Ending day prediction of nCoV2019
31/10/2020
options(width = 100)
source('./predict.R')## [1] "2020-10-29"
## country cum_confirm cum_heal cum_dead inc_r d_rate d_pm
## 1 United States 9202379 5968433 234079 1.78 2.54 707
## 2 Brazil 5494376 4934548 158969 0.98 2.89 748
## 3 India 8088046 7371898 121131 1.22 1.50 88
## 4 Mexico 906863 663639 90309 0.62 9.96 700
## 5 United Kingdom 965340 1918 45955 5.21 4.76 677
## 6 Italy 616595 279282 38122 9.17 6.18 631
## 7 France 1282769 115287 36020 7.01 2.81 552
## 8 Spain 1238922 196958 35639 5.45 2.88 762
## 9 Peru 897594 819717 34362 0.57 3.83 1042
## 10 Iran 596941 472598 34113 1.41 5.71 406
## 11 Colombia 1053122 950348 30926 1.93 2.94 608
## 12 Argentina 1143800 946134 30442 2.44 2.66 674
## 13 Russia 1581693 1186041 27301 1.13 1.73 187
## 14 South Africa 721770 649935 19164 0.55 2.66 323
## 15 Chile 507050 483922 14118 0.50 2.78 739
## 16 Indonesia 404048 329778 13701 0.89 3.39 50
## 17 Ecuador 166302 141759 12622 1.91 7.59 715
## 18 Belgium 368337 23969 11170 6.06 3.03 964
## 19 Iraq 467755 394386 10815 0.82 2.31 269
## 20 Germany 483313 339105 10383 3.37 2.15 124
## 21 Turkey 370832 320762 10099 1.26 2.72 120
## 22 Canada 228306 191005 10073 2.43 4.41 267
## 23 Bolivia 141321 110303 8694 0.14 6.15 745
## 24 Netherlands 330255 322 7258 5.89 2.20 424
## 25 Philippines 376935 329848 7147 0.47 1.90 65
## 26 Ukraine 370417 151632 6868 2.02 1.85 157
## 27 Pakistan 331108 312638 6775 0.27 2.05 31
## 28 Romania 229040 163852 6764 2.91 2.95 352
## 29 Egypt 107209 99273 6247 0.31 5.83 61
## 30 Sweden 121167 4971 5934 2.76 4.90 588
## 31 Bangladesh 404760 321281 5886 0.42 1.45 36
## 32 Saudi Arabia 346482 333005 5363 0.13 1.55 154
## 33 Poland 319205 129267 5149 6.74 1.61 136
## 34 China 91852 86599 4746 0.03 5.17 3
## 35 Guatemala 106790 96187 3704 1.15 3.47 207
## 36 Morocco 212038 174911 3572 4.08 1.68 97
## 37 Czech Republic 303984 120205 2826 7.02 0.93 264
## 38 Panama 131247 107391 2663 0.63 2.03 617
## 39 Honduras 95199 39126 2652 0.61 2.79 268
## 40 Israel 313114 299439 2508 0.35 0.80 290
## 41 Portugal 132616 75702 2428 6.58 1.83 238
## 42 Dominican Republic 125913 103944 2234 0.72 1.77 206
## 43 Switzerland 145044 65100 2200 6.92 1.52 254
## 44 Algeria 57332 39635 1949 1.10 3.40 44
## 45 Ireland 60297 23364 1902 2.60 3.15 385
## 46 Kazakhstan 111100 106059 1825 0.24 1.64 97
## 47 Japan 99804 90807 1748 0.82 1.75 14
## 48 Moldova 74233 54495 1747 2.45 2.35 433
## 49 Hungary 68127 17469 1634 3.33 2.40 169
## 50 Afghanistan 41268 34239 1532 0.30 3.71 39
## 51 Ethiopia 95301 50753 1457 1.15 1.53 13
## 52 Paraguay 61290 41288 1359 1.21 2.22 191
## 53 Costa Rica 107570 65666 1357 2.13 1.26 266
## 54 Armenia 85034 53257 1272 2.88 1.50 429
## 55 Bulgaria 48150 19695 1225 12.76 2.54 176
## 56 Oman 114434 103060 1208 0.00 1.06 237
## 57 Myanmar 50403 30007 1199 2.71 2.38 22
## 58 Bosnia and Herzegovina 46639 27580 1182 4.25 2.53 360
## 59 Tunisia 54278 5032 1153 3.59 2.12 98
## 60 Nigeria 62521 58249 1141 0.48 1.82 6
## 61 Kyrgyzstan 57798 49097 1139 0.91 1.97 175
## 62 Austria 93949 63366 1056 4.98 1.12 117
## 63 Republika Severna Makedonija 29558 19994 977 6.22 3.31 NA
## 64 Belarus 96529 85332 973 1.03 1.01 103
## 65 El Salvador 33445 29186 967 1.58 2.89 149
## 66 Kenya 52612 35604 964 3.50 1.83 18
## 67 Australia 27567 25236 907 0.05 3.29 36
## 68 Nepal 164718 124862 904 1.46 0.55 31
## 69 Sudan 13772 6764 837 0.18 6.08 19
## 70 Libya 59656 33550 831 1.33 1.39 121
## 71 Puerto Rico 63587 2267 813 0.14 1.28 284
## 72 Serbia 43592 31536 809 6.63 1.86 93
## 73 Venezuela 90876 85402 784 0.53 0.86 28
## 74 Kuwait 124666 115475 767 0.61 0.62 180
## 75 Jordan 65385 7508 740 11.10 1.13 73
## 76 Denmark 44545 33620 716 4.40 1.61 124
## 77 Azerbaijan 53152 42516 708 1.95 1.33 70
## 78 Greece 35510 9989 615 8.42 1.73 59
## 79 Lebanon 77778 39123 610 5.11 0.78 89
## 80 Uzbekistan 66392 63581 561 0.54 0.84 17
## 81 Croatia 43775 29233 511 6.77 1.17 124
## 82 Albania 20315 11007 499 2.97 2.46 173
## 83 United Arab Emirates 130336 126147 488 1.02 0.37 49
## 84 Palestinian Territory 52571 45448 473 1.20 0.90 NA
## 85 South Korea 26271 24168 462 0.48 1.76 9
## 86 Cameroon 21793 20117 426 0.00 1.95 16
## 87 Finland 15566 11300 354 1.22 2.27 64
## 88 Zambia 16325 15585 348 0.50 2.13 19
## 89 Senegal 15593 14660 323 0.07 2.07 19
## 90 Ghana 47991 47136 320 0.45 0.67 10
## 91 Bahrain 81262 78102 317 0.62 0.39 186
## 92 Democratic Republic of the Congo 11211 10509 305 0.18 2.72 NA
## 93 Slovenia 30705 10401 292 8.85 0.95 140
## 94 Montenegro 17746 13727 290 3.83 1.63 462
## 95 Norway 19355 11863 281 3.69 1.45 52
## 96 Angola 10269 3736 275 4.03 2.68 8
## 97 Georgia 35567 16904 273 5.05 0.77 68
## 98 Malaysia 30090 19757 246 2.20 0.82 8
## 99 Madagascar 16968 16301 244 0.00 1.44 9
## 100 Qatar 132150 129124 231 0.16 0.17 80
## 101 Slovakia 51728 12227 200 5.69 0.39 37
## 102 Luxembourg 16356 9865 150 9.89 0.92 240
## 103 Lithuania 13088 4582 150 7.83 1.15 55
## 104 Namibia 12858 10972 133 1.01 1.03 52
## 105 Côte d'Ivoire 20628 20310 124 0.68 0.60 5
## 106 Uganda 12201 7461 108 3.69 0.89 2
## 107 Mozambique 12525 10001 91 2.05 0.73 3
## 108 Tajikistan 10939 10128 82 0.36 0.75 9
## 109 Guinea 12020 10550 71 1.70 0.59 5
## 110 French Guiana 10425 9995 70 0.27 0.67 234
## 111 Maldives 11616 10733 37 0.42 0.32 68
## 112 Singapore 57994 57899 28 0.01 0.05 5
## [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 2020-10-29 China Shanghai 1168 1059 7 13
## 2 2020-10-29 China Inner Mongolia 287 268 1 4
## 3 2020-10-29 China Liaoning 283 276 2 4
## 4 2020-10-29 China Hong Kong 5313 5073 105 3
## 5 2020-10-29 China Taiwan 553 513 7 3
## 6 2020-10-29 China Guangdong 1916 1877 8 2
## 7 2020-10-29 China Sichuan 739 708 3 2
## 8 2020-10-29 China Tianjin 265 247 3 2
## 9 2020-10-29 China Shandong 847 833 7 1
## 10 2020-10-29 China Shaanxi 454 421 3 1
## 11 2020-10-29 China Fujian 432 410 1 1
## 12 2020-10-29 China Yunnan 212 206 2 1