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Table 1 Correlation between daily growth of confirmed cases (DGCC) across China and values of Baidu index (BI)

From: Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index

Region Values of BI
Fever Cough Fatigue Sputum production Shortness of breath
China
rs 0.768 0.556 0.763 0.665 0.780
p 8.013 × 10− 23 1.087 × 10− 9 7.930 × 10− 21 1.793 × 10− 14 2.673 × 10−22
Anhui
rs 0.801 0.770 0.760 − 0.028 0.775
p 5.39 × 1024 3.131 × 10− 21 2.172 × 10− 20 0.782 1.205 × 10− 21
Beijing
rs 0.657 0.431 0.582 0.249 0.610
p 6.336 × 10−14 6.502 × 10− 6 1.358 × 10−10 0.012 1.040 × 10− 11
Chongqing
rs 0.796 0.769 0.740 0.572 0.738
p 1.542 × 10−23 1.647 × 10− 23 6.057 × 10− 19 3.389 × 10− 10 8.809 × 10− 19
Fujian
rs 0.588 0.471 0.705 0.367 0.537
p 8.473 × 10− 11 5.677 × 10− 7 1.388 × 10− 16 1.485 × 10− 4 5.809 × 10− 9
Gansu
rs 0.527 0.444 0.373 − 0.150 0.484
p 1.277 × 10− 8 3.008 × 10− 6 1.112 × 10− 4 0.133 2.586 × 10− 7
Guangdong
rs 0.535 0.336 0.527 0.262 0.506
p 7.113 × 10−9 1.564 × 10− 4 1.287 × 10− 8 0.008 5.598 × 10− 8
Guangxi
rs 0.766 0.754 0.760 0.287 0.731
p 7.075 × 10−21 5.780 × 10−20 1.904 × 10− 20 0.004 6.872 × 10− 8
Guizhou
rs 0.673 0.657 0.622 0.355 0.629
p 9.182 × 10− 15 6.433 × 10− 14 2.921 × 10− 12 2.555 × 10− 4 1.388 × 10− 12
Hainan
rs 0.717 0.735 0.694 −0.354 0.693
p 2.474 × 10− 17 1.468 × 10− 18 6.080 × 10− 16 2.673 × 10− 4 6.597 × 10− 16
Hebei
rs 0.731 0.635 0.662 0.040 0.705
p 2.622 × 10−18 7.392 × 10− 13 3.396 × 10− 14 0.691 1.297 × 10− 16
Heilongjiang
rs 0.413 0.201 0.453 0.089 0.345
p 1.590 × 10− 5 0.042 1.710 × 10− 6 0.375 2.669 × 10− 4
Henan
rs 0.771 0.766 0.728 0.655 0.759
p 2.652 × 10− 21 6.291 × 10− 21 4.647 × 10− 18 7.887 × 10− 14 2.288 × 10− 20
Hong Kong
rs − 0.094 − 0.514 − 0.282 0.517 − 0.085
p 0.349 3.394 × 10− 8 0.004 2.676 × 10− 8 0.398
Hubei
rs 0.709 0.745 0.631 0.614 0.704
p 7.410 × 10− 17 2693 × 10− 19 1.131 × 10− 12 6.640 × 10− 12 1.640 × 10− 16
Hunan
rs 0.813 0.797 0.738 −0.244 0.759
p 2.942 × 10− 25 1.256 × 10− 23 9.111 × 10− 19 0.014 2.300 × 10− 20
Inner Mongolia
rs 0.322 0.129 0.369 0.385 0.316
p 0.001 0.197 1.384 × 10− 4 6.326 × 10− 5 0.001
Jiangsu
rs 0.695 0.565 0.629 0.502 0.630
p 5.378 × 10− 16 5.918 × 10− 10 1.441 × 10− 12 7.609 × 10− 8 1.306 × 10− 12
Jiangxi
rs 0.692 0.672 0.686 − 0.317 0.640
p 7.678 × 10− 16 1.052 × 10− 14 1.861 × 10− 15 0.001 4.433 × 10− 13
Jilin
rs 0.538 0.446 0.626 0.323 0.355
p 5.415 × 10− 9 2.646 × 10− 6 1.925 × 10− 12 0.001 2.472 × 10− 4
Liaoning
rs 0.575 0.425 0.486 − 0.221 0.513
p 2.685 × 10− 10 8.698 × 10− 6 2.179 × 10− 7 0.026 3.436 × 10− 8
Macau
rs 0.105 0.016 0.093 0.204 0.015
p 0.293 0.872 0.354 0.040 0.882
Ningxia
rs 0.696 0.649 0.541 −0.389 0.503
p 4.495 × 10−16 1.656 × 10−13 4.279 × 10−9 5.317 × 10−5 7.051 × 10−8
Qinghai
rs 0.461 0.465 0.428 0.297 0.396
p 1.115 × 10−6 8.234 × 10−7 7.029 × 10− 6 0.002 3.833 × 10−5
Shaanxi
rs 0.637 0.607 0.606 − 0.157 0.670
p 5.969 × 10−13 1.319 × 10−11 1.494 × 10− 11 0.115 1.406 × 10−14
Shandong
rs 0.706 0.584 0.702 0.528 0.708
p 1.230 × 10−16 1.217 × 10−10 2.135 × 10− 16 5.238 × 10−7 9.317 × 10−17
ShanghaiShanghai
rs 0.331 0.133 0.379 − 0.020 0.391
p 0.001 0.184 8.633 × 10−5 0.841 4.810 × 10− 5
Shanxi
rs 0.380 0.275 0.313 0.001 0.365
p 8.102 × 10−5 0.005 0.001 0.991 2.382 × 10−4
Sichuan
rs 0.775 0.687 0.720 0.681 0.771
p 1.247 × 10−21 1.565 × 10−15 1.588 × 10−17 3.530 × 10− 15 2.517 × 10− 21
Tianjin
rs 0.483 0.424 0.517 0.295 0.453
p 2.675 × 10−7 9.050 × 10−6 2.624 × 10−8 0.003 1.755 × 10− 6
Tibet
rs 0.167 0.139 0.173 −0.003 0.043
p 0.093 0.165 0.082 0.973 0.670
Xinjiang
rs 0.737 0.704 0.593 −0.284 0.504
p 9.948 × 10−19 1.642 × 10−16 4.944 × 10−11 0.004 6.872 × 10−8
Yunnan
rs 0.689 0.616 0.635 −0.340 0.638
p 1.274 × 10−15 5.308 × 10−12 7.636 × 10−13 4.776 × 10−14 5.252 × 10−13
Zhejiang
rs 0.592 0.530 0.628 0.349 0.618
p 5.553 × 10−11 1.026 × 10−8 1.569 × 10−12 3.250 × 10−4 4.461 × 10− 12
Taiwan
rs −0.111 − 0.428 −0.242 0.523 −0.019
p 0.269 7.105 × 10−6 0.014 1.699 × 10− 8 0.854