Poverty and population health - The need for A Paradigm shift to capture the working poor and better inform public health planning.

Background: Community-level socioeconomic disparities have a significant impact on an individual's health and overall well-being. However, current estimates for poverty threshold, which are often used to assess community-level socioeconomic status, do not account for cost-of-living differences or geography variability. The goals of this study were to compare geographic county-level overlap and gaps in access to care for households within poverty and working poor designations.

Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach.

Background: The COVID-19 pandemic has demonstrated the need for efficient and comprehensive, simultaneous assessment of multiple combined novel therapies for viral infection across the range of illness severity. Randomized Controlled Trials (RCT) are the gold standard by which efficacy of therapeutic agents is demonstrated. However, they rarely are designed to assess treatment combinations across all relevant subgroups.

Substance Abuse and Rural Appalachian Pediatric Trauma in West Virginia.

Introduction: Rural Appalachia is endemic to issues such as substance abuse, poverty, and lack of community support, all of which negatively influence health outcomes. The incidence of pediatric trauma as it relates to substance abuse is of concern in the region, where the rate of positive drug screens in pediatric trauma cases is higher than national average.

Methods: The West Virginia statewide pediatric trauma database was analyzed in a retrospective cohort study for the years 2009-2019.

Higher hospitalization and mortality rates among SARS-CoV-2-infected persons in rural America.

Purpose: Rural communities are among the most underserved and resource-scarce populations in the United States. However, there are limited data on COVID-19 outcomes in rural America. This study aims to compare hospitalization rates and inpatient mortality among SARS-CoV-2-infected persons stratified by residential rurality.

Predicting increases in COVID-19 incidence to identify locations for targeted testing in West Virginia: A machine learning enhanced approach.

During the COVID-19 pandemic, West Virginia developed an aggressive SARS-CoV-2 testing strategy which included utilizing pop-up mobile testing in locations anticipated to have near-term increases in SARS-CoV-2 infections. This study describes and compares two methods for predicting near-term SARS-CoV-2 incidence in West Virginia counties. The first method, Rt Only, is solely based on producing forecasts for each county using the daily instantaneous reproductive numbers, Rt.

Predicting increases in COVID-19 incidence to identify locations for targeted testing in West Virginia: A machine learning enhanced approach.

During the COVID-19 pandemic, West Virginia developed an aggressive SARS-CoV-2 testing strategy which included utilizing pop-up mobile testing in locations anticipated to have near-term increases in SARS-CXoV-2 infections. In this study, we describe and compare two methods for predicting near-term SARS-CoV-2 incidence in West Virginia counties. The first method, R Only, is solely based on producing forecasts for each county using the daily instantaneous reproductive numbers, R The second method, ML+ R , is a machine learning approach that uses a Long Short-Term Memory network to predict the near-term number of cases for each county using epidemiological statistics such as Rt, county population information, and time series trends including information on major holidays, as well as leveraging statewide COVID-19 trends across counties and county population size.

Clinical Characteristics and Outcomes of COVID-19 in West Virginia.

This study examines the clinical characteristics, outcomes and types of management in SARS-CoV-2 infected patients, in the hospitals affiliated with West Virginia University. We included patients from West Virginia with SARS-CoV-2 infection between 15 April to 30 December 2020. Descriptive analysis was performed to summarize the characteristics of patients.

High prevalence of co-occurring substance use in individuals with opioid use disorder.

Objective: Funding to address the current opioid epidemic has focused on treatment of opioid use disorder (OUD); however, rates of other substance use disorders (SUDs) remain high and non-opioid related overdoses account for nearly 30% of overdoses. This study assesses the prevalence of co-occurring substance use in West Virginia (WV) to inform treatment strategies. The objective of this study was to assess the prevalence of, and demographic and clinical characteristics (including age, gender, hepatitis C virus (HCV) status) associated with, co-occurring substance use among patients with OUD in WV.