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http://scihub22266oqcxt.onion/ 32963218!ä!32963218 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Rev+Esp+Salud+Publica 2020 ; 94 (ä): ä Nephropedia Template TP {{tp|p=32963218|t=2020. Aproximacion matematica del modelo epidemiologico SIR para la comprension de las medidas de contencion contra la COVID-19 |pdf=|usr=}}{{32963218}} gab.com Text Aproximacion matematica del modelo epidemiologico SIR para la comprension de las medidas de contencion contra la COVID-19 JO: Rev Esp Salud Publica http://www.kidney.de/pget.php?&tw=1&pmid=32963218 #FOAvip In December 2019, an acute respiratory disease outbreak from zoonotic origin was detected in the city of Wuhan, China. The outbreak's infectious agent was a type of coronavirus never seen. Thenceforth, the Covid-19 disease has rapidly spread to more than 200 countries around the world. To minimize the devastating effects of the virus, the States have adopted epidemiological measures of various kinds that involved enormous economic expenses and the massive use of the media to explain the measures to the entire population. For the prediction and mitigation of infectious events, various epidemiological models, such as SIR, SEIR, MSIR and MSEIR, are used. Among them, the most widely used is the SIR model, which is based on the analysis of the transition of individuals susceptible to infection (S) to the state of infected individuals that infect (I) and, finally, to that of recovered (cured or deceased) (R), by using differential equations. The objective of this article was the mathematical development of the SIR model and its application to predict the course of the Covid-19 pandemic in the city of Santa Marta (Colombia), in order to understand the reason behind several of the measures of containment adopted by the States of the world in the fight against the pandemic. Twit Text FOAVip Aproximacion matematica del modelo epidemiologico SIR para la comprension de las medidas de contencion contra la COVID-19 ????Rev Esp Salud Publica http://www.kidney.de/pget.php?&tw=1&pmid=32963218 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32963218 #FOAvip English Wikipedia <ref>{{Cite pmid|32963218}}</ref> Aproximacion matematica del modelo epidemiologico SIR para la comprension de las medidas de contencion contra la COVID-19 #MMPMID32963218 Wilches Visbal JH; Castillo Pedraza MC Rev Esp Salud Publica 2020[Sep]; 94 (ä): ä PMID32963218show ga In December 2019, an acute respiratory disease outbreak from zoonotic origin was detected in the city of Wuhan, China. The outbreak's infectious agent was a type of coronavirus never seen. Thenceforth, the Covid-19 disease has rapidly spread to more than 200 countries around the world. To minimize the devastating effects of the virus, the States have adopted epidemiological measures of various kinds that involved enormous economic expenses and the massive use of the media to explain the measures to the entire population. For the prediction and mitigation of infectious events, various epidemiological models, such as SIR, SEIR, MSIR and MSEIR, are used. Among them, the most widely used is the SIR model, which is based on the analysis of the transition of individuals susceptible to infection (S) to the state of infected individuals that infect (I) and, finally, to that of recovered (cured or deceased) (R), by using differential equations. The objective of this article was the mathematical development of the SIR model and its application to predict the course of the Covid-19 pandemic in the city of Santa Marta (Colombia), in order to understand the reason behind several of the measures of containment adopted by the States of the world in the fight against the pandemic. |*Communicable Disease Control[MESH] |*Models, Statistical[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Cities[MESH] |Colombia/epidemiology[MESH] |Coronavirus Infections/*epidemiology/prevention & control[MESH] |Disease Outbreaks[MESH] |Humans[MESH] |Pandemics/prevention & control[MESH] |Pneumonia, Viral/*epidemiology/prevention & control[MESH]Aproximacion matematica del modelo epidemiologico SIR para la comprens(epmc).pdf DeepDyve Pubget Overpricing