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10.1016/j.ijid.2020.05.122 http://scihub22266oqcxt.onion/10.1016/j.ijid.2020.05.122 32502662!7266579!32502662     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Infect+Dis 2020 ; 97 (ä): 219-224 Nephropedia Template TP {{tp|p=32502662|t=2020. Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope |pdf=|usr=}}{{32502662}} gab.com Text Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope JO: Int J Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32502662 #FOAvip OBJECTIVES: The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. METHODS: We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January-15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude. RESULTS: We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6-6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3-7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2-1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size. CONCLUSIONS: Early epidemic characteristics are important indicators for the size of the entire epidemic. Twit Text FOAVip Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope ????Int J Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32502662 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32502662 #FOAvip English Wikipedia <ref>{{Cite pmid|32502662}}</ref> Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope #MMPMID32502662 Zhang L; Tao Y; Wang J; Ong JJ; Tang W; Zou M; Bai L; Ding M; Shen M; Zhuang G; Fairley CK Int J Infect Dis 2020[Aug]; 97 (ä): 219-224 PMID32502662show ga OBJECTIVES: The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. METHODS: We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January-15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude. RESULTS: We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6-6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3-7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2-1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size. CONCLUSIONS: Early epidemic characteristics are important indicators for the size of the entire epidemic. |*Betacoronavirus[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Cities/epidemiology[MESH] |Coronavirus Infections/*epidemiology[MESH] |Disease Outbreaks[MESH] |Epidemics[MESH] |Humans[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology[MESH]Early characteristics of the COVID-19 outbreak predict the subsequent (epmc).pdf DeepDyve Pubget Overpricing