COVID-19 Testing Factors Among Great Plains American Indians.

BACKGROUND: COVID-19 created unparalleled challenges for vulnerable communities, especially among American Indians and Alaska Natives. An effective COVID-19 response requires a tribally driven effort to understand the perspectives of Tribal members on testing and to ensure that delivery strategies are grounded in the cultural values, traditions, and experiences of the Tribes. METHODS: We conducted a cross-sectional, anonymous survey in October 2021 using established methods to reach Tribal members residing in three Reservations in the Great Plains (N = 679). Multivariate analyses were conducted using logistic regression to assess the association between independent variables and COVID-19 testing uptake after adjusting for confounding. RESULTS: After multivariate adjustment, a respondent's employment status, ability to isolate if diagnosed with COVID-19, and endorsing that COVID-19 testing is only needed if one has symptoms were significantly correlated with having been previously tested for COVID-19. Participants without a full-time job were about half as likely to have been tested for COVID-19 compared to those with full-time jobs. Participants who reported not being able to isolate if they tested positive for COVID-19 and participants who did not think testing was needed if asymptomatic were also half as likely to be tested. CONCLUSIONS: Ensuring that everyone has the ability to isolate, that people who are not working have easy access to testing, and that everyone understands the value of testing after exposure are key steps to maximizing testing uptake. Efforts will only be successful if there is continued investment in programs that provide free testing access for everyone on Reservations.

Proteomic analysis of cardiometabolic biomarkers and predictive modeling of severe outcomes in patients hospitalized with COVID-19.

BACKGROUND: The high heterogeneity in the symptoms and severity of COVID-19 makes it challenging to identify high-risk patients early in the disease. Cardiometabolic comorbidities have shown strong associations with COVID-19 severity in epidemiologic studies. Cardiometabolic protein biomarkers, therefore, may provide predictive insight regarding which patients are most susceptible to severe illness from COVID-19. METHODS: In plasma samples collected from 343 patients hospitalized with COVID-19 during the first wave of the pandemic, we measured 92 circulating protein biomarkers previously implicated in cardiometabolic disease. We performed proteomic analysis and developed predictive models for severe outcomes. We then used these models to predict the outcomes of out-of-sample patients hospitalized with COVID-19 later in the surge (N = 194). RESULTS: We identified a set of seven protein biomarkers predictive of admission to the intensive care unit and/or death (ICU/death) within 28 days of presentation to care. Two of the biomarkers, ADAMTS13 and VEGFD, were associated with a lower risk of ICU/death. The remaining biomarkers, ACE2, IL-1RA, IL6, KIM1, and CTSL1, were associated with higher risk. When used to predict the outcomes of the future, out-of-sample patients, the predictive models built with these protein biomarkers outperformed all models built from standard clinical data, including known COVID-19 risk factors. CONCLUSIONS: These findings suggest that proteomic profiling can inform the early clinical impression of a patient's likelihood of developing severe COVID-19 outcomes and, ultimately, accelerate the recognition and treatment of high-risk patients.

COVID-19 and the future of clinical epidemiology.

Clinical epidemiology, the "basic science for clinical medicine"[1], has changed substantially over the last 50 years, moving its focus from clinician driven research and clinical settings to large cohorts and trials, NIH funding, and practice guidelines. The COVID-19 pandemic created major challenges for clinicians who needed to make urgent decisions about the management a new disease and for researchers who needed to understand the clinical syndrome and the questions of greatest importance to the pandemic response. Addressing these challenges reunited clinicians and researchers in collaborative efforts to inform decisions about disease risk, prevention, prognosis and treatment, at least in part because of the shared sense of the need to ration scarce resources, the rapid evolution of understanding of the clinical syndrome, the recognition of widespread uncertainty, and the emphasis on the common good over individual credit. Only time will tell whether the experience during COVID-19 will revive the original practice of clinical epidemiology as "the application by a physician who provides direct patient care, of epidemiologic and biometric methods to the study of diagnostic and therapeutic process in order to effect an improvement in health"[2].

Use of angiotensin converting enzyme inhibitors and angiotensin receptor blockers associated with lower risk of COVID-19 in household contacts.

BACKGROUND: Use of angiotensin converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) has been hypothesized to affect COVID-19 risk. OBJECTIVE: To examine the association between use of ACEI/ARB and household transmission of COVID-19. METHODS: We conducted a modified cohort study of household contacts of patients who tested positive for COVID-19 between March 4 and May 17, 2020 in a large Northeast US health system. Household members were identified by geocoding and full address matching with exclusion of addresses with >10 matched residents or known congregate living functions. Medication use, clinical conditions and sociodemographic characteristics were obtained from electronic medical record (EMR) data on cohort entry. Cohort members were followed for at least one month after exposure to determine who tested positive for SARS-CoV-2. Mixed effects logistic regression and propensity score analyses were used to assess adjusted associations between medication use and testing positive. RESULTS: 1,499 of the 9,101 household contacts were taking an ACEI or an ARB. Probability of COVID-19 diagnosis during the study period was slightly higher among ACEI/ARB users in unadjusted analyses. However, ACEI/ARB users were older and more likely to have clinical comorbidities so that use of ACEI/ARB was associated with a decreased risk of being diagnosed with COVID-19 in mixed effect models (OR 0.60, 95% CI 0.44-0.81) or propensity score analyses (predicted probability 18.6% in ACEI/ARB users vs. 24.5% in non-users, p = 0.03). These associations were similar within age and comorbidity subgroups, including patients with documented hypertension, diabetes or cardiovascular disease, as well as when including other medications in the models. CONCLUSIONS: In this observational study of household transmission, use of ACEIs or ARBs was associated with a decreased risk of being diagnosed with COVID-19. While causality cannot be inferred from these observational data, our results support current recommendations to continue ACEI/ARB in individuals at risk of COVID-19 exposure.

SARS-CoV-2 viral load is associated with increased disease severity and mortality.

The relationship between SARS-CoV-2 viral load and risk of disease progression remains largely undefined in coronavirus disease 2019 (COVID-19). Here, we quantify SARS-CoV-2 viral load from participants with a diverse range of COVID-19 disease severity, including those requiring hospitalization, outpatients with mild disease, and individuals with resolved infection. We detected SARS-CoV-2 plasma RNA in 27% of hospitalized participants, and 13% of outpatients diagnosed with COVID-19. Amongst the participants hospitalized with COVID-19, we report that a higher prevalence of detectable SARS-CoV-2 plasma viral load is associated with worse respiratory disease severity, lower absolute lymphocyte counts, and increased markers of inflammation, including C-reactive protein and IL-6. SARS-CoV-2 viral loads, especially plasma viremia, are associated with increased risk of mortality. Our data show that SARS-CoV-2 viral loads may aid in the risk stratification of patients with COVID-19, and therefore its role in disease pathogenesis should be further explored.