scholarly journals Protocol—Evaluating the Effect of ACA Medicaid Expansion on Mortality During the COVID-19 Pandemic Using County-level Matching

2021 ◽  
Vol 7 (2) ◽  
pp. S1-S31
Author(s):  
Charlotte Z. Mann ◽  
Ben B. Hansen ◽  
Lauren Gaydosh ◽  
Timothy Lycurgus
Keyword(s):  
County Level ◽  
Medicaid Expansion

scholarly journals 444. County-level COVID-19 Case Fatality Rate in Medicaid Expansion States Compared to Non-Expansion States

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S323-S324
Author(s):  
Walid El-Nahal ◽  
Stephen Berry ◽  
Kevin Psoter ◽  
Kelly Gebo
Keyword(s):  
Case Fatality Rate ◽  
Negative Binomial ◽  
District Of Columbia ◽  
Case Fatality ◽  
County Level ◽  
Medicaid Expansion ◽  
Fatality Rate ◽  
Physician Density ◽  
Related Case ◽  
Significant Difference

Abstract Background Medicaid expansion has been adopted by 38 states and the District of Columbia,1,2 contributing to lower rates of uninsured individuals in the US.3 During the COVID-19 pandemic, Medicaid enrollment offset employer-based insurance losses precipitated by the recession.4 The aim of this study was to evaluate whether Medicaid expansion may have impacted COVID-19 mortality. Methods We conducted an ecologic study that included all US counties in the 50 states and District of Columbia. County-specific Medicaid expansion status was based on whether expansion was adopted within the state. COVID-19 cases and deaths for each county were obtained from the Centers of Disease Control (CDC). Unadjusted and multivariable negative binomial regression with robust standard errors to account for clustering of counties within each state were used to evaluate the association of COVID-19 case fatality rate and Medicaid expansion status. Adjusted models included the addition of four sets of county-level covariates thought to influence the association of Medicaid status and COVID-19 fatality rate: demographics, comorbidities, economic indicators, and physician density. These analyses were then performed in subgroups of counties defined by urbanicity (metro, suburban or rural) and quartiles of poverty rates. Incidence Rate Ratios (IRR) and 95% confidence intervals (CI) are reported. Results A total of 1,814 Medicaid expansion and 1,328 non-expansion counties were included in the analysis. Crude case fatality rates were 2.1% (non-expansion) and 1.8% (expansion). Medicaid expansion was not associated with a significantly lower COVID-19 case fatality rate in either the unadjusted (IRR: 0.86; 95% CI: 0.74, 1.01) or fully adjusted (IRR: 1.02; 95% CI: 0.90, 1.16) models. In adjusted models, Medicaid expansion status was also not associated with differences in COVID-19 case fatality rate when counties were stratified by either urbanicity or percent of individuals living below the poverty line. Conclusion In this county-level analysis, Medicaid expansion status was not associated with a significant difference in county-level COVID-19-related case fatality rates among people of all ages. Future individual-level studies are needed to better characterize the effect of Medicaid on COVID-19 mortality. Disclosures All Authors: No reported disclosures

Convergence of regional population density in Russia over 120 years

2020 ◽  
pp. 133-158
Author(s):  
K. A. Kholodilin ◽  
Y. I. Yanzhimaeva
Keyword(s):  
Population Density ◽  
Spatial Dependence ◽  
Population Distribution ◽  
Regional Level ◽  
Capital City ◽  
County Level ◽  
Spatial Effects ◽  
Russian Regions ◽  
Regional Population ◽  
Regional Population Density

A relative uniformity of population distribution on the territory of the country is of importance from socio-economic and strategic perspectives. It is especially important in the case of Russia with its densely populated West and underpopulated East. This paper considers changes in population density in Russian regions, which occurred between 1897 and 2017. It explores whether there was convergence in population density and what factors influenced it. For this purpose, it uses the data both at county and regional levels, which are brought to common borders for comparability purposes. Further, the models of unconditional and conditional β-convergence are estimated, taking into account the spatial dependence. The paper concludes that the population density equalization took place in 1897-2017 at the county level and in 1926—1970 at the regional level. In addition, the population density increase is shown to be influenced not only by spatial effects, but also by political and geographical factors such as climate, number of GULAG camps, and the distance from the capital city.

Realizing the Devolution Dividend in Kenya through Cohesive Public Finance Management and Public Participation at County Level

10.1596/29624 ◽  
2017 ◽  
Author(s):  
Rose Wanjiru ◽  
Paul Otsola ◽  
Mutakha Kangu ◽  
Murumba Werunga ◽  
Christine Owuor ◽  
...  
Keyword(s):  
Public Finance ◽  
Public Participation ◽  
County Level ◽  
Finance Management
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