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10.1111/jrh.12477 http://scihub22266oqcxt.onion/10.1111/jrh.12477 C7323251!7323251 !32543751     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\32543751 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       J+Rural+Health 2020 ; 36 (3 ): 446-456 Nephropedia Template TP {{tp|p=32543751 |t=2020. Community Susceptibility and Resiliency to COVID-19 Across the Rural-Urban Continuum in the United States |pdf=|usr=}}{{32543751 }} gab.com Text Community Susceptibility and Resiliency to COVID-19 Across the Rural-Urban Continuum in the United States JO: J Rural Health http://www.kidney.de/pget.php?&tw=1&pmid=32543751 #FOAvip PURPOSE: This study creates a COVID-19 susceptibility scale at the county level, describes its components, and then assesses the health and socioeconomic resiliency of susceptible places across the rural-urban continuum. METHODS: Factor analysis grouped 11 indicators into 7 distinct susceptibility factors for 3,079 counties in the conterminous United States. Unconditional mean differences are assessed using a multivariate general linear model. Data from 2018 are primarily taken from the US Census Bureau and CDC. RESULTS: About 33% of rural counties are highly susceptible to COVID-19, driven by older and health-compromised populations, and care facilities for the elderly. Major vulnerabilities in rural counties include fewer physicians, lack of mental health services, higher disability, and more uninsured. Poor Internet access limits telemedicine. Lack of social capital and social services may hinder local pandemic recovery. Meat processing facilities drive risk in micropolitan counties. Although metropolitan counties are less susceptible due to healthier and younger populations, about 6% are at risk due to community spread from dense populations. Metropolitan vulnerabilities include minorities at higher health and diabetes risk, language barriers, being a transportation hub that helps spread infection, and acute housing distress. CONCLUSIONS: There is an immediate need to know specific types of susceptibilities and vulnerabilities ahead of time to allow local and state health officials to plan and allocate resources accordingly. In rural areas it is essential to shelter-in-place vulnerable populations, whereas in large metropolitan areas general closure orders are needed to stop community spread. Pandemic response plans should address vulnerabilities. Twit Text FOAVip Community Susceptibility and Resiliency to COVID-19 Across the Rural-Urban Continuum in the United States ????J Rural Health http://www.kidney.de/pget.php?&tw=1&pmid=32543751 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32543751 #FOAvip English Wikipedia <ref>{{Cite pmid|32543751 }}</ref> Community Susceptibility and Resiliency to COVID-19 Across the Rural-Urban Continuum in the United States #MMPMID32543751 Peters DJ J Rural Health 2020[Jun]; 36 (3 ): 446-456 PMID32543751 show ga PURPOSE: This study creates a COVID-19 susceptibility scale at the county level, describes its components, and then assesses the health and socioeconomic resiliency of susceptible places across the rural-urban continuum. METHODS: Factor analysis grouped 11 indicators into 7 distinct susceptibility factors for 3,079 counties in the conterminous United States. Unconditional mean differences are assessed using a multivariate general linear model. Data from 2018 are primarily taken from the US Census Bureau and CDC. RESULTS: About 33% of rural counties are highly susceptible to COVID-19, driven by older and health-compromised populations, and care facilities for the elderly. Major vulnerabilities in rural counties include fewer physicians, lack of mental health services, higher disability, and more uninsured. Poor Internet access limits telemedicine. Lack of social capital and social services may hinder local pandemic recovery. Meat processing facilities drive risk in micropolitan counties. Although metropolitan counties are less susceptible due to healthier and younger populations, about 6% are at risk due to community spread from dense populations. Metropolitan vulnerabilities include minorities at higher health and diabetes risk, language barriers, being a transportation hub that helps spread infection, and acute housing distress. CONCLUSIONS: There is an immediate need to know specific types of susceptibilities and vulnerabilities ahead of time to allow local and state health officials to plan and allocate resources accordingly. In rural areas it is essential to shelter-in-place vulnerable populations, whereas in large metropolitan areas general closure orders are needed to stop community spread. Pandemic response plans should address vulnerabilities. |Age Factors [MESH] |Betacoronavirus [MESH] |COVID-19 [MESH] |Coronavirus Infections/*epidemiology [MESH] |Health Services Accessibility/statistics & numerical data [MESH] |Health Status [MESH] |Humans [MESH] |Mental Health [MESH] |Pandemics [MESH] |Pneumonia, Viral/*epidemiology [MESH] |Rural Population/*statistics & numerical data [MESH] |SARS-CoV-2 [MESH] |Social Capital [MESH] |Social Work/statistics & numerical data [MESH] |Socioeconomic Factors [MESH] |United States/epidemiology [MESH]Community Susceptibility and Resiliency to COVID-19 Across the Rural-U(epmc).pdf DeepDyve Pubget Overpricing