Selected article for: "continuous variable and statistical analysis"

Author: Noh, Jin-Won; Yoo, Ki-Bong; Kwon, Young Dae; Hong, Jin Hyuk; Lee, Yejin; Park, Kisoo
Title: Effect of Information Disclosure Policy on Control of Infectious Disease: MERS-CoV Outbreak in South Korea
  • Document date: 2020_1_1
  • ID: 1g3u7xno_13
    Snippet: where t was time period (day), Time was a continuous variable initiated on 20 May 2015 (daily), disclosure was binary variable representing disclosure of the hospital list (0 before 5 June; 1 after 5 June 2015), Quarantines was a continuous variable representing the daily number of quarantined individuals, Time_after_disclosure was a continuous variable initiated on 5 June 2015 (daily), and was an error term. Results of segmented regression for c.....
    Document: where t was time period (day), Time was a continuous variable initiated on 20 May 2015 (daily), disclosure was binary variable representing disclosure of the hospital list (0 before 5 June; 1 after 5 June 2015), Quarantines was a continuous variable representing the daily number of quarantined individuals, Time_after_disclosure was a continuous variable initiated on 5 June 2015 (daily), and was an error term. Results of segmented regression for confirmed cases are shown in Table 1 . Baseline time trend showed a significant increase (Estimate = 0.337; p < 0.001). The number of confirmed cases was Results of segmented regression for confirmed cases are shown in Table 1 . Baseline time trend showed a significant increase (Estimate = 0.316; p < 0.001). The number of confirmed cases was increased by 9.632 on 5 June (p < 0.001). It showed a significant downward trend following disclosure of hospital list (Estimate = −0.699; p < 0.001). The spread of the disease ceased because potential MERS-CoV patients were screened. Figure 2 shows results and predictions of the statistical analysis. Results of sensitivity analyses are shown in Table 2 . They were almost consistent with those shown in Table 1 .

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