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10.1016/j.ijid.2020.06.055 http://scihub22266oqcxt.onion/10.1016/j.ijid.2020.06.055 32569839!7305719!32569839     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Infect+Dis 2020 ; 97 (ä): 360-364 Nephropedia Template TP {{tp|p=32569839|t=2020. Estimating a breakpoint in the pattern of spread of COVID-19 in South Korea |pdf=|usr=}}{{32569839}} gab.com Text Estimating a breakpoint in the pattern of spread of COVID-19 in South Korea JO: Int J Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32569839 #FOAvip OBJECTIVES: Amid the global coronavirus disease 2019 (COVID-19) crisis, South Korea has been lauded for successfully preventing the spread of this infectious disease, which may be due to the aggressive implementation of preventive policies. This study was performed to evaluate the pattern of spread of COVID-19 in South Korea considering the potential impact of policy interventions on transmission rates. METHODS: A SIR (susceptible-infected-removed) model with a breakpoint that allows a change in transmission rate at an unknown point was established. Estimated trajectories of COVID-19 from SIR models with and without a breakpoint were compared. RESULTS: The proposed model with a break fitted the actual series of infection cases much better than the classic model. The estimated breakpoint was March 7, 2020 and the transmission rate dropped by 0.23 after the breakpoint. A counterfactual study based on our estimate indicated that the number of infected could have reached 2 500 000 compared to the peak of 8000 in the observed series. CONCLUSIONS: It is critical to consider a change in the transmission rate to evaluate the trajectory of spread of COVID-19 in South Korea. Our estimation and counterfactual experiments indicate that public health interventions may play a role in determining the pattern of spread of infectious diseases. Twit Text FOAVip Estimating a breakpoint in the pattern of spread of COVID-19 in South Korea ????Int J Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32569839 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32569839 #FOAvip English Wikipedia <ref>{{Cite pmid|32569839}}</ref> Estimating a breakpoint in the pattern of spread of COVID-19 in South Korea #MMPMID32569839 Kim YJ; Seo MH; Yeom HE Int J Infect Dis 2020[Aug]; 97 (ä): 360-364 PMID32569839show ga OBJECTIVES: Amid the global coronavirus disease 2019 (COVID-19) crisis, South Korea has been lauded for successfully preventing the spread of this infectious disease, which may be due to the aggressive implementation of preventive policies. This study was performed to evaluate the pattern of spread of COVID-19 in South Korea considering the potential impact of policy interventions on transmission rates. METHODS: A SIR (susceptible-infected-removed) model with a breakpoint that allows a change in transmission rate at an unknown point was established. Estimated trajectories of COVID-19 from SIR models with and without a breakpoint were compared. RESULTS: The proposed model with a break fitted the actual series of infection cases much better than the classic model. The estimated breakpoint was March 7, 2020 and the transmission rate dropped by 0.23 after the breakpoint. A counterfactual study based on our estimate indicated that the number of infected could have reached 2 500 000 compared to the peak of 8000 in the observed series. CONCLUSIONS: It is critical to consider a change in the transmission rate to evaluate the trajectory of spread of COVID-19 in South Korea. Our estimation and counterfactual experiments indicate that public health interventions may play a role in determining the pattern of spread of infectious diseases. |Betacoronavirus[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology/*transmission[MESH] |Humans[MESH] |Models, Theoretical[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology/*transmission[MESH] |Public Health[MESH] |Republic of Korea/epidemiology[MESH]Estimating a breakpoint in the pattern of spread of COVID-19 in South (epmc).pdf DeepDyve Pubget Overpricing