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10.4178/epih.e2020042 http://scihub22266oqcxt.onion/10.4178/epih.e2020042 32580535!7644934!32580535     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Epidemiol+Health 2020 ; 42 (ä): e2020042 Nephropedia Template TP {{tp|p=32580535|t=2020. Individual-based simulation model for COVID-19 transmission in Daegu, Korea |pdf=|usr=}}{{32580535}} gab.com Text Individual-based simulation model for COVID-19 transmission in Daegu, Korea JO: Epidemiol Health http://www.kidney.de/pget.php?&tw=1&pmid=32580535 #FOAvip OBJECTIVES: The aims of this study were to obtain insights into the current coronavirus disease 2019 (COVID-19) epidemic in the city of Daegu, which accounted for 6,482 of the 9,241 confirmed cases in Korea as of March 26, 2020, to predict the future spread, and to analyze the impact of school opening. METHODS: Using an individual-based model, we simulated the spread of COVID-19 in Daegu. An individual can be infected through close contact with infected people in a household, at work/school, and at religious and social gatherings. We created a synthetic population from census sample data. Then, 9,000 people were randomly selected from the entire population of Daegu and set as members of the Shincheonji Church. We did not take into account population movements to and from other regions in Korea. RESULTS: Using the individual-based model, the cumulative confirmed cases in Daegu through March 26, 2020, were reproduced, and it was confirmed that the hotspot, i.e., the Shincheonji Church had a different probability of infection than non-hotspot, i.e., the Daegu community. For 3 scenarios (I: school closing, II: school opening after April 6, III: school opening after April 6 and the mean period from symptom onset to hospitalization increasing to 4.3 days), we predicted future changes in the pattern of COVID-19 spread in Daegu. CONCLUSIONS: Compared to scenario I, it was found that in scenario III, the cumulative number of patients would increase by 107 and the date of occurrence of the last patient would be delayed by 92 days. Twit Text FOAVip Individual-based simulation model for COVID-19 transmission in Daegu, Korea ????Epidemiol Health http://www.kidney.de/pget.php?&tw=1&pmid=32580535 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32580535 #FOAvip English Wikipedia <ref>{{Cite pmid|32580535}}</ref> Individual-based simulation model for COVID-19 transmission in Daegu, Korea #MMPMID32580535 Son WS Epidemiol Health 2020[]; 42 (ä): e2020042 PMID32580535show ga OBJECTIVES: The aims of this study were to obtain insights into the current coronavirus disease 2019 (COVID-19) epidemic in the city of Daegu, which accounted for 6,482 of the 9,241 confirmed cases in Korea as of March 26, 2020, to predict the future spread, and to analyze the impact of school opening. METHODS: Using an individual-based model, we simulated the spread of COVID-19 in Daegu. An individual can be infected through close contact with infected people in a household, at work/school, and at religious and social gatherings. We created a synthetic population from census sample data. Then, 9,000 people were randomly selected from the entire population of Daegu and set as members of the Shincheonji Church. We did not take into account population movements to and from other regions in Korea. RESULTS: Using the individual-based model, the cumulative confirmed cases in Daegu through March 26, 2020, were reproduced, and it was confirmed that the hotspot, i.e., the Shincheonji Church had a different probability of infection than non-hotspot, i.e., the Daegu community. For 3 scenarios (I: school closing, II: school opening after April 6, III: school opening after April 6 and the mean period from symptom onset to hospitalization increasing to 4.3 days), we predicted future changes in the pattern of COVID-19 spread in Daegu. CONCLUSIONS: Compared to scenario I, it was found that in scenario III, the cumulative number of patients would increase by 107 and the date of occurrence of the last patient would be delayed by 92 days. |*Epidemics[MESH] |Adolescent[MESH] |Adult[MESH] |COVID-19[MESH] |Cities/epidemiology[MESH] |Computer Simulation[MESH] |Coronavirus Infections/*epidemiology/prevention & control/*transmission[MESH] |Forecasting[MESH] |Humans[MESH] |Middle Aged[MESH] |Models, Theoretical[MESH] |Pandemics/prevention & control[MESH] |Pneumonia, Viral/*epidemiology/prevention & control/*transmission[MESH] |Republic of Korea/epidemiology[MESH] |Schools/organization & administration[MESH]Individual-based simulation model for COVID-19 transmission in Daegu, (epmc).pdf DeepDyve Pubget Overpricing