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10.1016/j.chaos.2020.109940 http://scihub22266oqcxt.onion/10.1016/j.chaos.2020.109940 32518474!7274126!32518474     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32518474&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 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Chaos+Solitons+Fractals 2020 ; 138 (ä): 109940 Nephropedia Template TP {{tp|p=32518474|t=2020. How to reduce epidemic peaks keeping under control the time-span of the epidemic |pdf=|usr=}}{{32518474}} gab.com Text How to reduce epidemic peaks keeping under control the time-span of the epidemic JO: Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32518474 #FOAvip One of the main challenges of the measures against the COVID-19 epidemic is to reduce the amplitude of the epidemic peak without increasing without control its timescale. We investigate this problem using the SIR model for the epidemic dynamics, for which reduction of the epidemic peak I(P) can be achieved only at the price of increasing the time t(P) of its occurrence and its entire time-span t(E) . By means of a time reparametrization we linearize the equations for the SIR dynamics. This allows us to solve exactly the dynamics in the time domain and to derive the scaling behaviour of the size, the timescale and the speed of the epidemics, by reducing the infection rate alpha and by increasing the removal rate beta by a factor of lambda. We show that for a given value of the size (I(P) , the total, I(E) and average I;P number of infected), its occurrence time t(P) and entire time-span t(E) can be reduced by a factor 1/lambda if the reduction of I is achieved by increasing the removal rate instead of reducing the infection rate. Thus, epidemic containment measures based on tracing, early detection followed by prompt isolation of infected individuals are more efficient than those based on social distancing. We apply our results to the COVID-19 epidemic in Northern Italy. We show that the peak time t(P) and the entire time span t(E) could have been reduced by a factor 0.9 </= 1/lambda </= 0.34 with containment measures focused on increasing beta instead of reducing alpha. Twit Text FOAVip How to reduce epidemic peaks keeping under control the time-span of the epidemic ????Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32518474 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32518474 #FOAvip English Wikipedia <ref>{{Cite pmid|32518474}}</ref> How to reduce epidemic peaks keeping under control the time-span of the epidemic #MMPMID32518474 Cadoni M Chaos Solitons Fractals 2020[Sep]; 138 (ä): 109940 PMID32518474show ga One of the main challenges of the measures against the COVID-19 epidemic is to reduce the amplitude of the epidemic peak without increasing without control its timescale. We investigate this problem using the SIR model for the epidemic dynamics, for which reduction of the epidemic peak I(P) can be achieved only at the price of increasing the time t(P) of its occurrence and its entire time-span t(E) . By means of a time reparametrization we linearize the equations for the SIR dynamics. This allows us to solve exactly the dynamics in the time domain and to derive the scaling behaviour of the size, the timescale and the speed of the epidemics, by reducing the infection rate alpha and by increasing the removal rate beta by a factor of lambda. We show that for a given value of the size (I(P) , the total, I(E) and average I;P number of infected), its occurrence time t(P) and entire time-span t(E) can be reduced by a factor 1/lambda if the reduction of I is achieved by increasing the removal rate instead of reducing the infection rate. Thus, epidemic containment measures based on tracing, early detection followed by prompt isolation of infected individuals are more efficient than those based on social distancing. We apply our results to the COVID-19 epidemic in Northern Italy. We show that the peak time t(P) and the entire time span t(E) could have been reduced by a factor 0.9 äHow to reduce epidemic peaks keeping under control the time-span of th(epmc).pdf DeepDyve Pubget Overpricing