Selected article for: "data analysis and real data analysis"

Author: Slav W Hermanowicz
Title: Forecasting the Wuhan coronavirus (2019-nCoV) epidemics using a simple (simplistic) model - update (Feb. 8, 2020)
  • Document date: 2020_2_5
  • ID: 8kdtpwbv_17
    Snippet: Eq. (5) also shows a linearization of the discrete logistic model (Eq. (3)) that was used to estimate the Re(t=30) = R0 * and capacity K. An example of such linearization for Period 1 is shown in Figure 2 with the initial 16 points (blue points and line in Figure 2) . The same figure also shows linearization using for Period 2 (orange points and line in Figure 2 ). For all periods the effective reproduction numbers decrease in time. As new data w.....
    Document: Eq. (5) also shows a linearization of the discrete logistic model (Eq. (3)) that was used to estimate the Re(t=30) = R0 * and capacity K. An example of such linearization for Period 1 is shown in Figure 2 with the initial 16 points (blue points and line in Figure 2) . The same figure also shows linearization using for Period 2 (orange points and line in Figure 2 ). For all periods the effective reproduction numbers decrease in time. As new data were reported daily, we followed with subsequent analysis in near-real time with three periods as shown in Table 2 In contrast, a simple linearization of Re in time (Figure 3) back-estimated the original basic reproduction number R0 at about 2.4 to 2.5, agreeing well with other values recently reported Liu et al., 2020; Majumder & Mandl, 2020; Zhang & Wang, 2020a , 2020b Zhao et al., 2020a) . The discrepancy between these two estimates can be attributed a potential loss of virulence of the virus but most likely due to extreme measures to contain virus spread in China. . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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