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": 2022-09-27 21:02
(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 +10 654 (+5 994) +10 (+1)
CZ Czechia +4 735 (+281) +0 (+11)
DE Germany +0 (+89 282) +0 (+118)
HU Hungary +0 (+0) +0 (+0)
PL Poland +6 484 (+729) +25 (+0)
SK Slovakia, [gov], [okr]+442 (+78) +3 (+2)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Europe 756 641 771 3.53% 1.48% 0.59%
2 North America 598 699 588 2.25% 0.88% 0.18%
3 Asia 4 709 849 202 0.64% 0.46% 0.17%
4 Australia/Oceania 43 935 166 8.14% 1.60% 0.17%
5 South America 441 939 772 1.50% 0.41% 0.12%
6 Africa 1 411 600 485 0.04% 0.01% 0.01%

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 441 939 772 0.43% 0.88% 0.41%
2 North America 598 699 588 0.37% 0.61% 0.88%
3 Australia/Oceania 43 935 166 0.21% 0.59% 1.60%
4 Africa 1 411 600 485 0.49% (0.58)% (0.01)%
5 Europe 756 641 771 0.25% 0.40% 1.48%
6 Asia 4 709 849 202 0.14% 0.22% 0.46%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 441 939 772 1 332 413 3.015
2 Europe 756 641 771 1 911 725 2.527
3 North America 598 699 588 1 492 614 2.493
4 Australia/Oceania 43 935 166 20 620 0.469
5 Asia 4 709 849 202 1 469 688 0.312
6 Africa 1 411 600 485 257 667 0.182

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 TW Taiwan 23 912 908 18.28% 18.45% 20.15%
2 Asia HK Hong Kong 7 632 666 7.09% 12.54% 7.60%
3 Asia GE Georgia 3 972 095 2.67% 5.18% 5.52%
4 South America PR Puerto Rico 3 193 694 10.55% 6.70% 5.06%
5 Europe SI Slovenia 2 079 575 5.89% 4.82% 3.18%
6 North America CR Costa Rica 5 197 894 4.61% 2.82% 2.69%
7 Europe AT Austria 9 121 024 8.07% 3.36% 2.00%
8 Europe HU Hungary 9 605 664 1.55% 2.23% 1.84%
9 Europe DE Germany 84 381 438 7.45% 2.51% 1.81%
10 Europe LT Lithuania 2 637 684 2.90% 2.35% 1.41%
11 Asia KR South Korea 51 367 577 11.78% 8.99% 1.31%
12 Europe IT Italy 60 263 602 7.82% 2.06% 1.28%
13 Europe BE Belgium 11 702 123 3.22% 1.52% 1.22%
14 Asia IL Israel 9 326 000 5.59% 1.21% 1.10%
15 North America PA Panama 4 466 324 3.98% 1.56% 0.93%
16 Asia AM Armenia 2 975 594 0.60% 1.14% 0.82%
17 North America CA Canada 38 480 391 0.97% 0.91% 0.82%
18 South America UY Uruguay 3 500 580 2.14% 0.87% 0.81%
19 Europe CZ Czechia 10 753 287 1.37% 1.18% 0.75%
20 Asia JP Japan 125 613 305 9.12% 6.66% 0.69%
21 Asia JO Jordan 10 429 112 0.44% 0.82% 0.56%
22 Europe CH Switzerland 8 795 811 4.39% 0.92% 0.55%
23 Europe RS Serbia 8 658 917 3.52% 2.40% 0.54%
24 Australia/Oceania NZ New Zealand 5 002 100 11.95% 2.27% 0.48%
25 Asia SG Singapore 5 952 983 9.53% 2.13% 0.46%
26 Asia TR Turkey 86 363 808 2.08% 1.50% 0.45%
27 Europe RU Russia 146 073 999 1.28% 2.16% 0.43%
28 Europe SE Sweden 10 239 736 0.66% 0.74% 0.40%
29 Asia QA Qatar 2 807 805 2.46% 1.49% 0.40%
30 Europe DK Denmark 5 837 695 2.52% 0.93% 0.32%
31 Europe PL Poland 37 754 189 0.58% 0.64% 0.29%
32 South America AR Argentina 46 120 998 1.22% 0.56% 0.29%
33 Europe BG Bulgaria 6 831 877 1.25% 0.61% 0.28%
34 Europe NL Netherlands 17 219 424 1.84% 0.40% 0.26%
35 Europe IE Ireland 5 060 845 2.14% 0.54% 0.26%
36 Europe GB United Kingdom 68 681 433 1.97% 0.64% 0.24%
37 Europe HR Croatia 4 048 842 2.09% 0.95% 0.22%
38 Europe FI Finland 5 559 915 3.46% 1.86% 0.22%
39 Europe FR France 65 595 624 7.59% 0.78% 0.20%
40 North America DO Dominican R. 11 090 604 0.55% 0.25% 0.17%
41 South America CL Chile 19 482 269 4.49% 1.66% 0.17%
42 Europe RO Romania 18 951 674 1.77% 0.73% 0.17%
43 Europe SK Slovakia 5 465 539 0.89% 0.32% 0.14%
44 Europe PT Portugal 10 130 428 7.75% 1.45% 0.14%
45 Asia KZ Kazakhstan 19 277 809 0.45% 0.31% 0.13%
46 Africa BW Botswana 2 457 583 0.80% 0.06% 0.13%
47 Australia/Oceania AU Australia 26 159 993 11.09% 2.10% 0.11%
48 North America MX Mexico 131 954 950 0.97% 0.23% 0.10%
49 Asia MN Mongolia 3 396 089 1.66% 0.49% 0.09%
50 North America US USA 335 049 756 3.22% 1.25% 0.09%
51 Europe ES Spain 46 795 160 2.04% 0.32% 0.08%
52 South America EC Ecuador 18 240 838 0.69% 0.33% 0.07%
53 Europe MK North Macedonia 2 083 183 1.44% 0.42% 0.07%
54 Asia MY Malaysia 33 291 238 0.91% 0.41% 0.06%
55 Asia AE Arab Emirates 10 157 018 1.12% 0.29% 0.06%
56 South America PY Paraguay 7 328 016 0.90% 0.16% 0.05%
57 South America BR Brazil 215 929 973 1.66% 0.30% 0.05%
58 South America CO Colombia 52 092 877 0.40% 0.14% 0.05%
59 Europe BA Bosnia and Herzegovina 3 235 336 0.60% 0.26% 0.05%
60 Asia LB Lebanon 6 757 312 1.68% 0.30% 0.04%
61 North America HN Honduras 10 256 108 0.30% 0.30% 0.04%
62 Africa ZM Zambia 19 533 022 0.06% 0.02% 0.04%
63 Europe NO Norway 5 515 806 0.51% 0.10% 0.03%
64 North America JM Jamaica 2 989 995 0.48% 0.19% 0.03%
65 Asia VN Vietnam 99 292 436 0.73% 0.17% 0.03%
66 Asia AZ Azerbaijan 10 343 058 0.24% 0.25% 0.02%
67 Asia PH Philippines 112 835 294 0.19% 0.13% 0.02%
68 Asia KG Kyrgyzstan 6 764 377 0.07% 0.03% 0.02%
69 Africa SO Somalia 16 882 823 0.00% 0.00% 0.02%
70 North America NI Nicaragua 6 800 402 0.01% 0.01% 0.02%
71 Africa GH Ghana 32 520 343 0.02% 0.00% 0.02%
72 Asia ID Indonesia 279 976 514 0.12% 0.08% 0.01%
73 Africa GA Gabon 2 342 935 0.05% 0.01% 0.01%
74 Asia LA Laos 7 511 127 0.07% 0.07% 0.01%
75 South America PE Peru 33 996 669 1.61% 0.37% 0.01%
76 Asia TH Thailand 70 190 589 0.32% 0.13% 0.01%
77 Asia MM Myanmar 55 223 453 0.01% 0.02% 0.01%
78 South America BO Bolivia 12 028 297 1.64% 0.24% 0.01%
79 Asia BD Bangladesh 168 349 895 0.04% 0.01% 0.01%
80 Europe AL Albania 2 870 791 1.88% 0.39% 0.01%
81 Asia AF Afghanistan 40 884 801 0.04% 0.04% 0.01%
82 Asia IR Iran 86 391 625 0.36% 0.10% 0.01%
83 North America HT Haiti 11 712 663 0.03% 0.03% 0.01%
84 Africa CI Ivory Coast 27 836 009 0.02% 0.01% 0.01%
85 Asia SA Saudi Arabia 36 023 641 0.13% 0.02% 0.01%
86 Africa BI Burundi 12 681 192 0.06% 0.01% 0.01%
87 Africa ZA South Africa 60 977 086 0.10% 0.02% 0.01%
88 Africa TG Togo 8 711 726 0.02% 0.01% 0.01%
89 North America GT Guatemala 18 655 084 1.35% 0.31% 0.01%
90 Africa GM Gambia 2 568 194 0.02% 0.02% 0.01%
91 Australia/Oceania PG Papua New Guinea 9 325 214 0.01% 0.00% 0.00%
92 Africa NG Nigeria 217 541 658 0.00% 0.00% 0.00%
93 Asia IN India 1 410 273 474 0.10% 0.03% 0.00%
94 Africa CF Central African R. 5 017 145 0.01% 0.00% 0.00%
95 Asia LK Sri Lanka 21 613 502 0.03% 0.01% 0.00%
96 Asia UZ Uzbekistan 34 551 503 0.01% 0.00% 0.00%
97 Africa UG Uganda 48 965 219 0.01% 0.00% 0.00%
98 Africa KE Kenya 56 414 444 0.03% 0.00% 0.00%
99 Asia NP Nepal 30 306 197 0.07% 0.03% 0.00%
100 Africa NE Niger 26 162 650 0.00% 0.00% 0.00%
101 Africa MZ Mozambique 33 209 769 0.01% 0.00% 0.00%
102 Africa SN Senegal 17 728 659 0.01% 0.00% 0.00%
103 Africa MR Mauritania 4 922 415 0.07% 0.00% 0.00%
104 Asia YE Yemen 31 291 872 0.00% 0.00% 0.00%
105 Africa BF Burkina Faso 22 182 502 0.00% 0.00% 0.00%
106 Africa LS Lesotho 2 180 133 0.05% 0.01% 0.00%
107 Africa LR Liberia 5 322 964 0.01% 0.02% 0.00%
108 South America VE Venezuela 28 256 320 0.07% 0.03% 0.00%
109 Africa ET Ethiopia 121 318 649 0.02% 0.00% 0.00%
110 Asia PK Pakistan 230 463 460 0.02% 0.01% 0.00%
111 Asia KW Kuwait 4 411 493 0.57% 0.12% 0.00%
112 Africa ER Eritrea 3 655 937 0.01% 0.00% 0.00%
113 Europe UA Ukraine 43 148 150 0.15% 0.39% 0.00%
114 Africa EG Egypt 106 641 391 0.00% 0.00% 0.00%
115 Africa AO Angola 35 148 150 0.01% 0.00% 0.00%
116 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
117 Africa TZ Tanzania 63 531 541 0.01% 0.00% 0.00%
118 Asia KH Cambodia 17 235 233 0.01% 0.00% 0.00%
119 Asia OM Oman 5 396 468 0.16% 0.06% 0.00%
120 Africa TN Tunisia 12 094 522 0.86% 0.18% 0.00%
121 Africa DZ Algeria 45 617 970 0.01% 0.00% 0.00%
122 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
123 Asia TJ Tajikistan 10 015 701 0.00% 0.00% 0.00%
124 Africa TD Chad 17 477 819 0.00% 0.00% 0.00%
125 North America CU Cuba 11 311 201 0.05% 0.02% 0.00%
126 Asia SY Syria 18 449 407 0.01% 0.00% 0.00%
127 Asia IQ Iraq 42 236 708 0.31% 0.07% 0.00%
128 North America SV El Salvador 6 559 204 0.61% 0.67% 0.00%
129 Africa NA Namibia 2 643 585 0.24% 0.01% 0.00%
130 Africa SS South Sudan 11 486 528 0.00% 0.00% 0.00%
131 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
132 Africa CM Cameroon 28 020 530 0.01% 0.00% 0.00%
133 Africa SL Sierra Leone 8 338 976 0.00% 0.00% 0.00%
134 Africa CG Congo 5 821 197 0.01% 0.00% 0.00%
135 Africa MW Malawi 20 233 145 0.01% 0.00% 0.00%
136 Africa CD DR Congo 95 638 591 0.00% 0.00% 0.00%
137 Europe BY Belarus 9 442 392 0.12% 0.00% 0.00%
138 Africa GW Guinea-Bissau 2 071 802 0.03% 0.06% 0.00%
139 Africa SD Sudan 46 134 014 0.00% 0.00% 0.00%
140 Africa ML Mali 21 552 636 0.01% 0.02% 0.00%
141 Asia PS Palestine 5 366 059 0.00% 0.00% 0.00%
142 Europe GR Greece 10 309 569 12.31% 8.69% 0.00%
143 Africa RW Rwanda 13 668 741 0.02% 0.00% 0.00%
144 Africa MG Madagascar 29 279 726 0.01% 0.00% 0.00%
145 Africa ZW Zimbabwe 15 345 688 0.03% 0.00% 0.00%
146 Africa GN Guinea 13 927 802 0.01% 0.01% 0.00%
147 Africa BJ Benin 12 831 863 0.01% 0.01% 0.00%
148 Europe MD Moldova 4 013 061 1.51% 2.72% 0.00%
149 Africa MA Morocco 37 886 664 0.26% 0.00% 0.00%
150 Africa LY Libya 7 079 771 0.07% 0.01% 0.00%

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

Filtered where Population more then 2 million, [All Countries] | Compare with [DEATHS]! and with [FATALITY RATE]
N.RegionCDCountryPopulationMortality last
120 days
Mortality last
30 days
New positive cases
last 30 days
1 Africa CD DR Congo 95 638 591 1.64% (12.78)% (0.00)%
2 Asia YE Yemen 31 291 872 5.36% (8.33)% (0.00)%
3 South America PY Paraguay 7 328 016 0.99% 3.70% 0.16%
4 Africa EG Egypt 106 641 391 7.12% (3.38)% (0.00)%
5 Asia LK Sri Lanka 21 613 502 3.21% (3.13)% (0.01)%
6 Africa NA Namibia 2 643 585 0.64% (2.91)% (0.01)%
7 Europe NO Norway 5 515 806 2.83% (2.59)% (0.10)%
8 Africa MR Mauritania 4 922 415 0.29% (2.13)% (0.00)%
9 Europe BA Bosnia and Herzegovina 3 235 336 1.60% 1.89% 0.26%
10 North America HT Haiti 11 712 663 0.75% 1.78% 0.03%
11 South America CO Colombia 52 092 877 0.90% 1.77% 0.14%
12 North America JM Jamaica 2 989 995 1.43% 1.74% 0.19%
13 Asia IR Iran 86 391 625 0.94% 1.64% 0.10%
14 Asia PH Philippines 112 835 294 0.87% 1.52% 0.13%
15 Asia SA Saudi Arabia 36 023 641 0.34% 1.50% 0.02%
16 Europe ES Spain 46 795 160 0.62% 1.31% 0.32%
17 Europe SE Sweden 10 239 736 1.55% 1.26% 0.74%
18 Europe GB United Kingdom 68 681 433 0.79% 1.24% 0.64%
19 Africa BW Botswana 2 457 583 0.46% 1.23% 0.06%
20 Europe HR Croatia 4 048 842 0.96% 1.14% 0.95%
21 Africa ZW Zimbabwe 15 345 688 1.55% 1.14% 0.00%
22 North America CA Canada 38 480 391 1.02% 1.13% 0.91%
23 Africa GN Guinea 13 927 802 0.71% 1.10% 0.01%
24 Europe SK Slovakia 5 465 539 0.66% 1.09% 0.32%
25 Europe IE Ireland 5 060 845 0.37% 1.05% 0.54%
26 Asia TH Thailand 70 190 589 1.02% 1.01% 0.13%
27 Africa ZA South Africa 60 977 086 1.16% 0.96% 0.02%
28 South America PE Peru 33 996 669 0.54% 0.91% 0.37%
29 Africa MW Malawi 20 233 145 1.92% 0.89% 0.00%
30 North America GT Guatemala 18 655 084 0.61% 0.85% 0.31%
31 Africa TN Tunisia 12 094 522 0.64% 0.84% 0.18%
32 Europe MK North Macedonia 2 083 183 0.66% 0.74% 0.42%
33 Africa TG Togo 8 711 726 0.69% 0.70% 0.01%
34 Africa MA Morocco 37 886 664 0.20% 0.69% 0.00%
35 Africa MZ Mozambique 33 209 769 0.45% 0.69% 0.00%
36 Europe HU Hungary 9 605 664 0.70% 0.66% 2.23%
37 Africa CI Ivory Coast 27 836 009 0.47% 0.63% 0.01%
38 Africa GM Gambia 2 568 194 1.70% 0.59% 0.02%
39 South America VE Venezuela 28 256 320 0.43% 0.57% 0.03%
40 South America BR Brazil 215 929 973 0.49% 0.56% 0.30%
41 Asia AZ Azerbaijan 10 343 058 0.59% 0.56% 0.25%
42 North America MX Mexico 131 954 950 0.32% 0.55% 0.23%
43 Asia PK Pakistan 230 463 460 0.53% 0.52% 0.01%
44 Europe BG Bulgaria 6 831 877 0.62% 0.49% 0.61%
45 Europe DK Denmark 5 837 695 0.42% 0.47% 0.93%
46 South America UY Uruguay 3 500 580 0.31% 0.42% 0.87%
47 Africa TZ Tanzania 63 531 541 0.11% 0.42% 0.00%
48 Europe RO Romania 18 951 674 0.35% 0.42% 0.73%
49 Africa NE Niger 26 162 650 0.53% 0.41% 0.00%
50 Australia/Oceania NZ New Zealand 5 002 100 0.29% 0.41% 2.27%
51 Asia NP Nepal 30 306 197 0.32% 0.40% 0.03%
52 Asia ID Indonesia 279 976 514 0.36% 0.40% 0.08%
53 Europe BE Belgium 11 702 123 0.24% 0.38% 1.52%
54 North America HN Honduras 10 256 108 0.30% 0.37% 0.30%
55 South America EC Ecuador 18 240 838 0.21% 0.36% 0.33%
56 Europe PL Poland 37 754 189 0.46% 0.36% 0.64%
57 Australia/Oceania AU Australia 26 159 993 0.19% 0.35% 2.10%
58 North America US USA 335 049 756 0.36% 0.33% 1.25%
59 Africa NG Nigeria 217 541 658 0.13% 0.33% 0.00%
60 Europe MD Moldova 4 013 061 0.43% 0.32% 2.72%
61 South America CL Chile 19 482 269 0.32% 0.32% 1.66%
62 Europe UA Ukraine 43 148 150 0.59% 0.31% 0.39%
63 Asia LB Lebanon 6 757 312 0.19% 0.31% 0.30%
64 South America AR Argentina 46 120 998 0.18% 0.30% 0.56%
65 Europe GR Greece 10 309 569 0.24% 0.30% 8.69%
66 South America PR Puerto Rico 3 193 694 0.21% 0.29% 6.70%
67 Africa GW Guinea-Bissau 2 071 802 0.69% 0.29% 0.06%
68 North America CR Costa Rica 5 197 894 0.20% 0.28% 2.82%
69 Europe FR France 65 595 624 0.12% 0.28% 0.78%
70 Asia IN India 1 410 273 474 0.26% 0.28% 0.03%
71 Asia AM Armenia 2 975 594 0.29% 0.28% 1.14%
72 Asia IQ Iraq 42 236 708 0.10% 0.28% 0.07%
73 Europe RS Serbia 8 658 917 0.25% 0.27% 2.40%
74 Europe CZ Czechia 10 753 287 0.43% 0.27% 1.18%
75 Africa LY Libya 7 079 771 0.14% 0.27% 0.01%
76 Asia AF Afghanistan 40 884 801 0.53% 0.26% 0.04%
77 Africa ET Ethiopia 121 318 649 0.27% 0.25% 0.00%
78 Africa KE Kenya 56 414 444 0.18% 0.25% 0.00%
79 Europe IT Italy 60 263 602 0.20% 0.24% 2.06%
80 Europe FI Finland 5 559 915 0.53% 0.23% 1.86%
81 Asia BD Bangladesh 168 349 895 0.33% 0.23% 0.01%
82 Africa UG Uganda 48 965 219 0.63% 0.22% 0.00%
83 Asia IL Israel 9 326 000 0.15% 0.22% 1.21%
84 Asia MM Myanmar 55 223 453 0.21% 0.21% 0.02%
85 North America PA Panama 4 466 324 0.15% 0.20% 1.56%
86 Asia TR Turkey 86 363 808 0.12% 0.19% 1.50%
87 Asia MY Malaysia 33 291 238 0.20% 0.19% 0.41%
88 South America BO Bolivia 12 028 297 0.14% 0.18% 0.24%
89 Europe PT Portugal 10 130 428 0.19% 0.18% 1.45%
90 Asia HK Hong Kong 7 632 666 0.15% 0.18% 12.54%
91 Europe RU Russia 146 073 999 0.35% 0.15% 2.16%
92 Asia JP Japan 125 613 305 0.11% 0.12% 6.66%
93 Europe SI Slovenia 2 079 575 0.32% 0.12% 4.82%
94 Africa DZ Algeria 45 617 970 0.09% 0.12% 0.00%
95 Asia TW Taiwan 23 912 908 0.19% 0.11% 18.45%
96 Asia JO Jordan 10 429 112 0.11% 0.10% 0.82%
97 North America SV El Salvador 6 559 204 0.25% 0.10% 0.67%
98 Europe NL Netherlands 17 219 424 0.09% 0.09% 0.40%
99 Europe AL Albania 2 870 791 0.16% 0.09% 0.39%
100 Europe AT Austria 9 121 024 0.11% 0.08% 3.36%
101 Asia MN Mongolia 3 396 089 0.03% 0.07% 0.49%
102 Asia KZ Kazakhstan 19 277 809 0.04% 0.07% 0.31%
103 Europe LT Lithuania 2 637 684 0.20% 0.06% 2.35%
104 Asia KR South Korea 51 367 577 0.06% 0.05% 8.99%
105 Europe DE Germany 84 381 438 0.11% 0.05% 2.51%
106 Asia GE Georgia 3 972 095 0.09% 0.04% 5.18%
107 Africa ZM Zambia 19 533 022 0.27% 0.04% 0.02%
108 Asia SG Singapore 5 952 983 0.04% 0.04% 2.13%
109 Asia VN Vietnam 99 292 436 0.01% 0.04% 0.17%
110 Europe CH Switzerland 8 795 811 0.07% 0.02% 0.92%
111 Asia AE Arab Emirates 10 157 018 0.03% 0.02% 0.29%
112 Asia QA Qatar 2 807 805 0.01% 0.01% 1.49%
113 North America DO Dominican R. 11 090 604 0.01% 0.00% 0.25%
114 Asia KW Kuwait 4 411 493 0.03% 0.00% 0.12%
115 Asia LA Laos 7 511 127 0.02% 0.00% 0.07%
116 Asia OM Oman 5 396 468 0.01% 0.00% 0.06%
117 Asia KG Kyrgyzstan 6 764 377 0.00% 0.00% 0.03%
118 North America CU Cuba 11 311 201 0.02% 0.00% 0.02%
119 Africa ML Mali 21 552 636 0.41% 0.00% 0.02%
120 Africa LR Liberia 5 322 964 0.00% 0.00% 0.02%
121 North America NI Nicaragua 6 800 402 1.57% 0.00% 0.01%
122 Africa LS Lesotho 2 180 133 0.56% 0.00% 0.01%
123 Africa GA Gabon 2 342 935 0.19% 0.00% 0.01%
124 Africa BJ Benin 12 831 863 0.00% 0.00% 0.01%
125 Africa BI Burundi 12 681 192 0.00% 0.00% 0.01%
126 Asia SY Syria 18 449 407 1.01% 0.00% 0.00%
127 Africa AO Angola 35 148 150 0.46% 0.00% 0.00%
128 Africa SN Senegal 17 728 659 0.09% 0.00% 0.00%
129 Asia KH Cambodia 17 235 233 0.00% 0.00% 0.00%
130 Africa GH Ghana 32 520 343 0.19% 0.00% 0.00%
131 Asia UZ Uzbekistan 34 551 503 0.00% 0.00% 0.00%
132 Australia/Oceania PG Papua New Guinea 9 325 214 2.54% 0.00% 0.00%
133 Africa RW Rwanda 13 668 741 0.28% 0.00% 0.00%
134 Africa ER Eritrea 3 655 937 0.00% 0.00% 0.00%
135 Africa TD Chad 17 477 819 0.00% 0.00% 0.00%
136 Africa SD Sudan 46 134 014 2.18% 0.00% 0.00%
137 Africa MG Madagascar 29 279 726 0.71% 0.00% 0.00%
138 Africa CF Central African R. 5 017 145 0.00% 0.00% 0.00%
139 Africa SL Sierra Leone 8 338 976 0.00% 0.00% 0.00%
140 Africa CM Cameroon 28 020 530 0.29% 0.00% 0.00%
141 Africa SO Somalia 16 882 823 0.00% 0.00% 0.00%
142 Africa BF Burkina Faso 22 182 502 1.31% 0.00% 0.00%
143 Europe BY Belarus 9 442 392 1.23% 0.00% 0.00%
144 Africa CG Congo 5 821 197 0.14% 0.00% 0.00%
145 Africa SS South Sudan 11 486 528 0.00% 0.00% 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 Asia TJ Tajikistan 10 015 701 0.00% 0.00% 0.00%
149 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
150 Asia PS Palestine 5 366 059 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 33 996 669 216 146 6.358
2 Europe BG Bulgaria 6 831 877 37 661 5.513
3 Europe BA Bosnia and Herzegovina 3 235 336 16 100 4.976
4 Europe HU Hungary 9 605 664 47 367 4.931
5 Europe MK North Macedonia 2 083 183 9 512 4.566
6 Asia GE Georgia 3 972 095 16 900 4.255
7 Europe HR Croatia 4 048 842 16 812 4.152
8 Europe SI Slovenia 2 079 575 8 185 3.936
9 Europe CZ Czechia 10 753 287 40 918 3.805
10 Europe SK Slovakia 5 465 539 20 420 3.736
11 Europe RO Romania 18 951 674 66 867 3.528
12 Europe LT Lithuania 2 637 684 9 295 3.524
13 Europe GR Greece 10 309 569 32 757 3.177
14 South America BR Brazil 215 929 973 684 874 3.172
15 South America CL Chile 19 482 269 60 814 3.122
16 Europe PL Poland 37 754 189 117 305 3.107
17 North America US USA 335 049 756 1 039 676 3.103
18 Europe MD Moldova 4 013 061 11 783 2.936
19 Europe IT Italy 60 263 602 176 306 2.926
20 Asia AM Armenia 2 975 594 8 673 2.915
21 South America AR Argentina 46 120 998 129 830 2.815
22 Europe BE Belgium 11 702 123 32 605 2.786
23 Europe GB United Kingdom 68 681 433 189 026 2.752
24 South America CO Colombia 52 092 877 141 708 2.720
25 South America PY Paraguay 7 328 016 19 530 2.665
26 Europe RU Russia 146 073 999 385 631 2.640
27 Europe UA Ukraine 43 148 150 108 885 2.523
28 North America MX Mexico 131 954 950 329 761 2.499
29 Europe PT Portugal 10 130 428 24 928 2.461
30 Europe ES Spain 46 795 160 113 148 2.418
31 Africa TN Tunisia 12 094 522 29 238 2.417
32 Europe FR France 65 595 624 151 031 2.303
33 Europe AT Austria 9 121 024 20 722 2.272
34 South America UY Uruguay 3 500 580 7 462 2.132
35 South America EC Ecuador 18 240 838 35 876 1.967
36 Europe SE Sweden 10 239 736 20 006 1.954
37 Europe RS Serbia 8 658 917 16 843 1.945
38 North America PA Panama 4 466 324 8 487 1.900
39 South America BO Bolivia 12 028 297 22 218 1.847
40 Europe DE Germany 84 381 438 148 507 1.760
41 North America CR Costa Rica 5 197 894 8 913 1.715
42 Africa ZA South Africa 60 977 086 102 129 1.675
43 Asia IR Iran 86 391 625 144 206 1.669
44 South America PR Puerto Rico 3 193 694 5 034 1.576
45 Asia LB Lebanon 6 757 312 10 648 1.576
46 Europe IE Ireland 5 060 845 7 870 1.555
47 Africa NA Namibia 2 643 585 4 077 1.542
48 Europe CH Switzerland 8 795 811 13 539 1.539
49 Asia JO Jordan 10 429 112 14 114 1.353
50 Asia HK Hong Kong 7 632 666 10 134 1.328
51 Europe NL Netherlands 17 219 424 22 616 1.313
52 Asia IL Israel 9 326 000 11 687 1.253
53 Europe AL Albania 2 870 791 3 586 1.249
54 Europe DK Denmark 5 837 695 6 986 1.197
55 Asia TR Turkey 86 363 808 101 068 1.170
56 North America CA Canada 38 480 391 44 347 1.153
57 Africa BW Botswana 2 457 583 2 781 1.132
58 North America JM Jamaica 2 989 995 3 285 1.099
59 Asia MY Malaysia 33 291 238 36 292 1.090
60 North America HN Honduras 10 256 108 10 989 1.071
61 North America GT Guatemala 18 655 084 19 672 1.054
62 Europe FI Finland 5 559 915 5 768 1.037
63 Asia KZ Kazakhstan 19 277 809 19 047 0.988
64 Asia AZ Azerbaijan 10 343 058 9 861 0.953
65 Africa LY Libya 7 079 771 6 437 0.909
66 Asia OM Oman 5 396 468 4 628 0.858
67 Asia LK Sri Lanka 21 613 502 16 732 0.774
68 North America CU Cuba 11 311 201 8 530 0.754
69 Europe BY Belarus 9 442 392 7 118 0.754
70 Europe NO Norway 5 515 806 4 004 0.726
71 North America SV El Salvador 6 559 204 4 228 0.645
72 Asia MN Mongolia 3 396 089 2 130 0.627
73 Asia IQ Iraq 42 236 708 25 348 0.600
74 Australia/Oceania NZ New Zealand 5 002 100 2 962 0.592
75 Asia KW Kuwait 4 411 493 2 563 0.581
76 Asia ID Indonesia 279 976 514 157 828 0.564
77 Asia PH Philippines 112 835 294 62 372 0.553
78 Australia/Oceania AU Australia 26 159 993 14 443 0.552
79 Asia KR South Korea 51 367 577 27 559 0.536
80 Asia TH Thailand 70 190 589 32 574 0.464
81 Asia TW Taiwan 23 912 908 10 912 0.456
82 Asia KG Kyrgyzstan 6 764 377 2 991 0.442
83 Asia VN Vietnam 99 292 436 43 131 0.434
84 Africa MA Morocco 37 886 664 16 276 0.430
85 Asia NP Nepal 30 306 197 12 015 0.397
86 North America DO Dominican R. 11 090 604 4 384 0.395
87 Asia IN India 1 410 273 474 528 217 0.375
88 Africa ZW Zimbabwe 15 345 688 5 596 0.365
89 Asia MM Myanmar 55 223 453 19 442 0.352
90 Asia JP Japan 125 613 305 42 882 0.341
91 Africa LS Lesotho 2 180 133 704 0.323
92 Asia SG Singapore 5 952 983 1 607 0.270
93 Asia SA Saudi Arabia 36 023 641 9 320 0.259
94 Asia QA Qatar 2 807 805 682 0.243
95 Africa EG Egypt 106 641 391 24 796 0.233
96 Asia AE Arab Emirates 10 157 018 2 343 0.231
97 Africa ZM Zambia 19 533 022 4 017 0.206
98 South America VE Venezuela 28 256 320 5 809 0.206
99 Africa MR Mauritania 4 922 415 993 0.202
100 Asia AF Afghanistan 40 884 801 7 789 0.191
101 Asia KH Cambodia 17 235 233 3 056 0.177
102 Asia BD Bangladesh 168 349 895 29 336 0.174
103 Asia SY Syria 18 449 407 3 163 0.171
104 Africa DZ Algeria 45 617 970 6 879 0.151
105 Africa GM Gambia 2 568 194 372 0.145
106 Asia PK Pakistan 230 463 460 30 599 0.133
107 Africa MW Malawi 20 233 145 2 675 0.132
108 Africa GA Gabon 2 342 935 306 0.131
109 Africa SN Senegal 17 728 659 1 968 0.111
110 Africa SD Sudan 46 134 014 4 961 0.107
111 Africa RW Rwanda 13 668 741 1 466 0.107
112 Asia LA Laos 7 511 127 757 0.101
113 Africa KE Kenya 56 414 444 5 674 0.101
114 Africa GW Guinea-Bissau 2 071 802 175 0.085
115 Africa SO Somalia 16 882 823 1 361 0.081
116 Africa UG Uganda 48 965 219 3 628 0.074
117 North America HT Haiti 11 712 663 857 0.073
118 Australia/Oceania PG Papua New Guinea 9 325 214 664 0.071
119 Africa CM Cameroon 28 020 530 1 935 0.069
120 Asia YE Yemen 31 291 872 2 155 0.069
121 Africa MZ Mozambique 33 209 769 2 222 0.067
122 Africa CG Congo 5 821 197 386 0.066
123 Africa ET Ethiopia 121 318 649 7 572 0.062
124 Africa LR Liberia 5 322 964 294 0.055
125 Africa AO Angola 35 148 150 1 917 0.054
126 Africa MG Madagascar 29 279 726 1 410 0.048
127 Asia UZ Uzbekistan 34 551 503 1 637 0.047
128 Africa GH Ghana 32 520 343 1 459 0.045
129 North America NI Nicaragua 6 800 402 244 0.036
130 Africa ML Mali 21 552 636 739 0.034
131 Africa TG Togo 8 711 726 284 0.033
132 Africa GN Guinea 13 927 802 449 0.032
133 Africa CI Ivory Coast 27 836 009 822 0.029
134 Africa ER Eritrea 3 655 937 103 0.028
135 Africa CF Central African R. 5 017 145 113 0.022
136 Africa BF Burkina Faso 22 182 502 387 0.017
137 Africa SL Sierra Leone 8 338 976 125 0.015
138 Africa CD DR Congo 95 638 591 1 422 0.015
139 Africa NG Nigeria 217 541 658 3 154 0.015
140 Africa TZ Tanzania 63 531 541 845 0.013
141 Africa BJ Benin 12 831 863 163 0.013
142 Africa SS South Sudan 11 486 528 138 0.012
143 Africa NE Niger 26 162 650 312 0.012
144 Africa TD Chad 17 477 819 193 0.011
145 Africa BI Burundi 12 681 192 15 0.001
146 Asia PS Palestine 5 366 059 3 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 10 015 701 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"