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": 2021-05-11 11:26
(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 +0 (+820) +0 (+10)
CZ Czechia +1 532 (+383) +16 (+27)
DE Germany +0 (+7 814) +0 (+110)
HU Hungary +493 (+677) +99 (+91)
PL Poland +3 098 (+2 031) +319 (+5)
SK Slovakia, [gov], [okr]+350 (+311) +26 (+32)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 South America 437 048 574 2.76% 3.35% 3.19%
2 Europe 756 025 174 2.56% 2.09% 1.50%
3 North America 592 629 439 2.11% 1.42% 1.14%
4 Asia 4 663 431 013 0.48% 1.12% 1.13%
5 Africa 1 367 277 088 0.12% 0.09% 0.08%
6 Australia/Oceania 43 226 880 0.04% 0.05% 0.05%

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

N.RegionPopulationMortality last
120 days
Mortality last
30 days
New positive cases
last 30 days
1 South America 437 048 574 2.78% 4.11% 3.35%
2 Africa 1 367 277 088 2.94% (3.81)% (0.09)%
3 Europe 756 025 174 2.16% 2.61% 2.09%
4 North America 592 629 439 2.22% 2.16% 1.42%
5 Australia/Oceania 43 226 880 1.02% (1.60)% (0.05)%
6 Asia 4 663 431 013 1.11% 1.24% 1.12%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 437 048 574 707 052 1.618
2 North America 592 629 439 852 046 1.438
3 Europe 756 025 174 1 037 668 1.373
4 Asia 4 663 431 013 563 466 0.121
5 Africa 1 367 277 088 125 058 0.091
6 Australia/Oceania 43 226 880 1 347 0.031

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 3 484 044 5.63% 9.53% 9.10%
2 South America AR Argentina 45 550 456 3.16% 5.76% 5.58%
3 Europe NL Netherlands 17 167 367 4.04% 5.22% 4.93%
4 Europe LT Lithuania 2 689 592 3.51% 4.89% 4.85%
5 Asia GE Georgia 3 982 596 2.12% 3.60% 4.53%
6 North America CR Costa Rica 5 133 901 1.72% 3.46% 4.06%
7 Europe SE Sweden 10 153 172 5.05% 5.93% 4.06%
8 Europe HR Croatia 4 083 518 3.06% 5.27% 3.87%
9 South America PY Paraguay 7 207 388 2.54% 3.67% 3.72%
10 Europe SI Slovenia 2 079 183 5.14% 3.88% 3.52%
11 Asia NP Nepal 29 583 618 0.47% 1.68% 3.50%
12 South America CO Colombia 51 346 483 2.39% 3.85% 3.49%
13 South America BR Brazil 213 852 486 3.32% 3.37% 3.37%
14 Asia KW Kuwait 4 324 481 3.05% 3.73% 3.26%
15 Europe FR France 65 397 303 4.51% 4.55% 3.18%
16 Asia MN Mongolia 3 323 332 1.32% 3.74% 3.05%
17 Asia IN India 1 391 605 161 0.88% 2.67% 2.93%
18 Asia TR Turkey 85 114 793 3.19% 5.86% 2.92%
19 South America CL Chile 19 256 563 3.14% 3.71% 2.80%
20 Europe GR Greece 10 379 331 2.11% 2.70% 2.53%
21 North America CA Canada 38 025 198 1.67% 2.55% 2.40%
22 Asia IR Iran 84 911 245 1.63% 2.94% 2.37%
23 Asia QA Qatar 2 807 805 2.33% 3.18% 2.32%
24 Europe BE Belgium 11 632 825 3.02% 3.13% 2.32%
25 Europe DE Germany 84 013 487 1.92% 2.56% 2.07%
26 Asia AE Arab Emirates 9 992 499 3.07% 2.23% 2.05%
27 South America PE Peru 33 364 023 2.45% 2.63% 1.91%
28 Europe DK Denmark 5 809 677 1.35% 1.58% 1.86%
29 Europe IT Italy 60 385 546 3.05% 2.40% 1.86%
30 Asia OM Oman 5 217 053 1.37% 2.60% 1.65%
31 Europe AT Austria 9 050 395 2.74% 2.48% 1.64%
32 Europe CZ Czechia 10 726 011 7.57% 2.49% 1.62%
33 Europe RS Serbia 8 707 154 3.92% 2.84% 1.61%
34 South America BO Bolivia 11 808 990 1.23% 1.29% 1.60%
35 Asia IQ Iraq 40 990 787 1.26% 1.95% 1.57%
36 Europe CH Switzerland 8 708 783 2.16% 2.37% 1.57%
37 North America US USA 332 664 383 3.11% 1.91% 1.45%
38 South America PR Puerto Rico 3 193 694 1.65% 2.94% 1.45%
39 Europe HU Hungary 9 639 299 4.66% 3.02% 1.43%
40 Europe BY Belarus 9 446 657 1.67% 1.48% 1.43%
41 Europe UA Ukraine 43 508 054 2.31% 2.49% 1.42%
42 Asia MY Malaysia 32 720 210 0.94% 1.04% 1.41%
43 Europe PL Poland 37 811 050 3.83% 2.79% 1.37%
44 Europe BG Bulgaria 6 903 494 2.94% 2.30% 1.35%
45 South America EC Ecuador 17 871 702 1.01% 1.28% 1.34%
46 Africa TN Tunisia 11 924 336 1.36% 1.73% 1.31%
47 Asia AM Armenia 2 967 990 1.91% 2.26% 1.27%
48 Asia LK Sri Lanka 21 490 154 0.37% 0.63% 1.18%
49 Asia LB Lebanon 6 799 199 4.62% 2.27% 1.18%
50 Asia KZ Kazakhstan 18 968 606 0.98% 1.59% 1.17%
51 Asia JO Jordan 10 289 738 4.02% 2.28% 1.14%
52 North America CU Cuba 11 320 686 0.91% 1.11% 1.13%
53 Europe MK North Macedonia 2 083 301 3.24% 2.48% 1.07%
54 Europe BA Bosnia and Herzegovina 3 263 287 2.62% 2.22% 1.07%
55 North America HN Honduras 10 039 017 0.93% 1.02% 1.05%
56 Europe IE Ireland 4 984 926 2.12% 1.01% 1.00%
57 Asia AZ Azerbaijan 10 217 339 1.01% 1.70% 0.96%
58 North America PA Panama 4 372 724 2.08% 0.86% 0.95%
59 Africa BW Botswana 2 392 078 1.38% 1.06% 0.85%
60 Europe NO Norway 5 457 510 1.11% 1.03% 0.79%
61 Europe ES Spain 46 770 308 3.00% 1.68% 0.77%
62 Europe RO Romania 19 127 428 2.07% 1.34% 0.75%
63 Africa NA Namibia 2 580 136 0.85% 0.76% 0.70%
64 Europe SK Slovakia 5 461 910 3.25% 1.08% 0.70%
65 Asia PH Philippines 110 826 667 0.56% 0.92% 0.69%
66 Asia KG Kyrgyzstan 6 616 017 0.25% 0.53% 0.64%
67 North America GT Guatemala 18 198 073 0.51% 0.72% 0.61%
68 Europe MD Moldova 4 025 917 2.57% 1.18% 0.61%
69 Europe RU Russia 145 988 122 1.00% 0.68% 0.57%
70 North America DO Dominican R. 10 940 917 0.81% 0.51% 0.55%
71 Asia JP Japan 126 144 121 0.28% 0.44% 0.51%
72 South America VE Venezuela 28 366 786 0.32% 0.50% 0.47%
73 Africa LY Libya 6 951 081 1.09% 0.77% 0.47%
74 North America JM Jamaica 2 972 237 1.12% 0.63% 0.43%
75 Europe GB United Kingdom 68 191 369 1.90% 0.41% 0.39%
76 Europe PT Portugal 10 171 190 3.50% 0.50% 0.38%
77 Africa ZA South Africa 59 947 455 0.61% 0.27% 0.37%
78 Europe FI Finland 5 548 099 0.90% 0.49% 0.35%
79 Asia KH Cambodia 16 916 534 0.11% 0.37% 0.35%
80 Asia TH Thailand 69 950 079 0.11% 0.31% 0.35%
81 Asia SA Saudi Arabia 35 276 532 0.18% 0.34% 0.34%
82 Europe AL Albania 2 875 101 2.37% 0.50% 0.28%
83 Africa GA Gabon 2 270 419 0.61% 0.52% 0.27%
84 Africa CM Cameroon 27 107 817 0.18% 0.26% 0.26%
85 North America SV El Salvador 6 514 231 0.33% 0.30% 0.24%
86 Asia ID Indonesia 275 996 044 0.32% 0.23% 0.23%
87 North America MX Mexico 130 090 737 0.65% 0.29% 0.22%
88 Asia PK Pakistan 224 547 359 0.16% 0.26% 0.21%
89 Australia/Oceania PG Papua New Guinea 9 091 473 0.13% 0.17% 0.18%
90 Asia PS Palestine 5 202 328 0.01% 0.04% 0.16%
91 Asia UZ Uzbekistan 33 883 283 0.05% 0.12% 0.14%
92 Asia KR South Korea 51 307 017 0.12% 0.15% 0.13%
93 Africa EG Egypt 103 979 506 0.09% 0.11% 0.13%
94 Asia BD Bangladesh 166 092 224 0.15% 0.23% 0.12%
95 Africa CG Congo 5 633 606 0.07% 0.09% 0.10%
96 Africa KE Kenya 54 779 649 0.12% 0.13% 0.10%
97 Africa CF Central African R. 4 901 378 0.03% 0.10% 0.09%
98 Africa MA Morocco 37 284 378 0.16% 0.13% 0.09%
99 Africa AO Angola 33 733 691 0.03% 0.07% 0.09%
100 Asia LA Laos 7 365 686 0.02% 0.07% 0.09%
101 Africa MG Madagascar 28 296 237 0.08% 0.16% 0.09%
102 Asia AF Afghanistan 39 674 585 0.02% 0.05% 0.08%
103 Africa MR Mauritania 4 753 541 0.07% 0.06% 0.08%
104 Africa ET Ethiopia 117 385 440 0.11% 0.12% 0.06%
105 Asia IL Israel 9 197 590 3.78% 0.14% 0.06%
106 Africa DZ Algeria 44 526 148 0.05% 0.05% 0.06%
107 Africa SO Somalia 16 269 885 0.06% 0.05% 0.05%
108 Africa RW Rwanda 13 225 276 0.12% 0.07% 0.05%
109 Asia SY Syria 17 862 285 0.06% 0.07% 0.04%
110 Asia SG Singapore 5 889 708 0.04% 0.05% 0.04%
111 Africa GN Guinea 13 435 484 0.07% 0.06% 0.04%
112 Africa ER Eritrea 3 588 331 0.06% 0.03% 0.04%
113 Africa ZM Zambia 18 821 296 0.34% 0.05% 0.04%
114 Africa LS Lesotho 2 156 778 0.38% 0.01% 0.03%
115 Africa TG Togo 8 443 823 0.11% 0.06% 0.03%
116 Africa SD Sudan 44 720 441 0.02% 0.02% 0.03%
117 Africa SN Senegal 17 118 966 0.11% 0.03% 0.03%
118 Africa BI Burundi 12 191 404 0.03% 0.04% 0.02%
119 North America NI Nicaragua 6 691 897 0.01% 0.01% 0.02%
120 Africa CI Ivory Coast 26 933 804 0.09% 0.02% 0.02%
121 Africa GM Gambia 2 474 337 0.08% 0.06% 0.02%
122 Africa GH Ghana 31 625 366 0.12% 0.02% 0.02%
123 Africa UG Uganda 46 966 406 0.01% 0.01% 0.02%
124 Africa MZ Mozambique 31 999 261 0.15% 0.02% 0.02%
125 Africa ML Mali 20 746 149 0.03% 0.05% 0.02%
126 Africa ZW Zimbabwe 15 047 621 0.11% 0.03% 0.02%
127 North America HT Haiti 11 521 285 0.03% 0.01% 0.01%
128 Asia VN Vietnam 98 087 634 0.00% 0.00% 0.01%
129 Africa BJ Benin 12 393 114 0.04% 0.01% 0.01%
130 Asia YE Yemen 30 385 204 0.01% 0.02% 0.01%
131 Australia/Oceania NZ New Zealand 5 002 100 0.01% 0.01% 0.01%
132 Africa MW Malawi 19 550 192 0.13% 0.01% 0.01%
133 Africa CD DR Congo 91 872 203 0.01% 0.01% 0.01%
134 Africa BF Burkina Faso 21 390 267 0.02% 0.01% 0.01%
135 Africa LR Liberia 5 158 828 0.01% 0.00% 0.01%
136 Australia/Oceania AU Australia 25 752 709 0.01% 0.01% 0.01%
137 Africa TD Chad 16 826 134 0.01% 0.01% 0.01%
138 Africa NE Niger 24 948 651 0.01% 0.00% 0.01%
139 Africa SS South Sudan 11 305 865 0.06% 0.01% 0.01%
140 Asia TW Taiwan 23 853 726 0.00% 0.00% 0.00%
141 Asia MM Myanmar 54 721 993 0.02% 0.00% 0.00%
142 Africa GW Guinea-Bissau 2 007 576 0.06% 0.01% 0.00%
143 Africa NG Nigeria 210 484 782 0.03% 0.00% 0.00%
144 Africa SL Sierra Leone 8 115 172 0.02% 0.00% 0.00%
145 Asia HK Hong Kong 7 549 016 0.00% 0.00% 0.00%
146 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
147 Africa TZ Tanzania 61 179 224 0.00% 0.00% 0.00%
148 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
149 Asia TJ Tajikistan 9 719 991 0.00% 0.00% 0.00%
150 Asia CN China 1 439 323 776 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 44 720 441 9.81% (15.21)% (0.02)%
2 Africa LS Lesotho 2 156 778 3.30% (14.81)% (0.01)%
3 Asia YE Yemen 30 385 204 15.58% (14.65)% (0.02)%
4 North America MX Mexico 130 090 737 9.48% 11.83% 0.29%
5 Europe SK Slovakia 5 461 910 4.65% 8.06% 1.08%
6 Asia SY Syria 17 862 285 7.90% (8.02)% (0.07)%
7 Africa SO Somalia 16 269 885 6.71% (6.20)% (0.05)%
8 Europe BA Bosnia and Herzegovina 3 263 287 5.24% 6.18% 2.22%
9 Africa EG Egypt 103 979 506 6.52% 5.92% 0.11%
10 Africa MW Malawi 19 550 192 3.40% (5.65)% (0.01)%
11 Europe HU Hungary 9 639 299 3.96% 5.44% 3.02%
12 Europe BG Bulgaria 6 903 494 4.40% 5.03% 2.30%
13 Asia AF Afghanistan 39 674 585 5.51% (4.86)% (0.05)%
14 Africa ZA South Africa 59 947 455 4.47% 4.69% 0.27%
15 Europe MK North Macedonia 2 083 301 3.62% 4.68% 2.48%
16 Europe RO Romania 19 127 428 2.96% 4.57% 1.34%
17 North America HT Haiti 11 521 285 0.93% (4.32)% (0.01)%
18 Europe RU Russia 145 988 122 3.25% 4.13% 0.68%
19 Africa TN Tunisia 11 924 336 3.70% 4.10% 1.73%
20 South America PE Peru 33 364 023 3.26% 4.04% 2.63%
21 Africa DZ Algeria 44 526 148 2.34% (4.02)% (0.05)%
22 South America BR Brazil 213 852 486 3.12% 3.99% 3.37%
23 South America PY Paraguay 7 207 388 2.73% 3.76% 3.67%
24 North America HN Honduras 10 039 017 2.62% 3.66% 1.02%
25 South America EC Ecuador 17 871 702 2.92% 3.58% 1.28%
26 Europe MD Moldova 4 025 917 2.67% 3.47% 1.18%
27 Europe PL Poland 37 811 050 2.63% 3.23% 2.79%
28 Asia ID Indonesia 275 996 044 2.52% 3.09% 0.23%
29 Europe GR Greece 10 379 331 2.79% 3.00% 2.70%
30 Africa SN Senegal 17 118 966 3.15% (2.85)% (0.03)%
31 Europe UA Ukraine 43 508 054 2.65% 2.81% 2.49%
32 Africa NA Namibia 2 580 136 1.82% 2.78% 0.76%
33 Africa ML Mali 20 746 149 3.05% (2.77)% (0.05)%
34 Africa ZW Zimbabwe 15 047 621 4.64% (2.75)% (0.03)%
35 South America CO Colombia 51 346 483 2.61% 2.70% 3.85%
36 Africa KE Kenya 54 779 649 1.88% 2.57% 0.13%
37 Asia AM Armenia 2 967 990 2.32% 2.51% 2.26%
38 North America JM Jamaica 2 972 237 1.51% 2.50% 0.63%
39 Asia PK Pakistan 224 547 359 2.41% 2.45% 0.26%
40 South America BO Bolivia 11 808 990 2.66% 2.38% 1.29%
41 North America NI Nicaragua 6 691 897 2.54% (2.33)% (0.01)%
42 Europe IT Italy 60 385 546 2.34% 2.27% 2.40%
43 Europe CZ Czechia 10 726 011 1.85% 2.26% 2.49%
44 North America SV El Salvador 6 514 231 3.26% 2.19% 0.30%
45 North America GT Guatemala 18 198 073 3.00% 2.17% 0.72%
46 Europe HR Croatia 4 083 518 2.56% 2.17% 5.27%
47 Europe AL Albania 2 875 101 1.64% 2.08% 0.50%
48 Africa GM Gambia 2 474 337 2.38% (2.04)% (0.06)%
49 South America UY Uruguay 3 484 044 1.58% 1.94% 9.53%
50 Asia KG Kyrgyzstan 6 616 017 1.95% 1.92% 0.53%
51 Africa BF Burkina Faso 21 390 267 1.16% 1.92% 0.01%
52 Africa MG Madagascar 28 296 237 2.34% 1.89% 0.16%
53 Asia IL Israel 9 197 590 0.68% 1.89% 0.14%
54 Africa AO Angola 33 733 691 2.32% 1.89% 0.07%
55 Africa MZ Mozambique 31 999 261 1.25% 1.80% 0.02%
56 Africa CM Cameroon 27 107 817 1.59% 1.76% 0.26%
57 Africa NE Niger 24 948 651 3.21% 1.75% 0.00%
58 Asia IR Iran 84 911 245 1.45% 1.74% 2.94%
59 Asia BD Bangladesh 166 092 224 1.69% 1.73% 0.23%
60 Asia LB Lebanon 6 799 199 1.74% 1.71% 2.27%
61 Africa TD Chad 16 826 134 2.45% 1.67% 0.01%
62 Africa ET Ethiopia 117 385 440 1.43% 1.65% 0.12%
63 Africa BW Botswana 2 392 078 2.13% 1.65% 1.06%
64 Africa CI Ivory Coast 26 933 804 0.64% 1.64% 0.02%
65 Africa CF Central African R. 4 901 378 2.07% 1.63% 0.10%
66 Asia JO Jordan 10 289 738 1.23% 1.62% 2.28%
67 South America AR Argentina 45 550 456 1.69% 1.61% 5.76%
68 Africa CD DR Congo 91 872 203 1.35% 1.58% 0.01%
69 Asia AZ Azerbaijan 10 217 339 1.77% 1.56% 1.70%
70 Africa LY Libya 6 951 081 1.94% 1.54% 0.77%
71 Asia GE Georgia 3 982 596 1.83% 1.53% 3.60%
72 South America CL Chile 19 256 563 1.69% 1.52% 3.71%
73 South America VE Venezuela 28 366 786 1.43% 1.48% 0.50%
74 Africa GH Ghana 31 625 366 1.19% 1.44% 0.02%
75 Africa BJ Benin 12 393 114 1.23% 1.38% 0.01%
76 Asia PH Philippines 110 826 667 1.56% 1.36% 0.92%
77 Africa GW Guinea-Bissau 2 007 576 1.71% 1.33% 0.01%
78 Africa MA Morocco 37 284 378 1.94% 1.32% 0.13%
79 Asia NP Nepal 29 583 618 2.38% 1.25% 1.68%
80 North America PA Panama 4 372 724 1.64% 1.24% 0.86%
81 Asia JP Japan 126 144 121 1.90% 1.24% 0.44%
82 Europe DE Germany 84 013 487 2.67% 1.20% 2.56%
83 Asia SA Saudi Arabia 35 276 532 1.39% 1.19% 0.34%
84 North America US USA 332 664 383 1.75% 1.16% 1.91%
85 Australia/Oceania PG Papua New Guinea 9 091 473 1.07% 1.14% 0.17%
86 Asia LK Sri Lanka 21 490 154 0.86% 1.14% 0.63%
87 Europe RS Serbia 8 707 154 0.86% 1.11% 2.84%
88 Europe LT Lithuania 2 689 592 1.79% 1.11% 4.89%
89 Europe AT Austria 9 050 395 1.37% 1.11% 2.48%
90 Asia MM Myanmar 54 721 993 2.21% 1.10% 0.00%
91 Europe BE Belgium 11 632 825 1.23% 1.10% 3.13%
92 Europe IE Ireland 4 984 926 1.74% 1.10% 1.01%
93 Africa MR Mauritania 4 753 541 1.75% 1.07% 0.06%
94 Africa ZM Zambia 18 821 296 1.12% 1.06% 0.05%
95 North America DO Dominican R. 10 940 917 1.17% 1.05% 0.51%
96 Asia OM Oman 5 217 053 0.92% 1.04% 2.60%
97 North America CR Costa Rica 5 133 901 1.27% 1.01% 3.46%
98 Asia IN India 1 391 605 161 0.96% 0.99% 2.67%
99 Asia TW Taiwan 23 853 726 1.48% 0.94% 0.00%
100 North America CU Cuba 11 320 686 0.61% 0.92% 1.11%
101 Asia KZ Kazakhstan 18 968 606 0.92% 0.92% 1.59%
102 South America PR Puerto Rico 3 193 694 1.38% 0.92% 2.94%
103 Europe FR France 65 397 303 1.30% 0.90% 4.55%
104 Africa GN Guinea 13 435 484 0.82% 0.89% 0.06%
105 Africa UG Uganda 46 966 406 0.72% 0.86% 0.01%
106 Europe BY Belarus 9 446 657 0.69% 0.83% 1.48%
107 Africa CG Congo 5 633 606 1.00% 0.82% 0.09%
108 Asia TH Thailand 69 950 079 0.60% 0.81% 0.31%
109 Africa RW Rwanda 13 225 276 1.31% 0.78% 0.07%
110 Europe SI Slovenia 2 079 183 1.12% 0.76% 3.88%
111 Europe GB United Kingdom 68 191 369 2.76% 0.75% 0.41%
112 Asia QA Qatar 2 807 805 0.42% 0.72% 3.18%
113 Asia KH Cambodia 16 916 534 0.79% 0.71% 0.37%
114 Asia TR Turkey 85 114 793 0.77% 0.66% 5.86%
115 Europe FI Finland 5 548 099 0.66% 0.65% 0.49%
116 Europe ES Spain 46 770 308 1.48% 0.64% 1.68%
117 Asia KW Kuwait 4 324 481 0.56% 0.60% 3.73%
118 Africa ER Eritrea 3 588 331 0.26% 0.59% 0.03%
119 Asia KR South Korea 51 307 017 1.23% 0.58% 0.15%
120 North America CA Canada 38 025 198 1.22% 0.57% 2.55%
121 Europe PT Portugal 10 171 190 2.24% 0.57% 0.50%
122 Asia MY Malaysia 32 720 210 0.39% 0.56% 1.04%
123 Asia IQ Iraq 40 990 787 0.60% 0.53% 1.95%
124 Asia MN Mongolia 3 323 332 0.45% 0.51% 3.74%
125 Europe NO Norway 5 457 510 0.44% 0.50% 1.03%
126 Africa GA Gabon 2 270 419 0.56% 0.48% 0.52%
127 Africa TG Togo 8 443 823 0.57% 0.46% 0.06%
128 Asia UZ Uzbekistan 33 883 283 0.31% 0.34% 0.12%
129 Europe CH Switzerland 8 708 783 0.95% 0.33% 2.37%
130 Africa SS South Sudan 11 305 865 0.74% 0.29% 0.01%
131 Europe DK Denmark 5 809 677 1.11% 0.28% 1.58%
132 Europe NL Netherlands 17 167 367 0.72% 0.27% 5.22%
133 Africa NG Nigeria 210 484 782 0.94% 0.24% 0.00%
134 Europe SE Sweden 10 153 172 0.68% 0.23% 5.93%
135 Australia/Oceania AU Australia 25 752 709 0.07% 0.20% 0.01%
136 Asia AE Arab Emirates 9 992 499 0.29% 0.15% 2.23%
137 Asia SG Singapore 5 889 708 0.08% 0.13% 0.05%
138 Asia LA Laos 7 365 686 0.11% 0.11% 0.07%
139 Africa BI Burundi 12 191 404 0.12% 0.00% 0.04%
140 Australia/Oceania NZ New Zealand 5 002 100 0.23% 0.00% 0.01%
141 Africa LR Liberia 5 158 828 0.67% 0.00% 0.00%
142 Africa SL Sierra Leone 8 115 172 0.14% 0.00% 0.00%
143 Asia VN Vietnam 98 087 634 0.00% 0.00% 0.00%
144 Asia PS Palestine 5 202 328 0.00% 0.00% 0.04%
145 Asia HK Hong Kong 7 549 016 0.00% 0.00% 0.00%
146 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
147 Africa TZ Tanzania 61 179 224 0.00% 0.00% 0.00%
148 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
149 Asia TJ Tajikistan 9 719 991 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 Europe HU Hungary 9 639 299 28 792 2.987
2 Europe CZ Czechia 10 726 011 29 727 2.772
3 Europe BA Bosnia and Herzegovina 3 263 287 8 862 2.716
4 Europe BG Bulgaria 6 903 494 17 045 2.469
5 Europe MK North Macedonia 2 083 301 5 109 2.452
6 Europe SI Slovenia 2 079 183 4 618 2.221
7 Europe SK Slovakia 5 461 910 12 045 2.205
8 Europe BE Belgium 11 632 825 24 583 2.113
9 Europe IT Italy 60 385 546 123 031 2.037
10 South America BR Brazil 213 852 486 422 334 1.975
11 South America PE Peru 33 364 023 64 096 1.921
12 Europe GB United Kingdom 68 191 369 127 609 1.871
13 Europe PL Poland 37 811 050 70 353 1.861
14 Europe HR Croatia 4 083 518 7 503 1.837
15 North America US USA 332 664 383 576 350 1.732
16 Europe ES Spain 46 770 308 78 761 1.684
17 North America MX Mexico 130 090 737 219 032 1.684
18 Europe PT Portugal 10 171 190 16 993 1.671
19 Europe FR France 65 397 303 105 922 1.620
20 Europe RO Romania 19 127 428 29 034 1.518
21 South America CO Colombia 51 346 483 77 847 1.516
22 Europe LT Lithuania 2 689 592 4 039 1.502
23 South America AR Argentina 45 550 456 67 538 1.483
24 Europe MD Moldova 4 025 917 5 958 1.480
25 North America PA Panama 4 372 724 6 271 1.434
26 Asia AM Armenia 2 967 990 4 256 1.434
27 South America CL Chile 19 256 563 27 201 1.413
28 Europe SE Sweden 10 153 172 14 173 1.396
29 Europe CH Switzerland 8 708 783 10 066 1.156
30 South America BO Bolivia 11 808 990 13 228 1.120
31 Europe AT Austria 9 050 395 10 131 1.119
32 Asia LB Lebanon 6 799 199 7 507 1.104
33 Asia GE Georgia 3 982 596 4 336 1.089
34 South America EC Ecuador 17 871 702 19 242 1.077
35 Europe UA Ukraine 43 508 054 46 631 1.072
36 Europe GR Greece 10 379 331 11 089 1.068
37 Europe DE Germany 84 013 487 84 939 1.011
38 Europe NL Netherlands 17 167 367 17 340 1.010
39 South America PY Paraguay 7 207 388 7 129 0.989
40 Europe IE Ireland 4 984 926 4 921 0.987
41 Africa TN Tunisia 11 924 336 11 468 0.962
42 Africa ZA South Africa 59 947 455 54 825 0.915
43 South America UY Uruguay 3 484 044 3 131 0.899
44 Asia JO Jordan 10 289 738 9 125 0.887
45 Asia IR Iran 84 911 245 75 261 0.886
46 Europe AL Albania 2 875 101 2 416 0.840
47 Europe RU Russia 145 988 122 113 655 0.778
48 Europe RS Serbia 8 707 154 6 576 0.755
49 South America PR Puerto Rico 3 193 694 2 372 0.743
50 Asia IL Israel 9 197 590 6 378 0.693
51 North America CR Costa Rica 5 133 901 3 386 0.659
52 North America CA Canada 38 025 198 24 624 0.648
53 North America HN Honduras 10 039 017 5 653 0.563
54 Asia TR Turkey 85 114 793 43 311 0.509
55 Asia AZ Azerbaijan 10 217 339 4 698 0.460
56 Africa LY Libya 6 951 081 3 072 0.442
57 Europe DK Denmark 5 809 677 2 497 0.430
58 North America GT Guatemala 18 198 073 7 736 0.425
59 Asia OM Oman 5 217 053 2 130 0.408
60 Asia IQ Iraq 40 990 787 15 800 0.386
61 Asia KW Kuwait 4 324 481 1 652 0.382
62 North America SV El Salvador 6 514 231 2 158 0.331
63 North America DO Dominican R. 10 940 917 3 531 0.323
64 Africa BW Botswana 2 392 078 751 0.314
65 Europe BY Belarus 9 446 657 2 642 0.280
66 North America JM Jamaica 2 972 237 809 0.272
67 Africa NA Namibia 2 580 136 691 0.268
68 Asia KG Kyrgyzstan 6 616 017 1 667 0.252
69 Africa MA Morocco 37 284 378 9 077 0.243
70 Asia KZ Kazakhstan 18 968 606 4 542 0.239
71 Asia SA Saudi Arabia 35 276 532 7 085 0.201
72 Asia QA Qatar 2 807 805 512 0.182
73 Asia IN India 1 391 605 161 246 116 0.177
74 Asia ID Indonesia 275 996 044 47 218 0.171
75 Asia PH Philippines 110 826 667 18 531 0.167
76 Europe FI Finland 5 548 099 922 0.166
77 Asia AE Arab Emirates 9 992 499 1 615 0.162
78 Africa LS Lesotho 2 156 778 319 0.148
79 Europe NO Norway 5 457 510 767 0.141
80 Africa EG Egypt 103 979 506 13 972 0.134
81 Asia NP Nepal 29 583 618 3 859 0.130
82 Africa ZW Zimbabwe 15 047 621 1 576 0.105
83 Africa MR Mauritania 4 753 541 456 0.096
84 Asia SY Syria 17 862 285 1 664 0.093
85 Asia JP Japan 126 144 121 10 876 0.086
86 Asia PK Pakistan 224 547 359 19 028 0.085
87 South America VE Venezuela 28 366 786 2 293 0.081
88 Africa DZ Algeria 44 526 148 3 335 0.075
89 Asia BD Bangladesh 166 092 224 11 972 0.072
90 Africa GM Gambia 2 474 337 175 0.071
91 Asia AF Afghanistan 39 674 585 2 710 0.068
92 Africa ZM Zambia 18 821 296 1 257 0.067
93 North America CU Cuba 11 320 686 741 0.066
94 Africa SN Senegal 17 118 966 1 120 0.065
95 Africa GA Gabon 2 270 419 143 0.063
96 Africa MW Malawi 19 550 192 1 153 0.059
97 Asia MM Myanmar 54 721 993 3 210 0.059
98 Africa SD Sudan 44 720 441 2 446 0.055
99 Africa KE Kenya 54 779 649 2 907 0.053
100 Asia MY Malaysia 32 720 210 1 700 0.052
101 Asia MN Mongolia 3 323 332 171 0.051
102 Africa SO Somalia 16 269 885 747 0.046
103 Africa CM Cameroon 27 107 817 1 144 0.042
104 Asia YE Yemen 30 385 204 1 276 0.042
105 Asia LK Sri Lanka 21 490 154 827 0.038
106 Asia KR South Korea 51 307 017 1 879 0.037
107 Australia/Oceania AU Australia 25 752 709 910 0.035
108 Africa GW Guinea-Bissau 2 007 576 67 0.033
109 Africa ET Ethiopia 117 385 440 3 897 0.033
110 North America NI Nicaragua 6 691 897 183 0.027
111 Africa CG Congo 5 633 606 148 0.026
112 Africa MG Madagascar 28 296 237 729 0.026
113 Africa MZ Mozambique 31 999 261 825 0.026
114 Africa RW Rwanda 13 225 276 338 0.026
115 Africa GH Ghana 31 625 366 783 0.025
116 Africa ML Mali 20 746 149 502 0.024
117 North America HT Haiti 11 521 285 266 0.023
118 Asia UZ Uzbekistan 33 883 283 664 0.020
119 Africa CF Central African R. 4 901 378 93 0.019
120 Africa AO Angola 33 733 691 636 0.019
121 Africa LR Liberia 5 158 828 85 0.017
122 Africa TG Togo 8 443 823 125 0.015
123 Australia/Oceania PG Papua New Guinea 9 091 473 121 0.013
124 Africa GN Guinea 13 435 484 151 0.011
125 Africa CI Ivory Coast 26 933 804 291 0.011
126 Africa SS South Sudan 11 305 865 115 0.010
127 Africa TD Chad 16 826 134 171 0.010
128 Africa NG Nigeria 210 484 782 2 065 0.010
129 Africa SL Sierra Leone 8 115 172 79 0.010
130 Asia TJ Tajikistan 9 719 991 90 0.009
131 Africa CD DR Congo 91 872 203 772 0.008
132 Africa BJ Benin 12 393 114 100 0.008
133 Africa NE Niger 24 948 651 192 0.008
134 Africa BF Burkina Faso 21 390 267 162 0.008
135 Asia KH Cambodia 16 916 534 125 0.007
136 Africa UG Uganda 46 966 406 346 0.007
137 Asia TH Thailand 69 950 079 452 0.006
138 Asia SG Singapore 5 889 708 31 0.005
139 Australia/Oceania NZ New Zealand 5 002 100 26 0.005
140 Asia PS Palestine 5 202 328 20 0.004
141 Africa ER Eritrea 3 588 331 12 0.003
142 Africa BI Burundi 12 191 404 6 0.001
143 Asia TW Taiwan 23 853 726 12 0.001
144 Asia VN Vietnam 98 087 634 35 0.000
145 Africa TZ Tanzania 61 179 224 21 0.000
146 Asia LA Laos 7 365 686 1 0.000
147 Asia CN China 1 439 323 776 0 0.000
148 Asia KP North Korea 25 660 000 0 0.000
149 Europe TM Turkmenistan 6 118 000 0 0.000
150 Asia HK Hong Kong 7 549 016 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]

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"