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": 2022-01-22 13:32
(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 +0 (+0) +0 (+0)
CZ Czechia +26 597 (+26 923) +9 (+18)
DE Germany +0 (+138 634) +0 (+175)
HU Hungary +0 (+15 957) +0 (+65)
PL Poland +40 876 (+36 667) +193 (+248)
SK Slovakia, [gov], [okr]+6 478 (+7 035) +35 (+57)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Europe 756 338 364 7.07% 15.61% 20.24%
2 North America 595 856 169 5.03% 13.45% 16.50%
3 Australia/Oceania 43 586 060 3.61% 12.47% 13.72%
4 South America 439 532 990 1.67% 5.07% 9.54%
5 Asia 4 687 071 694 0.40% 0.84% 1.58%
6 Africa 1 389 790 554 0.17% 0.37% 0.32%

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 1 389 790 554 1.20% 0.88% 0.37%
2 Asia 4 687 071 694 1.07% 0.59% 0.84%
3 Europe 756 338 364 0.83% 0.43% 15.61%
4 South America 439 532 990 1.03% 0.42% 5.07%
5 North America 595 856 169 0.82% 0.40% 13.45%
6 Australia/Oceania 43 586 060 0.22% 0.09% 12.47%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 439 532 990 1 205 661 2.743
2 North America 595 856 169 1 258 691 2.112
3 Europe 756 338 364 1 589 331 2.101
4 Asia 4 687 071 694 1 272 780 0.272
5 Africa 1 389 790 554 236 141 0.170
6 Australia/Oceania 43 586 060 5 577 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 10.46% 37.37% 84.27%
2 Europe DK Denmark 5 823 908 16.51% 43.62% 69.62%
3 Europe FR France 65 498 037 13.49% 43.07% 62.43%
4 Europe PT Portugal 10 150 485 10.38% 34.50% 51.27%
5 Europe SI Slovenia 2 079 382 14.05% 24.54% 49.29%
6 South America UY Uruguay 3 492 443 4.81% 17.27% 35.45%
7 Europe BE Belgium 11 668 024 12.60% 22.72% 35.43%
8 Europe IT Italy 60 323 606 8.20% 27.35% 35.26%
9 Europe SE Sweden 10 197 141 5.82% 18.76% 34.22%
10 North America PA Panama 4 420 267 3.38% 11.80% 28.88%
11 South America AR Argentina 45 840 255 5.06% 18.85% 28.86%
12 Europe CH Switzerland 8 752 988 11.66% 28.56% 28.70%
13 Europe NO Norway 5 487 121 7.48% 16.66% 28.16%
14 Europe NL Netherlands 17 193 809 10.39% 17.77% 27.69%
15 North America US USA 334 019 477 7.98% 21.41% 26.26%
16 Europe AT Austria 9 086 270 8.87% 12.40% 26.08%
17 Europe ES Spain 46 782 931 8.60% 27.90% 25.82%
18 Europe LT Lithuania 2 663 226 10.50% 14.15% 24.19%
19 Europe HR Croatia 4 065 905 11.38% 17.36% 23.83%
20 Europe CZ Czechia 10 739 865 9.70% 11.03% 23.12%
21 South America PR Puerto Rico 3 193 694 7.76% 28.61% 22.79%
22 Australia/Oceania AU Australia 25 959 584 5.82% 20.64% 22.53%
23 Asia GE Georgia 3 977 262 11.01% 12.38% 22.23%
24 Europe GR Greece 10 343 896 10.85% 27.57% 21.58%
25 Europe RS Serbia 8 682 653 7.20% 10.69% 20.82%
26 Europe IE Ireland 5 023 488 14.97% 36.75% 19.24%
27 Europe GB United Kingdom 68 440 290 11.90% 23.74% 16.11%
28 Asia QA Qatar 2 807 805 2.89% 9.98% 15.84%
29 South America PE Peru 33 685 367 1.82% 6.11% 15.72%
30 Europe FI Finland 5 554 100 5.19% 14.40% 14.26%
31 Europe BG Bulgaria 6 867 117 5.55% 8.19% 14.21%
32 Europe DE Germany 84 200 383 5.25% 7.96% 13.96%
33 Europe HU Hungary 9 622 214 6.05% 6.97% 13.26%
34 South America BO Bolivia 11 920 384 2.49% 7.57% 11.99%
35 Asia KW Kuwait 4 368 678 1.67% 6.41% 11.04%
36 Europe SK Slovakia 5 463 753 9.22% 6.65% 10.63%
37 North America CR Costa Rica 5 166 405 2.35% 5.31% 10.51%
38 Asia LB Lebanon 6 777 923 3.33% 8.30% 9.49%
39 Asia TR Turkey 85 749 213 4.49% 7.37% 9.39%
40 Europe MK North Macedonia 2 083 241 3.09% 5.93% 9.31%
41 Europe AL Albania 2 872 912 2.73% 5.23% 9.19%
42 Europe RO Romania 19 038 156 4.26% 3.85% 8.79%
43 Europe BA Bosnia and Herzegovina 3 249 090 3.06% 5.33% 8.65%
44 Europe PL Poland 37 782 168 4.19% 4.94% 8.43%
45 Asia KZ Kazakhstan 19 125 661 1.35% 2.81% 8.41%
46 Africa TN Tunisia 12 010 779 1.03% 3.50% 7.94%
47 North America CA Canada 38 256 407 3.34% 10.01% 7.92%
48 South America PY Paraguay 7 268 659 0.86% 3.14% 7.55%
49 Europe MD Moldova 4 019 387 2.94% 3.10% 7.53%
50 South America CO Colombia 51 725 604 1.37% 4.21% 7.11%
51 South America CL Chile 19 371 207 1.47% 2.88% 6.76%
52 North America DO Dominican R. 11 016 949 1.59% 4.31% 6.44%
53 South America BR Brazil 214 907 717 1.07% 2.54% 6.15%
54 North America JM Jamaica 2 981 257 1.22% 3.42% 5.02%
55 Asia JO Jordan 10 360 531 2.96% 3.01% 4.73%
56 Asia MN Mongolia 3 360 288 3.69% 3.13% 4.70%
57 Africa BW Botswana 2 425 350 2.89% 6.47% 4.43%
58 South America EC Ecuador 18 059 200 0.71% 2.17% 4.03%
59 Europe UA Ukraine 43 325 246 3.38% 1.95% 3.72%
60 Asia AE Arab Emirates 10 076 064 0.85% 2.95% 3.56%
61 North America CU Cuba 11 315 868 1.62% 1.80% 3.50%
62 Asia PH Philippines 111 846 922 0.82% 1.85% 3.46%
63 Asia JP Japan 125 874 500 0.30% 1.07% 3.22%
64 Asia NP Nepal 29 950 642 0.38% 1.04% 3.18%
65 Europe RU Russia 146 031 742 2.51% 1.99% 3.18%
66 Asia SG Singapore 5 921 848 3.68% 1.62% 3.09%
67 Asia OM Oman 5 308 184 0.28% 1.01% 2.56%
68 North America MX Mexico 131 037 639 0.68% 1.83% 2.52%
69 Asia IN India 1 401 087 479 0.38% 1.18% 2.51%
70 Asia VN Vietnam 98 699 597 1.40% 2.12% 2.07%
71 Asia AM Armenia 2 971 853 3.17% 0.91% 2.03%
72 Africa MA Morocco 37 590 301 0.40% 1.31% 1.96%
73 Asia SA Saudi Arabia 35 656 016 0.27% 1.03% 1.85%
74 Europe BY Belarus 9 444 491 2.10% 1.48% 1.80%
75 Africa LY Libya 7 016 448 0.97% 1.12% 1.64%
76 North America GT Guatemala 18 430 206 0.66% 0.84% 1.54%
77 Asia IQ Iraq 41 623 636 0.38% 0.51% 1.49%
78 Asia KG Kyrgyzstan 6 691 375 0.25% 0.61% 1.48%
79 Asia TH Thailand 70 072 243 1.19% 0.96% 1.31%
80 Asia LA Laos 7 439 561 1.45% 1.45% 1.28%
81 Asia KR South Korea 51 337 777 0.84% 1.06% 1.28%
82 Asia MY Malaysia 33 010 256 2.02% 1.17% 1.18%
83 Africa MR Mauritania 4 839 318 0.44% 1.38% 1.17%
84 Asia AZ Azerbaijan 10 281 196 1.49% 0.71% 1.04%
85 South America VE Venezuela 28 310 676 0.37% 0.30% 0.76%
86 Africa ZA South Africa 60 470 442 1.13% 1.48% 0.69%
87 North America HN Honduras 10 149 286 0.25% 0.31% 0.69%
88 Africa ZM Zambia 19 182 807 0.48% 1.64% 0.62%
89 Africa NA Namibia 2 612 364 1.06% 2.21% 0.60%
90 Africa GA Gabon 2 307 252 0.74% 1.36% 0.56%
91 Asia BD Bangladesh 167 238 978 0.07% 0.19% 0.52%
92 Asia PS Palestine 5 285 493 0.03% 0.11% 0.48%
93 Asia IR Iran 85 663 184 0.87% 0.29% 0.46%
94 Africa RW Rwanda 13 450 528 0.23% 0.74% 0.41%
95 Asia UZ Uzbekistan 34 222 696 0.12% 0.17% 0.41%
96 Asia LK Sri Lanka 21 552 807 0.41% 0.34% 0.36%
97 Africa GW Guinea-Bissau 2 040 199 0.06% 0.16% 0.32%
98 North America SV El Salvador 6 537 075 0.34% 0.16% 0.31%
99 Africa GM Gambia 2 522 010 0.07% 0.24% 0.31%
100 Africa CG Congo 5 728 890 0.16% 0.27% 0.29%
101 Africa DZ Algeria 45 080 724 0.07% 0.15% 0.28%
102 Africa CM Cameroon 27 571 417 0.10% 0.08% 0.28%
103 Asia PK Pakistan 227 552 363 0.05% 0.11% 0.27%
104 Africa ZW Zimbabwe 15 199 020 0.65% 0.75% 0.26%
105 Africa LS Lesotho 2 168 641 0.81% 1.09% 0.23%
106 Africa MZ Mozambique 32 614 122 0.22% 0.70% 0.22%
107 Africa SN Senegal 17 428 651 0.06% 0.22% 0.21%
108 Africa ER Eritrea 3 622 671 0.07% 0.15% 0.16%
109 Australia/Oceania NZ New Zealand 5 002 100 0.23% 0.15% 0.16%
110 Africa EG Egypt 105 331 574 0.10% 0.10% 0.13%
111 Africa ML Mali 21 155 793 0.07% 0.19% 0.12%
112 Africa AO Angola 34 452 146 0.12% 0.35% 0.12%
113 Africa GH Ghana 32 079 958 0.09% 0.27% 0.11%
114 Africa MW Malawi 19 897 089 0.11% 0.33% 0.11%
115 Africa TG Togo 8 579 900 0.13% 0.42% 0.11%
116 Africa SD Sudan 45 438 446 0.03% 0.07% 0.11%
117 Africa MG Madagascar 28 795 787 0.04% 0.12% 0.10%
118 Africa ET Ethiopia 119 383 260 0.10% 0.26% 0.10%
119 Africa KE Kenya 55 610 021 0.13% 0.35% 0.10%
120 Africa UG Uganda 47 981 676 0.08% 0.25% 0.09%
121 North America HT Haiti 11 618 493 0.06% 0.08% 0.09%
122 Africa BI Burundi 12 440 185 0.16% 0.43% 0.08%
123 Asia ID Indonesia 278 017 870 0.03% 0.03% 0.08%
124 Africa CI Ivory Coast 27 392 067 0.07% 0.25% 0.07%
125 Africa CF Central African R. 4 960 180 0.04% 0.12% 0.07%
126 Africa GN Guinea 13 685 550 0.04% 0.14% 0.07%
127 Africa TZ Tanzania 62 374 052 0.01% 0.04% 0.05%
128 Africa BF Burkina Faso 21 792 672 0.03% 0.06% 0.04%
129 Africa SL Sierra Leone 8 228 850 0.01% 0.05% 0.04%
130 Africa BJ Benin 12 615 970 0.03% 0.04% 0.04%
131 Asia AF Afghanistan 40 289 298 0.01% 0.02% 0.04%
132 Africa CD DR Congo 93 785 289 0.03% 0.06% 0.04%
133 Asia TW Taiwan 23 883 787 0.01% 0.02% 0.03%
134 Africa TD Chad 17 157 148 0.01% 0.03% 0.03%
135 Africa LR Liberia 5 242 199 0.03% 0.10% 0.03%
136 Africa SS South Sudan 11 397 630 0.04% 0.10% 0.03%
137 Asia MM Myanmar 54 976 703 0.14% 0.03% 0.02%
138 Asia KH Cambodia 17 078 413 0.08% 0.01% 0.02%
139 Asia SY Syria 18 160 506 0.11% 0.02% 0.02%
140 Asia HK Hong Kong 7 591 505 0.01% 0.02% 0.02%
141 Asia YE Yemen 30 845 734 0.01% 0.01% 0.02%
142 North America NI Nicaragua 6 747 011 0.04% 0.01% 0.01%
143 Africa NE Niger 25 565 285 0.01% 0.02% 0.01%
144 Africa NG Nigeria 214 069 227 0.02% 0.04% 0.01%
145 Asia TJ Tajikistan 9 870 193 0.00% 0.00% 0.00%
146 Australia/Oceania PG Papua New Guinea 9 210 199 0.19% 0.02% 0.00%
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 CN China 1 439 323 776 0.00% 0.00% 0.00%
150 Africa SO Somalia 16 581 219 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 30 845 734 19.27% (8.96)% (0.01)%
2 Asia SY Syria 18 160 506 3.81% (8.71)% (0.02)%
3 Asia AF Afghanistan 40 289 298 4.53% (4.72)% (0.02)%
4 Europe RU Russia 146 031 742 3.48% 3.76% 1.99%
5 North America NI Nicaragua 6 747 011 0.48% (3.13)% (0.01)%
6 Europe UA Ukraine 43 325 246 3.10% 3.09% 1.95%
7 Africa EG Egypt 105 331 574 5.06% 2.94% 0.10%
8 Asia KH Cambodia 17 078 413 4.51% (2.66)% (0.01)%
9 Europe PL Poland 37 782 168 2.02% 2.63% 4.94%
10 Europe BA Bosnia and Herzegovina 3 249 090 4.08% 2.53% 5.33%
11 Asia LK Sri Lanka 21 552 807 2.89% 2.45% 0.34%
12 Europe BG Bulgaria 6 867 117 3.66% 2.40% 8.19%
13 Africa DZ Algeria 45 080 724 3.00% 2.30% 0.15%
14 Europe MD Moldova 4 019 387 3.05% 2.29% 3.10%
15 Europe HU Hungary 9 622 214 2.09% 2.23% 6.97%
16 Asia AM Armenia 2 971 853 2.95% 2.13% 0.91%
17 Africa MG Madagascar 28 795 787 1.88% 2.08% 0.12%
18 Africa NE Niger 25 565 285 3.95% (2.02)% (0.02)%
19 Asia AZ Azerbaijan 10 281 196 1.39% 2.00% 0.71%
20 North America SV El Salvador 6 537 075 2.97% 1.82% 0.16%
21 Asia IR Iran 85 663 184 1.63% 1.79% 0.29%
22 Africa SD Sudan 45 438 446 4.28% 1.76% 0.07%
23 Africa ER Eritrea 3 622 671 2.25% 1.73% 0.15%
24 Africa LY Libya 7 016 448 1.98% 1.69% 1.12%
25 Europe SK Slovakia 5 463 753 1.06% 1.67% 6.65%
26 Asia GE Georgia 3 977 262 1.49% 1.56% 12.38%
27 Asia ID Indonesia 278 017 870 3.44% 1.50% 0.03%
28 Australia/Oceania PG Papua New Guinea 9 210 199 2.12% 1.48% 0.02%
29 Europe MK North Macedonia 2 083 241 2.85% 1.44% 5.93%
30 Africa NA Namibia 2 612 364 1.43% 1.43% 2.21%
31 Europe BY Belarus 9 444 491 0.91% 1.34% 1.48%
32 Asia MM Myanmar 54 976 703 2.10% 1.24% 0.03%
33 South America PY Paraguay 7 268 659 2.54% 1.24% 3.14%
34 Asia KG Kyrgyzstan 6 691 375 2.21% 1.23% 0.61%
35 Europe RO Romania 19 038 156 3.13% 1.21% 3.85%
36 Asia VN Vietnam 98 699 597 1.38% 1.16% 2.12%
37 Africa BF Burkina Faso 21 792 672 2.92% 1.09% 0.06%
38 Africa ZW Zimbabwe 15 199 020 0.70% 1.06% 0.75%
39 Asia KR South Korea 51 337 777 1.01% 1.05% 1.06%
40 Africa CM Cameroon 27 571 417 2.06% 1.05% 0.08%
41 Africa ZA South Africa 60 470 442 1.07% 1.05% 1.48%
42 South America EC Ecuador 18 059 200 1.75% 1.04% 2.17%
43 North America HN Honduras 10 149 286 3.03% 1.01% 0.31%
44 Asia JO Jordan 10 360 531 0.84% 0.99% 3.01%
45 Africa MW Malawi 19 897 089 1.13% 0.98% 0.33%
46 Asia IQ Iraq 41 623 636 1.62% 0.96% 0.51%
47 Africa GW Guinea-Bissau 2 040 199 2.34% 0.89% 0.16%
48 North America HT Haiti 11 618 493 2.70% 0.88% 0.08%
49 Europe HR Croatia 4 065 905 1.15% 0.86% 17.36%
50 Asia UZ Uzbekistan 34 222 696 0.88% 0.85% 0.17%
51 South America VE Venezuela 28 310 676 1.05% 0.85% 0.30%
52 Africa TN Tunisia 12 010 779 1.70% 0.82% 3.50%
53 South America CL Chile 19 371 207 0.97% 0.80% 2.88%
54 Asia PH Philippines 111 846 922 1.92% 0.80% 1.85%
55 North America MX Mexico 131 037 639 2.74% 0.78% 1.83%
56 Africa CD DR Congo 93 785 289 0.79% 0.76% 0.06%
57 Europe LT Lithuania 2 663 226 1.14% 0.75% 14.15%
58 Asia LA Laos 7 439 561 0.47% 0.75% 1.45%
59 South America PE Peru 33 685 367 1.54% 0.71% 6.11%
60 South America BR Brazil 214 907 717 1.68% 0.69% 2.54%
61 North America JM Jamaica 2 981 257 2.45% 0.69% 3.42%
62 South America BO Bolivia 11 920 384 0.85% 0.66% 7.57%
63 Asia MY Malaysia 33 010 256 0.96% 0.65% 1.17%
64 Africa UG Uganda 47 981 676 0.92% 0.65% 0.25%
65 Europe CZ Czechia 10 739 865 0.72% 0.65% 11.03%
66 Asia PK Pakistan 227 552 363 1.62% 0.63% 0.11%
67 Africa ML Mali 21 155 793 1.21% 0.61% 0.19%
68 South America CO Colombia 51 725 604 1.11% 0.61% 4.21%
69 North America GT Guatemala 18 430 206 2.38% 0.61% 0.84%
70 Africa CF Central African R. 4 960 180 0.45% 0.59% 0.12%
71 Europe DE Germany 84 200 383 0.62% 0.56% 7.96%
72 Europe RS Serbia 8 682 653 0.93% 0.54% 10.69%
73 Africa AO Angola 34 452 146 1.02% 0.53% 0.35%
74 Africa GN Guinea 13 685 550 0.68% 0.50% 0.14%
75 Asia KZ Kazakhstan 19 125 661 1.46% 0.48% 2.81%
76 Asia IN India 1 401 087 479 1.23% 0.47% 1.18%
77 Africa TD Chad 17 157 148 0.72% 0.47% 0.03%
78 Africa TZ Tanzania 62 374 052 0.13% 0.47% 0.04%
79 Africa GM Gambia 2 522 010 1.04% 0.46% 0.24%
80 Europe AL Albania 2 872 912 1.00% 0.46% 5.23%
81 Asia BD Bangladesh 167 238 978 1.15% 0.45% 0.19%
82 Africa MR Mauritania 4 839 318 0.82% 0.44% 1.38%
83 Africa GH Ghana 32 079 958 0.79% 0.44% 0.27%
84 Africa NG Nigeria 214 069 227 0.92% 0.44% 0.04%
85 Africa ET Ethiopia 119 383 260 1.54% 0.43% 0.26%
86 Africa SL Sierra Leone 8 228 850 0.40% 0.42% 0.05%
87 Asia LB Lebanon 6 777 923 0.61% 0.41% 8.30%
88 Africa SN Senegal 17 428 651 0.82% 0.40% 0.22%
89 Asia TH Thailand 70 072 243 0.69% 0.39% 0.96%
90 Europe GR Greece 10 343 896 0.78% 0.38% 27.57%
91 Asia TR Turkey 85 749 213 0.65% 0.38% 7.37%
92 North America US USA 334 019 477 0.76% 0.36% 21.41%
93 Africa RW Rwanda 13 450 528 0.65% 0.35% 0.74%
94 Africa CI Ivory Coast 27 392 067 0.90% 0.35% 0.25%
95 Africa LS Lesotho 2 168 641 1.67% 0.31% 1.09%
96 Africa MZ Mozambique 32 614 122 0.36% 0.30% 0.70%
97 Africa BW Botswana 2 425 350 0.26% 0.30% 6.47%
98 Africa MA Morocco 37 590 301 0.80% 0.29% 1.31%
99 Africa KE Kenya 55 610 021 0.68% 0.29% 0.35%
100 Asia NP Nepal 29 950 642 0.86% 0.29% 1.04%
101 North America PA Panama 4 420 267 0.49% 0.27% 11.80%
102 North America CR Costa Rica 5 166 405 1.24% 0.27% 5.31%
103 Europe SI Slovenia 2 079 382 0.57% 0.26% 24.54%
104 North America CA Canada 38 256 407 0.41% 0.25% 10.01%
105 Africa ZM Zambia 19 182 807 0.28% 0.24% 1.64%
106 Europe IT Italy 60 323 606 0.33% 0.22% 27.35%
107 Africa TG Togo 8 579 900 0.44% 0.22% 0.42%
108 Asia OM Oman 5 308 184 0.45% 0.21% 1.01%
109 Asia MN Mongolia 3 360 288 0.68% 0.20% 3.13%
110 Europe AT Austria 9 086 270 0.40% 0.20% 12.40%
111 Africa GA Gabon 2 307 252 0.68% 0.19% 1.36%
112 Asia SG Singapore 5 921 848 0.36% 0.18% 1.62%
113 Africa BJ Benin 12 615 970 0.20% 0.18% 0.04%
114 Australia/Oceania NZ New Zealand 5 002 100 0.23% 0.17% 0.15%
115 Africa SO Somalia 16 581 219 4.50% 0.17% 0.03%
116 South America PR Puerto Rico 3 193 694 0.23% 0.16% 28.61%
117 Europe GB United Kingdom 68 440 290 0.23% 0.15% 23.74%
118 Europe BE Belgium 11 668 024 0.25% 0.14% 22.72%
119 South America UY Uruguay 3 492 443 0.23% 0.14% 17.27%
120 South America AR Argentina 45 840 255 0.26% 0.13% 18.85%
121 North America CU Cuba 11 315 868 0.60% 0.13% 1.80%
122 Europe FR France 65 498 037 0.18% 0.12% 43.07%
123 Africa CG Congo 5 728 890 2.06% 0.12% 0.27%
124 Europe FI Finland 5 554 100 0.29% 0.12% 14.40%
125 Africa SS South Sudan 11 397 630 0.34% 0.11% 0.10%
126 Europe SE Sweden 10 197 141 0.19% 0.11% 18.76%
127 Europe PT Portugal 10 150 485 0.21% 0.11% 34.50%
128 Europe NL Netherlands 17 193 809 0.20% 0.11% 17.77%
129 Asia TW Taiwan 23 883 787 0.61% 0.10% 0.02%
130 Asia AE Arab Emirates 10 076 064 0.18% 0.10% 2.95%
131 Asia JP Japan 125 874 500 0.66% 0.09% 1.07%
132 Europe NO Norway 5 487 121 0.17% 0.09% 16.66%
133 Europe ES Spain 46 782 931 0.15% 0.09% 27.90%
134 Asia SA Saudi Arabia 35 656 016 0.40% 0.09% 1.03%
135 Europe DK Denmark 5 823 908 0.12% 0.08% 43.62%
136 Africa LR Liberia 5 242 199 0.36% 0.08% 0.10%
137 Australia/Oceania AU Australia 25 959 584 0.15% 0.08% 20.64%
138 Europe CH Switzerland 8 752 988 0.17% 0.08% 28.56%
139 North America DO Dominican R. 11 016 949 0.18% 0.07% 4.31%
140 Europe IE Ireland 5 023 488 0.12% 0.04% 36.75%
141 Asia QA Qatar 2 807 805 0.05% 0.04% 9.98%
142 Asia KW Kuwait 4 368 678 0.08% 0.04% 6.41%
143 Asia IL Israel 9 326 000 0.13% 0.03% 37.37%
144 Africa BI Burundi 12 440 185 0.00% 0.00% 0.43%
145 Asia HK Hong Kong 7 591 505 0.00% 0.00% 0.02%
146 Asia PS Palestine 5 285 493 0.00% 0.00% 0.11%
147 Asia TJ Tajikistan 9 870 193 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 33 685 367 203 876 6.052
2 Europe BG Bulgaria 6 867 117 32 604 4.748
3 Europe BA Bosnia and Herzegovina 3 249 090 13 984 4.304
4 Europe HU Hungary 9 622 214 40 822 4.242
5 Europe MK North Macedonia 2 083 241 8 177 3.925
6 Asia GE Georgia 3 977 262 14 673 3.689
7 Europe CZ Czechia 10 739 865 37 006 3.446
8 Europe HR Croatia 4 065 905 13 335 3.280
9 Europe SK Slovakia 5 463 753 17 612 3.223
10 Europe RO Romania 19 038 156 59 472 3.124
11 Europe SI Slovenia 2 079 382 6 228 2.995
12 Europe LT Lithuania 2 663 226 7 739 2.906
13 South America BR Brazil 214 907 717 622 251 2.895
14 Europe PL Poland 37 782 168 103 819 2.748
15 Asia AM Armenia 2 971 853 8 026 2.701
16 Europe MD Moldova 4 019 387 10 501 2.613
17 South America AR Argentina 45 840 255 118 788 2.591
18 North America US USA 334 019 477 855 111 2.560
19 South America CO Colombia 51 725 604 131 634 2.545
20 Europe BE Belgium 11 668 024 28 780 2.467
21 Europe IT Italy 60 323 606 142 963 2.370
22 South America PY Paraguay 7 268 659 16 910 2.326
23 North America MX Mexico 131 037 639 302 443 2.308
24 Europe UA Ukraine 43 325 246 99 129 2.288
25 Europe GB United Kingdom 68 440 290 153 490 2.243
26 Europe RU Russia 146 031 742 325 433 2.228
27 Europe GR Greece 10 343 896 22 476 2.173
28 Africa TN Tunisia 12 010 779 25 912 2.157
29 South America CL Chile 19 371 207 39 474 2.038
30 Europe ES Spain 46 782 931 91 741 1.961
31 Europe PT Portugal 10 150 485 19 496 1.921
32 Europe FR France 65 498 037 125 646 1.918
33 South America EC Ecuador 18 059 200 34 240 1.896
34 South America UY Uruguay 3 492 443 6 270 1.795
35 South America BO Bolivia 11 920 384 20 505 1.720
36 North America PA Panama 4 420 267 7 563 1.711
37 Africa ZA South Africa 60 470 442 93 949 1.554
38 Asia IR Iran 85 663 184 132 182 1.543
39 Europe SE Sweden 10 197 141 15 631 1.533
40 Europe RS Serbia 8 682 653 13 211 1.522
41 Africa NA Namibia 2 612 364 3 882 1.486
42 Europe AT Austria 9 086 270 13 501 1.486
43 North America CR Costa Rica 5 166 405 7 444 1.441
44 Asia LB Lebanon 6 777 923 9 444 1.393
45 Europe CH Switzerland 8 752 988 12 145 1.387
46 Europe DE Germany 84 200 383 116 660 1.385
47 Asia JO Jordan 10 360 531 13 034 1.258
48 Europe NL Netherlands 17 193 809 21 200 1.233
49 Europe IE Ireland 5 023 488 6 087 1.212
50 Europe AL Albania 2 872 912 3 292 1.146
51 South America PR Puerto Rico 3 193 694 3 593 1.125
52 Africa BW Botswana 2 425 350 2 544 1.049
53 North America HN Honduras 10 149 286 10 471 1.032
54 Asia TR Turkey 85 749 213 85 600 0.998
55 Asia MY Malaysia 33 010 256 31 869 0.965
56 Asia KZ Kazakhstan 19 125 661 18 357 0.960
57 Asia IL Israel 9 326 000 8 372 0.898
58 North America GT Guatemala 18 430 206 16 225 0.880
59 North America JM Jamaica 2 981 257 2 568 0.861
60 Africa LY Libya 7 016 448 5 907 0.842
61 North America CA Canada 38 256 407 32 157 0.841
62 Asia AZ Azerbaijan 10 281 196 8 581 0.835
63 Asia OM Oman 5 308 184 4 125 0.777
64 North America CU Cuba 11 315 868 8 353 0.738
65 Asia LK Sri Lanka 21 552 807 15 272 0.709
66 Europe BY Belarus 9 444 491 5 899 0.625
67 Europe DK Denmark 5 823 908 3 571 0.613
68 Asia MN Mongolia 3 360 288 2 016 0.600
69 North America SV El Salvador 6 537 075 3 844 0.588
70 Asia IQ Iraq 41 623 636 24 277 0.583
71 Asia KW Kuwait 4 368 678 2 481 0.568
72 Asia ID Indonesia 278 017 870 144 206 0.519
73 Asia PH Philippines 111 846 922 53 250 0.476
74 Asia KG Kyrgyzstan 6 691 375 2 846 0.425
75 Africa MA Morocco 37 590 301 15 060 0.401
76 Asia NP Nepal 29 950 642 11 651 0.389
77 North America DO Dominican R. 11 016 949 4 279 0.388
78 Asia VN Vietnam 98 699 597 36 419 0.369
79 Asia MM Myanmar 54 976 703 19 308 0.351
80 Asia IN India 1 401 087 479 488 885 0.349
81 Africa ZW Zimbabwe 15 199 020 5 288 0.348
82 Europe FI Finland 5 554 100 1 815 0.327
83 Africa LS Lesotho 2 168 641 690 0.318
84 Asia TH Thailand 70 072 243 22 019 0.314
85 Europe NO Norway 5 487 121 1 415 0.258
86 Asia SA Saudi Arabia 35 656 016 8 916 0.250
87 Asia QA Qatar 2 807 805 633 0.225
88 Asia AE Arab Emirates 10 076 064 2 208 0.219
89 Africa EG Egypt 105 331 574 22 267 0.211
90 Africa ZM Zambia 19 182 807 3 884 0.203
91 South America VE Venezuela 28 310 676 5 396 0.191
92 Africa MR Mauritania 4 839 318 920 0.190
93 Asia AF Afghanistan 40 289 298 7 387 0.183
94 Asia KH Cambodia 17 078 413 3 015 0.176
95 Asia BD Bangladesh 167 238 978 28 197 0.169
96 Asia SY Syria 18 160 506 2 959 0.163
97 Asia JP Japan 125 874 500 18 478 0.147
98 Africa DZ Algeria 45 080 724 6 468 0.143
99 Asia SG Singapore 5 921 848 846 0.143
100 Africa GM Gambia 2 522 010 347 0.138
101 Africa GA Gabon 2 307 252 300 0.130
102 Asia PK Pakistan 227 552 363 29 054 0.128
103 Asia KR South Korea 51 337 777 6 529 0.127
104 Africa MW Malawi 19 897 089 2 507 0.126
105 Australia/Oceania AU Australia 25 959 584 2 960 0.114
106 Africa SN Senegal 17 428 651 1 921 0.110
107 Africa RW Rwanda 13 450 528 1 428 0.106
108 Africa KE Kenya 55 610 021 5 528 0.099
109 Africa SO Somalia 16 581 219 1 335 0.081
110 Africa GW Guinea-Bissau 2 040 199 153 0.075
111 Africa SD Sudan 45 438 446 3 393 0.075
112 Africa UG Uganda 47 981 676 3 463 0.072
113 Asia LA Laos 7 439 561 514 0.069
114 Africa CM Cameroon 27 571 417 1 867 0.068
115 North America HT Haiti 11 618 493 780 0.067
116 Africa MZ Mozambique 32 614 122 2 149 0.066
117 Africa CG Congo 5 728 890 371 0.065
118 Australia/Oceania PG Papua New Guinea 9 210 199 596 0.065
119 Asia YE Yemen 30 845 734 1 995 0.065
120 Africa ET Ethiopia 119 383 260 7 226 0.060
121 Africa LR Liberia 5 242 199 288 0.055
122 Africa AO Angola 34 452 146 1 884 0.055
123 Asia UZ Uzbekistan 34 222 696 1 536 0.045
124 Africa GH Ghana 32 079 958 1 357 0.042
125 Africa MG Madagascar 28 795 787 1 169 0.041
126 Asia TW Taiwan 23 883 787 851 0.036
127 Africa ML Mali 21 155 793 704 0.033
128 North America NI Nicaragua 6 747 011 219 0.033
129 Africa TG Togo 8 579 900 266 0.031
130 Africa GN Guinea 13 685 550 410 0.030
131 Asia HK Hong Kong 7 591 505 213 0.028
132 Africa CI Ivory Coast 27 392 067 764 0.028
133 Africa ER Eritrea 3 622 671 90 0.025
134 Africa CF Central African R. 4 960 180 109 0.022
135 Africa BF Burkina Faso 21 792 672 353 0.016
136 Africa SL Sierra Leone 8 228 850 125 0.015
137 Africa NG Nigeria 214 069 227 3 124 0.015
138 Africa CD DR Congo 93 785 289 1 278 0.014
139 Africa BJ Benin 12 615 970 163 0.013
140 Africa TZ Tanzania 62 374 052 753 0.012
141 Africa SS South Sudan 11 397 630 137 0.012
142 Africa NE Niger 25 565 285 295 0.011
143 Africa TD Chad 17 157 148 185 0.011
144 Australia/Oceania NZ New Zealand 5 002 100 52 0.010
145 Africa BI Burundi 12 440 185 14 0.001
146 Asia PS Palestine 5 285 493 5 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 9 870 193 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"