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Table 3 Spearman’s correlation coefficients between the incidence, cattle stocks, sheep stocks, population density, GDP, precipitation, and climate

From: Spatial-temporal distribution of human brucellosis in mainland China from 2004 to 2017 and an analysis of social and environmental factors

 

Incidence (104 person)

Cattle (104 heads)

Sheep (104 heads)

Population density (person/km2)

GDP (100 million yuan)

Precipitation (mm)

Climate (mid-temperate)

Climate (subtropical)

Climate (warm-temperate)

Climate (tropical)

Incidence (104 person)

1.00

0.22

0.49

0.05

− 0.06

− 0.63

0.52

− 0.72

0.34

− 0.11

Cattle (104 heads)

0.22

1.00

0.71

0.12

− 0.12

− 0.19

0.29

− 0.16

− 0.08

− 0.14

Sheep (104 heads)

0.49

0.71

1.00

0.09

− 0.15

− 0.58

0.39

− 0.47

0.15

− 0.18

Population density (person/km2)

0.05

0.12

0.09

1.00

0.01

0.03

− 0.01

− 0.0002

0.008

− 0.05

GDP (100 million yuan)

− 0.06

− 0.12

− 0.15

0.01

1.00

0.48

− 0.42

0.37

0.14

− 0.19

Precipitation (mm)

− 0.63

− 0.19

− 0.58

0.03

0.48

1.00

− 0.59

0.79

− 0.30

0.21

Climate (mid-temperate)

0.52

0.29

0.39

− 0.01

− 0.42

− 0.59

1.00

− 0.45

− 0.36

− 0.07

Climate (subtropical)

− 0.72

− 0.16

− 0.46

− 0.0002

0.32

0.79

− 0.45

1.00

− 0.57

− 0.12

Climate (warm-temperate)

0.34

0.08

0.14

0.10

0.14

− 0.30

− 0.36

− 0.57

1.00

− 0.09

Climate (tropical)

− 0.11

− 0.14

− 0.18

− 0.05

− 0.19

0.21

− 0.07

− 0.12

− 0.09

1.00

  1. “Climate” was a categorical variable and thus encoded using dummy encoding. With dummy encoding, n categories will only generate n − 1 coded variables. In this case, the climate categorized as cold was dropped and not encoded and was set as the reference climate