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10.1126/sciadv.abf1374 http://scihub22266oqcxt.onion/10.1126/sciadv.abf1374 33536223!8128110!33536223     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Adv 2020 ; 7 (6): ä Nephropedia Template TP {{tp|p=33536223|t=2020. Vaccine optimization for COVID-19: Who to vaccinate first?|pdf=|usr=}}{{33536223}} gab.com Text Vaccine optimization for COVID-19: Who to vaccinate first JO: Sci Adv http://www.kidney.de/pget.php?&tw=1&pmid=33536223 #FOAvip Vaccines, when available, will likely become our best tool to control the COVID-19 pandemic. Even in the most optimistic scenarios, vaccine shortages will likely occur. Using an age-stratified mathematical model paired with optimization algorithms, we determined optimal vaccine allocation for four different metrics (deaths, symptomatic infections, and maximum non-ICU and ICU hospitalizations) under many scenarios. We find that a vaccine with effectiveness >/=50% would be enough to substantially mitigate the ongoing pandemic, provided that a high percentage of the population is optimally vaccinated. When minimizing deaths, we find that for low vaccine effectiveness, irrespective of vaccination coverage, it is optimal to allocate vaccine to high-risk (older) age groups first. In contrast, for higher vaccine effectiveness, there is a switch to allocate vaccine to high-transmission (younger) age groups first for high vaccination coverage. While there are other societal and ethical considerations, this work can provide an evidence-based rationale for vaccine prioritization. Twit Text FOAVip Vaccine optimization for COVID-19: Who to vaccinate first ????Sci Adv http://www.kidney.de/pget.php?&tw=1&pmid=33536223 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33536223 #FOAvip English Wikipedia <ref>{{Cite pmid|33536223}}</ref> Vaccine optimization for COVID-19: Who to vaccinate first? #MMPMID33536223 Matrajt L; Eaton J; Leung T; Brown ER Sci Adv 2020[Feb]; 7 (6): ä PMID33536223show ga Vaccines, when available, will likely become our best tool to control the COVID-19 pandemic. Even in the most optimistic scenarios, vaccine shortages will likely occur. Using an age-stratified mathematical model paired with optimization algorithms, we determined optimal vaccine allocation for four different metrics (deaths, symptomatic infections, and maximum non-ICU and ICU hospitalizations) under many scenarios. We find that a vaccine with effectiveness >/=50% would be enough to substantially mitigate the ongoing pandemic, provided that a high percentage of the population is optimally vaccinated. When minimizing deaths, we find that for low vaccine effectiveness, irrespective of vaccination coverage, it is optimal to allocate vaccine to high-risk (older) age groups first. In contrast, for higher vaccine effectiveness, there is a switch to allocate vaccine to high-transmission (younger) age groups first for high vaccination coverage. While there are other societal and ethical considerations, this work can provide an evidence-based rationale for vaccine prioritization. |Age Factors[MESH] |Algorithms[MESH] |COVID-19 Vaccines/*immunology[MESH] |COVID-19/epidemiology/pathology/*prevention & control/virology[MESH] |Epidemics[MESH] |Hospitalization/statistics & numerical data[MESH] |Humans[MESH] |Models, Biological[MESH] |Pandemics/*prevention & control[MESH] |Risk[MESH] |SARS-CoV-2/isolation & purification[MESH]Vaccine optimization for COVID-19: Who to vaccinate first?(epmc).pdf DeepDyve Pubget Overpricing