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. 2020 Aug 11;751:141663. doi: 10.1016/j.scitotenv.2020.141663

Table 2.

Hierarchical multiple regression analysis summary for populationi density, airports and wind variables predicting COVID-19 cases.

B SE β T p 95%Cl
Lower-Upper
VIF
Constant −377.138 45.518 −8.285 0.0001 −467.80 −286.48 6.41
Population 0.000 0.000 0.20 2.83 0.006 0.000 0.000 7.19
Density 2.50 0.22 0.78 11.56 0.0001 2.06 2.93 6.56
Airports −33.71 57.30 −0.02 −0.59 0.56 −147.84 80.42 1.57
Wind speed 25.33 12.18 −0.06 2.08 0.04 1.06 49.59 1.08



Model 1: Adj. R2 = 0.95. F (4, 76) = 340.19. p < .0001
Constant −445.76 137.42 −3.24 0.002 −719.35 −172.17
Density 3.06 0.09 0.96 33.64 0.0001 2.88 3.24 1.07
Wind speed 22.13 12.56 0.05 1.94 0.05 −2.93 47.18 1.07
Model 2 (airports and population excluded): Adj. R2 = 0.94. F (2,78) = 626.90, p < .0001.