Zeitschriftenartikel zum Thema „North dakota, census“

A funny thing happened on my way to becoming GODORT chair: after ten years as the regional Federal Depository Library coordinator at the University of Georgia, I accepted a new job outside of the government documents community. As of June 28, 2018, I am the associate dean of libraries for research and learning at North Dakota State University. Obviously, my new job was not on my radar when I agreed to run for GODORT chair-elect in 2017. And while I am no longer a depository coordinator, I am still tangentially involved with the depository community. NDSU is a shared regional with the University of North Dakota, and our regional depository coordinator—Susanne Caro, formerly of the University of Montana—reports to me. In fact, Susanne is the GODORT chair-elect, which makes North Dakota the nexus of GODORT for the next few years. Not bad for a state that, according to the Census Bureau, ranks forty-seventh in population!

In this article, we examine how demographic changes in Fargo and West Fargo, North Dakota between 2000 and 2017, including the resettlement of refugees, have impacted equitable educational arrangements in Fargo Public Schools (FPS) and West Fargo Public Schools (WFPS). Drawing on multiple data sources, including North Dakota’s Department of Public Instruction (DPI), Common Core of Data (CCD) available from the National Center for Educational Statistics (NCES) and block group data from the U.S. Census Bureau, we use Geographic Information Systems (GIS) to examine city and district level changes in the years 2000 and 2017. We also conduct descriptive statistics and a multivariate analysis of variance (MANOVA) to assess the relationships among Black student enrollment, performance on state tests and enrollment characteristics that include race and free and reduced lunch. Findings underscore the increasing isolation of students over time by race, socioeconomic background and language.

AbstractEarlier reports have summarized crop yield losses throughout various North American regions if weeds were left uncontrolled. Offered here is a report from the current WSSA Weed Loss Committee on potential yield losses due to weeds based on data collected from various regions of the United States and Canada. Dry bean yield loss estimates were made by comparing dry bean yield in the weedy control with plots that had >95% weed control from research studies conducted in dry bean growing regions of the United States and Canada over a 10-year period (2007 to 2016). Results from these field studies showed that dry bean growers in Idaho, Michigan, Montana, Nebraska, North Dakota, South Dakota, Wyoming, Ontario, and Manitoba would potentially lose an average of 50%, 31%, 36%, 59%, 94%, 31%, 71%, 56%, and 71% of their dry bean yield, respectively. This equates to a monetary loss of US $36, 40, 6, 56, 421, 2, 18, 44, and 44 million, respectively, if the best agronomic practices are used without any weed management tactics. Based on 2016 census data, at an average yield loss of 71.4% for North America due to uncontrolled weeds, dry bean production in the United States and Canada would be reduced by 941,000,000 and 184,000,000 kg, valued at approximately US $622 and US $100 million, respectively. This study documents the dramatic yield and monetary losses in dry beans due to weed interference and the importance of continued funding for weed management research to minimize dry bean yield losses.

Background: To investigate information sources utilized in pharmacists’ assessment of population-based health needs and/or community changes; and the association between information sources utilized and reported completion of continuing professional education topics. Methods: In 2017; licensed pharmacists (n = 1124) in North Dakota; South Dakota; Minnesota; Iowa; and Nebraska completed a questionnaire on continuing professional education and information sources on population-based health needs and community changes. Data were entered; cleaned and imported into Stata 11.1. Census Bureau county-level population density data were used to classify local area characteristics. Descriptive statistics and multivariate logistic regression analyses were performed. Results: Most sources of primary; county-level data on population-based health needs or community changes were minimally utilized. Pharmacists in more rural areas were statistically more likely to use local health professionals; local non-health professionals; and/or the state health department compared to pharmacists in less rural areas. Pharmacists reporting higher use of population-based information sources were more likely to have completed continuing education in the past 12 months for all 21 surveyed topics; 13 significantly so. Conclusions: There is a reliance of pharmacists on information from local health and non-health professionals for information on population-based health needs and/or community changes. Utilization of health departments and other primary information sources was associated with increased rates of completion of an array of continuing professional education topics. Expanding utilization of evidence-driven information sources would improve pharmacists’ ability to better identify and respond to population-based health needs and/or community changes through programs and services offered; and tailor continuing professional education to population-based health needs.

Introduction: Chronic lymphocytic leukemia (CLL) accounts for the highest number of leukemia diagnoses in adults over 19 and nearly 25% of new adult leukemia cases. CLL commonly affects older adults with a median age of 70 at diagnosis. Although the 5-year survival rate of CLL is high at 88%, there are disparities among various groups within the United States (U.S.) with marginalized groups experiencing lower survival than their counterparts. Currently, no study has assessed geographic and demographic trends in CLL mortality in older adults (65+) in the U.S. Our aim was to analyze demographic differences and trends in CLL mortality in older adults (65+) within the U.S. between 1999 to 2020. Methods: The CDC (Centers for Disease Control) Wonder database was used to determine mortality statistics for patients, 65 years or older, with an underlying cause of death from CLL (ICD-10 code C91.1) between 1999 and 2020. Age-adjusted mortality rates (AAMR) were calculated per 100,000 deaths. The AAMR was calculated by demographic variables such as race (Hispanic, Non-Hispanic Black, Non-Hispanic White), population density (Urban, Suburban, Rural), sex, state, and U.S. census region. Joinpoint regression software was used to identify temporal trends. Average annual percent change (APC) was considered statistically significant if p< 0.05. Results: Between 1999 and 2020, CLL accounted for 85,371 deaths in adults 65 years or older. During this time, the overall AAMR decreased by 30% from 11.2 to 7.8 with an APC of -1.7% (p<0.05). In 1999, men had an AAMR of 16.1, nearly double the female AAMR of 8.1. By 2020, both groups experienced a drop in AAMR with men at 11.4 and females at 5.1. Both groups experienced a significant drop in overall APC with a drop of -1.7 for men and -2.1 for females. Non-Hispanic Whites had the highest AAMR at 11.9 and had a decrease in APC at -1.4 (p<0.05). Non-Hispanic Blacks had an AAMR high of 9.6 and had the highest decrease in APC at -2.4 (p<0.05). Hispanic individuals had an AAMR high of 4.4 and had the lowest decrease in APC at -1.3 (p<0.05). Analysis by population density revealed the highest decrease in APC occurring in urban populations at -2.3 (p<0.05), and the lowest decrease in rural populations at -1.2. All census regions (Northeast, Midwest, South, and West) had significant drops in APC with the South having the largest decrease in APC at -2.1 (p<0.05) and the Northeast having the lowest drop in APC at -1.5 (p<0.05). States in the 90th percentile of mortality included Iowa, North Dakota, and South Dakota, whereas Hawaii, Nevada, and New Mexico were in the 10th percentile of mortality. Conclusions: Although the mortality rate for CLL in the U.S. has been decreasing since 1999, there are differences in the rate of decrease apparent amongst various demographic groups. This may be due to several factors, including longer travel times to see oncologists in rural areas or lack of access to newer treatments for these patients. Given that the typical presentation for CLL is asymptomatic and that there are few identifiable risk factors for CLL it has made identification of vulnerable patients challenging. However, demographic background may help to identify potential patients at risk for developing and experiencing higher mortality rates due to CLL.

231 Background: Prostate Cancer (PCa) is the most common cancer in men and the second cause of cancer mortality. The identification of the preferred place of death (PPOD) has been shown to improve the delivery of palliative care, reduce healthcare costs, and improve quality of care. We evaluated the trends in PPOD for patients and hospice utilization with PCa in the USA from 2003 to 2020 based on the CDC WONDER (Centers for Disease Control and Prevention for Wide-ranging Online Data for Epidemiologic Research) database. Methods: The US nationwide and state-level data was pooled using the CDC WONDER database from January 01, 2003, to December 31, 2020. The data trends of PPOD for prostate cancer were pooled using the International Classification of Diseases, Tenth Revision as C61: malignant neoplasm of prostate. The analysis of trends in mortality over the past decade was stratified according to age, census region, race, and place of death. Results: The analysis demonstrated that overall mortality due to PCa was 526,783 from 2003 to 2020. Of these deaths, 43,813 (8.32%) were recorded in hospice facilities. The hospice mortality steadily increased from 0.4% in 2003 to the highest of 9.20% in 2019, with a notable decline to 7.6% in 2020. We noticed that the PPOD differed based on racial subgroups. More than half of mortality in the Native American (NA) and African-American (AA) subgroups was observed in a medical facility (51.81% and 58.21%, respectively) compared to Whites (49.15%). Hospice or death at home in NA and AA groups were (48.11% and 41.11%, respectively) compared to Whites (50.85%). The age-stratified mortality analysis revealed increased hospice utilization in 25-44 years (11.95%) vs. 65+ years (8.13%). Upon stratifying the results by census showed the highest hospice utilization in Florida, compared to the lowest in North Dakota (22.6% vs. 0.02%). Conclusions: To our knowledge, this is the first study utilizing the CDC WONDER database to analyze PPOD in PCa-related deaths. We observed a steady increase in hospice utilization from 2003 to 2019 throughout the US, with a decline in 2020, possibly due to the COVID-19 pandemic. The AA and NA groups had higher mortality in medical facilities compared to Whites, whereas the White population utilized more hospice services or died at home. This highlights the existing disparities in end-of-life care in PCa and promotes policy-level changes in the states with lower utilization of hospice services to improve access of care in PCa patients.

1525 Background: The trials of bispecific antibodies to treat diffuse large B-cell lymphoma (DLBCL) have increased exponentially. However, there is a geographic limitation to offering these trials and universal access appears to be limited. Here, we investigate the geographical and racial disparities in accessing bispecific antibodies trials for DLBCL. Methods: We searched ClinicalTrials.gov using the terms for DLBCL and bispecific antibodies. A total of 13 out of 51 clinical trials with one or more open sites in the United States (US) were included in this systematic review. 2020 US Census Bureau data was used to obtain data on race and ethnicity. Analysis for this study was performed using SPSS version 26. Results: The majority of the included trials were Phase I (62%) followed by Phase II (23%), and Phase I/II (15%). A total of 885 participants were either enrolled or expected to enroll in these clinical trials. Nine (69%) clinical trials were only open in the US while 4 (31%) clinical trials were open in the US and other countries. The majority of the trials were funded by the pharmaceutical industry 62%. There were 50 unique study sites distributed over 24 states with a 2.4 (1-10) mean number of trials per state and 9.9 (1-39) mean number of sites per trial. Study sites were distributed in 24 different states. Midwestern states had the highest number of trials 28%, followed by Southern 26%, Northeastern 24%, and Western 22%. The highest number of study locations (10) and the highest number of open studies (10) were in California. Twenty-seven states had no open bispecific antibodies trials including three in the Northeast (Maine, Rhode Island, and Vermont), five in the Midwest (Illinois, Indiana, Nebraska, North and South Dakota), eight in the South (Delaware, Virginia, District of Columbia, West Virginia, Mississippi, Arkansas, Louisiana, and Oklahoma), and eleven in the West (Arizona, Colorado, Idaho, New Mexico, Montana, Nevada, Wyoming, Alaska, Hawaii, Oregon, and Washington). Using US Census Bureau data, only 20% of African Americans (AA) (8 349 699 of 41 104 200) lived in a county with a bispecific antibodies trial. There were only five states (21%) with 50% or more of the AA population living in a county with an open bispecific antibodies trial and seven states (29%) with 30-49.9% of their AA county residents. Five states (21%) had less than 10% of the AA population living in a county with an open bispecific antibodies trial. Nine (90%) out of ten states with the highest proportion of AA residents (18.6%-41.4%) have no (five states) or only one clinical trial site (four states). Conclusions: There is significant geographic and racial disparity in accessing bispecific antibodies trials for DLBCL. Strategies should be framed to address the causes of the observed disparities and to improve access to these trials.

Abstract Colorectal cancer mortality rates among those diagnosed under age 50 have been rising. Geospatial patterns of young-onset colorectal cancer (yoCRC) mortality rates in the U.S. have received limited attention, and prior studies were limited by a lack of adjustment for demographic factors, a focus only on hot spots, and a lack of cluster-specific relative risks (RRs). Adjustment allows clusters to represent areas where modifiable factors may be driving anomalous mortality rates. Aggregated 1999-2019 yoCRC mortality data for 3,036 counties was obtained from CDC WONDER Underlying Cause of Death, and demographics were obtained from 2005-2019 census variables and 2015 Robert Graham Center data. Mortality rates were stabilized via spatial smoothing, then a quasi-Poisson model was fit with median age, sex, race/ethnicity, and social deprivation. Adjusted yoCRC death counts were utilized in a Poisson circular spatial scan to identify Gini hot/cold spots at a maximum cluster size of 6% of the population at risk. Resulting RRs signified clusters where adjusted deaths were higher or lower than expected based on population and adjusted total deaths. Three statistically significant hot spots and five statistically significant cold spots were identified. The cluster with the largest log-likelihood ratio was a southern hot spot region encompassing counties horizontally from eastern Texas to central Georgia and vertically from southern Louisiana to southern Kentucky (RR: 1.26; p<0.0001). Other notable clusters included hot spots centered in North Carolina (RR: 1.18; p<0.0001) and Ohio (RR: 1.18; p<0.0001), and large cold spots in western counties (Table 1). Our results reiterate southern and Appalachian hot spots from prior literature and provide new insights into a notable Ohio hot spot along with vast western cold spots. Future work is needed to identify established and potentially novel factors that may be driving yoCRC mortality clustering patterns, such as obesity, diet, or physician access. Table 1. Poisson spatial scan results adjusted for median age, sex, race, and social deprivation Gini cluster Classification States in cluster Relative risk Log-likelihood ratio Monte Carlo p-value 1 Hot spot Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Tennessee, Texas 1.28 139.03 p<0.0001 2 Hot spot Georgia, Kentucky, North Carolina, South Carolina, Tennessee, Virginia, West Virginia 1.18 63.31 p<0.0001 3 Cold spot Arizona, California, Colorado, Idaho, Nevada, New Mexico, Utah, Wyoming 0.83 61.95 p<0.0001 4 Hot spot Kentucky, Michigan, Ohio, Pennsylvania, West Virginia 1.16 40.14 p<0.0001 5 Cold spot California, Oregon, Washington 0.86 39.10 p<0.0001 6 Cold spot California 0.87 35.53 p<0.0001 7 Cold spot Texas 0.86 29.91 p<0.0001 8 Cold spot Colorado, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska, North Dakota, Wisconsin, Wyoming 0.90 19.56 p<0.0001 Citation Format: R. Blake Buchalter, Alok A. Khorana, Shimoli Barot, David Liska, Stephanie L. Schmit. Hot and cold spots of young-onset colorectal cancer mortality in U.S. counties, 1999-2019 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5907.

Introduction: The number of clinical trials of chimeric antigen receptor T- cell (CAR-T) therapy and bispecific antibodies to treat diffuse large B-cell lymphoma (DLBCL) has increased exponentially. However, there is geographic limitation to offering these trial and universal access appears to be limited especially for minorities and those in low socioeconomic stratum. Here, we investigate the geographical and racial disparities in accessing CAR-T cell therapy and bispecific antibodies trials for DLBCL. Methods: Data on clinical trials were obtained from ClinicalTrials.gov, the largest clinical trials registry database that provides data on clinical trials that are completed or in process. We searched ClinicalTrials.gov in May 2023 using the terms diffuse large B-cell lymphoma, DLBCL, CAR-T, chimeric antigen receptor T cells, chimeric, bispecific antibodies, bispecific, BCMA, and T-cell engager. All available trials listed as completed, recruiting, active-nonrecruiting, terminated, or suspended. The collected data abstracted from ClinicalTrials.gov included study titles, National Clinical Trial identification numbers, trial phase and intervention, actual or expected number of participants (in studies that did not complete enrollment), primary outcomes, recruiting sites, funders, and specific inclusion and exclusion criteria. 2020 United States (US) Census Bureau data was used to obtain data on race and ethnicity. Analysis for this study was performed using SPSS version 26. Results: A total of 76 out of 133 clinical trials with one or more open site in the US were included for this systematic review. There were 63 (82.9%) CAR-T therapy and 13 (17.1%) bispecific antibodies trials. A total of 166823 participants were either enrolled or expected to enroll in these clinical trials including 165938 (99.5%) of CAR-T and 885 (0.5%) bispecific antibodies clinical trials participants. Sixty-five (85.5%) clinical trials were only open in the US while 11 (14.5%) clinical trials were open in the US and other countries. The majority of the trials 49 (64.5%) were funded by the industry, while 27 (35.5%) were non-industry sponsored. The primary outcomes of the studies were safety related, efficacy related, and both safety and efficacy related in 43 (56.6%), 22 (28.9%), and 11 (14.5%) trials, respectively. One hundred and twenty-six unique study sites for the 76 analyzed clinical trials were identified. The mean number of sites per trial were 4.5 (1-26) for CAR-T trials and 4.4 (1-24) for bispecific antibodies. The study sites were distributed in 31 different states and mean number of trial per state were 11 (0-51). Most sites for trials were in Southern states 39 (31%), followed by Midwestern 32 (25.4%), Northeastern 30 (23.8%), and Western states 25 (19.8%). The highest number of study locations were in California (13), New York (9), and Pennsylvania (9) while the highest number of open studies were in California (51), Texas (32), and New York (23). Twenty states had no open CAR-T or bispecific antibodies clinical trials including three in the Northeast (Maine, Rhode Island, and Vermont), three in the Midwest (Indiana, North and South Dakota), seven in the South (Delaware, District of Columbia, West Virginia, Mississippi, Arkansas, Louisiana, and Oklahoma), and seven in the West (Idaho, New Mexico, Montana, Nevada, Wyoming, Alaska, and Hawaii). (Figure 1A) Using Census Bureau data, only 33.3% of the African American (AA) (13 669 915 of 41 104 200) lived in a county with a CAR-T or bispecific antibodies trial. There were only six states (12%) with 50% or more of the AA population living in a county with an open CAR-T or bispecific antibody trial and 15 states (29%) with 30% or more of their AA county residents. Seven out of ten states with the highest proportion of AA residents (18.6%-41.4%) have no (four states) or less than four clinical trial sites (three states) for either CAR-T or bispecific antibodies. (Figure 1B) Conclusion: There is significant geographic and racial disparity in accessing CAR-T cell therapy and bispecific antibodies trials for DLBCL. Strategies should be framed to address the causes for the observed disparities and to improve access.

This paper explores the possible uses that the recent creation of Micropolitan Statistical Areas by the US Census Bureau could have for advancing research in the area of Human Management. An example is provided using a sample of five Great Plain states (i.e., North Dakota, South Dakota, Nebraska, Kansas, and Oklahoma). Additionally, ten human resource management research propositions are suggested illustrating possible application of the micropolitan concept.

Abstract Introduction Transcatheter aortic valve replacement (TAVR) has overtaken surgical aortic valve replacement and revolutionized the treatment strategy for aortic valve replacement. Little is known on the disparities among minorities, especially American Indians (AI), undergoing this procedure. We explore TAVR outcomes to identify disparities at our institution. Methods Retrospective chart review was completed on patients who underwent TAVR at a North Dakota community hospital between 2012 and 2021. There were 1133 non-AI and 20 AI patients identified (n = 1153). AI patients were identified by enrollment in nationally recognized tribes, Indian Health Service (IHS), or who self-identified as AI. Patient demographics, preoperative characteristics, procedural information, and outcomes were collected. United States 2020 census data was used for state-wide population racial percentages. Unpaired two tail t test assuming unequal variance and chi-squared tests were used to evaluate data and identify disparities between AI and non-AI. Results AI presented at an earlier age (71 vs. 79; p = .001) with higher rates of diabetes (60% vs. 35%; p = .018) and history of smoking (100% vs. 60%; p ≤ .001) than Caucasian/white (C/W). The Society of Thoracic Surgery (STS) risk scores (3.2% vs. 4.6%; p = .054) and aortic valve mean gradients were lower among AI (42.8 mmHg vs. 47.5 mmHg; p = .010). For those deceased, AI had significantly shorter lifespans post-TAVR compared to C/W (374 days vs. 755 days; p = .004). AI from North Dakota had fewer TAVR procedures performed than expected (4 actual vs. 32 expected; p < .001). Conclusions AI undergoing TAVR presented earlier, with higher rates of diabetes and smoking, lower STS risk scores, and lesser aortic valve gradients than C/W. The number of TAVR procedures performed on AI from North Dakota was lower than anticipated despite a nearly 10-year period and the disparities experienced by AI who could have otherwise benefited from TAVR.

Abstract Background Access to maternity care in the U.S. remains inequitable, impacting over two million women in maternity care “deserts." Living in these areas, exacerbated by hospital closures and workforce shortages, heightens the risks of pregnancy-related complications, particularly in rural regions. This study investigates travel distances and time to obstetric hospitals, emphasizing disparities faced by those in maternity care deserts and rural areas, while also exploring variances across races and ethnicities. Methods The research adopted a retrospective secondary data analysis, utilizing the American Hospital Association and Centers for Medicaid and Medicare Provider of Services Files to classify obstetric hospitals. The study population included census tract estimates of birthing individuals sourced from the U.S. Census Bureau's 2017-2021 American Community Survey. Using ArcGIS Pro Network Analyst, drive time and distance calculations to the nearest obstetric hospital were conducted. Furthermore, Hot Spot Analysis was employed to identify areas displaying significant spatial clusters of high and low travel distances. Results The mean travel distance and time to the nearest obstetric facility was 8.3 miles and 14.1 minutes. The mean travel distance for maternity care deserts and rural counties was 28.1 and 17.3 miles, respectively. While birthing people living in rural maternity care deserts had the highest average travel distance overall (33.4 miles), those living in urban maternity care deserts also experienced inequities in travel distance (25.0 miles). States with hotspots indicating significantly higher travel distances included: Montana, North Dakota, South Dakota, and Nebraska. Census tracts where the predominant race is American Indian/Alaska Native (AIAN) had the highest travel distance and time compared to those of all other predominant races/ethnicities. Conclusions Our study revealed significant disparities in obstetric hospital access, especially affecting birthing individuals in maternity care deserts, rural counties, and communities predominantly composed of AIAN individuals, resulting in extended travel distances and times. To rectify these inequities, sustained investment in the obstetric workforce and implementation of innovative programs are imperative, specifically targeting improved access in maternity care deserts as a priority area within healthcare policy and practice.

The American Heart Association (AHA) Mission: Lifeline Stroke program is a 3-year initiative in North Dakota which aims to improve guideline-based care of stroke patients. Improving outcomes involves widespread awareness of stroke symptoms, early recognition, and timely access to emergency health care services. The purpose was to evaluate effectiveness of the public awareness campaign through a pre and post survey in 2018 and 2020 which assessed knowledge of the F.A.S.T acronym, actions and behaviors when stroke is suspected, and media preferences. The AHA commissioned Marketing & Advertising Business Unlimited, Inc., to conduct four hundred phone interviews in 2018 and 2020. Residents were randomly selected from a list of 24,000 landlines and 8,000 mobile phones. Data was weighted by gender, age, and region to conform to the latest statewide census. The survey had a 4.9% margin of error and a 95% confidence interval. Respondents reported having learned the signs and symptoms of stroke increased from 47.0% in 2018 to 68.3% in 2020. Awareness of symptoms changed as follows from 2018 to 2020: face related 30.0% to 43.1%; arm related 17.0% to 32.8%; speech related 39.0% to 41.0%. When asked what they would do first if stroke was suspected “Call 9-1-1- immediately” 64.0% to 70.7%, assess for F.A.S.T. symptoms then call 9-1-1 3% to 14.2%, drive themselves to the hospital 14% to 7.3% respectively in 2018 to 2020 . When asked if It would be better to transport someone experiencing stroke symptoms to a hospital by personal vehicle because driving could be faster than an ambulance in 2020 65% urban and 46% rural respondents disagreed. Media preferences were: 1) F.A.S.T. acronym over other longer options, 2) visuals with real humans 3) tagline “Care Starts When You Call”. In 2020 60% of respondents recalled advertisements about stroke signs and symptoms in the past 12 months. They recalled seeing messaging on: TV: 74.1%, Facebook: 20.1%, Radio: 19.1%, Billboard: 14.1%. Overall, the ND M:L public awareness communications were shown to have improved stroke symptom awareness and inclination to activate emergency services during a potential stroke. A preference for private vehicle presentation was noted in the rural cohort where transport time appears to be an influencing factor.

Introduction: Extracorporeal Membrane Oxygenation (ECMO) is a form of complete cardiopulmonary support which has been associated with improved survival in both severe acute respiratory distress syndrome and refractory cardiac arrest. ECMO is a resource-intensive therapy limited to specialized centers in urban environments, restricting its availability in suburban and rural areas. We examined the proportion of the U.S. population within a 15-minute, 30-minute, and 45-minute drivetime area to an ECMO-capable center. Methods: Using geographic information systems (GIS), we created shapefiles with polygons representing 15, 30, and 45-minute drivetime areas to ECMO-capable centers. Census block group centroids were then overlaid to determine the proportion of the population with access to ECMO-capable centers. Results: We found that 22%, 52%, and 67% of the U.S. population live within 15, 30, and 45 minutes of ECMO-capable centers, respectively. One hundred and ten million people, more than one third of the U.S. population, live further than 45 minutes away from an ECMO-capable center. Puerto Rico, Wyoming, North Dakota, and Alaska have 0% population access. Texas, California, and Florida have the highest number of people with low access (9, 8, and 5 million, respectively). Conclusion: Population access to ECMO-capable centers in the U.S. is highly variable and limits time-dependent interventions, which are essential for successful deployment of extracorporeal cardiopulmonary resuscitation in refractory cardiac arrest. Our GIS model can be used for future planning of ECMO systems to optimize access for the U.S. population or to comparatively evaluate proposals to improve access.

Background: Little research exists on sociodemographic and geographic inequalities in Long COVID, defined as COVID-19 symptoms lasting 3 months or longer. Using the latest nationally representative data, we examine geographic disparities in prevalence of Long COVID and severe COVID symptoms among United States (US) adults aged ≥18 years. Methods: We analyzed five consecutive rounds of the US Census Bureau’s Household Pulse Survey from June 1 to October 17, 2022 (N=108,064). Using multivariable logistic regression and health disparity indices, we modeled disparities in Long COVID and severe COVID symptoms by state and metropolitan area, controlling for race/ethnicity, socioeconomic status, health insurance, and other demographic characteristics. Results: During June–October 2022, an estimated 35.4 million or 32.2% of COVID patients in the US reported developing Long COVID; and 15.2 million or 13.8% of COVID patients reported experiencing severe COVID symptoms. The prevalence of Long COVID ranged from 24.0% in the District of Columbia (DC), 25.4% in Hawaii to 39.2% in Alabama, 39.9% in Wyoming, and 43.6% in West Virginia. Adjusted for covariates, adults with COVID-19 diagnosis in Alabama, Wyoming, and West Virginia had 48-178% higher adjusted odds of developing Long COVID than their counterparts in DC. Adults with COVID-19 diagnosis in Alabama, Arkansas, Colorado, Iowa, Kentucky, Mississippi, Montana, North Dakota, South Dakota,Texas, Utah, Virginia, Wyoming, and West Virginia had 2.0-2.5 times higher adjusted odds of experiencing severe COVID symptoms than their counterparts in Vermont. Large disparities in prevalence of Long COVID and severe COVID symptoms existed among the 15 largest metropolitan areas of the US, with the prevalence of Long COVID ranging from 21.9% in San Francisco to 38.0% in Riverside, California. Socioeconomic, demographic and health insurance characteristics explained 34% of the state-level disparity and 45% of the metropolitan-area disparity in Long COVID prevalence. Conclusion and Implications for Translation: Marked geographic disparities existed, with COVID patients/survivors in the Southeast, Southwest, and Northern Plains states being at substantially higher risks of developing Long COVID and severe COVID symptoms. Equitable access to care and support services among patients with Long COVID is critical to reducing inequities in COVID-related healthoutcomes. Copyright © 2023 Singh et al. Published by Global Health and Education Projects, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution License CC BY 4.0.

Abstract Introduction Diabetes and chronic kidney diseases are associated with a large health burden in the USA and globally. Objective To estimate age-standardized mortality rates by county from diabetes mellitus and chronic kidney disease. Design and setting Validated small area estimation models were applied to de-identified death records from the National Center for Health Statistics (NCHS) and population counts from the census bureau, NCHS, and the Human Mortality Database to estimate county-level mortality rates from 1980 to 2014 from diabetes mellitus and chronic kidney disease (CKD). Exposures County of residence. Main outcomes and measures Age-standardized mortality rates by county, year, sex, and cause. Results Between 1980 and 2014, 2,067,805 deaths due to diabetes were recorded in the USA. The mortality rate due to diabetes increased by 33.6% (95% UI: 26.5%–41.3%) between 1980 and 2000 and then declined by 26.4% (95% UI: 22.8%–30.0%) between 2000 and 2014. Counties with very high mortality rates were found along the southern half of the Mississippi river and in parts of South and North Dakota, while very low rates were observed in central Colorado, and select counties in the Midwest, California, and southern Florida. A total of 1,659,045 deaths due to CKD were recorded between 1980 and 2014 (477,332 due to diabetes mellitus, 1,056,150 due to hypertension, 122,795 due to glomerulonephritis, and 2,768 due to other causes). CKD mortality varied among counties with very low mortality rates observed in central Colorado as well as some counties in southern Florida, California, and Great Plains states. High mortality rates from CKD were observed in counties throughout much of the Deep South, and a cluster of counties with particularly high rates was observed around the Mississippi river. Conclusions and relevance This study found large inequalities in diabetes and CKD mortality among US counties. The findings provide insights into the root causes of this variation and call for improvements in risk factors, access to medical care, and quality of medical care.

Abstract Introduction Collagenase clostridium histolyticum (CCH, Xiaflex®; Endo Pharmaceuticals) is the only FDA-approved non-surgical therapy for Peyronie’s Disease (PD). CCH is an effective alternative to surgery for patients with PD who have a palpable plaque and a curvature deformity of ≥30°. Clinicians who administer CCH must complete risk mitigation training, and access to specialists varies by region across the US. Identifying areas with low provider availability may improve patient access to this and other treatments for PD. Objective To review the availability of clinicians offering CCH for the treatment of Peyronie’s Disease in the conterminous United States. Methods We utilized a publicly available search tool on a website provided by Endo Pharmaceuticals to identify certified providers offering CCH in the conterminous United States. We created a list of 23 zip codes that, when surrounded by a 500-mile radius, encompass the entire conterminous United States. We then utilized the search tool to identify providers within those radii. The data gathered included the provider’s name, specialty, and practice address. Duplicate addresses were removed, but a single provider offering CCH at 2 different locations was considered 2 different data points. We compared the data relative to the American Urological Association’s “The State of the Urology Workforce and Practice in the United States” and 2021 State Population Estimates from the US Census Bureau. Results In total, 1948 locations offering CCH were identified (Figure 1a). The mean number of locations offering CCH per 100,000 state residents was 0.61 [SD 0.27] (Figure 1b). Wyoming had the highest number of locations per 100k residents with 1.39. New Mexico had the lowest with 0.05. The 10 states with the highest ratio of clinicians/locations (from high-low) per capita were Wyoming, Georgia, Rhode Island, Nebraska, Maryland, New Jersey, Kansas, North Carolina, South Carolina, and Alabama. The 10 states with the lowest were New Mexico, Delaware, Maine, Mississippi, Minnesota, Vermont, Missouri, Indiana, New Hampshire, and Idaho. The mean proportion of urologists providing CCH to total urologists (Figure 1c) was 0.15 [SD 0.07]. Wyoming had the highest proportion of 0.40 and New Mexico had the lowest of 0.02. The 10 states with the highest proportion (from high-low) were Wyoming, Georgia, Utah, Nebraska, Kansas, Alabama, Nevada, Arizona, South Carolina, and Oklahoma. The 10 states with the lowest proportion (from low-high) were New Mexico, Delaware, Maine, Vermont, New Hampshire, Minnesota, Missouri, South Dakota, and Mississippi. Conclusions There are notable differences in the relative availability of CCH providers across the US. These discrepancies may impact access to care, supporting an opportunity to expand training efforts. States with low numbers of treatment locations offering CCH per 100k residents relative to other states also had a low total proportion of urologists offering CCH as a treatment. There is room for current practicing urologists in these states and others to expand their practice to offer CCH and improve patient access to this important non-surgical treatment option. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Endo Pharmaceuticals.

ObjectiveThis abstract aims to: 1) describe human WNV infections in Harris County excluding the City of Houston, Texas, 2003 to 2018; 2) explore geographical distributions of WNV positive mosquito pools in relation to human cases; 3) provide a brief overview of the county’s rigorous multidisciplinary WNV surveillance and control in mosquitoes and humans.IntroductionWest Nile virus (WNV) is the leading cause of autochthonous arboviral disease in the United States1. The virus is primarily spread to people through the bite of infected Culex species of mosquitos. WNV was first identified in Harris County, Texas, in 20022. Since then, the mosquito-borne virus has become endemic in the region, with surges in 2012 and 2014. Although majority of individuals infected are asymptomatic, WNV induced neuroinvasive infections often result in hospitalizations and adverse outcomes3-7, thus may pose a significant concern in public health and healthcare. The Harris County Public Health (HCPH) Surveillance and Epidemiology Unit (SEU) conducts surveillance of WNV in humans, in collaboration with Mosquito and Vector Control Division (MVCD) that monitors the virus in mosquito populations and birds. Mosquito abatement activities are implemented in areas where positive mosquitoes and human cases are identified. In this integrated model, clusters of WNV positive mosquito pools in relation with human cases provide comprehensive surveillance data to guide targeted efforts of mosquito control, disease prevention, and community education.MethodsSurveillance data of human WNV cases and WNV tested mosquito pools 2003 to 2018 in Harris County excluding the City of Houston were used for the analysis. Human cases included were confirmed and probable cases. Frequencies, percentages, age-adjusted annual average rates were used to describe the data. Geographical locations of WNV positive mosquito pools and human cases were mapped and analyzed using ESRI ArcGIS to determine the spatial relationship between the positive mosquito pools and human cases. Space-Time analysis was performed on 16 years of human disease data using Scan statistics in SatScan™ to test the effect of time and identify significant geographical clusters of WNV cases over time, which revealed a statistically significant cluster in 2012 to 2014 in northwest of Harris County. Subsequently, human cases and WNV positive mosquito pools of 2012 to 2014 were selected for hotspot analysis to verify the results from Satscan analysis and visualize the geographical cluster. Human cases were aggregated into census tracts and analyzed by optimized hotspot method; the positive mosquito pools were geocoded using their intersection locations and analyzed by ESRI Getis-Ord Gi hotspot method.ResultsFrom 2003 to 2018, a total of 295 confirmed and probable human WNV cases were identified, including 217 neuroinvasive and 78 fever cases. The median age of patients was 58 years old; 64.8% were male. The onset of majority of the cases (80.7%) concentrated in July to September. Among case-patients, 72.9% were hospitalized, and 3.4% died. The annual average age-adjusted incidence rate of WNV was 0.7 per 100,000 during 2003 to 2018. However, the rate was 1.8 and 2.7 per 100,000 in 2012 and 2014, respectively. Over 68% of the cases clustered in west and northwest of the county.The annual WNV positive mosquito pools ranged from 0.2% to 10.2% amongst the years. The number of WNV positive mosquito pools in 2014 was more than 4 times higher than the average number during those years, the highest record in the County.Hot spots of human cases and the positive mosquito pools were both identified in northwest Harris County. There was a significant geographical overlap between human cases and the positive mosquito pools.The space-time analysis for the 16 years detected a significant high-risk cluster in 2012 to 2014 in northwest Harris County. Findings from optimized hotspot analysis on human cases are consistent with the results from SatScan analysis. Statistically significant hot spots of positive mosquito pools identified by Getis-Ord Gi hotspot analysis displayed highly overlay with the statistically significant cluster of human cases detected by Satscan space-time analysis.ConclusionsWNV infection is underestimated. Studies suggest that every one case identified represent five infections 8-9. Therefore, the actual number of cases is likely substantially higher. Clinicians should be alerted in WNV season and consider testing and reporting as early as possible, especially in neuroinvasive patients. The public should be encouraged to utilize personal protection, particularly during peak seasons. This analysis shows that GIS mapping and optimized hotspot analysis of WNV human cases in relation to positive mosquito pools can provide statistical evidences of areas most affected, thus inform targeted mosquito control, prevention and education strategies in people living in areas with high virus activitieReferences1. Reimann CA, Hayes EB, DiGuiseppi C, et al. Epidemiology of neuroinvasive arbovrial disease in the United States, 1999-2007, Am J Trop Med Hyg, 2008:79:974-9.2. Kristy M. Lillibridge, Ray Parsons, Yvonne Randle, et al. The 2002 introduction of West Nile virus into Harris county, Texas, an area historically endemic for St. Louis encephalitis3. Mostashari F, Bunning ML, Kitsutani PT, et al. Epidemic West Nile encephalitis, New York, 1999: results of a household-based seroepidemiological survey. Lancet 2001;358:261-4.4. Busch MP, Wright DJ, Custer B, et al. West Nile virus infections projected from blood donor screening data, United States, 2003. Emerg Infect Dis 2006;12:395–402.5. Carson PJ, Borchardt SM, Custer B, et al. Neuroinvasive disease and West Nile virus infection, North Dakota, USA, 1999–2008. Emerg Infect Dis 2012;18:684–6.6. Sejvar JJ, Haddad MB, Tierney BC, et al. Neurologic Manifestations and outcome of west nile virus infection. JAMA. 2003 Jul 23;290(4):511-5.7. The outbreak of west nile virus infection in the New York City area in 19998. Surveillance for Human West Nile Virus Disease --- United States, 1999—2008, MMWR, April 2, 2010 / 59(SS02);1-179. West Nile Virus and Other Arboviral Diseases — United States, 2012, MMWR, June 28, 2013 / 62(25);513-517.