County Population Research Articles

Measuring network dynamics of opioid overdose deaths in the United States

The US opioid overdose epidemic has been a major public health concern in recent decades. There has been increasing recognition that its etiology is rooted in part in the social contexts that mediate substance use and access; however, reliable statistical measures of social influence are lacking in the literature. We use Facebook’s social connectedness index (SCI) as a proxy for real-life social networks across diverse spatial regions that help quantify social connectivity across different spatial units. This is a measure of the relative probability of connections between localities that offers a unique lens to understand the effects of social networks on health outcomes. We use SCI to develop a variable, called “deaths in social proximity”, to measure the influence of social networks on opioid overdose deaths (OODs) in US counties. Our results show a statistically significant effect size for deaths in social proximity on OODs in counties in the United States, controlling for spatial proximity, as well as demographic and clinical covariates. The effect size of standardized deaths in social proximity in our cluster-robust linear regression model indicates that a one-standard-deviation increase, equal to 11.70 more deaths per 100,000 population in the social proximity of ego counties in the contiguous United States, is associated with thirteen more deaths per 100, 000 population in ego counties. To further validate our findings, we performed a series of robustness checks using a network autocorrelation model to account for social network effects, a spatial autocorrelation model to capture spatial dependencies, and a two-way fixed-effect model to control for unobserved spatial and time-invariant characteristics. These checks consistently provide statistically robust evidence of positive social influence on OODs in US counties. Our analysis provides a pathway for public health interventions informed by social network structures. The statistical robustness of our primary variable of interest, deaths in social proximity, supports the hypothesis of a social network effect on OODs. Using agent-based modeling (ABM) to simulate social networks can offer an effective method to design interventions that incorporate the dynamics of social networks for maximum impact.

Unincorporation in counties as a political determinant of health: An exploration of five states

Local government policies and practices shape the context of the places that can alter a population's life chances through socioeconomic factors, built environments, and healthcare access. County governments, one of the most ubiquitous U.S. political structures, impact health outcomes within their jurisdiction through multiple policy levers and pathways. By identifying which political determinants within counties are associated with variation in life expectancy and premature death, we can better intervene on modifiable factors. One overlooked political determinant from public health studies is the county's responsibility as the primary local government for approximately a third of the U.S. population and 93% of land in unincorporated areas. To conduct an ecological study and assess associations between county population health and county responsibility for unincorporated areas and populations, we created and tested two county indicators of unincorporation. Multilevel multivariable regression results showed that larger proportions of unincorporated land within a county are associated with lower average county life expectancy. More testing of the measurement is needed to understand the relationship between unincorporation, county government, and population health outcomes.

Social and policy characteristics associated with injurious shootings by police in US counties: A multilevel analysis, 2015–2020

From 2015 to 2020, shootings by police injured or killed 1769 people annually in the United States, disproportionately harming members of minoritized groups. Prior studies of the structural determinants of these inequities have largely examined state-level aggregations and fatal outcomes. This study aimed to: 1) describe state and county variation in fatal and nonfatal injurious shootings by police, and 2) analyze the relationship between state and county context and differences in county rates of injurious shootings by police. Injury data were developed from manual review of incidents listed in the Gun Violence Archive, then aggregated by county-year. Covariate selection was informed by theories of police use of force and the Social Basis of Disparities in Health conceptual framework. Fixed effects negative binomial regression models were estimated, nesting years within counties and states. Analyses controlled for county population, local reporting presence, and multiple measures of social conflict and community violence. From 2015 to 2020, 56% of counties experienced injurious shootings by police. Higher county rates of victimization were associated with greater state spending on police relative to health, county income inequality, prevalence of unmet substance use disorder needs, higher county firearm availability, and permitless concealed carry statutes. Firearm purchaser licensing polices were associated with lower incidence of injurious shootings by police. To prevent patterns of injurious shootings by police, policymakers should consider addressing undermanaged substance use disorder through crisis fund allocation and use, adopting stronger firearm licensing systems, and evaluating local strategies to combat inequities and strengthen non-policing responses to social needs.

Excess Cardiopulmonary Arrest and Mortality after COVID-19 Vaccination in King County, Washington

Introduction: Since the onset of widespread COVID-19 vaccination campaigns, there have been concerns about serious cardiovascular adverse events as a result of mass vaccination. This study aimed to estimate excess cardiopulmonary arrest mortality in King County, WA, and investigate any association with COVID-19 vaccination rates. Methods: An exploratory data analysis was performed. Comparative analyses were performed to evaluate the changes in total EMS attendances over time. Excess deaths were calculated using the 2015-2020 cardiopulmonary arrest mortality trend line. The relationship between excess cardiopulmonary arrest mortality and vaccination rates was analyzed using polynomial regression analysis. Results: Approximately 98% of the King County population received at least one dose of a COVID-19 vaccine by 2023. As of August 2nd, 2024, there have been approximately 589,247 confirmed COVID-19 cases in King County. In 2021- 2022, Total EMS attendances in King County sharply increased by 35.34% from 2020 and by 11% from pre-pandemic years. Cases of 'obvious death' upon EMS arrival increased by 19.89% in 2020, 36.57% in 2021, and 53.80% in 2022 compared to the 2017-2019 average. We found a 25.7% increase in total cardiopulmonary arrests and a 25.4% increase in cardiopulmonary arrest mortality from 2020 to 2023 in King County, WA. Excess fatal cardiopulmonary arrests were estimated to have increased by 1,236% from 2020 to 2023, rising from 11 excess deaths (95% CI: -12, 34) in 2020 to 147 excess deaths (95% CI: 123, 170) in 2023. A quadratic increase in excess cardiopulmonary arrest mortality was observed with higher COVID-19 vaccination rates. The general population of King County sharply declined by 0.94% (21,300) in 2021, deviating from the expected population size. Applying our model from these data to the entire United States yielded 49,240 excess fatal cardiopulmonary arrests from 2021-2023. Conclusions: We identified a significant ecological and temporal association between excess fatal cardiopulmonary arrests and the COVID-19 vaccination campaign. The increase in excess cardiopulmonary arrest deaths may also be attributed to COVID-19 infection and disruptions in emergency care during the pandemic. Urgent further research is needed to confirm our observations with attention to risk mitigation for incident events and improved survival with resuscitation.

Comparison of progression risk of monoclonal gammopathy of undetermined significance by method of detection

AbstractMonoclonal gammopathy of undetermined significance (MGUS) is an asymptomatic premalignant disorder. The current standard of care is not to screen for MGUS, so it is often incidentally diagnosed in the clinic. It is unknown whether the outcomes of screened vs clinically detected MGUS differ. We compared the progression risk between screened vs clinical MGUS cohorts and assessed whether the MGUS detection method affected risk prediction of established clinical factors (score). We included 379 screened MGUS cases from the Olmsted County population-based study and 1384 patients with MGUS diagnosed during routine clinical evaluation at Mayo Clinic. Median follow-up time for the screened vs clinical cohort was 26.6 and 40.1 years, respectively. Accounting for death as a competing risk, the cumulative incidence of progression at 25 years was similar in the screened (11.1% [95% confidence interval [CI], 8.3-14.8]) vs clinical (10.1% [95% CI, 8.6-11.8]) MGUS cohorts, even when stratified by sex, age, or the baseline MGUS risk score. Overall, 0.9 (95% CI, 0.6-1.2) of patients with screened MGUS vs 1.0 (95% CI, 0.9-1.2) of those with clinically detected MGUS experienced disease progression for every 100 person-years of follow-up. MGUS detection method did not modify the association between MGUS risk score and progression risk (pinteraction = 0.217) and did not add to known risk factors for progression (likelihood ratio test; P = .839). Here, we show that progression risk among patients with screened vs clinically detected heavy-chain MGUS was similar. Future studies are needed to assess whether tailored follow-up of patients with screened MGUS affects clinical outcomes.

Incidence, Mechanisms, and Clinical Characteristics of Traumatic Iritis: A Population-Based Analysis.

To describe the incidence, mechanisms, and clinical characteristics of patients diagnosed with traumatic iritis in a U.S. Midwestern county population. Retrospective population-based cohort of all residents of Olmsted County, Minnesota diagnosed with traumatic iritis from January 1, 2006, to December 31, 2015. The medical records of patients with traumatic iritis were identified using the Rochester Epidemiology Project database, which contains virtually all medical care in the county. Medical records were reviewed for demographics, presentation, and follow-up data. Incidence rates were calculated per 100,000 per year. There were 156 incident diagnoses of traumatic iritis during the 10-year study period, yielding an age- and sex-adjusted incidence rate of 10.7 per 100,000 per year. Traumatic iritis disproportionately occurred in male (p < 0.001) and Black (p < 0.001) patients. The mean age of diagnosis was 33 years (range: 4-96 years), mean number of traumatic iritis-specific follow-up visits was 2.1 (range: 0-26), and median duration of traumatic iritis-specific follow-up was 11 days (range: 1 day-1.6 years). There were 155 (99.4%) patients with unilateral disease. The most frequent mechanisms of traumatic iritis were sports-related (N = 29, 18.6%), assault-related (N = 23, 14.7%), scratch (N = 22, 14.1%), and work-related (N = 21, 13.5%) injuries. The mean initial and final best-corrected visual acuity (BCVA) of the affected eye was 20/40 and 20/30, respectively. Loss of follow-up was more frequently observed in Black patients (p < 0.001) and patients with smoking history (p = 0.004). Traumatic iritis was most frequently observed in younger males and Black patients. Common mechanisms included sports, assault, scratch, and work-related injuries.

Assessing social equity of federal disaster aid distribution: A nationwide analysis.

In this study, we conduct the first comprehensive, nationwide assessment of social equity performance of multiple federal post- and pre-disaster assistance programs that differ in targeted recipients, project types, forms of aid, and funding requirements. We draw on the social equity and distributive justice theory to develop and test a set of hypotheses on the influence of program design and specificity on their aid distributional patterns and equity performance. The analysis uses panel data of about 3000 US counties to examine the relationship between a county's receipt of federal assistance and its recent disaster damage, socioeconomic, demographic, political, local government, and geographic characteristics in a two-stage random effects Tobit model. Expectedly, we find that post-disaster grants are largely driven by recent disaster damage, while damage is simultaneously influenced by local socioeconomic conditions. For all disaster programs, disproportionately more federal aid is allocated to populous counties. For programs geared toward state and local governments and targeting community recovery and mitigation, more aid is received by counties with better socioeconomic conditions. Conversely, for programs targeting individual relief and recovery, more aid is given to counties with lower incomes and greater social vulnerability. Results also indicate that counties located in high-risk regions receive greater outlays. These findings shed light on the varying degrees of social equity of federal disaster assistance programs tied to their cost-share requirement, funding caps, and inherent complexity of application procedures.

Addressing Challenges to Ensuring Justice and Sustainability in Policy and Infrastructure for Texas Water Resources in the 21st Century

Environmental justice and sustainability have both become major concerns for water resource management, particularly with recent federal emphasis on environmental justice under the Biden administration in the United States. Texas, like many U.S. states, lags behind the federal government in this emphasis. While many localities have made progress in some respects—for example, some major Texas municipalities have included equity and sustainability metrics in their recent climate action plans—others have not. This has left a patchwork of persistent water management and availability issues that are exacerbated by extreme weather and worsening impacts of climate change. We provide a review of many of Texas’s water equity and sustainability challenges, both now and in a more extreme climate future. These include water access, affordability, contamination, flooding, drought, and aging infrastructure. For example, many Texas counties rank highest in the nation for flood risk, including coastal counties with high populations of disadvantaged communities and counties containing populations that live in persistent poverty in the Lower Rio Grande Valley. Additionally, approximately 44,000 Texans, or about 0.4% of the state population, lack access to complete plumbing facilities in their homes. The costs of water infrastructure leaks (estimated at about 51 gallons of water per day statewide) are shared across customers of all income levels, though they place a disproportionate burden on low-income customers. We then assess existing statewide and local policy and planning efforts and gaps in addressing these concerns in Texas. We focus particularly on the role of efforts to incorporate community voice—the ideas, concerns, needs, and expertise of impacted community members, dismantle causes of injustice, and improve equity in spending. If communities are not intentional with future development, new water infrastructure could continue to perpetuate existing harms. Thus, we provide a research agenda and recommendations for addressing some of the policy and planning gaps and persistent environmental justice issues. We aim to help water managers and policy makers identify and dismantle sources of inequity, particularly through including community voice.

Abstract PR002: County-level food insecurity and hepatocellular carcinoma risk: A cross-sectional analysis

Abstract Background: Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, is the sixth most common cancer and third leading cause of cancer deaths worldwide. Hepatitis B and/or C virus, alcohol use, and obesity are main drivers of HCC incidence and prognosis, with risk higher among Black and Hispanic individuals and those with lower socioeconomic status. HCC etiology recently shifted from viral to non-viral-related causes, with up to 40% of HCC cases unexplained by known risk factors. Food insecurity (FI) is associated with several known and emerging HCC risk factors, including poor diet quality, obesity, and diabetes. However, there is limited data on whether FI is in fact a social determinant of HCC risk. In this study, we conducted a county-level cross-sectional analysis to examine whether FI is associated with HCC risk in the United States. Methods: We used the Surveillance Epidemiology and End Results 22 database to obtain county-level counts of HCC cases from 2018-2021 stratified by age (20-64, ≥65 years), sex (female, male), and race and ethnicity (non-Hispanic White, non- Hispanic Black, non-Hispanic Asian or Pacific Islander, non-Hispanic American Indian or Alaska Native, and Hispanic). We obtained county-level FI rates for the years 2018-2021 from Feeding America’s Map the Meal Gap and calculated the average rate over these years. FI rates were calculated using imputation methods that consider state- and county-level sociodemographic variables associated with FI. We obtained additional county-level variables from the Behavior Risk Factor Surveillance System for the years 2018-2021. We used multi- level Poisson regression models with robust standard errors to estimate the association between FI and HCC risk. Models specified county population size as the offset term, and random effects for states and counties. We examined models adjusted for age, sex, race, and ethnicity (Model 1), and further adjusted for county-level binge drinking, smoking, obesity, and diabetes rates (Model 2). We tested multiplicative effect modification by individual-level factors. Results: We included 38,986 cases of HCC diagnosed in 1,085 counties. The mean county-level FI rate was 12.9% (standard deviation (SD)=3.6%). Overall, a 1-SD increase in FI was associated with a 9% increase in HCC risk in Model 1 (incidence rate ratio (IRR)=1.09, 95% CI=1.04-1.15) and a 5% increase in risk in Model 2 (IRR=1.05, 95% CI=1.02-1.09). When stratified by race and ethnicity, FI was only associated with HCC risk in non-Hispanic Whites in Model 2 (IRR=1.07, 95% CI=1.03-1.11; interaction p-value=.05). When stratified by age, FI was only associated with HCC risk in the &amp;lt;65 years group (IRR=1.13, 95% CI=1.08-1.18; interaction p-value &amp;lt;.001). The association did not differ by sex. Conclusion: This study provides some of the first data linking FI to increased HCC risk, in particular early onset HCC. If confirmed in other studies, these findings support the need for interventions that screen for, prevent, and address FI in populations at increased risk for HCC. Citation Format: Rebecca D. Kehm, Chrystelle L. Vilfranc, Jasmine A. McDonald, Hui Chen Wu. County-level food insecurity and hepatocellular carcinoma risk: A cross-sectional analysis [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr PR002.

Projections of Extreme Temperature–Related Deaths in the US

ImportanceExtreme heat in the US is increasing due to climate change, while extreme cold is projected to decline. Understanding how extreme temperature along with demographic changes will affect population health is important for devising policies to mitigate the health outcome of climate change.ObjectiveTo assess the burden of extreme temperature–related deaths in the contiguous US currently (2008-2019) and estimate the burden in the mid–21st century (2036-2065).Design, Setting, and ParticipantsThis cross-sectional study used historical (1979-2000) daily mean temperatures to calculate monthly extreme heat (&amp;amp;gt;97.5th percentile value) and extreme cold days (&amp;amp;lt;2.5th percentile value) for all contiguous US counties for 2008 to 2019 (current period). Temperature projections from 20 climate models and county population projections were used to estimate extreme temperature–related deaths for 2036 to 2065 (mid–21st century period). Data were analyzed from November 2023 to July 2024.ExposureCurrent monthly frequency of extreme heat days and projected mid–21st century frequency using 2 greenhouse gas emissions scenarios: Shared Socioeconomic Pathway (SSP)2-4.5, representing socioeconomic development with a lower emissions increase, and SSP5-8.5, representing higher emissions increase.Main Outcomes and MeasuresMean annual estimated number of extreme temperature–related excess deaths. Poisson regression model with county, month, and year fixed effects was used to estimate the association between extreme temperature and monthly all-cause mortality for older adults (aged ≥65 years) and younger adults (aged 18-64 years).ResultsAcross the contiguous US, extreme temperature days were associated with 8248.6 (95% CI, 4242.6-12 254.6) deaths annually in the current period and with 19 348.7 (95% CI, 11 388.7-27 308.6) projected deaths in the SSP2-4.5 scenario and 26 574.0 (95% CI, 15 408.0-37 740.1) in the SSP5-8.5 scenario. The mortality data included 30 924 133 decedents, of whom 15 573 699 were males (50.4%), with 6.3% of Hispanic ethnicity, 11.5% of non-Hispanic Black race, and 79.3% of non-Hispanic White race. Non-Hispanic Black adults (278.2%; 95% CI, 158.9%-397.5%) and Hispanic adults (537.5%; 95% CI, 261.6%-813.4%) were projected to have greater increases in extreme temperature–related deaths from the current period to the mid–21st century period compared with non-Hispanic White adults (70.8%; 95% CI, −5.8% to 147.3%).Conclusions and RelevanceThis cross-sectional study found that extreme temperature–related deaths in the contiguous US were projected to increase substantially by mid–21st century, with certain populations, such as non-Hispanic Black and Hispanic adults, projected to disproportionately experience this increase. The results point to the need to mitigate the adverse outcome of extreme temperatures for population health.

Drivers of universal health coverage in Makueni county, Kenya: Lessons for the Global South

All UN member States committed to realizing universal health coverage (UHC) when they included UHC as Target 3.8 in the Sustainable Development Goals in 2015. However, the global commitment to UHC has not been matched with action on the ground. According to the World Health Organization, about half of the world population lacks full coverage for essential health services. To accelerate progress toward UHC, a close understanding of factors that drive adoption of UHC policies at the national and local levels is essential. The purpose of this study was to investigate the impetus for establishing a sub-national health insurance program in Kenya—the Makueni county government health insurance program (MakueniCare)—which led to increasing the percentage of the county population with health insurance, the majority of whom live in poverty, from 8.8% in 2013 to 91% in 2018. This qualitative case study drew on Kenyan law and policy documents as well as semi-structured interviews with 30 key informants in government and NGOs to understand the drivers that led to the establishment of MakueniCare. Findings revealed that several drivers—namely, global norms, decentralization, democratic competition, and the strategic action of social change-minded leaders—coalesced to influence the adoption of MakueniCare. The study offers timely insights into the factors driving UHC in Makueni, Kenya and lessons for other low- and middle-income countries working toward UHC.

Incidence of symptomatic Borrelia burgdorferi sensu lato infection in Romania, 2018−2023

BackgroundLyme borreliosis (LB), caused by Borrelia burgdorferi sensu lato (Bbsl), is the most common tick-borne disease in Europe. Although public health surveillance for LB has been conducted in Romania since 2007, the extent of under-detection of Bbsl infections by LB surveillance has not been estimated. We therefore estimated the under-detection of symptomatic Bbsl infections by LB surveillance to better understand the LB burden in Romania.MethodsThe number of incident symptomatic Bbsl infections were estimated from a seroprevalence study conducted in six counties (population 2.3 M) and estimates of the symptomatic proportion and duration of persistence of anti-Bbsl immunoglobulin G (IgG) antibodies. The number of incident symptomatic Bbsl infections were compared with the number of surveillance-reported LB cases to derive an under-detection multiplier, and then the under-detection multiplier was applied to LB surveillance data to estimate the incidence of symptomatic Bbsl infection from 2018 to 2023.ResultsWe estimate that there were 1968 individuals with incident symptomatic Bbsl infection in the six counties where the seroprevalence study was conducted in 2020, compared with the 187 surveillance-reported LB cases, resulting in an under-detection multiplier of 10.5 (i.e., for every surveillance-reported LB case, there were 10.5 symptomatic incident Bbsl infections). The incidence of symptomatic Bbsl infection in the six counties was 86.9/100,000 population in 2023, similar to the incidence in 2018−2020 (86.0) and higher than in 2021−2022 (40.3).ConclusionsThere is a higher incidence of symptomatic Bbsl infection than is reported through public health surveillance for LB in Romania. Additional efforts are needed to strengthen disease prevention and address the important public health problem of LB.Graphic

COVID-19 vaccine uptake inequality among older adults: A multidimensional demographic analysis

Age, race, ethnicity, and sex are important determinants of coronavirus disease of 2019 (COVID-19) outcomes. Older adults (65 years and older) are at the highest risk of COVID-19 morbidity and mortality. Analyzing their vaccine uptake by subclassifying demographics is rare and can assist vaccination policies. This study investigates COVID-19 dose 1and 2vaccine uptakes among them by race, ethnicity, and sex. Immunization registry data were used to calculate temporal changes in older adults' COVID-19 vaccine uptake by race, ethnicity, race-sex, and ethnicity-sex in Kentucky's most populous county, Jefferson County, during the first 6 quarters of the COVID-19 vaccination program. By May 2022, the county's Asian residents had the highest dose 1 and 2 vaccination rates (97.0% and 80.4%), then White residents (90.0% and 80.2%). Black residents had one of the lowest COVID-19 vaccination rates (87.3% and 77.3%). The rate among Hispanic residents (82.0% and 66.4%) was considerably lower than non-Hispanic residents (90.2% and 80.1%). The rates were consistently lower in males. Racial, ethnic, and sex-based COVID-19 vaccine inequalities were largely maintained during the study period. Vaccine rollout practices and promotional programs should aim to boost the uptake of the COVID-19 vaccination among racial minority and male older adults.

Geographic Patterns of Youth Suicide in San Diego County

ObjectiveOur objectives were to evaluate for any cluster patterns of youth suicide deaths and characterize the level of child opportunity in the communities where suicide deaths occurred. MethodsDecedents <18 years were identified from San Diego County Medical Examiner death reports from 2000 to 2020. We mapped decedents’ residential Zone Improvement Plan (ZIP) codes and calculated suicide rates per 10,000 youths. ZIP codes identified in overlapping spatial statistical approaches — the spatial scan statistic and Local Moran with Empirical Bayes (EB) rates — were considered a cluster for the final analysis. We obtained Child Opportunity Index (COI) scores for each ZIP code to determine if there were differences in: 1) ZIP codes with suicide deaths compared to ZIPs with no deaths 2) differences in distribution of suicide death rates across quintiles of COI. ResultsScan statistic identified 25 ZIP codes within a cluster (RR 2.6, P = 0.00066). Local Moran with EB rates identified two ZIP codes as a high-high cluster (P < 0.05). The location identified as a cluster in both approaches was in Alpine. The median COI for ZIP codes with suicide deaths was higher at 63.5 (IQR 38–83) compared to 47 (IQR 22.5–75.5) for ZIP codes without suicide deaths. There was a significant difference in suicide rates between Very Low and Moderate levels of Overall opportunity (P = .013). ConclusionWe identified a cluster of youth suicides in one of the most populous counties in the country. These findings serve to inform policies and prevention programs that aim to mitigate youth suicide mortality.

Comparing Federal Communications Commission and Microsoft Estimates of Broadband Access for Mental Health Video Telemedicine Among Veterans: Retrospective Cohort Study.

The COVID-19 pandemic highlighted the importance of telemedicine in health care. However, video telemedicine requires adequate broadband internet speeds. As video-based telemedicine grows, variations in broadband access must be accurately measured and characterized. This study aims to compare the Federal Communications Commission (FCC) and Microsoft US broadband use data sources to measure county-level broadband access among veterans receiving mental health care from the Veterans Health Administration (VHA). Retrospective observational cohort study using administrative data to identify mental health visits from January 1, 2019, to December 31, 2020, among 1161 VHA mental health clinics. The exposure is county-level broadband percentages calculated as the percentage of the county population with access to adequate broadband speeds (ie, download >25 megabits per second) as measured by the FCC and Microsoft. All veterans receiving VHA mental health services during the study period were included and categorized based on their use of video mental health visits. Broadband access was compared between and within data sources, stratified by video versus no video telemedicine use. Over the 2-year study period, 1,474,024 veterans with VHA mental health visits were identified. Average broadband percentages varied by source (FCC mean 91.3%, SD 12.5% vs Microsoft mean 48.2%, SD 18.1%; P<.001). Within each data source, broadband percentages generally increased from 2019 to 2020. Adjusted regression analyses estimated the change after pandemic onset versus before the pandemic in quarterly county-based mental health visit counts at prespecified broadband percentages. Using FCC model estimates, given all other covariates are constant and assuming an FCC percentage set at 70%, the incidence rate ratio (IRR) of county-level quarterly mental video visits during the COVID-19 pandemic was 6.81 times (95% CI 6.49-7.13) the rate before the pandemic. In comparison, the model using Microsoft data exhibited a stronger association (IRR 7.28; 95% CI 6.78-7.81). This relationship held across all broadband access levels assessed. This study found FCC broadband data estimated higher and less variable county-level broadband percentages compared to those estimated using Microsoft data. Regardless of the data source, veterans without mental health video visits lived in counties with lower broadband access, highlighting the need for accurate broadband speeds to prioritize infrastructure and intervention development based on the greatest community-level impacts. Future work should link broadband access to differences in clinical outcomes.

FRAP 2.0: a community engagement method applied to cervical cancer disparities among Hispanic women

focused Rapid Assessment Process (fRAP) 2.0 is a community engagement approach combining geospatial mapping with rapid qualitative assessment in cyclical fashion within communities to capture multifactorial and multilevel features impacting...

Expanding the opioid use disorder medication treatment workforce in rural communities through the RCORP initiative.

The Rural Communities Opioid Response Program (RCORP) was funded to help rural communities improve prevention, treatment, and recovery services for Opioid Use Disorder (OUD), including increasing the supply of clinicians with a Drug Enforcement Administration (DEA) waiver to prescribe buprenorphine, which was required before 2023. This research investigates the impact of RCORP funding on the supply of DEA-waivered clinicians in rural communities. We used 2017-2022 DEA lists of waivered clinicians to assign clinicians to US counties. Using RCORP service area data, we classified rural counties as either being served by an RCORP grantee or not. We calculated the number of counties in each category with a waivered clinician, clinician-to-population ratios, and treatment slot-to-population ratios. In 2017, 3.7% more of RCORP funded counties had a waivered clinician than non-RCORP counties. RCORP counties also had 1.2 more waivered clinicians per 100,000 population and 57.5 more treatment slots per 100,000 population compared to non-RCORP counties. From 2017 to 2022, these differences more than doubled. The supply of waivered clinicians varied across Census Divisions. In most Census Divisions, a greater percentage of RCORP counties had a waivered clinician as well as more waivered clinicians and treatment slots per population, except for the Pacific Census Division, which had more clinicians and treatment slots per population in non-RCORP counties. Study findings suggest that federal investments to expand rural OUD patients' access to care may have been successful, but only if increases in clinician supply translate into greater provision of OUD treatment.

County-level total factor productivity of food in China and its spatio-temporal evolution and drivers

In the context of the ongoing process of high-quality development in the new era, which is focused on improving total factor productivity, it is of great importance to explore the spatial and temporal variations of total factor productivity growth and its driving factors in China’s county regions’ grain cultivation industry. This paper employs a three-stage DEA-Malmquist productivity method, the Gini coefficient method, and a panel fixed-effects model to analyze data from Chinese counties between 2009 and 2019. The analysis indicates that the growth of county food total factor productivity (FTFP) exhibits a fluctuating upward trend during the examination period, with an average annual growth rate of 2.43%. This is primarily driven by technological progress, yet the core driving role of technological efficiency is not effectively played. The average annual growth rate of county FTFP varies across different regions. The highest average annual growth rate of county FTFP in the eastern region and the primary grain-producing area is 2.75 and 3.04%, respectively. The lowest growth rates were observed in the western region and the main grain marketing area, at 1.44 and 1.23%, respectively. Secondly, the Gini coefficient of county FTFP continues to demonstrate a persistent upward trend during the examination period, with an average annual growth rate of 14.729%. The primary factor contributing to the observed variation in total factor productivity growth of the food sector at the regional level is the existence of disparate technological progress. Thirdly, there is a notable positive correlation between county financial deepening and financial self-sufficiency rates and county FTFP growth, with impact coefficients of 0.0503 and 0.0924, respectively. Conversely, county population density, degree of economic development, farmers’ income level, and industrial structure exert a significant negative influence on county FTFP growth and technological progress.

From Confidence to Convenience: Changes in Voting Systems, Donald Trump, and Voter Confidence

Abstract A growing body of research indicates that voters’ perceptions of the electoral system change when the means of administering elections change. As some electoral jurisdictions have moved to systems designed to increase voter convenience, little is known about whether convenience is achieved at the expense of confidence. Utah’s rollout of Vote by Mail (VBM) occurred county by county across five federal elections, and the three most populous counties adopted all VBM elections successively in 2014, 2016, and 2018. This meaningful variance in voter experience with VBM allows us to model the relationship between experience with VBM and voter confidence. We find that the switch to a more convenient system of voting came at the expense of diminished confidence in the voting process. However, experience with VBM is positively related to confidence such that the loss in confidence can be recouped over time. To capture this dynamic relative to other factors, we also estimate the effects of partisanship and the messages of political elites. In the aftermath of the 2020 election, the effect of partisanship on voter confidence changed compared to just two years earlier. Elite messages appear to be especially negative for Trump voters after 2020. More experience with VBM acts as a bulwark against those negative messages, almost completely attenuating the negative effects of Trump’s fraud claims among his voters with the highest levels of VBM experience.

What did we catch? Predictors of infection after tissue expander–based breast reconstruction in a safety-net system

BackgroundInfection is a common complication following tissue expander (TE)–based breast reconstruction. Few studies have examined risk factors specifically in the unique populations encountered at safety-net hospitals. The purpose of this study was to identify predictors of TE infection at Harris Health safety-net hospitals, which serve the third most populous county in the United States. MethodsA retrospective review was performed to evaluate women over the age of 18 years who underwent TE placement at two safety-net hospitals from October 2015 to November 2022. Demographic information, medical history, operative details, and postoperative course were recorded for each individual TE. The primary outcome was TE infection, for which univariate and multivariate analysis was conducted. The secondary outcome was the time to onset of TE infection, for which a Kaplan-Meier analysis was undertaken. ResultsThere were 279 patients, totaling 372 breasts, meeting the inclusion criteria. The TE infection rate was 23%. Increased body mass index (BMI), diabetes, use of acellular dermal matrix (ADM), and prolonged surgical drain use were all significantly associated with TE infection in univariate and multivariate analysis. Similarly, BMI ≥30 kg/m2, diabetes, and ADM use were also associated with earlier onset of TE infection. ConclusionsThis study demonstrated similar TE infection rates at our safety-net hospitals compared with previously reported literature. To optimize the quality of care for patients in safety-net institutions, these risk factors must be addressed in the context of the unique challenges encountered in these settings.