Table 1. Descriptive statistics of variables
Variable
|
Definition
|
Obs
|
Mean
|
Std.
|
Min
|
Max
|
NCOV
|
Number of infected people (people)
|
31
|
2619.581
|
12164.41
|
1
|
68127
|
PHM
|
Number of people who migrated from Hubei to another province (10,000 people)
|
30
|
31.87
|
74.059
|
0.85
|
397.34
|
PMH
|
Number of people who migrated from another province to Hubei(10,000 people)
|
30
|
9.891
|
9.973
|
0.6
|
44.89
|
P
|
Number of permanent residents in each province (10,000 people)
|
31
|
4395.032
|
2797.833
|
318
|
10724
|
PD
|
Population density, number of people per km2 (people)
|
31
|
453.376
|
705.27
|
2.59
|
3825.99
|
TD
|
Traffic density, mileage per km2 (km)
|
31
|
.955
|
.571
|
.06
|
2.46
|
neighbor
|
Whether it neighbors Hubei, yes=1, no=0
|
30
|
0.233
|
0.43
|
0
|
1
|
region
|
Whether it is in southern China, yes=1, no=0
|
30
|
0.467
|
0.507
|
0
|
1
|
QHrail
|
Number of high-speed trains between the provincial capital and Wuhan(trains)
|
30
|
21.1
|
26.61
|
0
|
99
|
distance
|
Distance from Hubei(km)
|
30
|
1230.333
|
721.342
|
327.1
|
3263.8
|
comparison
|
Whether the disposable income per capita is higher than that in Hubei, yes=1, no=0
|
31
|
0.387
|
0.495
|
0
|
1
|
Over65
|
the proportion of population over 65 years old
|
31
|
.096
|
.02
|
.05
|
.14
|
FiveA
|
the comparison of number of 5A-level scenic spots between the province and Hubei
|
31
|
.226
|
.425
|
0
|
1
|
Emergency
|
whether to start the first level response before January 24
|
31
|
.581
|
.502
|
0
|
1
|
Table 2 Hubei-related population migration and numbers of infected people
Rank
|
Province
|
PHM
|
Province
|
PMH
|
Province
|
P
|
Province
|
NCOV
|
1
|
Hubei
|
-
|
Hubei
|
-
|
Guangdong
|
10724
|
Hubei
|
68127
|
2
|
Guangdong
|
397.34
|
Henan
|
44.89
|
Shandong
|
9789
|
Guangdong
|
1395
|
3
|
Zhejiang
|
124.51
|
Hunan
|
28.8
|
Henan
|
9436
|
Henan
|
1273
|
4
|
Shanghai
|
73.55
|
Guangdong
|
20.79
|
Sichuan
|
8140
|
Zhejiang
|
1218
|
5
|
Jiangsu
|
60.77
|
Chongqing
|
20.65
|
Jiangsu
|
7960
|
Hunan
|
1018
|
6
|
Beijing
|
49.39
|
Anhui
|
20.6
|
Hebei
|
7384
|
Anhui
|
990
|
7
|
Fujian
|
43.96
|
Jiangxi
|
17.32
|
Hunan
|
6737
|
Jiangxi
|
935
|
8
|
Hunan
|
25.08
|
Sichuan
|
15.97
|
Anhui
|
6083
|
Shandong
|
763
|
9
|
Tianjin
|
23.51
|
Zhejiang
|
15.59
|
Hubei
|
5816
|
Jiangsu
|
631
|
10
|
Sichuan
|
15.04
|
Shandong
|
13.34
|
Zhejiang
|
5508
|
Chongqing
|
576
|
11
|
Jiangxi
|
12.49
|
Fujian
|
13.06
|
Guangxi
|
4754
|
Heilongjiang
|
558
|
12
|
Yunnan
|
12.25
|
Jiangsu
|
12.33
|
Yunnan
|
4714
|
Sichuan
|
540
|
13
|
Henan
|
10.93
|
Hebei
|
8.63
|
Jiangxi
|
4542
|
Beijing
|
419
|
14
|
Anhui
|
10.62
|
Guizhou
|
8.38
|
Liaoning
|
4391
|
Shanghai
|
339
|
15
|
Shaanxi
|
10.33
|
Shaanxi
|
7.26
|
Heilongjiang
|
3833
|
Hebei
|
318
|
16
|
Shandong
|
9.76
|
Guangxi
|
6.67
|
Fujian
|
3806
|
Fujian
|
296
|
17
|
Hebei
|
9.4
|
Yunnan
|
5.21
|
Shaanxi
|
3775
|
Guangxi
|
252
|
18
|
Shanxi
|
8.86
|
Shanxi
|
4.85
|
Shanxi
|
3648
|
Shaanxi
|
245
|
19
|
Guizhou
|
8.05
|
Gansu
|
4.85
|
Guizhou
|
3508
|
Yunnan
|
174
|
20
|
Guangxi
|
7.97
|
Xinjiang
|
4.38
|
Chongqing
|
2991
|
Hainan
|
168
|
21
|
Xinjiang
|
7.73
|
Shanghai
|
3.37
|
Jilin
|
2752
|
Guizhou
|
146
|
22
|
Chongqing
|
7.6
|
Heilongjiang
|
3.19
|
Gansu
|
2591
|
Tianjin
|
136
|
23
|
Hainan
|
7.15
|
Hainan
|
2.91
|
Inner Mongolia
|
2505
|
Shanxi
|
133
|
24
|
Gansu
|
4.24
|
Inner Mongolia
|
2.74
|
Shanghai
|
2426
|
Liaoning
|
125
|
25
|
Qinghai
|
3.23
|
Beijing
|
2.67
|
Xinjiang
|
2298
|
Jilin
|
93
|
26
|
Liaoning
|
2.85
|
Liaoning
|
2.11
|
Beijing
|
2152
|
Gansu
|
92
|
27
|
Heilongjiang
|
2.74
|
Jilin
|
1.92
|
Tianjin
|
1517
|
Inner Mongolia
|
77
|
28
|
Inner Mongolia
|
2.73
|
Tianjin
|
1.65
|
Hainan
|
903
|
Xinjiang
|
76
|
29
|
Jilin
|
2.18
|
Qinghai
|
1.23
|
Ningxia
|
662
|
Ningxia
|
75
|
30
|
Ningxia
|
0.99
|
Tibet
|
0.76
|
Qinghai
|
583
|
Qinghai
|
18
|
31
|
Tibet
|
0.85
|
Ningxia
|
0.6
|
Tibet
|
318
|
Tibet
|
1
|
Table 3. Population migration-related factors for the number of infected people
Variable
|
Model 1
|
Model 2
|
Model 3
|
Model 4
|
P
|
0.519
(0.462)
|
|
|
|
PHM
|
|
1.953***
(0.452)
|
|
|
PMH
|
|
30.89***
(3.438)
|
|
|
PPHM
|
|
|
0.000115**
(0.0000455)
|
0.0000973***
(0.0000335)
|
PPMH
|
|
|
0.00324***
(0.000649)
|
0.00265***
(0.000401)
|
PD
|
|
|
|
-0.0992
(0.0632)
|
TD
|
|
|
|
202.2*
(99.99)
|
Over65
|
|
|
|
-628.6
(1773.9)
|
Emergency
|
|
|
|
150.1
(89.33)
|
_cons
|
339.2
(829.3)
|
60.64*
(34.48)
|
194.9***
(43.71)
|
66.53
(129.0)
|
N
|
31
|
30
|
30
|
30
|
R2
|
0.014
|
0.831
|
0.721
|
0.801
|
Notes: *, **, and *** represent significance at 10%, 5%, and 1% respectively; bracketed values denote the standard errors.
Table 4. Factors affecting population migration
Variable
|
Model 5
|
Model 6
|
Model 7
|
PHM
|
PMH
|
PTH
|
P
|
0.00367
(0.00831)
|
0.000340
(0.000428)
|
0.00401
(0.00827)
|
neighbor
|
-42.48
(35.08)
|
8.464***
(2.735)
|
-34.02
(33.64)
|
region
|
36.42
(22.87)
|
1.086
(2.184)
|
37.51
(22.07)
|
QHrail
|
1.124
(0.863)
|
0.138**
(0.0582)
|
1.261
(0.847)
|
distan
|
0.0313
(0.0293)
|
-0.00154
(0.00132)
|
0.0298
(0.0287)
|
comparison
|
45.45*
(25.08)
|
-1.818
(1.929)
|
43.63*
(24.56)
|
FiveA
|
31.81
(34.85)
|
8.588*
(4.186)
|
40.40
(34.77)
|
_cons
|
-76.44
(78.76)
|
3.877
(2.966)
|
-72.56
(77.56)
|
N
|
30
|
30
|
30
|
R2
|
0.477
|
0.863
|
0.526
|
Notes: *, **, and *** represent significance at 10%, 5%, and 1% respectively; bracketed values denote the standard errors.