Ending day prediction of nCoV2019
27/06/2020
source('./predict.R')
## [1] "2020-06-26"
## country cum_confirm cum_heal cum_dead inc_r death_r dead_pm
## 1 France 161348 75351 29752 0.00 18.44 456
## 2 Belgium 61106 16918 9731 0.16 15.92 840
## 3 Italy 239706 186725 34678 0.12 14.47 574
## 4 United Kingdom 307980 1918 43230 0.00 14.04 637
## 5 Mexico 202951 149318 25060 3.10 12.35 194
## 6 Netherlands 50005 322 6103 0.18 12.20 356
## 7 Spain 294566 196958 28330 0.14 9.62 606
## 8 Canada 102622 65425 8504 0.37 8.29 225
## 9 Ecuador 53156 26097 4343 2.93 8.17 246
## 10 Sweden 65137 4971 5280 4.51 8.11 523
## 11 Algeria 12445 8920 878 1.61 7.06 20
## 12 Ireland 25405 23364 1727 0.04 6.80 350
## 13 Switzerland 31486 29000 1962 0.18 6.23 227
## 14 Romania 25697 18181 1579 1.63 6.14 82
## 15 China 85151 80012 4648 0.02 5.46 3
## 16 Japan 18315 16392 971 1.02 5.30 8
## 17 Indonesia 51427 21333 2683 2.47 5.22 10
## 18 United States 2506370 1052446 126839 1.70 5.06 383
## 19 Denmark 12836 11660 603 0.16 4.70 104
## 20 Iran 217724 177852 10239 1.22 4.70 122
## 21 Germany 194455 179464 9103 0.24 4.68 109
## 22 Brazil 1233147 649908 55054 3.31 4.46 259
## 23 Poland 33395 19218 1436 0.83 4.30 38
## 24 Egypt 61130 16338 2533 2.63 4.14 25
## 25 Guatemala 15619 2949 623 5.40 3.99 35
## 26 Austria 17522 16348 698 0.26 3.98 78
## 27 Portugal 40866 26633 1555 1.12 3.81 153
## 28 Iraq 39139 18051 1437 6.64 3.67 36
## 29 Philippines 34073 9182 1224 3.04 3.59 11
## 30 Colombia 80599 33349 2654 4.52 3.29 52
## 31 Peru 268602 156074 8761 1.48 3.26 266
## 32 Moldova 15453 8599 502 2.49 3.25 124
## 33 Bolivia 28503 7338 913 3.70 3.20 78
## 34 Czech Republic 10870 7649 345 0.83 3.17 32
## 35 India 496853 288714 15319 4.66 3.08 11
## 36 Honduras 15366 1600 426 5.46 2.77 43
## 37 Ukraine 41117 18299 1086 2.77 2.64 25
## 38 Turkey 193115 165706 5046 0.76 2.61 60
## 39 Cameroon 12592 10100 313 0.00 2.49 12
## 40 Nigeria 22614 7822 549 2.70 2.43 3
## 41 Dominican Republic 29141 16223 698 1.78 2.40 64
## 42 Afghanistan 30451 10306 683 0.91 2.24 18
## 43 South Korea 12602 11172 282 0.31 2.24 6
## 44 Argentina 52457 14788 1150 5.23 2.19 25
## 45 Pakistan 195745 84168 3962 1.44 2.02 18
## 46 Serbia 13565 12232 265 1.44 1.95 30
## 47 Panama 29037 14800 564 3.59 1.94 131
## 48 South Africa 118375 59974 2292 5.88 1.94 39
## 49 Chile 259064 219327 4903 1.83 1.89 256
## 50 Morocco 11465 8560 217 1.65 1.89 6
## 51 Armenia 23247 12149 410 3.38 1.76 138
## 52 Russia 620794 384152 8781 1.11 1.41 60
## 53 Israel 22638 16589 313 2.25 1.38 36
## 54 Bangladesh 130474 53133 1661 3.06 1.27 10
## 55 Azerbaijan 15369 8364 187 3.48 1.22 18
## 56 Saudi Arabia 174577 120471 1474 2.31 0.84 42
## 57 Kuwait 43703 33969 341 2.14 0.78 80
## 58 Kazakhstan 19750 12220 140 2.41 0.71 7
## 59 United Arab Emirates 46973 35469 310 0.88 0.66 31
## 60 Belarus 60713 42689 373 0.55 0.61 39
## 61 Ghana 15473 11431 95 3.06 0.61 3
## 62 Oman 36034 19482 153 3.24 0.42 30
## 63 Bahrain 24081 18501 71 2.17 0.29 42
## 64 Nepal 11755 2698 27 5.31 0.23 1
## 65 Qatar 92784 76072 109 1.03 0.12 38
## 66 Singapore 42955 36604 26 0.51 0.06 4
## [1] "Pakistan leading 1 cum_confirm == 0 trimed"
## [1] "Provinces added more than 0 cases in last 1-day:"
## time country province cum_confirm cum_heal cum_dead added
## 1 2020-06-26 China Beijing 874 585 9 11
## 2 2020-06-26 China Hong Kong 1196 1091 7 3
## 3 2020-06-26 China Shanghai 705 674 7 2
## 4 2020-06-26 China Macau 46 45 0 1