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": 2022-08-03 14:57
(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 +8 475 (+6 638) +11 (+22)
CZ Czechia +3 079 (+3 440) +5 (+13)
DE Germany +0 (+87 681) +0 (+210)
HU Hungary +21 840 (+0) +96 (+0)
PL Poland +4 479 (+5 641) +16 (+22)
SK Slovakia, [gov], [okr]+1 078 (+934) +4 (+5)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 North America 598 024 150 1.98% 2.87% 2.76%
2 Australia/Oceania 43 859 049 12.28% 9.06% 2.02%
3 Europe 756 574 482 4.37% 4.47% 1.37%
4 South America 441 406 008 1.29% 1.62% 0.66%
5 Asia 4 704 797 741 0.43% 0.43% 0.31%
6 Africa 1 406 763 609 0.05% 0.05% 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 Africa 1 406 763 609 0.50% (0.59)% (0.05)%
2 South America 441 406 008 0.42% 0.43% 1.62%
3 North America 598 024 150 0.49% 0.40% 2.87%
4 Europe 756 574 482 0.23% 0.17% 4.47%
5 Australia/Oceania 43 859 049 0.11% 0.15% 9.06%
6 Asia 4 704 797 741 0.17% 0.13% 0.43%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 441 406 008 1 317 013 2.984
2 Europe 756 574 482 1 871 931 2.474
3 North America 598 024 150 1 461 980 2.445
4 Australia/Oceania 43 859 049 16 092 0.367
5 Asia 4 704 797 741 1 440 518 0.306
6 Africa 1 406 763 609 256 765 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 Europe GR Greece 10 317 182 12.94% 18.73% 24.66%
2 Asia TW Taiwan 23 906 450 19.36% 12.69% 11.03%
3 South America PR Puerto Rico 3 193 694 10.93% 10.60% 9.70%
4 Asia HK Hong Kong 7 623 538 2.46% 5.78% 7.19%
5 Asia IL Israel 9 326 000 6.70% 8.65% 4.61%
6 North America US USA 334 776 423 2.91% 4.24% 4.57%
7 Asia TR Turkey 86 227 507 0.91% 1.98% 4.50%
8 Asia KR South Korea 51 360 968 9.60% 6.24% 4.00%
9 Europe HU Hungary 9 609 334 1.17% 1.86% 3.90%
10 North America PA Panama 4 456 110 4.04% 3.39% 3.84%
11 South America PY Paraguay 7 314 852 0.57% 1.94% 3.51%
12 Asia GE Georgia 3 973 241 0.77% 1.60% 3.37%
13 Europe BE Belgium 11 694 561 5.15% 5.92% 3.34%
14 Asia SG Singapore 5 946 078 8.97% 12.05% 2.95%
15 Australia/Oceania AU Australia 26 115 548 17.15% 12.05% 2.69%
16 Asia JP Japan 125 671 231 3.38% 5.04% 2.67%
17 Europe IE Ireland 5 052 560 4.66% 4.22% 2.67%
18 Europe GB United Kingdom 68 627 954 3.83% 3.82% 2.35%
19 Australia/Oceania NZ New Zealand 5 002 100 16.57% 15.03% 2.29%
20 Europe IT Italy 60 276 909 9.38% 11.70% 1.84%
21 Europe DE Germany 84 341 285 9.87% 8.76% 1.78%
22 Europe AT Austria 9 113 317 8.57% 9.47% 1.59%
23 South America AR Argentina 46 058 736 0.96% 1.08% 1.48%
24 Europe SI Slovenia 2 079 532 4.50% 5.37% 1.46%
25 South America EC Ecuador 18 200 555 0.47% 0.92% 1.44%
26 Europe MD Moldova 4 014 464 0.37% 0.67% 1.43%
27 Europe FR France 65 573 982 10.94% 11.85% 1.42%
28 Europe RS Serbia 8 664 181 1.12% 2.17% 1.37%
29 South America UY Uruguay 3 498 775 2.57% 1.81% 1.19%
30 Asia KZ Kazakhstan 19 244 066 0.11% 0.42% 1.13%
31 North America CA Canada 38 430 718 1.46% 0.81% 1.11%
32 Europe SE Sweden 10 230 290 0.52% 0.77% 0.98%
33 Asia AM Armenia 2 974 765 0.11% 0.33% 0.83%
34 Europe RO Romania 18 970 854 0.72% 1.49% 0.82%
35 South America CO Colombia 52 011 425 0.27% 0.71% 0.81%
36 South America BO Bolivia 12 004 365 0.74% 2.05% 0.76%
37 Europe LT Lithuania 2 643 349 2.06% 2.04% 0.76%
38 Europe HR Croatia 4 052 626 1.78% 2.34% 0.75%
39 Europe AL Albania 2 871 261 0.64% 1.32% 0.72%
40 Asia MN Mongolia 3 388 150 0.48% 0.80% 0.71%
41 Europe PT Portugal 10 134 876 15.21% 4.61% 0.69%
42 Asia QA Qatar 2 807 805 1.33% 2.13% 0.51%
43 Europe CZ Czechia 10 750 310 1.19% 1.18% 0.49%
44 Europe BG Bulgaria 6 839 692 0.77% 1.23% 0.49%
45 North America DO Dominican R. 11 074 270 0.42% 0.92% 0.48%
46 South America PE Peru 33 927 630 0.73% 1.91% 0.47%
47 South America CL Chile 19 457 638 3.48% 2.94% 0.44%
48 Asia OM Oman 5 376 889 0.10% 0.21% 0.43%
49 Europe DK Denmark 5 834 637 2.55% 3.04% 0.41%
50 Asia JO Jordan 10 413 903 0.17% 0.26% 0.40%
51 North America HN Honduras 10 232 418 0.16% 0.37% 0.40%
52 Europe SK Slovakia 5 465 143 1.45% 1.03% 0.34%
53 Asia LB Lebanon 6 761 883 0.82% 1.96% 0.34%
54 Africa LY Libya 7 065 728 0.03% 0.10% 0.34%
55 Europe NL Netherlands 17 213 743 2.23% 2.43% 0.33%
56 North America MX Mexico 131 751 514 0.61% 1.23% 0.28%
57 South America BR Brazil 215 703 263 1.62% 1.88% 0.27%
58 Europe BA Bosnia and Herzegovina 3 238 386 0.22% 0.49% 0.25%
59 Europe CH Switzerland 8 786 314 4.32% 5.17% 0.24%
60 Asia MY Malaysia 33 228 923 1.17% 0.85% 0.22%
61 North America GT Guatemala 18 605 212 0.91% 1.75% 0.21%
62 Europe PL Poland 37 760 394 0.20% 0.35% 0.20%
63 Asia IR Iran 86 230 076 0.15% 0.28% 0.19%
64 Europe ES Spain 46 792 448 3.20% 2.73% 0.18%
65 Asia AE Arab Emirates 10 139 064 0.85% 1.08% 0.17%
66 Europe RU Russia 146 064 628 0.42% 0.25% 0.17%
67 Europe MK North Macedonia 2 083 196 0.71% 1.41% 0.15%
68 Africa TN Tunisia 12 075 950 0.64% 2.09% 0.12%
69 Asia AZ Azerbaijan 10 329 338 0.04% 0.10% 0.09%
70 Africa BI Burundi 12 627 743 0.04% 0.04% 0.09%
71 Asia KG Kyrgyzstan 6 748 187 0.01% 0.04% 0.07%
72 Europe NO Norway 5 509 445 0.80% 0.38% 0.07%
73 Asia TH Thailand 70 164 343 1.16% 0.22% 0.06%
74 Africa ZA South Africa 60 864 725 0.48% 0.09% 0.06%
75 Europe UA Ukraine 43 187 425 0.17% 0.04% 0.06%
76 Asia IQ Iraq 42 100 744 0.23% 0.60% 0.05%
77 Asia PH Philippines 112 616 098 0.06% 0.13% 0.05%
78 North America JM Jamaica 2 988 057 0.54% 0.24% 0.04%
79 Asia ID Indonesia 279 542 137 0.05% 0.09% 0.04%
80 Asia VN Vietnam 99 160 960 0.91% 0.07% 0.04%
81 Asia NP Nepal 30 227 344 0.02% 0.05% 0.03%
82 South America VE Venezuela 28 268 374 0.04% 0.07% 0.03%
83 Africa GW Guinea-Bissau 2 064 793 0.01% 0.01% 0.02%
84 Africa GM Gambia 2 557 951 0.00% 0.01% 0.02%
85 Asia IN India 1 408 236 258 0.06% 0.09% 0.02%
86 Africa MA Morocco 37 820 938 0.24% 0.31% 0.02%
87 Asia LA Laos 7 495 255 0.35% 0.02% 0.02%
88 Africa ZW Zimbabwe 15 313 161 0.07% 0.03% 0.02%
89 Africa NA Namibia 2 636 661 0.33% 0.07% 0.01%
90 Africa MG Madagascar 29 172 400 0.01% 0.02% 0.01%
91 Asia AF Afghanistan 40 752 734 0.02% 0.02% 0.01%
92 Asia SA Saudi Arabia 35 942 111 0.15% 0.10% 0.01%
93 Asia LK Sri Lanka 21 600 042 0.01% 0.01% 0.01%
94 Africa ER Eritrea 3 648 560 0.01% 0.01% 0.01%
95 North America CU Cuba 11 312 236 0.12% 0.04% 0.01%
96 Asia PK Pakistan 229 817 854 0.01% 0.02% 0.01%
97 North America NI Nicaragua 6 788 561 0.01% 0.01% 0.01%
98 Africa SS South Sudan 11 466 813 0.00% 0.00% 0.01%
99 Africa AO Angola 34 993 794 0.01% 0.02% 0.01%
100 Africa MW Malawi 20 158 617 0.01% 0.01% 0.01%
101 Africa MR Mauritania 4 903 986 0.07% 0.14% 0.01%
102 Africa CI Ivory Coast 27 737 554 0.01% 0.02% 0.01%
103 Africa ZM Zambia 19 455 353 0.06% 0.07% 0.01%
104 Asia BD Bangladesh 168 103 522 0.03% 0.05% 0.00%
105 Africa EG Egypt 106 350 908 0.01% 0.00% 0.00%
106 Asia KH Cambodia 17 200 455 0.00% 0.01% 0.00%
107 Africa DZ Algeria 45 498 823 0.00% 0.01% 0.00%
108 Africa NG Nigeria 216 771 563 0.00% 0.00% 0.00%
109 Asia SY Syria 18 385 337 0.00% 0.00% 0.00%
110 Africa SN Senegal 17 662 125 0.01% 0.01% 0.00%
111 Africa CF Central African R. 5 004 512 0.01% 0.00% 0.00%
112 Africa LR Liberia 5 305 052 0.00% 0.00% 0.00%
113 Asia UZ Uzbekistan 34 478 582 0.01% 0.02% 0.00%
114 Australia/Oceania PG Papua New Guinea 9 299 707 0.01% 0.00% 0.00%
115 Africa KE Kenya 56 236 044 0.02% 0.02% 0.00%
116 Africa TG Togo 8 682 490 0.01% 0.02% 0.00%
117 Africa MZ Mozambique 33 077 670 0.01% 0.02% 0.00%
118 Africa SO Somalia 16 815 935 0.00% 0.00% 0.00%
119 Africa SL Sierra Leone 8 314 553 0.00% 0.00% 0.00%
120 Africa SD Sudan 45 979 755 0.00% 0.00% 0.00%
121 Asia YE Yemen 31 192 930 0.00% 0.00% 0.00%
122 Africa BF Burkina Faso 22 096 048 0.00% 0.00% 0.00%
123 Africa LS Lesotho 2 177 585 0.05% 0.02% 0.00%
124 Africa GA Gabon 2 335 022 0.03% 0.09% 0.00%
125 Europe FI Finland 5 558 625 5.49% 2.46% 0.00%
126 Africa ET Ethiopia 120 889 430 0.02% 0.01% 0.00%
127 Africa UG Uganda 48 747 095 0.01% 0.01% 0.00%
128 Asia KW Kuwait 4 401 998 0.46% 0.72% 0.00%
129 Africa TZ Tanzania 63 274 840 0.00% 0.01% 0.00%
130 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
131 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
132 Asia TJ Tajikistan 9 983 431 0.00% 0.00% 0.00%
133 Africa TD Chad 17 406 702 0.00% 0.00% 0.00%
134 North America CR Costa Rica 5 190 911 2.47% 4.27% 0.00%
135 Africa NE Niger 26 030 170 0.00% 0.00% 0.00%
136 North America SV El Salvador 6 554 297 0.30% 0.69% 0.00%
137 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
138 Africa CM Cameroon 27 920 928 0.00% 0.00% 0.00%
139 Africa CG Congo 5 800 725 0.01% 0.03% 0.00%
140 North America HT Haiti 11 691 779 0.01% 0.03% 0.00%
141 Asia MM Myanmar 55 168 730 0.00% 0.00% 0.00%
142 Africa CD DR Congo 95 227 577 0.01% 0.00% 0.00%
143 Europe BY Belarus 9 442 858 0.42% 0.47% 0.00%
144 Africa ML Mali 21 464 627 0.00% 0.00% 0.00%
145 Africa BW Botswana 2 450 435 0.72% 0.52% 0.00%
146 Asia PS Palestine 5 348 192 0.00% 0.00% 0.00%
147 Africa RW Rwanda 13 620 347 0.02% 0.02% 0.00%
148 Africa GN Guinea 13 874 077 0.01% 0.01% 0.00%
149 Africa BJ Benin 12 783 983 0.01% 0.00% 0.00%
150 Africa GH Ghana 32 422 677 0.02% 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 Africa EG Egypt 106 350 908 2.07% (16.09)% (0.00)%
2 Africa GM Gambia 2 557 951 7.50% (15.79)% (0.01)%
3 Africa GW Guinea-Bissau 2 064 793 1.18% (3.85)% (0.01)%
4 Asia LK Sri Lanka 21 600 042 1.67% (3.26)% (0.01)%
5 North America NI Nicaragua 6 788 561 2.58% (2.27)% (0.01)%
6 Africa LS Lesotho 2 177 585 0.43% (2.22)% (0.02)%
7 Europe NO Norway 5 509 445 1.71% 2.03% 0.38%
8 Africa NA Namibia 2 636 661 0.59% 1.78% 0.07%
9 Africa ZW Zimbabwe 15 313 161 1.11% 1.71% 0.03%
10 Africa ZA South Africa 60 864 725 0.69% 1.52% 0.09%
11 Africa CD DR Congo 95 227 577 0.96% 1.50% 0.00%
12 Europe UA Ukraine 43 187 425 0.95% 1.46% 0.04%
13 Africa SD Sudan 45 979 755 3.75% 1.38% 0.00%
14 North America JM Jamaica 2 988 057 1.73% 1.37% 0.24%
15 Europe BY Belarus 9 442 858 0.75% 1.25% 0.47%
16 Africa MW Malawi 20 158 617 2.08% 1.18% 0.01%
17 North America CA Canada 38 430 718 0.84% 0.88% 0.81%
18 Europe BA Bosnia and Herzegovina 3 238 386 1.58% 0.87% 0.49%
19 Europe RU Russia 146 064 628 1.65% 0.85% 0.25%
20 Europe SE Sweden 10 230 290 1.64% 0.84% 0.77%
21 Europe MD Moldova 4 014 464 1.35% 0.81% 0.67%
22 Asia TH Thailand 70 164 343 0.55% 0.74% 0.22%
23 Asia AZ Azerbaijan 10 329 338 0.96% 0.72% 0.10%
24 Europe HU Hungary 9 609 334 1.17% 0.71% 1.86%
25 Asia AF Afghanistan 40 752 734 1.02% 0.68% 0.02%
26 Africa RW Rwanda 13 620 347 0.31% 0.64% 0.02%
27 South America PY Paraguay 7 314 852 1.74% 0.62% 1.94%
28 Africa GN Guinea 13 874 077 0.55% 0.61% 0.01%
29 Africa MG Madagascar 29 172 400 0.88% 0.57% 0.02%
30 Africa ET Ethiopia 120 889 430 0.26% 0.56% 0.01%
31 South America CO Colombia 52 011 425 0.73% 0.55% 0.71%
32 Africa AO Angola 34 993 794 0.37% 0.51% 0.02%
33 Africa UG Uganda 48 747 095 0.75% 0.47% 0.01%
34 Europe HR Croatia 4 052 626 0.74% 0.44% 2.34%
35 Asia PK Pakistan 229 817 854 0.42% 0.43% 0.02%
36 Europe GB United Kingdom 68 627 954 0.51% 0.42% 3.82%
37 Asia IR Iran 86 230 076 0.91% 0.39% 0.28%
38 North America HN Honduras 10 232 418 0.37% 0.39% 0.37%
39 Africa TN Tunisia 12 075 950 0.65% 0.38% 2.09%
40 Africa TG Togo 8 682 490 0.51% 0.36% 0.02%
41 North America SV El Salvador 6 554 297 0.33% 0.35% 0.69%
42 South America UY Uruguay 3 498 775 0.25% 0.35% 1.81%
43 Africa GA Gabon 2 335 022 0.42% 0.35% 0.09%
44 North America US USA 334 776 423 0.50% 0.34% 4.24%
45 Europe ES Spain 46 792 448 0.38% 0.34% 2.73%
46 South America VE Venezuela 28 268 374 0.61% 0.33% 0.07%
47 South America BR Brazil 215 703 263 0.45% 0.33% 1.88%
48 Europe BG Bulgaria 6 839 692 1.26% 0.32% 1.23%
49 South America CL Chile 19 457 638 0.34% 0.31% 2.94%
50 Africa ZM Zambia 19 455 353 0.38% 0.30% 0.07%
51 Africa KE Kenya 56 236 044 0.16% 0.29% 0.02%
52 Europe SK Slovakia 5 465 143 0.65% 0.29% 1.03%
53 North America GT Guatemala 18 605 212 0.89% 0.28% 1.75%
54 Europe MK North Macedonia 2 083 196 0.71% 0.26% 1.41%
55 Asia BD Bangladesh 168 103 522 0.28% 0.26% 0.05%
56 South America EC Ecuador 18 200 555 0.52% 0.25% 0.92%
57 Europe PL Poland 37 760 394 1.21% 0.25% 0.35%
58 South America PR Puerto Rico 3 193 694 0.17% 0.24% 10.60%
59 Asia TW Taiwan 23 906 450 0.18% 0.23% 12.69%
60 South America PE Peru 33 927 630 0.66% 0.22% 1.91%
61 Europe IE Ireland 5 052 560 0.28% 0.21% 4.22%
62 Africa CG Congo 5 800 725 0.33% 0.21% 0.03%
63 Europe DK Denmark 5 834 637 0.47% 0.21% 3.04%
64 Africa LY Libya 7 065 728 1.11% 0.20% 0.10%
65 Africa GH Ghana 32 422 677 0.17% 0.20% 0.03%
66 Asia ID Indonesia 279 542 137 0.99% 0.19% 0.09%
67 Africa MZ Mozambique 33 077 670 0.37% 0.19% 0.02%
68 Australia/Oceania NZ New Zealand 5 002 100 0.17% 0.18% 15.03%
69 Europe RO Romania 18 970 854 0.53% 0.18% 1.49%
70 Asia SA Saudi Arabia 35 942 111 0.34% 0.18% 0.10%
71 North America PA Panama 4 456 110 0.14% 0.18% 3.39%
72 Europe PT Portugal 10 134 876 0.17% 0.18% 4.61%
73 North America MX Mexico 131 751 514 0.23% 0.17% 1.23%
74 Asia AM Armenia 2 974 765 0.47% 0.17% 0.33%
75 Asia GE Georgia 3 973 241 0.60% 0.17% 1.60%
76 Africa MA Morocco 37 820 938 0.16% 0.17% 0.31%
77 Africa CI Ivory Coast 27 737 554 0.38% 0.17% 0.02%
78 Asia IN India 1 408 236 258 0.56% 0.17% 0.09%
79 South America AR Argentina 46 058 736 0.21% 0.17% 1.08%
80 Europe CZ Czechia 10 750 310 0.35% 0.16% 1.18%
81 Europe RS Serbia 8 664 181 0.36% 0.16% 2.17%
82 Asia PH Philippines 112 616 098 1.99% 0.15% 0.13%
83 Europe BE Belgium 11 694 561 0.23% 0.14% 5.92%
84 Asia MY Malaysia 33 228 923 0.16% 0.14% 0.85%
85 Europe AL Albania 2 871 261 0.15% 0.14% 1.32%
86 Africa BW Botswana 2 450 435 0.37% 0.14% 0.52%
87 Europe GR Greece 10 317 182 0.27% 0.14% 18.73%
88 Europe LT Lithuania 2 643 349 0.37% 0.14% 2.04%
89 Asia IL Israel 9 326 000 0.12% 0.14% 8.65%
90 Europe SI Slovenia 2 079 532 0.36% 0.13% 5.37%
91 Asia HK Hong Kong 7 623 538 0.65% 0.12% 5.78%
92 Europe FI Finland 5 558 625 0.41% 0.12% 2.46%
93 Australia/Oceania AU Australia 26 115 548 0.10% 0.11% 12.05%
94 North America HT Haiti 11 691 779 0.54% 0.10% 0.03%
95 Europe IT Italy 60 276 909 0.18% 0.10% 11.70%
96 Africa MR Mauritania 4 903 986 0.12% 0.08% 0.14%
97 Asia TR Turkey 86 227 507 0.25% 0.08% 1.98%
98 Africa NG Nigeria 216 771 563 0.10% 0.08% 0.00%
99 Asia LB Lebanon 6 761 883 0.32% 0.07% 1.96%
100 South America BO Bolivia 12 004 365 0.12% 0.07% 2.05%
101 Europe FR France 65 573 982 0.10% 0.06% 11.85%
102 Asia NP Nepal 30 227 344 0.07% 0.06% 0.05%
103 Europe AT Austria 9 113 317 0.12% 0.05% 9.47%
104 Europe NL Netherlands 17 213 743 0.08% 0.05% 2.43%
105 Asia IQ Iraq 42 100 744 0.10% 0.05% 0.60%
106 Asia JO Jordan 10 413 903 0.26% 0.04% 0.26%
107 Asia KZ Kazakhstan 19 244 066 0.14% 0.04% 0.42%
108 Asia KR South Korea 51 360 968 0.11% 0.04% 6.24%
109 Europe DE Germany 84 341 285 0.07% 0.04% 8.76%
110 Asia JP Japan 125 671 231 0.08% 0.04% 5.04%
111 Europe CH Switzerland 8 786 314 0.06% 0.03% 5.17%
112 Asia SG Singapore 5 946 078 0.04% 0.03% 12.05%
113 Asia AE Arab Emirates 10 139 064 0.03% 0.02% 1.08%
114 Asia VN Vietnam 99 160 960 0.03% 0.02% 0.07%
115 Asia MN Mongolia 3 388 150 0.07% 0.02% 0.80%
116 Asia KW Kuwait 4 401 998 0.01% 0.01% 0.72%
117 Asia QA Qatar 2 807 805 0.01% 0.01% 2.13%
118 North America CR Costa Rica 5 190 911 0.20% 0.00% 4.27%
119 North America DO Dominican R. 11 074 270 0.02% 0.00% 0.92%
120 Asia OM Oman 5 376 889 0.24% 0.00% 0.21%
121 Africa BI Burundi 12 627 743 0.00% 0.00% 0.04%
122 Asia KG Kyrgyzstan 6 748 187 1.41% 0.00% 0.04%
123 North America CU Cuba 11 312 236 0.07% 0.00% 0.04%
124 Asia LA Laos 7 495 255 0.18% 0.00% 0.02%
125 Asia UZ Uzbekistan 34 478 582 0.00% 0.00% 0.02%
126 Africa ER Eritrea 3 648 560 0.00% 0.00% 0.01%
127 Africa SN Senegal 17 662 125 0.28% 0.00% 0.01%
128 Africa TZ Tanzania 63 274 840 1.49% 0.00% 0.01%
129 Asia KH Cambodia 17 200 455 0.20% 0.00% 0.01%
130 Africa DZ Algeria 45 498 823 0.10% 0.00% 0.01%
131 Africa BJ Benin 12 783 983 0.00% 0.00% 0.00%
132 Africa SO Somalia 16 815 935 0.00% 0.00% 0.00%
133 Asia SY Syria 18 385 337 1.41% 0.00% 0.00%
134 Australia/Oceania PG Papua New Guinea 9 299 707 1.28% 0.00% 0.00%
135 Africa BF Burkina Faso 22 096 048 2.54% 0.00% 0.00%
136 Asia MM Myanmar 55 168 730 0.04% 0.00% 0.00%
137 Africa SS South Sudan 11 466 813 0.00% 0.00% 0.00%
138 Africa SL Sierra Leone 8 314 553 0.00% 0.00% 0.00%
139 Africa CF Central African R. 5 004 512 0.00% 0.00% 0.00%
140 Africa ML Mali 21 464 627 1.22% 0.00% 0.00%
141 Africa LR Liberia 5 305 052 0.00% 0.00% 0.00%
142 Asia YE Yemen 31 192 930 13.73% 0.00% 0.00%
143 Africa NE Niger 26 030 170 0.99% 0.00% 0.00%
144 Africa TD Chad 17 406 702 1.85% 0.00% 0.00%
145 Africa CM Cameroon 27 920 928 0.60% 0.00% 0.00%
146 Asia PS Palestine 5 348 192 0.00% 0.00% 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 TJ Tajikistan 9 983 431 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 33 927 630 213 937 6.306
2 Europe BG Bulgaria 6 839 692 37 329 5.458
3 Europe BA Bosnia and Herzegovina 3 238 386 15 840 4.891
4 Europe HU Hungary 9 609 334 46 832 4.874
5 Europe MK North Macedonia 2 083 196 9 353 4.490
6 Asia GE Georgia 3 973 241 16 854 4.242
7 Europe HR Croatia 4 052 626 16 202 3.998
8 Europe SI Slovenia 2 079 532 7 881 3.790
9 Europe CZ Czechia 10 750 310 40 385 3.757
10 Europe SK Slovakia 5 465 143 20 197 3.696
11 Europe LT Lithuania 2 643 349 9 198 3.480
12 Europe RO Romania 18 970 854 65 879 3.473
13 South America BR Brazil 215 703 263 676 488 3.136
14 Europe PL Poland 37 760 394 116 514 3.086
15 South America CL Chile 19 457 638 59 223 3.044
16 North America US USA 334 776 423 1 015 897 3.035
17 Europe GR Greece 10 317 182 30 707 2.976
18 Asia AM Armenia 2 974 765 8 628 2.900
19 Europe MD Moldova 4 014 464 11 592 2.888
20 Europe IT Italy 60 276 909 170 717 2.832
21 South America AR Argentina 46 058 736 129 202 2.805
22 Europe BE Belgium 11 694 561 32 118 2.746
23 South America CO Colombia 52 011 425 140 365 2.699
24 Europe GB United Kingdom 68 627 954 182 727 2.663
25 Europe RU Russia 146 064 628 382 123 2.616
26 South America PY Paraguay 7 314 852 19 083 2.609
27 Europe UA Ukraine 43 187 425 108 699 2.517
28 North America MX Mexico 131 751 514 326 897 2.481
29 Europe PT Portugal 10 134 876 24 527 2.420
30 Africa TN Tunisia 12 075 950 28 951 2.397
31 Europe ES Spain 46 792 448 109 642 2.343
32 Europe FR France 65 573 982 147 926 2.256
33 Europe AT Austria 9 113 317 20 237 2.221
34 South America UY Uruguay 3 498 775 7 387 2.111
35 South America EC Ecuador 18 200 555 35 781 1.966
36 North America PA Panama 4 456 110 8 395 1.884
37 Europe SE Sweden 10 230 290 19 249 1.882
38 Europe RS Serbia 8 664 181 16 203 1.870
39 South America BO Bolivia 12 004 365 22 002 1.833
40 Europe DE Germany 84 341 285 143 271 1.699
41 Africa ZA South Africa 60 864 725 101 942 1.675
42 North America CR Costa Rica 5 190 911 8 525 1.642
43 Asia IR Iran 86 230 076 141 606 1.642
44 Asia LB Lebanon 6 761 883 10 498 1.552
45 Africa NA Namibia 2 636 661 4 069 1.543
46 Europe CH Switzerland 8 786 314 13 387 1.524
47 Europe IE Ireland 5 052 560 7 620 1.508
48 South America PR Puerto Rico 3 193 694 4 708 1.474
49 Asia JO Jordan 10 413 903 14 070 1.351
50 Europe NL Netherlands 17 213 743 22 453 1.304
51 Asia HK Hong Kong 7 623 538 9 520 1.249
52 Europe AL Albania 2 871 261 3 519 1.226
53 Asia IL Israel 9 326 000 11 407 1.223
54 Asia TR Turkey 86 227 507 99 184 1.150
55 Europe DK Denmark 5 834 637 6 586 1.129
56 Africa BW Botswana 2 450 435 2 752 1.123
57 North America CA Canada 38 430 718 42 148 1.097
58 Asia MY Malaysia 33 228 923 35 896 1.080
59 North America HN Honduras 10 232 418 10 937 1.069
60 North America JM Jamaica 2 988 057 3 175 1.063
61 North America GT Guatemala 18 605 212 18 873 1.014
62 Asia KZ Kazakhstan 19 244 066 19 020 0.988
63 Asia AZ Azerbaijan 10 329 338 9 733 0.942
64 Africa LY Libya 7 065 728 6 431 0.910
65 Europe FI Finland 5 558 625 5 012 0.902
66 Asia OM Oman 5 376 889 4 628 0.861
67 Asia LK Sri Lanka 21 600 042 16 542 0.766
68 North America CU Cuba 11 312 236 8 529 0.754
69 Europe BY Belarus 9 442 858 7 118 0.754
70 Europe NO Norway 5 509 445 3 596 0.653
71 North America SV El Salvador 6 554 297 4 186 0.639
72 Asia MN Mongolia 3 388 150 2 119 0.625
73 Asia IQ Iraq 42 100 744 25 279 0.600
74 Asia KW Kuwait 4 401 998 2 556 0.581
75 Asia ID Indonesia 279 542 137 156 898 0.561
76 Asia PH Philippines 112 616 098 60 654 0.539
77 Asia KR South Korea 51 360 968 24 851 0.484
78 Asia TH Thailand 70 164 343 31 105 0.443
79 Asia KG Kyrgyzstan 6 748 187 2 991 0.443
80 Asia VN Vietnam 99 160 960 43 091 0.435
81 Africa MA Morocco 37 820 938 16 202 0.428
82 Australia/Oceania AU Australia 26 115 548 11 033 0.422
83 North America DO Dominican R. 11 074 270 4 383 0.396
84 Asia NP Nepal 30 227 344 11 954 0.396
85 Australia/Oceania NZ New Zealand 5 002 100 1 918 0.383
86 Asia TW Taiwan 23 906 450 9 026 0.378
87 Asia IN India 1 408 236 258 525 917 0.373
88 Africa ZW Zimbabwe 15 313 161 5 570 0.364
89 Asia MM Myanmar 55 168 730 19 434 0.352
90 Africa LS Lesotho 2 177 585 702 0.322
91 Asia SA Saudi Arabia 35 942 111 9 236 0.257
92 Asia JP Japan 125 671 231 31 860 0.254
93 Asia SG Singapore 5 946 078 1 488 0.250
94 Asia QA Qatar 2 807 805 680 0.242
95 Africa EG Egypt 106 350 908 24 750 0.233
96 Asia AE Arab Emirates 10 139 064 2 328 0.230
97 Africa ZM Zambia 19 455 353 4 013 0.206
98 South America VE Venezuela 28 268 374 5 753 0.203
99 Africa MR Mauritania 4 903 986 986 0.201
100 Asia AF Afghanistan 40 752 734 7 737 0.190
101 Asia KH Cambodia 17 200 455 3 056 0.178
102 Asia BD Bangladesh 168 103 522 29 259 0.174
103 Asia SY Syria 18 385 337 3 150 0.171
104 Africa DZ Algeria 45 498 823 6 875 0.151
105 Africa GM Gambia 2 557 951 368 0.144
106 Asia PK Pakistan 229 817 854 30 461 0.133
107 Africa MW Malawi 20 158 617 2 651 0.132
108 Africa GA Gabon 2 335 022 306 0.131
109 Africa SN Senegal 17 662 125 1 968 0.111
110 Africa SD Sudan 45 979 755 4 956 0.108
111 Africa RW Rwanda 13 620 347 1 466 0.108
112 Asia LA Laos 7 495 255 757 0.101
113 Africa KE Kenya 56 236 044 5 670 0.101
114 Africa GW Guinea-Bissau 2 064 793 173 0.084
115 Africa SO Somalia 16 815 935 1 361 0.081
116 Africa UG Uganda 48 747 095 3 626 0.074
117 North America HT Haiti 11 691 779 838 0.072
118 Australia/Oceania PG Papua New Guinea 9 299 707 662 0.071
119 Africa CM Cameroon 27 920 928 1 931 0.069
120 Asia YE Yemen 31 192 930 2 149 0.069
121 Africa MZ Mozambique 33 077 670 2 215 0.067
122 Africa CG Congo 5 800 725 386 0.067
123 Africa ET Ethiopia 120 889 430 7 564 0.063
124 Africa LR Liberia 5 305 052 294 0.055
125 Africa AO Angola 34 993 794 1 912 0.055
126 Africa MG Madagascar 29 172 400 1 406 0.048
127 Asia UZ Uzbekistan 34 478 582 1 637 0.048
128 Africa GH Ghana 32 422 677 1 456 0.045
129 North America NI Nicaragua 6 788 561 244 0.036
130 Africa ML Mali 21 464 627 737 0.034
131 Africa GN Guinea 13 874 077 445 0.032
132 Africa TG Togo 8 682 490 277 0.032
133 Africa CI Ivory Coast 27 737 554 808 0.029
134 Africa ER Eritrea 3 648 560 103 0.028
135 Africa CF Central African R. 5 004 512 113 0.023
136 Africa BF Burkina Faso 22 096 048 387 0.018
137 Africa SL Sierra Leone 8 314 553 125 0.015
138 Africa CD DR Congo 95 227 577 1 390 0.015
139 Africa NG Nigeria 216 771 563 3 146 0.015
140 Africa TZ Tanzania 63 274 840 841 0.013
141 Africa BJ Benin 12 783 983 163 0.013
142 Africa SS South Sudan 11 466 813 138 0.012
143 Africa NE Niger 26 030 170 311 0.012
144 Africa TD Chad 17 406 702 193 0.011
145 Asia PS Palestine 5 348 192 8 0.002
146 Africa BI Burundi 12 627 743 15 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 9 983 431 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"