Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Data providing detailed county level information for eWIC rollout in Ohio.

ABSTRACT: By October 2020, states across the nation must deliver benefits for the WIC program via electronic benefits transfer, also referred to as eWIC. The state of Ohio made the transition from 2014 to 2015 and staggered implementation across counties. In this article, we present county-level data on the specific dates Ohio counties changed to eWIC. We also present detailed demographic data for the counties included in each roll-out date.

SUBMITTER: Hanks AS

PROVIDER: S-EPMC6517565 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Data providing detailed county level information for eWIC rollout in Ohio.

Hanks Andrew S AS Gunther Carolyn C Lillard Dean D Scharff Robert R

Data in brief 20190427

By October 2020, states across the nation must deliver benefits for the WIC program via electronic benefits transfer, also referred to as eWIC. The state of Ohio made the transition from 2014 to 2015 and staggered implementation across counties. In this article, we present county-level data on the specific dates Ohio counties changed to eWIC. We also present detailed demographic data for the counties included in each roll-out date. ...[more]

PMID: 31193092

Similar Datasets

Pathway-Level Information ExtractoR (PLIER) for gene expression data

Project description:A major challenge in gene expression analysis is to accurately infer relevant biological insight, such as variation in cell type proportion or pathway activity, from global gene expression studies. We present a general solution for this problem that outperforms available cell proportion inference algorithms, and is more widely useful to automatically identify specific pathways that regulate gene expression. Our method improves replicability and biological insight when applied to trans-eQTL identification.

2019-05-14 | GSE130824 | GEO

Pathway-level information extractor (PLIER) for gene expression data.

Project description:A major challenge in gene expression analysis is to accurately infer relevant biological insights, such as variation in cell-type proportion or pathway activity, from global gene expression studies. We present pathway-level information extractor (PLIER) ( https://github.com/wgmao/PLIER and http://gobie.csb.pitt.edu/PLIER ), a broadly applicable solution for this problem that outperforms available cell proportion inference algorithms and can automatically identify specific pathways that regulate gene expression. Our method improves interstudy replicability and reveals biological insights when applied to trans-eQTL (expression quantitative trait loci) identification.

| S-EPMC7262669 | biostudies-literature

Spatial Disparities in Access to Healthcare Professionals in Sichuan: Evidence from County-Level Data.

Project description:As a southwestern province of China, Sichuan is confronted with geographical disparities in access to healthcare professionals because of its complex terrain, uneven population distribution and huge economic gaps between regions. With 10-year data, this study aims to explore the county-level spatial disparities in access to different types of healthcare professionals (licensed doctors, registered nurses, pharmacists, technologists and interns) in Sichuan using temporal and spatial analysis methods. The time-series results showed that the quantity of all types of healthcare professionals increased, especially the registered nurses, while huge spatial disparities exist in the distribution of healthcare professionals in Sichuan. The local Moran's I calculations showed that high-high clusters (significantly high healthcare professional quantity in a group of counties) were detected in Chengdu (capital of Sichuan) and relatively rich areas, while low-low clusters (significantly low healthcare professional quantity in a group of counties) were usually found near the mountain areas, namely, Tsinling Mountains and Hengduan Mountains. The findings may deserve considerations in making region-oriented policies in educating and attracting more healthcare professionals to the disadvantaged areas.

| S-EPMC8394835 | biostudies-literature

Integrating environmental and satellite data to estimate county-level cotton yield in Xinjiang Province.

Project description:Accurate and timely estimation of cotton yield over large areas is essential for precision agriculture, facilitating the operation of commodity markets and guiding agronomic management practices. Remote sensing (RS) and crop models are effective means to predict cotton yield in the field. The satellite vegetation indices (VIs) can describe crop yield variations over large areas but can't take the exact environmental impact into consideration. Climate variables (CVs), the result of the influence of spatial heterogeneity in large regions, can provide environmental information for better estimation of cotton yield. In this study, the most important VIs and CVs for estimating county-level cotton yield across Xinjiang Province were screened out. We found that the VIs of canopy structure and chlorophyll contents, and the CVs of moisture, were the most significant factors for cotton growth. For yield estimation, we utilized four approaches: least absolute shrinkage and selection operator regression (LASSO), support vector regression (SVR), random forest regression (RFR) and long short-term memory (LSTM). Due to its ability to capture temporal features over the long term, LSTM performed best, with an R2 of 0.76, root mean square error (RMSE) of 150 kg/ha and relative RMSE (rRMSE) of 8.67%; moreover, an additional 10% of the variance could be explained by adding CVs to the VIs. For the within-season yield estimation using LSTM, predictions made 2 months before harvest were the most accurate (R2 = 0.65, RMSE = 220 kg/ha, rRMSE = 15.97%). Our study demonstrated the feasibility of yield estimation and early prediction at the county level over large cotton cultivation areas by integrating satellite and environmental data.

| S-EPMC9889829 | biostudies-literature

Role of independent versus chain pharmacies in providing pharmacy access: a nationwide, individual-level geographic information systems analysis.

Project description:Pharmacy accessibility is critical for equity in medication access and is jeopardized by pharmacy closures, which disproportionately affect independent pharmacies. We conducted a geographic information systems analysis to quantify how many individuals across the US do not have optimal pharmacy access or solely rely on independent pharmacies for access. We generated service areas of pharmacies using OpenStreetMap data. For each individual in a 30% random sample of the 2020 RTI US Household Synthetic Population™ (n=90,778,132), we defined optimal pharmacy access as having a driving distance to the closest pharmacy ≤2 miles in urban counties, ≤5 miles in suburban counties, and ≤10 miles in rural counties. Individuals were then categorized according to their access to chain and independent pharmacies. Five percent of the sample or ~15.1 million individuals nationwide relied on independent pharmacies for optimal access. Individuals relying on independent pharmacies for optimal access were more likely to live in rural areas, be 65 years or older, and belong to low-income households. Another 19.5% of individuals in the sample did not have optimal pharmacy access, which corresponds to 59.0 million individuals nationwide. Our findings demonstrate that independent pharmacies play a critical role in ensuring equity in pharmacy access.

| S-EPMC10519705 | biostudies-literature

Private Companies Providing Health Care Price Data: Who Are They and What Information do They Provide?

Project description:There is interest in making health care price information more transparent given the increase in enrollment in high-deductible and consumer-directed health plans, and as policy efforts intensify to engage consumers to obtain high value care. We examine the role of private companies that market price transparency tools, primarily to self-insured employers - an important yet understudied topic. What companies exist? How did they emerge? What information do they provide? Where do they get that information? How does the price and quality information provided compare across companies?

| S-EPMC4323083 | biostudies-literature

Mapping European research networks providing health data: results from the InfAct Joint Action on health information.

Project description:BackgroundResearch networks offer multidisciplinary expertise and promote information exchange between researchers across Europe. They are essential for the European Union's (EU) health information system as providers of health information and data. The aim of this mapping exercise was to identify and analyze EU research networks in terms of health data collection methods, quality assessment, availability and accessibility procedures.MethodsA web-based search was performed to identify EU research networks that are not part of international organizations (e.g., WHO-Europe, OECD) and are involved in collection of data for health monitoring or health system performance assessment. General characteristics of the research networks (e.g., data sources, representativeness), quality assessment procedures, availability and accessibility of health data were collected through an ad hoc extraction form.ResultsFifty-seven research networks, representative at national, international or regional level, were identified. In these networks, data are mainly collected through administrative sources, health surveys and cohort studies. Over 70% of networks provide information on quality assessment of their data collection procedures. Most networks share macrodata through articles and reports, while microdata are available from ten networks. A request for data access is required by 14 networks, of which three apply a financial charge. Few networks share data with other research networks (8/49) or specify the metadata-reporting standards used for data description (9/49).ConclusionsImproving health information and availability of high quality data is a priority in Europe. Research networks could play a major role in tackling health data and information inequalities by enhancing quality, availability, and accessibility of health data and data sharing across European networks.

| S-EPMC8744039 | biostudies-literature

MODELLING COUNTY LEVEL BREAST CANCER SURVIVAL DATA USING A COVARIATE-ADJUSTED FRAILTY PROPORTIONAL HAZARDS MODEL.

Project description:Understanding the factors that explain differences in survival times is an important issue for establishing policies to improve national health systems. Motivated by breast cancer data arising from the Surveillance Epidemiology and End Results program, we propose a covariate-adjusted proportional hazards frailty model for the analysis of clustered right-censored data. Rather than incorporating exchangeable frailties in the linear predictor of commonly-used survival models, we allow the frailty distribution to flexibly change with both continuous and categorical cluster-level covariates and model them using a dependent Bayesian nonparametric model. The resulting process is flexible and easy to fit using an existing R package. The application of the model to our motivating example showed that, contrary to intuition, those diagnosed during a period of time in the 1990s in more rural and less affluent Iowan counties survived breast cancer better. Additional analyses showed the opposite trend for earlier time windows. We conjecture that this anomaly has to be due to increased hormone replacement therapy treatments prescribed to more urban and affluent subpopulations.

| S-EPMC4520441 | biostudies-literature

Providing a detailed estimate of mortality using a simulation-based collision risk model.

Project description:Marine renewables could form a significant part of the green energy mix. However, a potential environmental impact of tidal energy converters (TECs) is collision risk between a device and animal, which has been a significant barrier in the consenting process. While it is important to understand the number of collisions of an animal with the device, the relative speed at which an animal collides with the device, and the point on the animal where collision occurs, will determine whether a collision is fatal, which is important in understanding population-level impacts. Using a simulation-based collision risk model, this paper demonstrates a novel method for producing estimates of mortality. Extracting both the speed and the location of collisions between an animal and TEC, in this instance a seal and horizontal axis turbine, collision speed and location of collision are used to produce probabilities of mortality. To provide a hypothetical example we quantified the speed and position at which a collision occurs to estimate mortality and, using collision position, we determine all predicted collisions with the head of the animal as fatal, for example, whilst deeming other collisions non-fatal. This is the first collision risk model to incorporate speed at the point of contact and the location where the collision occurs on the animal, to estimate the probability of mortality resulting from a collision. The hypothetical scenarios outline how these important variables extracted from the model can be used to predict the proportion of fatal events. This model enables a comprehensive approach that ultimately provides advancements in collision risk modelling for use in the consenting process of TECs. Furthermore, these methods can easily be adapted to other renewable energy devices and receptors, such as wind and birds.

| S-EPMC9671428 | biostudies-literature

Providing personal information to the benefit of others.

Project description:Personal information is a precious resource, not only for commercial interests but also for the public benefit. Reporting personal location data, for example, may aid efficient traffic flows and sharing one's health status may be a crucial instrument of disease management. We experimentally study individuals' willingness to contribute personal information to information-based public goods. Our data provide evidence that-compared to monetary contributions to public goods-information may be substantially under-provided. We show that the degree of information provision is strongly correlated to the information's implicit (emotional and cognitive) costs. Individual's reluctance to share personal information with high implicit, in particular emotional costs, may seriously limit the effectiveness of information-based public goods.

| S-EPMC7437809 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data