Selected article for: "study period and time distribution"
Author: Tao Liu; Jianxiong Hu; Jianpeng Xiao; Guanhao He; Min Kang; Zuhua Rong; Lifeng Lin; Haojie Zhong; Qiong Huang; Aiping Deng; Weilin Zeng; Xiaohua Tan; Siqing Zeng; Zhihua Zhu; Jiansen Li; Dexin Gong; Donghua Wan; Shaowei Chen; Lingchuan Guo; Yan Li; Limei Sun; Wenjia Liang; Tie Song; Jianfeng He; Wenjun Ma
Title: Time-varying transmission dynamics of Novel Coronavirus Pneumonia in China
  • Document date: 2020_1_26
    • ID: 3e2soc6w_8
    Snippet: The number of occurred-but-not-yet-reported cases were further estimated during the study period, which caused by reporting delays. Reasons for such delays include the time to complete diagnosis test, logistics, and overwhelmed surveillance systems. To minimize the effects of reporting delay, we applied a Bayesian nowcasting model (Nowcasting by Bayesian Smoothing) to complement the daily total number of incidences (19) . This model is characteri.....
    Document: The number of occurred-but-not-yet-reported cases were further estimated during the study period, which caused by reporting delays. Reasons for such delays include the time to complete diagnosis test, logistics, and overwhelmed surveillance systems. To minimize the effects of reporting delay, we applied a Bayesian nowcasting model (Nowcasting by Bayesian Smoothing) to complement the daily total number of incidences (19) . This model is characterized by its ability to deal with the uncertainty in the delay distribution and the time evolution of epidemic curve.

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