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10.1007/s11684-020-0787-4 http://scihub22266oqcxt.onion/10.1007/s11684-020-0787-4 32468343!7255828!32468343     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Front+Med 2020 ; 14 (5): 613-622 Nephropedia Template TP {{tp|p=32468343|t=2020. Estimation of reproduction numbers of COVID-19 in typical countries and epidemic trends under different prevention and control scenarios |pdf=|usr=}}{{32468343}} gab.com Text Estimation of reproduction numbers of COVID-19 in typical countries and epidemic trends under different prevention and control scenarios JO: Front Med http://www.kidney.de/pget.php?&tw=1&pmid=32468343 #FOAvip The coronavirus disease 2019 (COVID-19) has become a life-threatening pandemic. The epidemic trends in different countries vary considerably due to different policy-making and resources mobilization. We calculated basic reproduction number (R(0)) and the time-varying estimate of the effective reproductive number (R(t)) of COVID-19 by using the maximum likelihood method and the sequential Bayesian method, respectively. European and North American countries possessed higher R(0) and unsteady R(t) fluctuations, whereas some heavily affected Asian countries showed relatively low R(0) and declining R(t) now. The numbers of patients in Africa and Latin America are still low, but the potential risk of huge outbreaks cannot be ignored. Three scenarios were then simulated, generating distinct outcomes by using SEIR (susceptible, exposed, infectious, and removed) model. First, evidence-based prompt responses yield lower transmission rate followed by decreasing R(t). Second, implementation of effective control policies at a relatively late stage, in spite of huge casualties at early phase, can still achieve containment and mitigation. Third, wisely taking advantage of the time-window for developing countries in Africa and Latin America to adopt adequate measures can save more people's life. Our mathematical modeling provides evidence for international communities to develop sound design of containment and mitigation policies for COVID-19. Twit Text FOAVip Estimation of reproduction numbers of COVID-19 in typical countries and epidemic trends under different prevention and control scenarios ????Front Med http://www.kidney.de/pget.php?&tw=1&pmid=32468343 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32468343 #FOAvip English Wikipedia <ref>{{Cite pmid|32468343}}</ref> Estimation of reproduction numbers of COVID-19 in typical countries and epidemic trends under different prevention and control scenarios #MMPMID32468343 Xu C; Dong Y; Yu X; Wang H; Tsamlag L; Zhang S; Chang R; Wang Z; Yu Y; Long R; Wang Y; Xu G; Shen T; Wang S; Zhang X; Wang H; Cai Y Front Med 2020[Oct]; 14 (5): 613-622 PMID32468343show ga The coronavirus disease 2019 (COVID-19) has become a life-threatening pandemic. The epidemic trends in different countries vary considerably due to different policy-making and resources mobilization. We calculated basic reproduction number (R(0)) and the time-varying estimate of the effective reproductive number (R(t)) of COVID-19 by using the maximum likelihood method and the sequential Bayesian method, respectively. European and North American countries possessed higher R(0) and unsteady R(t) fluctuations, whereas some heavily affected Asian countries showed relatively low R(0) and declining R(t) now. The numbers of patients in Africa and Latin America are still low, but the potential risk of huge outbreaks cannot be ignored. Three scenarios were then simulated, generating distinct outcomes by using SEIR (susceptible, exposed, infectious, and removed) model. First, evidence-based prompt responses yield lower transmission rate followed by decreasing R(t). Second, implementation of effective control policies at a relatively late stage, in spite of huge casualties at early phase, can still achieve containment and mitigation. Third, wisely taking advantage of the time-window for developing countries in Africa and Latin America to adopt adequate measures can save more people's life. Our mathematical modeling provides evidence for international communities to develop sound design of containment and mitigation policies for COVID-19. |*Bayes Theorem[MESH] |*Communicable Disease Control/methods/statistics & numerical data[MESH] |*Coronavirus Infections/epidemiology/prevention & control[MESH] |*Disease Transmission, Infectious/prevention & control/statistics & numerical data[MESH] |*Likelihood Functions[MESH] |*Pandemics/prevention & control/statistics & numerical data[MESH] |*Pneumonia, Viral/epidemiology/prevention & control[MESH] |Basic Reproduction Number/statistics & numerical data[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Forecasting/methods[MESH] |Global Health/statistics & numerical data/trends[MESH] |Humans[MESH] |Models, Theoretical[MESH] |Risk Adjustment[MESH]Estimation of reproduction numbers of COVID-19 in typical countries an(epmc).pdf DeepDyve Pubget Overpricing