Selected article for: "primary analysis and secondary analysis"
Author: Songmin Ying; Fei Li; Xinwei Geng; Zhouyang Li; Xufei Du; Haixia Chen; Sisi Chen; Min Zhang; Zhehua Shao; Yinfang Wu; Madiha Zahra Syeda; Fugui Yan; Luanqing Che; Bin Zhang; Jian Lou; Shaobin Wang; Zhengming Chen; Wen Li; Ye Shen; Zhihua Chen; Huahao Shen
Title: Spread and control of COVID-19 in China and their associations with population movement, public health emergency measures, and medical resources
  • Document date: 2020_2_27
    • ID: mopydeq5_8
    Snippet: The correlations between the number of total confirmed or primary cases and total inflow index at 116 provincial or city scale, between the medical resources score and fatality or cure rates, and between 117 the employees in centers for disease control and prevention (CDC) per capita and the confirmed cases 118 or the incidence of COVID-19 were analyzed using Spearman's correlation analysis. Cross-119 correlation of primary and secondary cases wa.....
    Document: The correlations between the number of total confirmed or primary cases and total inflow index at 116 provincial or city scale, between the medical resources score and fatality or cure rates, and between 117 the employees in centers for disease control and prevention (CDC) per capita and the confirmed cases 118 or the incidence of COVID-19 were analyzed using Spearman's correlation analysis. Cross-119 correlation of primary and secondary cases was calculated by Pearson's correlation analysis. Principal 120 components analysis was performed on Stata 14.0, and other data were analyzed using Prism 121 GraphPad 8.0. Statistical significance was set at p < 0.05.

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