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10.1016/j.physd.2020.132649 http://scihub22266oqcxt.onion/10.1016/j.physd.2020.132649 32834250!7365130!32834250     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32834250&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 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       Physica+D 2020 ; 412 (ä): 132649 Nephropedia Template TP {{tp|p=32834250|t=2020. On the emergence of a power law in the distribution of COVID-19 cases |pdf=|usr=}}{{32834250}} gab.com Text On the emergence of a power law in the distribution of COVID-19 cases JO: Physica D http://www.kidney.de/pget.php?&tw=1&pmid=32834250 #FOAvip The first confirmed case of Coronavirus Disease 2019 (COVID-19) in the US was reported on January 21, 2020. By the end of March, 2020, there were more than 180,000 confirmed cases in the US, distributed across more than 2000 counties. We find that the right tail of this distribution exhibits a power law, with Pareto exponent close to one. We investigate whether a simple model of the growth of COVID-19 cases involving Gibrat's law can explain the emergence of this power law. The model is calibrated to match (i) the growth rates of confirmed cases, and (ii) the varying lengths of time during which COVID-19 had been present within each county. Thus calibrated, the model generates a power law with Pareto exponent nearly exactly equal to the exponent estimated directly from the distribution of confirmed cases across counties at the end of March. Twit Text FOAVip On the emergence of a power law in the distribution of COVID-19 cases ????Physica D http://www.kidney.de/pget.php?&tw=1&pmid=32834250 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32834250 #FOAvip English Wikipedia <ref>{{Cite pmid|32834250}}</ref> On the emergence of a power law in the distribution of COVID-19 cases #MMPMID32834250 Beare BK; Toda AA Physica D 2020[Nov]; 412 (ä): 132649 PMID32834250show ga The first confirmed case of Coronavirus Disease 2019 (COVID-19) in the US was reported on January 21, 2020. By the end of March, 2020, there were more than 180,000 confirmed cases in the US, distributed across more than 2000 counties. We find that the right tail of this distribution exhibits a power law, with Pareto exponent close to one. We investigate whether a simple model of the growth of COVID-19 cases involving Gibrat's law can explain the emergence of this power law. The model is calibrated to match (i) the growth rates of confirmed cases, and (ii) the varying lengths of time during which COVID-19 had been present within each county. Thus calibrated, the model generates a power law with Pareto exponent nearly exactly equal to the exponent estimated directly from the distribution of confirmed cases across counties at the end of March. äOn the emergence of a power law in the distribution of COVID-19 cases (epmc).pdf DeepDyve Pubget Overpricing