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10.1111/poms.12788 http://scihub22266oqcxt.onion/10.1111/poms.12788 32327917!7168135!32327917     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32327917&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       Prod+Oper+Manag 2018 ; 27 (1): 143-159 Nephropedia Template TP {{tp|p=32327917|t=2018. Dose-Optimal Vaccine Allocation over Multiple Populations |pdf=|usr=}}{{32327917}} gab.com Text Dose-Optimal Vaccine Allocation over Multiple Populations JO: Prod Oper Manag http://www.kidney.de/pget.php?&tw=1&pmid=32327917 #FOAvip Vaccination is an effective way to prevent an epidemic. It results in immunity for the vaccinated individuals, but it also reduces the infection pressure for unvaccinated people. Thus people may actually escape infection without being vaccinated: the so-called "herd effect." We analytically study the relation between the herd effect and the vaccination fraction for the seminal SIR compartmental model, which consists of a set of differential equations describing the time course of an epidemic. We prove that the herd effect is in general convex-concave in the vaccination fraction and give precise conditions on the epidemic for the convex part to arise. We derive the significant consequences of these structural insights for allocating a limited vaccine stockpile to multiple non-interacting populations. We identify for each population a unique vaccination fraction that is most efficient per dose of vaccine: our dose-optimal coverage. We characterize the solution of the vaccine allocation problem and we show the crucial importance of the dose-optimal coverage. A single dose of vaccine may be a drop in the ocean, but multiple doses together can save a population. To benefit from this, policy makers should select a subset of populations to which the vaccines are allocated. Focusing on a limited number of populations can make a significant difference, whereas allocating equally to all populations would be substantially less effective. Twit Text FOAVip Dose-Optimal Vaccine Allocation over Multiple Populations ????Prod Oper Manag http://www.kidney.de/pget.php?&tw=1&pmid=32327917 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32327917 #FOAvip English Wikipedia <ref>{{Cite pmid|32327917}}</ref> Dose-Optimal Vaccine Allocation over Multiple Populations #MMPMID32327917 Duijzer LE; van Jaarsveld WL; Wallinga J; Dekker R Prod Oper Manag 2018[Jan]; 27 (1): 143-159 PMID32327917show ga Vaccination is an effective way to prevent an epidemic. It results in immunity for the vaccinated individuals, but it also reduces the infection pressure for unvaccinated people. Thus people may actually escape infection without being vaccinated: the so-called "herd effect." We analytically study the relation between the herd effect and the vaccination fraction for the seminal SIR compartmental model, which consists of a set of differential equations describing the time course of an epidemic. We prove that the herd effect is in general convex-concave in the vaccination fraction and give precise conditions on the epidemic for the convex part to arise. We derive the significant consequences of these structural insights for allocating a limited vaccine stockpile to multiple non-interacting populations. We identify for each population a unique vaccination fraction that is most efficient per dose of vaccine: our dose-optimal coverage. We characterize the solution of the vaccine allocation problem and we show the crucial importance of the dose-optimal coverage. A single dose of vaccine may be a drop in the ocean, but multiple doses together can save a population. To benefit from this, policy makers should select a subset of populations to which the vaccines are allocated. Focusing on a limited number of populations can make a significant difference, whereas allocating equally to all populations would be substantially less effective. ?Dose-Optimal Vaccine Allocation over Multiple Populations (epmc).pdf DeepDyve Pubget Overpricing