Skip to main content

Table 3 The prediction effect of ARIMA and ARIMAX model in different regions

From: Effects of meteorological factors on the incidence of mumps and models for prediction, China

Region

Month

Actual incidence (1/100,000)

ARIMA

ARIMAX

Predicting incidence (95%CI)

Relative error (%)

Predicting incidence (95%CI)

Relative error (%)

North China

Jan

0.79

0.83(0.57–1.17)

5.06

0.82(0.57 ~ 1.20)

3.80

Feb

0.52

0.51(0.31–0.81)

1.92

0.52(0.33 ~ 0.69)

0.00

Mar

0.72

0.82(0.44–1.39)

13.89

0.79(0.34 ~ 1.32)

9.72

Apr

0.94

1.21(0.61–2.17)

28.72

1.18(0.43 ~ 2.07)

25.53

May

1.22

1.53(0.73–2.83)

25.41

1.40(0.67 ~ 2.62)

14.75

Jun

1.30

1.52(0.70–2.90)

16.92

1.48(0.68 ~ 2.85)

13.85

Jul

1.11

1.25(0.56–2.44)

12.61

1.20(0.43 ~ 2.38)

8.11

Aug

0.90

0.81(0.35–1.62)

10.00

0.80(0.44 ~ 1.78)

11.11

Sep

0.85

0.71(0.30–1.43)

16.47

0.73(0.45 ~ 1.67)

14.12

Oct

0.79

0.84(0.35–1.70)

6.33

0.81(0.23 ~ 1.63)

2.53

Nov

0.99

1.00(0.41–2.04)

11.11

1.00(0.40 ~ 2.27)

1.01

Dec

1.21

1.26(0.51–2.60)

4.13

1.19(0.51 ~ 2.52)

1.65

East China

Jan

0.83

0.89(0.59–1.28)

7.23

0.85(0.61 ~ 1.25)

2.41

Feb

0.54

0.53(0.30–0.88)

1.85

0.48(0.32 ~ 0.74)

11.11

Mar

0.81

0.87(0.42–1.60)

7.41

0.74(0.35 ~ 1.66)

8.64

Apr

1.04

1.35(0.58–2.69)

29.81

1.07(0.61 ~ 2.01)

2.88

May

1.34

1.81(0.70–3.89)

35.07

1.45(0.57 ~ 2.58)

8.21

Jun

1.39

1.85(0.65–4.23)

33.09

1.49(0.62 ~ 2.98)

7.19

Jul

1.25

1.47(0.47–3.55)

17.60

1.10(0.43 ~ 2.57)

12.00

Aug

0.93

0.80(0.23–2.04)

13.98

1.02(0.24 ~ 1.47)

9.68

Sep

0.90

0.64(0.17–1.69)

28.89

0.85(0.21 ~ 1.45)

5.56

Oct

0.84

0.67(0.17–1.87)

20.24

0.70(0.18 ~ 1.59)

16.67

Nov

0.82

0.75(0.17–2.18)

8.54

0.79(0.19 ~ 1.54)

3.66

Dec

0.79

0.94(0.20–2.83)

18.99

0.83(0.22 ~ 1.98)

5.06

South China

Jan

1.33

1.36(0.91–1.94)

2.26

Feb

0.78

0.79(0.57–1.40)

1.28

Mar

1.15

1.26(0.73–2.02)

9.57

Apr

1.40

1.50(0.82–2.53)

7.14

May

1.66

1.96(1.01–3.44)

18.07

Jun

2.17

1.93(0.95–3.52)

11.06

Jul

2.27

1.97(0.92–3.74)

13.22

Aug

1.61

1.50(0.67–2.94)

6.83

Sep

1.60

1.57(0.67–3.17)

1.88

Oct

1.79

1.60(0.65–3.33)

10.61

Nov

1.87

1.84(0.72–3.94)

1.60

Dec

2.01

1.66(0.62–3.65)

17.41

Central China

Jan

1.83

1.86(1.21–2.75)

1.64

1.85(1.36 ~ 1.52)

1.09

Feb

1.03

1.07(0.64–1.70)

3.88

1.06(0.47 ~ 1.68)

2.91

Mar

1.15

1.19(0.88–2.67)

3.48

1.30(0.79 ~ 2.10)

13.04

Apr

1.58

2.01(1.33–4.56)

27.33

1.89(0.86 ~ 2.40)

19.62

May

2.20

2.58(1.65–6.28)

17.27

2.40(1.92 ~ 5.67)

9.09

Jun

2.46

3.56(1.62–6.85)

44.72

3.35(1.92 ~ 6.04)

36.18

Jul

2.37

2.83(1.22–5.66)

19.41

2.21(1.14 ~ 4.07)

6.75

Aug

1.48

1.48(0.61–3.06)

0.00

1.31(0.71 ~ 2.45)

11.49

Sep

1.26

1.12(0.44–2.40)

11.11

1.19(0.56 ~ 2.28)

5.56

Oct

1.62

1.43(0.53–3.16)

11.73

1.51(0.68 ~ 2.93)

6.79

Nov

2.22

1.71(0.60–3.89)

22.97

1.56(0.62 ~ 3.21)

29.73

Dec

3.30

2.11(0.71–4.92)

36.06

2.34(0.63 ~ 3.45)

29.09

South west

Jan

1.17

1.26(0.77–1.99)

7.69

1.20(0.82 ~ 1.69)

2.56

Feb

0.59

0.70(0.40–1.14)

18.64

0.63(0.53 ~ 1.38)

6.78

Mar

1.06

0.96(0.51–1.67)

9.43

1.04(0.54 ~ 1.71)

1.89

Apr

1.41

1.60(0.79–2.89)

13.48

1.46(0.73 ~ 1.55)

3.55

May

1.89

2.20(1.05–4.09)

16.40

2.21(1.06 ~ 4.10)

16.93

Jun

1.95

2.43(1.13–4.62)

24.62

2.51(1.23 ~ 4.61)

28.72

Jul

1.69

1.84(0.84–3.55)

8.88

1.85(0.89 ~ 3.45)

9.47

Aug

1.18

1.07(0.48–2.08)

9.32

1.12(0.61 ~ 2.14)

5.08

Sep

1.28

1.00(0.44–1.96)

21.88

1.01(0.47 ~ 1.93)

21.09

Oct

1.55

1.18(0.52–2.33)

23.87

1.20(0.57 ~ 2.29)

22.58

Nov

1.57

1.36(0.59–2.68)

13.38

1.39(0.54 ~ 2.68)

11.46

Dec

1.58

1.29(0.56–2.56)

18.35

1.31(0.59 ~ 2.55)

17.09

North west

Jan

1.59

1.55(1.00–2.29)

2.52

1.64(1.13 ~ 2.46)

3.14

Feb

0.89

0.90(0.49–1.52)

1.12

0.89(0.51 ~ 1.49)

0.00

Mar

1.17

1.26(0.62–2.39)

7.69

1.34(0.64 ~ 2.38)

14.53

Apr

1.45

1.76(0.77–3.45)

21.38

1.63(0.76 ~ 3.19)

12.41

May

1.84

2.16(0.89–4.46)

17.39

2.06(0.89 ~ 4.01)

11.96

Jun

1.93

2.13(0.82–4.56)

10.36

1.90(0.76 ~ 3.98)

1.55

Jul

1.53

1.71(0.63–3.78)

11.76

1.64(0.63 ~ 3.45)

7.19

Aug

1.28

1.06(0.38–2.40)

17.19

1.04(0.36 ~ 2.28)

18.75

Sep

1.31

1.01(0.35–2.33)

22.90

1.10(0.36 ~ 2.22)

16.03

Oct

1.41

1.30(0.43–3.05)

7.80

1.26(0.44 ~ 2.89)

10.64

Nov

2.26

1.70(0.55–4.05)

24.78

1.83(0.61 ~ 3.94)

19.03

Dec

2.29

1.85(0.59–4.47)

19.21

1.96(0.71 ~ 4.50)

14.41

North east

Jan

0.44

0.37(0.25–0.52)

15.91

0.39(0.29 ~ 0.54)

11.36

Feb

0.29

0.18(0.10–0.30)

37.93

0.20(0.13 ~ 0.30)

31.03

Mar

0.49

0.26(0.13–0.46)

46.94

0.32(0.26 ~ 0.55)

34.69

Apr

0.49

0.34(0.15–0.65)

30.61

0.39(0.20 ~ 0.69)

20.41

May

0.72

0.47(0.19–0.97)

34.72

0.62(0.29 ~ 1.18)

13.89

Jun

0.70

0.47(0.17–1.04)

32.86

0.66(0.29 ~ 1.32)

5.71

Jul

0.53

0.35(0.12–0.81)

33.96

0.52(0.23 ~ 1.10)

1.89

Aug

0.43

0.22(0.07–0.55)

48.84

0.29(0.14 ~ 0.66)

32.56

Sep

0.46

0.23(0.07–0.61)

50.00

0.30(0.12 ~ 0.71)

34.78

Oct

0.40

0.24(0.06–0.64)

40.00

0.26(0.10 ~ 0.59)

35.00

Nov

0.44

0.33(0.08–0.93)

25.00

0.33(0.10 ~ 0.85)

25.00

Dec

0.46

0.39(0.09–1.12)

15.22

0.43(0.13 ~ 1.09)

6.52

  1. Note: There were no meteorological factors related to the incidence of mumps in south China