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": 2021-10-18 11:50
(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 +1 897 (+2 242) +13 (+6)
CZ Czechia +791 (+1 157) +9 (+3)
DE Germany +0 (+6 807) +0 (+10)
HU Hungary +3 274 (+0) +51 (+0)
PL Poland +1 537 (+2 522) +3 (+1)
SK Slovakia, [gov], [okr]+553 (+1 735) +8 (+13)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Europe 756 220 922 1.82% 2.02% 1.87%
2 North America 594 646 145 2.41% 2.31% 1.18%
3 Australia/Oceania 43 446 846 0.48% 0.69% 0.56%
4 South America 438 601 336 1.53% 0.67% 0.26%
5 Asia 4 678 254 590 0.50% 0.33% 0.21%
6 Africa 1 381 348 008 0.24% 0.09% 0.04%

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 1 381 348 008 2.30% (3.70)% (0.09)%
2 South America 438 601 336 2.60% 2.66% 0.67%
3 North America 594 646 145 1.39% 2.07% 2.31%
4 Europe 756 220 922 1.24% 1.87% 2.02%
5 Asia 4 678 254 590 1.62% 1.60% 0.33%
6 Australia/Oceania 43 446 846 1.09% 1.42% 0.69%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 438 601 336 1 165 382 2.657
2 North America 594 646 145 1 088 394 1.830
3 Europe 756 220 922 1 257 787 1.663
4 Asia 4 678 254 590 1 142 132 0.244
5 Africa 1 381 348 008 215 519 0.156
6 Australia/Oceania 43 446 846 3 550 0.082

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 GE Georgia 3 979 263 7.45% 6.17% 8.43%
2 Europe LT Lithuania 2 673 113 3.24% 7.49% 7.57%
3 Europe RO Romania 19 071 633 1.90% 6.23% 6.85%
4 Europe RS Serbia 8 691 841 3.69% 8.41% 6.15%
5 Europe GB United Kingdom 68 346 945 5.47% 5.80% 5.22%
6 Asia MN Mongolia 3 346 429 7.12% 7.07% 4.74%
7 Asia SG Singapore 5 909 795 1.34% 4.44% 4.18%
8 Asia AM Armenia 2 970 404 1.86% 3.57% 3.85%
9 Europe BG Bulgaria 6 880 758 1.66% 3.17% 3.60%
10 Europe HR Croatia 4 072 510 1.64% 3.57% 3.34%
11 Europe SI Slovenia 2 079 308 2.33% 4.55% 3.19%
12 Asia TR Turkey 85 511 306 2.61% 3.74% 3.02%
13 Europe MD Moldova 4 021 836 1.43% 3.32% 2.95%
14 Europe UA Ukraine 43 393 799 0.90% 2.54% 2.78%
15 Europe IE Ireland 5 009 027 2.91% 3.06% 2.69%
16 North America CR Costa Rica 5 154 216 3.95% 4.17% 2.68%
17 Europe SK Slovakia 5 463 062 0.79% 2.36% 2.60%
18 Europe BE Belgium 11 654 825 1.65% 2.05% 2.03%
19 Europe GR Greece 10 357 184 2.56% 2.38% 2.01%
20 Europe BA Bosnia and Herzegovina 3 254 414 1.18% 2.49% 2.01%
21 North America CU Cuba 11 317 675 6.75% 5.18% 1.89%
22 Asia MY Malaysia 32 901 489 5.12% 3.75% 1.88%
23 Europe BY Belarus 9 445 303 1.67% 2.35% 1.83%
24 Europe RU Russia 146 015 385 1.81% 1.93% 1.82%
25 Europe AT Austria 9 072 817 1.35% 2.21% 1.79%
26 North America US USA 333 511 317 3.32% 3.33% 1.74%
27 Europe NL Netherlands 17 183 893 2.11% 1.38% 1.62%
28 Asia IL Israel 9 326 000 5.11% 4.12% 1.59%
29 Europe AL Albania 2 873 733 1.55% 2.20% 1.27%
30 Asia TH Thailand 70 026 431 2.22% 1.77% 1.26%
31 Asia IR Iran 85 381 207 3.14% 1.73% 1.26%
32 Europe HU Hungary 9 628 621 0.30% 0.80% 1.23%
33 Asia KZ Kazakhstan 19 066 765 2.77% 1.45% 1.21%
34 Europe MK North Macedonia 2 083 263 1.95% 1.97% 1.15%
35 Africa GA Gabon 2 293 440 0.37% 1.08% 1.15%
36 Europe FI Finland 5 551 850 1.00% 1.06% 1.09%
37 Asia AZ Azerbaijan 10 257 249 1.59% 1.16% 1.09%
38 Europe CZ Czechia 10 734 670 0.37% 0.78% 1.07%
39 Africa BW Botswana 2 412 873 4.88% 2.69% 1.01%
40 Europe DK Denmark 5 818 572 1.30% 0.90% 0.97%
41 Europe DE Germany 84 130 297 0.76% 1.08% 0.97%
42 Europe CH Switzerland 8 736 411 1.73% 1.54% 0.93%
43 Asia JO Jordan 10 333 984 0.90% 1.06% 0.86%
44 Africa LY Libya 6 991 935 2.27% 1.12% 0.80%
45 Australia/Oceania AU Australia 25 882 006 0.42% 0.87% 0.72%
46 Europe SE Sweden 10 180 653 0.75% 0.77% 0.71%
47 Asia PH Philippines 111 464 326 1.21% 1.37% 0.59%
48 North America CA Canada 38 169 704 0.69% 1.13% 0.56%
49 Asia LA Laos 7 411 857 0.39% 0.68% 0.55%
50 Europe PL Poland 37 792 999 0.15% 0.40% 0.55%
51 Europe NO Norway 5 476 017 1.20% 1.04% 0.53%
52 Europe PT Portugal 10 158 250 2.11% 0.71% 0.53%
53 Europe FR France 65 460 262 1.85% 0.77% 0.53%
54 North America DO Dominican R. 10 988 437 0.48% 0.52% 0.52%
55 North America GT Guatemala 18 343 156 1.67% 1.30% 0.51%
56 Asia LB Lebanon 6 785 901 1.31% 0.94% 0.51%
57 South America CL Chile 19 328 215 0.81% 0.44% 0.44%
58 North America JM Jamaica 2 977 875 1.25% 1.11% 0.43%
59 South America PR Puerto Rico 3 193 694 1.36% 0.73% 0.43%
60 North America HN Honduras 10 107 935 1.21% 0.70% 0.41%
61 South America VE Venezuela 28 331 718 0.46% 0.52% 0.39%
62 Asia IQ Iraq 41 386 318 1.81% 0.59% 0.35%
63 Europe IT Italy 60 346 834 0.76% 0.56% 0.34%
64 Europe ES Spain 46 778 197 2.61% 0.47% 0.31%
65 Australia/Oceania PG Papua New Guinea 9 165 677 0.08% 0.24% 0.31%
66 Asia VN Vietnam 98 470 111 0.86% 0.77% 0.30%
67 South America BR Brazil 214 512 005 1.77% 1.00% 0.29%
68 South America UY Uruguay 3 489 294 1.12% 0.37% 0.29%
69 North America PA Panama 4 402 439 1.76% 0.56% 0.28%
70 North America MX Mexico 130 682 551 0.97% 0.59% 0.27%
71 Asia LK Sri Lanka 21 529 312 1.35% 0.51% 0.26%
72 Asia KR South Korea 51 326 242 0.37% 0.44% 0.25%
73 Asia QA Qatar 2 807 805 0.61% 0.38% 0.23%
74 South America BO Bolivia 11 878 612 0.72% 0.30% 0.23%
75 South America CO Colombia 51 583 433 2.11% 0.32% 0.21%
76 Africa CG Congo 5 693 159 0.06% 0.13% 0.21%
77 Africa CM Cameroon 27 397 567 0.07% 0.19% 0.19%
78 South America PE Peru 33 564 863 0.49% 0.27% 0.18%
79 Asia MM Myanmar 54 881 187 0.61% 0.29% 0.17%
80 Asia PS Palestine 5 254 306 0.01% 0.03% 0.14%
81 Asia KH Cambodia 17 017 708 0.43% 0.31% 0.13%
82 Asia NP Nepal 29 813 008 0.62% 0.28% 0.12%
83 Asia SY Syria 18 048 673 0.07% 0.18% 0.12%
84 Africa NA Namibia 2 600 279 2.17% 0.26% 0.11%
85 North America NI Nicaragua 6 726 343 0.09% 0.11% 0.11%
86 Asia KG Kyrgyzstan 6 663 116 0.97% 0.13% 0.11%
87 South America AR Argentina 45 731 580 2.24% 0.30% 0.10%
88 Australia/Oceania NZ New Zealand 5 002 100 0.04% 0.07% 0.10%
89 Asia AE Arab Emirates 10 044 727 1.28% 0.26% 0.10%
90 Asia UZ Uzbekistan 34 095 416 0.22% 0.15% 0.09%
91 Africa TN Tunisia 11 978 363 2.75% 0.38% 0.09%
92 Africa ZA South Africa 60 274 322 1.83% 0.25% 0.09%
93 Asia IN India 1 397 531 610 0.30% 0.18% 0.08%
94 South America EC Ecuador 17 988 888 0.39% 0.15% 0.07%
95 Africa BI Burundi 12 346 893 0.12% 0.17% 0.07%
96 Africa MA Morocco 37 475 580 1.11% 0.29% 0.07%
97 South America PY Paraguay 7 245 683 0.79% 0.05% 0.07%
98 Asia KW Kuwait 4 352 104 1.72% 0.11% 0.06%
99 Africa MR Mauritania 4 807 152 0.34% 0.10% 0.06%
100 Africa EG Egypt 104 824 549 0.04% 0.08% 0.06%
101 Africa ZW Zimbabwe 15 142 246 0.60% 0.12% 0.05%
102 Africa AO Angola 34 182 726 0.07% 0.12% 0.05%
103 Africa ET Ethiopia 118 634 078 0.07% 0.09% 0.05%
104 North America HT Haiti 11 582 040 0.05% 0.05% 0.04%
105 Africa RW Rwanda 13 366 059 0.52% 0.12% 0.04%
106 Asia JP Japan 125 975 608 0.74% 0.14% 0.04%
107 Africa SO Somalia 16 464 469 0.04% 0.07% 0.04%
108 Asia PK Pakistan 226 425 487 0.14% 0.08% 0.03%
109 Africa BJ Benin 12 532 399 0.13% 0.10% 0.03%
110 Africa LS Lesotho 2 164 193 0.48% 1.31% 0.03%
111 Asia ID Indonesia 277 259 685 0.81% 0.06% 0.03%
112 Asia OM Oman 5 274 010 1.09% 0.06% 0.02%
113 Africa CF Central African R. 4 938 130 0.09% 0.01% 0.02%
114 Africa SD Sudan 45 169 194 0.01% 0.01% 0.02%
115 Asia BD Bangladesh 166 808 945 0.43% 0.06% 0.02%
116 Africa DZ Algeria 44 872 758 0.15% 0.03% 0.02%
117 Africa KE Kenya 55 298 632 0.13% 0.04% 0.02%
118 Africa TG Togo 8 528 871 0.14% 0.07% 0.02%
119 Africa BF Burkina Faso 21 641 770 0.01% 0.01% 0.02%
120 Africa UG Uganda 47 600 950 0.12% 0.03% 0.02%
121 Africa ER Eritrea 3 609 793 0.04% 0.01% 0.01%
122 Africa SS South Sudan 11 363 218 0.01% 0.02% 0.01%
123 Asia SA Saudi Arabia 35 513 709 0.21% 0.02% 0.01%
124 Africa GN Guinea 13 591 775 0.05% 0.01% 0.01%
125 Africa GH Ghana 31 909 486 0.11% 0.05% 0.01%
126 Asia AF Afghanistan 40 058 781 0.13% 0.01% 0.01%
127 Africa CI Ivory Coast 27 220 218 0.05% 0.03% 0.01%
128 Africa ML Mali 21 002 177 0.01% 0.01% 0.01%
129 Africa ZM Zambia 19 047 240 0.43% 0.02% 0.01%
130 Asia YE Yemen 30 673 035 0.01% 0.01% 0.01%
131 Africa NG Nigeria 212 725 060 0.02% 0.01% 0.01%
132 Asia HK Hong Kong 7 575 572 0.01% 0.01% 0.01%
133 Africa MZ Mozambique 32 383 549 0.24% 0.01% 0.01%
134 Africa GW Guinea-Bissau 2 027 965 0.11% 0.01% 0.01%
135 Africa GM Gambia 2 504 133 0.16% 0.01% 0.01%
136 Africa MW Malawi 19 767 002 0.14% 0.01% 0.00%
137 Asia TW Taiwan 23 872 514 0.01% 0.00% 0.00%
138 Africa CD DR Congo 93 067 881 0.02% 0.00% 0.00%
139 Africa LR Liberia 5 210 935 0.06% 0.01% 0.00%
140 Africa TZ Tanzania 61 925 991 0.04% 0.16% 0.00%
141 Africa TD Chad 17 033 018 0.00% 0.00% 0.00%
142 Africa NE Niger 25 334 047 0.00% 0.00% 0.00%
143 Africa SN Senegal 17 312 519 0.18% 0.01% 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 9 813 867 0.00% 0.00% 0.00%
147 North America SV El Salvador 6 528 508 0.47% 0.49% 0.00%
148 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
149 Africa SL Sierra Leone 8 186 221 0.02% 0.00% 0.00%
150 Africa MG Madagascar 28 608 455 0.01% 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 LR Liberia 5 210 935 5.50% (56.94)% (0.01)%
2 Africa SD Sudan 45 169 194 9.16% (16.69)% (0.01)%
3 Asia YE Yemen 30 673 035 17.60% (15.02)% (0.01)%
4 South America PY Paraguay 7 245 683 6.62% (8.33)% (0.05)%
5 Africa GW Guinea-Bissau 2 027 965 3.11% (7.28)% (0.01)%
6 Africa MW Malawi 19 767 002 4.13% (6.41)% (0.01)%
7 Asia SA Saudi Arabia 35 513 709 1.32% (6.07)% (0.02)%
8 Africa SN Senegal 17 312 519 2.23% (6.05)% (0.01)%
9 Africa GM Gambia 2 504 133 4.02% (6.00)% (0.01)%
10 Africa ER Eritrea 3 609 793 1.37% (5.81)% (0.01)%
11 South America EC Ecuador 17 988 888 15.10% 5.37% 0.15%
12 North America MX Mexico 130 682 551 4.11% 5.36% 0.59%
13 Africa BF Burkina Faso 21 641 770 3.47% (5.26)% (0.01)%
14 Africa SO Somalia 16 464 469 6.62% (5.01)% (0.07)%
15 Europe BA Bosnia and Herzegovina 3 254 414 4.27% 4.59% 2.49%
16 Africa EG Egypt 104 824 549 5.06% (4.49)% (0.08)%
17 Europe BG Bulgaria 6 880 758 4.13% 4.30% 3.17%
18 Africa ZA South Africa 60 274 322 2.55% 4.08% 0.25%
19 Asia ID Indonesia 277 259 685 3.81% (3.92)% (0.06)%
20 Europe MK North Macedonia 2 083 263 3.64% 3.92% 1.97%
21 North America SV El Salvador 6 528 508 3.48% 3.92% 0.49%
22 Africa DZ Algeria 44 872 758 3.13% (3.89)% (0.03)%
23 North America HT Haiti 11 582 040 4.41% (3.89)% (0.05)%
24 Africa NA Namibia 2 600 279 3.76% 3.81% 0.26%
25 Africa CI Ivory Coast 27 220 218 2.79% (3.76)% (0.03)%
26 Europe RU Russia 146 015 385 3.58% 3.64% 1.93%
27 Africa LS Lesotho 2 164 193 3.08% 3.57% 1.31%
28 Asia SY Syria 18 048 673 4.46% 3.53% 0.18%
29 South America PE Peru 33 564 863 5.30% 3.51% 0.27%
30 Africa ET Ethiopia 118 634 078 2.34% (3.28)% (0.09)%
31 Asia LK Sri Lanka 21 529 312 3.60% 3.24% 0.51%
32 South America AR Argentina 45 731 580 2.33% 3.14% 0.30%
33 Africa CG Congo 5 693 159 2.09% 3.13% 0.13%
34 Asia TW Taiwan 23 872 514 8.68% (3.11)% (0.00)%
35 Asia KH Cambodia 17 017 708 2.84% 3.05% 0.31%
36 North America HN Honduras 10 107 935 2.69% 3.04% 0.70%
37 Asia AF Afghanistan 40 058 781 4.75% (3.01)% (0.01)%
38 Africa KE Kenya 55 298 632 2.32% (2.99)% (0.04)%
39 Africa TZ Tanzania 61 925 991 2.76% 2.74% 0.16%
40 North America JM Jamaica 2 977 875 2.81% 2.56% 1.11%
41 Asia MM Myanmar 54 881 187 4.49% 2.54% 0.29%
42 Asia AM Armenia 2 970 404 2.52% 2.54% 3.57%
43 Africa AO Angola 34 182 726 3.22% 2.42% 0.12%
44 Europe RO Romania 19 071 633 3.18% 2.41% 6.23%
45 Africa TN Tunisia 11 978 363 3.24% 2.39% 0.38%
46 Europe UA Ukraine 43 393 799 2.54% 2.33% 2.54%
47 South America PR Puerto Rico 3 193 694 1.54% 2.25% 0.73%
48 South America CO Colombia 51 583 433 2.20% 2.14% 0.32%
49 South America BR Brazil 214 512 005 2.42% 2.05% 1.00%
50 Africa ML Mali 21 002 177 2.76% (2.02)% (0.01)%
51 Asia KG Kyrgyzstan 6 663 116 1.01% 2.00% 0.13%
52 South America BO Bolivia 11 878 612 2.79% 1.96% 0.30%
53 Asia KZ Kazakhstan 19 066 765 1.73% 1.95% 1.45%
54 Africa GN Guinea 13 591 775 3.05% 1.95% 0.01%
55 Europe PL Poland 37 792 999 2.71% 1.93% 0.40%
56 Asia PK Pakistan 226 425 487 1.97% 1.90% 0.08%
57 Europe HU Hungary 9 628 621 1.99% 1.89% 0.80%
58 Africa MA Morocco 37 475 580 1.27% 1.83% 0.29%
59 Europe MD Moldova 4 021 836 1.97% 1.81% 3.32%
60 Asia VN Vietnam 98 470 111 2.53% 1.75% 0.77%
61 Africa RW Rwanda 13 366 059 1.32% 1.71% 0.12%
62 North America GT Guatemala 18 343 156 1.83% 1.68% 1.30%
63 Africa CD DR Congo 93 067 881 1.00% 1.68% 0.00%
64 Africa ZW Zimbabwe 15 142 246 3.25% 1.67% 0.12%
65 Asia GE Georgia 3 979 263 1.52% 1.66% 6.17%
66 Asia BD Bangladesh 166 808 945 1.93% 1.66% 0.06%
67 Asia IR Iran 85 381 207 1.52% 1.64% 1.73%
68 Africa CM Cameroon 27 397 567 1.55% 1.63% 0.19%
69 Africa LY Libya 6 991 935 1.08% 1.61% 1.12%
70 Africa SS South Sudan 11 363 218 1.06% 1.58% 0.02%
71 Africa NG Nigeria 212 725 060 1.67% 1.53% 0.01%
72 Australia/Oceania PG Papua New Guinea 9 165 677 1.61% 1.51% 0.24%
73 Africa NE Niger 25 334 047 1.64% 1.48% 0.00%
74 North America CR Costa Rica 5 154 216 1.13% 1.45% 4.17%
75 Asia KW Kuwait 4 352 104 0.69% 1.44% 0.11%
76 South America CL Chile 19 328 215 3.21% 1.44% 0.44%
77 Europe GR Greece 10 357 184 1.06% 1.42% 2.38%
78 North America PA Panama 4 402 439 0.98% 1.41% 0.56%
79 Europe LT Lithuania 2 673 113 1.36% 1.34% 7.49%
80 Africa MR Mauritania 4 807 152 1.87% 1.34% 0.10%
81 Asia AZ Azerbaijan 10 257 249 1.13% 1.31% 1.16%
82 Asia MY Malaysia 32 901 489 1.39% 1.25% 3.75%
83 North America US USA 333 511 317 1.08% 1.23% 3.33%
84 Asia OM Oman 5 274 010 2.01% 1.22% 0.06%
85 Africa ZM Zambia 19 047 240 2.08% 1.21% 0.02%
86 Europe AL Albania 2 873 733 0.83% 1.21% 2.20%
87 Europe IT Italy 60 346 834 0.93% 1.21% 0.56%
88 Asia IQ Iraq 41 386 318 0.76% 1.21% 0.59%
89 Africa TG Togo 8 528 871 0.91% 1.16% 0.07%
90 Europe ES Spain 46 778 197 0.44% 1.13% 0.47%
91 Europe HR Croatia 4 072 510 1.20% 1.11% 3.57%
92 South America VE Venezuela 28 331 718 1.31% 1.10% 0.52%
93 Asia JP Japan 125 975 608 0.39% 1.10% 0.14%
94 Africa MZ Mozambique 32 383 549 1.36% 1.06% 0.01%
95 Asia LB Lebanon 6 785 901 0.67% 1.02% 0.94%
96 Asia JO Jordan 10 333 984 1.32% 0.97% 1.06%
97 Asia NP Nepal 29 813 008 1.32% 0.96% 0.28%
98 Asia IN India 1 397 531 610 1.44% 0.95% 0.18%
99 Europe SK Slovakia 5 463 062 0.94% 0.92% 2.36%
100 Europe PT Portugal 10 158 250 0.47% 0.85% 0.71%
101 North America CA Canada 38 169 704 0.91% 0.84% 1.13%
102 Asia TH Thailand 70 026 431 1.09% 0.83% 1.77%
103 Asia PH Philippines 111 464 326 1.23% 0.82% 1.37%
104 Africa GH Ghana 31 909 486 1.08% 0.79% 0.05%
105 Asia TR Turkey 85 511 306 0.85% 0.73% 3.74%
106 North America CU Cuba 11 317 675 0.90% 0.71% 5.18%
107 Asia UZ Uzbekistan 34 095 416 0.76% 0.69% 0.15%
108 Europe BY Belarus 9 445 303 0.87% 0.67% 2.35%
109 Europe DE Germany 84 130 297 0.69% 0.66% 1.08%
110 Europe FR France 65 460 262 0.42% 0.66% 0.77%
111 Europe RS Serbia 8 691 841 0.69% 0.65% 8.41%
112 Australia/Oceania AU Australia 25 882 006 0.61% 0.64% 0.87%
113 Asia MN Mongolia 3 346 429 0.42% 0.64% 7.07%
114 Africa GA Gabon 2 293 440 0.77% 0.63% 1.08%
115 South America UY Uruguay 3 489 294 1.52% 0.57% 0.37%
116 Africa MG Madagascar 28 608 455 3.73% 0.54% 0.01%
117 Europe SE Sweden 10 180 653 0.38% 0.53% 0.77%
118 Europe CZ Czechia 10 734 670 0.46% 0.51% 0.78%
119 Europe SI Slovenia 2 079 308 0.49% 0.50% 4.55%
120 Europe DK Denmark 5 818 572 0.20% 0.48% 0.90%
121 Asia AE Arab Emirates 10 044 727 0.26% 0.47% 0.26%
122 Europe AT Austria 9 072 817 0.38% 0.47% 2.21%
123 North America DO Dominican R. 10 988 437 0.57% 0.45% 0.52%
124 Europe BE Belgium 11 654 825 0.34% 0.40% 2.05%
125 Asia KR South Korea 51 326 242 0.34% 0.39% 0.44%
126 Europe GB United Kingdom 68 346 945 0.29% 0.34% 5.80%
127 Europe IE Ireland 5 009 027 0.23% 0.32% 3.06%
128 Asia IL Israel 9 326 000 0.33% 0.32% 4.12%
129 Europe CH Switzerland 8 736 411 0.25% 0.31% 1.54%
130 Asia SG Singapore 5 909 795 0.28% 0.28% 4.44%
131 Africa BW Botswana 2 412 873 1.22% 0.27% 2.69%
132 Africa UG Uganda 47 600 950 3.92% 0.25% 0.03%
133 Europe FI Finland 5 551 850 0.26% 0.25% 1.06%
134 Europe NL Netherlands 17 183 893 0.15% 0.23% 1.38%
135 North America NI Nicaragua 6 726 343 0.30% 0.20% 0.11%
136 Asia LA Laos 7 411 857 0.13% 0.19% 0.68%
137 Africa BJ Benin 12 532 399 0.36% 0.18% 0.10%
138 Europe NO Norway 5 476 017 0.14% 0.15% 1.04%
139 Australia/Oceania NZ New Zealand 5 002 100 0.10% 0.13% 0.07%
140 Asia QA Qatar 2 807 805 0.14% 0.09% 0.38%
141 Africa BI Burundi 12 346 893 0.04% 0.04% 0.17%
142 Africa CF Central African R. 4 938 130 0.05% 0.00% 0.01%
143 Asia HK Hong Kong 7 575 572 0.77% 0.00% 0.01%
144 Africa TD Chad 17 033 018 0.00% 0.00% 0.00%
145 Africa SL Sierra Leone 8 186 221 1.82% 0.00% 0.00%
146 Asia PS Palestine 5 254 306 0.00% 0.00% 0.03%
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 9 813 867 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 33 564 863 199 773 5.952
2 Europe BA Bosnia and Herzegovina 3 254 414 11 078 3.404
3 Europe MK North Macedonia 2 083 263 6 906 3.315
4 Europe BG Bulgaria 6 880 758 22 145 3.218
5 Europe HU Hungary 9 628 621 30 402 3.158
6 Europe CZ Czechia 10 734 670 30 537 2.845
7 South America BR Brazil 214 512 005 601 699 2.805
8 South America AR Argentina 45 731 580 115 585 2.527
9 South America CO Colombia 51 583 433 126 761 2.457
10 Europe SI Slovenia 2 079 308 4 966 2.388
11 Asia GE Georgia 3 979 263 9 438 2.372
12 Europe SK Slovakia 5 463 062 12 824 2.347
13 South America PY Paraguay 7 245 683 16 208 2.237
14 Europe BE Belgium 11 654 825 25 732 2.208
15 Europe HR Croatia 4 072 510 8 881 2.181
16 Europe IT Italy 60 346 834 131 485 2.179
17 Europe RO Romania 19 071 633 41 428 2.172
18 North America MX Mexico 130 682 551 283 253 2.167
19 North America US USA 333 511 317 715 340 2.145
20 Africa TN Tunisia 11 978 363 25 066 2.093
21 Europe GB United Kingdom 68 346 945 138 294 2.023
22 Europe LT Lithuania 2 673 113 5 390 2.016
23 Europe PL Poland 37 792 999 76 070 2.013
24 South America CL Chile 19 328 215 37 595 1.945
25 Asia AM Armenia 2 970 404 5 740 1.932
26 Europe ES Spain 46 778 197 86 917 1.858
27 South America EC Ecuador 17 988 888 32 848 1.826
28 Europe MD Moldova 4 021 836 7 172 1.783
29 Europe PT Portugal 10 158 250 18 080 1.780
30 Europe FR France 65 460 262 114 875 1.755
31 South America UY Uruguay 3 489 294 6 067 1.739
32 North America PA Panama 4 402 439 7 275 1.653
33 South America BO Bolivia 11 878 612 18 813 1.584
34 Europe RU Russia 146 015 385 222 311 1.522
35 Europe GR Greece 10 357 184 15 316 1.479
36 Africa ZA South Africa 60 274 322 88 531 1.469
37 Europe SE Sweden 10 180 653 14 926 1.466
38 Asia IR Iran 85 381 207 123 697 1.449
39 Europe UA Ukraine 43 393 799 60 314 1.390
40 Africa NA Namibia 2 600 279 3 534 1.359
41 North America CR Costa Rica 5 154 216 6 744 1.308
42 Asia LB Lebanon 6 785 901 8 406 1.239
43 Europe CH Switzerland 8 736 411 10 726 1.228
44 Europe AT Austria 9 072 817 10 916 1.203
45 Europe DE Germany 84 130 297 94 536 1.124
46 Europe NL Netherlands 17 183 893 18 237 1.061
47 Europe IE Ireland 5 009 027 5 306 1.059
48 Asia JO Jordan 10 333 984 10 855 1.050
49 Europe RS Serbia 8 691 841 8 999 1.035
50 South America PR Puerto Rico 3 193 694 3 201 1.002
51 North America HN Honduras 10 107 935 10 065 0.996
52 Africa BW Botswana 2 412 873 2 386 0.989
53 Europe AL Albania 2 873 733 2 807 0.977
54 Asia KZ Kazakhstan 19 066 765 16 618 0.872
55 Asia IL Israel 9 326 000 7 999 0.858
56 Asia MY Malaysia 32 901 489 27 744 0.843
57 Asia TR Turkey 85 511 306 67 230 0.786
58 Asia OM Oman 5 274 010 4 104 0.778
59 North America GT Guatemala 18 343 156 14 271 0.778
60 North America CA Canada 38 169 704 28 378 0.744
61 North America CU Cuba 11 317 675 8 015 0.708
62 Africa LY Libya 6 991 935 4 872 0.697
63 North America JM Jamaica 2 977 875 2 066 0.694
64 Asia AZ Azerbaijan 10 257 249 6 739 0.657
65 Asia LK Sri Lanka 21 529 312 13 441 0.624
66 Asia KW Kuwait 4 352 104 2 456 0.564
67 Asia IQ Iraq 41 386 318 22 699 0.548
68 North America SV El Salvador 6 528 508 3 452 0.529
69 Asia ID Indonesia 277 259 685 142 867 0.515
70 Europe BY Belarus 9 445 303 4 369 0.463
71 Europe DK Denmark 5 818 572 2 681 0.461
72 Asia MN Mongolia 3 346 429 1 454 0.434
73 Asia KG Kyrgyzstan 6 663 116 2 631 0.395
74 Africa MA Morocco 37 475 580 14 507 0.387
75 Asia NP Nepal 29 813 008 11 283 0.379
76 North America DO Dominican R. 10 988 437 4 085 0.372
77 Asia PH Philippines 111 464 326 40 307 0.362
78 Asia MM Myanmar 54 881 187 18 285 0.333
79 Asia IN India 1 397 531 610 451 814 0.323
80 Africa ZW Zimbabwe 15 142 246 4 656 0.307
81 Africa LS Lesotho 2 164 193 655 0.303
82 Asia TH Thailand 70 026 431 18 186 0.260
83 Asia SA Saudi Arabia 35 513 709 8 758 0.247
84 Asia QA Qatar 2 807 805 607 0.216
85 Asia VN Vietnam 98 470 111 21 013 0.213
86 Asia AE Arab Emirates 10 044 727 2 119 0.211
87 Europe FI Finland 5 551 850 1 113 0.201
88 Africa ZM Zambia 19 047 240 3 657 0.192
89 Asia AF Afghanistan 40 058 781 7 241 0.181
90 Africa EG Egypt 104 824 549 17 850 0.170
91 Asia BD Bangladesh 166 808 945 27 753 0.166
92 South America VE Venezuela 28 331 718 4 679 0.165
93 Africa MR Mauritania 4 807 152 786 0.164
94 Europe NO Norway 5 476 017 884 0.161
95 Asia KH Cambodia 17 017 708 2 596 0.152
96 Asia JP Japan 125 975 608 18 062 0.143
97 Africa GM Gambia 2 504 133 339 0.135
98 Asia SY Syria 18 048 673 2 383 0.132
99 Africa DZ Algeria 44 872 758 5 866 0.131
100 Asia PK Pakistan 226 425 487 28 212 0.125
101 Africa MW Malawi 19 767 002 2 292 0.116
102 Africa SN Senegal 17 312 519 1 869 0.108
103 Africa RW Rwanda 13 366 059 1 313 0.098
104 Africa KE Kenya 55 298 632 5 210 0.094
105 Africa GA Gabon 2 293 440 209 0.091
106 Africa SO Somalia 16 464 469 1 180 0.072
107 Africa GW Guinea-Bissau 2 027 965 141 0.070
108 Africa UG Uganda 47 600 950 3 183 0.067
109 Africa SD Sudan 45 169 194 2 976 0.066
110 Africa MZ Mozambique 32 383 549 1 925 0.059
111 Asia YE Yemen 30 673 035 1 795 0.059
112 Australia/Oceania AU Australia 25 882 006 1 507 0.058
113 Africa CM Cameroon 27 397 567 1 550 0.057
114 North America HT Haiti 11 582 040 649 0.056
115 Africa LR Liberia 5 210 935 286 0.055
116 Africa ET Ethiopia 118 634 078 6 161 0.052
117 Asia KR South Korea 51 326 242 2 634 0.051
118 Africa AO Angola 34 182 726 1 655 0.048
119 Africa CG Congo 5 693 159 222 0.039
120 Asia UZ Uzbekistan 34 095 416 1 286 0.038
121 Asia SG Singapore 5 909 795 216 0.036
122 Africa GH Ghana 31 909 486 1 160 0.036
123 Asia TW Taiwan 23 872 514 846 0.035
124 Africa MG Madagascar 28 608 455 960 0.034
125 North America NI Nicaragua 6 726 343 206 0.031
126 Australia/Oceania PG Papua New Guinea 9 165 677 266 0.029
127 Africa GN Guinea 13 591 775 385 0.028
128 Asia HK Hong Kong 7 575 572 213 0.028
129 Africa TG Togo 8 528 871 238 0.028
130 Africa ML Mali 21 002 177 555 0.026
131 Africa CI Ivory Coast 27 220 218 674 0.025
132 Africa CF Central African R. 4 938 130 100 0.020
133 Africa SL Sierra Leone 8 186 221 121 0.015
134 Africa NG Nigeria 212 725 060 2 794 0.013
135 Africa BJ Benin 12 532 399 161 0.013
136 Africa ER Eritrea 3 609 793 45 0.013
137 Africa TZ Tanzania 61 925 991 724 0.012
138 Africa CD DR Congo 93 067 881 1 089 0.012
139 Africa SS South Sudan 11 363 218 130 0.011
140 Africa TD Chad 17 033 018 174 0.010
141 Africa BF Burkina Faso 21 641 770 203 0.009
142 Africa NE Niger 25 334 047 204 0.008
143 Australia/Oceania NZ New Zealand 5 002 100 28 0.006
144 Asia LA Laos 7 411 857 38 0.005
145 Asia PS Palestine 5 254 306 9 0.002
146 Africa BI Burundi 12 346 893 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 9 813 867 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.

* 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"