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10.1016/j.chaos.2020.110157 http://scihub22266oqcxt.onion/10.1016/j.chaos.2020.110157 32834645!7386477!32834645     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       Chaos+Solitons+Fractals 2020 ; 140 (ä): 110157 Nephropedia Template TP {{tp|p=32834645|t=2020. A minimal model of hospital patients dynamics in COVID-19 |pdf=|usr=}}{{32834645}} gab.com Text A minimal model of hospital patients dynamics in COVID-19 JO: Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32834645 #FOAvip Italy has been one of the countries hardest hit by the coronavirus disease (COVID-19) pandemic. While the overall policy in response to the epidemic was to a large degree centralised, the regional basis of the healthcare system represented an important factor affecting the natural dynamics of the disease induced geographic specificities. Here, we characterise the region-specific modulation of COVID dynamics with a reduced exponential model leveraging available data on sub-intensive and intensive care unit patients made available by all regional councils from the very onset of the disease. This simple model provides a rather good fit of regional patient dynamics, particularly for regions where the affected population was large, highlighting important region-specific patterns of epidemic dynamics. Twit Text FOAVip A minimal model of hospital patients dynamics in COVID-19 ????Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32834645 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32834645 #FOAvip English Wikipedia <ref>{{Cite pmid|32834645}}</ref> A minimal model of hospital patients dynamics in COVID-19 #MMPMID32834645 Papo D; Righetti M; Fadiga L; Biscarini F; Zanin M Chaos Solitons Fractals 2020[Nov]; 140 (ä): 110157 PMID32834645show ga Italy has been one of the countries hardest hit by the coronavirus disease (COVID-19) pandemic. While the overall policy in response to the epidemic was to a large degree centralised, the regional basis of the healthcare system represented an important factor affecting the natural dynamics of the disease induced geographic specificities. Here, we characterise the region-specific modulation of COVID dynamics with a reduced exponential model leveraging available data on sub-intensive and intensive care unit patients made available by all regional councils from the very onset of the disease. This simple model provides a rather good fit of regional patient dynamics, particularly for regions where the affected population was large, highlighting important region-specific patterns of epidemic dynamics. äA minimal model of hospital patients dynamics in COVID-19 (epmc).pdf DeepDyve Pubget Overpricing