Ending day prediction of nCoV2019
08/08/2020
source('./predict.R')
## [1] "2020-08-07"
## country cum_confirm cum_heal cum_dead inc_r d_rate d_pm
## 1 El Salvador 19544 9379 520 4.51 2.66 80
## 2 Venezuela 23280 12470 202 4.40 0.87 7
## 3 Morocco 29644 20553 449 4.01 1.51 12
## 4 Japan 45895 30153 1042 3.63 2.27 8
## 5 Colombia 357710 192355 11939 3.47 3.34 235
## 6 Argentina 228195 99852 4251 3.40 1.86 94
## 7 Costa Rica 21070 7038 200 3.20 0.95 39
## 8 India 2040261 1386452 41792 3.15 2.05 30
## 9 Bosnia and Herzegovina 13687 7373 394 2.86 2.88 120
## 10 Ethiopia 20900 9027 365 2.77 1.75 3
## 11 Philippines 122754 66852 2168 2.76 1.77 20
## 12 Iraq 144064 103197 5236 2.46 3.63 130
## 13 Israel 80431 55274 578 2.44 0.72 67
## 14 Palestinian Territory 13722 7210 94 2.42 0.69 NA
## 15 Romania 59273 29289 2616 2.38 4.41 136
## 16 Bulgaria 13014 7374 435 2.34 3.34 63
## 17 Kenya 24411 10444 399 2.25 1.63 7
## 18 Nepal 22214 15814 70 2.13 0.32 2
## 19 Indonesia 121226 77557 5593 2.08 4.61 20
## 20 Australia 20272 11147 266 1.92 1.31 10
## 21 Brazil 2917562 2047660 98644 1.91 3.38 464
## 22 Ukraine 78261 43055 1852 1.89 2.37 42
## 23 Ecuador 90537 71318 5877 1.88 6.49 333
## 24 Peru 455409 310337 20424 1.74 4.48 619
## 25 Uzbekistan 28809 19587 179 1.74 0.62 5
## 26 Algeria 33626 23238 1273 1.73 3.79 29
## 27 Panama 71418 45658 1574 1.69 2.20 365
## 28 Poland 50324 36041 1787 1.63 3.55 47
## 29 Senegal 10887 7186 225 1.61 2.07 13
## 30 South Africa 538184 387316 9604 1.57 1.78 162
## 31 Guatemala 54339 42070 2119 1.55 3.90 118
## 32 Moldova 26628 18676 828 1.55 3.11 205
## 33 Bolivia 86423 27373 3465 1.51 4.01 297
## 34 Honduras 45755 6225 1446 1.46 3.16 146
## 35 Madagascar 12708 10412 135 1.45 1.06 5
## 36 Mexico 462690 308848 50517 1.44 10.92 392
## 37 Kyrgyzstan 39162 30764 1451 1.30 3.71 222
## 38 Belgium 72016 17700 9861 1.21 13.69 851
## 39 United States 5033723 2577914 162836 1.17 3.23 492
## 40 Dominican Republic 76536 40539 1246 1.16 1.63 115
## 41 Czech Republic 17731 12320 390 1.15 2.20 36
## 42 Ghana 40097 36638 206 1.15 0.51 7
## 43 Bangladesh 252502 145584 3333 1.14 1.32 20
## 44 Kazakhstan 96922 70680 1058 1.02 1.09 56
## 45 Kuwait 70727 62330 471 0.97 0.67 110
## 46 Netherlands 57501 322 6154 0.91 10.70 359
## 47 Bahrain 42889 39945 158 0.88 0.37 93
## 48 France 195633 82460 30312 0.83 15.49 464
## 49 Nigeria 45244 32430 930 0.79 2.06 5
## 50 Iran 322567 279724 18132 0.77 5.62 216
## 51 United Arab Emirates 62061 56015 356 0.74 0.57 36
## 52 Austria 21837 19690 720 0.65 3.30 80
## 53 Côte d'Ivoire 16447 12484 103 0.60 0.63 4
## 54 Russia 877135 683592 14725 0.60 1.68 101
## 55 Saudi Arabia 285793 248948 3093 0.55 1.08 89
## 56 Chile 366671 340168 9889 0.53 2.70 517
## 57 Germany 215609 199910 9332 0.51 4.33 111
## 58 Turkey 237265 220546 5798 0.49 2.44 69
## 59 Spain 354530 196958 28500 0.48 8.04 610
## 60 Switzerland 36269 31600 1986 0.45 5.48 229
## 61 Oman 81067 72263 502 0.44 0.62 98
## 62 Singapore 54797 48031 27 0.44 0.05 5
## 63 Armenia 39985 32008 777 0.42 1.94 262
## 64 Azerbaijan 33376 29696 483 0.39 1.45 48
## 65 Afghanistan 37015 25903 1307 0.32 3.53 34
## 66 Canada 118561 103106 8966 0.32 7.56 238
## 67 United Kingdom 308134 1918 46413 0.31 15.06 684
## 68 Pakistan 282645 258099 6052 0.28 2.14 27
## 69 Ireland 26372 23364 1768 0.26 6.70 358
## 70 Qatar 112383 109142 180 0.26 0.16 62
## 71 Denmark 14586 12993 617 0.17 4.23 107
## 72 Italy 249204 201323 35187 0.16 14.12 582
## 73 China 89026 82223 4687 0.14 5.26 3
## 74 Egypt 95006 48898 4951 0.14 5.21 48
## 75 South Korea 14519 13543 303 0.14 2.09 6
## 76 Belarus 68503 63756 580 0.00 0.85 61
## 77 Cameroon 17718 15320 391 0.00 2.21 15
## 78 Republika Severna Makedonija 11399 7480 517 0.00 4.54 NA
## 79 Puerto Rico 19934 0 258 0.00 1.29 90
## 80 Portugal 52061 37840 1743 0.00 3.35 171
## 81 Serbia 27332 14047 621 0.00 2.27 71
## 82 Sudan 11780 6194 763 0.00 6.48 17
## 83 Sweden 81967 4971 5766 0.00 7.03 571
## [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 2020-08-07 China Hong Kong 3938 2620 46 89
## 2 2020-08-07 China Xinjiang 799 181 3 26
## 3 2020-08-07 China Shanghai 764 728 7 7
## 4 2020-08-07 China Beijing 935 920 9 1
## 5 2020-08-07 China Liaoning 259 165 2 1
## 6 2020-08-07 China Jiangsu 659 654 0 1
## 7 2020-08-07 China Sichuan 611 599 3 1