Your Outpatient has Coronavirus Disease 2019: What Are the Treatment Options in the Current Severe Acute Respiratory Syndrome Coronavirus 2 Variant Climate?

Mutations accumulated by novel Severe Acute Respiratory Syndrome Coronavirus 2 Omicron sublineages contribute to evasion of previously effective monoclonal antibodies for treatment or prevention of Coronavirus Disease 2019 (COVID-19). Other authorized or approved antiviral drugs such as nirmatrelvir/ritonavir, remdesivir, and molnupiravir are, however, predicted to maintain activity against these sublineages and are key tools to reduce severe COVID-19 outcomes in vulnerable populations. A stepwise approach may be taken to target the appropriate antiviral drug to the appropriate patient, beginning with identifying whether a patient is at high risk for hospitalization or other complications of COVID-19. Among higher risk individuals, patient profile (including factors such as age, organ function, and comedications) and antiviral drug access inform suitable antiviral drug selection. When applied in targeted fashion, these therapies serve as a complement to vital ongoing nonpharmaceutical interventions and vaccination strategies that reduce morbidity and maximize protection against COVID-19.

COVID-19 vaccine coverage disparities in rural and farm children.

BACKGROUND: The risks of severe outcomes associated with SARS-CoV-2 (COVID-19) are elevated in unvaccinated individuals. It remains crucial to understand patterns of COVID-19 vaccination, particularly in younger and remote populations where coverage often lags. This study examined disparities in COVID-19 vaccine coverage in farm children and adolescents. METHODS: A cross-sectional analysis was conducted in patients of the Marshfield Clinic Health System (MCHS) in Wisconsin. The sample included children/adolescents age 5-17 years who were eligible for COVID-19 vaccine initiation for ≥ 90 days (as of September 30, 2022), stratified by those who lived vs did not live on a farm. Outcomes included COVID-19 vaccine initiation, series completion, and booster receipt. Multivariable regression was used to examine associations between COVID-19 vaccination and farm, as well as rural and non-rural, residence. RESULTS: There were 47,104 individuals (5% farm residents) in the sample. Overall, 33% of participants initiated and 31% completed the COVID-19 vaccine series. After adjustment, farm residence was associated with significantly lower odds of COVID-19 vaccine initiation (aOR [95% CI] = 0.68 [0.61, 0.75], p < 0.001), series completion (aOR = 0.67 [0.60, 0.75], p < 0.001), and booster receipt (aOR = 0.73 [0.61, 0.88], p = 0.001). Secondary analyses found COVID-19 vaccine coverage was lowest in young children who lived on dairy farms. CONCLUSIONS: COVID-19 vaccine coverage is low in north-central Wisconsin children and adolescents. Those who live on farms have significantly lower likelihood of COVID-19 vaccine initiation, series completion, and booster receipt compared to non-farm counterparts. Farm families are an underserved group and require more effective public health interventions designed to prevent COVID-19.

Effectiveness of COVID-19 Vaccines Over Time Prior to Omicron Emergence in Ontario, Canada: Test-Negative Design Study.

Background: Waning protection from 2 doses of coronavirus disease 2019 (COVID-19) vaccines led to third dose availability in multiple countries even before the emergence of the Omicron variant. Methods: We used the test-negative study design to estimate vaccine effectiveness (VE) against any severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, any symptomatic infection, and severe outcomes (COVID-19-related hospitalizations or death) by time since second dose of any combination of BNT162b2, mRNA-1273, and ChAdOx1 between January 11, and November 21, 2021, for subgroups based on patient and vaccine characteristics. Results: We included 261 360 test-positive cases (of any SARS-CoV-2 lineage) and 2 783 699 individuals as test-negative controls. VE of 2 mRNA vaccine doses decreased from 90% (95% CI, 90%-90%) 7-59 days after the second dose to 75% (95% CI, 72%-78%) after ≥240 days against infection, decreased from 94% (95% CI, 84%-95%) to 87% (95% CI, 85%-89%) against symptomatic infection, and remained stable (98% [95% CI, 97%-98%] to 98% [95% CI, 96%-99%]) against severe outcomes. Similar trends were seen with heterologous ChAdOx1 and mRNA vaccine schedules. VE estimates for dosing intervals <35 days were lower than for longer intervals (eg, VE of 2 mRNA vaccines against symptomatic infection at 120-179 days was 86% [95% CI, 85%-88%] for dosing intervals <35 days, 92% [95% CI, 91%-93%] for 35-55 days, and 91% [95% CI, 90%-92%] for ≥56 days), but when stratified by age group and subperiod, there were no differences between dosing intervals. Conclusions: Before the emergence of Omicron, VE of any 2-dose primary series, including heterologous schedules and varying dosing intervals, decreased over time against any infection and symptomatic infection but remained high against severe outcomes.

Estimated Effectiveness of COVID-19 Vaccines Against Omicron or Delta Symptomatic Infection and Severe Outcomes.

Importance: The incidence of SARS-CoV-2 infection, including among individuals who have received 2 doses of COVID-19 vaccine, increased substantially following the emergence of the Omicron variant in Ontario, Canada. Understanding the estimated effectiveness of 2 or 3 doses of COVID-19 vaccine against outcomes associated with Omicron and Delta infections may aid decision-making at the individual and population levels. Objective: To estimate vaccine effectiveness (VE) against symptomatic infections due to the Omicron and Delta variants and severe outcomes (hospitalization or death) associated with these infections. Design, Setting, and Participants: This test-negative case-control study used linked provincial databases for SARS-CoV-2 laboratory testing, reportable disease, COVID-19 vaccination, and health administration in Ontario, Canada. Participants were individuals aged 18 years or older who had COVID-19 symptoms or severe outcomes (hospitalization or death) and were tested for SARS-CoV-2 between December 6 and 26, 2021. Exposures: Receipt of 2 or 3 doses of the COVID-19 vaccine and time since last dose. Main Outcomes and Measures: The main outcomes were symptomatic Omicron or Delta infection and severe outcomes (hospitalization or death) associated with infection. Multivariable logistic regression was used to estimate the effectiveness of 2 or 3 COVID-19 vaccine doses by time since the latest dose compared with no vaccination. Estimated VE was calculated using the formula VE = (1 - [adjusted odds ratio]) × 100%. Results: Of 134 435 total participants, 16 087 were Omicron-positive cases (mean [SD] age, 36.0 [14.1] years; 8249 [51.3%] female), 4261 were Delta-positive cases (mean [SD] age, 44.2 [16.8] years; 2199 [51.6%] female), and 114 087 were test-negative controls (mean [SD] age, 42.0 [16.5] years; 67 884 [59.5%] female). Estimated VE against symptomatic Delta infection decreased from 89% (95% CI, 86%-92%) 7 to 59 days after a second dose to 80% (95% CI, 74%-84%) after 240 or more days but increased to 97% (95% CI, 96%-98%) 7 or more days after a third dose. Estimated VE against symptomatic Omicron infection was 36% (95% CI, 24%-45%) 7 to 59 days after a second dose and 1% (95% CI, -8% to 10%) after 180 days or longer, but 7 or more days after a third dose, it increased to 61% (95% CI, 56%-65%). Estimated VE against severe outcomes was high 7 or more days after a third dose for both Delta (99%; 95% CI, 98%-99%) and Omicron (95%; 95% CI, 87%-98%). Conclusions and Relevance: In this study, in contrast to high estimated VE against symptomatic Delta infection and severe outcomes after 2 doses of COVID-19 vaccine, estimated VE was modest and short term against symptomatic Omicron infection but better maintained against severe outcomes. A third dose was associated with improved estimated VE against symptomatic infection and with high estimated VE against severe outcomes for both variants. Preventing infection due to Omicron and potential future variants may require tools beyond the currently available vaccines.

Predictors of all-cause mortality among patients hospitalized with influenza, respiratory syncytial virus, or SARS-CoV-2.

BACKGROUND: Shared and divergent predictors of clinical severity across respiratory viruses may support clinical and community responses in the context of a novel respiratory pathogen. METHODS: We conducted a retrospective cohort study to identify predictors of 30-day all-cause mortality following hospitalization with influenza (N = 45,749; 2010-09 to 2019-05), respiratory syncytial virus (RSV; N = 24 345; 2010-09 to 2019-04), or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; N = 8988; 2020-03 to 2020-12; pre-vaccine) using population-based health administrative data from Ontario, Canada. Multivariable modified Poisson regression was used to assess associations between potential predictors and mortality. We compared the direction, magnitude, and confidence intervals of risk ratios to identify shared and divergent predictors of mortality. RESULTS: A total of 3186 (7.0%), 697 (2.9%), and 1880 (20.9%) patients died within 30 days of hospital admission with influenza, RSV, and SARS-CoV-2, respectively. Shared predictors of increased mortality included older age, male sex, residence in a long-term care home, and chronic kidney disease. Positive associations between age and mortality were largest for patients with SARS-CoV-2. Few comorbidities were associated with mortality among patients with SARS-CoV-2 as compared with those with influenza or RSV. CONCLUSIONS: Our findings may help identify patients at greatest risk of illness secondary to a respiratory virus, anticipate hospital resource needs, and prioritize local prevention and therapeutic strategies to communities with higher prevalence of risk factors.

Effectiveness of COVID-19 vaccines against symptomatic SARS-CoV-2 infection and severe outcomes with variants of concern in Ontario.

SARS-CoV-2 variants of concern (VOC) are more transmissible and may have the potential for increased disease severity and decreased vaccine effectiveness. We estimated the effectiveness of BNT162b2 (Pfizer-BioNTech Comirnaty), mRNA-1273 (Moderna Spikevax) and ChAdOx1 (AstraZeneca Vaxzevria) vaccines against symptomatic SARS-CoV-2 infection and COVID-19 hospitalization or death caused by the Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1) and Delta (B.1.617.2) VOC in Ontario, Canada, using a test-negative design study. We identified 682,071 symptomatic community-dwelling individuals who were tested for SARS-CoV-2, and 15,269 individuals with a COVID-19 hospitalization or death. Effectiveness against symptomatic infection ≥7 d after two doses was 89-92% against Alpha, 87% against Beta, 88% against Gamma, 82-89% against Beta/Gamma and 87-95% against Delta across vaccine products. The corresponding estimates ≥14 d after one dose were lower. Effectiveness estimates against hospitalization or death were similar to or higher than against symptomatic infection. Effectiveness against symptomatic infection was generally lower for older adults (≥60 years) than for younger adults (<60 years) for most of the VOC-vaccine combinations. Our findings suggest that jurisdictions facing vaccine supply constraints may benefit from delaying the second dose in younger individuals to more rapidly achieve greater overall population protection; however, older adults would likely benefit most from minimizing the delay in receiving the second dose to achieve adequate protection against VOC.

Background incidence rates of hospitalisations and emergency department visits for thromboembolic and coagulation disorders in Ontario, Canada for COVID-19 vaccine safety assessment: a population-based retrospective observational study.

OBJECTIVE: The objective of this study was to estimate background rates of selected thromboembolic and coagulation disorders in Ontario, Canada. DESIGN: Population-based retrospective observational study using linked health administrative databases. Records of hospitalisations and emergency department visits were searched to identify cases using International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada diagnostic codes. PARTICIPANTS: All Ontario residents. PRIMARY OUTCOME MEASURES: Incidence rates of ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, deep vein thrombosis, pulmonary embolism, idiopathic thrombocytopaenia, disseminated intravascular coagulation and cerebral venous thrombosis during five prepandemic years (2015-2019) and 2020. RESULTS: The average annual population was 14 million with 51% female. The mean annual rates per 100 000 population during 2015-2019 were 127.1 (95% CI 126.2 to 127.9) for ischaemic stroke, 22.0 (95% CI 21.6 to 22.3) for intracerebral haemorrhage, 9.4 (95% CI 9.2 to 9.7) for subarachnoid haemorrhage, 86.8 (95% CI 86.1 to 87.5) for deep vein thrombosis, 63.7 (95% CI 63.1 to 64.3) for pulmonary embolism, 6.1 (95% CI 5.9 to 6.3) for idiopathic thrombocytopaenia, 1.6 (95% CI 1.5 to 1.7) for disseminated intravascular coagulation, and 1.5 (95% CI 1.4 to 1.6) for cerebral venous thrombosis. Rates were lower in 2020 than during the prepandemic years for ischaemic stroke, deep vein thrombosis and idiopathic thrombocytopaenia. Rates were generally consistent over time, except for pulmonary embolism, which increased from 57.1 to 68.5 per 100 000 between 2015 and 2019. Rates were higher for females than males for subarachnoid haemorrhage, pulmonary embolism and cerebral venous thrombosis, and vice versa for ischaemic stroke and intracerebral haemorrhage. Rates increased with age for most of these conditions, but idiopathic thrombocytopaenia demonstrated a bimodal distribution with incidence peaks at 0-19 years and ≥60 years. CONCLUSIONS: Our estimated background rates help contextualise observed events of these potential adverse events of special interest and to detect potential safety signals related to COVID-19 vaccines.

Déterminants individuels et sociaux du test de dépistage du SRAS-CoV-2 et de l'obtention d'un résultat positif en Ontario, au Canada: une étude populationnelle.

CONTEXTE: Optimiser la réponse de la santé publique pour diminuer le fardeau de la COVID-19 nécessite la caractérisation de l'hétérogénéité du risque posé par la maladie à l'échelle de la population. Cependant, l'hétérogénéité du dépistage du SRAS-CoV-2 peut fausser les estimations selon le modèle d'étude analytique utilisé. Notre objectif était d'explorer les biais collisionneurs dans le cadre d'une vaste étude portant sur les déterminants de la maladie et d'évaluer les déterminants individuels, environnementaux et sociaux du dépistage et du diagnostic du SRAS-CoV-2 parmi les résidents de l'Ontario, au Canada. MÉTHODES: Nous avons exploré la présence potentielle de biais collisionneurs et caractérisé les déterminants individuels, environnementaux et sociaux de l'obtention d'un test de dépistage et d'un résultat positif à la présence de l'infection au SRAS-CoV-2 à l'aide d'analyses transversales parmi les 14,7 millions de personnes vivant dans la collectivité en Ontario, au Canada. Parmi les personnes ayant obtenu un diagnostic, nous avons utilisé des études analytiques distinctes afin de comparer les prédicteurs pour les personnes d'obtenir un résultat de test de dépistage positif plutôt que négatif, pour les personnes symptomatiques d'obtenir un résultat de test de dépistage positif plutôt que négatif et pour les personnes d'obtenir un résultat de test de dépistage positif plutôt que de ne pas obtenir un résultat positif (c.-à-d., obtenir un résultat de test de dépistage négatif ou ne pas obtenir de test de dépistage). Nos analyses comprennent des tests de dépistage réalisés entre le 1er mars et le 20 juin 2020. RÉSULTATS: Sur 14 695 579 personnes, nous avons constaté que 758 691 d'entre elles ont passé un test de dépistage du SRAS-CoV-2, parmi lesquelles 25 030 (3,3 %) ont obtenu un résultat positif. Plus la probabilité d'obtenir un test de dépistage s'éloignait de zéro, plus la variabilité généralement observée dans la probabilité d'un diagnostic était grande parmi les modèles d'études analytiques, particulièrement en ce qui a trait aux facteurs individuels. Nous avons constaté que la variabilité dans l'obtention d'un test de dépistage était moins importante en fonction des déterminants sociaux dans l'ensemble des études analytiques. Les facteurs tels que le fait d'habiter dans une région ayant une plus haute densité des ménages (rapport de cotes corrigé 1,86; intervalle de confiance [IC] à 95 % 1,75­1,98), une plus grande proportion de travailleurs essentiels (rapport de cotes corrigé 1,58; IC à 95 % 1,48­1,69), une population atteignant un plus faible niveau de scolarité (rapport de cotes corrigé 1,33; IC à 95 % 1,26­1,41) et une plus grande proportion d'immigrants récents (rapport de cotes corrigé 1,10; IC à 95 % 1,05­1,15), étaient systématiquement corrélés à une probabilité plus importante d'obtenir un diagnostic de SRAS-CoV-2, peu importe le modèle d'étude analytique employé. INTERPRÉTATION: Lorsque la capacité de dépister est limitée, nos résultats suggèrent que les facteurs de risque peuvent être estimés plus adéquatement en utilisant des comparateurs populationnels plutôt que des comparateurs de résultat négatif au test de dépistage. Optimiser la lutte contre la COVID-19 nécessite des investissements dans des interventions structurelles déployées de façon suffisante et adaptées à l'hétérogénéité des déterminants sociaux du risque, dont le surpeuplement des ménages, l'occupation professionnelle et le racisme structurel.

Social determinants of COVID-19 mortality at the county level

OBJECTIVE: To assess the associations between COVID-19 mortality and immigrant and farm worker population at the county level. METHODS: We used publicly accessible datasets to build a series of spatial autoregressive models assessing county level associations between COVID-19 mortality and (1) Percentage of Non-English speaking households, (2) percentage of individuals engaged in hired farm work, (3) percentage of uninsured individuals under the age of 65, and (3) percentage of individuals living at or below the poverty line. RESULTS: In urban counties (n=114), only population density was significantly associated with COVID19 mortality (b = 0.21, p <0.001). In non-urban counties (n=2,629), all hypothesized social determinants were significantly associated with higher levels of mortality. Percentage of uninsured individuals was associated with lower reported COVID-19 mortality (b = -0.36, p = 0.001). CONCLUSIONS: Individuals who do not speak English, individuals engaged in farm work, and individuals living in poverty may be at heightened risk for COVID-19 mortality in non-urban counties. Mortality among the uninsured may be being systematically undercounted in county and national level surveillance.

Effectiveness of BNT162b2 and mRNA-1273 covid-19 vaccines against symptomatic SARS-CoV-2 infection and severe covid-19 outcomes in Ontario, Canada: test negative design study.

OBJECTIVE: To estimate the effectiveness of mRNA covid-19 vaccines against symptomatic infection and severe outcomes (hospital admission or death). DESIGN: Test negative design study. SETTING: Ontario, Canada between 14 December 2020 and 19 April 2021. PARTICIPANTS: 324 033 community dwelling people aged ≥16 years who had symptoms of covid-19 and were tested for SARS-CoV-2. INTERVENTIONS: BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) vaccine. MAIN OUTCOME MEASURES: Laboratory confirmed SARS-CoV-2 by reverse transcription polymerase chain reaction (RT-PCR) and hospital admissions and deaths associated with SARS-CoV-2 infection. Multivariable logistic regression was adjusted for personal and clinical characteristics associated with SARS-CoV-2 and vaccine receipt to estimate vaccine effectiveness against symptomatic infection and severe outcomes. RESULTS: Of 324 033 people with symptoms, 53 270 (16.4%) were positive for SARS-CoV-2 and 21 272 (6.6%) received at least one dose of vaccine. Among participants who tested positive, 2479 (4.7%) were admitted to hospital or died. Vaccine effectiveness against symptomatic infection observed ≥14 days after one dose was 60% (95% confidence interval 57% to 64%), increasing from 48% (41% to 54%) at 14-20 days after one dose to 71% (63% to 78%) at 35-41 days. Vaccine effectiveness observed ≥7 days after two doses was 91% (89% to 93%). Vaccine effectiveness against hospital admission or death observed ≥14 days after one dose was 70% (60% to 77%), increasing from 62% (44% to 75%) at 14-20 days to 91% (73% to 97%) at ≥35 days, whereas vaccine effectiveness observed ≥7 days after two doses was 98% (88% to 100%). For adults aged ≥70 years, vaccine effectiveness estimates were observed to be lower for intervals shortly after one dose but were comparable to those for younger people for all intervals after 28 days. After two doses, high vaccine effectiveness was observed against variants with the E484K mutation. CONCLUSIONS: Two doses of mRNA covid-19 vaccines were observed to be highly effective against symptomatic infection and severe outcomes. Vaccine effectiveness of one dose was observed to be lower, particularly for older adults shortly after the first dose.

Individual and social determinants of SARS-CoV-2 testing and positivity in Ontario, Canada: a population-wide study.

BACKGROUND: Optimizing the public health response to reduce the burden of COVID-19 necessitates characterizing population-level heterogeneity of risks for the disease. However, heterogeneity in SARS-CoV-2 testing may introduce biased estimates depending on analytic design. We aimed to explore the potential for collider bias in a large study of disease determinants, and evaluate individual, environmental and social determinants associated with SARS-CoV-2 testing and diagnosis among residents of Ontario, Canada. METHODS: We explored the potential for collider bias and characterized individual, environmental and social determinants of being tested and testing positive for SARS-CoV-2 infection using cross-sectional analyses among 14.7 million community-dwelling people in Ontario, Canada. Among those with a diagnosis, we used separate analytic designs to compare predictors of people testing positive versus negative; symptomatic people testing positive versus testing negative; and people testing positive versus people not testing positive (i.e., testing negative or not being tested). Our analyses included tests conducted between Mar. 1 and June 20, 2020. RESULTS: Of 14 695 579 people, we found that 758 691 were tested for SARS-CoV-2, of whom 25 030 (3.3%) had a positive test result. The further the odds of testing from the null, the more variability we generally observed in the odds of diagnosis across analytic design, particularly among individual factors. We found that there was less variability in testing by social determinants across analytic designs. Residing in areas with the highest household density (adjusted odds ratio [OR] 1.86, 95% confidence interval [CI] 1.75-1.98), highest proportion of essential workers (adjusted OR 1.58, 95% CI 1.48-1.69), lowest educational attainment (adjusted OR 1.33, 95% CI 1.26-1.41) and highest proportion of recent immigrants (adjusted OR 1.10, 95% CI 1.05-1.15) were consistently related to increased odds of SARS-CoV-2 diagnosis regardless of analytic design. INTERPRETATION: Where testing is limited, our results suggest that risk factors may be better estimated using population comparators rather than test-negative comparators. Optimizing COVID-19 responses necessitates investment in and sufficient coverage of structural interventions tailored to heterogeneity in social determinants of risk, including household crowding, occupation and structural racism.

Delayed production of neutralizing antibodies correlates with fatal COVID-19.

Recent studies have provided insights into innate and adaptive immune dynamics in coronavirus disease 2019 (COVID-19). However, the exact features of antibody responses that govern COVID-19 disease outcomes remain unclear. In this study, we analyzed humoral immune responses in 229 patients with asymptomatic, mild, moderate and severe COVID-19 over time to probe the nature of antibody responses in disease severity and mortality. We observed a correlation between anti-spike (S) immunoglobulin G (IgG) levels, length of hospitalization and clinical parameters associated with worse clinical progression. Although high anti-S IgG levels correlated with worse disease severity, such correlation was time dependent. Deceased patients did not have higher overall humoral response than discharged patients. However, they mounted a robust, yet delayed, response, measured by anti-S, anti-receptor-binding domain IgG and neutralizing antibody (NAb) levels compared to survivors. Delayed seroconversion kinetics correlated with impaired viral control in deceased patients. Finally, although sera from 85% of patients displayed some neutralization capacity during their disease course, NAb generation before 14 d of disease onset emerged as a key factor for recovery. These data indicate that COVID-19 mortality does not correlate with the cross-sectional antiviral antibody levels per se but, rather, with the delayed kinetics of NAb production.

Social determinants of COVID-19 mortality at the county level.

As of August 2020, the United States is the global epicenter of the COVID-19 pandemic. Emerging data suggests that "essential" workers, who are disproportionately more likely to be racial/ethnic minorities and immigrants, bear a disproportionate degree of risk. We used publicly available data to build a series of spatial autoregressive models assessing county level associations between COVID-19 mortality and (1) percentage of individuals engaged in farm work, (2) percentage of households without a fluent, adult English-speaker, (3) percentage of uninsured individuals under the age of 65, and (4) percentage of individuals living at or below the federal poverty line. We further adjusted these models for total population, population density, and number of days since the first reported case in a given county. We found that across all counties that had reported a case of COVID-19 as of July 12, 2020 (n = 3024), a higher percentage of farmworkers, a higher percentage of residents living in poverty, higher density, higher population, and a higher percentage of residents over the age of 65 were all independently and significantly associated with a higher number of deaths in a county. In urban counties (n = 115), a higher percentage of farmworkers, higher density, and larger population were all associated with a higher number of deaths, while lower rates of insurance coverage in a county was independently associated with fewer deaths. In non-urban counties (n = 2909), these same patterns held true, with higher percentages of residents living in poverty and senior residents also significantly associated with more deaths. Taken together, our findings suggest that farm workers may face unique risks of contracting and dying from COVID-19, and that these risks are independent of poverty, insurance, or linguistic accessibility of COVID-19 health campaigns.

Social determinants of COVID-19 mortality at the county level.

OBJECTIVE: To assess the associations between COVID-19 mortality and immigrant and farm worker population at the county level. METHODS: We used publicly accessible datasets to build a series of spatial autoregressive models assessing county level associations between COVID-19 mortality and (1) Percentage of Non-English speaking households, (2) percentage of individuals engaged in hired farm work, (3) percentage of uninsured individuals under the age of 65, and (3) percentage of individuals living at or below the poverty line. RESULTS: In urban counties (n=114), only population density was significantly associated with COVID19 mortality (b = 0.21, p <0.001). In non-urban counties (n=2,629), all hypothesized social determinants were significantly associated with higher levels of mortality. Percentage of uninsured individuals was associated with lower reported COVID-19 mortality (b = -0.36, p = 0.001). CONCLUSIONS: Individuals who do not speak English, individuals engaged in farm work, and individuals living in poverty may be at heightened risk for COVID-19 mortality in non-urban counties. Mortality among the uninsured may be being systematically undercounted in county and national level surveillance.