The Epidemiology of COVID-19 by Race/Ethnicity in Oklahoma City-County, Oklahoma (12 March 2020-31 May 2021).

We aimed to better understand the racially-/ethnically-specific COVID-19-related outcomes, with respect to time, to respond more effectively to emerging variants. Surveillance data from Oklahoma City-County (12 March 2020-31 May 2021) were used to summarize COVID-19 cases, hospitalizations, deaths, and COVID-19 vaccination status by racial/ethnic group and ZIP code. We estimated racially-/ethnically-specific daily hospitalization rates, the proportion of cases hospitalized, and disease odds ratios (OR) adjusting for sex, age, and the presence of at least one comorbidity. Hot spot analysis was performed using normalized values of cases, hospitalizations, and deaths generated from incidence rates per 100,000 population. During the study period, there were 103,030 confirmed cases, 3457 COVID-19-related hospitalizations, and 1500 COVID-19-related deaths. The daily 7-day average hospitalization rate for Hispanics peaked earlier than other groups and reached a maximum (3.0/100,000) in July 2020. The proportion of cases hospitalized by race/ethnicity was 6.09% among non-Hispanic Blacks, 5.48% among non-Hispanic Whites, 3.66% among Hispanics, 3.43% among American Indians, and 2.87% among Asian/Pacific Islanders. COVID-19 hot spots were identified in ZIP codes with minority communities. The Hispanic population experienced the first surge in COVID-19 cases and hospitalizations, while non-Hispanic Blacks ultimately bore the highest burden of COVID-19-related hospitalizations and deaths.

Characterization of persons with reported SARS-CoV-2 infection in the Oklahoma City tri-county area: Evidence from the first 12 months of transmission.

BACKGROUND: To describe characteristics, hospitalization, and death for reported cases of SARS-CoV-2 infection in the Oklahoma City tri-county area. METHODS: We extracted notified cases of SARS-CoV-2 infection for our study area and used descriptive statistics and modeling to examine case characteristics and calculate the odds of hospitalization and death in relation to a range of explanatory variables. RESULTS: Between March 12th, 2020 and February 28th, 2021, 124,925 cases of SARS-CoV-2 infection were reported from the study region. Being male, White or Black/African American, aged 50 years or older, presenting with apnea, cough, and shortness of breath, and having diabetes was associated with increased odds of hospitalization. The odds of dying were significantly associated with being Black/African American, presenting with cough and fever, having kidney disease and diabetes and being aged 70 years or older. CONCLUSIONS: The first cohort analysis of SARS-CoV-2 positive individuals in the Oklahoma City tri-county area confirms comorbidities and age as important predictors of COVID-19 hospitalization or death. As a novel aspect, we show that early symptoms of breathing difficulties in particular are associated with hospitalization and death. Initial case assessment and SARS-CoV-2 guidelines should continue to focus on age, comorbidities, and early symptoms.

COVID-19 Mortality Among American Indian and Alaska Native Persons - 14 States, January-June 2020.

American Indian/Alaska Native (AI/AN) persons experienced disproportionate mortality during the 2009 influenza A(H1N1) pandemic (1,2). Concerns of a similar trend during the coronavirus disease 2019 (COVID-19) pandemic led to the formation of a workgroup* to assess the prevalence of COVID-19 deaths in the AI/AN population. As of December 2, 2020, CDC has reported 2,689 COVID-19-associated deaths among non-Hispanic AI/AN persons in the United States.† A recent analysis found that the cumulative incidence of laboratory-confirmed COVID-19 cases among AI/AN persons was 3.5 times that among White persons (3). Among 14 participating states, the age-adjusted AI/AN COVID-19 mortality rate (55.8 deaths per 100,000; 95% confidence interval [CI] = 52.5-59.3) was 1.8 (95% CI = 1.7-2.0) times that among White persons (30.3 deaths per 100,000; 95% CI = 29.9-30.7). Although COVID-19 mortality rates increased with age among both AI/AN and White persons, the disparity was largest among those aged 20-49 years. Among persons aged 20-29 years, 30-39 years, and 40-49 years, the COVID-19 mortality rates among AI/AN were 10.5, 11.6, and 8.2 times, respectively, those among White persons. Evidence that AI/AN communities might be at increased risk for COVID-19 illness and death demonstrates the importance of documenting and understanding the reasons for these disparities while developing collaborative approaches with federal, state, municipal, and tribal agencies to minimize the impact of COVID-19 on AI/AN communities. Together, public health partners can plan for medical countermeasures and prevention activities for AI/AN communities.

Professors and Practitioners: Assessing the Impact of COVID-19 in the State of Oklahoma with and Without Residents of Long-Term Care Facilities.

Objectives: Our analysis, which began as a request from the Oklahoma Governor for useable analysis for state decision making, seeks to predict statewide COVID-19 spread through a variety of lenses, including with and without long-term care facilities (LTCFs), accounting for rural/urban differences, and considering the impact of state government regulations of the citizenry on disease spread. Methods: We utilize a deterministic susceptible exposed infectious resistant (SEIR) model designed to fit observed fatalities, hospitalizations, and ICU beds for the state of Oklahoma with a particular focus on the role of the rural/urban nature of the state and the impact that COVID-19 cases in LTCFs played in the outbreak. Results: The model provides a reasonable fit for the observed data on new cases, deaths, and hospitalizations. Moreover, removing LTCF cases from the analysis sharpens the analysis of the population in general, showing a more gradual increase in cases at the start of the pandemic and a steeper increase when the second surge occurred. Conclusions: We anticipate that this procedure could be helpful to policymakers in other states or municipalities now and in the future.

Tabletop exercise to prepare institutions of higher education for an outbreak of COVID-19.

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