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10.1016/j.chaos.2020.109999 http://scihub22266oqcxt.onion/10.1016/j.chaos.2020.109999 C7305517!7305517!32834581     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       Chaos+Solitons+Fractals 2020 ; 138 (ä): 109999 Nephropedia Template TP {{tp|p=32834581|t=2020. Quantifying the effects of quarantine using an IBM SEIR model on scalefree networks |pdf=|usr=}}{{32834581}} gab.com Text Quantifying the effects of quarantine using an IBM SEIR model on scalefree networks JO: Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32834581 #FOAvip The COVID-19 pandemic led several countries to resort to social distancing, the only known way to slow down the spread of the virus and keep the health system under control. Here we use an individual based model (IBM) to study how the duration, start date and intensity of quarantine affect the height and position of the peak of the infection curve. We show that stochastic effects, inherent to the model dynamics, lead to variable outcomes for the same set of parameters, making it crucial to compute the probability of each result. To simplify the analysis we divide the outcomes in only two categories, that we call best and worst scenarios. Although long and intense quarantine is the best way to end the epidemic, it is very hard to implement in practice. Here we show that relatively short and intense quarantine periods can also be very effective in flattening the infection curve and even killing the virus, but the likelihood of such outcomes are low. Long quarantines of relatively low intensity, on the other hand, can delay the infection peak and reduce its size considerably with more than 50% probability, being a more effective policy than complete lockdown for short periods. Twit Text FOAVip Quantifying the effects of quarantine using an IBM SEIR model on scalefree networks ????Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32834581 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32834581 #FOAvip English Wikipedia <ref>{{Cite pmid|32834581}}</ref> Quantifying the effects of quarantine using an IBM SEIR model on scalefree networks #MMPMID32834581 Marquioni VM; de Aguiar MA Chaos Solitons Fractals 2020[Sep]; 138 (ä): 109999 PMID32834581show ga The COVID-19 pandemic led several countries to resort to social distancing, the only known way to slow down the spread of the virus and keep the health system under control. Here we use an individual based model (IBM) to study how the duration, start date and intensity of quarantine affect the height and position of the peak of the infection curve. We show that stochastic effects, inherent to the model dynamics, lead to variable outcomes for the same set of parameters, making it crucial to compute the probability of each result. To simplify the analysis we divide the outcomes in only two categories, that we call best and worst scenarios. Although long and intense quarantine is the best way to end the epidemic, it is very hard to implement in practice. Here we show that relatively short and intense quarantine periods can also be very effective in flattening the infection curve and even killing the virus, but the likelihood of such outcomes are low. Long quarantines of relatively low intensity, on the other hand, can delay the infection peak and reduce its size considerably with more than 50% probability, being a more effective policy than complete lockdown for short periods. äQuantifying the effects of quarantine using an IBM SEIR model on scale(epmc).pdf DeepDyve Pubget Overpricing