Comparative Analysis of Early Dynamic Trends in Novel Coronavirus Outbreak: a Modeling Framework”

Supplementary Material for “Comparative Analysis of Early Dynamic Trends in Novel Coronavirus Outbreak: a Modeling Framework”

1750 80 600 1500

60 1250 500

1000 400 40 750 miles 300 500

daily total_hours_air 20 daily total_hours_rail 200 250

0 0 100 Jilin Jilin Tibet Tibet Anhui Hubei Hebei Hubei Fujian Fujian Gansu Gansu Henan Henan Hunan Jiangxi Tianjin Jiangxi Tianjin Shanxi Beijing Shanxi Beijing Hainan Hainan Jiangsu Jiangsu Yunnan Ningxia Yunnan Ningxia Enshi Qinghai Sichuan Sichuan Shannxi Xinjiang Shannxi Xinjiang Guizhou Guizhou Guangxi Guangxi Ezhou Liaoning Liaoning Zhejiang Zhejiang Shiyan Shanghai Shanghai Xiantao Shandong Yichang Suizhou Shandong Xiaogan Jingmen Tianmen Xianning Chongqing Chongqing Jingzhou Huangshi Qianjiang Guangdong Guangdong Xiangyang Heilongjiang Heilongjiang Huanggang Shennongjia InnerMongolia InnerMongolia (a) (b) (c)

0.8 0.30 0.7

0.6 0.25

0.5 0.20

0.4 0.15 0.3 migration rate

migration rate 0.10 0.2 0.05 0.1 0.00 0.0 Jilin Tibet Anhui Hebei Fujian Tianjin Gansu Hunan Henan Beijing Shanxi Jiangxi Hainan Enshi Ningxia Jiangsu Qinghai Yunnan Ezhou Xinjiang Shannxi Sichuan Guizhou Guangxi Shiyan Liaoning Zhejiang Xiantao Shanghai Yichang Suizhou Xiaogan Jingmen Shandong Tianman Xianning Jingzhou Chongqing Huangshi Qianjiang Guangdong Xiangyang Heilongjiang Huanggang Shennongjia InnerMongolia (d) (e)

Figure 1: (a) Daily average total traveling hours through airplane from Wuhan; (b) daily total traveling hours through railway from Wuhan; (c) highway mileage from Wuhan to the cities in Hubei; (d) and (e): migration rate from Wuhan during January 1 to 28, 2020.

Preprint submitted to Journal April 19, 2020 66000 645 70.5 64000 62000 70.0 630 60000 Prediction error Prediction error Prediction error 69.5 58000 615 56000 69.0 54000 3 4 5 6 7 8 9 3 4 5 6 7 8 9 4 5 6 7 8 9 10 11 12 13 14 15 16 10 11 12 13 14 15 16 10 11 12 13 m m m (a) 28 provinces (b) Hubei (c) Wuhan

● 12000 79375 40000 11000

● 10000 36000 68125 9000

● Prediction error Prediction error Prediction error

● 8000 32000 56875 7000

● ●

28000 ● 6000 45625 6 7 8 9 6 7 8 9 8 9 10 11 10 11 12 13 14 10 11 12 13 14 m m m (d) Australia (e) Austria (f) Belgium

● ● ● ● 51000 2525.0 213750

● 49625

2487.5 ● 48250 ●

201250 ● 2450.0 ● ● ● 46875

● Prediction error Prediction error Prediction error

● ● 2412.5 45500 ● 188750 2375.0 44125

●

● ● ● 2337.5 176250 42750 5 6 7 8 9 5 6 7 8 9 5 6 7 8 9 10 11 10 11 m m m (g) Brazil (h) Canada (i) Chile 1250 ● ● ● 7900 17100 1225 6850 15550

1200 ● ●

● ● 5800 1175 14000

● Prediction error Prediction error Prediction error ● ● ● 1150 ● 4750 12450 ●

1125 ● ●

● ● ● 3700 10900 6 7 8 9 5 6 7 8 9 5 6 7 8 9 10 11 10 10 m m m (j) Colombia (k) Czechia (l) Denmark

● ● ● ● ● 10917600 2888

●

● ● 3087.5 10771750 2850

● 2812 10625900 ● 3012.5 Prediction error Prediction error Prediction error ●

● 2775 ● 10480050 2937.5 ● ● ● ● 2738 10334200 5 6 7 8 9 7 8 9 5 6 7 8 9 10 11 12 10 m m m (m) Dominican Republic (n) Finland (o) France

Figure 2: Prediction error vs m by countries. 2 ● ● ● ● 37700.0 2580100 2975

●

● 2750

● 33275.0 2230350

● 2525 2300 28850.0 1880600 Prediction error Prediction error Prediction error 2075

● ● 1850 24425.0 1530850 ● ● ● ● 1625

● ● ● 1400 20000.0 1181100 5 6 7 8 9 8 9 5 6 7 8 9 10 11 12 10 11 m m m (a) Germany (b) India (c) Indonesia

● ● ● 28700 4150 252200

● 4100 ● ● 28000 229200 4050

●

● 4000 27300 206200 Prediction error Prediction error Prediction error ● 3950

● ● ● 26600 183200 3900

● ● 3850 ● ● 160200 25900 7 8 9 5 6 7 8 9 6 7 8 9 10 11 10 10 m m m (d) Iran (e) Ireland (f) Israel

● ● ● ● 91500 45400.0 13358200 74650

● 42525.0 11771250

● 57800 39650.0 10184300 Prediction error Prediction error Prediction error

●

● 40950 ● 36775.0 8597350

● ● ● ● ● ● ● ● ● ● ● 24100 33900.0 7010400 8 9 6 7 8 9 3 4 5 6 7 10 11 12 13 14 15 10 11 12 m m m (g) Italy (h) Japan (i) Korea South

● ● ● ● 1500 4238 2000

● 4175 1450

● ●

1975 ●

● 4112 1400 ●

● 4050 1950 Prediction error Prediction error ● Prediction error ● 1350 ● ● 3988 1300 ● 1925 ● ● 3925 ●

● ● ● 1250 3862 5 6 7 8 9 8 9 6 7 8 9 10 10 11 12 13 14 15 10 11 12 13 m m m (j) Luxembourg (k) Malaysia (l) Mexico

● ● ● 47100 11250 7887.5

● 39350 ● 7850.0 ● 9950 ●

● 9300 31600 7812.5

● Prediction error Prediction error Prediction error 8650

● ● 7775.0 8000 23850 ●

● 7350

● 7737.5

● ● ● 16100 6700 5 6 7 8 9 4 5 6 7 8 9 5 6 7 8 9 10 m m m (m) Netherlands (n) Norway (o) Pakistan

Figure 3: Prediction error vs m by countries. 3 ● ● ● ● 4325 2075 4250 10225.0

● 2050 4175 ● ●

2025 ● ● ● 9950.0 4100 Prediction error Prediction error Prediction error 2000 4025

● ● 9675.0 1975

● 3950

● ● ● 1950 3875 8 9 4 5 6 7 6 7 8 9 9400.0 10 11 12 13 10 11 m m m (a) Panama (b) Philippines (c) Poland

● ● ● 6700 17000 6550 10975

● 6400 15950

● ● ● 6250 10325

●

● ● 6100 14900 ●

● Prediction error Prediction error Prediction error 9675 5950 ● 13850 9350 5800 ●

● 9025

● 5650 ● ● ● 12800 8700 9 5 6 7 8 9 5 6 7 8 9 10 11 12 13 10 11 10 11 m m m (d) Portugal (e) Romania (f) Russia

● ● ● 3600 24800 3126100 ● 3425

● 3250 19750 ● 2848525

● 3075

●

● 14700 2900 2570950 Prediction error Prediction error Prediction error 2725

● 9650 2293375

2550 ● ● ● ●

● 2375 ● ● ● 4600 2015800 7 8 9 4 5 6 7 8 9 6 7 8 9 10 11 10 11 12 m m m (g) Saudi Arabia (h) Singapore (i) Spain

● ● ● ● 5925.0

104800 ● ●

● 562

5887.5 ● ● 97350 5850.0

● 89900 ● ● Prediction error Prediction error Prediction error 5812.5 550 82450

● 5775.0

●

● ● ● 75000 8 9 9 7 8 9 5737.5 10 11 12 13 10 11 12 13 10 11 12 m m m (j) Sweden (k) Switzerland (l) Thailand

● ● ● ● ● ●

165000 ● 7844500 681600.0 147425 6960300 623275.0

● 129850 6076100

564950.0 ● Prediction error Prediction error Prediction error

● ● ● ● 112275 5191900 506625.0

●

● ● ● ● ● 94700 4307700 448300.0 3 4 5 6 7 8 9 4 5 6 7 7 8 9 10 11 12 13 14 m m m (m) Turkey (n) US (o) United Kingdom

Figure 4: Prediction error vs m by countries. 4 m oiia Republic Dominican (m) eta_t eta_t eta_t eta_t eta_t

0.50 0.62 0.74 0.86 0.98 0.84 0.91 0.97 1.04 0.86 0.95 1.03 1.12 1.20 0.84 0.88 0.92 0.96 1.00 0.1 0.5 0.9 1.3 1.7 2.1 2.5 ● ● ● 2020−03−19 2020−03−10 2020−03−08 2020−02−29 2020−01−21 ● ● 2020−03−01 ● 2020−03−11 2020−03−09

2020−03−20 ● ● 2020−03−02 2020−01−22 2020−03−12 2020−03−10 provinces 28 (a)

● 2020−03−03 ● 2020−03−21 2020−03−13 ● 2020−03−11 2020−03−04 2020−01−23 ● ●

● 2020−03−12 2020−03−05

2020−03−14 Australia (d) j Colombia (j) 2020−03−22 ● 2020−01−24

● 2020−03−06 2020−03−15 2020−03−13 ● ● 2020−03−07 2020−01−25 2020−03−23 ● 2020−03−14

2020−03−16 ● 2020−03−08 g Brazil (g) ● 2020−03−15 ● 2020−03−09 2020−01−26 2020−03−24 2020−03−17 ●

● 2020−03−16 2020−03−10

2020−03−18 ● 2020−01−27 ● 2020−03−11

2020−03−25 ● 2020−03−17

2020−03−19 ● 2020−03−12 2020−03−18 2020−01−28 ● ●

● 2020−03−13 2020−03−26 2020−03−20 2020−03−19 ● 2020−03−14 2020−01−29 ●

● 2020−03−21 2020−03−27 2020−03−20 2020−03−15 ● 2020−03−22 2020−03−21 ● 2020−03−16 2020−01−30 ● ● ● 2020−03−17 2020−03−28 2020−03−23 2020−03−22 2020−01−31 ●

● 2020−03−18 2020−03−29 ● 2020−03−24 2020−03−23 2020−03−19

● ● 2020−02−01 2020−03−25 2020−03−24 2020−03−20 ● ● 2020−03−30 2020−03−26 ● 2020−03−25 2020−03−21 2020−02−02 ●

● 2020−03−22 2020−03−31 ● 2020−03−27 2020−03−26 2020−02−03

● 2020−03−23 2020−03−28 ● 2020−03−27 2020−03−24 ●

● 2020−02−04 2020−04−01 ● 2020−03−29 2020−03−28 2020−03−25 ●

● ● 2020−03−26 2020−02−05 2020−04−02 2020−03−30 2020−03−29 ● 2020−03−27 ● 2020−03−30

● 2020−02−06

2020−03−31 ● 2020−03−28 2020−04−03 ● 2020−03−31 2020−03−29 2020−04−01 ● 2020−02−07 ●

● 2020−04−01 2020−03−30 2020−04−04 2020−04−02 ●

iue5: Figure 2020−03−31

● 2020−04−02 2020−02−08 ● 2020−04−03 ● 2020−04−01 2020−04−05 2020−04−03 ●

2020−04−04 ● 2020−04−02 2020−02−09 ● 2020−04−04

● 2020−04−03

2020−04−06 ● 2020−04−05 2020−04−05 2020−04−04 2020−02−10 ● ● 2020−04−06 ● 2020−04−05 2020−04−07 2020−04−06 2020−02−11 ● 2020−04−07 ● 2020−04−06 ● 2020−04−07 ● 2020−04−08 ● 2020−04−07 2020−02−12 2020−04−08 2020−04−08 2020−04−08 2020−04−09 ● 2020−04−09 ● 2020−04−09 ● 2020−04−09 2020−02−13

h siainof estimation The eta_t eta_t eta_t eta_t eta_t

0.84 0.98 1.12 1.26 1.40 0.78 0.86 0.94 1.02 0.84 0.91 0.97 1.04 0.78 0.83 0.89 0.94 1.00 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

2020−03−05 ● 2020−03−03 ● 2020−02−27 ● 2020−02−29 ●

● 2020−01−21 2020−03−06 ● 2020−03−04 2020−02−28 2020−03−01 ● ● ● 2020−02−29 2020−03−02 2020−01−22 2020−03−07 2020−03−05 ● ● ● 2020−03−01 2020−03−03 2020−03−08 2020−03−06 ● ● 2020−03−02 2020−01−23 ● 2020−03−04 2020−03−09 2020−03−07 ● ● 2020−03−03

● ● 2020−03−05 2020−03−10 2020−03−08 2020−03−04 2020−01−24 ●

● 2020−03−06 ● 2020−03−09

n Finland (n) 2020−03−05 h Canada (h) k Czechia (k)

2020−03−11 ● ● 2020−03−07

e Austria (e) 2020−01−25 ● 2020−03−10 2020−03−06 ● 2020−03−12 ● 2020−03−08 b Hubei (b) ● 2020−03−11 2020−03−07 ● 2020−01−26

● 2020−03−09 2020−03−13 2020−03−08 ● 2020−03−12 ● 2020−03−10 2020−03−14 ● 2020−03−09 2020−01−27 ● 2020−03−13 ● 2020−03−11 2020−03−15 ● 2020−03−10 ●

● 2020−03−14 2020−03−12 2020−03−16 ● 2020−03−11 2020−01−28 ●

● 2020−03−15 2020−03−13

● 2020−03−12 2020−03−17 2020−03−16 ● 2020−03−14 ● 2020−03−13 2020−01−29 ● 2020−03−18 2020−03−17 2020−03−14 ● 2020−03−15 ● ● 2020−03−19 2020−03−18 ● 2020−03−15 2020−03−16 2020−01−30 ● ● ● 5 2020−03−20 2020−03−19 2020−03−16 2020−03−17 ●

● 2020−01−31 2020−03−21 ● 2020−03−17 2020−03−18 2020−03−20 ● ● ● 2020−03−18 2020−03−19 2020−03−22 2020−03−21 ● 2020−02−01 ● ● 2020−03−19 2020−03−20 2020−03−23 2020−03−22 ●

● 2020−03−20 ● 2020−03−21 2020−02−02 2020−03−24 2020−03−23 2020−03−21 ● ● 2020−03−22 2020−03−25 ● 2020−03−24 2020−03−22 ● 2020−03−23 2020−02−03 ● ● 2020−03−26 ● 2020−03−25 2020−03−23 2020−03−24 ● ● ● 2020−03−26 2020−03−24 2020−02−04 2020−03−27 ● 2020−03−25 ●

● 2020−03−25 2020−03−27 ● 2020−03−26 2020−02−05 2020−03−28 ● 2020−03−26 ●

2020−03−28 ● 2020−03−27

2020−03−29 ● 2020−03−27 ● 2020−03−29 ● 2020−03−28 2020−02−06

2020−03−30 ● 2020−03−28 ● ● 2020−03−30 2020−03−29

2020−03−31 ● 2020−03−29 2020−02−07 ● 2020−03−30 ● 2020−03−31 2020−03−30 η ● 2020−04−01 ● 2020−03−31

● 2020−04−01 2020−03−31 2020−02−08 ● 2020−04−02 ● 2020−04−01 2020−04−01 ● 2020−04−02 ● t ● 2020−04−02 2020−02−09 2020−04−03 2020−04−03 2020−04−02 ● ● 2020−04−04 ● 2020−04−03 2020−04−03

2020−04−04 ● ● 2020−02−10 2020−04−05 ● 2020−04−04 2020−04−04 2020−04−05 ● ycountries. by ● ● 2020−04−05 2020−04−05 2020−04−06 2020−04−06 ● 2020−02−11

● 2020−04−06

● 2020−04−06 2020−04−07 2020−04−07 2020−04−07 ● 2020−04−07 ●

● 2020−02−12 2020−04−08 2020−04−08 2020−04−08 ● 2020−04−08 2020−04−09 ● 2020−04−09 ● 2020−04−09 ● 2020−04−09 2020−02−13

eta_t eta_t eta_t eta_t eta_t

0.70 0.78 0.86 0.94 0.81 0.87 0.93 0.99 1.06 1.12 1.18 0.85 0.88 0.90 0.93 0.95 0.98 0.92 0.93 0.95 0.96 0.98 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 ● ● ● 2020−02−27 ● 2020−02−29 2020−03−10 2020−03−01 ● ●

● 2020−01−20 2020−02−28 2020−03−01 ● 2020−03−02 ● ●

2020−03−11 ● 2020−02−29 2020−03−02 ● 2020−03−03 2020−01−21 ● ● 2020−03−01 2020−03−03 2020−03−12 ●

● 2020−03−04 ● ● 2020−03−02 2020−03−04 2020−03−13 ● 2020−01−22 ● 2020−03−05 ● ●

2020−03−03 ●

● 2020−03−05 2020−03−06

● 2020−03−14 2020−01−23 2020−03−04 ● l Denmark (l) ● ● 2020−03−06 2020−03−07 ● ●

2020−03−07 ● 2020−01−25 ● ● 2020−03−09 2020−03−10 ● 2020−03−17

2020−03−08 ● i Chile (i) ● 2020−03−10 ● 2020−01−26 2020−03−09 ● 2020−03−11 2020−03−18 ● ● 2020−03−11

2020−03−10 ● ● 2020−03−12 ● ● 2020−03−12 2020−03−19 2020−01−27

2020−03−11 ● 2020−03−13 ● ● ● 2020−03−13 2020−03−12 ● 2020−03−20 2020−03−14 2020−01−28 ● ●

2020−03−14 ●

2020−03−13 ● 2020−03−15 ●

2020−03−21 ● 2020−03−14 2020−03−15 2020−01−29 ● ● 2020−03−16 ● 2020−03−15 2020−03−16 2020−03−22 ● ●

● 2020−03−17 ● 2020−03−16 2020−03−17 ● 2020−01−30

● 2020−03−23 ● 2020−03−18 ●

2020−03−17 2020−03−18 ● ● ● 2020−03−24 2020−03−19 2020−01−31 2020−03−18 2020−03−19 ● ● ● ● 2020−03−20 2020−03−19 2020−03−20 2020−03−25 ● 2020−02−01 ● ● 2020−03−21 ● 2020−03−20 2020−03−21 ● ● ● 2020−03−26 2020−03−22 2020−02−02 2020−03−21 ● 2020−03−22 ● ● ● 2020−03−27 2020−03−23 2020−03−22 2020−03−23 ● ● ● 2020−03−23 ● 2020−03−24 2020−02−03 2020−03−24 2020−03−28 ● ● ●

2020−03−24 ● 2020−03−25 ● ● 2020−03−25 2020−02−04 2020−03−25 ● 2020−03−29 2020−03−26 ● ● ● 2020−03−26 2020−03−26 ● 2020−03−30 2020−03−27 2020−02−05 ●

2020−03−27 ● ● 2020−03−27 ● 2020−03−28 ●

2020−03−28 2020−03−31 ● 2020−03−28 ● 2020−02−06 ● 2020−03−29 ●

2020−03−29 ● 2020−03−29 ● 2020−04−01

● 2020−03−30

2020−03−30 ● ● 2020−02−07 2020−03−30 ● 2020−04−02 ● 2020−03−31 2020−03−31 ●

2020−03−31 ● ● ● 2020−04−01 2020−04−03 2020−04−01 2020−02−08 ●

2020−04−01 ● ● ● 2020−04−02 2020−04−02 ●

2020−04−02 ● 2020−04−04 2020−02−09 ● 2020−04−03 2020−04−03 ● ●

2020−04−03 ● ● 2020−04−04 2020−04−05 2020−04−04 2020−02−10

2020−04−04 ● ● ● ● 2020−04−05 2020−04−06 2020−04−05

2020−04−05 ● ● ●

● 2020−02−11 2020−04−06 2020−04−06 2020−04−06 ● ● 2020−04−07 ●

2020−04−07 2020−04−07 ● 2020−04−07 ● ●

● 2020−02−12 2020−04−08 2020−04−08 2020−04−08 2020−04−08 ● ● ● 2020−04−09 ● 2020−04−09 2020−04−09 2020−04−09 2020−02−13 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

0.96 ● ● 0.95 ● ●

● 0.94 ● ● ● ●

0.82 ● ● ● 0.94 ● ● ●

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.86 ● eta_t eta_t ● eta_t ●

0.68 ● ● ● ● 0.93 ● 0.78 0.54 0.92 0.70 2020−02−26 2020−02−27 2020−02−28 2020−02−29 2020−03−01 2020−03−02 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 (a) Germany (b) India (c) Indonesia 0.95

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.95 ● ● ● ● ● ● ● 0.95 ● ● ● ● ● ● 0.90 ● ●

● 0.93 ● ● ● ● ● ● ● ● ● 0.91 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.92 ● 0.85 ●

eta_t ● eta_t ● eta_t ● 0.88 0.80 0.90 0.75 0.84 0.89 2020−02−19 2020−02−21 2020−02−23 2020−02−25 2020−02−27 2020−02−29 2020−03−02 2020−03−04 2020−03−06 2020−03−08 2020−03−10 2020−03−12 2020−03−14 2020−03−16 2020−03−18 2020−03−20 2020−03−22 2020−03−24 2020−03−26 2020−03−28 2020−03−30 2020−04−01 2020−04−03 2020−04−05 2020−04−07 2020−04−09 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 (d) Iran (e) Ireland (f) Israel 0.95

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 1.05 ● ● ● ● ●

● 1.00 ● ● ● ● ● ● 1.02

0.90 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.95 0.99 ● ● ● ● ● ● ● ● ● ● ● ● 0.85 ● ● ● eta_t eta_t ● eta_t ● ● ● ● ● ● ● ● ● 0.95 0.90 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.80 ● ● 0.92 0.85 0.89 0.82 0.75 2020−02−21 2020−02−23 2020−02−25 2020−02−27 2020−02−29 2020−03−02 2020−03−04 2020−03−06 2020−03−08 2020−03−10 2020−03−12 2020−03−14 2020−03−16 2020−03−18 2020−03−20 2020−03−22 2020−03−24 2020−03−26 2020−03−28 2020−03−30 2020−04−01 2020−04−03 2020−04−05 2020−04−07 2020−04−09 2020−02−14 2020−02−16 2020−02−18 2020−02−20 2020−02−22 2020−02−24 2020−02−26 2020−02−28 2020−03−01 2020−03−03 2020−03−05 2020−03−07 2020−03−09 2020−03−11 2020−03−13 2020−03−15 2020−03−17 2020−03−19 2020−03−21 2020−03−23 2020−03−25 2020−03−27 2020−03−29 2020−03−31 2020−04−02 2020−04−04 2020−04−06 2020−04−08 2020−01−24 2020−01−26 2020−01−28 2020−01−30 2020−02−01 2020−02−03 2020−02−05 2020−02−07 2020−02−09 2020−02−11 2020−02−13 2020−02−15 2020−02−17 2020−02−19 2020−02−21 2020−02−23 2020−02−25 2020−02−27 2020−02−29 2020−03−02 2020−03−04 2020−03−06 2020−03−08 2020−03−10 2020−03−12 2020−03−14 2020−03−16 2020−03−18 2020−03−20 2020−03−22 2020−03−24 2020−03−26 2020−03−28 2020−03−30 2020−04−01 2020−04−03 2020−04−05 2020−04−07 2020−04−09 (g) Italy (h) Japan (i) Korea South 0.98 1.00 0.95

● 0.99 0.95 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

0.90 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.92 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● eta_t eta_t eta_t 0.85 0.97 0.88 0.96 0.80 0.95 0.85 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−02−27 2020−02−28 2020−02−29 2020−03−01 2020−03−02 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 (j) Luxembourg (k) Malaysia (l) Mexico

0.96 ● ● ● ● ● ● ● 1.00 0.99

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.97 ● ● ● 0.92 ● ● ● ● ● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ● 0.93 ● ● ● ● ● eta_t eta_t ● ● eta_t ● ● 0.94 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

0.88 ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.91 ●

0.88 ● 0.84 0.88 2020−02−28 2020−02−29 2020−03−01 2020−03−02 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−02−28 2020−02−29 2020−03−01 2020−03−02 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 (m) Netherlands (n) Norway (o) Pakistan

Figure 6: The estimation of ηt by countries. 6 0.97 0.98

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.96 ● ● ● 0.95 0.91

● 0.96 ● ●

● 0.94

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

0.84 ●

● eta_t eta_t

● 0.95 ● eta_t 0.78 0.92 0.91 0.94 0.71 0.90 0.64 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 (a) Panama (b) Philippines (c) Poland 0.99 1.00 0.97 ●

● ● 0.98 0.98 ● ●

● 0.96 ● ● 0.96 ● ● 0.97 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.95 eta_t ● ● eta_t eta_t

● ● 0.93

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.96

● 0.94

● 0.91 0.95 0.93 0.89 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 (d) Portugal (e) Romania (f) Russia 1.03 0.94

0.98 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

1.00 ● ●

0.97 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

0.96 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● 0.93 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

eta_t eta_t ● eta_t ● ● ● ● ● ●

0.95 ● ● ●

0.96 ● ● ● ● ● ● ● ● ● ● ● ● ● 0.94 ● ● 0.93 0.93 0.92 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−01−23 2020−01−25 2020−01−27 2020−01−29 2020−01−31 2020−02−02 2020−02−04 2020−02−06 2020−02−08 2020−02−10 2020−02−12 2020−02−14 2020−02−16 2020−02−18 2020−02−20 2020−02−22 2020−02−24 2020−02−26 2020−02−28 2020−03−01 2020−03−03 2020−03−05 2020−03−07 2020−03−09 2020−03−11 2020−03−13 2020−03−15 2020−03−17 2020−03−19 2020−03−21 2020−03−23 2020−03−25 2020−03−27 2020−03−29 2020−03−31 2020−04−02 2020−04−04 2020−04−06 2020−04−08 2020−02−25 2020−02−26 2020−02−27 2020−02−28 2020−02−29 2020−03−01 2020−03−02 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 (g) Saudi Arabia (h) Singapore (i) Spain 0.92 0.99 0.94 0.91

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.98 0.93 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.90 eta_t eta_t eta_t 0.92 0.97 0.89 0.91 0.96 0.88 2020−02−29 2020−03−01 2020−03−02 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−02−29 2020−03−01 2020−03−02 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 (j) Sweden (k) Switzerland (l) Thailand 0.97

● ● ● ● ● ● ● ● ● ● ● ●

0.92 ● 1.09 ● ● ● ● ● ● ● ●

● ● 0.96 ● 0.87 ● ● ● 1.04 ● ● ● ●

eta_t eta_t ● eta_t ● ●

0.83 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● 0.95 ●

0.98 ● ●

0.78 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.93 0.94 0.74 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 2020−02−24 2020−02−26 2020−02−28 2020−03−01 2020−03−03 2020−03−05 2020−03−07 2020−03−09 2020−03−11 2020−03−13 2020−03−15 2020−03−17 2020−03−19 2020−03−21 2020−03−23 2020−03−25 2020−03−27 2020−03−29 2020−03−31 2020−04−02 2020−04−04 2020−04−06 2020−04−08 2020−02−26 2020−02−27 2020−02−28 2020−02−29 2020−03−01 2020−03−02 2020−03−03 2020−03−04 2020−03−05 2020−03−06 2020−03−07 2020−03−08 2020−03−09 2020−03−10 2020−03−11 2020−03−12 2020−03−13 2020−03−14 2020−03−15 2020−03−16 2020−03−17 2020−03−18 2020−03−19 2020−03−20 2020−03−21 2020−03−22 2020−03−23 2020−03−24 2020−03−25 2020−03−26 2020−03−27 2020−03−28 2020−03−29 2020−03−30 2020−03−31 2020−04−01 2020−04−02 2020−04−03 2020−04−04 2020−04−05 2020−04−06 2020−04−07 2020−04−08 2020−04−09 (m) Turkey (n) US (o) United Kingdom

Figure 7: The estimation of ηt by countries. 7 Anhui Beijing Chongqing 1200 500

600 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

1000 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 400 ● ● ● ●

● 500 ● ● ● ● ● ● ● ● ● ● ● 800 ● ● ● ● ● ●

● 400

● 300 ● ● ● ● ● 600 ● ● ● ● 300 Cum. Num. ● Cum. Num. Cum. Num. ●

200 ● ● ● 2020−02−21

400 ● ● ● 2020−02−19 200 ● 2020−02−23 ● ● ● ● ● ● ● ● 100 ● ● 200 ● ● 100 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 ● ● 0 0

2020−01−20 2020−01−29 2020−02−07 2020−02−16 2020−02−25 2020−01−20 2020−01−29 2020−02−07 2020−02−16 2020−02−25 2020−01−20 2020−01−29 2020−02−07 2020−02−16 2020−02−25

Date Date Date

Fujian Gansu Guangdong 350 1500 120

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 ● ● ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 250 ● ● ● ● ● 80 ● 1000 ● ● ● ● ● 200 ● ● ● ●

60 ● ● ● ● Cum. Num. Cum. Num. Cum. Num. ● ● 150 2020−02−19 ●

● ● ● 2020−02−20 40 500 ● ● 2020−02−20

100 ● ● ● ● ● ● ● ● ● 20

50 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 ● ● 0 0

Date Date Date

Guangxi Guizhou Hainan 300 200 200 ● ● ● ● ● ● ● ● ● ● ● ● 250 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

150 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● 150

200 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

150 ● ● 100 ● 100 Cum. Num. ● Cum. Num. Cum. Num. ● ● ● ● ● ● 2020−02−20 ●

100 ● ● ● ● ● ● ● 2020−02−22 ●

50 ●

50 ● ● ● ● ● ●

50 ● ● 2020−02−21 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● ● 0 ● ● 0 0

Date Date Date

Hebei Heilongjiang Henan 1500 400 600

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 500 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

300 ● ● ● ● ● ● ● ● 1000 ● 400 ● ● ● ● ● ● ● ● ● ● ● ● 200 300 ● ● ● Cum. Num. Cum. Num. Cum. Num. ● ● ● ● ●

● ● 500 200 ● ● 2020−02−21 ● ● ● ●

100 2020−02−22 ● ● ● ● ●

100 ● ● ● 2020−02−24 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

0 ● 0 ● 0

Date Date Date

Hunan InnerMongolia Jiangsu 1200

● ● 80 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 1000 ● ● ●

● 600 ● ● ● ● ● ● ● ● ● ● ● ● ●

800 ● 60 ● ● ●

● ● ● ● ● ● ● 400 ● ● ● 600 ● ● ● Cum. Num. Cum. Num. Cum. Num. 40 ● ● ● ● ● ● 2020−02−22 ● 400 ● ● ● 2020−02−22

● 200 ● ● ● 2020−02−19 ● 20 ● ● ● ●

200 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 ● ● ● 0

Date Date Date

Figure 8: The estimated (red-solid) and observed (black-dotted) number of infectious over time t, as well as 95% CI (red-dashed) of the estimators for 28 Provinces in China. The green dots refer to the number of reported cases which were not included for the model fitting.

8 Jiangxi Jilin Liaoning 1200 150 120 1000 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

800 ● ● ● ● ● ● ● ● 80

● 100 ● ● ● ● ● ● ● ● 600 ● ● ● 60 ● ● Cum. Num. ● Cum. Num. Cum. Num. ● ● 2020−02−21 ● ● 400 50 ● 40 ● ● ● ● 2020−02−22 ● ● ● ● 200 ● 20 ● 2020−02−22 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

Date Date Date

Ningxia Shaanxi Shandong 100 300 600

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

80 ● ● ● ● ● ● ● ● ● ● ● ● 250 ● ● ● ● ● ● ● 500 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 200 400 60 ● ● ● ● ● ● ● ● ● ● ●

150 ● ● 300 Cum. Num. Cum. Num. Cum. Num. ● ● ●

40 ● ● ● ● ● ● ● ● 2020−02−22 100 ● 200 ● ● 2020−02−22 ● 2020−02−20 ● ● ●

20 ● ● ●

50 ● ● ● ● 100 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0

● ● ● 0 0

Date Date Date

Shanghai Shanxi Sichuan 600 400

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 150 ● ● ●

● 500 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 ● ● ● ● ● ● ● ● ● ●

400 ● ● ● ● ● ●

100 ● ● ● ● ● ● 300 200 ● ● ● ● ● Cum. Num. Cum. Num. Cum. Num. ● 2020−02−20 ● ● ● 2020−02−20 ● ● 200 ●

50 ● ● 2020−02−20 ●

100 ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

Date Date Date

Tianjin Xinjiang Yunnan 100 200 150 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● 80 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 150 ● ● ● ● ● ● ● ● ● ● 60 ●

100 ● ● ● ● ● ● ● ● ● ● 100 Cum. Num. Cum. Num. ● Cum. Num. ● 2020−02−20 ● ● ● ● ● 40 ● ● ● ● ● ● 50

● ● ● ● 50 ● ● 2020−02−23 20 ● ● ● 2020−02−19 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 ●

● ● ● 0 0

Date Date Date

Zhejiang 1500

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 1000 ●

●

● ● Cum. Num. ● 2020−02−23 ● 500 ●

●

● ● ● ● ● ● ● ● 0

2020−01−20 2020−01−29 2020−02−07 2020−02−16 2020−02−25

Date

Figure 9: The estimated (red-solid) and observed (black-dotted) number of infectious over time t, as well as 95% CI (red-dashed) of the estimators for 28 Provinces in China. The green dots refer to the number of reported cases which were not included for the model fitting.

9 Enshi Ezhou Huanggang 300 1400 3000 1200 250 ● ●

2500 ● ● ● ● ● ● ● 1000 ● ● ● ● 200 ● ● 2000 ● ● ● ● ● 800 ● ● ●

● 150 ● ● ● 1500

● 600 ● ● ● ● 2020−02−18 ● ●

100 ● 2020−02−22

● 1000 ● ● 400 ● ● ● ● ● 2020−02−22 ● ● ● ● 50

● 500

● 200 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 ● ● ● 0 0

2020−01−21 2020−01−30 2020−02−08 2020−02−17 2020−02−26 2020−01−21 2020−01−30 2020−02−08 2020−02−17 2020−02−26 2020−01−21 2020−01−30 2020−02−08 2020−02−17 2020−02−26

Date Date Date

Huangshi Jingmen Jingzhou 1500 1000 1000 ● ● ● ● 800 ● ● ● ● ● ● ● ● ● 800 ● ● ● ● ● ● 1000 ● ● ● ● 600 ● ● 600 ● ● ● ● ● ● ●

● 400 ● 400 ● 2020−02−21 ● ● 500

● ● 2020−02−22 ● ● 2020−02−21 ● ● ● 200

200 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

Date Date Date

Qianjiang Shiyan Suizhou 150 1500

600 ● ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● ● ● ● 1000 ● ● ● ● ● ● 400

● ● ● ● ● ● ● ● ● 50

● ● 2020−02−21 500 ●

200 ● ● ● 2020−02−19 ● 2020−02−22 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 ● ● ● ● ● 0 0

Date Date Date

Tianmen Xiangyang Xianning 1400 600 500

1200 ● ● ● ● ● ● ● ● ● ● ● 500 ● ● 1000 400 ● ●

● ● ● ●

400 ● ● 800 ● ● ● 300

● ● ● 300

600 ● ● ● 2020−02−20 ● 200 ● ● 2020−02−21 ● ● 200 400 ● ● ● ● ● ● ● ● ● 2020−02−21 ● 100 ● ● 100

● 200 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 ● ● ● ● 0

Date Date Date

Xiantao Xiaogan Yichang 700 4000 1000 600

● ● ●

● 3000 ● ●

800 ● 500 ● ● ● ● ● ● ● ● ● ● ● ● ● 400 ● ●

● 600 ● ● 2000 ● ● ● 300 ● ● ● 400 ● ● 2020−02−21 ● ● 200 ● ● ● ● 1000 2020−02−21 ● 2020−02−22

● 200 ● ● ● ● 100 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

Date Date Date

Figure 10: The estimated (red-solid) and observed (black-dotted) cumulative number of infectious over time t, as well as 95% CI (red-dashed) of the estimators for the cities in Hubei.

10 Chile Israel Norway 8750 13125 14000

● ● ● ● 9375 6250 ● ● ● ● ●● ● 10000 ● ● ● ● ● ● ● ● ● Cum. Num. ● Cum. Num. Cum. Num. ● ● ● ● ● ● 5625 ● 3750 ● ● ● ● 6000 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 2020−05−07 ● ● ● ● ● ● ● ● ● ● ● ● 1875 ● 1250

2000 ● ● 2020−05−23 ●● ● ● ● ● ● ● ● ● ●● 2020−05−10 ● ● ● ●●●● ● ● ● ● ● ● ● ● ● ● ● ●●●●●●●●●●●● ● ● ● ● ● ● ● 0 0 0

2020−03−10 2020−03−23 2020−04−05 2020−04−18 2020−05−01 2020−05−14 2020−05−27 2020−03−03 2020−03−17 2020−03−31 2020−04−14 2020−04−28 2020−05−12 2020−05−26 2020−02−28 2020−03−12 2020−03−25 2020−04−07 2020−04−20 2020−05−03 2020−05−16 Date Date Date

Brazil Canada Colombia

● 2400

● 18000 ●

●

● 2100

● 17500 ● ● 1800

13500 ●

● ●

● 1500 ●

12500 ● ●

● 1200 ● ● 9000

● Cum. Num. Cum. Num. Cum. Num. ●

● 900 ● 6750 7500 ● ●

● ● ● ● 600 ● 4500 5000 ● ●

● ● ● ●

● 300 ●

2250 ● 2500 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

2020−03−08 2020−03−14 2020−03−20 2020−03−26 2020−04−01 2020−04−07 2020−02−27 2020−03−05 2020−03−12 2020−03−19 2020−03−26 2020−04−02 2020−04−09 2020−03−10 2020−03−15 2020−03−20 2020−03−25 2020−03−30 2020−04−04 2020−04−09 Date Date Date

Dominican_Republic Finland Czechia

● ●

● 2500 ● ● 2187.5

● ● 9625 ● ● ● ● 1875

● ● ● 1562.5 ● ●

6875 ● ● ● ● ● ● ● ● ●

● 1250 ● Cum. Num. Cum. Num. ● ● ●

Cum. Num. ● ● ● ● ● 937.5 ● 938 4125 ● ● ● ● ● ● ● ● ● ●

● ● 625 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 312

● 312.5 ● ● 1375 ● 2020−05−13 ● ● ● ●● ●● ● ● ● ●● ● ● ● ●●●●●●●●●● ● ● ● ● 0 0 0.0

2020−03−03 2020−03−19 2020−04−04 2020−04−20 2020−05−06 2020−05−22 2020−06−07 2020−03−19 2020−03−23 2020−03−27 2020−03−31 2020−04−04 2020−04−08 2020−03−05 2020−03−11 2020−03−17 2020−03−23 2020−03−29 2020−04−04 Date Date Date

France India Indonesia

● 3500

7000 ● ● ● ●

● ● 3062

● 6000 105000 ● ● ● ●

2625 ● ● 5000 ●

● 2188 ● 75000

● 4000 ● ● ● ● ● 1750 ● ● ● ● Cum. Num. Cum. Num. Cum. Num. 3000 ● ● ● ●

● 1312 ●

45000 ● ● ● ● ●

● 2000 ● ● 875 ● ● ● ● ● ● ● ● ● ● ● ● ●

● 1000 ● ● ● ● 438 ● ● 15000 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

2020−02−27 2020−03−05 2020−03−12 2020−03−19 2020−03−26 2020−04−02 2020−04−09 2020−03−04 2020−03−10 2020−03−16 2020−03−22 2020−03−28 2020−04−03 2020−04−09 2020−03−08 2020−03−14 2020−03−20 2020−03−26 2020−04−01 2020−04−07 Date Date Date

Figure 11: The estimated (red-solid) and observed (black-dotted) cumulative number of infectious over time t, as well as 95% CI (red-dashed) of the estimators by countries.

11 Japan Mexico Pakistan

● ● ●

● 4375 ● ● 3000 ● ● ●

● 3750 ● 2500

3500 ● ● ● ● 3125 ● ● ● 2000 ● ● ● ● 2500 2500 ● ● ●

● ● ● 1500 Cum. Num. ● ● Cum. Num. Cum. Num. ●

● 1875 ● ● ● ● ● ● ● ●

1500 ●

1000 ● ● ● ● ● 1250 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● 500 ● ●

625 ● ● ● ● ● ● ●

500 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

2020−02−14 2020−02−23 2020−03−03 2020−03−12 2020−03−21 2020−03−30 2020−04−08 2020−03−13 2020−03−18 2020−03−23 2020−03−28 2020−04−02 2020−04−07 2020−03−09 2020−03−14 2020−03−19 2020−03−24 2020−03−29 2020−04−03 2020−04−08 Date Date Date

Panama Philippines Poland

● ● ● ●

4000 ● 2500 ● ● ● ● 5000

● ● ● ● ●

2000 ● ●

● 3000 4000

● ● ● ●

● ●

1500 ● ● ● 3000

● ● ● 2000 Cum. Num. Cum. Num. Cum. Num. ● ● ● ●

1000 ● ● ● ● 2000 ● ● ● ● ● ● 1000 ● ● ● ● 500 ● ●

● ● ● 1000 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

2020−03−10 2020−03−15 2020−03−20 2020−03−25 2020−03−30 2020−04−04 2020−04−09 2020−03−05 2020−03−11 2020−03−17 2020−03−23 2020−03−29 2020−04−04 2020−03−07 2020−03−13 2020−03−19 2020−03−25 2020−03−31 2020−04−06 Date Date Date

Romania Russia Saudi_Arabia

● ● 3500 ● 10000

5000 ● ●

● 3000 ● ●

● ●

● 8000 ●

4000 ● 2500 ●

● ● ● ●

● 2000 6000

3000 ● ● ●

● ● ●

● ● Cum. Num. Cum. Num. Cum. Num. ● ● 1500 ● ● ● 4000 ● 2000 ● ● ● ● ● ● 1000 ● ● ● ● ● ● 2000

1000 ● ● ● ● 500 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

2020−03−04 2020−03−10 2020−03−16 2020−03−22 2020−03−28 2020−04−03 2020−04−09 2020−03−11 2020−03−16 2020−03−21 2020−03−26 2020−03−31 2020−04−05 2020−03−08 2020−03−14 2020−03−20 2020−03−26 2020−04−01 2020−04−07 Date Date Date

Singapore Sweden United_Kingdom

● ●

2000 ● ● ●

60000 ● ● 8000 ● ● ●

● ● ● 50000 1500 ● ● ● ● ●

6000 ● ● ●

● 40000 ● ● ● ● ● ● 1000 ● ● ● ● Cum. Num. Cum. Num. Cum. Num. ● ● 30000 4000 ● ● ● ● ● ● ● ● ● ● ● ● ● ● 20000 ● ●

500 ● ● ● ● ●

● 2000 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 10000 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0 0

2020−01−23 2020−02−05 2020−02−18 2020−03−02 2020−03−15 2020−03−28 2020−02−29 2020−03−07 2020−03−14 2020−03−21 2020−03−28 2020−04−04 2020−02−26 2020−03−04 2020−03−11 2020−03−18 2020−03−25 2020−04−01 2020−04−08 Date Date Date

Figure 12: The estimated (red-solid) and observed (black-dotted) cumulative number of infectious over time t, as well as 95% CI (red-dashed) of the estimators by countries.

12 Australia Austria Belgium 2020−03−28 2020−03−26 718 380 predict with m predict with m 2020−03−25 2020−04−05 2020−03−27 predict with m predict with m−1 predict with m−1 1416 predict with m−1 639 338 2020−03−25 predict with m−2 2020−04−05 predict with m−2 2020−03−27 predict with m−2 2020−04−05 559 296 1101 254 479 399 211 786 169 319 127 239 472 Number of cases per day Number of cases per day Number of cases per day 85 160 80 42 157 0 0 0

2020−03−01 2020−03−12 2020−03−23 2020−04−03 2020−04−14 2020−04−25 2020−05−06 2020−02−29 2020−03−12 2020−03−24 2020−04−05 2020−04−17 2020−04−29 2020−02−29 2020−03−12 2020−03−24 2020−04−05 2020−04−17 2020−04−29 Date Date Date

Brazil Canada Chile

predict with m 2020−05−22 predict with m 2020−04−08 predict with m 2020−04−07 367 1420

10216 predict with m−1 predict with m−1 predict with m−1 predict with m−2 predict with m−2 2020−04−08 predict with m−2 2020−05−21 2020−04−07

2020−04−07 286 1105 7946 2020−05−21 2020−04−06 204 789 5675 473 122 3405 Number of cases per day Number of cases per day Number of cases per day 82 41 158 1135 0 0 0

2020−03−08 2020−04−06 2020−05−05 2020−06−03 2020−07−02 2020−07−31 2020−08−29 2020−02−27 2020−03−18 2020−04−07 2020−04−27 2020−05−17 2020−06−06 2020−06−26 2020−03−10 2020−03−23 2020−04−05 2020−04−18 2020−05−01 2020−05−14 2020−05−27 Date Date Date

Colombia Czechia Denmark

predict with m 2020−04−30 predict with m 2020−04−01 predict with m 2020−08−01 276 predict with m−1 predict with m−1 7536 predict with m−1 predict with m−2 predict with m−2 predict with m−2 292 2020−04−29 245 2020−03−31 2020−08−01

2020−04−29 5861 2020−03−31 184 219 2020−07−31 4186 123 146 92 109 2512 Number of cases per day Number of cases per day Number of cases per day 73 61 31 36 837 0 0 0

2020−03−10 2020−03−28 2020−04−15 2020−05−03 2020−05−21 2020−06−08 2020−06−26 2020−03−03 2020−03−17 2020−03−31 2020−04−14 2020−04−28 2020−05−12 2020−05−26 2020−02−29 2020−04−18 2020−06−06 2020−07−25 2020−09−12 2020−10−31 2020−12−19 Date Date Date

Dominican_Republic Finland France

predict with m 2020−04−16 predict with m 2020−04−19 predict with m 2020−04−14 169 predict with m−1 predict with m−1 8438 predict with m−1 predict with m−2 2020−04−16 predict with m−2 predict with m−2 157 150 2020−04−18 2020−04−15 2020−04−14 137 131 2020−04−18 6563 117 112 2020−04−14 94 98 4688 75 78 59 56 2813 Number of cases per day Number of cases per day Number of cases per day 39 37 20 19 938 0 0 0

2020−03−19 2020−03−31 2020−04−12 2020−04−24 2020−05−06 2020−05−18 2020−03−05 2020−03−22 2020−04−08 2020−04−25 2020−05−12 2020−05−29 2020−06−15 2020−02−27 2020−03−21 2020−04−13 2020−05−06 2020−05−29 2020−06−21 2020−07−14 Date Date Date

Figure 13: The estimated (red-solid) and observed (black-dotted) cumulative number of infectious over time t, as well as 95% CI (red-dashed) of the estimators by countries.

13 Germany India Indonesia

predict with m 2020−03−31 predict with m 2020−08−07 predict with m 2020−04−24 327 5681 predict with m−1 predict with m−1 predict with m−1 predict with m−2 predict with m−2 predict with m−2 2020−04−24

2020−03−31 290 256776 2020−08−06 2020−04−23

4418 2020−03−30 218

192582 2020−08−06 181 3156 128388 109 1894 Number of cases per day Number of cases per day Number of cases per day 73 64194 36 631 0 0 0

2020−02−26 2020−03−12 2020−03−27 2020−04−11 2020−04−26 2020−05−11 2020−05−26 2020−03−04 2020−04−30 2020−06−26 2020−08−22 2020−10−18 2020−12−14 2021−02−09 2020−03−08 2020−03−29 2020−04−19 2020−05−10 2020−05−31 2020−06−21 2020−07−12 Date Date Date

Iran Ireland Israel

predict with m 2020−04−03 predict with m 2020−04−06 predict with m 2020−04−01 577 383 2460 predict with m−1 predict with m−1 predict with m−1 predict with m−2 predict with m−2 predict with m−2 2020−04−02 2020−04−06 512 2020−04−01 298

1913 2020−04−02 2020−04−05 2020−03−31 384 213 1366 256 128 820 Number of cases per day Number of cases per day Number of cases per day 85 128 43 64 273 0 0 0

2020−02−19 2020−03−06 2020−03−22 2020−04−07 2020−04−23 2020−05−09 2020−05−25 2020−03−08 2020−03−21 2020−04−03 2020−04−16 2020−04−29 2020−05−12 2020−05−25 2020−03−03 2020−03−14 2020−03−25 2020−04−05 2020−04−16 2020−04−27 2020−05−08 Date Date Date

Italy Korea South Luxembourg

predict with m 2020−03−25 predict with m 2020−03−04 predict with m 2020−03−27 428 5944 predict with m−1 2020−03−25 predict with m−1 predict with m−1 predict with m−2 2020−03−24 predict with m−2 predict with m−2 158 2020−03−26 2020−03−04 138 333 4623 2020−03−26 118 98

238 2020−03−03 3302 79 59 143 1981 Number of cases per day Number of cases per day Number of cases per day 95 39 20 48 660 0 0 0

2020−02−21 2020−03−06 2020−03−20 2020−04−03 2020−04−17 2020−05−01 2020−01−24 2020−02−09 2020−02−25 2020−03−12 2020−03−28 2020−04−13 2020−04−29 2020−03−10 2020−03−18 2020−03−26 2020−04−03 2020−04−11 2020−04−19 2020−04−27 Date Date Date

Malaysia Mexico Netherlands

predict with m 2020−03−29 predict with m 2020−05−23 predict with m 2020−04−03 181 1077 1931 predict with m−1 2020−03−29 predict with m−1 predict with m−1 predict with m−2 predict with m−2 2020−05−22 predict with m−2 2020−03−28 2020−04−03 2020−05−22 838 141 1502 2020−04−02 101 598 1073 81 60 644 359 Number of cases per day Number of cases per day Number of cases per day 40 20 120 215 0 0 0

2020−02−27 2020−03−10 2020−03−22 2020−04−03 2020−04−15 2020−04−27 2020−05−09 2020−03−13 2020−04−10 2020−05−08 2020−06−05 2020−07−03 2020−07−31 2020−08−28 2020−02−28 2020−03−11 2020−03−23 2020−04−04 2020−04−16 2020−04−28 Date Date Date

Norway Pakistan

predict with m 2020−03−23 predict with m 2020−08−05

predict with m−1 20471 predict with m−1 predict with m−2 predict with m−2 223 2020−03−22 2020−08−05 15922

167 2020−03−22 2020−08−04 11373 111 84 6824 Number of cases per day Number of cases per day 56 28 2275 0 0

2020−02−28 2020−03−11 2020−03−23 2020−04−04 2020−04−16 2020−04−28 2020−03−09 2020−04−23 2020−06−07 2020−07−22 2020−09−05 2020−10−20 2020−12−04 Date Date

Figure 14: The estimated (red-solid) and observed (black-dotted) cumulative number of infectious over time t, as well as 95% CI (red-dashed) of the estimators by countries.

14 Panama Philippines Poland

predict with m 2020−04−12 predict with m 2020−04−04 predict with m 2020−04−12 187 predict with m−1 predict with m−1 predict with m−1 predict with m−2 2020−04−12 predict with m−2 predict with m−2 2020−04−12 363 214 2020−04−11 2020−04−04 2020−04−11 146 317

161 2020−04−03 227 104 83 107 80 62 136 Number of cases per day Number of cases per day Number of cases per day 42 54 91 21 27 45 0 0 0

2020−03−10 2020−03−25 2020−04−09 2020−04−24 2020−05−09 2020−05−24 2020−06−08 2020−03−05 2020−03−17 2020−03−29 2020−04−10 2020−04−22 2020−05−04 2020−05−16 2020−03−07 2020−03−21 2020−04−04 2020−04−18 2020−05−02 2020−05−16 Date Date Date

Portugal Romania Russia

predict with m 2020−04−02 predict with m 2020−04−11 predict with m 2020−05−11 predict with m−1 2020−04−01 predict with m−1 5792 predict with m−1 predict with m−2 predict with m−2 predict with m−2 2020−04−01 2020−05−10 331 714 2020−04−11 2020−05−10 289 4505 2020−04−10 536 207 3218 357 124 1931 Number of cases per day Number of cases per day Number of cases per day 83 179 89 41 644 0 0 0

2020−03−03 2020−03−16 2020−03−29 2020−04−11 2020−04−24 2020−05−07 2020−03−04 2020−03−18 2020−04−01 2020−04−15 2020−04−29 2020−05−13 2020−05−27 2020−03−11 2020−04−01 2020−04−22 2020−05−13 2020−06−03 2020−06−24 2020−07−15 Date Date Date

Saudi_Arabia Spain Sweden

predict with m 2020−04−12 predict with m 2020−03−30 predict with m 2020−05−09 216 1106 predict with m−1 7578 predict with m−1 predict with m−1 predict with m−2 2020−04−12 predict with m−2 2020−03−30 predict with m−2 2020−05−09 2020−05−08 2020−04−11 2020−03−29 168 860 5894 120 614 4210 96 72 369 2526 Number of cases per day Number of cases per day Number of cases per day 48 24 123 842 0 0 0

2020−03−08 2020−03−23 2020−04−07 2020−04−22 2020−05−07 2020−05−22 2020−06−06 2020−02−25 2020−03−10 2020−03−24 2020−04−07 2020−04−21 2020−05−05 2020−05−19 2020−02−29 2020−03−30 2020−04−29 2020−05−29 2020−06−28 2020−07−28 2020−08−27 Date Date Date

Switzerland Thailand Turkey

predict with m 2020−03−27 predict with m 2020−03−28 predict with m 2020−04−11 3943 1105 predict with m−1 predict with m−1 predict with m−1 2020−03−27 2020−03−28 predict with m−2 predict with m−2 predict with m−2

117 2020−03−27 2020−03−26 2020−04−10 860 102 3067

88 2020−04−10 73 614 2190 58 44 368 1314 Number of cases per day Number of cases per day Number of cases per day 29 15 123 438 0 0 0

2020−02−29 2020−03−12 2020−03−24 2020−04−05 2020−04−17 2020−04−29 2020−03−09 2020−03−18 2020−03−27 2020−04−05 2020−04−14 2020−04−23 2020−03−15 2020−03−27 2020−04−08 2020−04−20 2020−05−02 2020−05−14 2020−05−26 Date Date Date

US United_Kingdom

predict with m 2020−04−09 predict with m 2020−04−13 5260

32923 predict with m−1 predict with m−1 2020−04−13 predict with m−2 predict with m−2 2020−04−09 2020−04−12 4091 25607

2020−04−08 2922 18291 1753 10974 Number of cases per day Number of cases per day 584 3658 0 0

2020−02−24 2020−03−12 2020−03−29 2020−04−15 2020−05−02 2020−05−19 2020−06−05 2020−02−26 2020−03−14 2020−03−31 2020−04−17 2020−05−04 2020−05−21 2020−06−07 Date Date

Figure 15: The estimated (red-solid) and observed (black-dotted) cumulative number of infectious over time t, as well as 95% CI (red-dashed) of the estimators by countries.

15 1.6 6 1.4 5 1.2 4 1 1.0 R_t R_t 3 0.8 2 0.6 1 0.4

2020−02−14 2020−02−22 2020−03−01 2020−03−09 2020−03−17 2020−03−25 2020−04−02 2020−01−23 2020−02−03 2020−02−14 2020−02−25 2020−03−07 2020−03−18 2020−03−29 2020−04−09 Date Date (a) Japan (b) Singapore

Figure 16: The curve of effective reproduction number for Japan and Singapore.

16 Table 1: Estimated sizes (95% CI) and observed size among 28 provinces in China Size Level Province baseline size Observation Prediction(CI 95%) Low risk Ningxia 1.63(0.34, 2.93) 42 52(38, 66) Jilin 1.64(0.39, 2.90) 62 65(50, 80) Tianjin 1.91(0.49, 3.34) 74 86(63, 109) Hainan 3.18(0.38, 5.99) 106 114(90, 138) Heilongjiang 3.48(0.88, 6.28) 252 288(239, 336) Liaoning 3.69(0.78, 6.59) 92 87(67, 107) InnerMongolia 4.14(0.99, 7.29) 44 55(41, 69) Gansu 4.27(1.12, 7.42) 64 75(59, 92) Guizhou 4.94(1.15, 8.73) 73 121(92, 150) Moderate risk Xinjiang 5.094(1.20, 8.99) 38 63(47, 79) Hebei 5.24(1.03, 9.45) 164 213(174, 251) Shanxi 6.25(1.68, 10.81) 93 107(92, 122) Yunnan 7.42(1.94, 12.90) 132 129(102, 156) Shaanxi 9.10(2.47, 15.73) 169 188(151, 227) Guangxi 11.35(3.03, 19.67) 170 185(153, 217) Anhui 11.86(1.89, 21.82) 628 646(584, 708) Jiangsu 11.97(2.95, 20.99) 390 444(408, 480) Shandong 12.94(3.49, 22.38) 361 392(346, 438) Zhejiang 13.42(3.66, 23.38) 980 724(554, 894) High risk Jiangxi 15.14(3.69, 26.59) 630 657(587, 727) Shanghai 16.01(4.14, 27.88) 262 257(226, 289) Fujian 16.35(4.20, 28.50) 220 238(205, 271) Chongqing 17.20(4.64, 29.76) 400 400(354, 446) Hunan 22.54(4.96, 40.11) 742 728(654, 802) Sichuan 23.41(6.13, 40.89) 332 389(349, 429) Beijing 28.46(7.09, 49.82) 286 332(284, 380) Henan 35.05(7.72, 62.38) 882 924(839, 1009) Guangdong 54.58(13.81, 95.35) 980 1030(917, 1143) Baseline size is the estimated number of cases exported from Wuhan using transportation and immigration data between December 1 2019 to January 23, 2020. Low risk: number of cases ă 5; Moderate risk: 5 ´ 15 and high risk: ą 15.