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.

Predicting COVID-19 cases in diverse population groups using SARS-CoV-2 wastewater monitoring across Oklahoma City.

SARS-CoV-2 was discovered among humans in late 2019 and rapidly spread across the world. Although the virus is transmitted by respiratory droplets, most infected persons also excrete viral particles in their feces. This fact prompted a range of studies assessing the usefulness of wastewater surveillance to determine levels of infection and transmission and produce early warnings of outbreaks in local communities, independently of human testing. In this study, we collected samples of wastewater from 13 locations across Oklahoma City, representing different population types, twice per week from November 2020 to end of March 2021. Wastewater samples were collected and analyzed for the presence and concentration of SARS-CoV-2 RNA using RT-qPCR. The concentration of SARS-CoV-2 in the wastewater showed notable peaks, preceding the number of reported COVID-19 cases by an average of one week (ranging between 4 and 10 days). The early warning lead-time for an outbreak or increase in cases was significantly higher in areas with larger Hispanic populations and lower in areas with a higher household income or higher proportion of persons aged 65 years or older. Using this relationship, we predicted the number of cases with an accuracy of 81-92% compared to reported cases. These results confirm the validity and timeliness of using wastewater surveillance for monitoring local disease transmission and highlight the importance of differences in population structures when interpreting surveillance outputs and planning preventive action.