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
|
0.955
|
0.571
|
0.06
|
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
|
0.096
|
0.02
|
0.05
|
0.14
|
FiveA
|
the comparison of number of 5A-level scenic spots between the province and Hubei
|
31
|
0.226
|
0.425
|
0
|
1
|
Emergency
|
whether to start the first level response before January 24
|
31
|
0.581
|
0.502
|
0
|
1
|
Notes: Data were obtained from the National Health Commission of China (as of May 2, 2020), 2015 China 1% National Population Sample Survey, 2015 China Statistical Yearbook, Ministry of Land and Resources of China, official website of the China Railway Corporation, and local government website. The research area of this article covers 31 provinces, municipalities, and autonomous regions in China.
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
|
Notes: PHM, number of people who migrated from Hubei to another province; PMH, number of people who migrated from another province to Hubei; P, number of permanent residents in each province; NCOV, number of infected people. “Rank” represents sorting the value of each variable from high to low. The data of PHM and PMH were obtained from the 2015 China 1% National Population Sample Survey, the data of P were obtained from the 2015 China Statistical Yearbook, and the data of NCOV were obtained from the China’s National Health Commission (as of May 2, 2020).
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.