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10.1016/j.ejor.2021.07.049 http://scihub22266oqcxt.onion/10.1016/j.ejor.2021.07.049 34413569!8364218!34413569     free     free     free       Eur+J+Oper+Res 2023 ; 304 (1): 57-68 Nephropedia Template TP {{tp|p=34413569|t=2023. Modeling local coronavirus outbreaks |pdf=|usr=}}{{34413569}} gab.com Text Modeling local coronavirus outbreaks JO: Eur J Oper Res http://www.kidney.de/pget.php?&tw=1&pmid=34413569 #FOAvip This article presents an overview of methods developed for the modeling and control of local coronavirus outbreaks. The article reviews early transmission dynamics featuring exponential growth in infections, and links this to a renewal epidemic model where the current incidence of infection depends upon the expected value of incidence randomly lagged into the past. This leads directly to simple formulas for the fraction of the population infected in an unmitigated outbreak, and reveals herd immunity as the solution to an optimization problem. The model also leads to direct and easy-to-understand formulas for aligning observable epidemic indicators such as cases, hospitalizations and deaths with the unobservable incidence of infection, and as a byproduct leads to a simple first-order approach for estimating the effective reproduction number Rt . The model also leads naturally to direct assessments of the effectiveness of isolation in preventing the spread of infection. This is illustrated with application to repeat asymptomatic screening programs of the sort utilized by universities, sports teams and businesses to prevent the spread of infection. Twit Text FOAVip Modeling local coronavirus outbreaks ????Eur J Oper Res http://www.kidney.de/pget.php?&tw=1&pmid=34413569 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34413569 #FOAvip English Wikipedia <ref>{{Cite pmid|34413569}}</ref> Modeling local coronavirus outbreaks #MMPMID34413569 Chang JT; Kaplan EH Eur J Oper Res 2023[Jan]; 304 (1): 57-68 PMID34413569show ga This article presents an overview of methods developed for the modeling and control of local coronavirus outbreaks. The article reviews early transmission dynamics featuring exponential growth in infections, and links this to a renewal epidemic model where the current incidence of infection depends upon the expected value of incidence randomly lagged into the past. This leads directly to simple formulas for the fraction of the population infected in an unmitigated outbreak, and reveals herd immunity as the solution to an optimization problem. The model also leads to direct and easy-to-understand formulas for aligning observable epidemic indicators such as cases, hospitalizations and deaths with the unobservable incidence of infection, and as a byproduct leads to a simple first-order approach for estimating the effective reproduction number Rt . The model also leads naturally to direct assessments of the effectiveness of isolation in preventing the spread of infection. This is illustrated with application to repeat asymptomatic screening programs of the sort utilized by universities, sports teams and businesses to prevent the spread of infection. äModeling local coronavirus outbreaks (epmc).pdf DeepDyve Pubget Overpricing