COVID-19, Relative by Population

The following tables show the spread of COVID-19 for a percentage of the population.
The New Cases percentage of "Last 120 days" means that the percentage of people in the skin has become infected. The percentage for the "Last 30 to 7 days" shows the percentage of the population that would still become infected in 120 days according to the growth rate. The Relative Mortality rates from last positive cases are also in percentages (with 7-day shift). This means relative percentage of patients (with 7-day shift) die from COVID-19 infection. [1] The Total Mortality is the ratio of total deaths in COVID-19 to population. An exact description of the calculations can be found at the bottom of this page.
COVID-19 World map by Johns Hopkins University.
Last actualisation from "WHO" and "WorldoMeter": 2021-12-08 12:21
(For some countries, the data from the WHO and from "Our World in Data by Johns Hopkins University" and from "WorldoMeter" are completely different, such as: Israel.)
What can help, is at the bottom of this page. I recommend searching here "Global literature on coronavirus disease" or here "Google Scholar".

COVID-19, Selected Countries by WorldoMeter

Our World in Data, (2 days late data visualization) [CASES][DEATHS], [VACCINATION]
CDCountryNew CasesNew Deaths
AT Austria +5 663 (+4 233) +58 (+77)
CZ Czechia +19 482 (+15 544) +61 (+107)
DE Germany +0 (+51 592) +0 (+448)
HU Hungary +6 849 (+4 311) +213 (+224)
PL Poland +28 542 (+19 373) +592 (+503)
SK Slovakia, [gov], [okr]+9 425 (+7 049) +91 (+104)

COVID-19, New Cases in Regions (incidence rate)

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Europe 756 283 315 3.13% 5.27% 5.55%
2 North America 595 288 967 2.63% 1.99% 2.26%
3 South America 439 096 278 0.72% 0.53% 0.55%
4 Australia/Oceania 43 523 718 0.62% 0.48% 0.48%
5 Asia 4 682 938 676 0.39% 0.23% 0.21%
6 Africa 1 385 833 112 0.13% 0.08% 0.15%

COVID-19, Relative Mortality rate from positive cases in Regions

N.RegionPopulationMortality last
120 days
Mortality last
30 days
New positive cases
last 30 days
1 Africa 1 385 833 112 2.37% (3.12)% (0.08)%
2 South America 439 096 278 2.41% 2.64% 0.53%
3 Asia 4 682 938 676 1.48% 2.15% 0.23%
4 North America 595 288 967 1.48% 1.83% 1.99%
5 Europe 756 283 315 1.35% 1.53% 5.27%
6 Australia/Oceania 43 523 718 1.04% 1.21% 0.48%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 439 096 278 1 187 685 2.705
2 North America 595 288 967 1 175 738 1.975
3 Europe 756 283 315 1 444 165 1.910
4 Asia 4 682 938 676 1 221 695 0.261
5 Africa 1 385 833 112 224 648 0.162
6 Australia/Oceania 43 523 718 4 567 0.105

COVID-19, New Cases in Countries

Filtered where Population more then 2 million, [All Countries] | Compare with [CASES]
N.RegionCDCountryPopulationLast 120 daysLast 30 daysLast 7 days
1 Europe SK Slovakia 5 463 429 6.51% 16.64% 18.62%
2 Europe CZ Czechia 10 737 430 5.64% 17.21% 17.52%
3 Europe NL Netherlands 17 189 161 5.26% 13.73% 14.75%
4 Europe HR Croatia 4 069 001 6.67% 13.29% 11.93%
5 Europe BE Belgium 11 661 837 6.30% 14.98% 11.58%
6 Europe IE Ireland 5 016 709 5.82% 10.49% 11.14%
7 Asia GE Georgia 3 978 200 10.56% 12.14% 11.08%
8 Europe DK Denmark 5 821 407 3.40% 8.25% 10.36%
9 Europe SI Slovenia 2 079 347 8.30% 14.75% 9.70%
10 Europe HU Hungary 9 625 218 3.73% 10.75% 9.70%
11 Europe AT Austria 9 079 964 6.03% 14.34% 9.18%
12 Europe CH Switzerland 8 745 217 3.91% 8.13% 8.36%
13 Europe GB United Kingdom 68 396 535 6.53% 7.36% 8.32%
14 Europe FR France 65 480 330 2.43% 4.63% 8.08%
15 Europe LT Lithuania 2 667 861 7.41% 8.38% 7.84%
16 Europe DE Germany 84 167 530 2.95% 7.09% 7.53%
17 Europe PL Poland 37 787 245 2.24% 6.57% 7.41%
18 Europe NO Norway 5 481 916 2.72% 5.38% 7.21%
19 Europe GR Greece 10 350 125 4.44% 7.47% 6.50%
20 Asia JO Jordan 10 348 087 2.03% 4.34% 5.67%
21 Europe PT Portugal 10 154 125 1.82% 2.95% 4.25%
22 North America US USA 333 781 277 3.94% 3.26% 3.76%
23 Europe BG Bulgaria 6 873 511 4.06% 4.37% 3.20%
24 Europe IT Italy 60 334 494 1.22% 2.16% 3.01%
25 Asia TR Turkey 85 637 694 3.50% 3.33% 2.97%
26 Europe UA Ukraine 43 357 380 2.91% 3.98% 2.75%
27 Asia LB Lebanon 6 781 663 1.61% 2.05% 2.69%
28 Europe RU Russia 146 024 075 2.33% 2.91% 2.65%
29 Europe FI Finland 5 553 045 1.49% 2.34% 2.42%
30 Europe RS Serbia 8 686 960 6.22% 3.87% 2.42%
31 Africa ZA South Africa 60 378 511 0.85% 0.84% 2.36%
32 Europe BA Bosnia and Herzegovina 3 251 585 2.24% 2.42% 2.17%
33 Europe BY Belarus 9 444 872 2.24% 2.21% 2.07%
34 Asia LA Laos 7 426 575 0.99% 1.88% 1.89%
35 Asia MY Malaysia 32 959 271 4.21% 1.96% 1.83%
36 Europe MK North Macedonia 2 083 252 2.86% 2.25% 1.80%
37 Asia VN Vietnam 98 592 025 1.13% 1.50% 1.73%
38 Asia AZ Azerbaijan 10 269 971 2.39% 2.00% 1.70%
39 Asia SG Singapore 5 916 198 3.46% 3.53% 1.70%
40 Europe MD Moldova 4 020 535 2.65% 2.13% 1.52%
41 Europe SE Sweden 10 189 412 1.05% 1.35% 1.45%
42 Asia AM Armenia 2 971 174 3.66% 2.72% 1.41%
43 Europe AL Albania 2 873 297 2.38% 1.83% 1.40%
44 Asia KR South Korea 51 332 370 0.54% 0.84% 1.24%
45 Europe ES Spain 46 780 712 1.15% 1.43% 1.13%
46 South America CL Chile 19 351 055 0.78% 1.36% 1.10%
47 South America BO Bolivia 11 900 803 0.56% 0.91% 1.05%
48 Africa ZW Zimbabwe 15 172 407 0.17% 0.26% 0.95%
49 Africa LY Libya 7 004 957 1.52% 0.86% 0.82%
50 South America UY Uruguay 3 490 967 0.53% 0.69% 0.81%
51 Asia MN Mongolia 3 353 792 6.17% 1.94% 0.81%
52 Asia TH Thailand 70 050 769 1.94% 1.01% 0.77%
53 Europe RO Romania 19 053 849 3.69% 1.71% 0.77%
54 Australia/Oceania AU Australia 25 923 219 0.71% 0.63% 0.70%
55 Asia IL Israel 9 326 000 4.73% 0.58% 0.70%
56 North America PA Panama 4 411 910 0.84% 0.55% 0.69%
57 North America CA Canada 38 215 765 0.96% 0.78% 0.68%
58 Asia QA Qatar 2 807 805 0.59% 0.63% 0.67%
59 South America AR Argentina 45 789 314 0.71% 0.41% 0.57%
60 South America BR Brazil 214 722 227 0.93% 0.52% 0.55%
61 South America CO Colombia 51 658 961 0.47% 0.54% 0.51%
62 South America PE Peru 33 628 881 0.36% 0.46% 0.51%
63 South America PR Puerto Rico 3 193 694 1.16% 0.43% 0.48%
64 Asia IR Iran 85 531 007 2.27% 0.72% 0.48%
65 Asia KZ Kazakhstan 19 098 054 1.85% 0.64% 0.47%
66 Asia LK Sri Lanka 21 541 794 1.07% 0.43% 0.35%
67 Africa BW Botswana 2 419 501 3.02% 0.43% 0.34%
68 Africa NA Namibia 2 606 699 0.32% 0.10% 0.30%
69 North America DO Dominican R. 11 003 584 0.59% 0.76% 0.27%
70 Australia/Oceania NZ New Zealand 5 002 100 0.19% 0.39% 0.27%
71 North America MX Mexico 130 871 191 0.65% 0.21% 0.26%
72 South America VE Venezuela 28 320 539 0.43% 0.32% 0.24%
73 South America EC Ecuador 18 026 241 0.21% 0.23% 0.24%
74 North America CR Costa Rica 5 160 692 2.87% 0.37% 0.23%
75 North America GT Guatemala 18 389 401 1.25% 0.32% 0.22%
76 Asia IQ Iraq 41 512 393 0.88% 0.22% 0.18%
77 North America JM Jamaica 2 979 671 1.22% 0.25% 0.17%
78 Africa TN Tunisia 11 995 584 0.88% 0.18% 0.16%
79 Africa MR Mauritania 4 824 240 0.24% 0.16% 0.13%
80 Africa GA Gabon 2 300 778 0.52% 0.23% 0.13%
81 North America CU Cuba 11 316 715 4.39% 0.26% 0.12%
82 Asia PS Palestine 5 270 874 0.01% 0.03% 0.11%
83 Africa EG Egypt 105 093 906 0.08% 0.10% 0.10%
84 South America PY Paraguay 7 257 889 0.11% 0.12% 0.10%
85 Asia NP Nepal 29 886 126 0.35% 0.11% 0.10%
86 Australia/Oceania PG Papua New Guinea 9 189 329 0.19% 0.17% 0.09%
87 Asia KG Kyrgyzstan 6 678 128 0.21% 0.11% 0.09%
88 Africa ER Eritrea 3 616 635 0.03% 0.06% 0.08%
89 Asia KW Kuwait 4 360 909 0.22% 0.07% 0.08%
90 Asia UZ Uzbekistan 34 163 034 0.17% 0.08% 0.07%
91 Asia IN India 1 399 420 665 0.19% 0.08% 0.07%
92 Asia MM Myanmar 54 931 930 0.35% 0.13% 0.07%
93 Asia AE Arab Emirates 10 061 375 0.48% 0.08% 0.07%
94 Africa TD Chad 17 098 962 0.00% 0.01% 0.06%
95 Asia SY Syria 18 108 084 0.13% 0.08% 0.06%
96 North America HT Haiti 11 601 406 0.04% 0.05% 0.05%
97 Africa ML Mali 21 083 786 0.02% 0.03% 0.05%
98 Africa DZ Algeria 44 983 240 0.07% 0.04% 0.05%
99 Africa LS Lesotho 2 166 556 0.38% 0.03% 0.05%
100 Asia PH Philippines 111 667 580 1.05% 0.12% 0.05%
101 North America HN Honduras 10 129 903 0.71% 0.07% 0.05%
102 Africa MA Morocco 37 536 525 0.66% 0.04% 0.04%
103 Africa SD Sudan 45 312 234 0.01% 0.03% 0.04%
104 Africa MZ Mozambique 32 506 041 0.06% 0.01% 0.03%
105 Africa CG Congo 5 712 141 0.10% 0.08% 0.03%
106 Africa BF Burkina Faso 21 721 937 0.01% 0.02% 0.03%
107 Asia OM Oman 5 292 165 0.11% 0.02% 0.03%
108 Africa CM Cameroon 27 489 925 0.09% 0.04% 0.02%
109 Asia PK Pakistan 227 024 140 0.10% 0.02% 0.02%
110 North America NI Nicaragua 6 737 323 0.08% 0.03% 0.02%
111 Africa ZM Zambia 19 119 260 0.05% 0.01% 0.02%
112 Africa CD DR Congo 93 449 004 0.01% 0.01% 0.02%
113 Africa GH Ghana 32 000 049 0.07% 0.01% 0.02%
114 Asia BD Bangladesh 167 037 400 0.12% 0.02% 0.02%
115 Asia KH Cambodia 17 049 958 0.22% 0.03% 0.02%
116 Africa BI Burundi 12 396 454 0.09% 0.01% 0.02%
117 Africa ET Ethiopia 119 032 081 0.07% 0.02% 0.01%
118 Africa KE Kenya 55 464 057 0.08% 0.01% 0.01%
119 Africa TG Togo 8 555 980 0.11% 0.01% 0.01%
120 Africa CF Central African R. 4 949 844 0.01% 0.01% 0.01%
121 Asia SA Saudi Arabia 35 589 310 0.04% 0.01% 0.01%
122 Africa RW Rwanda 13 410 933 0.18% 0.01% 0.01%
123 Asia AF Afghanistan 40 181 243 0.02% 0.01% 0.01%
124 Asia JP Japan 125 921 894 0.54% 0.01% 0.01%
125 Africa SS South Sudan 11 381 500 0.01% 0.01% 0.01%
126 Asia ID Indonesia 277 662 471 0.21% 0.01% 0.01%
127 Africa UG Uganda 47 803 211 0.07% 0.01% 0.01%
128 Africa MW Malawi 19 836 111 0.03% 0.00% 0.01%
129 Asia HK Hong Kong 7 584 036 0.01% 0.01% 0.01%
130 Africa AO Angola 34 325 856 0.06% 0.01% 0.01%
131 Africa NE Niger 25 456 893 0.01% 0.01% 0.01%
132 Africa CI Ivory Coast 27 311 513 0.04% 0.01% 0.01%
133 Africa GM Gambia 2 513 630 0.05% 0.00% 0.01%
134 Africa NG Nigeria 213 439 149 0.02% 0.00% 0.01%
135 Africa SN Senegal 17 374 215 0.03% 0.00% 0.01%
136 Asia TW Taiwan 23 878 502 0.00% 0.00% 0.01%
137 Africa SO Somalia 16 526 492 0.04% 0.01% 0.00%
138 Africa GW Guinea-Bissau 2 034 464 0.08% 0.06% 0.00%
139 Africa GN Guinea 13 641 593 0.03% 0.00% 0.00%
140 Asia YE Yemen 30 764 781 0.01% 0.00% 0.00%
141 Africa LR Liberia 5 227 544 0.01% 0.00% 0.00%
142 Africa BJ Benin 12 576 796 0.13% 0.00% 0.00%
143 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
144 Africa TZ Tanzania 62 164 023 0.04% 0.00% 0.00%
145 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
146 Asia TJ Tajikistan 9 843 790 0.00% 0.00% 0.00%
147 North America SV El Salvador 6 533 059 0.48% 0.22% 0.00%
148 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
149 Africa SL Sierra Leone 8 208 868 0.00% 0.00% 0.00%
150 Africa MG Madagascar 28 707 975 0.01% 0.01% 0.00%

COVID-19, Relative Mortality rate from positive cases in Countries

Filtered where Population more then 2 million, [All Countries] | Compare with [DEATHS]! and with [FATALITY RATE]
N.RegionCDCountryPopulationMortality last
120 days
Mortality last
30 days
New positive cases
last 30 days
1 Asia YE Yemen 30 764 781 19.36% (21.60)% (0.00)%
2 Africa TD Chad 17 098 962 5.22% (15.79)% (0.01)%
3 Asia PH Philippines 111 667 580 1.67% 11.57% 0.12%
4 South America PY Paraguay 7 257 889 11.55% 11.23% 0.12%
5 Africa SN Senegal 17 374 215 3.74% (8.57)% (0.00)%
6 Asia KH Cambodia 17 049 958 3.32% (8.56)% (0.03)%
7 Africa NE Niger 25 456 893 5.10% (6.86)% (0.01)%
8 Africa EG Egypt 105 093 906 5.71% 6.33% 0.10%
9 North America JM Jamaica 2 979 671 3.12% 6.08% 0.25%
10 North America MX Mexico 130 871 191 4.63% 5.90% 0.21%
11 Africa BF Burkina Faso 21 721 937 5.02% (5.72)% (0.02)%
12 Africa SD Sudan 45 312 234 7.28% (5.60)% (0.03)%
13 Africa NA Namibia 2 606 699 3.88% 5.47% 0.10%
14 South America EC Ecuador 18 026 241 4.28% 5.03% 0.23%
15 Europe RO Romania 19 053 849 3.29% 4.94% 1.71%
16 Europe BA Bosnia and Herzegovina 3 251 585 4.50% 4.88% 2.42%
17 Africa CG Congo 5 712 141 3.13% (4.77)% (0.08)%
18 Africa GH Ghana 32 000 049 1.27% (4.75)% (0.01)%
19 Africa GM Gambia 2 513 630 4.79% (4.55)% (0.00)%
20 Europe MD Moldova 4 020 535 2.87% 4.50% 2.13%
21 Europe BG Bulgaria 6 873 511 4.04% 4.42% 4.37%
22 Africa TZ Tanzania 62 164 023 2.81% (4.31)% (0.00)%
23 Africa ET Ethiopia 119 032 081 2.62% (4.18)% (0.02)%
24 Africa MW Malawi 19 836 111 5.12% (4.17)% (0.00)%
25 North America HN Honduras 10 129 903 2.84% (4.15)% (0.07)%
26 Asia IN India 1 399 420 665 1.58% (4.15)% (0.08)%
27 Africa DZ Algeria 44 983 240 4.20% (4.14)% (0.04)%
28 North America HT Haiti 11 601 406 3.51% (3.81)% (0.05)%
29 Asia SA Saudi Arabia 35 589 310 2.29% (3.79)% (0.01)%
30 Africa SO Somalia 16 526 492 6.36% (3.63)% (0.01)%
31 Asia SY Syria 18 108 084 3.91% (3.52)% (0.08)%
32 Asia KG Kyrgyzstan 6 678 128 1.95% 3.51% 0.11%
33 Asia AM Armenia 2 971 174 2.83% 3.47% 2.72%
34 Europe RU Russia 146 024 075 3.55% 3.30% 2.91%
35 Europe UA Ukraine 43 357 380 3.04% 3.28% 3.98%
36 Africa NG Nigeria 213 439 149 2.00% (3.28)% (0.00)%
37 Europe MK North Macedonia 2 083 252 3.66% 3.26% 2.25%
38 Africa ML Mali 21 083 786 2.99% (3.16)% (0.03)%
39 Africa ER Eritrea 3 616 635 3.45% (3.16)% (0.06)%
40 North America GT Guatemala 18 389 401 2.09% 3.13% 0.32%
41 Australia/Oceania PG Papua New Guinea 9 189 329 2.19% 3.04% 0.17%
42 South America PE Peru 33 628 881 3.66% 2.93% 0.46%
43 Asia ID Indonesia 277 662 471 4.45% (2.89)% (0.01)%
44 Africa LS Lesotho 2 166 556 3.50% (2.78)% (0.03)%
45 Africa MZ Mozambique 32 506 041 1.18% (2.73)% (0.01)%
46 Asia LK Sri Lanka 21 541 794 3.71% 2.73% 0.43%
47 Africa TN Tunisia 11 995 584 3.57% 2.71% 0.18%
48 North America CR Costa Rica 5 160 692 1.38% 2.61% 0.37%
49 Asia AF Afghanistan 40 181 243 4.08% (2.58)% (0.01)%
50 Africa GN Guinea 13 641 593 2.64% (2.56)% (0.00)%
51 South America BR Brazil 214 722 227 2.46% 2.33% 0.52%
52 Africa UG Uganda 47 803 211 1.36% (2.25)% (0.01)%
53 Asia IQ Iraq 41 512 393 1.08% 2.22% 0.22%
54 Africa MR Mauritania 4 824 240 1.83% 2.21% 0.16%
55 Asia PK Pakistan 227 024 140 1.99% (2.11)% (0.02)%
56 Africa CD DR Congo 93 449 004 0.78% (2.06)% (0.01)%
57 Africa AO Angola 34 325 856 3.07% (2.04)% (0.01)%
58 South America CO Colombia 51 658 961 2.34% 2.02% 0.54%
59 Africa MA Morocco 37 536 525 1.39% 1.99% 0.04%
60 Africa GW Guinea-Bissau 2 034 464 3.60% 1.95% 0.06%
61 Europe HU Hungary 9 625 218 1.97% 1.94% 10.75%
62 Africa LY Libya 7 004 957 1.51% 1.93% 0.86%
63 Asia KZ Kazakhstan 19 098 054 1.77% 1.82% 0.64%
64 Africa ZW Zimbabwe 15 172 407 3.35% 1.79% 0.26%
65 Africa CM Cameroon 27 489 925 1.90% 1.70% 0.04%
66 Europe PL Poland 37 787 245 1.68% 1.68% 6.57%
67 North America SV El Salvador 6 533 059 3.19% 1.65% 0.22%
68 Africa CI Ivory Coast 27 311 513 3.21% 1.64% 0.01%
69 Asia BD Bangladesh 167 037 400 1.73% 1.60% 0.02%
70 Asia IR Iran 85 531 007 1.64% 1.59% 0.72%
71 Asia GE Georgia 3 978 200 1.50% 1.56% 12.14%
72 Africa GA Gabon 2 300 778 0.97% 1.49% 0.23%
73 Africa ZA South Africa 60 378 511 2.96% 1.46% 0.84%
74 Asia MM Myanmar 54 931 930 3.30% 1.46% 0.13%
75 South America AR Argentina 45 789 314 2.35% 1.43% 0.41%
76 Europe RS Serbia 8 686 960 0.91% 1.42% 3.87%
77 Africa KE Kenya 55 464 057 2.28% 1.41% 0.01%
78 Africa RW Rwanda 13 410 933 1.57% 1.38% 0.01%
79 North America US USA 333 781 277 1.27% 1.33% 3.26%
80 Europe HR Croatia 4 069 001 1.25% 1.32% 13.29%
81 Asia VN Vietnam 98 592 025 2.14% 1.32% 1.50%
82 Asia AZ Azerbaijan 10 269 971 1.20% 1.29% 2.00%
83 Asia JP Japan 125 921 894 0.39% 1.28% 0.01%
84 Europe GR Greece 10 350 125 1.29% 1.28% 7.47%
85 Europe LT Lithuania 2 667 861 1.31% 1.21% 8.38%
86 Asia KR South Korea 51 332 370 0.75% 1.21% 0.84%
87 Asia UZ Uzbekistan 34 163 034 0.79% 1.18% 0.08%
88 South America BO Bolivia 11 900 803 1.97% 1.15% 0.91%
89 Europe AL Albania 2 873 297 0.99% 1.14% 1.83%
90 Asia NP Nepal 29 886 126 1.17% 1.10% 0.11%
91 North America PA Panama 4 411 910 1.15% 1.04% 0.55%
92 South America CL Chile 19 351 055 1.68% 0.99% 1.36%
93 South America VE Venezuela 28 320 539 1.20% 0.97% 0.32%
94 Asia MN Mongolia 3 353 792 0.51% 0.93% 1.94%
95 Africa ZM Zambia 19 119 260 1.29% 0.92% 0.01%
96 Europe SK Slovakia 5 463 429 0.86% 0.90% 16.64%
97 Asia MY Malaysia 32 959 271 1.33% 0.89% 1.96%
98 South America PR Puerto Rico 3 193 694 1.62% 0.89% 0.43%
99 Asia LB Lebanon 6 781 663 0.79% 0.87% 2.05%
100 South America UY Uruguay 3 490 967 0.83% 0.86% 0.69%
101 North America CA Canada 38 215 765 0.87% 0.85% 0.78%
102 Europe BY Belarus 9 444 872 0.80% 0.82% 2.21%
103 Asia TR Turkey 85 637 694 0.86% 0.80% 3.33%
104 Europe IT Italy 60 334 494 0.92% 0.78% 2.16%
105 Africa CF Central African R. 4 949 844 0.07% 0.78% 0.01%
106 Asia JO Jordan 10 348 087 0.93% 0.75% 4.34%
107 North America NI Nicaragua 6 737 323 0.29% 0.75% 0.03%
108 Europe CZ Czechia 10 737 430 0.70% 0.69% 17.21%
109 Asia TH Thailand 70 050 769 0.98% 0.66% 1.01%
110 Europe PT Portugal 10 154 125 0.62% 0.65% 2.95%
111 Australia/Oceania AU Australia 25 923 219 0.64% 0.62% 0.63%
112 Europe DE Germany 84 167 530 0.57% 0.57% 7.09%
113 Europe SI Slovenia 2 079 347 0.58% 0.54% 14.75%
114 Asia TW Taiwan 23 878 502 3.83% 0.52% 0.00%
115 Asia IL Israel 9 326 000 0.35% 0.50% 0.58%
116 North America CU Cuba 11 316 715 0.86% 0.47% 0.26%
117 Asia KW Kuwait 4 360 909 0.66% 0.44% 0.07%
118 Africa MG Madagascar 28 707 975 1.19% 0.43% 0.01%
119 Asia AE Arab Emirates 10 061 375 0.29% 0.42% 0.08%
120 Asia SG Singapore 5 916 198 0.37% 0.41% 3.53%
121 Europe AT Austria 9 079 964 0.40% 0.40% 14.34%
122 Asia LA Laos 7 426 575 0.31% 0.40% 1.88%
123 Asia OM Oman 5 292 165 2.22% 0.38% 0.02%
124 Europe FR France 65 480 330 0.43% 0.35% 4.63%
125 Europe GB United Kingdom 68 396 535 0.36% 0.34% 7.36%
126 Europe FI Finland 5 553 045 0.47% 0.34% 2.34%
127 Europe ES Spain 46 780 712 0.74% 0.32% 1.43%
128 Europe BE Belgium 11 661 837 0.31% 0.28% 14.98%
129 Europe SE Sweden 10 189 412 0.47% 0.27% 1.35%
130 Europe NO Norway 5 481 916 0.23% 0.25% 5.38%
131 North America DO Dominican R. 11 003 584 0.37% 0.24% 0.76%
132 Europe NL Netherlands 17 189 161 0.25% 0.24% 13.73%
133 Australia/Oceania NZ New Zealand 5 002 100 0.20% 0.23% 0.39%
134 Europe CH Switzerland 8 745 217 0.27% 0.23% 8.13%
135 Europe DK Denmark 5 821 407 0.24% 0.23% 8.25%
136 Europe IE Ireland 5 016 709 0.25% 0.18% 10.49%
137 Africa BW Botswana 2 419 501 0.81% 0.15% 0.43%
138 Asia QA Qatar 2 807 805 0.06% 0.00% 0.63%
139 Africa SS South Sudan 11 381 500 0.77% 0.00% 0.01%
140 Africa BI Burundi 12 396 454 0.03% 0.00% 0.01%
141 Africa TG Togo 8 555 980 0.79% 0.00% 0.01%
142 Asia HK Hong Kong 7 584 036 0.22% 0.00% 0.01%
143 Africa BJ Benin 12 576 796 0.31% 0.00% 0.00%
144 Africa LR Liberia 5 227 544 15.99% 0.00% 0.00%
145 Africa SL Sierra Leone 8 208 868 0.00% 0.00% 0.00%
146 Asia PS Palestine 5 270 874 0.00% 0.00% 0.03%
147 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
148 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
149 Asia TJ Tajikistan 9 843 790 0.00% 0.00% 0.00%
150 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%

COVID-19, Total Mortality rate (from population) in Countries

Filtered where Population more then 2 million, [All Countries] | Compare with [DEATHS] ! and with [CUMULATIVE DEATHS]
N.RegionCDCountryPopulationDeaths 1000*Deaths/Pop.
1 South America PE Peru 33 628 881 201 408 5.989
2 Europe BG Bulgaria 6 873 511 29 163 4.243
3 Europe BA Bosnia and Herzegovina 3 251 585 12 814 3.941
4 Europe HU Hungary 9 625 218 36 048 3.745
5 Europe MK North Macedonia 2 083 252 7 674 3.684
6 Europe CZ Czechia 10 737 430 33 963 3.163
7 Asia GE Georgia 3 978 200 12 519 3.147
8 Europe RO Romania 19 053 849 57 254 3.005
9 South America BR Brazil 214 722 227 615 914 2.868
10 Europe HR Croatia 4 069 001 11 323 2.783
11 Europe SK Slovakia 5 463 429 15 095 2.763
12 Europe SI Slovenia 2 079 347 5 698 2.740
13 Asia AM Armenia 2 971 174 7 728 2.601
14 Europe LT Lithuania 2 667 861 6 896 2.585
15 South America AR Argentina 45 789 314 116 669 2.548
16 South America CO Colombia 51 658 961 128 833 2.494
17 North America US USA 333 781 277 783 747 2.348
18 Europe BE Belgium 11 661 837 27 360 2.346
19 Europe MD Moldova 4 020 535 9 270 2.306
20 Europe PL Poland 37 787 245 86 797 2.297
21 South America PY Paraguay 7 257 889 16 483 2.271
22 North America MX Mexico 130 871 191 295 492 2.258
23 Europe IT Italy 60 334 494 134 375 2.227
24 Europe GB United Kingdom 68 396 535 145 826 2.132
25 Africa TN Tunisia 11 995 584 25 407 2.118
26 Europe UA Ukraine 43 357 380 89 436 2.063
27 South America CL Chile 19 351 055 38 535 1.991
28 Europe RU Russia 146 024 075 284 823 1.950
29 Europe ES Spain 46 780 712 88 140 1.884
30 South America EC Ecuador 18 026 241 33 484 1.857
31 Europe PT Portugal 10 154 125 18 572 1.829
32 Europe GR Greece 10 350 125 18 815 1.818
33 Europe FR France 65 480 330 117 221 1.790
34 South America UY Uruguay 3 490 967 6 135 1.757
35 North America PA Panama 4 411 910 7 378 1.672
36 South America BO Bolivia 11 900 803 19 239 1.617
37 Asia IR Iran 85 531 007 130 356 1.524
38 Africa ZA South Africa 60 378 511 90 002 1.491
39 Europe SE Sweden 10 189 412 15 170 1.489
40 North America CR Costa Rica 5 160 692 7 318 1.418
41 Europe AT Austria 9 079 964 12 556 1.383
42 Europe RS Serbia 8 686 960 11 995 1.381
43 Africa NA Namibia 2 606 699 3 573 1.371
44 Asia LB Lebanon 6 781 663 8 795 1.297
45 Europe CH Switzerland 8 745 217 11 219 1.283
46 Europe DE Germany 84 167 530 103 968 1.235
47 Europe NL Netherlands 17 189 161 19 770 1.150
48 Asia JO Jordan 10 348 087 11 817 1.142
49 Europe IE Ireland 5 016 709 5 707 1.138
50 Europe AL Albania 2 873 297 3 122 1.087
51 North America HN Honduras 10 129 903 10 413 1.028
52 South America PR Puerto Rico 3 193 694 3 273 1.025
53 Africa BW Botswana 2 419 501 2 420 1.000
54 Asia KZ Kazakhstan 19 098 054 17 958 0.940
55 Asia MY Malaysia 32 959 271 30 718 0.932
56 Asia TR Turkey 85 637 694 78 215 0.913
57 Asia IL Israel 9 326 000 8 210 0.880
58 North America GT Guatemala 18 389 401 15 993 0.870
59 North America JM Jamaica 2 979 671 2 411 0.809
60 Africa LY Libya 7 004 957 5 503 0.786
61 Asia AZ Azerbaijan 10 269 971 8 004 0.779
62 North America CA Canada 38 215 765 29 784 0.779
63 Asia OM Oman 5 292 165 4 113 0.777
64 North America CU Cuba 11 316 715 8 311 0.734
65 Asia LK Sri Lanka 21 541 794 14 505 0.673
66 Asia MN Mongolia 3 353 792 1 947 0.581
67 North America SV El Salvador 6 533 059 3 787 0.580
68 Asia IQ Iraq 41 512 393 23 919 0.576
69 Asia KW Kuwait 4 360 909 2 465 0.565
70 Europe BY Belarus 9 444 872 5 193 0.550
71 Asia ID Indonesia 277 662 471 143 893 0.518
72 Europe DK Denmark 5 821 407 2 965 0.509
73 Asia PH Philippines 111 667 580 49 670 0.445
74 Asia KG Kyrgyzstan 6 678 128 2 762 0.414
75 Africa MA Morocco 37 536 525 14 788 0.394
76 Asia NP Nepal 29 886 126 11 545 0.386
77 North America DO Dominican R. 11 003 584 4 212 0.383
78 Asia MM Myanmar 54 931 930 19 146 0.348
79 Asia IN India 1 399 420 665 473 952 0.339
80 Africa ZW Zimbabwe 15 172 407 4 715 0.311
81 Africa LS Lesotho 2 166 556 663 0.306
82 Asia TH Thailand 70 050 769 21 035 0.300
83 Asia VN Vietnam 98 592 025 26 700 0.271
84 Europe FI Finland 5 553 045 1 394 0.251
85 Asia SA Saudi Arabia 35 589 310 8 847 0.249
86 Asia QA Qatar 2 807 805 611 0.218
87 Asia AE Arab Emirates 10 061 375 2 149 0.214
88 Europe NO Norway 5 481 916 1 096 0.200
89 Africa EG Egypt 105 093 906 20 821 0.198
90 Africa ZM Zambia 19 119 260 3 668 0.192
91 South America VE Venezuela 28 320 539 5 199 0.184
92 Asia AF Afghanistan 40 181 243 7 317 0.182
93 Africa MR Mauritania 4 824 240 844 0.175
94 Asia KH Cambodia 17 049 958 2 967 0.174
95 Asia BD Bangladesh 167 037 400 28 010 0.168
96 Asia SY Syria 18 108 084 2 788 0.154
97 Asia JP Japan 125 921 894 18 367 0.146
98 Africa GM Gambia 2 513 630 342 0.136
99 Africa DZ Algeria 44 983 240 6 114 0.136
100 Asia SG Singapore 5 916 198 771 0.130
101 Asia PK Pakistan 227 024 140 28 786 0.127
102 Africa GA Gabon 2 300 778 281 0.122
103 Africa MW Malawi 19 836 111 2 307 0.116
104 Africa SN Senegal 17 374 215 1 886 0.109
105 Africa RW Rwanda 13 410 933 1 343 0.100
106 Africa KE Kenya 55 464 057 5 337 0.096
107 Africa SO Somalia 16 526 492 1 331 0.081
108 Australia/Oceania AU Australia 25 923 219 2 063 0.080
109 Asia KR South Korea 51 332 370 4 020 0.078
110 Africa GW Guinea-Bissau 2 034 464 149 0.073
111 Africa SD Sudan 45 312 234 3 200 0.071
112 Africa UG Uganda 47 803 211 3 258 0.068
113 Africa CM Cameroon 27 489 925 1 804 0.066
114 North America HT Haiti 11 601 406 750 0.065
115 Asia YE Yemen 30 764 781 1 955 0.064
116 Africa CG Congo 5 712 141 359 0.063
117 Australia/Oceania PG Papua New Guinea 9 189 329 573 0.062
118 Africa MZ Mozambique 32 506 041 1 941 0.060
119 Africa ET Ethiopia 119 032 081 6 808 0.057
120 Africa LR Liberia 5 227 544 287 0.055
121 Africa AO Angola 34 325 856 1 735 0.051
122 Asia UZ Uzbekistan 34 163 034 1 425 0.042
123 Africa GH Ghana 32 000 049 1 228 0.038
124 Asia TW Taiwan 23 878 502 848 0.035
125 Africa MG Madagascar 28 707 975 967 0.034
126 North America NI Nicaragua 6 737 323 213 0.032
127 Africa ML Mali 21 083 786 619 0.029
128 Asia LA Laos 7 426 575 215 0.029
129 Africa GN Guinea 13 641 593 388 0.028
130 Africa TG Togo 8 555 980 243 0.028
131 Asia HK Hong Kong 7 584 036 213 0.028
132 Africa CI Ivory Coast 27 311 513 706 0.026
133 Africa CF Central African R. 4 949 844 101 0.020
134 Africa ER Eritrea 3 616 635 62 0.017
135 Africa SL Sierra Leone 8 208 868 121 0.015
136 Africa NG Nigeria 213 439 149 2 980 0.014
137 Africa BF Burkina Faso 21 721 937 290 0.013
138 Africa BJ Benin 12 576 796 161 0.013
139 Africa CD DR Congo 93 449 004 1 113 0.012
140 Africa SS South Sudan 11 381 500 133 0.012
141 Africa TZ Tanzania 62 164 023 730 0.012
142 Africa TD Chad 17 098 962 181 0.011
143 Africa NE Niger 25 456 893 265 0.010
144 Australia/Oceania NZ New Zealand 5 002 100 44 0.009
145 Africa BI Burundi 12 396 454 14 0.001
146 Asia PS Palestine 5 270 874 1 0.000
147 Asia CN China 1 439 323 776 0 0.000
148 Asia KP North Korea 25 660 000 0 0.000
149 Asia TJ Tajikistan 9 843 790 0 0.000
150 Europe TM Turkmenistan 6 118 000 0 0.000

Elhalálozási adatok hozzávetőleges értékei 2018/2019:
 *  Abortusz: 56 millió, Szív és érrendszer: 17,9 millió, Rákbetegség: 9,6 millió.

COVID-19, Mi segíthet? - What can help? Above all, active prevention.

(2021-02-02 ...)

* Azelastine: [1], [2] , [*], [3], nálunk Szlovákiában, mint Allergodil, orr spray ismert. (5ml recept nélkül vásárolható)
* Cistus creticus (Cystus pandalis): [4], [5] nálunk, mint ViroStop ismert, torokspray (de van orrspay és tabletta is) Cistus a Vironal
* Artemisinin + Zinc: [6] egynyáriüröm kivonat, tabletta (Nagyon jó többfajta rákbetegségre is, de konzultálni kell az orvossal, ha más gyógyszereket is szedünk).
* Inosine pranobex: [9]
* Melatonin [10] , Quercetin (Kvercetín) [8] , Fluvoxamine [11] , NAC, N-acetylcysteín
* Ivermectin: [7] , [Ivermectin Triple Therapy Protocol for COVID-19 to Australian GP] , [Prof. Marik] , [SK, konečne] _
Ivermectin statisztikai adatok: [Epidemiologic Analyses on COVID-19 and Ivermectin] , [Dr. Thomas Borody, Australia] , [CZ]
[FLCCC, Ivermectin video], [A sok tesztelés nem segít], [FLCCC, Ivermectin] , [SK] , [Ivermectin, Vitamin D, Melatonin] , [Tanulmányok] , [ivmmeta.com]

Allergodil ViroStop D3 Artemisinin Artemisinin Zinc Melatonin Quercetin Ivermectin Inosine Galmektin

Az aktív prevenció abban van, hogy az Allergodil és a ViroStop meggátolja a vírus elszaporodását az orr és a száj nyálkahártyán. Mindezt "in-vitro" bizonyították. Az Allergodilt elegendő naponta egyszer (reggel) használni prevenciónak (de lehet többször is). A ViroStop-ot érdemes naponta többször is használni. A többi gyógyszer inkább csak akkor kell, ha a vírus mégis valahogyan nagyobb mennyiségben bejutna a szervezetünkbe, akkor az már fel legyen rá készülve. (Természetesen itt nem említek meg olyan alapvető dolgokat, mint a C vitamín, Aspirin, B1 stb.) Sajnos, relatíve kevés tanulmány foglalkozik az aktív megelőzéssel. Statistic Általában bizonyított COVID pozitív betegeken kísérleteznek, viszont a legjobb, ha el sem kapjuk ezt a betegséget, tehát meggátoljuk, hogy bejusson a szervezetünkbe. Az Ivermectint szintén használhatjuk preventíve, nagyon sok orvos már javasolja főleg időseknek. Tatiana Betáková (Szlovák Tudományos Akadémia): "Kérdés az, hogy a vírus továbbra is fog szaporodni a mi nyálkahártyankon, ha be leszünk oltva? Ezt még nem tudjuk, azért az oltás után is javasolva lesz a maszk viselése, hogy másokat ne fertőzzünk meg."
(This information has been compiled based on thousands of scientific studies. Anyone can check this here: [Google Scholar], [FLCCC Alliance] , [Protocol PDF] , [Hatásos gyógymód])
[Az oltás megoldás lesz?], [Mi történt Izraelben? PDF] ([PDF translate]) és [Israel CZ] , [Angliai jelentés] , [USA adatok] , [Furcsa eredmények] , [Agyi karosodások a covid után] , [Németországi adatok]
Mi mindent csináltak rosszul a COVID-19 kapcsán, mert nálunk is az történt, ami az USA-ban: [Link 1. video] vagy [Link 2. video] , [Link 3. cikk] , [DOC. MUDR. TÖRÖK az Ivermectinről] , [Ivermectin tapasztalatok] , [EU adatok a gyógyszerek mellékhatásairól, köztük a COVID vakcinák is]

Egy tudós (specialista a vakcinákra):
[Figyelmezteti a világot a lehetséges következményekre] , [VACCINATION WARNING]
HU: [G. V. Bossche figyelmeztésének rövid kivonata]
SK: [Varovanie od G. V. Bossche v skratke]
[Dr. Tenpenny, mRNA]
Latest SPR Covid Updates

Az Európa Tanács (ET) a 2361 (2021) állásfoglalásban úgy határozott, hogy betiltja a tagállamok oltási kötelezettségeinek előírását.
EU-tagállamok kötelesek:
7.3.1 annak biztosítása, hogy az állampolgárok tájékoztatást kapjanak arról, hogy az oltás NEM kötelező, és hogy senkit sem politikai, társadalmi vagy egyéb módon nem kényszerítenek oltásra, hacsak nem akarják
7.3.2 annak biztosítása, hogy senkit ne érjen hátrányos megkülönböztetés, mert esetleges egészségügyi kockázatok miatt nem oltották be, vagy nem oltották be
7.1.5 független kompenzációs programok létrehozása az oltásokkal szemben az aránytalan és az oltásokkal okozott károk megtérítése érdekében

STOP VACCINATION - Why?

DR. ZELENKO
Prof. RNDr. Jaroslav Turánek, CSc. DSc.
Dr. Robert Malone, inventor of mRNA technology
Prof. MUDr. Jiří Beran, CSc.


SK: [Pravidelné a celoplošné testovanie?]
2021-02-17
Jeden z najrenomovanejších lekárskych časopisov na svete „The Lancet“ publikuje štúdiu, ktorá ukazuje, že PCR test je na detekciu SARS-CoV-2 nepoužiteľný: I-MASK

"Väčšina ľudí infikovaných SARS-CoV-2 je nákazlivá po dobu 4–8 dní. Všeobecne sa nezistí, že by vzorky obsahovali kultúrne pozitívny (potenciálne nákazlivý) vírus po 9. dni po objavení sa symptómov, pričom väčšina prenosu nastala pred 5. dňom."

Uvedené platí aj pre antigenové aj pre protilátkové testy. Pred nástupom príznakov ochorenia 5 až 8 dní ešte nič nezistia, ale práve v tomto období pacient najviac infikuje svoje okolie. Na základe týchto informácií je úplne zbytočné robiť pravidelné plošné testovanie, ako je to na Slovenku. Zvyšuje sa iba nákaza. Potvrdenia vydané na jeden týždeň (covid negative) sú nanič.
Niektorí ľudia už museli absolvovať 48 testov, aby mohli chodiť do roboty. Neviem ako to "naši odborníci" odôvodňujú, ale je to proti zdravému rozumu a vyhadzovaniu peňazí. Nikde vo svete to takto nerobia, iba na Slovensku. (Asi naši "odborníci" majú patent na rozum.) [Dr. Horáková vrátila štátné vyznamenanie] , [Ivermectin na Slovensku video] , [News]
Čo všetko robili zle "odborníci", lebo to isté, čo sa stalo v USA, stalo sa aj u nás: [Link 1.] alebo [Link 2.] , [Link 3. text]

Je dôležité vedieť, že pacient môže žiadať od lekára liečenie pomocou Ivermectinu (po celom Slovensku aj v nemocniciach) v prípade COVID-19.

Kiszámolt értékek

New Cases, az új esteket százalékos értékei:
case120 = 100 * ws_case_120_days / ws_population
case30 = (120/30) * 100 * ws_case_30_days / ws_population
case7 = (120/7) * 100 * ws_case_7_days / ws_population

Relative Mortality számolása:
mortality120 = 100 * ws_death_120_days / (ws_case_127_days - ws_case_7_days)
mortality30 = 100 * ws_death_30_days / (ws_case_37_days - ws_case_7_days)

Ahol, ws_case_7_days (30,37,120,127), mindig az utolsó leadott jelentéstől kiszámított esetek száma, tehát
- ha Hungary utolsó jelentése 2021-02-10 volt, akkor onnan van számolva neki a 7,30,37,120,127 napos új esetek száma
- ha Szlovákia utolsó jelentése 2021-02-11 volt , akkor onnan van számolva neki a 7,30,37,120,127 napos új esetek száma
Ez azt jelenti, hogy lehet egy napos eltérés Szlovákia es Hungary kiszámolt értékei közt, de ezzel nem igen lehet semmit kezdeni.
Tekintettel arra, hogy a mortalitást 30 napra számolom, az ebből következő eltéres mértéke igen kicsi.
Itt sajnos probléma van USA és JAPAN esetében is, mivel más időzónában vannak, és mindenki máskor adja le a jelentést.
A WHO ezért 1-2 napos késéssel közli az adatokat. Ezen a weboldalon a WorldoMeter-től is aktualizálom az adatokat, melyek néhány ország esetében csak 1 napos vagy fél napos késéssel jönnek.
A kiszámolt értekek szempontjábol viszont ennek nincs nagy jelentősége, mert az eltérés igen kicsi a 30 napos átlagokat illetően.

Nagyon érdekes, ha ezeket az adatokat összehasonlítjuk "Our World in Data" által kiszámolt elhalálozási adatokkal.
Ott ugyanis az összes átlagon felüli elhalálozást veszik, nem csak a COVID-19 betegekét, amiből következtetni lehet a valódi elhalálozás mértékére, ami a COVID-19 kapcsán történik (függetlenül attól, hogy mit mondanak a COVID-19 kimutatások az adott országban). Az eltérő értékeknek több oka is lehet, például kevesebb ember kap színvonalas orvosi ellátást, vagy egyéb okok (mint például a kimutatások pontalansága) stb. Az is nagyon érdekes, ha összehasonlítjuk Izrael mortalitási adatatit más országokéval pl. Szlovákiával, akkor látható, hogy Izreaelben sokkal jobb eredményeket érnek el. Ez a vakcinázást megelőzően is igaz.

OurWorldInData: "https://github.com/owid/covid-19-data/tree/master/public/data", Slovakia: "https://github.com/Institut-Zdravotnych-Analyz/covid19-data"