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": 2022-01-24 13:33
(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 +25 610 (+22 453) +9 (+6)
CZ Czechia +12 889 (+18 344) +4 (+17)
DE Germany +0 (+75 280) +0 (+31)
HU Hungary +39 928 (+0) +122 (+0)
PL Poland +29 100 (+34 085) +2 (+25)
SK Slovakia, [gov], [okr]+3 503 (+7 608) +32 (+31)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Europe 756 340 814 6.98% 14.97% 15.64%
2 North America 595 881 376 4.87% 12.64% 10.72%
3 Australia/Oceania 43 588 815 3.57% 12.19% 8.65%
4 South America 439 552 404 1.62% 4.87% 6.41%
5 Asia 4 687 255 385 0.39% 0.82% 1.19%
6 Africa 1 389 966 446 0.17% 0.34% 0.23%

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 1 389 966 446 1.14% 0.86% 0.34%
2 Asia 4 687 255 385 1.01% 0.47% 0.82%
3 Europe 756 340 814 0.79% 0.38% 14.97%
4 North America 595 881 376 0.76% 0.33% 12.64%
5 South America 439 552 404 0.89% 0.32% 4.87%
6 Australia/Oceania 43 588 815 0.19% 0.08% 12.19%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 439 552 404 1 205 333 2.742
2 North America 595 881 376 1 256 178 2.108
3 Europe 756 340 814 1 588 241 2.100
4 Asia 4 687 255 385 1 272 717 0.272
5 Africa 1 389 966 446 236 068 0.170
6 Australia/Oceania 43 588 815 5 566 0.128

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 Asia IL Israel 9 326 000 10.18% 36.47% 74.08%
2 Europe DK Denmark 5 824 020 16.42% 41.90% 53.25%
3 Europe FR France 65 498 824 13.32% 41.34% 44.06%
4 Europe PT Portugal 10 150 323 10.23% 33.07% 37.19%
5 Europe SI Slovenia 2 079 384 13.89% 23.80% 36.79%
6 Europe SE Sweden 10 197 485 5.82% 18.76% 34.22%
7 Europe BE Belgium 11 668 299 12.16% 21.11% 32.08%
8 Europe CH Switzerland 8 753 333 11.47% 28.25% 30.63%
9 Europe ES Spain 46 783 030 8.30% 27.32% 25.65%
10 South America UY Uruguay 3 492 509 4.69% 16.72% 25.44%
11 Europe IT Italy 60 323 122 8.12% 26.45% 24.16%
12 South America PR Puerto Rico 3 193 694 7.76% 28.61% 22.79%
13 Europe NL Netherlands 17 194 015 10.42% 17.36% 21.68%
14 Europe AT Austria 9 086 551 9.09% 13.21% 21.29%
15 Europe NO Norway 5 487 352 7.24% 15.39% 19.70%
16 Europe LT Lithuania 2 663 020 10.29% 13.28% 18.35%
17 Europe CZ Czechia 10 739 974 9.57% 10.17% 18.29%
18 South America AR Argentina 45 842 519 4.94% 18.21% 18.21%
19 North America US USA 334 030 063 7.73% 20.09% 16.95%
20 Asia GE Georgia 3 977 221 10.87% 11.66% 16.95%
21 Europe HU Hungary 9 622 081 6.46% 8.48% 16.60%
22 North America PA Panama 4 420 639 3.26% 11.24% 16.36%
23 Europe HR Croatia 4 065 767 11.22% 16.27% 15.94%
24 Europe GR Greece 10 343 620 10.73% 26.69% 15.51%
25 Europe RS Serbia 8 682 461 7.00% 10.38% 15.28%
26 Europe FI Finland 5 554 147 5.19% 14.40% 14.26%
27 Australia/Oceania AU Australia 25 961 200 5.76% 20.16% 14.02%
28 Europe GB United Kingdom 68 442 235 11.77% 22.19% 11.70%
29 Europe DE Germany 84 201 843 5.15% 7.38% 10.91%
30 Asia QA Qatar 2 807 805 2.88% 9.91% 10.88%
31 South America PE Peru 33 687 878 1.79% 5.98% 10.82%
32 Europe BG Bulgaria 6 866 833 5.41% 7.61% 10.76%
33 North America CR Costa Rica 5 166 659 2.28% 4.84% 10.03%
34 Europe IE Ireland 5 023 789 14.89% 35.12% 9.96%
35 Europe BA Bosnia and Herzegovina 3 248 979 3.01% 5.08% 8.96%
36 Asia KZ Kazakhstan 19 126 888 1.35% 2.81% 8.41%
37 Europe SK Slovakia 5 463 768 9.13% 6.01% 8.37%
38 Asia KW Kuwait 4 369 023 1.66% 6.35% 7.32%
39 Asia TR Turkey 85 754 170 4.42% 7.16% 6.89%
40 Asia LB Lebanon 6 777 757 3.32% 8.12% 6.76%
41 Europe PL Poland 37 781 943 4.15% 4.54% 6.75%
42 Europe RO Romania 19 037 459 4.14% 3.66% 6.54%
43 Europe MK North Macedonia 2 083 241 3.01% 5.69% 6.32%
44 Europe AL Albania 2 872 895 2.64% 5.01% 6.28%
45 Europe MD Moldova 4 019 336 2.85% 2.87% 5.98%
46 South America BO Bolivia 11 921 255 2.43% 7.23% 5.67%
47 South America PY Paraguay 7 269 138 0.84% 3.07% 5.55%
48 Africa TN Tunisia 12 011 455 0.99% 3.39% 5.16%
49 North America CA Canada 38 258 213 3.29% 9.55% 4.93%
50 South America CL Chile 19 372 103 1.45% 2.78% 4.92%
51 South America CO Colombia 51 728 566 1.36% 4.14% 4.61%
52 North America DO Dominican R. 11 017 543 1.55% 4.15% 4.49%
53 Africa BW Botswana 2 425 610 2.89% 6.47% 4.43%
54 North America JM Jamaica 2 981 327 1.21% 3.41% 4.33%
55 South America BR Brazil 214 915 961 1.01% 2.37% 4.19%
56 Asia JO Jordan 10 361 084 2.95% 2.86% 3.87%
57 South America EC Ecuador 18 060 665 0.68% 2.04% 3.86%
58 Europe UA Ukraine 43 323 817 3.32% 1.76% 2.89%
59 Asia SG Singapore 5 922 099 3.63% 1.60% 2.66%
60 Asia NP Nepal 29 953 509 0.38% 1.04% 2.58%
61 Europe RU Russia 146 032 083 2.49% 1.87% 2.54%
62 Asia JP Japan 125 872 394 0.30% 1.06% 2.54%
63 North America CU Cuba 11 315 830 1.48% 1.80% 2.44%
64 Asia AE Arab Emirates 10 076 717 0.84% 2.84% 2.44%
65 Asia OM Oman 5 308 896 0.31% 1.12% 2.42%
66 Asia PH Philippines 111 854 893 0.79% 1.83% 2.21%
67 Asia MN Mongolia 3 360 577 3.53% 3.01% 2.15%
68 Asia IN India 1 401 161 559 0.37% 1.17% 1.83%
69 North America MX Mexico 131 045 037 0.65% 1.72% 1.76%
70 Asia AM Armenia 2 971 883 3.10% 0.84% 1.65%
71 Africa LY Libya 7 016 958 0.97% 1.09% 1.58%
72 Asia VN Vietnam 98 704 378 1.38% 1.98% 1.49%
73 Europe BY Belarus 9 444 474 2.06% 1.35% 1.34%
74 Asia SA Saudi Arabia 35 658 981 0.27% 1.02% 1.32%
75 Asia IQ Iraq 41 628 580 0.36% 0.48% 1.15%
76 Africa MA Morocco 37 592 691 0.39% 1.26% 1.13%
77 Asia KR South Korea 51 338 018 0.83% 0.97% 1.03%
78 Asia KG Kyrgyzstan 6 691 963 0.24% 0.59% 0.97%
79 Asia TH Thailand 70 073 197 1.15% 0.92% 0.92%
80 Asia AZ Azerbaijan 10 281 695 1.47% 0.68% 0.89%
81 Asia LA Laos 7 440 138 1.44% 1.30% 0.89%
82 Asia MY Malaysia 33 012 522 1.94% 1.08% 0.85%
83 North America GT Guatemala 18 432 019 0.62% 0.77% 0.81%
84 Africa MR Mauritania 4 839 988 0.44% 1.36% 0.67%
85 Asia PS Palestine 5 286 143 0.04% 0.15% 0.65%
86 Africa GA Gabon 2 307 540 0.73% 1.36% 0.64%
87 Africa NA Namibia 2 612 616 1.06% 2.20% 0.56%
88 South America VE Venezuela 28 310 238 0.36% 0.28% 0.53%
89 North America HN Honduras 10 150 147 0.25% 0.28% 0.53%
90 Asia BD Bangladesh 167 247 937 0.07% 0.20% 0.45%
91 Africa ZA South Africa 60 474 528 1.12% 1.20% 0.44%
92 Asia IR Iran 85 669 059 0.84% 0.28% 0.41%
93 Africa ZM Zambia 19 185 632 0.48% 1.49% 0.38%
94 Africa GM Gambia 2 522 383 0.07% 0.24% 0.31%
95 Asia UZ Uzbekistan 34 225 348 0.12% 0.16% 0.30%
96 Africa CM Cameroon 27 575 039 0.10% 0.08% 0.28%
97 Africa RW Rwanda 13 452 288 0.23% 0.70% 0.28%
98 Asia LK Sri Lanka 21 553 297 0.40% 0.31% 0.25%
99 Africa DZ Algeria 45 085 057 0.07% 0.15% 0.25%
100 Africa GW Guinea-Bissau 2 040 454 0.06% 0.16% 0.23%
101 Africa LS Lesotho 2 168 734 0.81% 1.09% 0.23%
102 Asia PK Pakistan 227 575 840 0.05% 0.11% 0.22%
103 Africa ZW Zimbabwe 15 200 203 0.65% 0.66% 0.19%
104 Africa ER Eritrea 3 622 939 0.07% 0.15% 0.14%
105 Africa MZ Mozambique 32 618 926 0.22% 0.70% 0.13%
106 Australia/Oceania NZ New Zealand 5 002 100 0.23% 0.13% 0.12%
107 Africa SN Senegal 17 431 071 0.06% 0.22% 0.12%
108 Africa AO Angola 34 457 759 0.12% 0.30% 0.11%
109 Africa SD Sudan 45 444 056 0.03% 0.07% 0.11%
110 Africa GH Ghana 32 083 509 0.09% 0.26% 0.11%
111 Africa MG Madagascar 28 799 689 0.04% 0.12% 0.10%
112 Africa EG Egypt 105 342 137 0.10% 0.10% 0.09%
113 Africa BI Burundi 12 442 129 0.16% 0.45% 0.08%
114 Africa CG Congo 5 729 635 0.16% 0.28% 0.07%
115 Asia HK Hong Kong 7 591 837 0.01% 0.03% 0.07%
116 Africa ML Mali 21 158 994 0.07% 0.18% 0.07%
117 Asia ID Indonesia 278 033 665 0.03% 0.03% 0.07%
118 Africa GN Guinea 13 687 504 0.04% 0.14% 0.07%
119 Africa CF Central African R. 4 960 640 0.04% 0.12% 0.07%
120 Africa MW Malawi 19 899 799 0.11% 0.28% 0.06%
121 Africa KE Kenya 55 616 509 0.13% 0.30% 0.06%
122 Africa ET Ethiopia 119 398 868 0.10% 0.24% 0.05%
123 Africa TG Togo 8 580 963 0.13% 0.41% 0.05%
124 Africa TZ Tanzania 62 383 386 0.01% 0.04% 0.05%
125 North America HT Haiti 11 619 253 0.06% 0.08% 0.05%
126 Africa UG Uganda 47 989 608 0.08% 0.22% 0.05%
127 Africa SL Sierra Leone 8 229 738 0.01% 0.04% 0.04%
128 Africa BJ Benin 12 617 712 0.03% 0.04% 0.04%
129 Africa BF Burkina Faso 21 795 816 0.03% 0.06% 0.04%
130 Asia TW Taiwan 23 884 021 0.01% 0.02% 0.04%
131 Africa CD DR Congo 93 800 235 0.03% 0.06% 0.04%
132 Asia AF Afghanistan 40 294 100 0.01% 0.02% 0.03%
133 Africa TD Chad 17 159 734 0.01% 0.03% 0.03%
134 Africa CI Ivory Coast 27 395 647 0.07% 0.24% 0.03%
135 Africa LR Liberia 5 242 850 0.03% 0.10% 0.03%
136 Africa SS South Sudan 11 398 347 0.04% 0.10% 0.03%
137 Asia MM Myanmar 54 978 693 0.14% 0.03% 0.02%
138 Asia YE Yemen 30 849 332 0.01% 0.01% 0.02%
139 Asia KH Cambodia 17 079 678 0.07% 0.01% 0.02%
140 North America NI Nicaragua 6 747 441 0.04% 0.01% 0.01%
141 Asia SY Syria 18 162 836 0.10% 0.02% 0.01%
142 Africa NG Nigeria 214 097 230 0.02% 0.03% 0.01%
143 Africa NE Niger 25 570 103 0.01% 0.02% 0.01%
144 Asia TJ Tajikistan 9 871 366 0.00% 0.00% 0.01%
145 Australia/Oceania PG Papua New Guinea 9 211 126 0.19% 0.02% 0.00%
146 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
147 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
148 North America SV El Salvador 6 537 253 0.33% 0.11% 0.00%
149 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
150 Africa SO Somalia 16 583 651 0.03% 0.03% 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 30 849 332 19.27% (8.96)% (0.01)%
2 Asia SY Syria 18 162 836 3.74% (8.53)% (0.02)%
3 Asia AF Afghanistan 40 294 100 4.45% (3.79)% (0.02)%
4 Europe RU Russia 146 032 083 3.41% 3.43% 1.87%
5 North America NI Nicaragua 6 747 441 0.48% (3.13)% (0.01)%
6 Europe UA Ukraine 43 323 817 3.08% 2.81% 1.76%
7 Africa EG Egypt 105 342 137 4.94% (2.75)% (0.10)%
8 Europe BA Bosnia and Herzegovina 3 248 979 4.18% 2.72% 5.08%
9 Europe PL Poland 37 781 943 1.97% 2.45% 4.54%
10 Asia LK Sri Lanka 21 553 297 2.80% 2.23% 0.31%
11 Europe BG Bulgaria 6 866 833 3.57% 2.13% 7.61%
12 Africa MG Madagascar 28 799 689 1.88% 2.08% 0.12%
13 Asia KH Cambodia 17 079 678 4.60% (2.05)% (0.01)%
14 Africa DZ Algeria 45 085 057 2.82% 2.04% 0.15%
15 Europe HU Hungary 9 622 081 2.03% 2.03% 8.48%
16 Asia AM Armenia 2 971 883 2.95% 1.96% 0.84%
17 Europe MD Moldova 4 019 336 3.02% 1.92% 2.87%
18 Africa NE Niger 25 570 103 3.90% 1.83% 0.02%
19 Asia AZ Azerbaijan 10 281 695 1.39% 1.82% 0.68%
20 Africa SD Sudan 45 444 056 4.28% 1.76% 0.07%
21 Asia IR Iran 85 669 059 1.61% 1.64% 0.28%
22 Europe SK Slovakia 5 463 768 1.05% 1.63% 6.01%
23 Africa LY Libya 7 016 958 1.95% 1.61% 1.09%
24 Africa ER Eritrea 3 622 939 2.19% 1.61% 0.15%
25 Australia/Oceania PG Papua New Guinea 9 211 126 2.12% 1.48% 0.02%
26 Africa NA Namibia 2 612 616 1.36% 1.43% 2.20%
27 Asia ID Indonesia 278 033 665 3.37% 1.35% 0.03%
28 Asia GE Georgia 3 977 221 1.45% 1.32% 11.66%
29 Europe BY Belarus 9 444 474 0.90% 1.27% 1.35%
30 North America SV El Salvador 6 537 253 2.81% 1.23% 0.11%
31 Europe MK North Macedonia 2 083 241 2.70% 1.22% 5.69%
32 Africa ZW Zimbabwe 15 200 203 0.69% 1.13% 0.66%
33 South America EC Ecuador 18 060 665 1.85% 1.12% 2.04%
34 Africa ZA South Africa 60 474 528 1.02% 1.12% 1.20%
35 Asia MM Myanmar 54 978 693 2.05% 1.11% 0.03%
36 Asia VN Vietnam 98 704 378 1.34% 1.10% 1.98%
37 Africa BF Burkina Faso 21 795 816 2.92% 1.09% 0.06%
38 Africa CM Cameroon 27 575 039 2.06% 1.05% 0.08%
39 Asia KR South Korea 51 338 018 0.99% 0.98% 0.97%
40 Africa MW Malawi 19 899 799 1.08% 0.98% 0.28%
41 South America PY Paraguay 7 269 138 2.02% 0.93% 3.07%
42 Asia JO Jordan 10 361 084 0.82% 0.92% 2.86%
43 Africa GW Guinea-Bissau 2 040 454 2.05% 0.91% 0.16%
44 Europe RO Romania 19 037 459 3.06% 0.90% 3.66%
45 Asia KG Kyrgyzstan 6 691 963 1.92% 0.84% 0.59%
46 Africa CD DR Congo 93 800 235 0.79% 0.76% 0.06%
47 Europe HR Croatia 4 065 767 1.12% 0.75% 16.27%
48 Asia LA Laos 7 440 138 0.47% 0.72% 1.30%
49 North America HN Honduras 10 150 147 3.22% 0.71% 0.28%
50 Asia IQ Iraq 41 628 580 1.56% 0.66% 0.48%
51 North America JM Jamaica 2 981 327 2.45% 0.66% 3.41%
52 Africa UG Uganda 47 989 608 0.89% 0.66% 0.22%
53 North America HT Haiti 11 619 253 2.57% 0.66% 0.08%
54 Europe LT Lithuania 2 663 020 1.10% 0.65% 13.28%
55 North America MX Mexico 131 045 037 2.55% 0.65% 1.72%
56 South America VE Venezuela 28 310 238 1.01% 0.63% 0.28%
57 Asia UZ Uzbekistan 34 225 348 0.83% 0.62% 0.16%
58 Africa CF Central African R. 4 960 640 0.45% 0.59% 0.12%
59 Europe CZ Czechia 10 739 974 0.71% 0.58% 10.17%
60 Asia PH Philippines 111 854 893 1.84% 0.58% 1.83%
61 Asia MY Malaysia 33 012 522 0.92% 0.57% 1.08%
62 Africa TN Tunisia 12 011 455 1.32% 0.57% 3.39%
63 Africa ML Mali 21 158 994 1.17% 0.56% 0.18%
64 South America CL Chile 19 372 103 0.89% 0.56% 2.78%
65 Africa GN Guinea 13 687 504 0.71% 0.52% 0.14%
66 Europe DE Germany 84 201 843 0.60% 0.50% 7.38%
67 South America BO Bolivia 11 921 255 0.70% 0.50% 7.23%
68 South America PE Peru 33 687 878 1.20% 0.50% 5.98%
69 South America BR Brazil 214 915 961 1.50% 0.49% 2.37%
70 South America CO Colombia 51 728 566 0.97% 0.49% 4.14%
71 Africa AO Angola 34 457 759 0.96% 0.49% 0.30%
72 Asia KZ Kazakhstan 19 126 888 1.46% 0.48% 2.81%
73 Africa TD Chad 17 159 734 0.72% 0.47% 0.03%
74 Africa TZ Tanzania 62 383 386 0.13% 0.47% 0.04%
75 Africa GM Gambia 2 522 383 1.04% 0.46% 0.24%
76 Africa NG Nigeria 214 097 230 0.91% 0.46% 0.03%
77 Africa GH Ghana 32 083 509 0.78% 0.45% 0.26%
78 Asia PK Pakistan 227 575 840 1.48% 0.45% 0.11%
79 Europe RS Serbia 8 682 461 0.90% 0.43% 10.38%
80 North America GT Guatemala 18 432 019 2.39% 0.42% 0.77%
81 Africa ET Ethiopia 119 398 868 1.48% 0.40% 0.24%
82 Europe AL Albania 2 872 895 0.94% 0.39% 5.01%
83 Africa MR Mauritania 4 839 988 0.77% 0.39% 1.36%
84 Asia IN India 1 401 161 559 1.07% 0.35% 1.17%
85 Asia LB Lebanon 6 777 757 0.57% 0.35% 8.12%
86 Europe GR Greece 10 343 620 0.76% 0.34% 26.69%
87 Africa CI Ivory Coast 27 395 647 0.85% 0.34% 0.24%
88 Africa SN Senegal 17 431 071 0.70% 0.34% 0.22%
89 Asia TR Turkey 85 754 170 0.62% 0.33% 7.16%
90 Africa KE Kenya 55 616 509 0.63% 0.32% 0.30%
91 Africa RW Rwanda 13 452 288 0.58% 0.32% 0.70%
92 Asia BD Bangladesh 167 247 937 0.96% 0.32% 0.20%
93 Asia TH Thailand 70 073 197 0.67% 0.32% 0.92%
94 Africa LS Lesotho 2 168 734 1.67% 0.31% 1.09%
95 Africa MZ Mozambique 32 618 926 0.35% 0.30% 0.70%
96 Africa BW Botswana 2 425 610 0.26% 0.30% 6.47%
97 North America US USA 334 030 063 0.70% 0.29% 20.09%
98 North America CR Costa Rica 5 166 659 1.28% 0.28% 4.84%
99 Africa ZM Zambia 19 185 632 0.27% 0.24% 1.49%
100 Africa MA Morocco 37 592 691 0.68% 0.23% 1.26%
101 North America CA Canada 38 258 213 0.38% 0.22% 9.55%
102 Europe SI Slovenia 2 079 384 0.54% 0.22% 23.80%
103 Africa SL Sierra Leone 8 229 738 0.40% 0.22% 0.04%
104 Africa TG Togo 8 580 963 0.38% 0.21% 0.41%
105 North America PA Panama 4 420 639 0.36% 0.19% 11.24%
106 Europe IT Italy 60 323 122 0.30% 0.19% 26.45%
107 Africa GA Gabon 2 307 540 0.69% 0.18% 1.36%
108 Africa BJ Benin 12 617 712 0.20% 0.18% 0.04%
109 Asia OM Oman 5 308 896 0.35% 0.17% 1.12%
110 Africa SO Somalia 16 583 651 4.50% 0.17% 0.03%
111 Asia NP Nepal 29 953 509 0.72% 0.17% 1.04%
112 Asia SG Singapore 5 922 099 0.36% 0.16% 1.60%
113 South America PR Puerto Rico 3 193 694 0.23% 0.16% 28.61%
114 Asia MN Mongolia 3 360 577 0.66% 0.16% 3.01%
115 Europe BE Belgium 11 668 299 0.26% 0.15% 21.11%
116 Europe AT Austria 9 086 551 0.37% 0.14% 13.21%
117 Europe GB United Kingdom 68 442 235 0.22% 0.13% 22.19%
118 Europe FI Finland 5 554 147 0.29% 0.12% 14.40%
119 Africa SS South Sudan 11 398 347 0.34% 0.11% 0.10%
120 Australia/Oceania NZ New Zealand 5 002 100 0.23% 0.11% 0.13%
121 North America CU Cuba 11 315 830 0.58% 0.11% 1.80%
122 Europe SE Sweden 10 197 485 0.19% 0.11% 18.76%
123 South America UY Uruguay 3 492 509 0.19% 0.11% 16.72%
124 South America AR Argentina 45 842 519 0.21% 0.10% 18.21%
125 Europe FR France 65 498 824 0.16% 0.10% 41.34%
126 Africa CG Congo 5 729 635 1.89% 0.10% 0.28%
127 Europe PT Portugal 10 150 323 0.19% 0.09% 33.07%
128 Asia TW Taiwan 23 884 021 0.57% 0.09% 0.02%
129 Europe ES Spain 46 783 030 0.15% 0.09% 27.32%
130 Europe NO Norway 5 487 352 0.16% 0.09% 15.39%
131 Asia AE Arab Emirates 10 076 717 0.16% 0.09% 2.84%
132 Europe NL Netherlands 17 194 015 0.19% 0.09% 17.36%
133 Europe CH Switzerland 8 753 333 0.18% 0.08% 28.25%
134 Africa LR Liberia 5 242 850 0.36% 0.08% 0.10%
135 Asia SA Saudi Arabia 35 658 981 0.32% 0.07% 1.02%
136 Europe DK Denmark 5 824 020 0.11% 0.07% 41.90%
137 Australia/Oceania AU Australia 25 961 200 0.13% 0.07% 20.16%
138 Asia JP Japan 125 872 394 0.50% 0.07% 1.06%
139 North America DO Dominican R. 11 017 543 0.17% 0.05% 4.15%
140 Europe IE Ireland 5 023 789 0.12% 0.04% 35.12%
141 Asia QA Qatar 2 807 805 0.05% 0.04% 9.91%
142 Asia IL Israel 9 326 000 0.12% 0.03% 36.47%
143 Asia KW Kuwait 4 369 023 0.07% 0.03% 6.35%
144 Africa BI Burundi 12 442 129 0.00% 0.00% 0.45%
145 Asia HK Hong Kong 7 591 837 0.00% 0.00% 0.03%
146 Asia PS Palestine 5 286 143 0.00% 0.00% 0.15%
147 Asia TJ Tajikistan 9 871 366 0.00% 0.00% 0.00%
148 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
149 Europe TM Turkmenistan 6 118 000 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 33 687 878 203 932 6.054
2 Europe BG Bulgaria 6 866 833 32 546 4.740
3 Europe BA Bosnia and Herzegovina 3 248 979 13 951 4.294
4 Europe HU Hungary 9 622 081 40 944 4.255
5 Europe MK North Macedonia 2 083 241 8 186 3.929
6 Asia GE Georgia 3 977 221 14 662 3.687
7 Europe CZ Czechia 10 739 974 37 001 3.445
8 Europe HR Croatia 4 065 767 13 336 3.280
9 Europe SK Slovakia 5 463 768 17 609 3.223
10 Europe RO Romania 19 037 459 59 468 3.124
11 Europe SI Slovenia 2 079 384 6 234 2.998
12 Europe LT Lithuania 2 663 020 7 729 2.902
13 South America BR Brazil 214 915 961 622 021 2.894
14 Europe PL Poland 37 781 943 103 628 2.743
15 Asia AM Armenia 2 971 883 8 026 2.701
16 Europe MD Moldova 4 019 336 10 497 2.612
17 South America AR Argentina 45 842 519 118 693 2.589
18 North America US USA 334 030 063 852 908 2.553
19 South America CO Colombia 51 728 566 131 654 2.545
20 Europe BE Belgium 11 668 299 28 759 2.465
21 Europe IT Italy 60 323 122 142 817 2.368
22 South America PY Paraguay 7 269 138 16 904 2.325
23 North America MX Mexico 131 045 037 302 210 2.306
24 Europe UA Ukraine 43 323 817 99 060 2.287
25 Europe GB United Kingdom 68 442 235 153 277 2.240
26 Europe RU Russia 146 032 083 325 431 2.228
27 Europe GR Greece 10 343 620 22 452 2.171
28 Africa TN Tunisia 12 011 455 25 899 2.156
29 South America CL Chile 19 372 103 39 471 2.038
30 Europe ES Spain 46 783 030 91 599 1.958
31 Europe PT Portugal 10 150 323 19 477 1.919
32 Europe FR France 65 498 824 125 528 1.917
33 South America EC Ecuador 18 060 665 34 232 1.895
34 South America UY Uruguay 3 492 509 6 263 1.793
35 South America BO Bolivia 11 921 255 20 461 1.716
36 North America PA Panama 4 420 639 7 569 1.712
37 Africa ZA South Africa 60 474 528 93 900 1.553
38 Asia IR Iran 85 669 059 132 180 1.543
39 Europe SE Sweden 10 197 485 15 631 1.533
40 Europe RS Serbia 8 682 461 13 213 1.522
41 Europe AT Austria 9 086 551 13 510 1.487
42 Africa NA Namibia 2 612 616 3 864 1.479
43 North America CR Costa Rica 5 166 659 7 434 1.439
44 Asia LB Lebanon 6 777 757 9 442 1.393
45 Europe CH Switzerland 8 753 333 12 142 1.387
46 Europe DE Germany 84 201 843 116 516 1.384
47 Asia JO Jordan 10 361 084 13 039 1.258
48 Europe NL Netherlands 17 194 015 21 189 1.232
49 Europe IE Ireland 5 023 789 6 087 1.212
50 Europe AL Albania 2 872 895 3 294 1.147
51 South America PR Puerto Rico 3 193 694 3 593 1.125
52 Africa BW Botswana 2 425 610 2 544 1.049
53 North America HN Honduras 10 150 147 10 458 1.030
54 Asia TR Turkey 85 754 170 85 604 0.998
55 Asia MY Malaysia 33 012 522 31 863 0.965
56 Asia KZ Kazakhstan 19 126 888 18 357 0.960
57 Asia IL Israel 9 326 000 8 393 0.900
58 North America GT Guatemala 18 432 019 16 208 0.879
59 North America JM Jamaica 2 981 327 2 583 0.866
60 Africa LY Libya 7 016 958 5 904 0.841
61 North America CA Canada 38 258 213 32 103 0.839
62 Asia AZ Azerbaijan 10 281 695 8 577 0.834
63 Asia OM Oman 5 308 896 4 126 0.777
64 North America CU Cuba 11 315 830 8 357 0.739
65 Asia LK Sri Lanka 21 553 297 15 270 0.709
66 Europe BY Belarus 9 444 474 5 898 0.625
67 Europe DK Denmark 5 824 020 3 562 0.612
68 Asia MN Mongolia 3 360 577 2 016 0.600
69 North America SV El Salvador 6 537 253 3 844 0.588
70 Asia IQ Iraq 41 628 580 24 276 0.583
71 Asia KW Kuwait 4 369 023 2 481 0.568
72 Asia ID Indonesia 278 033 665 144 215 0.519
73 Asia PH Philippines 111 854 893 53 200 0.476
74 Asia KG Kyrgyzstan 6 691 963 2 845 0.425
75 Africa MA Morocco 37 592 691 15 044 0.400
76 Asia NP Nepal 29 953 509 11 639 0.389
77 North America DO Dominican R. 11 017 543 4 276 0.388
78 Asia VN Vietnam 98 704 378 36 431 0.369
79 Asia MM Myanmar 54 978 693 19 308 0.351
80 Asia IN India 1 401 161 559 488 870 0.349
81 Africa ZW Zimbabwe 15 200 203 5 282 0.347
82 Europe FI Finland 5 554 147 1 815 0.327
83 Africa LS Lesotho 2 168 734 690 0.318
84 Asia TH Thailand 70 073 197 22 013 0.314
85 Europe NO Norway 5 487 352 1 414 0.258
86 Asia SA Saudi Arabia 35 658 981 8 916 0.250
87 Asia QA Qatar 2 807 805 633 0.225
88 Asia AE Arab Emirates 10 076 717 2 209 0.219
89 Africa EG Egypt 105 342 137 22 276 0.211
90 Africa ZM Zambia 19 185 632 3 884 0.202
91 South America VE Venezuela 28 310 238 5 395 0.191
92 Africa MR Mauritania 4 839 988 919 0.190
93 Asia AF Afghanistan 40 294 100 7 386 0.183
94 Asia KH Cambodia 17 079 678 3 015 0.176
95 Asia BD Bangladesh 167 247 937 28 195 0.169
96 Asia SY Syria 18 162 836 2 959 0.163
97 Asia JP Japan 125 872 394 18 485 0.147
98 Africa DZ Algeria 45 085 057 6 467 0.143
99 Asia SG Singapore 5 922 099 846 0.143
100 Africa GM Gambia 2 522 383 347 0.138
101 Africa GA Gabon 2 307 540 299 0.130
102 Asia PK Pakistan 227 575 840 29 050 0.128
103 Asia KR South Korea 51 338 018 6 526 0.127
104 Africa MW Malawi 19 899 799 2 506 0.126
105 Australia/Oceania AU Australia 25 961 200 2 954 0.114
106 Africa SN Senegal 17 431 071 1 919 0.110
107 Africa RW Rwanda 13 452 288 1 422 0.106
108 Africa KE Kenya 55 616 509 5 543 0.100
109 Africa SO Somalia 16 583 651 1 335 0.081
110 Africa GW Guinea-Bissau 2 040 454 154 0.075
111 Africa SD Sudan 45 444 056 3 393 0.075
112 Africa UG Uganda 47 989 608 3 472 0.072
113 Asia LA Laos 7 440 138 509 0.068
114 Africa CM Cameroon 27 575 039 1 867 0.068
115 North America HT Haiti 11 619 253 780 0.067
116 Africa MZ Mozambique 32 618 926 2 150 0.066
117 Africa CG Congo 5 729 635 371 0.065
118 Australia/Oceania PG Papua New Guinea 9 211 126 596 0.065
119 Asia YE Yemen 30 849 332 1 995 0.065
120 Africa ET Ethiopia 119 398 868 7 220 0.060
121 Africa LR Liberia 5 242 850 288 0.055
122 Africa AO Angola 34 457 759 1 883 0.055
123 Asia UZ Uzbekistan 34 225 348 1 534 0.045
124 Africa GH Ghana 32 083 509 1 367 0.043
125 Africa MG Madagascar 28 799 689 1 169 0.041
126 Asia TW Taiwan 23 884 021 851 0.036
127 Africa ML Mali 21 158 994 705 0.033
128 North America NI Nicaragua 6 747 441 219 0.033
129 Africa TG Togo 8 580 963 266 0.031
130 Africa GN Guinea 13 687 504 412 0.030
131 Asia HK Hong Kong 7 591 837 213 0.028
132 Africa CI Ivory Coast 27 395 647 765 0.028
133 Africa ER Eritrea 3 622 939 91 0.025
134 Africa CF Central African R. 4 960 640 109 0.022
135 Africa BF Burkina Faso 21 795 816 353 0.016
136 Africa SL Sierra Leone 8 229 738 125 0.015
137 Africa NG Nigeria 214 097 230 3 123 0.015
138 Africa CD DR Congo 93 800 235 1 278 0.014
139 Africa BJ Benin 12 617 712 163 0.013
140 Africa TZ Tanzania 62 383 386 753 0.012
141 Africa SS South Sudan 11 398 347 137 0.012
142 Africa NE Niger 25 570 103 296 0.012
143 Africa TD Chad 17 159 734 185 0.011
144 Australia/Oceania NZ New Zealand 5 002 100 52 0.010
145 Asia PS Palestine 5 286 143 7 0.001
146 Africa BI Burundi 12 442 129 14 0.001
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 9 871 366 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"