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Table 1 Characteristics of the 30 study counties

From: Characterizing the effect of temperature fluctuation on the incidence of malaria: an epidemiological study in south-west China using the varying coefficient distributed lag non-linear model

County

Cases

Annualized average incidences (/100,000)

Mean temperature☆ (°C)

DTR☆ (°C)

Rain☆☆ (mm)

Relative humidity☆ (%)

Ruili

3,442

348.204

21.2 (17.7, 24.6)

10.8 (7.7,14)

26.53 (0, 43.03)

73.0 (67, 80)

Tengchong

9,255

246.049

20.4 (16, 24.5)

10.7 (7.8, 13.8)

17.80 (1, 24.7)

65.0 (54, 77)

Gongshan

300

136.897

6.7 (1.4,12.3)

10.8 (8, 13.8)

12.29 (2, 17.63)

69.6 (61, 80)

Fugong

455

80.657

12.3 (7.1, 17.7)

12.4 (9, 15.9)

16.59 (2, 27.85)

67.6 (58, 78)

Mengla

1,203

79.980

22.0 (18.9, 25.1)

11.3 (8.2,14.1)

28.02 (0, 41.83)

80.6 (77, 85)

Cangyuan

859

65.931

19.8 (16, 23.4)

12.3 (8.5, 16.3)

23.63 (0, 37.93)

72.4 (65, 81)

Menglian

735

55.274

20 (16.6, 23.1)

12.2 (8.4, 16.1)

32.56 (0, 51.6)

75.3 (70, 82)

Jinping

966

47.375

16.5 (12.7, 20.7)

7.3 (4.6, 9.6)

28.95 (2.25, 40.35)

84.8 (81, 91)

Longyang

1,976

37.041

16.6 (12.1, 20.7)

11.2 (7.9, 14.6)

17.94 (0.08, 27.23)

73.1 (66, 81)

Congjiang

688

34.928

19 (12.3, 25.7)

8.7 (5.1, 11.9)

22.03 (0.7, 33.8)

78.6 (73, 84)

Jiangcheng

142

22.283

19.1 (15.7, 22.4)

9.9 (6.7, 13)

41.89 (0.38, 69.28)

79.2 (76, 84)

Menghai

420

21.036

22.8 (19.8, 25.6)

11.8 (8.6, 14.5)

23.17 (0, 38.63)

77.4 (72, 84)

Weixi

174

18.725

7.0 (1.6, 12.8)

12.5 (7.9, 16.7)

11.76 (0, 17.93)

65.9 (58, 74)

Shuangjiang

113

10.580

18.3 (14.6, 21.6)

11.3 (7.8, 14.9)

21.22 (0.08, 32.63)

67.6 (59, 77)

Simao

119

8.132

19.3 (16.2, 22.3)

10.2 (7.2, 13.1)

27.18 (0, 43.8)

75.9 (71, 83)

Mojiang

173

7.565

24.1 (20.1, 28.1)

11.6 (8.4, 14.3)

15.40 (0, 21.4)

66.6 (59, 75)

Jingdong

166

7.382

19 (14.6, 23.1)

12.4 (8.3, 16.6)

22.21 (0.38, 31.23)

74.7 (70, 82)

Dechang

86

7.335

17.6 (13.1, 22.2)

11.4 (8.5, 14.4)

18.39 (0, 28.1)

59.3 (50, 71)

Gejiu

156

5.535

19.5 (16.1, 23.2)

8.7 (6.7, 10.6)

15.90 (0, 21.18)

68.3 (63, 75)

Dushan

102

4.984

15.6 (9.7, 22)

7.3 (4.6, 9.5)

23.94 (1.5, 32.68)

79.4 (73, 88)

Changshun

53

3.598

16.4 (10.3, 22.6)

8.1 (5.1, 10.5)

22.30 (1.48, 29.1)

77.5 (72, 84)

Liping

75

2.522

16.3 (9.2, 23.8)

7.8 (4.3, 10.9)

23.68 (1.9, 33.33)

81.3 (74, 90)

Wenshan

64

2.325

16.5 (12.9, 20.6)

9.6 (6.8, 12.1)

17.64 (0.5, 26.03)

78.3 (74, 85)

Wangmo

29

1.609

20.0 (14.8, 25.6)

9.1 (5.9, 11.8)

22.43 (0.5, 26.43)

73.2 (67, 80)

Guangnan

74

1.575

17.5 (13.1, 22.4)

10.0 (6.5, 13)

16.98 (0.5, 23.8)

76.8 (72, 84)

Weishan

28

1.482

15.5 (11.5, 19.5)

10.6 (8.2, 13.1)

20.37 (0, 33.28)

66.2 (55, 78)

Nanhua

19

1.318

16.5 (12.3, 20.5)

10.4 (7.6, 13.1)

15.66 (0, 24.08)

68.2 (59, 80)

Weng’an

32

1.263

15.9 (9.1, 22.8)

7.3 (3.8, 10.1)

19.65 (2.6, 27.85)

77.1 (71, 85)

Eshan

11

1.156

16.4(12.3, 20.3)

10.8 (7.8, 13.8)

16.23 (0, 23.63)

72.6 (67, 81)

Huili

29

1.089

15.6 (10.7, 20.3)

11.9 (8.2, 15.9)

21.53 (0, 27.95)

68.0 (60, 77)

  1. ☆: weekly mean, and the two values in the parenthesis are 25% and 75% percentiles, respectively.
  2. ☆☆: weekly total, and the two values in the parenthesis are 25% and 75% percentiles, respectively.