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": 2021-09-27 13:24
(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 +1 312 (+1 588) +7 (+8)
CZ Czechia +250 (+415) +0 (+2)
DE Germany +0 (+5 267) +0 (+13)
HU Hungary +1 183 (+0) +20 (+0)
PL Poland +421 (+643) +0 (+1)
SK Slovakia, [gov], [okr]+121 (+689) +0 (+0)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 North America 594 381 453 2.15% 3.50% 2.77%
2 Europe 756 195 227 1.57% 1.89% 1.85%
3 Australia/Oceania 43 417 974 0.37% 0.65% 0.66%
4 South America 438 397 537 2.12% 0.85% 0.62%
5 Asia 4 676 325 848 0.52% 0.51% 0.41%
6 Africa 1 379 501 199 0.25% 0.17% 0.14%

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 South America 438 397 537 2.64% 3.35% 0.85%
2 Africa 1 379 501 199 2.31% 3.30% 0.17%
3 Asia 4 676 325 848 1.73% 1.90% 0.51%
4 North America 594 381 453 1.41% 1.86% 3.50%
5 Europe 756 195 227 1.26% 1.71% 1.89%
6 Australia/Oceania 43 417 974 1.09% 1.41% 0.65%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 438 397 537 1 154 551 2.634
2 North America 594 381 453 1 041 702 1.753
3 Europe 756 195 227 1 216 614 1.609
4 Asia 4 676 325 848 1 109 559 0.237
5 Africa 1 379 501 199 209 890 0.152
6 Australia/Oceania 43 417 974 2 964 0.068

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 RS Serbia 8 693 850 2.29% 7.25% 8.95%
2 North America CU Cuba 11 318 070 6.31% 8.02% 8.00%
3 Asia MN Mongolia 3 343 398 7.04% 10.51% 7.14%
4 Europe LT Lithuania 2 675 276 1.96% 4.38% 6.38%
5 Europe GB United Kingdom 68 326 526 4.66% 5.84% 5.87%
6 Asia IL Israel 9 326 000 4.58% 9.47% 5.81%
7 North America CR Costa Rica 5 151 550 4.06% 5.50% 5.33%
8 Asia MY Malaysia 32 877 696 4.99% 6.51% 5.24%
9 Europe SI Slovenia 2 079 291 1.73% 4.58% 4.97%
10 Asia GE Georgia 3 979 700 6.62% 6.70% 4.84%
11 North America US USA 333 400 157 2.90% 5.10% 3.92%
12 Asia TR Turkey 85 459 264 2.11% 3.41% 3.86%
13 Europe RO Romania 19 078 957 0.61% 2.05% 3.72%
14 Europe HR Croatia 4 073 955 1.08% 2.68% 3.31%
15 Europe IE Ireland 5 005 864 2.53% 3.41% 3.19%
16 Europe MD Moldova 4 022 371 0.84% 2.23% 3.12%
17 Africa BW Botswana 2 410 144 4.98% 3.76% 2.97%
18 Europe AL Albania 2 873 912 1.24% 3.44% 2.95%
19 Asia SG Singapore 5 907 159 0.44% 1.41% 2.93%
20 Asia AM Armenia 2 970 088 1.22% 2.43% 2.92%
21 Europe BG Bulgaria 6 883 742 1.08% 2.48% 2.66%
22 Europe BA Bosnia and Herzegovina 3 255 579 0.85% 2.45% 2.52%
23 Europe GR Greece 10 360 091 2.32% 2.63% 2.51%
24 Europe BY Belarus 9 445 481 1.47% 2.28% 2.49%
25 Europe MK North Macedonia 2 083 268 1.66% 3.11% 2.45%
26 Asia IR Iran 85 319 524 3.09% 3.11% 2.18%
27 Europe AT Austria 9 069 874 1.02% 2.35% 2.14%
28 Asia TH Thailand 70 016 410 2.02% 2.37% 2.02%
29 Asia PH Philippines 111 380 633 1.14% 2.06% 1.91%
30 Europe SK Slovakia 5 462 911 0.35% 1.02% 1.78%
31 Europe UA Ukraine 43 408 795 0.45% 1.04% 1.77%
32 Europe RU Russia 146 011 806 1.63% 1.59% 1.74%
33 North America GT Guatemala 18 324 114 1.60% 1.89% 1.62%
34 Asia KZ Kazakhstan 19 053 882 2.70% 2.43% 1.61%
35 North America JM Jamaica 2 977 135 1.14% 2.33% 1.49%
36 Africa LY Libya 6 986 573 2.18% 1.90% 1.46%
37 North America CA Canada 38 150 737 0.59% 1.23% 1.40%
38 Asia AZ Azerbaijan 10 252 011 1.44% 2.77% 1.36%
39 Europe BE Belgium 11 651 937 1.44% 1.88% 1.33%
40 Europe CH Switzerland 8 732 785 1.59% 2.80% 1.28%
41 Asia VN Vietnam 98 419 911 0.76% 1.41% 1.21%
42 Europe NL Netherlands 17 181 724 2.05% 1.51% 1.16%
43 Asia LB Lebanon 6 787 647 1.21% 1.43% 1.16%
44 Europe DE Germany 84 114 966 0.62% 1.32% 1.14%
45 Africa GA Gabon 2 290 418 0.21% 0.59% 1.11%
46 Asia JO Jordan 10 328 177 0.82% 1.00% 1.03%
47 Europe NO Norway 5 473 588 1.11% 2.15% 0.97%
48 Europe FR France 65 451 999 1.87% 1.58% 0.93%
49 North America HN Honduras 10 098 890 1.26% 1.20% 0.91%
50 South America PR Puerto Rico 3 193 694 1.31% 1.66% 0.88%
51 South America BR Brazil 214 425 443 2.31% 1.23% 0.85%
52 Europe PT Portugal 10 159 948 2.15% 1.42% 0.83%
53 Australia/Oceania AU Australia 25 865 035 0.26% 0.75% 0.77%
54 Asia IQ Iraq 41 334 404 1.94% 1.27% 0.77%
55 North America MX Mexico 130 604 875 0.93% 1.01% 0.77%
56 North America PA Panama 4 398 539 2.02% 1.00% 0.73%
57 Asia LK Sri Lanka 21 524 173 1.55% 1.80% 0.73%
58 Europe DK Denmark 5 817 404 1.33% 1.00% 0.70%
59 Africa TN Tunisia 11 971 272 3.02% 1.57% 0.70%
60 Europe IT Italy 60 351 915 0.74% 0.95% 0.69%
61 Asia LA Laos 7 405 797 0.27% 0.42% 0.69%
62 Europe FI Finland 5 551 357 0.83% 0.93% 0.68%
63 Africa TZ Tanzania 61 827 978 0.04% 0.16% 0.67%
64 North America SV El Salvador 6 526 635 0.44% 0.49% 0.61%
65 Europe SE Sweden 10 177 046 0.80% 1.07% 0.60%
66 Europe HU Hungary 9 630 022 0.18% 0.40% 0.54%
67 Asia KR South Korea 51 323 719 0.32% 0.44% 0.53%
68 Europe CZ Czechia 10 733 533 0.26% 0.40% 0.52%
69 Africa MA Morocco 37 450 484 1.10% 0.92% 0.51%
70 Asia KH Cambodia 17 004 429 0.47% 0.42% 0.50%
71 Asia QA Qatar 2 807 805 0.69% 0.61% 0.50%
72 South America VE Venezuela 28 336 320 0.47% 0.46% 0.48%
73 South America AR Argentina 45 707 808 3.39% 0.77% 0.44%
74 South America UY Uruguay 3 488 605 3.04% 0.45% 0.41%
75 Africa ZA South Africa 60 231 421 2.06% 1.00% 0.41%
76 Asia NP Nepal 29 782 900 0.79% 0.46% 0.39%
77 South America CL Chile 19 318 811 1.46% 0.31% 0.38%
78 Asia AE Arab Emirates 10 037 872 1.67% 0.82% 0.37%
79 Africa NA Namibia 2 597 635 2.79% 0.44% 0.37%
80 Asia MM Myanmar 54 860 292 0.57% 0.52% 0.36%
81 South America CO Colombia 51 552 334 3.12% 0.39% 0.35%
82 Asia PS Palestine 5 247 484 0.02% 0.08% 0.35%
83 North America DO Dominican R. 10 982 200 0.61% 0.29% 0.31%
84 South America PE Peru 33 538 503 0.67% 0.31% 0.29%
85 Europe ES Spain 46 777 162 2.68% 0.88% 0.28%
86 Africa UG Uganda 47 517 666 0.18% 0.26% 0.25%
87 South America BO Bolivia 11 869 474 1.13% 0.33% 0.25%
88 Europe PL Poland 37 795 368 0.08% 0.17% 0.24%
89 Asia JP Japan 125 997 725 0.76% 0.90% 0.24%
90 Asia SY Syria 18 024 209 0.05% 0.12% 0.23%
91 Asia IN India 1 396 753 763 0.41% 0.29% 0.21%
92 Africa BJ Benin 12 514 118 0.12% 0.33% 0.21%
93 Africa RW Rwanda 13 347 581 0.52% 0.33% 0.20%
94 Africa ZW Zimbabwe 15 129 826 0.60% 0.14% 0.19%
95 Asia UZ Uzbekistan 34 067 574 0.21% 0.22% 0.18%
96 Africa BI Burundi 12 326 485 0.10% 0.18% 0.16%
97 Australia/Oceania PG Papua New Guinea 9 155 938 0.04% 0.07% 0.15%
98 Asia KW Kuwait 4 348 478 2.41% 0.21% 0.14%
99 Africa MR Mauritania 4 800 115 0.34% 0.24% 0.14%
100 Asia KG Kyrgyzstan 6 656 934 1.11% 0.19% 0.14%
101 Africa AO Angola 34 123 790 0.06% 0.10% 0.14%
102 North America NI Nicaragua 6 721 822 0.07% 0.11% 0.13%
103 Africa ET Ethiopia 118 470 194 0.06% 0.13% 0.13%
104 South America EC Ecuador 17 973 507 0.47% 0.17% 0.13%
105 Africa TG Togo 8 517 708 0.14% 0.21% 0.13%
106 Africa CG Congo 5 685 342 0.04% 0.04% 0.12%
107 Asia PK Pakistan 226 178 982 0.14% 0.17% 0.11%
108 Asia ID Indonesia 277 093 832 0.86% 0.21% 0.10%
109 Africa SO Somalia 16 438 930 0.03% 0.07% 0.10%
110 Asia BD Bangladesh 166 714 875 0.45% 0.16% 0.09%
111 Africa GH Ghana 31 872 195 0.10% 0.13% 0.09%
112 Africa EG Egypt 104 713 637 0.04% 0.05% 0.08%
113 Asia OM Oman 5 266 535 1.68% 0.14% 0.07%
114 Africa KE Kenya 55 230 515 0.14% 0.11% 0.06%
115 Africa CI Ivory Coast 27 182 627 0.05% 0.08% 0.05%
116 South America PY Paraguay 7 240 657 1.54% 0.09% 0.04%
117 Africa DZ Algeria 44 827 265 0.17% 0.08% 0.04%
118 Africa MG Madagascar 28 567 477 0.01% 0.01% 0.04%
119 Australia/Oceania NZ New Zealand 5 002 100 0.03% 0.07% 0.04%
120 Africa GM Gambia 2 500 222 0.16% 0.07% 0.04%
121 Africa ZM Zambia 19 017 585 0.60% 0.07% 0.03%
122 Africa GN Guinea 13 571 262 0.05% 0.03% 0.03%
123 Africa MZ Mozambique 32 333 112 0.25% 0.07% 0.02%
124 Africa NG Nigeria 212 431 024 0.02% 0.03% 0.02%
125 Africa SS South Sudan 11 355 690 0.01% 0.02% 0.02%
126 Asia AF Afghanistan 40 008 355 0.21% 0.02% 0.02%
127 North America HT Haiti 11 574 066 0.06% 0.02% 0.02%
128 Asia SA Saudi Arabia 35 482 580 0.28% 0.04% 0.02%
129 Africa GW Guinea-Bissau 2 025 289 0.12% 0.08% 0.02%
130 Asia YE Yemen 30 635 257 0.01% 0.02% 0.02%
131 Africa MW Malawi 19 738 546 0.14% 0.03% 0.01%
132 Africa BF Burkina Faso 21 608 760 0.00% 0.01% 0.01%
133 Africa ER Eritrea 3 606 977 0.07% 0.01% 0.01%
134 Africa CF Central African R. 4 933 306 0.09% 0.01% 0.01%
135 Africa SN Senegal 17 287 116 0.19% 0.03% 0.01%
136 Africa ML Mali 20 968 573 0.00% 0.01% 0.01%
137 Asia HK Hong Kong 7 572 086 0.00% 0.01% 0.01%
138 Africa CD DR Congo 92 910 949 0.03% 0.01% 0.01%
139 Asia TW Taiwan 23 870 048 0.03% 0.00% 0.00%
140 Africa NE Niger 25 283 464 0.00% 0.00% 0.00%
141 Africa SD Sudan 45 110 295 0.01% 0.00% 0.00%
142 Africa LS Lesotho 2 163 220 0.17% 0.00% 0.00%
143 Africa LR Liberia 5 204 096 0.07% 0.02% 0.00%
144 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
145 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
146 Asia TJ Tajikistan 9 801 546 0.00% 0.00% 0.00%
147 Africa TD Chad 17 005 864 0.00% 0.00% 0.00%
148 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
149 Africa CM Cameroon 27 359 538 0.03% 0.03% 0.00%
150 Africa SL Sierra Leone 8 176 896 0.03% 0.00% 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 South America PY Paraguay 7 240 657 5.48% (21.56)% (0.09)%
2 Asia YE Yemen 30 635 257 18.57% (20.36)% (0.02)%
3 Africa LR Liberia 5 204 096 5.40% (13.87)% (0.02)%
4 Africa SD Sudan 45 110 295 7.14% (10.53)% (0.00)%
5 Africa ER Eritrea 3 606 977 1.02% (9.43)% (0.01)%
6 Africa MG Madagascar 28 567 477 6.01% (8.11)% (0.01)%
7 Africa NA Namibia 2 597 635 3.62% 7.21% 0.44%
8 Africa SO Somalia 16 438 930 8.06% (7.01)% (0.07)%
9 Africa SN Senegal 17 287 116 2.20% (6.25)% (0.03)%
10 Africa MW Malawi 19 738 546 4.14% (6.05)% (0.03)%
11 South America EC Ecuador 17 973 507 13.69% 5.86% 0.17%
12 Africa DZ Algeria 44 827 265 3.09% (5.75)% (0.08)%
13 Asia SY Syria 18 024 209 6.87% 5.52% 0.12%
14 North America MX Mexico 130 604 875 4.42% 4.77% 1.01%
15 Asia AF Afghanistan 40 008 355 4.83% (4.69)% (0.02)%
16 Africa AO Angola 34 123 790 3.67% (4.61)% (0.10)%
17 Africa GM Gambia 2 500 222 3.99% (4.58)% (0.07)%
18 Asia ID Indonesia 277 093 832 3.77% 4.53% 0.21%
19 Africa EG Egypt 104 713 637 4.94% (4.40)% (0.05)%
20 Europe BG Bulgaria 6 883 742 4.32% 4.27% 2.48%
21 South America PE Peru 33 538 503 6.46% 4.26% 0.31%
22 South America CL Chile 19 318 811 2.59% 4.21% 0.31%
23 North America SV El Salvador 6 526 635 3.44% 4.20% 0.49%
24 Europe RU Russia 146 011 806 3.64% 4.20% 1.59%
25 Africa ZW Zimbabwe 15 129 826 3.37% 4.07% 0.14%
26 Asia TW Taiwan 23 870 048 6.20% (3.90)% (0.00)%
27 Europe MK North Macedonia 2 083 268 3.75% 3.85% 3.11%
28 Europe BA Bosnia and Herzegovina 3 255 579 5.28% 3.70% 2.45%
29 Australia/Oceania PG Papua New Guinea 9 155 938 1.79% (3.65)% (0.07)%
30 North America HT Haiti 11 574 066 3.84% (3.60)% (0.02)%
31 Asia LK Sri Lanka 21 524 173 3.28% 3.51% 1.80%
32 Asia SA Saudi Arabia 35 482 580 1.28% (3.35)% (0.04)%
33 Asia MM Myanmar 54 860 292 4.72% 3.29% 0.52%
34 Africa CI Ivory Coast 27 182 627 2.48% (3.17)% (0.08)%
35 Africa GN Guinea 13 571 262 3.01% (3.10)% (0.03)%
36 South America AR Argentina 45 707 808 2.17% 3.07% 0.77%
37 Europe RO Romania 19 078 957 7.92% 2.97% 2.05%
38 Africa GW Guinea-Bissau 2 025 289 2.88% (2.81)% (0.08)%
39 South America BO Bolivia 11 869 474 2.86% 2.78% 0.33%
40 Africa ML Mali 20 968 573 3.60% (2.74)% (0.01)%
41 North America HN Honduras 10 098 890 2.69% 2.73% 1.20%
42 Africa ZA South Africa 60 231 421 2.46% 2.72% 1.00%
43 Asia AM Armenia 2 970 088 2.60% 2.71% 2.43%
44 Africa CG Congo 5 685 342 1.71% (2.64)% (0.04)%
45 Europe UA Ukraine 43 408 795 3.12% 2.64% 1.04%
46 South America CO Colombia 51 552 334 2.23% 2.63% 0.39%
47 Africa BF Burkina Faso 21 608 760 2.19% (2.52)% (0.01)%
48 Africa TN Tunisia 11 971 272 3.32% 2.50% 1.57%
49 Asia KH Cambodia 17 004 429 2.57% 2.38% 0.42%
50 Asia VN Vietnam 98 419 911 2.72% 2.35% 1.41%
51 Africa NG Nigeria 212 431 024 1.69% (2.28)% (0.03)%
52 Africa KE Kenya 55 230 515 2.50% 2.24% 0.11%
53 South America BR Brazil 214 425 443 2.56% 2.22% 1.23%
54 Asia KG Kyrgyzstan 6 656 934 1.06% 2.17% 0.19%
55 Asia PK Pakistan 226 178 982 2.11% 2.00% 0.17%
56 Africa ET Ethiopia 118 470 194 1.96% 2.00% 0.13%
57 Asia KZ Kazakhstan 19 053 882 1.64% 1.97% 2.43%
58 Europe PL Poland 37 795 368 5.61% 1.97% 0.17%
59 Asia GE Georgia 3 979 700 1.58% 1.96% 6.70%
60 North America JM Jamaica 2 977 135 2.80% 1.91% 2.33%
61 Asia OM Oman 5 266 535 1.90% 1.89% 0.14%
62 South America PR Puerto Rico 3 193 694 1.53% 1.81% 1.66%
63 Asia BD Bangladesh 166 714 875 1.97% 1.75% 0.16%
64 Asia IR Iran 85 319 524 1.52% 1.74% 3.11%
65 Europe MD Moldova 4 022 371 2.20% 1.73% 2.23%
66 Africa MR Mauritania 4 800 115 1.87% 1.69% 0.24%
67 Europe LT Lithuania 2 675 276 1.46% 1.69% 4.38%
68 Asia MY Malaysia 32 877 696 1.43% 1.69% 6.51%
69 Africa MA Morocco 37 450 484 1.25% 1.60% 0.92%
70 Africa NE Niger 25 283 464 1.53% 1.58% 0.00%
71 North America GT Guatemala 18 324 114 1.84% 1.54% 1.89%
72 Europe HU Hungary 9 630 022 2.86% 1.53% 0.40%
73 Europe GR Greece 10 360 091 1.09% 1.46% 2.63%
74 Africa RW Rwanda 13 347 581 1.31% 1.44% 0.33%
75 Africa SS South Sudan 11 355 690 1.14% 1.40% 0.02%
76 South America VE Venezuela 28 336 320 1.35% 1.40% 0.46%
77 Africa ZM Zambia 19 017 585 2.05% 1.31% 0.07%
78 North America PA Panama 4 398 539 0.92% 1.29% 1.00%
79 Africa GH Ghana 31 872 195 1.15% 1.28% 0.13%
80 Asia JO Jordan 10 328 177 1.47% 1.26% 1.00%
81 Europe HR Croatia 4 073 955 1.55% 1.23% 2.68%
82 Asia TH Thailand 70 016 410 1.13% 1.20% 2.37%
83 Africa LY Libya 6 986 573 1.00% 1.16% 1.90%
84 North America CR Costa Rica 5 151 550 1.08% 1.15% 5.50%
85 North America US USA 333 400 157 1.03% 1.13% 5.10%
86 Asia AZ Azerbaijan 10 252 011 1.11% 1.12% 2.77%
87 Africa CF Central African R. 4 933 306 0.05% 1.12% 0.01%
88 Asia TR Turkey 85 459 264 0.95% 1.11% 3.41%
89 Asia NP Nepal 29 782 900 1.41% 1.04% 0.46%
90 Europe IT Italy 60 351 915 1.05% 1.03% 0.95%
91 Africa CD DR Congo 92 910 949 1.18% 1.00% 0.01%
92 Asia IQ Iraq 41 334 404 0.71% 0.97% 1.27%
93 Asia KW Kuwait 4 348 478 0.60% 0.95% 0.21%
94 North America CU Cuba 11 318 070 0.94% 0.94% 8.02%
95 Africa MZ Mozambique 32 333 112 1.35% 0.92% 0.07%
96 Africa TG Togo 8 517 708 0.90% 0.90% 0.21%
97 Asia LB Lebanon 6 787 647 0.71% 0.89% 1.43%
98 Europe ES Spain 46 777 162 0.41% 0.89% 0.88%
99 Asia HK Hong Kong 7 572 086 0.90% 0.89% 0.01%
100 Asia IN India 1 396 753 763 1.74% 0.88% 0.29%
101 Asia PH Philippines 111 380 633 1.40% 0.82% 2.06%
102 Asia UZ Uzbekistan 34 067 574 0.76% 0.78% 0.22%
103 Africa UG Uganda 47 517 666 3.53% 0.72% 0.26%
104 North America CA Canada 38 150 737 1.01% 0.72% 1.23%
105 Europe BY Belarus 9 445 481 0.96% 0.72% 2.28%
106 South America UY Uruguay 3 488 605 1.50% 0.68% 0.45%
107 Africa GA Gabon 2 290 418 0.79% 0.64% 0.59%
108 Europe RS Serbia 8 693 850 0.77% 0.64% 7.25%
109 Europe AL Albania 2 873 912 0.62% 0.62% 3.44%
110 Africa CM Cameroon 27 359 538 1.13% 0.61% 0.03%
111 Africa BW Botswana 2 410 144 1.29% 0.57% 3.76%
112 Australia/Oceania AU Australia 25 865 035 0.58% 0.56% 0.75%
113 Europe SK Slovakia 5 462 911 1.82% 0.54% 1.02%
114 Europe PT Portugal 10 159 948 0.43% 0.53% 1.42%
115 Europe FR France 65 451 999 0.46% 0.52% 1.58%
116 Europe DE Germany 84 114 966 1.01% 0.45% 1.32%
117 Europe CZ Czechia 10 733 533 0.61% 0.43% 0.40%
118 North America DO Dominican R. 10 982 200 0.57% 0.41% 0.29%
119 Europe GB United Kingdom 68 326 526 0.28% 0.39% 5.84%
120 Asia JP Japan 125 997 725 0.47% 0.38% 0.90%
121 Europe SI Slovenia 2 079 291 0.49% 0.37% 4.58%
122 Europe SE Sweden 10 177 046 0.31% 0.37% 1.07%
123 Europe AT Austria 9 069 874 0.39% 0.36% 2.35%
124 Europe DK Denmark 5 817 404 0.15% 0.35% 1.00%
125 Asia KR South Korea 51 323 719 0.33% 0.34% 0.44%
126 Europe BE Belgium 11 651 937 0.36% 0.32% 1.88%
127 Asia IL Israel 9 326 000 0.32% 0.27% 9.47%
128 Europe IE Ireland 5 005 864 0.22% 0.25% 3.41%
129 Africa BJ Benin 12 514 118 0.39% 0.24% 0.33%
130 Europe NL Netherlands 17 181 724 0.15% 0.23% 1.51%
131 Europe CH Switzerland 8 732 785 0.23% 0.23% 2.80%
132 North America NI Nicaragua 6 721 822 0.38% 0.23% 0.11%
133 Asia SG Singapore 5 907 159 0.29% 0.23% 1.41%
134 Asia AE Arab Emirates 10 037 872 0.24% 0.23% 0.82%
135 Asia MN Mongolia 3 343 398 0.38% 0.22% 10.51%
136 Europe FI Finland 5 551 357 0.21% 0.12% 0.93%
137 Europe NO Norway 5 473 588 0.11% 0.11% 2.15%
138 Australia/Oceania NZ New Zealand 5 002 100 0.07% 0.09% 0.07%
139 Africa BI Burundi 12 326 485 0.07% 0.07% 0.18%
140 Asia QA Qatar 2 807 805 0.25% 0.06% 0.61%
141 Asia LA Laos 7 405 797 0.07% 0.05% 0.42%
142 Africa SL Sierra Leone 8 176 896 1.85% 0.00% 0.00%
143 Africa TD Chad 17 005 864 0.92% 0.00% 0.00%
144 Africa LS Lesotho 2 163 220 2.15% 0.00% 0.00%
145 Africa TZ Tanzania 61 827 978 80.77% 0.00% 0.16%
146 Asia PS Palestine 5 247 484 0.00% 0.00% 0.08%
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 9 801 546 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 33 538 503 199 246 5.941
2 Europe BA Bosnia and Herzegovina 3 255 579 10 443 3.208
3 Europe MK North Macedonia 2 083 268 6 594 3.165
4 Europe HU Hungary 9 630 022 30 171 3.133
5 Europe BG Bulgaria 6 883 742 20 489 2.976
6 Europe CZ Czechia 10 733 533 30 453 2.837
7 South America BR Brazil 214 425 443 593 901 2.770
8 South America AR Argentina 45 707 808 114 862 2.513
9 South America CO Colombia 51 552 334 126 111 2.446
10 Europe SI Slovenia 2 079 291 4 857 2.336
11 Europe SK Slovakia 5 462 911 12 596 2.306
12 South America PY Paraguay 7 240 657 16 143 2.229
13 Asia GE Georgia 3 979 700 8 844 2.222
14 Europe BE Belgium 11 651 937 25 554 2.193
15 Europe IT Italy 60 351 915 130 697 2.166
16 Europe HR Croatia 4 073 955 8 606 2.112
17 North America MX Mexico 130 604 875 274 850 2.104
18 Africa TN Tunisia 11 971 272 24 743 2.067
19 North America US USA 333 400 157 681 761 2.045
20 Europe PL Poland 37 795 368 75 572 2.000
21 Europe GB United Kingdom 68 326 526 136 163 1.993
22 South America CL Chile 19 318 811 37 440 1.938
23 Europe RO Romania 19 078 957 36 339 1.905
24 Europe ES Spain 46 777 162 86 185 1.843
25 Europe LT Lithuania 2 675 276 4 927 1.842
26 South America EC Ecuador 17 973 507 32 720 1.821
27 Asia AM Armenia 2 970 088 5 264 1.772
28 Europe PT Portugal 10 159 948 17 954 1.767
29 Europe FR France 65 451 999 114 245 1.746
30 South America UY Uruguay 3 488 605 6 051 1.734
31 Europe MD Moldova 4 022 371 6 695 1.664
32 North America PA Panama 4 398 539 7 204 1.638
33 South America BO Bolivia 11 869 474 18 698 1.575
34 Europe SE Sweden 10 177 046 14 821 1.456
35 Africa ZA South Africa 60 231 421 87 052 1.445
36 Europe GR Greece 10 360 091 14 679 1.417
37 Europe RU Russia 146 011 806 204 679 1.402
38 Asia IR Iran 85 319 524 119 360 1.399
39 Africa NA Namibia 2 597 635 3 494 1.345
40 Europe UA Ukraine 43 408 795 55 720 1.284
41 Asia LB Lebanon 6 787 647 8 286 1.221
42 Europe CH Switzerland 8 732 785 10 607 1.215
43 North America CR Costa Rica 5 151 550 6 189 1.201
44 Europe AT Austria 9 069 874 10 737 1.184
45 Europe DE Germany 84 114 966 93 406 1.111
46 Europe NL Netherlands 17 181 724 18 150 1.056
47 Europe IE Ireland 5 005 864 5 209 1.041
48 Asia JO Jordan 10 328 177 10 680 1.034
49 Africa BW Botswana 2 410 144 2 360 0.979
50 South America PR Puerto Rico 3 193 694 3 127 0.979
51 North America HN Honduras 10 098 890 9 679 0.958
52 Europe RS Serbia 8 693 850 8 051 0.926
53 Europe AL Albania 2 873 912 2 640 0.919
54 Asia IL Israel 9 326 000 7 684 0.824
55 Asia KZ Kazakhstan 19 053 882 15 503 0.814
56 Asia OM Oman 5 266 535 4 094 0.777
57 Asia MY Malaysia 32 877 696 25 437 0.774
58 Asia TR Turkey 85 459 264 63 166 0.739
59 North America GT Guatemala 18 324 114 13 327 0.727
60 North America CA Canada 38 150 737 27 629 0.724
61 Africa LY Libya 6 986 573 4 599 0.658
62 North America CU Cuba 11 318 070 7 227 0.638
63 Asia AZ Azerbaijan 10 252 011 6 457 0.630
64 North America JM Jamaica 2 977 135 1 831 0.615
65 Asia LK Sri Lanka 21 524 173 12 680 0.589
66 Asia KW Kuwait 4 348 478 2 446 0.563
67 Asia IQ Iraq 41 334 404 22 110 0.535
68 Asia ID Indonesia 277 093 832 141 585 0.511
69 North America SV El Salvador 6 526 635 3 186 0.488
70 Europe DK Denmark 5 817 404 2 642 0.454
71 Europe BY Belarus 9 445 481 4 091 0.433
72 Asia KG Kyrgyzstan 6 656 934 2 602 0.391
73 Africa MA Morocco 37 450 484 14 167 0.378
74 Asia NP Nepal 29 782 900 11 103 0.373
75 North America DO Dominican R. 10 982 200 4 039 0.368
76 Asia PH Philippines 111 380 633 37 405 0.336
77 Asia MN Mongolia 3 343 398 1 117 0.334
78 Asia IN India 1 396 753 763 446 918 0.320
79 Asia MM Myanmar 54 860 292 17 527 0.320
80 Africa ZW Zimbabwe 15 129 826 4 604 0.304
81 Asia SA Saudi Arabia 35 482 580 8 699 0.245
82 Asia TH Thailand 70 016 410 16 369 0.234
83 Asia QA Qatar 2 807 805 605 0.215
84 Asia AE Arab Emirates 10 037 872 2 093 0.208
85 Africa ZM Zambia 19 017 585 3 646 0.192
86 Europe FI Finland 5 551 357 1 062 0.191
87 Asia VN Vietnam 98 419 911 18 584 0.189
88 Africa LS Lesotho 2 163 220 403 0.186
89 Asia AF Afghanistan 40 008 355 7 199 0.180
90 Asia BD Bangladesh 166 714 875 27 414 0.164
91 Africa EG Egypt 104 713 637 17 187 0.164
92 Africa MR Mauritania 4 800 115 768 0.160
93 Europe NO Norway 5 473 588 850 0.155
94 South America VE Venezuela 28 336 320 4 396 0.155
95 Asia JP Japan 125 997 725 17 482 0.139
96 Africa GM Gambia 2 500 222 335 0.134
97 Asia KH Cambodia 17 004 429 2 236 0.132
98 Africa DZ Algeria 44 827 265 5 777 0.129
99 Asia SY Syria 18 024 209 2 207 0.122
100 Asia PK Pakistan 226 178 982 27 555 0.122
101 Africa MW Malawi 19 738 546 2 276 0.115
102 Africa SN Senegal 17 287 116 1 855 0.107
103 Africa RW Rwanda 13 347 581 1 253 0.094
104 Africa KE Kenya 55 230 515 5 102 0.092
105 Africa GA Gabon 2 290 418 178 0.078
106 Africa SO Somalia 16 438 930 1 103 0.067
107 Africa GW Guinea-Bissau 2 025 289 135 0.067
108 Africa UG Uganda 47 517 666 3 147 0.066
109 Africa SD Sudan 45 110 295 2 835 0.063
110 Africa MZ Mozambique 32 333 112 1 908 0.059
111 Asia YE Yemen 30 635 257 1 694 0.055
112 Africa LR Liberia 5 204 096 283 0.054
113 North America HT Haiti 11 574 066 610 0.053
114 Africa CM Cameroon 27 359 538 1 368 0.050
115 Asia KR South Korea 51 323 719 2 456 0.048
116 Australia/Oceania AU Australia 25 865 035 1 233 0.048
117 Africa ET Ethiopia 118 470 194 5 401 0.046
118 Africa AO Angola 34 123 790 1 501 0.044
119 Africa GH Ghana 31 872 195 1 146 0.036
120 Asia UZ Uzbekistan 34 067 574 1 225 0.036
121 Asia TW Taiwan 23 870 048 842 0.035
122 Africa CG Congo 5 685 342 191 0.034
123 Africa MG Madagascar 28 567 477 958 0.034
124 North America NI Nicaragua 6 721 822 203 0.030
125 Asia HK Hong Kong 7 572 086 213 0.028
126 Africa GN Guinea 13 571 262 376 0.028
127 Africa TG Togo 8 517 708 226 0.026
128 Africa ML Mali 20 968 573 547 0.026
129 Australia/Oceania PG Papua New Guinea 9 155 938 229 0.025
130 Africa CI Ivory Coast 27 182 627 600 0.022
131 Africa CF Central African R. 4 933 306 100 0.020
132 Africa SL Sierra Leone 8 176 896 121 0.015
133 Asia SG Singapore 5 907 159 78 0.013
134 Africa NG Nigeria 212 431 024 2 678 0.013
135 Africa BJ Benin 12 514 118 154 0.012
136 Africa CD DR Congo 92 910 949 1 084 0.012
137 Africa ER Eritrea 3 606 977 42 0.012
138 Africa TZ Tanzania 61 827 978 714 0.011
139 Africa SS South Sudan 11 355 690 128 0.011
140 Africa TD Chad 17 005 864 174 0.010
141 Africa BF Burkina Faso 21 608 760 180 0.008
142 Africa NE Niger 25 283 464 201 0.008
143 Australia/Oceania NZ New Zealand 5 002 100 27 0.005
144 Asia LA Laos 7 405 797 16 0.002
145 Asia PS Palestine 5 247 484 7 0.001
146 Africa BI Burundi 12 326 485 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 9 801 546 0 0.000
150 Europe TM Turkmenistan 6 118 000 0 0.000

Elhalálozási adatok hozzávetőleges értékei 2018: Abortusz: 56 millió, Rákbetegség: 9,6 millió.

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

* ÚV lámpa (neon) használata a helységekben.
* 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"