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|標題:||Real-time forecast of multiphase outbreak||作者:||Hsieh, Y.H.
|關鍵字:||acute-respiratory-syndrome;epidemiology;dynamics;sars||Project:||Emerging Infectious Diseases||期刊/報告no：:||Emerging Infectious Diseases, Volume 12, Issue 1, Page(s) 122-127.||摘要:||
We used a single equation with discrete phases to fit the daily cumulative case data from the 20 03 severe acute respiratory syndrome outbreak in Toronto. This model enabled us to estimate turning points and case numbers during the 2 phases of this outbreak. The 3 estimated turning points are March 25, April 27, and May 24. The estimated case number during the first phase of the outbreak between February 23 and April 26 is 140.53 (95% confidence interval [Cl] 115.88-165.17) if we use the data from February 23 to April 4; and 249 (95% Cl: 246.67-251.25) at the end of the second phase on June 12 if we use the data from April 28 to June 4. The second phase can be detected by using case data just 3 days past the beginning of the phase, while the first and third turning points can be identified only approximate to 10 days afterwards. Our modeling procedure provides insights into ongoing outbreaks that may facilitate real-time public health responses.
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