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Using Less Oil Despite the unquenchable thirst for oil to fuel nina's fast growing economy,the oil consumption growth rate is dropping
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作者 TONG LIXIA is an associate researcher at the Chinese Academy of International Trade and Economic Cooperation under the Ministry of Commerce 《Beijing Review》 2006年第14期34-35,共2页
At first glance, the official figures of China's oil consumption in 2005 seem a bit confusing. With a robust economic growth and rising annual oil imports, China made the surprise announcement that its oil consump... At first glance, the official figures of China's oil consumption in 2005 seem a bit confusing. With a robust economic growth and rising annual oil imports, China made the surprise announcement that its oil consumption growth rate was dropping sharply, from 15.3 percent in 2004 to 2.1 percent in 2005. Earlier, China's Ministry 展开更多
关键词 Using Less Oil Despite the unquenchable thirst for oil to fuel nina’s fast growing economy the oil consumption growth rate is dropping
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Short-term forecast in the early stage of the COVID-19 outbreak in Italy. Application of a weighted and cumulative average daily growth rate to an exponential decay model
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作者 Nicola Bartolomeo Paolo Trerotoli Gabriella Serio 《Infectious Disease Modelling》 2021年第1期212-221,共10页
To estimate the size of the novel coronavirus(COVID-19)outbreak in the early stage in Italy,this paper introduces the cumulated and weighted average daily growth rate(WR)to evaluate an epidemic curve.On the basis of a... To estimate the size of the novel coronavirus(COVID-19)outbreak in the early stage in Italy,this paper introduces the cumulated and weighted average daily growth rate(WR)to evaluate an epidemic curve.On the basis of an exponential decay model(EDM),we provide estimations of the WR in four-time intervals from February 27 to April 07,2020.By calibrating the parameters of the EDM to the reported data in Hubei Province of China,we also attempt to forecast the evolution of the outbreak.We compare the EDM applied to WR and the Gompertz model,which is based on exponential decay and is often used to estimate cumulative events.Specifically,we assess the performance of each model to short-term forecast of the epidemic,and to predict the final epidemic size.Based on the official counts for confirmed cases,the model applied to data from February 27 until the 17th of March estimate that the cumulative number of infected in Italy could reach 131,280(with a credibility interval 71,415-263,501)by April 25(credibility interval April 12 to May 3).With the data available until the 24st of March the peak date should be reached on May 3(April 23 to May 23)with 197,179 cumulative infections expected(130,033e315,269);with data available until the 31st of March the peak should be reached on May 4(April 25 to May 18)with 202,210 cumulative infections expected(155.235 e270,737);with data available until the 07st of April the peak should be reached on May 3(April 26 toMay 11)with 191,586(160,861-232,023)cumulative infections expected.Based on the average mean absolute percentage error(MAPE),cumulated infections forecasts provided by the EDM applied to WR performed better across all scenarios than the Gompertz model.An exponential decay model applied to the cumulated and weighted average daily growth rate appears to be useful in estimating the number of cases and peak of the COVID-19 outbreak in Italy and the model was more reliable in the exponential growth phase. 展开更多
关键词 Covid-19 CORONAVIRUS ITALY Short-term forecasts Daily grow rate Exponential decay model
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