Ending day prediction of nCoV2019
18/08/2020
source('./predict.R')
## [1] "2020-08-17"
## country cum_confirm cum_heal cum_dead inc_r d_rate d_pm
## 1 United States 5569520 2922936 173143 0.66 3.11 523
## 2 Brazil 3340197 2432456 107879 0.67 3.23 508
## 3 India 2661396 1932839 51176 1.62 1.92 37
## 4 Russia 927745 736101 15740 0.53 1.70 108
## 5 South Africa 587345 472377 11839 0.63 2.02 200
## 6 Peru 535946 365367 26281 1.93 4.90 797
## 7 Chile 385946 358828 10452 0.53 2.71 547
## 8 Mexico 522162 355101 56757 0.86 10.87 440
## 9 Iran 345450 299157 19804 0.65 5.73 236
## 10 Colombia 468332 287436 15097 2.55 3.22 297
## 11 Pakistan 289215 269087 6175 0.17 2.14 28
## 12 Saudi Arabia 299914 268385 3436 0.46 1.15 99
## 13 Turkey 249309 230969 5974 0.48 2.40 71
## 14 Argentina 294569 211702 5703 1.89 1.94 126
## 15 Germany 225397 205345 9391 0.17 4.17 112
## 16 Italy 253915 203786 35396 0.19 13.94 585
## 17 Spain 358843 196958 28617 0.00 7.97 612
## 18 Bangladesh 279144 160591 3694 0.94 1.32 22
## 19 Iraq 176931 125374 5860 0.00 3.31 146
## 20 Philippines 164474 112759 2681 4.15 1.63 24
## 21 Qatar 115080 111794 193 0.00 0.17 67
## 22 Canada 122087 108484 9026 0.16 7.39 239
## 23 Indonesia 141370 94458 6207 1.30 4.39 23
## 24 Ecuador 101542 87022 6070 0.85 5.98 344
## 25 France 218536 83848 30410 1.40 13.92 466
## 26 China 89906 83726 4710 0.08 5.24 3
## 27 Kazakhstan 103033 82777 1269 0.33 1.23 68
## 28 Oman 83226 77812 588 0.23 0.71 115
## 29 Israel 93691 69062 690 1.39 0.74 80
## 30 Kuwait 76827 68633 502 0.82 0.65 118
## 31 Belarus 69516 67072 610 0.13 0.88 65
## 32 Egypt 96475 59743 5160 0.14 5.35 50
## 33 United Arab Emirates 64541 57794 364 0.36 0.56 37
## 34 Panama 81940 55001 1767 1.58 2.16 410
## 35 Dominican Republic 86309 52905 1453 0.89 1.68 134
## 36 Singapore 55838 51953 27 0.16 0.05 5
## 37 Guatemala 62562 50692 2379 0.40 3.80 133
## 38 Ukraine 92820 48164 2089 1.60 2.25 48
## 39 Bahrain 46835 43128 172 0.87 0.37 101
## 40 Ghana 42653 40567 239 1.05 0.56 8
## 41 Japan 56214 40080 1103 0.36 1.96 9
## 42 Portugal 54234 39800 1779 0.24 3.28 174
## 43 Poland 57279 39359 1885 1.05 3.29 50
## 44 Nigeria 49068 36497 975 0.61 1.99 5
## 45 Bolivia 100344 36491 4058 1.21 4.04 348
## 46 Armenia 41701 34655 824 0.09 1.98 278
## 47 Kyrgyzstan 41991 34537 1496 0.32 3.56 229
## 48 Switzerland 38252 33300 1991 0.34 5.20 230
## 49 Romania 71194 32759 3029 1.04 4.25 157
## 50 Azerbaijan 34219 31875 506 0.00 1.48 50
## 51 Uzbekistan 35513 30973 234 1.15 0.66 7
## 52 Morocco 42489 29344 658 3.59 1.55 18
## 53 Afghanistan 37599 27166 1375 0.01 3.66 35
## 54 Serbia 29682 27061 674 0.00 2.27 77
## 55 Algeria 38583 27017 1370 1.18 3.55 31
## 56 Ireland 27257 23364 1774 0.24 6.51 359
## 57 Venezuela 33755 22700 281 3.52 0.83 10
## 58 Moldova 30183 21220 896 0.93 2.97 222
## 59 Austria 23534 20765 729 0.70 3.10 81
## 60 Belgium 78323 17994 9939 0.58 12.69 858
## 61 Nepal 27241 17495 107 2.18 0.39 4
## 62 Kenya 30365 17160 482 1.73 1.59 9
## 63 Cameroon 18469 16540 401 0.00 2.17 15
## 64 Australia 23559 14539 421 1.17 1.79 17
## 65 Côte d'Ivoire 17026 13947 110 0.19 0.65 4
## 66 South Korea 15515 13917 305 1.29 1.97 6
## 67 Czech Republic 20012 13799 397 0.61 1.98 37
## 68 Denmark 16003 13579 621 0.86 3.88 107
## 69 Madagascar 13886 12603 171 0.43 1.23 6
## 70 Ethiopia 29876 12359 528 3.40 1.77 5
## 71 El Salvador 22912 10814 618 0.00 2.70 95
## 72 Bosnia and Herzegovina 16111 9856 486 1.96 3.02 148
## 73 Palestinian Territory 16534 9838 110 0.00 0.67 NA
## 74 Bulgaria 14365 9186 498 0.22 3.47 72
## 75 Republika Severna Makedonija 12739 9174 544 0.00 4.27 NA
## 76 Costa Rica 28465 9062 294 2.62 1.03 58
## 77 Norway 10005 8857 261 0.16 2.61 48
## 78 Senegal 12237 7728 256 1.70 2.09 15
## 79 Honduras 50502 7339 1575 1.05 3.12 159
## 80 Sudan 12410 6385 803 0.78 6.47 18
## 81 Sweden 85045 4971 5787 0.89 6.80 573
## 82 Puerto Rico 26006 2267 335 1.21 1.29 117
## 83 United Kingdom 318484 1918 41366 0.35 12.99 609
## 84 Netherlands 63484 322 6172 0.77 9.72 360
## [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 2020-08-17 China Hong Kong 4524 3599 69 44
## 2 2020-08-17 China Guangdong 1720 1684 8 8
## 3 2020-08-17 China Yunnan 195 188 2 4
## 4 2020-08-17 China Shanghai 828 752 7 3
## 5 2020-08-17 China Shaanxi 354 324 3 3
## 6 2020-08-17 China Tianjin 209 202 3 2
## 7 2020-08-17 China Sichuan 626 606 3 2
## 8 2020-08-17 China Fujian 370 365 1 1
## 9 2020-08-17 China Shandong 822 790 7 1
## 10 2020-08-17 China Taiwan 485 450 7 1