County Population Research Articles

Allocation Efficiency of Public Sports Resources Based on the DEA Model in the Top 100 Economic Counties of China in Zhejiang Province

Background: The county is the basic unit of national economic and social development, and is also the foothold and starting point of public sports services. Purpose: Taking the top 100 economic counties of China in Zhejiang Province as the research object, this study explores the allocation efficiency and influencing factors of public sports resources in the period of 2016 to 2020. Methods: The output-oriented Super-SBM model, which is used to measure the static efficiency of its public sports resource allocation, is combined with the DEA–Malmquist model to measure the total factor productivity from the perspectives of overall characteristics, regional heterogeneity, and individual differences. Moreover, we objectively evaluate the dynamic evolution and spatiotemporal characteristics of resource quality growth, financial management technology, and allocation efficiency from the horizontal cross-section and vertical time series. Results: (1) The efficiency of allocation of public sports resources in the top 100 economic counties in Zhejiang Province is relatively high, but it presents the characteristics of “extensive” allocation, and the allocation structure is unreasonable. (2) The super-efficiency gradient division of public sports resources shows that Yuhuan City ranks first with a state of super-efficiency allocation; Ruian, Linhai, Wenling, Yiwu, and Haining have a state of high-efficiency allocation; and other regions are characterized by a state of medium- or low-efficiency allocation. (3) The improvement of total factor productivity depends on the catching-up feature of technological efficiency on the production frontier, but it has not yet compensated for the negative effect of the decline of technological progress, resulting in a decline in total factor productivity with an average annual trend of 0.3%. (4) The level of county economic development has a highly significant positive effect on the allocation efficiency of public sports resources, while the per capita sports ground area has a highly significant negative effect on efficiency. The county population density has a highly significant impact, and regional factors have no significant effect on efficiency. Conclusions: The results of this study provide useful insights for the development of sound public sports service improvement policies.

Data-driven strategies for increasing patient diversity in Bristol Myers Squibb-sponsored US oncology clinical trials.

Determining whether clinical trial findings are applicable to diverse, real-world patient populations can be challenging when the full demographic characteristics of enrolled patients are not consistently reported. Here, we present the results of a descriptive analysis of racial and ethnic demographic information for patients in Bristol Myers Squibb (BMS)-sponsored oncology trials in the United States (US) and describe factors associated with increased patient diversity. BMS-sponsored oncology trials conducted at US sites with study enrollment dates between 1 January 2013 and 31 May 2021 were analyzed. Patient race/ethnicity information was self-reported in case report forms. As principal investigators (PIs) did not report their own race/ethnicity, a deep-learning algorithm (ethnicolr) was used to predict PI race/ethnicity. Trial sites were linked to counties to understand the role of county-level demographics. The impact of working with patient advocacy and community-based organizations to increase diversity in prostate cancer trials was analyzed. The magnitude of associations between patient diversity and PI diversity, US county demographics, and recruitment interventions in prostate cancer trials were assessed by bootstrapping. A total of 108 trials for solid tumors were analyzed, including 15,763 patients with race/ethnicity information and 834 unique PIs. Of the 15,763 patients, 13,968 (89%) self-reported as White, 956 (6%) Black, 466 (3%) Asian, and 373 (2%) Hispanic. Among 834 PIs, 607 (73%) were predicted to be White, 17 (2%) Black, 161 (19%) Asian, and 49 (6%) Hispanic. A positive concordance was observed between Hispanic patients and PIs (mean = 5.9%; 95% confidence interval (CI) = 2.4, 8.9), a less positive concordance between Black patients and PIs (mean = 1.0%; 95% CI = -2.7, 5.5), and no concordance between Asian patients and PIs. Geographic analyses showed that more non-White patients enrolled in study sites in counties with higher proportions of non-White residents (e.g. a county population that was 5%-30% Black had 7%-14% more Black patients enrolled in study sites). Following purposeful recruitment efforts in prostate cancer trials, 11% (95% CI = 7.7, 15.3) more Black men enrolled in prostate cancer trials. Most patients in these clinical trials were White. PI diversity, geographic diversity, and recruitment efforts were related to greater patient diversity. This report constitutes an essential step in benchmarking patient diversity in BMS US oncology trials and enables BMS to understand which initiatives may increase patient diversity. While complete reporting of patient characteristics such as race/ethnicity is critical, identifying diversity improvement tactics with the highest impact is essential. Strategies with the greatest concordance to clinical trial patient diversity should be implemented to make meaningful improvements to the diversity of clinical trial populations.

Does transportation infrastructure construction promote population agglomeration? Evidence from 1838 Chinese county-level administrative units

This study used panel data selected from 1838 county-level administrative regions for the period 2003–2018 on the opening of high-speed railway in China. Using the difference in difference (DID) method, the impact of transportation infrastructure construction on population agglomeration in different counties was studied by utilizing the exogenous impact of high-speed railway opening. Baseline regression results and robustness tests indicated that the opening of high-speed railways in the selected counties has significantly promoted population agglomeration compared to counties without high-speed railways. This result further proves that transportation infrastructure construction can directly improve a county's population agglomeration level, while labour mobility plays an effective intermediary role in the agglomeration effect. Also, the county population agglomeration effect produced by the construction of transportation infrastructure has a significant administrative division heterogeneity and geographical location heterogeneity. Additionally, due to the “siphon effect” and “trickle-down effect” of the central city, counties within different geographic distance circles exhibit different agglomeration characteristics after the construction of transportation infrastructure. Generally, with an increase in the distance from the central city, the population agglomeration effect shows an “inverted U-shaped” change trend where the threshold for high-speed rail is 200 km. This study provides theoretical support and a practical basis for railway layout, population element allocation, and coordinated regional development.

Demographics of the tumor formerly known as bronchiolo-alveolar carcinoma.

e20604 Background: Bronchiolo-alveolar carcinoma (BAC) is a rare subtype of non-small cell lung cancer of the lung periphery, often characterized by lepidic growth. Although BAC has undergone various reclassifications in recent years, International Classification of Disease codes still classifies these subtypes using the same codes that previously belonged to BAC. Changing diagnostic criteria and other factors cause BAC to be among the most overdiagnosed forms of lung cancer and thus a demographic study could provide insight into trends. Methods: A retrospective cohort analysis utilizing the National Cancer Database (NCDB) from 2004 – 2020 included patients with malignant forms of BAC (Invasive mucinous adenocarcinoma, mixed invasive mucinous, and nonmucinous adenocarcinoma) confirmed through histology. Demographic factors such as sex, age, race, Hispanic status, median household income, insurance status, facility type, county population, distance from facility, and Charlson Deyo score were analyzed by descriptive statistics and incidence trends. Results: In total, 12,607 patients were identified in the database with a confirmed diagnosis of BAC between 2004 – 2020. The number of cases per year remained steady (mean = 565.4) until 2018. From 2018 to 2020, the average number of diagnoses per year was 1575.0. The average age of diagnosis was 69.3 years (SD = 10.7, range = 10 to > 90 years). 58.1% of the cases were female patients. The top primary sites were the lower and upper lobes (46.2% and 39.9% respectively). The majority (59.2%) had Charlson-Deyo comorbidity scores of 0. Most cases occurred in Non-Hispanic White persons (86.8%). More patients were in the top quartile of income earners (34.0%) compared to those in lower quartiles. Medicare was the insurance provider for most patients (65.0%). More patients were diagnosed in counties with a population over 1 million (52.4%). More patients were treated in comprehensive community cancer programs (38.1%) followed closely by academic cancer programs (35.2%). Patients lived an average of 31.6 miles (SD = 113.0, range = 0.1 – 2390.7) from the treatment facility. Conclusions: This is the first NCDB analysis on the demographics of BAC. The sudden rise in cases per year in 2018 aligns with the changing pathologic and histologic definitions for BAC. A 2006 review of BAC found that 50-70% of cases occur in female patients, similar to our results. The majority of BAC patients tend to be non-Hispanic and White with a primary site diagnosis in the lower lobe, followed by the upper lobe. BAC patients are more likely to be in the top income quartile, live in densely-populated metropolitan areas, and receive treatment in a non-academic program. Further research is needed to better understand the impact of demographic, socioeconomic, and environmental factors on the diagnosis and prognosis of BAC, especially because its diagnostic criteria have changed recently.

The role of natural resources, clean energy and technology in mitigating carbon emissions in top populated countries

This study highlights the significance of natural resources, clean energy production, and technological advancement to control carbon emissions and to attain COP-26 targets in populous counties of the World. The empirical investigation is based on 30 years (1990–2019) of data analysis of 14 world’s highly populated countries. This study tries to investigate the aforementioned relationship by employing CS-ARDL econometric techniques that mitigate Cross-sectional Dependence and heterogeneity in slop parameters across panels. For this purpose, the study employed some additional independent variables such as economic growth. The empirical findings reveal the facts that high reliance on natural resources to earn more rent worsen the environmental quality. While, clean energy, and technological innovation brings economies toward a clean natural environment through carbon mitigation. The study suggests that the abundance of green natural resources, efficient use of natural resources may help to protect the natural environment even in those countries which are experiencing high population pressure. In addition, the study spot lights that clean energy production and improvement in technology are also helping to achieve the carbon neutrality targets of COP-26 in highly populated economies of the world.

ИЗМЕНЕНИЯ ГРАНИЦ РЕГИОНОВ ЦЕНТРАЛЬНОЙ РОССИИ В XVIII-XX ВВ

The article discusses the administrative-territorial division of Central Russia (within the modern Central Federal District) over the past three centuries. The purpose of the study was to find out how the composition of regional centers and the territories of the regions associated with them have changed during this time. There are two periods of the most active transformations - the provincial reform of Catherine II, 1775-1785, and a series of Soviet reforms of 1917- 1970, - between which the borders of the regions in the center of the country were stable. Based on a wide range of cartographic sources (both published and archival), accurate maps of the borders of the regions for 1760 (provinces and governorates) and 1792 (governorates) were compiled; then they were compared with each other and with the borders of modern regions. Based on this comparison, it was shown that the composition of regional centers in Central Russia was significantly stable: 13 of the 17 modern regional centers were previously the centers of provinces, and 12 of them were provinces even earlier. On the contrary, the borders changed significantly at each of the stages of transformation, which is related to specific circumstances: the provincial reform of Catherine II was carried out based primarily on the principle of approximate equality of the population of provinces and counties; Soviet transformations were based on the logic of industrial development. The historical ties of the territories in both cases were little taken into account, and as a result, in most cases the core of the region is surrounded by the periphery, which in the past changed its administrative registration. The work contains maps of the historical borders of each of the regions, which have independent scientific and practical significance.

The incidence of periocular melanoma: An epidemiologic study in Olmsted County, Minnesota

To the Editor: Melanoma arising in the periocular area presents a unique treatment challenge due to anatomic and functional constraints. To date, most information regarding periocular melanoma is gleaned from extrapolated data from other sites of the body, assuming similar biologic behavior. We aimed to identify the overall incidence, pathologic features, and surgical outcomes of periocular melanoma. Following Institutional Review Board (IRB) approval, using the Rochester Epidemiology Project (a multicenter medical records–linkage system encompassing the Olmsted County population), we identified patients with a first lifetime diagnosis of periocular melanoma between January 1, 1970, and December 31, 2020, while a local resident of Olmsted County, Minnesota. Outside (nonresident) referral cases were excluded. Periocular melanoma was defined as a melanoma arising within the orbital rim – on the upper or lower eyelid, lateral canthus, or eyebrow. A total of 10 patients with primary periocular melanoma were identified. The overall incidence rate of periocular melanoma was 0.2686 per 100,000 patient-years. Among all melanomas diagnosed during that timeframe in Olmsted County, 0.43% were periocular in location. No cases extended onto conjunctiva. The histogenic subtype was lentigo maligna in 8 (80.0%). There was 1 superficial spreading melanoma and 1 case without documentation of histogenic subtype. Incidence of in situ (50.0%) and invasive (50.0%) melanomas was equal. Among invasive melanomas, the average Breslow depth was 0.90 mm (range, 0.2-2.6 mm). Seven (70.0%) were treated with Mohs micrographic surgery (MMS). One (10%) was treated with wide local excision. The 2 cases that did not undergo further surgical treatment were both diagnosed prior to 2000 and were removed entirely via initial excisional biopsy. There was 1 regional metastasis to the parotid gland and lymph node, 2.5 years after diagnosis of a superficial spreading melanoma, Breslow 0.7 mm, status-post treatment with MMS. There were no other local or distant recurrences. There were no melanoma-specific deaths. Mean follow-up time was 7.4 years (range 3.1-13.2). This study demonstrates the relative rarity of periocular melanoma, comprising only 0.43% of all melanomas. Comparatively, basal cell carcinoma (BCC) occurs on the eyelid 16% of the time.1Salomon J. Bieniek A. Baran E. Szepietowski J.C. Basal cell carcinoma on the eyelids: own experience.Dermatol Surg. 2004; 30: 257-263PubMed Google Scholar Our study found an overall periocular melanoma incidence rate of 0.2686 per 100,000 patient-years. A previous Olmsted County cohort reported an incidence of eyelid BCC as 14.35 per 10,000 individuals per year, and an incidence of eyelid SCC as 1.37 cases per 100,000 individuals per year.2Cook Jr., B.E. Bartley G.B. Epidemiologic characteristics and clinical course of patients with malignant eyelid tumors in an incidence cohort in Olmsted County, Minnesota.Ophthalmology. 1999; 106: 746-750Abstract Full Text Full Text PDF PubMed Google Scholar The behavior of melanoma seems to parallel primary cutaneous melanoma of head and neck sites. Most tumors were associated with chronic sun exposure; 80% of cases were lentigo maligna subtype. There was 1 regional recurrence in our study, no distant recurrences, and no deaths due to melanoma. The most significant advantage of our study is in its epidemiologic design. The limitations of this study include the retrospective nature of our analysis and the homogenous demographics of Olmsted County, comprised of mostly Caucasian individuals of higher socioeconomic status.3St Sauver J.L. Grossardt B.R. Leibson C.L. Yawn B.P. Melton 3rd, L.J. Rocca W.A. Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project.Mayo Clin Proc. 2012; 87: 151-160Abstract Full Text Full Text PDF PubMed Scopus (487) Google Scholar Additionally, some melanomas may have been missed if the tumor was initially labeled as another anatomic site (cheek, nose, temple, etc.) and had extension onto the lid proper. None disclosed. We would like to acknowledge Austin Todd, MS, for his assistance in statistical analysis.

The Differential Impact of Socioeconomic Factors on Amputation Rates Among the Most Populous Counties in the United States

The Differential Impact of Socioeconomic Factors on Amputation Rates Among the Most Populous Counties in the United States

Amputation Rates and Associated Social Determinants of Health in the Most Populous US Counties

Social Determinants of Health (SDoH) are the environmental conditions that affect individuals’ health, functional status, and quality of life, and have been demonstrated to contribute to health outcome disparities in patients with peripheral artery disease (PAD). However, the impact of specific components that comprise the SDoH are not well understood. We evaluated how the components of SDoH and related demographic factors impact amputation rates in the most populous counties of the United States (U.S.). The Healthcare Cost and Utilization Project (HCUP) State Inpatient Database (SID) was used to determine the rates of discharge following lower extremity amputation for circulatory system disorders across the 100 largest counties of the U.S. in 2017. County demographic, hospital and SDoH data were matched using the U.S. Census, Dartmouth Atlas of HealthCare, and University of Wisconsin Population Health Institute County Health Rankings & Roadmaps data sources. Counties were divided into quartiles (Qs) based on amputation rates, and linear regression analysis was performed to assess associations between county-level amputation rates and SDoH factors. Amputation rates in the most populous U.S. counties assessed in the study varied widely from an average of 5.5 per 100,000 in Q1 to 15 per 100,000 in Q4. Compared with Q1, counties in Q4 had a higher proportion of African Americans (27% vs 7.9%; P < .05), diabetics (11% vs 7.9%; P < .05), smokers (17% vs 13%; P < .05), higher rates of unemployment (5.8% vs 4.6%; P = .01), poverty (16% vs 10%; P < .05), food insecurity (17% vs 13%; P < .05), single-parent households (42% vs 29%; P < .05), and physical inactivity (21% vs 17%; P < .05) (Table I). A significant association was found between amputation rate and county diabetes mellitus prevalence (ß = 0.68; 95% confidence interval [CI], 1.3-2.1; P < .05), mental distress (ß = 5.3; 95% CI, 3.7-6.9; P < .05), adult smokers (ß = 0.69; 95% CI, 0.46-0.92; P < .05), poverty (ß = 0.46; 95% CI, 0.32-0.60; P < .05), unemployment (ß = 1.2; 95% CI, 0.59-1.73; P < .05), homicide rate (ß = 0.61; 95% CI, 0.45-0.77; P < .05), physical inactivity (ß = 0.74; 95% CI, 0.57-0.90; P < .05), and food insecurity (ß = 0.51; 95% CI, 0.30-0.72; P < .05) (Table II). Amputation rates in the most populous U.S. counties are associated with several population characteristics and components of the SDoH, particularly rates of diabetes mellitus, physical inactivity, mental and physical distress, income/wealth, and food access. These findings indicate potential individual and community-level targets for improvement in the disparities present in the management of PAD.Table IPatient characteristics by amputation quartile (Q)1Q2Q3Q4QP valueAmputation rate per 100,000 Average5.57.910.415<.05Demographic data Age 65 and over13141314.16 African American7.912.01427<.05 Asian12.611.46.04.4<.05 Hispanic25203120.20 Non-Hispanic White51534747.54 Uninsured13121516.13 Diabetic7.98.99.411<.05 Current smokers13131517<.05 Physical inactivity17202121<.05 Rural2.93.03.23.6.91 Unemployed4.65.25.75.8.01 Poverty rate10111516<.05 Single-parent household29283742<.05 Housing insecurity21202221.73 Food insecurity13131517<.05 High school graduate81858179.12 Some college71706463<.05 Not proficient in English6.75.78.15.3.15Data are presented as percentages.Boldface P values indicate statistical significance.Quartiles corresponding to amputation rate per 100,000 in 76 US counties. 1Q (lowest amputation rate) to 4Q (highest amputation rate).Percentages reported correspondent to county averages. Open table in a new tab Table IIAssociation between social determinants of health components and amputation rateHealth care access and qualityß coefficient; [95% CI]P valueEducation access and qualityß coefficient; [95% CI]P valueSocial and community contextß coefficient; [95% CI]P valuePrimary care provider ratio0.0021 [0.0001-0.004]<.05English proficiency−0.027 [−0.23 to 0.18].798Racial segregation Black/White0.19 [0.13-0.26]<.05Health care cost0.00090 [0.00033-0.0014].002High school graduate−0.67 [−1.39 to 0.048].067Racial segregation non-white/White0.19 [0.13-0.25]<.05Diabetes mellitus prevalence1.7 [1.3-2.1]<.05Some college−0.18 [−0.27 to −0.098]<.05Limited access to healthy foods0.29 [0.074-0.50]<.05Diabetes mellitus monitoring−0.04 [-0.29-0.21].755Economic stabilityß coefficient; [CI]P valueFood insecurity0.51 [0.30-0.72]<.05Uninsured adults0.18 [0.035-0.32].015Poverty (%)0.46 [0.32-0.60]<.05Single-parent household0.29 [0.22-0.36]<.05Drug overdose mortality rate0.14 [0.015-0.27]<.05Median household income−0.0013 [−0.001 to −0.0009]<.05Mental distress5.3 [3.7-6.9]<.05Unemployment (%)1.2 [0.59-1.73]<.05Physical distress1.2 [0.86-1.6]<.05Neighborhood and built environmentß coefficient; [CI]P valueObesity0.51 [0.35-0.66]<.05Homicide rate (per 100,000)0.61 [0.45-0.77]<.05Adult smokers0.69 [0.46-0.92]<.05Severe housing problem0.13 [−0.058 to 0.31].174Total beds per county0.0019 [−0.0007 to 0.00004].158Air pollution particulate matter0.10 [−0.32 to 0.52].630Major teaching institutions per county0.41 [−0.090 to 0.90].107Physical inactivity0.74 [0.57-0.90]<.05ß coefficient, Percent difference in amputation rate; CI, confidence Interval. 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Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. The methodology developed can be used to extend the analysis to other locations.

Progress in reducing cancer mortality in the United States by congressional district, 1996-2003 to 2012-2020.

United States cancer death rates have been steadily declining since the early 1990s, but information on disparities in progress against cancer mortality across congressional districts is lacking. This study examined trends in cancer death rates, overall and for lung, colorectal, female breast, and prostate cancer by congressional district. County level cancer death counts and population data from the National Center for Health Statistics were used to estimate relative change in age-standardized cancer death rates from 1996-2003 to 2012-2020 by sex and congressional district. From 1996-2003 to 2012-2020, overall cancer death rates declined in every congressional district, with most congressional districts showing a 20%-45% decline among males and a 10%-40% decline among females. In general, the smallest percent of relative declines were found in the Midwest and Appalachia, whereas the largest declines were found in the South along the East Coast and the southern border. As a result, the highest cancer death rates generally shifted from congressional districts across the South in 1996-2003 to districts in the Midwest and central divisions of the South (including Appalachia) in 2012-2020. Death rates for lung, colorectal, female breast, and prostate cancers also declined in almost all congressional districts, although with some variation in relative changes and geographical patterns. Progress in reducing cancer death rates during the past 25years considerably vary by congressional district, underscoring the need for strengthening existing and implementing new public health policies for broad and equitable application of proven interventions such as raising tax on tobacco and Medicaid expansion.

A Method to Detect Whether Countywide Vote Centers Are Located Optimally: The Case of North Carolina

This article introduces a framework to detect suboptimally located vote centers and demonstrates the method using North Carolina as a test case. Because traveling to the polls is a central cost borne by voters, choosing vote center locations is one of many decisions made by local election officials that has the potential to decrease voting costs or to introduce bias in favor of certain voters living closer to selected vote centers. This article proposes a method designed to detect vote centers that create longer-than-expected travel times for voters given a county's population density. The article presents seven metrics to score travel costs borne by voters, and while controlling for population density, use these metrics to assess the optimality of vote center locations. This proposed method can be used by election administrators and other elections stakeholders to assess the optimality of existing and proposed distributions of county vote centers. In light of the increasing number of votes cast at vote centers—and the increasing number of states adopting vote center models—efficiently placing vote centers has become an important task for election administrators.

Balancing Data Provision and Data Protection: A Natural Experiment With HIV and Syphilis Surveillance Data in the United States.

Public release of health data typically requires statistical disclosure limitation (SDL), but scant research demonstrates how real-world SDL affects data usability. Recent changes of federal data re-release policy allow a pseudo-counterfactual comparison of HIV and syphilis data suppression rules. Incident counts (2019) of HIV and syphilis infections by county for Black and White populations were downloaded from the US Centers for Disease Control and Prevention. We quantified and compared suppression status by disease and county between Black and White populations and calculated incident rate ratios for counties with statistically reliable counts. Approximately 50% of US counties have incident HIV counts suppressed for Black and White populations compared with only 5% for syphilis, which has an alternative suppression strategy. The county population sizes protected by a numerator disclosure rule (<4) spans several orders of magnitude. Calculations of incident rate ratios, used as a measure of health disparity, were impossible in the 220 counties most susceptible to an HIV outbreak. Balancing tradeoffs between providing and protecting data are key to health initiatives worldwide. We encourage an increase in empirical research on the impact of SDL, especially in the context of health disparities, and recommend new approaches to avoid the "oppression of data suppression."

Assessing the accuracy of California county level COVID-19 hospitalization forecasts to inform public policy decision making

BackgroundThe COVID-19 pandemic has highlighted the role of infectious disease forecasting in informing public policy. However, significant barriers remain for effectively linking infectious disease forecasts to public health decision making, including a lack of model validation. Forecasting model performance and accuracy should be evaluated retrospectively to understand under which conditions models were reliable and could be improved in the future.MethodsUsing archived forecasts from the California Department of Public Health’s California COVID Assessment Tool (https://calcat.covid19.ca.gov/cacovidmodels/), we compared how well different forecasting models predicted COVID-19 hospitalization census across California counties and regions during periods of Alpha, Delta, and Omicron variant predominance.ResultsBased on mean absolute error estimates, forecasting models had variable performance across counties and through time. When accounting for model availability across counties and dates, some individual models performed consistently better than the ensemble model, but model rankings still differed across counties. Local transmission trends, variant prevalence, and county population size were informative predictors for determining which model performed best for a given county based on a random forest classification analysis. Overall, the ensemble model performed worse in less populous counties, in part because of fewer model contributors in these locations.ConclusionsEnsemble model predictions could be improved by incorporating geographic heterogeneity in model coverage and performance. Consistency in model reporting and improved model validation can strengthen the role of infectious disease forecasting in real-time public health decision making.

Patterns of West Nile Virus in the Northeastern United States Using Negative Binomial and Mechanistic Trait-Based Models.

West Nile virus (WNV) primarily infects birds and mosquitoes but has also caused over 2,000 human deaths, and >50,000 reported human cases in the United States. Expected numbers of WNV neuroinvasive cases for the present were described for the Northeastern United States, using a negative binomial model. Changes in temperature-based suitability for WNV due to climate change were examined for the next decade using a temperature-trait model. WNV suitability was generally expected to increase over the next decade due to changes in temperature, but the changes in suitability were generally small. Many, but not all, populous counties in the northeast are already near peak suitability. Several years in a row of low case numbers is consistent with a negative binomial, and should not be interpreted as a change in disease dynamics. Public health budgets need to be prepared for the expected infrequent years with higher-than-average cases. Low-population counties that have not yet had a case are expected to have similar probabilities of having a new case as nearby low-population counties with cases, as these absences are consistent with a single statistical distribution and random chance.

The BARI-hoods Project: neighborhood social determinants of health and postoperative weight loss using integrated electronic health record, census, and county data.

While social determinants of health (SDoH) have gained attention for their role in weight loss following bariatric surgery, electronic health record (EHR) data provide limited information beyond demographics associated with disparities in weight loss. To integrate EHR, census, and county data to explore disparities in SDoH and weight loss among patients in the largest populous county of Ohio. Seven hundred seventy-two patients (82.1% female; 37.0% Black) who had primary bariatric surgery (48.7% gastric bypass) from 2015 to 2019 at Ohio State University. EHR variables included race, insurance, procedure, and percent total weight lost (%TWL) at 2/3, 6, 12, and 24 months. Census variables included poverty and unemployment rates. County variables included food stores, fitness/recreational facilities, and open area within a 5- and 10-minute walk from home. Two mixed multilevel models were conducted with %TWL over 24 months, with visits as the between-subjects factor; race, census, county, insurance, and procedure variables were covariates. Two additional sets of models determined within-group differences for Black and White patients. Access to more food stores within a 10-minute walk was associated with greater %TWL over 24 months (P = .029). Black patients with access to more food stores within a 10-minute (P = .017) and White patients with more access within a 5-minute walk (P = .015) had greater %TWL over 24 months. Black patients who lived in areas with higher poverty rates (P = .036) experienced greater %TWL over 24 months. No significant differences were found for unemployment rate or proximity to fitness/recreational facilities and open areas. Close proximity to food stores is associated with better weight loss 2 years after bariatric surgery. Lower poverty levels did not negatively affect weight loss in Black patients.

Statewide assessment of telehealth use for obstetrical care during the COVID-19 pandemic

The COVID-19 pandemic started a period of rapid transition to telehealth in obstetrical care delivery to maintain social distancing and curb the spread of the virus. The use of telehealth, such as telephone and video visits, remote imaging interpretation, and provider-to-provider consultations, increased in the early months of the pandemic to maintain access to prenatal and postpartum care. Although there is considerable literature on the use of telehealth in obstetrical care, there are limited data on widespread telehealth use among different practice types and patient populations during the pandemic and whether these are preferred technologies. This study aimed to describe variations in telehealth use for obstetrical care among practices in North Carolina during the COVID-19 pandemic and to outline future preferences and needs for continued telehealth use. This study also aimed to delineate telehealth use among rural and micropolitan and metropolitan practices to better understand if telehealth use varied by practice location. A web-based survey was distributed to practice managers of obstetrical practices in North Carolina from June 14, 2020 to September 14, 2020. Practice managers were contacted through assistance of the Community Care of North Carolina Pregnancy Medical Home program. Practice location was defined as rural, micropolitan, or metropolitan based on the county population. The survey assessed telehealth use before and during the COVID-19 pandemic, types of modalities used, and preferences for future use. Descriptive statistics were performed to describe survey responses and compare them by practice location. A total of 295 practice managers were sent a web-based survey and 98 practice managers responded. Responding practices represented 66 of 100 counties in North Carolina with 50 practices from rural and micropolitan counties and 48 practices from metropolitan counties. The most common type of provider reported by practice managers were general obstetrician and gynecologists (85%), and the most common practice type was county health departments (38%). Overall, 9% of practices reported telehealth use before the pandemic and 60% reported telehealth use during the pandemic. The most common type of telehealth modality was telephone visits. There were no significant differences in the uptake of telehealth or in the modalities used by practice location. A total of 40% of practices endorsed a preference for continued telehealth use beyond the COVID-19 pandemic. The most commonly reported need for continuation of telehealth use was assistance with patient access to telehealth technologies (54%). There were no significant differences in the preferences for telehealth continuation or future needs by practice location. Telehealth use increased among a variety of practice types during the pandemic with no variation observed by practice location in terms of modalities used, future preferences, or needs. This study assessed statewide uptake of and differences in obstetrical telehealth use during the early COVID-19 pandemic. With telehealth becoming an integral part of obstetrical care delivery, this survey has implications for anticipating the needs of practices and designing innovative solutions for providers and pregnant people beyond the COVID-19 pandemic.

Current patterns of trauma center proliferation have not led to proportionate improvements in access to care or mortality after injury: An ecologic study.

Timely access to high-level (I/II) trauma centers (HLTCs) is essential to minimize mortality after injury. Over the last 15 years, there has been a proliferation of HLTC nationally. The current study evaluates the impact of additional HLTC on population access and injury mortality. A geocoded list of HLTC, with year designated, was obtained from the American Trauma Society, and 60-minute travel time polygons were created using OpenStreetMap data. Census block group population centroids, county population centroids, and American Communities Survey data from 2005 and 2020 were integrated. Age-adjusted nonoverdose injury mortality was obtained from CDC Wide-ranging Online Data for Epidemiologic Research and the Robert Wood Johnson Foundation. Geographically weighted regression models were used to identify independent predictors of HLTC access and injury mortality. Over the 15-year (2005-2020) study period, the number of HLTC increased by 31.0% (445 to 583), while population access to HLTC increased by 6.9% (77.5-84.4%). Despite this increase, access was unchanged in 83.1% of counties, with a median change in access of 0.0% (interquartile range, 0.0-1.1%). Population-level age-adjusted injury mortality rates increased by 5.39 per 100,000 population during this time (60.72 to 66.11 per 100,000). Geographically weighted regression controlling for population demography and health indicators found higher median income and higher population density to be positively associated with majority (≥50%) HLTC population coverage and negatively associated with county-level nonoverdose mortality. Over the past 15 years, the number of HLTC increased 31%, while population access to HLTC increased only 6.9%. High-level (I/II) trauma center designation is likely driven by factors other than population need. To optimize efficiency and decrease potential oversupply, the designation process should include population level metrics. Geographic information system methodology can be an effective tool to assess optimal placement. Prognostic and Epidemiological; Level IV.

Increasing demand for ophthalmic pathology: time trends in a laboratory with nationwide coverage

PurposeTo report the time trends in basic patient characteristics and the number of specimens received at a national referral center for ophthalmic pathology.MethodsData on patient sex, age at surgical resection and geographical location of the referring unit were obtained for all specimens received at the St. Erik Ophthalmic Pathology laboratory, Stockholm, Sweden, between January 1st, 1959, and December 31st, 2021.ResultsA total of 33 057 specimens had been received, of which 14 560 (44%) came from men and 18 477 (56%) from women (for 20 patients, the sex was not specified). The average annual percent change (AAPC) in the number specimens received was + 10.5%, whereas the Swedish population increased with 0.5% per year. Patients became older throughout the period, with an average yearly increase of patient age at surgery of 0.3 years (AAPC 0.2%). Overall, women were three years older than men at surgery (59.4 versus 56.4 years, P < 0.0001) The number of specimens increased with patient age from the first to the 8th decade, after which it decreased to zero in the 11th decade. The largest portion of patients had undergone their surgery in one of the hospitals or clinics in the capital region, with four of the five largest sources corresponding to the most populous counties in the country.ConclusionsDuring six decades, the growth in number of specimens sent to our national referral center for ophthalmic pathology has greatly outpaced the growth of the population, indicating an increasing demand for subspecialized services. Throughout the period, patients have become older, and a higher number of specimens have been submitted from female patients.

The effect of changing COVID-19 restrictions on the transmission rate in a veterinary clinic

With the declaration of the COVID-19 pandemic by the World Health Organization on March 11, 2020, the University of Tennessee College of Veterinary Medicine (UTCVM), like other institutions, restructured their services to reduce the potential spread of the COVID-19 virus while simultaneously providing critical and essential veterinary services. A mathematical model was developed to predict the change in the level of possible COVID-19 infections due to the increased number of potential contacts within the UTCVM hospital. A system of ordinary differential equations with different compartments for UTCVM individuals and the Knox county population was formulated to show the dynamics of transmission and the number of confirmed cases. Key transmission rates in the model were estimated using COVID-19 case data from the surrounding county and UTCVM personnel. Simulations from this model show the increasing number of COVID-19 cases among UTCVM personnel as the number of daily clients and the number of veterinary staff in the clinic are increased. We also investigate how changes within the Knox county community impact the UTCVM hospital. These scenarios show the importance of understanding the effects of re-opening scenarios in veterinary teaching hospitals.