County-Level Vulnerability Research Articles

Assessing county-level vulnerability to the energy transition in the United States using machine learning

Energy sector decarbonization will play a critical role in society's attempt to minimize climate change. This transition will unavoidably involve economic disruption to communities that rely on fossil fuels for jobs and economic activity. In this work, we assess the economic vulnerability of counties across the contiguous United States to the energy transition using a novel methodological approach that combines exposure through reduction in energy employment and socio-economic sensitivity due to a lack of adaptive capacity during the energy transition. Using machine learning clustering, we first identify county-level exposure to negative employment shocks. We then develop and implement the Resilience during the Energy Transition Index (RETI) to measure county-level sensitivity and adaptive capacity and compared this Index across employment clusters. We find that counties in coal mining clusters are significantly – and uniquely – less able to cope with economic distress. We also apply our framework to a case study focused on three of the states in Marcellus-Utica shale plays: Pennsylvania, Ohio and West Virginia. The results of this case study support the argument that financial and infrastructure boosts from non-renewable energy extraction and utilization build resilience only if they are used to building capital for the post‑carbon economy, providing further evidence of the conditions required for fossil fuels to serve as bridge fuels towards a low-carbon economy.

County-level social vulnerability and nonfatal drug overdose emergency department visits and hospitalizations, January 2018–December 2020

BackgroundNonfatal drug overdoses (NFODs) are often attributed to individual behaviors and risk factors; however, identifying community-level social determinants of health (SDOH) associated with increased NFOD rates may allow public health and clinical providers to develop more targeted interventions to address substance use and overdose health disparities. CDC’s Social Vulnerability Index (SVI), which aggregates social vulnerability data from the American Community Survey to produce ranked county-level vulnerability scores, can help identify community factors associated with NFOD rates. This study aims to describe associations between county-level social vulnerability, urbanicity, and NFOD rates. MethodsWe analyzed county-level 2018–2020 emergency department (ED) and hospitalization discharge data submitted to CDC’s Drug Overdose Surveillance and Epidemiology system. Counties were ranked in vulnerability quartiles based on SVI data. We used crude and adjusted negative binomial regression models, by drug category, to calculate rate ratios and 95% confidence intervals comparing NFOD rates by vulnerability. ResultsGenerally, as social vulnerability scores increased, ED and hospitalization NFOD rates increased; however, the magnitude of the association varied across drugs, visit type, and urbanicity. SVI-related theme and individual variable analyses highlighted specific community characteristics associated with NFOD rates. ConclusionsThe SVI can help identify associations between social vulnerabilities and NFOD rates. Development of an overdose-specific validated index could improve translation of findings to public health action. The development and implementation of overdose prevention strategies should consider a socioecological perspective and address health inequities and structural barriers associated with increased risk of NFODs at all levels of the social ecology.

Mapping county-level vulnerability to the energy transition in US fossil fuel communities

The energy transition toward lower-carbon energy sources will inevitably result in socioeconomic impacts on certain communities, particularly those that have historically produced fossil fuel resources and electricity generation using fossil fuels. Such communities stand to lose jobs, tax revenues, and support for public services. Which communities are most likely to be affected, which are more susceptible to being harmed, and how to target adaptive capacity programs—such as economic development and workforce training—accordingly are pressing scholarly and policy questions. In this study, we apply a vulnerability framework to calculate, rank, and map exposure and sensitivity scores for fossil fuel producing regions in the US. We find that, while counties in most regions of the United States will be affected by the transition away from fossil fuels, counties in Appalachia, Texas and the Gulf Coast region, and the Intermountain West are likely to experience the most significant impacts, and some regions experience overlapping and significant incidence of vulnerability. These results can be used to target future adaptive capacity programs.

Assessment of Tennessee's county-level vulnerability to hepatitis C virus and HIV outbreaks using socioeconomic, healthcare, and substance use indicators.

BackgroundHuman immunodeficiency virus (HIV), hepatitis C virus (HCV), and injection drug use are syndemic in the central Appalachian states. In Tennessee (TN), declines in HIV among persons who inject drugs (PWID) stalled, and HCV infection rates increased significantly from 2013–2017. To better target strategies to address the syndemic, county-level socioeconomic, opioid use, access to healthcare, and health factors were modeled to identify indicators predictive of vulnerability to an HIV/HCV outbreak among PWID in TN.MethodsNewly reported chronic HCV cases among persons aged 13–39 years in 2016–2017 were used as a proxy for county-level HIV/HCV vulnerability among TN’s 95 counties. Seventy-five publicly available county-level measures from 2016–2017 were collected and reduced through multiple dimension reduction techniques. Negative binomial regression identified indicators associated with HCV which were used to calculate county-level vulnerability to a local HIV/HCV outbreak.ResultsThirteen county-level indicators were identified as strongly predictive of HIV/HCV vulnerability with the statistically significant indicators being percentage of the population aged 20–44 years, per capita income, teen birth rate, percentage of clients in TDMHSAS-funded opioid treatment and recovery, syphilis case rate, and percentage of homes with at least one vehicle. Based on the 13 indicators, we identified the distribution of vulnerability to an HIV/HCV outbreak among TN’s counties. Eleven high vulnerability counties were identified, with the preponderance located in east and middle TN.ConclusionThis analysis identified the county-level factors most associated with vulnerability to an HIV/HCV outbreak among PWID in TN. These results, alongside routine surveillance, will guide targeted prevention and linkage to care efforts for the most vulnerable communities.

Abstract 3662: Association of US county-level social vulnerability index (SVI) with breast and colon cancer screening rates

Abstract Introduction: Whether social determinants of health (SDOH) affect US breast and colon cancer screening rates remains unclear. That said, in 2011 the CDC began recording a social vulnerability index (SVI) for all US counties. SVI was designed to capture four SDOH: socioeconomic status (SES), household composition and disability, minority status and language, and housing type and transportation. This retrospective study sought to determine the association of county-level SVI with breast and colon cancer screening rates. Methods: We used publicly available data from the CDC 2018 SVI database to collect SVI scores for every US county. SVI scores range from 0.1 to 1. A lower score indicates low vulnerability, while a higher score suggests high vulnerability. SVI scores were merged with publicly available data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS) and National Health Interview Survey (NHIS) containing county modeled estimates for breast and colon cancer screening rates. Counties were then divided into < 50th percentile and >= 50th percentile for breast and colon cancer screening. SVI scores and their four SDOH were compared between groups. Statistical significance between groups was assessed at an alpha less than 0.5. Linear regression was used to identify the association between high county-level SVI and the probability of being >= 50th percentile in breast and colon cancer screening. Results: This study involved 3,109 counties. Compared to counties >= 50th percentile in breast cancer screening (n = 1543), those < 50th percentile (n = 1566) were significantly worse off in SES (0.60 ± 0.27 vs. 0.41 ± 0.27), household composition and disability (0.58 ± 0.28 vs. 0.42 ± 0.28), minority status and language (0.51 ± .30 vs. 0.49 ± .28), housing type and transportation (0.53 ± 0.29 vs. 0.46 ± 0.28), and overall SVI (0.58 ± 0.28 vs. 0.42 ± 0.27) (p < .0001). Likewise, compared to counties >= 50th percentile in colon cancer screening (n = 1548), those < 50th percentile (n = 1561) were also significantly worse off in SES (0.63 ± 0.27 vs. 0.38 ± 0.25), household composition and disability (0.59 ± 0.27 vs. 0.41 ± 0.27), minority status and language (0.54 ± .30 vs. 0.45 ± .27), housing type and transportation (0.54 ± 0.29 vs. 0.46 ± 0.28), and overall SVI (0.61 ± 0.28 vs. 0.39 ± 0.27) (p < .0001). High SVI counties compared with low SVI counties were significantly less likely to be >= 50th percentile in breast cancer and colon cancer screening, OR 0.24 (95% CI 0.20 - 0.29) and 0.14 (95% CI 0.12 - 0.18). Finally, county-level SVI percentile correlated negatively with breast and colon cancer screening rates, Pearson coefficient -0.35 and -0.46. Conclusions: This study highlights the significant impact of US county-level SVI on breast and colon cancer screening rates, signaling the need for more effective intervention strategies and allocation of resources to help improve SDOH for our country's most vulnerable citizens. Citation Format: Akhil Mehta, Eric Lau, Gayathri Nagaraj, Hamid Mirshahidi. Association of US county-level social vulnerability index (SVI) with breast and colon cancer screening rates [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 3662.

Abstract 12208: Ecological Analysis of the Temporal Trends in the Association of Social Vulnerability and Race/Ethnicity With County-Level COVID-19 Incidence and Outcomes in the United States

Background: The COVID-19 pandemic adversely affected socially vulnerable and minority communities in the US initially, but the temporal trends during the year-long pandemic remain unknown. Objective: We examined temporal association between county-level Social Vulnerability Index (SVI), a percentile-based measure of social vulnerability to disasters, its subcomponents and race/ethnic composition with COVID-19 incidence and mortality in US in the year starting in March 2020. Methods: Counties (n=3091) with > 50 COVID-19 cases by March 6th, 2021 were included. Associations between SVI (and its subcomponents) and county level racial composition with incidence and death per capita were assessed using a negative-binomial mixed-effects model. This model was used to examine potential time varying associations between weekly number of cases/deaths and SVI or racial composition. Data was adjusted for percentage of population aged ≥65 years, state level testing rate, county-level comorbidities, and environmental factors. Results: Higher SVI, indicative of greater social vulnerability, was independently associated with higher COVID-19 incidence (adjusted incidence rate ratio [IRR] per-10 percentile increase:1.02, (95% CI 1.02, 1.03, p<0.001), and death per capita (1.04, (95% CI 1.04, 1.05, p<0.001). SVI became an independent predictor of incidence starting from March 2020, but this association became weak or insignificant by winter, a period that coincided with sharp increase in infection rates and mortality, and when counties with higher proportion of White residents were disproportionately represented (“third wave”). By Spring 2021, SVI was again a predictor of COVID-19 outcomes. Counties with greater proportion of Blacks also observed similar temporal trends in COVID-19-related adverse outcomes. Counties with greater proportion of Hispanics had worse outcomes throughout the duration of the analysis. Conclusion: Except for winter “third wave” when majority White communities had highest incidence of cases, counties with greater social vulnerability and higher minority populations, experienced worse COVID-19 outcomes.

A time-varying vulnerability index for COVID-19 in New Mexico, USA using generalized propensity scores

The coronavirus disease (COVID-19) pandemic has highlighted systemic inequities in the United States and resulted in a larger burden of negative social outcomes for marginalized communities. New Mexico, a state in the southwestern US, has a unique population with a large racial minority population and a high rate of poverty that may make communities more vulnerable to negative social outcomes from COVID-19. To identify which communities may be at the highest relative risk, we created a county-level vulnerability index. After the first COVID-19 case was reported in New Mexico on March 11, 2020, we fit a generalized propensity score model that incorporates sociodemographic factors to predict county-level viral exposure and thus, the generic risk to negative social outcomes such as unemployment or mental health impacts. We used four static sociodemographic covariates important for the state of New Mexico—population, poverty, household size, and minority population—and weekly cumulative case counts to iteratively run our model each week and normalize the exposure score to create a time-varying vulnerability index. We found the relative vulnerability between counties varied in the first eight weeks from the initial COVID-19 case before stabilizing. This framework for creating a location-specific vulnerability index in response to an ongoing disaster may be used as a quick, deployable metric to inform health policy decisions such as allocating state resources to the county level.

Characterizing opioid-involved overdose risk in local communities: An opioid overdose vulnerability assessment across Indiana, 2017

The objective of this initiative was to conduct a comprehensive opioid overdose vulnerability assessment in Indiana and evaluate spatial accessibility to opioid use disorder treatment, harm reduction services, and opioid response programs. We compiled 2017 county-level (n = 92) data on opioid-related and socioeconomic indicators from publicly available state and federal sources. First, we assessed the spatial distribution of opioid-related indicators in a geographic information system (GIS). Next, we used a novel regression-weighted ranking approach with mean standardized covariates and an opioid-involved overdose mortality outcome to calculate county-level vulnerability scores. Finally, we examined accessibility to opioid use disorder treatment services and opioid response programs at the census tract-level (n = 1511) using two-step floating catchment area analysis. Opioid-related emergency department visit rate, opioid-related arrest rate, chronic hepatitis C virus infection rate, opioid prescription rate, unemployment rate, and percent of female-led households were independently and positively associated with opioid-involved overdose mortality (p < 0.05). We identified high-risk counties across the rural–urban continuum and primarily in east central Indiana. We found that only one of the 19 most vulnerable counties was in the top quintile for treatment services and had naloxone provider accessibility in all of its census tracts. Findings from our vulnerability assessment provide local-level context and evidence to support and inform future public health policies and targeted interventions in Indiana in areas with high opioid overdose vulnerability and low service accessibility. Our approach can be replicated in other state and local public health jurisdictions to assess opioid-involved public health vulnerabilities.

ASO Visual Abstract: Impact of Race/Ethnicity and County-Level Vulnerability on Receipt of Surgery Among Older Medicare Beneficiaries Diagnosed with Early Pancreatic Cancer

ASO Visual Abstract: Impact of Race/Ethnicity and County-Level Vulnerability on Receipt of Surgery Among Older Medicare Beneficiaries Diagnosed with Early Pancreatic Cancer

Impact of Race/Ethnicity and County-Level Vulnerability on Receipt of Surgery Among Older Medicare Beneficiaries With the Diagnosis of Early Pancreatic Cancer.

Patients can experience barriers and disparities to access high-quality cancer care. This study sought to characterize receipt of surgery and chemotherapy among Medicare beneficiaries with a diagnosis of early-stage pancreatic adenocarcinoma cancer (PDAC) relative to race/ethnicity and social vulnerability. The Surveillance, Epidemiology, and End Results(SEER)-Medicare database was used to identify patients with a diagnosis of early-stage (stage 1 or 2) PDAC between 2004 and 2016. Data were merged with the CDC's Social Vulnerability Index (SVI) at the beneficiary's county of residence. Multivariable, mixed-effects logistic regression was used to assess the association of SVI with resection. Among 15,931 older Medicare beneficiaries with early-stage PDAC (median age, 77 years; interquartile range [IQR], 71-82 years), the majority was White (n = 12,737, 80.0 %), whereas a smaller subset was Black or Latino (n = 3194, 20.0 %) A minority of patients was more likely to live in highly vulnerable communities (low SVI: white [90.5 %] vs minority [9.5 %] vs high SVI: white [71.9 %] vs minority [28.1 %]; p < 0.001). Use of resection for early-stage PDAC was lowest among the patients who resided in high-SVI areas (low [38.0 %] vs average [34.3 %] vs high [31.9 %]; p < 0.001). The minority patients were less likely to undergo resection than the White patients (no resection: white [64.1 %] vs minority [70.7 %]; p < 0.001). The median SVI was higher among the patients who underwent resection (57.6; IQR, 36.0-81.0) than among those who did not (60.4; IQR, 41.9-84.3), and increased SVI resulted in a decline in the likelihood of resection (SVI trend: OR, 0.98; 95 % confidence interval [CI], 0.97-1.00), especially among the minority patients. Minority patients from high-SVI counties had markedly lower odds of preoperative chemotherapy than minority patients from a low-SVI neighborhood (OR, 0.62; 95 % CI, 0.52-0.73). Older Medicare beneficiaries with early-stage PDAC residing in counties with higher social vulnerability had lower odds of undergoing pancreatic resection, which was more pronounced among minority versus older White Medicare beneficiaries.

ASO Author Reflections: County-Level Social Vulnerability Associated with Disparities in Pancreatic Cancer Treatment, Especially among Patients from Racial and Ethnic Minorities.

ASO Author Reflections: County-Level Social Vulnerability Associated with Disparities in Pancreatic Cancer Treatment, Especially among Patients from Racial and Ethnic Minorities.

Adjusting statistical benchmark risk analysis to account for non-spatial autocorrelation, with application to natural hazard risk assessment

ABSTRACT We develop and study a quantitative, interdisciplinary strategy for conducting statistical risk analyses within the ‘benchmark risk’ paradigm of contemporary risk assessment when potential autocorrelation exists among sample units. We use the methodology to explore information on vulnerability to natural hazards across 3108 counties in the conterminous 48 US states, applying a place-based resilience index to an existing knowledgebase of hazardous incidents and related human casualties. An extension of a centered autologistic regression model is applied to relate local, county-level vulnerability to hazardous outcomes. Adjustments for autocorrelation embedded in the resiliency information are applied via a novel, non-spatial neighborhood structure. Statistical risk-benchmarking techniques are then incorporated into the modeling framework, wherein levels of high and low vulnerability to hazards are identified.

The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning.

The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning.

Association of County-Level Vulnerability, Patient-Level Race/Ethnicity, and Receipt of Surgery for Early-Stage Hepatocellular Carcinoma

This study assesses the association and interaction of county-level social vulnerability index with patient-level race/ethnicity compared with the probability of undergoing resection/transplant for early-stage hepatocellular carcinoma.

County-level Social Vulnerability is Associated With Worse Surgical Outcomes Especially Among Minority Patients.

We sought to characterize the association between patient county-level vulnerability with postoperative outcomes. Although the impact of demographic-, clinical- and hospital-level factors on outcomes following surgery have been examined, little is known about the effect of a patient's community of residence on surgical outcomes. Individuals who underwent colon resection, coronary artery bypass graft (CABG), lung resection, or lower extremity joint replacement (LEJR) were identified in the 2016 to 2017 Medicare database, which was merged with Center for Disease Control social vulnerability index (SVI) dataset at the beneficiary level of residence. Logistic regression models were utilized to estimate the probability of postoperative complications, mortality, readmission, and expenditures. Among 299,583 Medicare beneficiary beneficiaries who underwent a colectomy (n = 88,778, 29.6%), CABG (n = 109,564, 36.6%), lung resection (n = 30,401, 10.1%), or LEJR (n = 70,840, 23.6%).Mean SVI score was 50.2 (standard deviation: (25.2); minority patients were more likely to reside in highly vulnerable communities (low SVI: n = 3531, 5.8% vs high SVI: n = 7895, 13.3%; P < 0.001). After controlling for competing risk factors, the risk-adjusted probability of a serious complication among patients from a high versus low SVI county was 10% to 20% higher following colectomy [odds ratio (OR) 1.1 95% confidence intervals (CI) 1.1-1.2] or CABG (OR 1.2 95%CI 1.1-1.3), yet there no association of SVI with risk of serious complications following lung resection (OR 1.2 95%CI 1.0-1.3) or LEJR (OR 1.0 95%CI 0.93-1.2). The risk-adjusted probability of 30-day mortality was incrementally higher among patients from high SVI counties following colectomy (OR 1.1 95%CI 1.1-1.3), CABG (OR 1.4, 95%CI 1.2-1.5), and lung resection (OR 1.4 (95%CI 1.1-1.8), yet not LEJR (OR 0.95 95%CI 0.72-1.2). Black/minority patients undergoing a colectomy, CABG, or lung resection who lived in highly socially vulnerable counties had an estimate 28% to 68% increased odds of a serious complication and a 58% to 60% increased odds of 30-day mortality compared with a Black/minority patient from a low socially vulnerable county, as well as a markedly higher risk than White patients (all P > 0.05). Patients residing in vulnerable communities characterized by a high SVI generally had worse postoperative outcomes. The impact of social vulnerability was most pronounced among Black/minority patients, rather than White individuals. Efforts to ensure equitable surgical outcomes need to focus on both patient-level, as well as community-specific factors.

Race/Ethnicity and County-Level Social Vulnerability Impact Hospice Utilization Among Patients Undergoing Cancer Surgery.

Integration of palliative care services into the surgical treatment plan is important for holistic patient care. We soughtto examine the association between patient race/ethnicity and county-level vulnerability relative to patterns of hospice utilization. Medicare Standard Analytic Files were used to identify patients undergoing lung, esophageal, pancreatic, colon, or rectal cancer surgery between 2013 and 2017. Data were merged with the Centers for Disease Control and Prevention's social vulnerability index (SVI). Logistic regression was utilized to identify factors associated with overall hospice utilization among deceased individuals. A total of 54,256 Medicare beneficiaries underwent lung (n = 16,645, 30.7%), esophageal (n = 1427, 2.6%), pancreatic (n = 6183, 11.4%), colon (n = 26,827, 49.4%), or rectal (n = 3174, 5.9%) cancer resection. Median patient age was 76years (IQR 71-82years), and 28,887 patients (53.2%) were male; the majority of individuals were White (91.1%, n = 49,443), while a smaller subset was Black or Latino (racial/ethnic minority: n = 4813, 8.9%). Overall, 35,416 (65.3%) patients utilized hospice services prior to death. Median SVI was 52.8 [interquartile range (IQR) 30.3-71.2]. White patients were more likely to utilize hospice carecompared with minority patients (OR 1.24, 95% CI 1.17-1.31, p < 0.001). Unlike White patients, there was reduced odds of hospice utilization (OR 0.97, 95% CI 0.96-0.99) and early hospice initiation (OR 0.94, 95% CI 0.91-0.97) as SVI increased among minority patients. Patients residing in counties with high social vulnerability were less likely to be enrolled in hospice care at the time of death, as well as be less likely to initiate hospice care early. The effects of increasing social vulnerability on hospice utilizationwere more profound among minority patients.

Assessing County-Level Vulnerability for Opioid Overdose and Rapid Spread of Human Immunodeficiency Virus and Hepatitis C Infection in South Dakota.

Key indicators of vulnerability for the syndemic of opioid overdose, human immunodeficiency virus (HIV), and hepatitis C virus (HCV) due to injection drug use (IDU) in rural reservation and frontier counties are unknown. We examined county-level vulnerability for this syndemic in South Dakota. Informed by prior methodology from the Centers for Disease Control and Prevention, we used acute and chronic HCV infections among persons aged ≤40 years as a proxy measure of IDU. Twenty-nine county-level indicators potentially associated with HCV infection rates were identified. Using these indicators, we examined relationships through bivariate and multivariate analysis and calculated a composite index score to identify the most vulnerable counties (top 20%) to this syndemic. Of the most vulnerable counties, 69% are reservation counties and 62% are rural. The county-level HCV infection rate is 4 times higher in minority counties than nonminority counties, and almost all significant indicators of opioid-related vulnerability in our analysis are structural and potentially modifiable through public health interventions and policies. Our assessment gives context to the magnitude of this syndemic in rural reservation and frontier counties and should inform the strategic allocation of prevention and intervention services.

Association of County-Level Social Vulnerability with Elective Versus Non-elective Colorectal Surgery

IntroductionA person’s community, or lived environment, may play an important role in achieving optimal health outcomes. The objective of the current study was to assess the association of county-level vulnerability with the probability of having a non-elective colon resection. We hypothesized that individuals from areas with a high social vulnerability would be at greater risk of non-elective colon resection compared with patients from low social vulnerability areas. MethodsPatients aged 65–99 who underwent a colon resection for a primary diagnosis of either diverticulitis (n = 11,812) or colon cancer (n = 33,312) were identified in Medicare Part A and Part B for years 2016–2017. Logistic regression analysis was used to evaluate differences in probability of undergoing an elective versus non-elective operation from counties relative to county-level social vulnerability index (SVI). Secondary outcomes included postoperative complications, mortality, readmission, and index hospitalization expenditure. ResultsAmong 45,124 patients, 11,812 (26.2%) underwent a colon resection for diverticulitis, while 33,312 (73.8%) had a resection for colon cancer; 31,012 (68.7%) patients had an elective procedure (diverticulitis n = 7291 (61.7%) vs. cancer n = 23,721 (71.2%)), while 14,112 (31.3%) had an emergent operation (diverticulitis n = 4521 (38.3%) vs. cancer n = 9591 (28.8%)). Patients with a high SVI were more likely to undergo an emergent colon operation compared with low SVI patients (43.7% vs. 40.4%) (p < 0.001). The association of high SVI with increased risk of an emergent colon operation was similar among patients with diverticulitis (emergent: low SVI 37.2% vs. high SVI 40.4%) or colon cancer (emergent: low SVI 26.0% vs. high SVI 29.9%) (both p < 0.05). On multivariable analyses, risk-adjusted probability of undergoing an urgent/emergent operation remained associated with SVI (p < 0.05). ConclusionPatients residing in vulnerable communities characterized by a high SVI were more likely to undergo a non-elective colon resection for either diverticulitis or colon cancer. Patients from high SVI areas had a higher risk of postoperative complications, as well as index hospitalization expenditures; however, there were no differences in mortality or readmission rates.

Tennessee's In-state Vulnerability Assessment for a "Rapid Dissemination of Human Immunodeficiency Virus or Hepatitis C Virus Infection" Event Utilizing Data About the Opioid Epidemic.

Knowing which factors contribute to county-level vulnerability to a human immunodeficiency virus (HIV)/hepatitis C virus (HCV) outbreak, and which counties are most vulnerable, guides public health and clinical interventions. We therefore examined the impact of locally available indicators related to the opioid epidemic on prior national models of HIV/HCV outbreak vulnerability. Tennessee's 95 counties were the study sample. Predictors from 2012 and 2013 were used, mirroring prior methodology from the US Centers for Disease Control and Prevention (CDC). Acute HCV incidence was the proxy measure of county-level vulnerability. Seventy-eight predictors were identified as potentially predictive for HIV/HCV vulnerability. We used multiple dimension reduction techniques to determine predictors for inclusion and Poisson regression to generate a composite index score ranking county-level vulnerability for HIV/HCV. There was overlap of high-risk counties with the national analysis (25 of 41 counties). The distribution of vulnerability reinforces earlier research indicating that eastern Tennessee is at particularly high risk but also demonstrates that the entire state has high vulnerability. Prior research placed Tennessee among the top states for opioid prescribing, acute HCV infection, and greatest risk for an HIV/HCV outbreak. Given this confluence of risk, the Tennessee Department of Health expanded upon prior work to include more granular, local data, including on opioid prescribing. We also explored nonfatal and fatal overdoses. The more complete statewide view of risk generated, not only in eastern counties but also in the western corridor, will enable local officials to monitor vulnerability and better target resources.

Medications for opioid use disorder: bridging the gap in care

For the past two decades, the USA has been in the throes of an opioid crisis marked by a rising number of deaths; in 2016, opioids were responsible for most of the nation's estimated 64 000 fatal drug overdoses. 1 US Centers for Disease Control and PreventionNational Center for Health StatisticsNational Vital Statistics SystemProvisional counts of drug overdose deaths, as of 8/6/2017. https://www.cdc.gov/nchs/data/health_policy/monthly-drug-overdose-death-estimates.pdfDate: 2017 Google Scholar The problem began with overprescribing of opioid analgesics in the 1990s, which exposed pain patients to the risks of addiction and produced large surpluses of pain pills that were diverted for misuse by the larger community. Additionally, the escalating numbers of opioid-addicted Americans led to increased HIV and hepatitis C transmission among people who misuse these drugs by injecting them 2 Van Handel MM Rose CE Hallisey EJ et al. County-level vulnerability assessment for rapid dissemination of HIV or HCV infections among persons who inject drugs, United States. J Acquir Immune Defic Syndr. 2016; 73: 323-331 Crossref PubMed Scopus (278) Google Scholar and increased numbers of infants born dependent on opioids as a result of the mother's opioid use (neonatal abstinence syndrome). 3 Brown JD Goodin AJ Talbert JC Rural and Appalachian disparities in neonatal abstinence syndrome incidence and access to opioid abuse treatment. J Rural Health. 2017; (published online July 7.)DOI: 10.1111/jrh.12251 Google Scholar Extended-release naltrexone: good but not a panaceaUnlike other addictions, opioid-use disorder has several highly effective medication treatments available, in particular methadone, buprenorphine, and naltrexone.1–3 Methadone is the least accessible or acceptable of these in many settings, so providers and patients are often faced with a choice between buprenorphine-naloxone (BUP-NX) and extended-release naltrexone injection (XR-NTX). Full-Text PDF Comparative effectiveness of extended-release naltrexone versus buprenorphine-naloxone for opioid relapse prevention (X:BOT): a multicentre, open-label, randomised controlled trialIn this population it is more difficult to initiate patients to XR-NTX than BUP-NX, and this negatively affected overall relapse. However, once initiated, both medications were equally safe and effective. Future work should focus on facilitating induction to XR-NTX and on improving treatment retention for both medications. Full-Text PDF