccine recipients had a higher S/C ratio. Individuals who were fully vaccinated with Pfizer-BioNTech had a 72.4% lower S/C ratio compared to those who were fully vaccinated with Moderna. Subjects with asthma, diabetes, and cardiovascular disease all demonstrated more than a 20% decrease in S/C ratio. In support of previous findings, we show that antibody response to the Moderna vaccine is higher than the Pfizer-BioNTech vaccine. We also observed that antibody response was associated with side-effects, and participants with a history of asthma, diabetes, and cardiovascular disease had lower antibody responses. This information is important to consider as further vaccines are recommended.

Stakeholders’ perspectives on the feasibility of adopting a Healthy Nail Salon Recognition Program in Philadelphia: A qualitative study (preprint)

ABSTRACT Background The California Healthy Nail Salon Recognition Program is a statewide initiative to incentivize nail salons to adopt safer practices such as use of safer nail products without certain harmful chemicals, installation of ventilation systems, proper personal protective equipment use, and staff training. This public policy intervention is in response to the call to protect nail care workers, mostly women of color, who bear disproportionate burden of chemical exposure at work. Because there is interest from the community to adopt similar program in the Greater Philadelphia region, we conducted this formative research to document stakeholders’ perspectives on the feasibility of adopting the Healthy Nail Salon Recognition Program in Philadelphia. Methods We conducted semi-structured interviews with a purposive sample of 31 stakeholders in Philadelphia in 2021. Using the Consolidated Framework for Implementation Science as our theoretical framework, we developed the interview guide and analyzed the data using qualitative research method to identify key facilitators and barriers. Results Key facilitating themes were perceived need and benefits of program to improve workers’ health and working conditions, and willingness of stakeholders to leverage their organizational resources. Barriers included perceived high cost and time commitment from salon owners and employees, lack of funding and implementation leaders at the city government, community members’ willingness to be visible and advocate for the program affected by the stigmas of being immigrant workers, fear of interacting with authorities, as well as the impact of COVID-19 pandemic. Our results suggest successful adoption of the Healthy Nail Salon Recognition Program in Philadelphia will require outreach within the community to raise awareness of the benefits of the program and close partnership with community-based organizations to facilitate mutual understanding between the authority and the ethnically diverse nail salon communities.

The Effect of SARS-COV-2 Variant on Respiratory Features and Mortality Among Vaccinated and Non-Fully Vaccinated Patients (preprint)

Background SARS-CoV-2 (COVID-19) has caused over 80 million infections and 973,000 deaths in the United States, and mutations are linked to increased transmissibility. This study aimed to determine the effect of SARS-CoV-2 variants on respiratory features and mortality and to determine the effect of vaccination status. Method A retrospective review of medical records (n=63,454 unique patients) using The University of California Health COvid Research Data Set (UC CORDS) was performed to identify respiratory features, vaccination status, and mortality. Variants were identified using the CDC data tracker. Results Increased odds of death were observed among those not fully vaccinated (Delta OR: 1.64, p = 0.052; Omicron OR: 1.96, p < 0.01). Later variants (i.e., Delta and Omicron) demonstrated a reduction in the frequency of lower respiratory tract features with a concomitant increase in upper respiratory tract features. Vaccination status was associated with survival and a decrease in the frequency of many upper and lower respiratory tract features. Discussion SARS-CoV-2 variants show a reduction in lower respiratory tract features with an increase in upper respiratory tract features. Being fully vaccinated results in fewer respiratory features and higher odds of survival, supporting vaccination in preventing morbidity and mortality from COVID-19.

Ultra-deep Sequencing of Hadza Hunter-Gatherers Recovers Vanishing Microbes (preprint)

The gut microbiome has been identified as a key to immune and metabolic health, especially in industrialized populations 1 . Non-industrialized individuals harbor more diverse microbiomes and distinct bacterial lineages 2 , but systemic under-sampling has hindered insight into the extent and functional consequences of these differences 3 . Here, we performed ultra-deep metagenomic sequencing and laboratory strain isolation on fecal samples from the Hadza, hunter-gatherers in Tanzania, and comparative populations in Nepal and California. We recover 94,971 total genomes of bacteria, archaea, bacteriophage, and eukaryotes, and find that 43% are novel upon aggregating with existing unified datasets 4,5 . Analysis of in situ growth rates, genetic pN/pS signatures, and high-resolution strain tracking reveal dynamics in the hunter-gatherer gut microbiome that are distinct from industrialized populations. Industrialized versus Hadza gut microbes are enriched in genes associated with oxidative stress, possibly a result of microbiome adaptation to inflammatory processes. We use phylogenomics to reveal that global spread of the spirochaete Treponema succinifaciens parallels historic human migration prior to its extinction in industrialized populations. When combined with a detailed definition of gut-resident strains that are vanishing in industrialized populations, our data demonstrate extensive perturbation in many facets of the gut microbiome brought on by the industrialized lifestyle. Recognition of work with indigenous communities Research involving indigenous communities is needed for a variety of reasons including to ensure that scientific discoveries and understanding appropriately represent all populations and do not only benefit those living in industrialized nations 3,6 . Special considerations must be made to ensure that this research is conducted ethically and in a non-exploitative manner. In this study we performed deep metagenomic sequencing on fecal samples that were collected from Hadza hunter-gatherers in 2013/2014 and were analyzed in previous publications using different methods 2,7 . A material transfer agreement with the National Institute for Medical Research in Tanzania specifies that stool samples collected are used solely for academic purposes, permission for the study was obtained from the National Institute of Medical Research (MR/53i 100/83, NIMR/HQ/R.8a/Vol.IX/1542) and the Tanzania Commission for Science and Technology, and verbal consent was obtained from the Hadza after the study’s intent and scope was described with the help of a translator. The publications that first described these samples included several scientists and Tanzanian and Nepali field-guides as co-authors for the critical roles they played in sample collection, but as no new samples were collected in this study, only scientists who contributed to the analyses described here were included as co-authors in this publication. It is currently not possible for us to travel to Tanzania and present our results to the Hadza people, however we intend to do so once the conditions of the COVID-19 pandemic allow it.

Waning of Vaccine-Conferred Protection against SARS-CoV-2 Infection: Matched Case-Control Test-Negative Design Study in Two High-Risk Populations (preprint)

To distinguish waning of vaccine responses from differential variant protection, we performed a test-negative case-control analysis during a Delta variant-dominant period in California’s prisons. We found that infection odds increased each 28-day period post-vaccination, reaching 3.4-fold (residents) to 4.7-fold (staff) increased odds of infection after 180 days.

Factors Associated with COVID-19 Testing among People who Inject Drugs: Missed Opportunities for Reaching those Most at Risk (preprint)

People who inject drugs (PWID) are vulnerable to SARS-CoV-2 infection. We examined correlates of COVID-19 testing among PWID in the U.S.-Mexico border region and described encounters with services or venues representing potential opportunities (i.e., "touchpoints") where COVID-19 testing could have been offered. Between October, 2020 and September, 2021, participants aged [≥]18 years from San Diego, California, USA and Tijuana, Baja California, Mexico who injected drugs within the last month completed surveys and SARS-CoV-2, HIV, and HCV serologic testing. Logistic regression was used to identify factors associated with COVID-19 testing prior to enrollment. Of 583 PWID, 30.5% previously had a COVID-19 test. Of 172 PWID who tested SARS-CoV-2 seropositive in our study (30.1%), 50.3% encountered at least one touchpoint within the prior six months where COVID-19 testing could have been offered. Factors independently associated with at least two fold higher odds of COVID-19 testing were living in San Diego (versus Tijuana), having recently been incarcerated or attending substance use disorder (SUD) treatment and having at least one chronic health condition. In addition, recent homelessness, having had at least one COVID-19 vaccine dose and having been tested for HIV or HCV since the pandemic began were independently associated with COVID-19 testing. We identified several factors independently associated with COVID-19 testing and multiple touchpoints where COVID-19 testing could be scaled up for PWID, such as SUD treatment programs and syringe service programs. Integrated health services are needed to improve access to rapid, free COVID-19 testing in this vulnerable population.

A descriptive analysis of 2020 California Occupational Safety and Health Administration COVID-19-related complaints (preprint)

COVID-19 mortality disproportionately affected specific occupations and industries. The Occupational Safety and Health Administration (OSHA) protects the health and safety of workers by setting and enforcing standards for working conditions. Workers may file OSHA complaints about unsafe conditions. Complaints may indicate poor workplace safety during the pandemic. We evaluated COVID-19-related complaints filed with California (Cal)/OSHA between January 1, 2020 and December 14, 2020 across seven industries. To assess whether workers in occupations with high COVID-19-related mortality were also most likely to file Cal/OSHA complaints, we compared industry-specific per-capita COVID-19 confirmed deaths from the California Department of Public Health with COVID-19-related complaints. Although 7,820 COVID-19-related complaints were deemed valid by Cal/OSHA, only 627 onsite inspections occurred and 32 citations were issued. Agricultural workers had the highest per-capita COVID-19 death rates (402 per 100,000 workers) but were least represented among workplace complaints (44 per 100,000 workers). Health Care workers had the highest complaint rates (81 per 100,000 workers) but the second lowest COVID-19 death rate (81 per 100,000 workers). Industries with the highest inspection rates also had high COVID-19 mortality. Our findings suggest complaints are not proportional to COVID-19 risk. Instead, higher complaint rates may reflect worker groups with greater empowerment, resources, or capacity to advocate for better protections. This capacity to advocate for safe workplaces may account for relatively low mortality rates in potentially high-risk occupations. Future research should examine factors determining worker complaints and complaint systems to promote participation of those with the greatest need of protection.

Outbreak of COVID-19 among vaccinated and unvaccinated homeless shelter residents — Sonoma County, California, July 2021 (preprint)

In July 2021, the Sonoma County Health Department was alerted to three cases of COVID-19 among residents of a homeless shelter in Santa Rosa, California. Among 153 shelter residents, 83 (54%) were fully vaccinated; 71 (86%) vaccinated residents had received the Janssen COVID-19 vaccine and 12 (14%) received an mRNA (Pfizer BioNTech or Moderna) COVID-19 vaccine. Within 1 month, 116 shelter residents (76%) received positive SARS-CoV-2 test results, including 66 fully vaccinated residents and 50 not fully vaccinated. 9 fully vaccinated and 1 unvaccinated were hospitalized for COVID-19. All hospitalized cases had at least one underlying medical condition. Two deaths occurred, one in a vaccinated resident and one in a non-vaccinated resident. Specimens from 52 residents underwent whole genome sequencing; all were identified as SARS-CoV-2, Delta Variant AY.13 lineage. Additional mitigation measures are needed in medically vulnerable congregate setting where limited resources make individual quarantine and isolation not feasible.

Rapid increase of SpO2 on room air for 34 severe COVID-19 patients after ivermectin-based combination treatment: 55-62% normalization within 12-24 hours (preprint)

Background: . The emergence of COVID-19 in March 2020 challenged Zimbabwe to mount a response with limited medical facilities and therapeutic options. Ivermectin (IVM) had by then been safely used to treat a variety of human diseases affecting millions, as noted by the Nobel Committee in awarding its 2015 prize for medicine. Based upon early clinical indications of efficacy against COVID-19, IVM-based combination treatments were deployed to treat this infection in Zimbabwe. Methods: . Data were retrospectively analyzed for 34 severe COVID-19 patients treated with IVM-based combination therapy between August 2020 and May 2021, for whom pre- and post-treatment SpO2 values were all recorded on room air. Mortality and deterioration outcomes were also analyzed for a larger set of 92 severe COVID-19 patients receiving IVM-based treatment. Results: For the 34-patient SpO2 tracking series, all but two patients had significantly increased SpO2 values after the first IVM dose, and all patients recovered. Mean increases in SpO2 as percentages of full normalization to SpO2=97 were 55.1% at +12 hours and 62.3% at +24 hours post-treatment. These results paralleled similar sharp increases in SpO2, all on room air, for a series of 24 RT-qPCR confirmed, mostly severe COVID-19 patients in the USA (California) who were given IVM combination treatment, all of whom recovered. For 19 of those patients having SpO2 ≤ 90 prior to IVM, the mean SpO2 normalization at +24 hours post-treatment was 65.2% as calculated from the SpO2 values reported. For our larger series of 92 severe COVID-19 patients in Zimbabwe, median age 53, only two died and two more deteriorated prior to recovery, far less than a predicted 7 deaths and 17 deteriorations for the demographics and risk factors of these patients. Conclusions: . The rapid, marked increases in SpO2 for both the Zimbabwe and California patients stand in sharp contrast to the decline in SpO2 and associated pulmonary function following onset of moderate or severe COVID-19 symptoms under standard care. These rapid SpO2 increases and low mortality rates support extended deployment of IVM treatment for COVID-19, complementary to immunizations for prevention.