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10.1016/j.healthplace.2020.102404

http://scihub22266oqcxt.onion/10.1016/j.healthplace.2020.102404
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suck abstract from ncbi


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pmid32736312      Health+Place 2020 ; 64 (ä): 102404
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  • Spatiotemporal transmission dynamics of the COVID-19 pandemic and its impact on critical healthcare capacity #MMPMID32736312
  • Cuadros DF; Xiao Y; Mukandavire Z; Correa-Agudelo E; Hernandez A; Kim H; MacKinnon NJ
  • Health Place 2020[Jul]; 64 (ä): 102404 PMID32736312show ga
  • The role of geospatial disparities in the dynamics of the COVID-19 pandemic is poorly understood. We developed a spatially-explicit mathematical model to simulate transmission dynamics of COVID-19 disease infection in relation with the uneven distribution of the healthcare capacity in Ohio, U.S. The results showed substantial spatial variation in the spread of the disease, with localized areas showing marked differences in disease attack rates. Higher COVID-19 attack rates experienced in some highly connected and urbanized areas (274 cases per 100,000 people) could substantially impact the critical health care response of these areas regardless of their potentially high healthcare capacity compared to more rural and less connected counterparts (85 cases per 100,000). Accounting for the spatially uneven disease diffusion linked to the geographical distribution of the critical care resources is essential in designing effective prevention and control programmes aimed at reducing the impact of COVID-19 pandemic.
  • |*Coronavirus Infections/epidemiology/transmission[MESH]
  • |*Health Services Accessibility[MESH]
  • |*Hospital Bed Capacity[MESH]
  • |*Intensive Care Units[MESH]
  • |*Pneumonia, Viral/epidemiology/transmission[MESH]
  • |*Spatial Analysis[MESH]
  • |Betacoronavirus/isolation & purification[MESH]
  • |COVID-19[MESH]
  • |Humans[MESH]
  • |Incidence[MESH]
  • |Models, Theoretical[MESH]
  • |Ohio/epidemiology[MESH]
  • |Pandemics/*statistics & numerical data[MESH]
  • |Rural Population[MESH]


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