Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1038/s41598-021-85496-9 http://scihub22266oqcxt.onion/10.1038/s41598-021-85496-9 33753777!7985510!33753777     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+Rep 2021 ; 11 (1): 6525 Nephropedia Template TP {{tp|p=33753777|t=2021. Data-driven optimized control of the COVID-19 epidemics |pdf=|usr=}}{{33753777}} gab.com Text Data-driven optimized control of the COVID-19 epidemics JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33753777 #FOAvip Optimizing the impact on the economy of control strategies aiming at containing the spread of COVID-19 is a critical challenge. We use daily new case counts of COVID-19 patients reported by local health administrations from different Metropolitan Statistical Areas (MSAs) within the US to parametrize a model that well describes the propagation of the disease in each area. We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time. We find that with the exception of the initial time and of the final time, the optimal control input is well approximated by a constant, specific to each area, which contrasts with the implemented system of reopening 'in phases'. For all the areas considered, this optimal level corresponds to stricter social distancing than the level estimated from data. Proper selection of the time period for application of the control action optimally is important: depending on the particular MSA this period should be either short or long or intermediate. We also consider the case that the transmissibility increases in time (due e.g. to increasingly colder weather), for which we find that the optimal control solution yields progressively stricter measures of social distancing. We finally compute the optimal control solution for a model modified to incorporate the effects of vaccinations on the population and we see that depending on a number of factors, social distancing measures could be optimally reduced during the period over which vaccines are administered to the population. Twit Text FOAVip Data-driven optimized control of the COVID-19 epidemics ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33753777 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33753777 #FOAvip English Wikipedia <ref>{{Cite pmid|33753777}}</ref> Data-driven optimized control of the COVID-19 epidemics #MMPMID33753777 Shirin A; Lin YT; Sorrentino F Sci Rep 2021[Mar]; 11 (1): 6525 PMID33753777show ga Optimizing the impact on the economy of control strategies aiming at containing the spread of COVID-19 is a critical challenge. We use daily new case counts of COVID-19 patients reported by local health administrations from different Metropolitan Statistical Areas (MSAs) within the US to parametrize a model that well describes the propagation of the disease in each area. We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time. We find that with the exception of the initial time and of the final time, the optimal control input is well approximated by a constant, specific to each area, which contrasts with the implemented system of reopening 'in phases'. For all the areas considered, this optimal level corresponds to stricter social distancing than the level estimated from data. Proper selection of the time period for application of the control action optimally is important: depending on the particular MSA this period should be either short or long or intermediate. We also consider the case that the transmissibility increases in time (due e.g. to increasingly colder weather), for which we find that the optimal control solution yields progressively stricter measures of social distancing. We finally compute the optimal control solution for a model modified to incorporate the effects of vaccinations on the population and we see that depending on a number of factors, social distancing measures could be optimally reduced during the period over which vaccines are administered to the population. |*Models, Theoretical[MESH] |COVID-19/epidemiology/*prevention & control/transmission/virology[MESH] |Epidemics[MESH] |Humans[MESH] |Physical Distancing[MESH] |Quarantine[MESH] |SARS-CoV-2/isolation & purification[MESH]Data-driven optimized control of the COVID-19 epidemics (epmc).pdf DeepDyve Pubget Overpricing