Spatiotemporal Ecologic Analysis of COVID-19 Vaccination Coverage and Outcomes, Oklahoma, USA, February 2020-December 2021.

Data on COVID-19 cases, deaths, hospitalizations, and vaccinations in Oklahoma, USA, have not been systematically described. The relationship between vaccination and COVID-19-related outcomes over time has not been investigated. We graphically described data collected during February 2020-December 2021 and conducted spatiotemporal modeling of monthly increases in COVID-19 cumulative death and hospitalization rates, adjusting for cumulative case rate, to explore the relationship. A 1 percentage point increase (absolute change) in the cumulative vaccination rate was associated with a 6.3% (95% CI 1.4%-10.9%) relative decrease in death outcome during April-June 2021, and a 1.9% (95% CI 1.1%-2.6%) relative decrease in death outcome and 1.1% (95% CI 0.5%-1.7%) relative decrease in hospitalization outcome during July-December 2021; the effect on hospitalizations was driven largely by data from urban counties. Our findings from Oklahoma suggest that increasing cumulative vaccination rates might reduce the increase in cumulative death and hospitalization rates from COVID-19.

Opioid and other drug use and drug-related mortality as indicators of Hepatitis C and Human Immunodeficiency Virus in Oklahoma.

OBJECTIVES: Outbreaks of injection drug use (IDU)-associated infections have become major public health concerns in the era of the opioid epidemic. This study aimed to (1) identify county-level characteristics associated with acute HCV infection and newly diagnosed IDU-associated HIV in Oklahoma and (2) develop a vulnerability index using these metrics. METHODS: This study employs a county-level ecological design to examine those diagnosed with acute or chronic HCV or newly diagnosed IDU-associated HIV. Poisson regression was used to estimate the association between indicators and the number of new infections in each county. Primary outcomes were acute HCV and newly diagnosed IDU-associated HIV. A sensitivity analysis included all HCV (acute and chronic) cases. Three models were run using variations of these outcomes. Stepwise backward Poisson regression predicted new infection rates and 95% confidence intervals for each county from the final multivariable model, which served as the metric for vulnerability scores. RESULTS: Predictors for HIV-IDU cases and acute HCV cases differed. The percentage of the county population aged 18-24 years with less than a high school education and population density were predictive of new HIV-IDU cases, whereas the percentage of the population that was male, white, Pacific Islander, two or more races, and people aged 18-24 years with less than a high school education were predictors of acute HCV infection. Counties with the highest predicted rates of HIV-IDU tended to be located in central Oklahoma and have higher population density than the counties with the highest predicted rates of acute HCV infection. CONCLUSIONS: There is high variability in county-level factors predictive of new IDU-associated HIV infection and acute HCV infection, suggesting that different public health interventions need to be tailored to these two case populations.

Achieving a Healthy Oklahoma: Cross-Sector Cooperation to Improve Public Health Preparedness and Pandemic Response.

In response to the COVID-19 pandemic, the University of Oklahoma Hudson College of Public Health launched the Achieving a Healthy Oklahoma (AHO) initiative in 2021. The goals of AHO were to assess lessons learned in Oklahoma from COVID-19 and set the foundation for enhanced public-private community collaboration by developing recommendations to prepare for future public health crises and promote health across all major economic sectors. Over 700 stakeholders were engaged in surveys, interviews, workgroup meetings, community listening sessions, and steering committee meetings over 8 months to accomplish these goals. Stakeholders produced 60 sector- and stakeholder-specific policy recommendations to address the major issues uncovered during the initiative. The AHO team then distilled them into 5 recommendations: (1) invest in the future of Oklahoma's health workforce to include critically needed public health professions in Oklahoma's healthcare loan repayment programs; (2) establish contracts between higher education institutions in Oklahoma and state and local health departments to monitor health sector workforce needs and provide training; (3) strengthen the delivery of coordinated public health services within local communities during emergencies and daily operations by dedicating health department roles to coordinate public health projects and services; (4) improve preparedness by coordinating annual emergency management exercises across local and state health departments; and (5) emphasize the efficiency and effectiveness of cross-sector collaborative efforts between public, private, and tribal partners. The AHO initiative serves as an action guide for assessing and improving state-level public health emergency responses and strengthening public health infrastructure. Implementing the recommendations in Oklahoma and assessing and addressing similar needs across the nation are necessary to prepare the United States for future public health emergencies.

Factors impacting medication adherence in a birth cohort at higher risk for Hepatitis C infection.

Due to the high prevalence of Hepatitis C virus (HCV) infection among individuals born between 1945 and 1965, in 2012 the Centers for Disease Control and Prevention began recommending HCV screening for this birth cohort. As adherence to HCV treatment is essential for sustained virologic response, identifying factors influencing medication adherence is important. The validated Adherence to Refills and Medications Scale (ARMS) is used to study recent medication adherence in those with chronic disease. This cross-sectional pilot study assesses factors associated with reduced adherence, indicated by higher ARMS scores, among individuals in this birth cohort. To elucidate factors associated with medication adherence, measured by the ARMS score, among a birth cohort at higher risk for HCV to guide future treatment and improve adherence. Patients born between 1945 and 1965, accessing care at an academic family medicine clinic, were recruited between April and June 2019. Demographics, prior HCV diagnosis, HCV risk factors (prior imprisonment, tattoos, and intravenous drug use), depression assessment (Patient Health Questionnaire-9), adverse childhood experiences (ACEs), and ARMS scores were collected. Mean ARMS scores were compared using t tests and analysis of variance (α = 0.05), while multiple variable models were performed using linear regression. Women comprised 58% of participants (n = 76), 52% reported depression and 37% 4 or more ACEs. The mean ARMS score was 16.3 (SD = 3.43) and 10% reported prior diagnosis of HCV. In the final multiple variable model, ARMS scores were 2.3 points higher in those with mild depression (95% CI: 0.63, 4.04), 2.0 in those with at least 4 ACEs (95% CI: 0.55, 3.49), and 1.8 in those with tattoos (95% CI: 0.30, 3.28). ACEs and food insecurity were identified as confounding variables in those with moderate to severe depression. This study found medication adherence was related to depression, ACEs, tattoos, and food insecurity among patients in this birth cohort at higher risk for HCV.

Evaluating the Accuracy of the Annual Statewide Kindergarten Vaccination Survey Submitted to Public Health Authorities by School Systems, Oklahoma, 2018.

Recent trends in vaccine hesitancy have brought to light the importance of using accurate school vaccination data. This study evaluated the accuracy of a pilot statewide kindergarten vaccination survey in Oklahoma. School vaccination and exemption data were collected from November 2017 to April 2018 via the Research Electronic Data Capture system. A multivariable linear regression model was used to evaluate the relationship between students who are up to date for all vaccines comparing school reported and Oklahoma State Department of Health-validated data. Adjusted vaccination data were overestimated by 1.0% among public schools and 3.3% among private schools. These results were validated by a random audit of participating schools finding the school-reported vaccination data to be overestimated by 0.6% compared to true student immunization records on file. Our analysis indicates that school-reported vaccination data are sufficiently valid. Immunization record audits provide confidence in available data, which drives evidence-based decision-making.

Cancer-associated venous thromboembolism: Incidence and features in a racially diverse population.

BACKGROUND: Data on the population-based incidence of cancer-associated venous thromboembolism (VTE) from racially diverse populations are limited. OBJECTIVE: To evaluate the incidence and burden of cancer-associated VTE, including demographic and racial subgroups in the general population of Oklahoma County-which closely mirrors the United States. DESIGN: A population-based prospective study. SETTING: We conducted surveillance of VTE at tertiary care facilities and outpatient clinics in Oklahoma County, Oklahoma, from 2012-2014. Surveillance included reviewing all imaging reports used to diagnose VTE and identifying VTE events from hospital discharge data and death certificates. Cancer status was determined by linkage to the Oklahoma Central Cancer Registry. MEASUREMENTS: We used Poisson regression to calculate crude and age-adjusted incidence rates of cancer-associated VTE per 100 000 general population per year, with 95% confidence intervals (95% CI). RESULTS: The age-adjusted incidence (95% CI) of cancer-associated VTE among adults age ≥ 18 was 70.0 (65.1-75.3). The age-adjusted incidence rates (95% CI) were 85.9 (72.7-101.6) for non-Hispanic Blacks, 79.5 (13.2-86.5) for non-Hispanic Whites, 18.8 (8.9-39.4) for Native Americans, 15.6 (7.0-34.8) for Asian/Pacific Islanders, and 15.2 (9.2-25.1) for Hispanics. Recurrent VTE up to 2 years after the initial diagnosis occurred in 38 of 304 patients (12.5%) with active cancer and in 34 of 424 patients (8.0%) with a history of cancer > 6 months previously. CONCLUSION: Age-adjusted incidence rates of cancer-associated VTE vary substantially by race and ethnicity. The relatively high incidence rates of first VTE and of recurrence warrant further assessment of strategies to prevent VTE among cancer patients.

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.

Exploring the Applicability of Using Natural Language Processing to Support Nationwide Venous Thromboembolism Surveillance: Model Evaluation Study.

Background: Venous thromboembolism (VTE) is a preventable, common vascular disease that has been estimated to affect up to 900,000 people per year. It has been associated with risk factors such as recent surgery, cancer, and hospitalization. VTE surveillance for patient management and safety can be improved via natural language processing (NLP). NLP tools have the ability to access electronic medical records, identify patients that meet the VTE case definition, and subsequently enter the relevant information into a database for hospital review. Objective: We aimed to evaluate the performance of a VTE identification model of IDEAL-X (Information and Data Extraction Using Adaptive Learning; Emory University)-an NLP tool-in automatically classifying cases of VTE by "reading" unstructured text from diagnostic imaging records collected from 2012 to 2014. Methods: After accessing imaging records from pilot surveillance systems for VTE from Duke University and the University of Oklahoma Health Sciences Center (OUHSC), we used a VTE identification model of IDEAL-X to classify cases of VTE that had previously been manually classified. Experts reviewed the technicians' comments in each record to determine if a VTE event occurred. The performance measures calculated (with 95% CIs) were accuracy, sensitivity, specificity, and positive and negative predictive values. Chi-square tests of homogeneity were conducted to evaluate differences in performance measures by site, using a significance level of .05. Results: The VTE model of IDEAL-X "read" 1591 records from Duke University and 1487 records from the OUHSC, for a total of 3078 records. The combined performance measures were 93.7% accuracy (95% CI 93.7%-93.8%), 96.3% sensitivity (95% CI 96.2%-96.4%), 92% specificity (95% CI 91.9%-92%), an 89.1% positive predictive value (95% CI 89%-89.2%), and a 97.3% negative predictive value (95% CI 97.3%-97.4%). The sensitivity was higher at Duke University (97.9%, 95% CI 97.8%-98%) than at the OUHSC (93.3%, 95% CI 93.1%-93.4%; P<.001), but the specificity was higher at the OUHSC (95.9%, 95% CI 95.8%-96%) than at Duke University (86.5%, 95% CI 86.4%-86.7%; P<.001). Conclusions: The VTE model of IDEAL-X accurately classified cases of VTE from the pilot surveillance systems of two separate health systems in Durham, North Carolina, and Oklahoma City, Oklahoma. NLP is a promising tool for the design and implementation of an automated, cost-effective national surveillance system for VTE. Conducting public health surveillance at a national scale is important for measuring disease burden and the impact of prevention measures. We recommend additional studies to identify how integrating IDEAL-X in a medical record system could further automate the surveillance process.

Cost-Benefit Analysis of Allowing Additional Time in Cleaning Hospital Contact Precautions Rooms.

Increasing cleaning time may reduce hospital-acquired transmission of Clostridioides difficile, methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant enterococcus (VRE). We constructed a cost-benefit model to estimate the impact of implementing an enhanced cleaning protocol, allowing hospital housekeepers an additional 15 minutes to terminally clean contact precautions rooms. The enhanced cleaning protocol saved the hospital $758 per terminally-cleaned room when accounting for only C. difficile. Scaling up to a hospital with 100 cases of C. difficile/year, and the US annual C. difficile incidence, cost savings were $75,832/year and $169.8 million/year, respectively. These results may inform infection control strategic decision-making and resource allocation.

Incidence of Venous Thromboembolism in a Racially Diverse Population of Oklahoma County, Oklahoma.

BACKGROUND: Contemporary incidence data for venous thromboembolism (VTE) from racially diverse populations are limited. The racial distribution of Oklahoma County closely mirrors that of the United States. OBJECTIVE: To evaluate VTE incidence and mortality, including demographic and racial subgroups. DESIGN: Population-based prospective study. SETTING: We conducted VTE surveillance at all relevant tertiary care facilities and outpatient clinics in Oklahoma County, Oklahoma during 2012 to 2014, using both active and passive methods. Active surveillance involved reviewing all imaging reports used to diagnose VTE. Passive surveillance entailed identifying VTE events from hospital discharge data and death certificate records. MEASUREMENTS: We used Poisson regression to calculate crude, age-stratified, and age-adjusted incidence and mortality rates per 1,000 population per year and 95% confidence intervals (CIs). RESULTS: The incidence rate of all VTE was 3.02 (2.92-3.12) for those age ≥18 years and 0.05 (0.04-0.08) for those <18 years. The age-adjusted incidence rates of all VTE, deep vein thrombosis, and pulmonary embolism were 2.47 (95% CI: 2.39-2.55), 1.47 (1.41-1.54), and 0.99 (0.93-1.04), respectively. The age-adjusted VTE incidence and the 30-day mortality rates, respectively, were 0.63 and 0.121 for Asians/Pacific Islanders, 3.25 and 0.355 for blacks, 0.67 and 0.111 for Hispanics, 1.25 and 0.195 for Native Americans, and 2.71 and 0.396 for whites. CONCLUSION: The age-adjusted VTE incidence and mortality rates vary substantially by race. The incidence of three per 1,000 adults per year indicates an important disease burden, and is informative of the burden in the U.S.

Age-sex specific pulmonary embolism-related mortality in the USA and Canada, 2000-18: an analysis of the WHO Mortality Database and of the CDC Multiple Cause of Death database.

BACKGROUND: Pulmonary embolism (PE)-related mortality is decreasing in Europe. However, time trends in the USA and Canada remain uncertain because the most recent analyses of PE-related mortality were published in the early 2000s. METHODS: For this retrospective epidemiological study, we accessed medically certified vital registration data from the WHO Mortality Database (USA and Canada, 2000-17) and the Multiple Cause of Death database produced by the Division of Vital Statistics of the US Centers for Disease Control and Prevention (CDC; US, 2000-18). We investigated contemporary time trends in PE-related mortality in the USA and Canada and the prevalence of conditions contributing to PE-related mortality reported on the death certificates. We also estimated PE-related mortality by age group and sex. A subgroup analysis by race was performed for the USA. FINDINGS: In the USA, the age-standardised annual mortality rate (PE as the underlying cause) decreased from 6·0 deaths per 100 000 population (95% CI 5·9-6·1) in 2000 to 4·4 deaths per 100 000 population (4·3-4·5) in 2006. Thereafter, it continued to decrease to 4·1 deaths per 100 000 population (4·0-4·2) in women in 2017 and plateaued at 4·5 deaths per 100 000 population (4·4-4·7) in men in 2017. Among adults aged 25-64 years, it increased after 2006. The median age at death from PE decreased from 73 years to 68 years (2000-18). The prevalence of cancer, respiratory diseases, and infections as a contributing cause of PE-related death increased in all age categories from 2000 to 2018. The annual age-standardised PE-related mortality was consistently higher by up to 50% in Black individuals than in White individuals; these rates were approximately 50% higher in White individuals than in those of other races. In Canada, the annual age-standardised mortality rate from PE as the underlying cause of death decreased from 4·7 deaths per 100 000 population (4·4-5·0) in 2000 to 2·6 deaths per 100 000 population (2·4-2·8) in 2017; this decline slowed after 2006 across age groups and sexes. INTERPRETATION: After 2006, the initially decreasing PE-related mortality rates in North America progressively reached a plateau in Canada, while a rebound increase was observed among young and middle-aged adults in the USA. These findings parallel recent upward trends in mortality from other cardiovascular diseases and might reflect increasing inequalities in the exposure to risk factors and access to health care. FUNDING: None.

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.

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.

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

Complete Table Top Exercise Manual.

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

Preparing for public health emergencies is an ongoing process and involves a variety of approaches and tools. Tabletop exercises are one of the tools designed to simulate the emergence of a public health emergency and address some or all of the phases of emergency management: mitigation, preparedness, response, and recovery.1 They typically are designed to include participation of stakeholders from diverse and complementary backgrounds, including command, operations, logistics, planning, and finance.2 Effective tabletop exercises provide a plausible scenario that require cooperation and communication from these functional areas. Tabletops also require forward thinking and planning in a variety of scenarios. When a public health emergency occurs, decision makers may be overwhelmed with decisions that need their immediate attention. Tabletop exercises can provide a framework to help decision makers anticipate future challenges, which may provide the mental model encompassing knowledge and insights that inform both current and future decisions.

Is There Less Opioid Abuse in States Where Marijuana Has Been Decriminalized, Either for Medicinal or Recreational Use? A Clin-IQ.

Opioid use, abuse, and associated mortality have reached an epidemic level. In some states, cannabis is being used to treat chronic pain. To examine the hypothesis that medical marijuana legislation may reduce adverse opioid-related outcomes if patients substitute cannabis for opioids for pain management, we conducted a clinical inquiry (Clin-IQ). We searched Ovid MEDLINE, Ovid MEDLINE In-Process, and Embase for studies using the search terms marijuana, cannabis, legal, marijuana smoking, medical marijuana, opioid-related disorders, cannabis use, medical cannabis, legal aspect, and opiate addiction. We included population-based articles published from January 1, 2012, through December 5, 2018, that assessed the relationship between marijuana use and decriminalization and the aforementioned opioid-related outcomes. Ten peer-reviewed studies met the inclusion criteria; 3 cross-sectional studies, 6 ecologic studies (ie, using aggregate data), and 1 retrospective cohort study. Eight studies reported associations between policies decriminalizing marijuana and reduced prescription opioid use, 1 study was inconclusive, and the retrospective cohort study reported an increase in adverse opioid-related outcomes. These results should be interpreted with caution given limitations associated with the studies' design. Results demonstrating association between marijuana decriminalization and opioid-related outcomes are mixed. Longitudinal studies are needed, and further analysis of this policy should continue to be tracked.