Asset Mapping and Focus Group Usage: An Exploration of the Russian-Ukrainian Population’s Need For and Use of Health-Related Community Resources

Community resources are an important aspect of preventive medicine and can also provide support to individuals with existing medical conditions. However, resources may not address all population groups within the community equally, and immigrants, who frequently face cultural and language barriers, are often unable to access the full range of healthcare resources available in the community. The purpose of this study was to gain insight on healthcare needs, attitudes, and access of a Ukrainian immigrant population in a large town in northern Indiana. Focus groups were conducted as a first step to creating connections upon which a community-based participatory research project could be built. Findings revealed cultural barriers (lack of understanding of health insurance options or value, belief that similar services were less expensive in the Ukraine) and language issues (lack of translation services or resources written in languages other than English or Spanish) were key barriers to accessing healthcare resources in the community. Concerns about dental care and its expense were also voiced. Future efforts might build on these findings by exploring policies and practices that affect various immigrant groups’ access to community healthcare resources. Recommendations for such efforts are also discussed

The Effectiveness of Incarceration-Based Drug Treatment on Criminal Behavior: A Systematic Review

Many, if not most, incarcerated offenders have substance abuse problems. Without effective treatment, these substance-abusing offenders are likely to persist in non-drug offending. The period of incarceration offers an opportunity to intervene in the cycle of drug abuse and crime. Although many types of incarceration-based drug treatment programs are available (e.g., therapeutic communities and group counseling), the effectiveness of these programs is unclear. The objective of this research synthesis is to systematically review quasi-experimental and experimental (RCT) evaluations of the effectiveness of incarceration-based drug treatment programs in reducing post-release recidivism and drug relapse. A secondary objective of this synthesis is to examine variation in effectiveness by programmatic, sample, and methodological features. In this update of the original 2006 review (see Mitchell, Wilson, and MacKenzie, 2006), studies made available since the original review were included in an effort to keep current with emerging research. This synthesis of evaluations of incarceration-based drug treatment programs found that such programs are modestly effective in reducing recidivism. These findings most strongly support the effectiveness of therapeutic communities, as these programs produced relatively consistent reductions in recidivism and drug use. Both counseling and incarceration-based narcotic maintenance programs had mixed effects. Counseling programs were associated with reductions in recidivism but not drug use; whereas, incarceration-based narcotic maintenance programs were associated with reductions in drug use but not recidivism. Note that our findings regarding the effectiveness of incarceration-based narcotic maintenance programs differ from a larger review of community-based narcotic maintenance programs (see Egli, Pina, Christensen, Aebi, and Killias, 2009). Finally, boot camp programs for drug offenders had negligible effects on both recidivism and drug use

Engineering the Properties of Polymer Photonic Crystals with Mesoporous Silicon Templates

The effect of molecular weight on the rate and extent of melt-infiltration of polystyrene into mesoporous silicon-based photonic crystals is investigated as a function of polymer molecular weight. Polymer viscosity and chain end-to-end (Ree) distance correlate with the rate and extent of infiltration. High molecular weight (Mw) polystyrene (200 or 400 kDa) infiltrates the mesoporous material in two distinct phases: a rapid phase where the larger pores of the template are filled, followed by a slower phase during which the smaller pores fill. Low molecular weight polystyrene (20 and 35 kDa) fills the pores more uniformly, progressing into the film as a single, relatively distinct front of liquid polymer. Scanning electron microscope (SEM) analyses of cross sections of the films are consistent with the optical measurements, showing a lower extent of infiltration for the higher molecular weight polymers. Removal of the porous Si templates by soaking in a chemical etchant generates free-standing films of nanostructured polymer. The low molecular weight samples display better replication. Partial removal of the template enables tuning of the hydrophobicity of the free-standing polymer films, which is demonstrated with a flexible and chemically stable polyvinylidene fluoride polymer

Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program.

BackgroundThe risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death.Methods and resultsWe included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30-0.76) and 0.59 (0.31-1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32-1.77) and 1.63 (1.32-2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20-24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality.ConclusionsOlder age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted

Effectiveness of COVID-19 Vaccines in Preventing Hospitalization Among Adults Aged ≥65 Years - COVID-NET, 13 States, February-April 2021.

Clinical trials of COVID-19 vaccines currently authorized for emergency use in the United States (Pfizer-BioNTech, Moderna, and Janssen [Johnson & Johnson]) indicate that these vaccines have high efficacy against symptomatic disease, including moderate to severe illness (1-3). In addition to clinical trials, real-world assessments of COVID-19 vaccine effectiveness are critical in guiding vaccine policy and building vaccine confidence, particularly among populations at higher risk for more severe illness from COVID-19, including older adults. To determine the real-world effectiveness of the three currently authorized COVID-19 vaccines among persons aged ≥65 years during February 1-April 30, 2021, data on 7,280 patients from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) were analyzed with vaccination coverage data from state immunization information systems (IISs) for the COVID-NET catchment area (approximately 4.8 million persons). Among adults aged 65-74 years, effectiveness of full vaccination in preventing COVID-19-associated hospitalization was 96% (95% confidence interval [CI] = 94%-98%) for Pfizer-BioNTech, 96% (95% CI = 95%-98%) for Moderna, and 84% (95% CI = 64%-93%) for Janssen vaccine products. Effectiveness of full vaccination in preventing COVID-19-associated hospitalization among adults aged ≥75 years was 91% (95% CI = 87%-94%) for Pfizer-BioNTech, 96% (95% CI = 93%-98%) for Moderna, and 85% (95% CI = 72%-92%) for Janssen vaccine products. COVID-19 vaccines currently authorized in the United States are highly effective in preventing COVID-19-associated hospitalizations in older adults. In light of real-world data demonstrating high effectiveness of COVID-19 vaccines among older adults, efforts to increase vaccination coverage in this age group are critical to reducing the risk for COVID-19-related hospitalization

A large, open source dataset of stroke anatomical brain images and manual lesion segmentations.

Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals experiencing long-term disabilities. Large-scale neuroimaging studies have shown promise in identifying robust biomarkers (e.g., measures of brain structure) of long-term stroke recovery following rehabilitation. However, analyzing large rehabilitation-related datasets is problematic due to barriers in accurate stroke lesion segmentation. Manually-traced lesions are currently the gold standard for lesion segmentation on T1-weighted MRIs, but are labor intensive and require anatomical expertise. While algorithms have been developed to automate this process, the results often lack accuracy. Newer algorithms that employ machine-learning techniques are promising, yet these require large training datasets to optimize performance. Here we present ATLAS (Anatomical Tracings of Lesions After Stroke), an open-source dataset of 304 T1-weighted MRIs with manually segmented lesions and metadata. This large, diverse dataset can be used to train and test lesion segmentation algorithms and provides a standardized dataset for comparing the performance of different segmentation methods. We hope ATLAS release 1.1 will be a useful resource to assess and improve the accuracy of current lesion segmentation methods