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10.5582/bst.2020.03133 http://scihub22266oqcxt.onion/10.5582/bst.2020.03133 32461511!ä!32461511 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biosci+Trends 2020 ; 14 (3): 174-181 Nephropedia Template TP {{tp|p=32461511|t=2020. Predicting intervention effect for COVID-19 in Japan: state space modeling approach |pdf=|usr=}}{{32461511}} gab.com Text Predicting intervention effect for COVID-19 in Japan: state space modeling approach JO: Biosci Trends http://www.kidney.de/pget.php?&tw=1&pmid=32461511 #FOAvip Japan has observed a surge in the number of confirmed cases of the coronavirus disease (COVID-19) that has caused a serious impact on the society especially after the declaration of the state of emergency on April 7, 2020. This study analyzes the real time data from March 1 to April 22, 2020 by adopting a sophisticated statistical modeling based on the state space model combined with the well-known susceptible-infected-recovered (SIR) model. The model estimation and forecasting are conducted using the Bayesian methodology. The present study provides the parameter estimates of the unknown parameters that critically determine the epidemic process derived from the SIR model and prediction of the future transition of the infectious proportion including the size and timing of the epidemic peak with the prediction intervals that naturally accounts for the uncertainty. Even though the epidemic appears to be settling down during this intervention period, the prediction results under various scenarios using the data up to May 18 reveal that the temporary reduction in the infection rate would still result in a delayed the epidemic peak unless the long-term reproduction number is controlled. Twit Text FOAVip Predicting intervention effect for COVID-19 in Japan: state space modeling approach ????Biosci Trends http://www.kidney.de/pget.php?&tw=1&pmid=32461511 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32461511 #FOAvip English Wikipedia <ref>{{Cite pmid|32461511}}</ref> Predicting intervention effect for COVID-19 in Japan: state space modeling approach #MMPMID32461511 Kobayashi G; Sugasawa S; Tamae H; Ozu T Biosci Trends 2020[Jul]; 14 (3): 174-181 PMID32461511show ga Japan has observed a surge in the number of confirmed cases of the coronavirus disease (COVID-19) that has caused a serious impact on the society especially after the declaration of the state of emergency on April 7, 2020. This study analyzes the real time data from March 1 to April 22, 2020 by adopting a sophisticated statistical modeling based on the state space model combined with the well-known susceptible-infected-recovered (SIR) model. The model estimation and forecasting are conducted using the Bayesian methodology. The present study provides the parameter estimates of the unknown parameters that critically determine the epidemic process derived from the SIR model and prediction of the future transition of the infectious proportion including the size and timing of the epidemic peak with the prediction intervals that naturally accounts for the uncertainty. Even though the epidemic appears to be settling down during this intervention period, the prediction results under various scenarios using the data up to May 18 reveal that the temporary reduction in the infection rate would still result in a delayed the epidemic peak unless the long-term reproduction number is controlled. |*Models, Statistical[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology/prevention & control[MESH] |Humans[MESH] |Japan/epidemiology[MESH] |Pandemics/prevention & control[MESH] |Pneumonia, Viral/*epidemiology/prevention & control[MESH]Predicting intervention effect for COVID-19 in Japan: state space mode(epmc).pdf DeepDyve Pubget Overpricing