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": 2021-06-12 21:11
(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 +200 (+216) +0 (+2)
CZ Czechia +180 (+189) +1 (+5)
DE Germany +679 (+2 194) +31 (+115)
HU Hungary +0 (+199) +0 (+8)
PL Poland +239 (+338) +47 (+68)
SK Slovakia, [gov], [okr]+91 (+84) +3 (+0)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 South America 437 359 128 3.08% 3.62% 2.98%
2 Europe 756 064 321 2.01% 0.84% 0.53%
3 North America 593 032 781 1.29% 0.68% 0.41%
4 Asia 4 666 498 454 0.62% 0.67% 0.35%
5 Africa 1 370 091 267 0.09% 0.10% 0.11%
6 Australia/Oceania 43 270 874 0.05% 0.05% 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 North America 593 032 781 2.29% 3.49% 0.68%
2 Africa 1 370 091 267 2.84% (3.48)% (0.10)%
3 South America 437 359 128 3.23% 3.38% 3.62%
4 Europe 756 064 321 2.01% 2.92% 0.84%
5 Asia 4 666 498 454 1.21% 2.07% 0.67%
6 Australia/Oceania 43 270 874 0.94% (0.89)% (0.05)%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 437 359 128 931 035 2.129
2 North America 593 032 781 884 083 1.491
3 Europe 756 064 321 1 083 973 1.434
4 Asia 4 666 498 454 722 534 0.155
5 Africa 1 370 091 267 134 137 0.098
6 Australia/Oceania 43 270 874 1 392 0.032

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 South America UY Uruguay 3 485 094 8.02% 11.54% 10.83%
2 South America AR Argentina 45 586 681 4.46% 7.41% 5.69%
3 South America CO Colombia 51 393 873 2.86% 4.74% 5.11%
4 Asia MN Mongolia 3 327 951 2.06% 2.93% 4.24%
5 South America PY Paraguay 7 215 047 3.34% 4.42% 4.07%
6 South America CL Chile 19 270 893 3.58% 4.00% 3.74%
7 Asia KW Kuwait 4 330 005 3.42% 3.24% 3.46%
8 North America CR Costa Rica 5 137 964 2.67% 4.82% 3.30%
9 Asia OM Oman 5 228 445 1.77% 2.02% 2.97%
10 Africa NA Namibia 2 584 165 1.02% 1.74% 2.78%
11 South America BR Brazil 213 984 390 3.49% 3.44% 2.56%
12 South America BO Bolivia 11 822 915 1.38% 2.49% 2.29%
13 Africa BW Botswana 2 396 237 1.51% 1.94% 2.24%
14 Asia AE Arab Emirates 10 002 945 2.52% 2.04% 2.15%
15 Asia MY Malaysia 32 756 466 1.17% 2.28% 1.91%
16 Asia GE Georgia 3 981 930 2.21% 2.64% 1.79%
17 North America PA Panama 4 378 667 1.26% 1.49% 1.74%
18 Africa TN Tunisia 11 935 141 1.19% 1.29% 1.46%
19 Asia LK Sri Lanka 21 497 986 0.66% 1.55% 1.31%
20 Asia NP Nepal 29 629 496 1.11% 2.41% 1.14%
21 South America PE Peru 33 404 191 2.36% 1.59% 1.13%
22 North America DO Dominican R. 10 950 421 0.72% 1.17% 1.12%
23 North America CU Cuba 11 320 084 1.04% 1.22% 1.07%
24 Europe DK Denmark 5 811 456 1.49% 1.82% 1.07%
25 Europe SE Sweden 10 158 668 4.78% 2.48% 1.03%
26 Africa ZA South Africa 60 012 828 0.39% 0.79% 1.00%
27 Asia IQ Iraq 41 069 893 1.47% 1.11% 0.97%
28 Europe NL Netherlands 17 170 672 3.80% 2.13% 0.96%
29 Europe GB United Kingdom 68 222 484 0.78% 0.60% 0.94%
30 Asia IR Iran 85 005 237 1.77% 1.37% 0.88%
31 Europe SI Slovenia 2 079 208 3.80% 1.65% 0.87%
32 Europe GR Greece 10 374 902 2.35% 1.68% 0.87%
33 Europe BY Belarus 9 446 386 1.47% 1.33% 0.85%
34 Europe RU Russia 145 993 575 0.78% 0.73% 0.75%
35 Asia TR Turkey 85 194 096 3.23% 1.13% 0.73%
36 Europe LT Lithuania 2 686 296 3.21% 2.24% 0.71%
37 Africa ZM Zambia 18 866 484 0.21% 0.29% 0.70%
38 Asia KG Kyrgyzstan 6 625 437 0.36% 0.58% 0.69%
39 Europe FR France 65 409 895 3.52% 1.47% 0.68%
40 Asia IN India 1 392 790 451 1.32% 1.59% 0.68%
41 Europe ES Spain 46 771 885 1.50% 1.04% 0.67%
42 Europe PT Portugal 10 168 602 0.76% 0.58% 0.65%
43 North America HN Honduras 10 052 801 0.86% 0.88% 0.65%
44 Asia QA Qatar 2 807 805 2.26% 1.02% 0.62%
45 Asia KZ Kazakhstan 18 988 238 1.09% 1.10% 0.61%
46 Asia PH Philippines 110 954 199 0.68% 0.63% 0.60%
47 Europe BE Belgium 11 637 225 2.90% 1.59% 0.54%
48 North America GT Guatemala 18 227 090 0.55% 0.61% 0.54%
49 Europe IE Ireland 4 989 746 1.17% 0.90% 0.53%
50 South America VE Venezuela 28 359 773 0.40% 0.51% 0.50%
51 Asia JO Jordan 10 298 587 3.88% 0.76% 0.50%
52 South America EC Ecuador 17 895 139 0.96% 0.68% 0.40%
53 Europe NO Norway 5 461 212 1.13% 0.73% 0.40%
54 Asia AF Afghanistan 39 751 424 0.08% 0.24% 0.39%
55 Asia TH Thailand 69 965 349 0.24% 0.55% 0.39%
56 North America US USA 332 833 770 1.78% 0.74% 0.39%
57 North America CA Canada 38 054 099 1.53% 1.01% 0.39%
58 Africa LY Libya 6 959 252 0.89% 0.44% 0.39%
59 Asia KH Cambodia 16 936 769 0.21% 0.37% 0.39%
60 Europe CH Switzerland 8 714 309 1.81% 0.94% 0.34%
61 Europe IT Italy 60 377 804 2.58% 0.72% 0.33%
62 Asia SA Saudi Arabia 35 323 967 0.26% 0.37% 0.33%
63 Europe AT Austria 9 054 880 2.41% 0.62% 0.33%
64 Europe HR Croatia 4 081 316 2.97% 0.98% 0.33%
65 Europe UA Ukraine 43 485 203 2.20% 0.78% 0.30%
66 Asia ID Indonesia 276 248 772 0.25% 0.23% 0.25%
67 Europe DE Germany 84 036 849 1.65% 0.69% 0.24%
68 Europe CZ Czechia 10 727 742 5.51% 0.55% 0.23%
69 Asia AM Armenia 2 968 473 1.84% 0.45% 0.23%
70 Asia LB Lebanon 6 796 539 3.10% 0.46% 0.23%
71 Africa UG Uganda 47 093 315 0.04% 0.13% 0.23%
72 North America SV El Salvador 6 517 087 0.28% 0.28% 0.22%
73 South America PR Puerto Rico 3 193 694 1.34% 0.45% 0.20%
74 Europe BG Bulgaria 6 898 946 2.78% 0.42% 0.19%
75 North America MX Mexico 130 209 100 0.37% 0.22% 0.19%
76 Europe RS Serbia 8 704 091 3.43% 0.50% 0.19%
77 North America JM Jamaica 2 973 365 1.04% 0.30% 0.19%
78 Europe FI Finland 5 548 849 0.80% 0.31% 0.18%
79 Europe SK Slovakia 5 462 140 2.19% 0.30% 0.18%
80 Africa ER Eritrea 3 592 624 0.07% 0.11% 0.16%
81 Asia JP Japan 126 110 418 0.28% 0.35% 0.16%
82 Asia TW Taiwan 23 857 483 0.05% 0.19% 0.13%
83 Europe HU Hungary 9 637 163 4.39% 0.47% 0.13%
84 Europe BA Bosnia and Herzegovina 3 261 513 2.44% 0.34% 0.13%
85 Asia BD Bangladesh 166 235 568 0.17% 0.10% 0.12%
86 Africa GA Gabon 2 275 023 0.55% 0.18% 0.11%
87 Asia KR South Korea 51 310 862 0.12% 0.13% 0.11%
88 North America HT Haiti 11 533 436 0.04% 0.10% 0.10%
89 Europe MD Moldova 4 025 101 2.19% 0.25% 0.10%
90 Africa MA Morocco 37 322 618 0.12% 0.09% 0.10%
91 Europe PL Poland 37 807 440 3.44% 0.33% 0.09%
92 Europe MK North Macedonia 2 083 293 2.85% 0.21% 0.09%
93 Africa DZ Algeria 44 595 470 0.05% 0.07% 0.08%
94 Africa MR Mauritania 4 764 263 0.07% 0.10% 0.08%
95 Africa LR Liberia 5 169 249 0.01% 0.03% 0.08%
96 Africa EG Egypt 104 148 514 0.10% 0.12% 0.08%
97 Europe RO Romania 19 116 269 1.70% 0.22% 0.08%
98 Asia UZ Uzbekistan 33 925 709 0.07% 0.08% 0.08%
99 Asia AZ Azerbaijan 10 225 321 1.01% 0.27% 0.07%
100 Australia/Oceania PG Papua New Guinea 9 106 314 0.17% 0.16% 0.07%
101 Africa CM Cameroon 27 165 767 0.18% 0.05% 0.07%
102 Asia PK Pakistan 224 922 985 0.17% 0.12% 0.07%
103 Africa KE Kenya 54 883 446 0.13% 0.07% 0.07%
104 Africa RW Rwanda 13 253 433 0.08% 0.05% 0.06%
105 Africa ZW Zimbabwe 15 066 546 0.03% 0.03% 0.05%
106 Africa AO Angola 33 823 498 0.05% 0.08% 0.05%
107 North America NI Nicaragua 6 698 786 0.02% 0.03% 0.03%
108 Europe AL Albania 2 874 828 1.48% 0.08% 0.03%
109 Africa CD DR Congo 92 111 338 0.01% 0.02% 0.03%
110 Asia VN Vietnam 98 164 129 0.01% 0.03% 0.03%
111 Africa SN Senegal 17 157 677 0.07% 0.03% 0.03%
112 Asia SG Singapore 5 893 725 0.04% 0.06% 0.02%
113 Africa SL Sierra Leone 8 129 382 0.01% 0.01% 0.02%
114 Africa CG Congo 5 645 517 0.06% 0.04% 0.02%
115 Asia MM Myanmar 54 753 832 0.01% 0.01% 0.02%
116 Asia IL Israel 9 326 000 1.34% 0.03% 0.02%
117 Africa MG Madagascar 28 358 680 0.08% 0.03% 0.02%
118 Africa MZ Mozambique 32 076 119 0.07% 0.01% 0.02%
119 Africa ET Ethiopia 117 635 168 0.11% 0.03% 0.01%
120 Africa BI Burundi 12 222 502 0.03% 0.02% 0.01%
121 Africa GH Ghana 31 682 190 0.07% 0.02% 0.01%
122 Africa TG Togo 8 460 832 0.09% 0.02% 0.01%
123 Asia SY Syria 17 899 562 0.06% 0.03% 0.01%
124 Africa GN Guinea 13 466 742 0.06% 0.02% 0.01%
125 Africa SD Sudan 44 810 191 0.01% 0.01% 0.01%
126 Africa SO Somalia 16 308 802 0.06% 0.01% 0.01%
127 Africa CI Ivory Coast 26 991 087 0.06% 0.02% 0.01%
128 Africa GM Gambia 2 480 296 0.07% 0.01% 0.01%
129 Australia/Oceania NZ New Zealand 5 002 100 0.01% 0.00% 0.01%
130 Africa MW Malawi 19 593 554 0.03% 0.01% 0.01%
131 Africa GW Guinea-Bissau 2 011 654 0.05% 0.01% 0.01%
132 Asia LA Laos 7 374 920 0.03% 0.03% 0.01%
133 Australia/Oceania AU Australia 25 778 568 0.01% 0.00% 0.01%
134 Asia HK Hong Kong 7 554 327 0.02% 0.00% 0.01%
135 Asia YE Yemen 30 442 770 0.02% 0.00% 0.00%
136 Africa LS Lesotho 2 158 261 0.05% 0.01% 0.00%
137 Africa NG Nigeria 210 932 837 0.01% 0.00% 0.00%
138 Africa CF Central African R. 4 908 729 0.04% 0.03% 0.00%
139 Africa ML Mali 20 797 354 0.03% 0.00% 0.00%
140 Africa BJ Benin 12 420 971 0.03% 0.00% 0.00%
141 Africa BF Burkina Faso 21 440 567 0.01% 0.00% 0.00%
142 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
143 Africa TZ Tanzania 61 328 577 0.00% 0.00% 0.00%
144 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
145 Asia TJ Tajikistan 9 738 767 0.00% 0.00% 0.00%
146 Africa TD Chad 16 867 510 0.01% 0.00% 0.00%
147 Africa NE Niger 25 025 730 0.00% 0.00% 0.00%
148 Africa SS South Sudan 11 317 335 0.05% 0.00% 0.00%
149 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
150 Asia PS Palestine 5 212 723 0.00% 0.00% 0.00%

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

Filtered where Population more then 2 million, [All Countries] | Compare with [DEATHS]! and with [FATALITY RATE]
N.RegionCDCountryPopulationMortality last
120 days
Mortality last
30 days
New positive cases
last 30 days
1 Africa SD Sudan 44 810 191 13.73% (20.16)% (0.01)%
2 Asia YE Yemen 30 442 770 15.60% (18.03)% (0.00)%
3 Europe MK North Macedonia 2 083 293 4.07% 14.14% 0.21%
4 North America MX Mexico 130 209 100 11.02% 13.57% 0.22%
5 Europe RO Romania 19 116 269 3.58% 12.20% 0.22%
6 Europe BA Bosnia and Herzegovina 3 261 513 5.67% 11.99% 0.34%
7 South America PE Peru 33 404 191 9.53% 8.58% 1.59%
8 Asia SY Syria 17 899 562 8.07% (8.48)% (0.03)%
9 Africa LS Lesotho 2 158 261 6.10% (6.82)% (0.01)%
10 North America JM Jamaica 2 973 365 1.94% 6.62% 0.30%
11 Europe BG Bulgaria 6 898 946 4.22% 6.32% 0.42%
12 Europe PL Poland 37 807 440 2.55% 6.15% 0.33%
13 Africa ZW Zimbabwe 15 066 546 4.89% (5.84)% (0.03)%
14 Africa LR Liberia 5 169 249 2.94% (5.80)% (0.03)%
15 Africa ML Mali 20 797 354 2.97% (5.54)% (0.00)%
16 Africa GM Gambia 2 480 296 2.42% (5.32)% (0.01)%
17 Europe SK Slovakia 5 462 140 5.10% 5.30% 0.30%
18 Europe MD Moldova 4 025 101 2.74% 4.66% 0.25%
19 Europe HU Hungary 9 637 163 3.76% 4.63% 0.47%
20 Africa BF Burkina Faso 21 440 567 1.30% (4.50)% (0.00)%
21 Africa TN Tunisia 11 935 141 4.24% 4.50% 1.29%
22 Asia IL Israel 9 326 000 0.70% (4.40)% (0.03)%
23 South America EC Ecuador 17 895 139 3.26% 4.25% 0.68%
24 Africa EG Egypt 104 148 514 5.75% 4.24% 0.12%
25 Europe RU Russia 145 993 575 3.93% 4.18% 0.73%
26 Africa GW Guinea-Bissau 2 011 654 2.10% (4.08)% (0.01)%
27 Asia TW Taiwan 23 857 483 4.01% 4.08% 0.19%
28 Asia AF Afghanistan 39 751 424 4.32% 4.07% 0.24%
29 Africa MG Madagascar 28 358 680 2.63% (4.06)% (0.03)%
30 Africa KE Kenya 54 883 446 2.22% (3.92)% (0.07)%
31 Asia AM Armenia 2 968 473 2.42% 3.88% 0.45%
32 South America PY Paraguay 7 215 047 3.23% 3.86% 4.42%
33 Europe UA Ukraine 43 485 203 2.81% 3.64% 0.78%
34 Africa NG Nigeria 210 932 837 1.33% (3.50)% (0.00)%
35 Africa SO Somalia 16 308 802 6.46% (3.48)% (0.01)%
36 North America HT Haiti 11 533 436 2.64% (3.39)% (0.10)%
37 North America HN Honduras 10 052 801 3.09% 3.16% 0.88%
38 Asia ID Indonesia 276 248 772 2.77% 3.10% 0.23%
39 Africa NA Namibia 2 584 165 2.48% 3.07% 1.74%
40 Europe AL Albania 2 874 828 1.86% (3.04)% (0.08)%
41 Africa SL Sierra Leone 8 129 382 0.68% (3.00)% (0.01)%
42 Europe HR Croatia 4 081 316 2.31% 2.99% 0.98%
43 Africa DZ Algeria 44 595 470 2.83% (2.85)% (0.07)%
44 South America BO Bolivia 11 822 915 2.71% 2.81% 2.49%
45 Africa TD Chad 16 867 510 3.20% (2.80)% (0.00)%
46 Africa SN Senegal 17 157 677 3.08% (2.80)% (0.03)%
47 North America SV El Salvador 6 517 087 3.08% 2.78% 0.28%
48 South America BR Brazil 213 984 390 3.27% 2.75% 3.44%
49 Asia PK Pakistan 224 922 985 2.47% 2.65% 0.12%
50 South America PR Puerto Rico 3 193 694 1.43% 2.62% 0.45%
51 South America CO Colombia 51 393 873 2.70% 2.59% 4.74%
52 Africa ZA South Africa 60 012 828 4.61% 2.58% 0.79%
53 Africa ET Ethiopia 117 635 168 1.55% (2.34)% (0.03)%
54 Asia BD Bangladesh 166 235 568 1.75% 2.33% 0.10%
55 Africa MW Malawi 19 593 554 2.88% (2.19)% (0.01)%
56 Africa AO Angola 33 823 498 2.14% (2.19)% (0.08)%
57 Asia LB Lebanon 6 796 539 1.71% 2.14% 0.46%
58 Asia AZ Azerbaijan 10 225 321 1.72% 2.09% 0.27%
59 Europe IT Italy 60 377 804 2.09% 2.08% 0.72%
60 Europe GR Greece 10 374 902 2.56% 2.07% 1.68%
61 Asia GE Georgia 3 981 930 1.92% 2.07% 2.64%
62 Asia KG Kyrgyzstan 6 625 437 2.00% 2.06% 0.58%
63 Africa CD DR Congo 92 111 338 1.49% (2.03)% (0.02)%
64 Africa CM Cameroon 27 165 767 1.72% (2.01)% (0.05)%
65 Asia PH Philippines 110 954 199 1.50% 1.99% 0.63%
66 North America US USA 332 833 770 1.77% 1.95% 0.74%
67 Asia JP Japan 126 110 418 1.99% 1.94% 0.35%
68 Europe RS Serbia 8 704 091 0.89% 1.90% 0.50%
69 North America GT Guatemala 18 227 090 2.38% 1.90% 0.61%
70 Asia MM Myanmar 54 753 832 1.67% 1.85% 0.01%
71 South America AR Argentina 45 586 681 1.74% 1.80% 7.41%
72 Asia NP Nepal 29 629 496 2.00% 1.80% 2.41%
73 Africa GN Guinea 13 466 742 0.94% 1.78% 0.02%
74 Europe DE Germany 84 036 849 1.77% 1.76% 0.69%
75 Asia JO Jordan 10 298 587 1.26% 1.75% 0.76%
76 Europe CZ Czechia 10 727 742 1.92% 1.74% 0.55%
77 South America UY Uruguay 3 485 094 1.64% 1.63% 11.54%
78 Asia IR Iran 85 005 237 1.52% 1.57% 1.37%
79 South America CL Chile 19 270 893 1.64% 1.52% 4.00%
80 Africa RW Rwanda 13 253 433 1.21% 1.49% 0.05%
81 Asia TR Turkey 85 194 096 0.77% 1.46% 1.13%
82 Africa MZ Mozambique 32 076 119 1.19% 1.45% 0.01%
83 Africa BW Botswana 2 396 237 1.95% 1.39% 1.94%
84 Asia OM Oman 5 228 445 1.07% 1.37% 2.02%
85 Asia IN India 1 392 790 451 1.14% 1.34% 1.59%
86 Africa MA Morocco 37 322 618 1.60% 1.32% 0.09%
87 Asia LK Sri Lanka 21 497 986 1.16% 1.27% 1.55%
88 Africa ZM Zambia 18 866 484 1.08% 1.26% 0.29%
89 Asia SA Saudi Arabia 35 323 967 1.28% 1.23% 0.37%
90 South America VE Venezuela 28 359 773 1.38% 1.23% 0.51%
91 North America CR Costa Rica 5 137 964 1.21% 1.21% 4.82%
92 Europe LT Lithuania 2 686 296 1.45% 1.17% 2.24%
93 Africa CI Ivory Coast 26 991 087 0.74% 1.16% 0.02%
94 Africa MR Mauritania 4 764 263 1.49% 1.16% 0.10%
95 North America NI Nicaragua 6 698 786 1.84% 1.11% 0.03%
96 Europe AT Austria 9 054 880 1.04% 1.09% 0.62%
97 Asia MY Malaysia 32 756 466 0.74% 1.08% 2.28%
98 Europe FR France 65 409 895 1.21% 1.02% 1.47%
99 Asia KH Cambodia 16 936 769 0.91% 1.01% 0.37%
100 Africa GA Gabon 2 275 023 0.63% 0.94% 0.18%
101 North America PA Panama 4 378 667 1.52% 0.92% 1.49%
102 Africa LY Libya 6 959 252 1.76% 0.91% 0.44%
103 Asia TH Thailand 69 965 349 0.87% 0.90% 0.55%
104 Africa CF Central African R. 4 908 729 1.67% 0.88% 0.03%
105 Africa CG Congo 5 645 517 0.83% 0.84% 0.04%
106 Europe BY Belarus 9 446 386 0.78% 0.84% 1.33%
107 North America CU Cuba 11 320 084 0.69% 0.82% 1.22%
108 Africa UG Uganda 47 093 315 0.79% 0.80% 0.13%
109 North America CA Canada 38 054 099 0.80% 0.80% 1.01%
110 Asia KZ Kazakhstan 18 988 238 2.06% 0.79% 1.10%
111 Asia MN Mongolia 3 327 951 0.55% 0.71% 2.93%
112 Australia/Oceania PG Papua New Guinea 9 106 314 1.01% 0.69% 0.16%
113 Europe BE Belgium 11 637 225 0.96% 0.69% 1.59%
114 Europe FI Finland 5 548 849 0.55% 0.67% 0.31%
115 Asia IQ Iraq 41 069 893 0.59% 0.62% 1.11%
116 Asia QA Qatar 2 807 805 0.49% 0.60% 1.02%
117 Europe SI Slovenia 2 079 208 0.84% 0.59% 1.65%
118 Europe ES Spain 46 771 885 1.33% 0.54% 1.04%
119 Africa BJ Benin 12 420 971 1.16% 0.51% 0.00%
120 Asia KR South Korea 51 310 862 0.75% 0.49% 0.13%
121 North America DO Dominican R. 10 950 421 0.99% 0.46% 1.17%
122 Africa GH Ghana 31 682 190 1.15% 0.44% 0.02%
123 Asia UZ Uzbekistan 33 925 709 0.36% 0.44% 0.08%
124 Asia KW Kuwait 4 330 005 0.56% 0.41% 3.24%
125 Asia VN Vietnam 98 164 129 0.33% 0.39% 0.03%
126 Europe CH Switzerland 8 714 309 0.54% 0.35% 0.94%
127 Asia SG Singapore 5 893 725 0.20% 0.34% 0.06%
128 Europe PT Portugal 10 168 602 2.10% 0.30% 0.58%
129 Europe GB United Kingdom 68 222 484 2.08% 0.29% 0.60%
130 Africa ER Eritrea 3 592 624 0.33% 0.28% 0.11%
131 Europe SE Sweden 10 158 668 0.40% 0.26% 2.48%
132 Africa BI Burundi 12 222 502 0.16% 0.25% 0.02%
133 Europe NL Netherlands 17 170 672 0.46% 0.24% 2.13%
134 Asia LA Laos 7 374 920 0.16% 0.23% 0.03%
135 Africa TG Togo 8 460 832 0.56% 0.22% 0.02%
136 Asia AE Arab Emirates 10 002 945 0.28% 0.19% 2.04%
137 Europe NO Norway 5 461 212 0.32% 0.13% 0.73%
138 Europe DK Denmark 5 811 456 0.29% 0.08% 1.82%
139 Europe IE Ireland 4 989 746 1.74% 0.03% 0.90%
140 Australia/Oceania NZ New Zealand 5 002 100 0.27% 0.00% 0.00%
141 Australia/Oceania AU Australia 25 778 568 0.08% 0.00% 0.00%
142 Asia HK Hong Kong 7 554 327 1.46% 0.00% 0.00%
143 Africa NE Niger 25 025 730 2.91% 0.00% 0.00%
144 Africa SS South Sudan 11 317 335 0.75% 0.00% 0.00%
145 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
146 Africa TZ Tanzania 61 328 577 0.00% 0.00% 0.00%
147 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
148 Asia TJ Tajikistan 9 738 767 0.00% 0.00% 0.00%
149 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
150 Asia PS Palestine 5 212 723 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 33 404 191 187 410 5.610
2 Europe HU Hungary 9 637 163 29 813 3.094
3 Europe BA Bosnia and Herzegovina 3 261 513 9 473 2.905
4 Europe CZ Czechia 10 727 742 30 212 2.816
5 Europe MK North Macedonia 2 083 293 5 468 2.625
6 Europe BG Bulgaria 6 898 946 17 878 2.591
7 Europe SK Slovakia 5 462 140 12 436 2.277
8 Europe SI Slovenia 2 079 208 4 712 2.266
9 South America BR Brazil 213 984 390 479 007 2.239
10 Europe BE Belgium 11 637 225 25 068 2.154
11 Europe IT Italy 60 377 804 126 819 2.100
12 Europe HR Croatia 4 081 316 8 112 1.988
13 Europe PL Poland 37 807 440 74 494 1.970
14 Europe GB United Kingdom 68 222 484 127 872 1.874
15 South America AR Argentina 45 586 681 83 354 1.829
16 South America CO Colombia 51 393 873 93 492 1.819
17 North America US USA 332 833 770 592 972 1.782
18 North America MX Mexico 130 209 100 229 343 1.761
19 Europe ES Spain 46 771 885 80 368 1.718
20 Europe PT Portugal 10 168 602 17 038 1.675
21 Europe FR France 65 409 895 109 336 1.672
22 Europe RO Romania 19 116 269 31 388 1.642
23 Europe LT Lithuania 2 686 296 4 330 1.612
24 South America CL Chile 19 270 893 30 248 1.570
25 Europe MD Moldova 4 025 101 6 148 1.527
26 Asia AM Armenia 2 968 473 4 478 1.508
27 North America PA Panama 4 378 667 6 416 1.465
28 Europe SE Sweden 10 158 668 14 562 1.434
29 South America PY Paraguay 7 215 047 10 294 1.427
30 South America UY Uruguay 3 485 094 4 793 1.375
31 South America BO Bolivia 11 822 915 15 273 1.292
32 Asia GE Georgia 3 981 930 5 018 1.260
33 Europe GR Greece 10 374 902 12 367 1.192
34 Europe UA Ukraine 43 485 203 51 576 1.186
35 Europe CH Switzerland 8 714 309 10 244 1.175
36 South America EC Ecuador 17 895 139 20 951 1.171
37 Europe AT Austria 9 054 880 10 388 1.147
38 Asia LB Lebanon 6 796 539 7 785 1.145
39 Africa TN Tunisia 11 935 141 13 289 1.113
40 Europe DE Germany 84 036 849 89 616 1.066
41 Europe NL Netherlands 17 170 672 17 701 1.031
42 Europe IE Ireland 4 989 746 4 941 0.990
43 Asia IR Iran 85 005 237 81 634 0.960
44 Africa ZA South Africa 60 012 828 57 492 0.958
45 Asia JO Jordan 10 298 587 9 566 0.929
46 Europe RU Russia 145 993 575 125 677 0.861
47 Europe AL Albania 2 874 828 2 452 0.853
48 North America CR Costa Rica 5 137 964 4 275 0.832
49 Europe RS Serbia 8 704 091 6 945 0.798
50 South America PR Puerto Rico 3 193 694 2 524 0.790
51 Asia IL Israel 9 326 000 6 428 0.689
52 North America CA Canada 38 054 099 25 809 0.678
53 North America HN Honduras 10 052 801 6 564 0.653
54 Asia TR Turkey 85 194 096 48 503 0.569
55 Asia AZ Azerbaijan 10 225 321 4 950 0.484
56 Asia OM Oman 5 228 445 2 448 0.468
57 North America GT Guatemala 18 227 090 8 359 0.459
58 Africa LY Libya 6 959 252 3 155 0.453
59 Europe DK Denmark 5 811 456 2 522 0.434
60 Asia KW Kuwait 4 330 005 1 809 0.418
61 Asia IQ Iraq 41 069 893 16 636 0.405
62 Asia KZ Kazakhstan 18 988 238 7 465 0.393
63 Africa NA Namibia 2 584 165 955 0.370
64 Africa BW Botswana 2 396 237 885 0.369
65 North America SV El Salvador 6 517 087 2 283 0.350
66 North America DO Dominican R. 10 950 421 3 691 0.337
67 North America JM Jamaica 2 973 365 994 0.334
68 Europe BY Belarus 9 446 386 2 950 0.312
69 Asia KG Kyrgyzstan 6 625 437 1 874 0.283
70 Asia NP Nepal 29 629 496 8 240 0.278
71 Asia IN India 1 392 790 451 360 156 0.259
72 Africa MA Morocco 37 322 618 9 195 0.246
73 Asia SA Saudi Arabia 35 323 967 7 519 0.213
74 Asia QA Qatar 2 807 805 575 0.205
75 Asia PH Philippines 110 954 199 22 335 0.201
76 Asia ID Indonesia 276 248 772 52 326 0.189
77 Europe FI Finland 5 548 849 964 0.174
78 Asia AE Arab Emirates 10 002 945 1 714 0.171
79 Africa LS Lesotho 2 158 261 326 0.151
80 Africa EG Egypt 104 148 514 15 508 0.149
81 Europe NO Norway 5 461 212 789 0.144
82 Asia MY Malaysia 32 756 466 3 687 0.113
83 Asia JP Japan 126 110 418 13 911 0.110
84 Africa ZW Zimbabwe 15 066 546 1 625 0.108
85 Asia SY Syria 17 899 562 1 803 0.101
86 Asia MN Mongolia 3 327 951 333 0.100
87 Africa MR Mauritania 4 764 263 471 0.099
88 South America VE Venezuela 28 359 773 2 766 0.098
89 Asia PK Pakistan 224 922 985 21 510 0.096
90 North America CU Cuba 11 320 084 1 055 0.093
91 Asia LK Sri Lanka 21 497 986 1 910 0.089
92 Asia AF Afghanistan 39 751 424 3 404 0.086
93 Africa DZ Algeria 44 595 470 3 552 0.080
94 Asia BD Bangladesh 166 235 568 12 988 0.078
95 Africa GM Gambia 2 480 296 180 0.073
96 Africa ZM Zambia 18 866 484 1 341 0.071
97 Africa GA Gabon 2 275 023 156 0.069
98 Africa SN Senegal 17 157 677 1 150 0.067
99 Africa KE Kenya 54 883 446 3 363 0.061
100 Africa SD Sudan 44 810 191 2 719 0.061
101 Asia MM Myanmar 54 753 832 3 235 0.059
102 Africa MW Malawi 19 593 554 1 158 0.059
103 Africa CM Cameroon 27 165 767 1 310 0.048
104 Africa SO Somalia 16 308 802 774 0.048
105 Asia YE Yemen 30 442 770 1 342 0.044
106 Asia KR South Korea 51 310 862 1 980 0.039
107 Africa ET Ethiopia 117 635 168 4 230 0.036
108 Australia/Oceania AU Australia 25 778 568 910 0.035
109 Africa GW Guinea-Bissau 2 011 654 69 0.034
110 Africa MG Madagascar 28 358 680 877 0.031
111 North America HT Haiti 11 533 436 345 0.030
112 North America NI Nicaragua 6 698 786 188 0.028
113 Asia HK Hong Kong 7 554 327 210 0.028
114 Africa RW Rwanda 13 253 433 366 0.028
115 Africa CG Congo 5 645 517 155 0.028
116 Africa MZ Mozambique 32 076 119 840 0.026
117 Africa ML Mali 20 797 354 523 0.025
118 Africa GH Ghana 31 682 190 789 0.025
119 Africa AO Angola 33 823 498 815 0.024
120 Asia UZ Uzbekistan 33 925 709 703 0.021
121 Asia TH Thailand 69 965 349 1 404 0.020
122 Africa CF Central African R. 4 908 729 98 0.020
123 Africa LR Liberia 5 169 249 93 0.018
124 Australia/Oceania PG Papua New Guinea 9 106 314 164 0.018
125 Asia KH Cambodia 16 936 769 298 0.018
126 Asia TW Taiwan 23 857 483 411 0.017
127 Africa TG Togo 8 460 832 126 0.015
128 Africa GN Guinea 13 466 742 165 0.012
129 Africa CI Ivory Coast 26 991 087 306 0.011
130 Africa TD Chad 16 867 510 174 0.010
131 Africa SS South Sudan 11 317 335 115 0.010
132 Africa SL Sierra Leone 8 129 382 82 0.010
133 Africa NG Nigeria 210 932 837 2 117 0.010
134 Asia TJ Tajikistan 9 738 767 90 0.009
135 Africa UG Uganda 47 093 315 417 0.009
136 Africa CD DR Congo 92 111 338 824 0.009
137 Africa BJ Benin 12 420 971 102 0.008
138 Africa BF Burkina Faso 21 440 567 167 0.008
139 Africa NE Niger 25 025 730 192 0.008
140 Asia SG Singapore 5 893 725 34 0.006
141 Australia/Oceania NZ New Zealand 5 002 100 26 0.005
142 Africa ER Eritrea 3 592 624 14 0.004
143 Africa BI Burundi 12 222 502 8 0.001
144 Asia VN Vietnam 98 164 129 56 0.001
145 Asia PS Palestine 5 212 723 2 0.000
146 Asia LA Laos 7 374 920 3 0.000
147 Africa TZ Tanzania 61 328 577 21 0.000
148 Asia CN China 1 439 323 776 0 0.000
149 Asia KP North Korea 25 660 000 0 0.000
150 Europe TM Turkmenistan 6 118 000 0 0.000

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

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

* ÚV lámpa (neon) használata a helységekben.
* Azelastine: [1], [2] , [*] 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

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"