Ending day prediction of nCoV2019
03/07/2020
source('./predict.R')
## [1] "2020-07-02"
## country cum_confirm cum_heal cum_dead inc_r death_r dead_pm
## 1 France 165719 76539 29861 0.56 18.02 457
## 2 Belgium 61598 17044 9761 0.14 15.85 842
## 3 Italy 240760 190717 34788 0.08 14.45 575
## 4 United Kingdom 313483 1918 43906 0.27 14.01 647
## 5 Mexico 231770 138319 28510 2.51 12.30 221
## 6 Netherlands 50273 322 6113 0.00 12.16 357
## 7 Spain 296739 196958 28363 0.13 9.56 607
## 8 Canada 104271 67743 8615 0.06 8.26 228
## 9 Ecuador 58257 27887 4576 3.23 7.85 259
## 10 Sweden 69692 4971 5370 1.81 7.71 532
## 11 Ireland 25477 23364 1738 0.02 6.82 352
## 12 Algeria 14272 10040 920 2.62 6.45 21
## 13 Switzerland 31967 29200 1965 0.36 6.15 227
## 14 Romania 27746 19363 1687 1.65 6.08 88
## 15 China 85273 80096 4648 0.02 5.45 3
## 16 Japan 19090 16731 977 1.71 5.12 8
## 17 Indonesia 59394 26667 2987 2.81 5.03 11
## 18 Iran 232863 194098 11106 1.15 4.77 132
## 19 United States 2782346 1165159 130856 1.89 4.70 395
## 20 Denmark 12994 11893 606 0.33 4.66 105
## 21 Germany 196997 182064 9162 0.49 4.65 109
## 22 Egypt 69814 18881 3034 2.20 4.35 30
## 23 Guatemala 19011 3231 817 5.06 4.30 46
## 24 Poland 35146 22209 1492 1.07 4.25 39
## 25 Brazil 1456969 916147 60813 3.35 4.17 286
## 26 Iraq 53708 27912 2160 4.24 4.02 54
## 27 Austria 17941 16514 705 0.38 3.93 78
## 28 Portugal 42782 28097 1587 1.52 3.71 156
## 29 Bolivia 34227 9764 1201 3.03 3.51 103
## 30 Peru 288477 178245 9860 1.14 3.42 299
## 31 Colombia 102009 43407 3470 4.25 3.40 68
## 32 Philippines 38805 10673 1274 0.76 3.28 12
## 33 Moldova 16898 9846 551 1.72 3.26 137
## 34 India 607344 360378 17873 2.69 2.94 13
## 35 Czech Republic 12046 7797 349 0.72 2.90 33
## 36 Honduras 20262 2123 542 3.60 2.67 55
## 37 Ukraine 45887 20053 1185 1.98 2.58 27
## 38 Turkey 201098 175422 5150 0.60 2.56 61
## 39 Afghanistan 32022 16041 807 0.58 2.52 21
## 40 Cameroon 12592 10100 313 0.00 2.49 12
## 41 Nigeria 26484 10152 603 3.07 2.28 3
## 42 Dominican Republic 33387 17904 754 2.51 2.26 70
## 43 South Korea 12904 11684 282 0.42 2.19 6
## 44 Pakistan 217809 104694 4473 2.03 2.05 20
## 45 Chile 282043 245443 5753 0.95 2.04 301
## 46 Argentina 67197 24186 1363 4.13 2.03 30
## 47 Serbia 15195 12912 287 2.42 1.89 33
## 48 Panama 34463 15945 645 2.72 1.87 149
## 49 Morocco 12854 9052 228 2.05 1.77 6
## 50 South Africa 159333 76025 2749 5.37 1.73 46
## 51 Armenia 26658 15036 459 2.28 1.72 155
## 52 Russia 661165 428978 9683 1.03 1.46 66
## 53 Bangladesh 153277 66442 1926 2.69 1.26 12
## 54 Israel 26452 17481 324 3.54 1.22 37
## 55 Azerbaijan 18112 10061 220 3.36 1.21 22
## 56 Saudi Arabia 197608 137669 1752 1.74 0.89 50
## 57 Kuwait 47859 38390 359 1.96 0.75 84
## 58 Belarus 62698 48378 405 0.44 0.65 43
## 59 Ghana 18134 13550 117 2.22 0.65 4
## 60 United Arab Emirates 49069 38160 316 0.83 0.64 32
## 61 Kazakhstan 42574 25319 188 90.85 0.44 10
## 62 Oman 42555 25318 188 3.30 0.44 37
## 63 Bahrain 27414 21948 93 2.45 0.34 55
## 64 Nepal 14519 5320 31 3.37 0.21 1
## 65 Qatar 97897 86597 118 1.88 0.12 41
## 66 Singapore 44310 39011 26 0.43 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 2020-07-02 China Hong Kong 1242 1120 7 9
## 2 2020-07-02 China Beijing 923 590 9 1
## 3 2020-07-02 China Shanghai 713 678 7 1
## 4 2020-07-02 China Guangdong 1642 1627 8 1
## 5 2020-07-02 China Taiwan 448 438 7 1