Results
Table 1 presents the demographic characteristics of the hospitalized
COVID-19 cases registered in COVIREGI-JP. Tables 2 and 3 present the
posterior distribution of the model parameters.
(Table 1)
(Table 2)
(Table 3)
All variables other than the number of beds included as fixed effects
exhibited significant associations with the NEWS score at the time of
admission in both models.
Figure 1 presents the choropleth graph of the median value of the
posterior distribution of prefecture-specific random intercept in model
A. Figure 2 presents the choropleth graph of the median value of the
posterior distribution of prefecture-specific random intercept in model
B.
(Figure 1)
(Figure 2)
Several prefectures exhibited a higher risk of higher NEWS scores upon
admission, but these prefectures did not significantly change between
model A and B. The Bayesian factor of model A over model B was
136988.360.