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1.
PLoS One ; 16(10): e0257437, 2021.
Article in English | MEDLINE | ID: covidwho-1456086

ABSTRACT

INTRODUCTION: This article presents the Louisiana Hepatitis C Elimination Program's evaluation protocol underway at the Louisiana State University Health Sciences Center-New Orleans. With the availability of direct-acting antiviral (DAA) agents, the elimination of Hepatitis C (HCV) has become a possibility. The HCV Elimination Program was initiated by the Louisiana Department of Health (LDH) Office of Public Health (OPH), LDH Bureau of Health Services Financing (Medicaid), and the Louisiana Department of Public Safety and Corrections (DPSC) to provide HCV treatment through an innovative pricing arrangement with Asegua Therapeutics, whereby a fixed cost is set for a supply of treatment over five years. MATERIALS AND METHODS: A cross-sectional study design will be used. Data will be gathered from two sources: 1) an online survey administered via REDCap to a sample of Medicaid members who are receiving HCV treatment, and 2) a de-identified data set that includes both Medicaid claims data and OPH surveillance data procured via a Data Use Agreement between LSUHSC-NO and Louisiana Medicaid. DISCUSSION: The evaluation will contribute to an understanding of the scope and reach of this innovative treatment model, and as a result, an understanding of areas for improvement. Further, this evaluation may provide insight for other states considering similar contracting mechanisms and programs.


Subject(s)
Antiviral Agents/therapeutic use , Hepatitis C/drug therapy , Cross-Sectional Studies , Health Services Accessibility , Hepacivirus/drug effects , Humans , Louisiana/epidemiology , Medicaid , New Orleans/epidemiology , United States/epidemiology
2.
PLoS One ; 15(12): e0243028, 2020.
Article in English | MEDLINE | ID: covidwho-1004440

ABSTRACT

BACKGROUND: Louisiana in the summer of 2020 had the highest per capita case count for COVID-19 in the United States and COVID-19 deaths disproportionately affects the African American population. Neighborhood deprivation has been observed to be associated with poorer health outcomes. The purpose of this study was to examine the relationship between neighborhood deprivation and COVID-19 in Louisiana. METHODS: The Area Deprivation Index (ADI) was calculated and used to classify neighborhood deprivation at the census tract level. A total of 17 US census variables were used to calculate the ADI for each of the 1148 census tracts in Louisiana. The data were extracted from the American Community Survey (ACS) 2018. The neighborhoods were categorized into quintiles as well as low and high deprivation. The publicly available COVID-19 cumulative case counts by census tract were obtained from the Louisiana Department of Health website on July 31, 2020. Descriptive and Poisson regression analyses were performed. RESULTS: Neighborhoods in Louisiana were substantially different with respect to deprivation. The ADI ranged from 136.00 for the most deprived neighborhood and -33.87 in the least deprived neighborhood. We observed that individuals residing in the most deprived neighborhoods had almost a 40% higher risk of COVID-19 compared to those residing in the least deprived neighborhoods. CONCLUSION: While the majority of previous studies were focused on very limited socio-environmental factors such as crowding and income, this study used a composite area-based deprivation index to examine the role of neighborhood environment on COVID-19. We observed a positive relationship between neighborhood deprivation and COVID-19 risk in Louisiana. The study findings can be utilized to promote public health preventions measures besides social distancing, wearing a mask while in public and frequent handwashing in vulnerable neighborhoods with greater deprivation.


Subject(s)
COVID-19/epidemiology , Health Status Disparities , Poverty Areas , Residence Characteristics/statistics & numerical data , Employment/statistics & numerical data , Humans , Income/statistics & numerical data , Louisiana/epidemiology , Vulnerable Populations/statistics & numerical data
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