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": 2021-09-24 13:43
(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 +1 754 (+1 707) +10 (+10)
CZ Czechia +488 (+524) +2 (+2)
DE Germany +0 (+10 076) +0 (+77)
HU Hungary +531 (+526) +6 (+2)
PL Poland +813 (+973) +14 (+14)
SK Slovakia, [gov], [okr]+829 (+949) +2 (+3)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 North America 594 343 641 2.11% 3.68% 3.13%
2 Europe 756 191 561 1.55% 1.94% 1.86%
3 South America 438 368 422 2.20% 0.90% 1.14%
4 Australia/Oceania 43 413 850 0.35% 0.62% 0.65%
5 Asia 4 676 050 314 0.53% 0.54% 0.43%
6 Africa 1 379 237 369 0.25% 0.18% 0.09%

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 438 368 422 2.68% 3.98% 0.90%
2 Africa 1 379 237 369 2.27% 2.93% 0.18%
3 Asia 4 676 050 314 1.74% 1.92% 0.54%
4 North America 594 343 641 1.42% 1.80% 3.68%
5 Europe 756 191 561 1.27% 1.65% 1.94%
6 Australia/Oceania 43 413 850 1.09% 1.47% 0.62%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 438 368 422 1 152 070 2.628
2 North America 594 343 641 1 033 381 1.739
3 Europe 756 191 561 1 212 031 1.603
4 Asia 4 676 050 314 1 103 582 0.236
5 Africa 1 379 237 369 207 602 0.150
6 Australia/Oceania 43 413 850 2 884 0.066

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 MN Mongolia 3 342 965 7.05% 11.16% 10.49%
2 Europe RS Serbia 8 694 138 2.09% 6.75% 9.25%
3 North America CU Cuba 11 318 126 6.15% 8.12% 8.51%
4 Asia IL Israel 9 326 000 4.45% 10.43% 8.45%
5 Europe LT Lithuania 2 675 585 1.86% 4.09% 5.78%
6 Europe GB United Kingdom 68 323 609 4.53% 5.92% 5.72%
7 Asia MY Malaysia 32 874 297 4.94% 6.85% 5.58%
8 North America CR Costa Rica 5 151 169 4.06% 5.49% 5.53%
9 Europe SI Slovenia 2 079 289 1.67% 4.44% 5.49%
10 Asia GE Georgia 3 979 763 6.61% 7.61% 5.17%
11 North America US USA 333 384 277 2.83% 5.37% 4.54%
12 Asia TR Turkey 85 451 829 2.05% 3.31% 3.88%
13 Europe HR Croatia 4 074 161 1.04% 2.63% 3.41%
14 Europe RO Romania 19 080 003 0.51% 1.70% 3.41%
15 Europe AL Albania 2 873 938 1.17% 3.53% 3.28%
16 Europe IE Ireland 5 005 412 2.48% 3.55% 3.23%
17 Europe MD Moldova 4 022 448 0.79% 2.12% 3.15%
18 Africa BW Botswana 2 409 754 5.02% 4.25% 2.97%
19 Europe BA Bosnia and Herzegovina 3 255 745 0.82% 2.43% 2.82%
20 Europe GR Greece 10 360 506 2.32% 2.82% 2.64%
21 Europe BG Bulgaria 6 884 168 1.04% 2.58% 2.62%
22 Europe MK North Macedonia 2 083 269 1.61% 3.50% 2.62%
23 Asia AM Armenia 2 970 042 1.15% 2.36% 2.58%
24 Europe BY Belarus 9 445 506 1.43% 2.23% 2.50%
25 Asia SG Singapore 5 906 782 0.35% 1.09% 2.32%
26 Europe AT Austria 9 069 454 0.98% 2.32% 2.32%
27 Asia IR Iran 85 310 713 3.08% 3.46% 2.31%
28 Asia TH Thailand 70 014 978 1.99% 2.48% 2.17%
29 Asia PH Philippines 111 368 677 1.12% 2.03% 2.03%
30 North America JM Jamaica 2 977 029 1.12% 2.41% 1.96%
31 South America BR Brazil 214 413 077 2.37% 1.28% 1.90%
32 Asia KZ Kazakhstan 19 052 041 2.69% 2.69% 1.77%
33 Asia AZ Azerbaijan 10 251 263 1.41% 3.10% 1.74%
34 Europe SK Slovakia 5 462 889 0.32% 0.91% 1.73%
35 Europe RU Russia 146 011 295 1.60% 1.57% 1.67%
36 Europe UA Ukraine 43 410 937 0.43% 0.95% 1.63%
37 North America GT Guatemala 18 321 394 1.57% 2.03% 1.56%
38 Europe BE Belgium 11 651 525 1.46% 1.96% 1.54%
39 Europe CH Switzerland 8 732 267 1.59% 2.98% 1.52%
40 Africa LY Libya 6 985 807 2.16% 2.07% 1.50%
41 North America CA Canada 38 148 028 0.59% 1.22% 1.39%
42 Europe NO Norway 5 473 241 1.12% 2.43% 1.36%
43 Asia LB Lebanon 6 787 896 1.20% 1.57% 1.32%
44 Asia VN Vietnam 98 412 739 0.73% 1.46% 1.26%
45 Europe NL Netherlands 17 181 414 2.08% 1.59% 1.26%
46 Asia JO Jordan 10 327 347 0.82% 1.01% 1.18%
47 South America PR Puerto Rico 3 193 694 1.30% 1.86% 1.15%
48 Europe DE Germany 84 112 776 0.62% 1.39% 1.14%
49 North America HN Honduras 10 097 597 1.26% 1.25% 1.08%
50 Europe FR France 65 450 818 1.90% 1.81% 1.03%
51 Europe PT Portugal 10 160 191 2.15% 1.66% 0.93%
52 Europe FI Finland 5 551 287 0.83% 1.04% 0.87%
53 Europe SE Sweden 10 176 531 0.82% 1.19% 0.86%
54 Asia IQ Iraq 41 326 988 1.95% 1.43% 0.84%
55 North America PA Panama 4 397 982 2.05% 1.10% 0.79%
56 Australia/Oceania AU Australia 25 862 611 0.24% 0.72% 0.78%
57 Europe IT Italy 60 352 641 0.74% 1.03% 0.76%
58 Asia LK Sri Lanka 21 523 439 1.56% 1.90% 0.74%
59 North America MX Mexico 130 593 779 0.92% 1.12% 0.73%
60 Asia PS Palestine 5 246 509 0.04% 0.16% 0.68%
61 Africa MA Morocco 37 446 899 1.09% 1.11% 0.67%
62 Africa TN Tunisia 11 970 259 3.04% 1.86% 0.66%
63 Europe DK Denmark 5 817 238 1.37% 1.13% 0.65%
64 Africa GA Gabon 2 289 987 0.17% 0.42% 0.62%
65 North America SV El Salvador 6 526 367 0.45% 0.57% 0.61%
66 Asia QA Qatar 2 807 805 0.70% 0.67% 0.60%
67 Asia LA Laos 7 404 932 0.25% 0.40% 0.54%
68 Europe ES Spain 46 777 014 2.70% 1.05% 0.53%
69 Europe HU Hungary 9 630 223 0.18% 0.36% 0.52%
70 Europe CZ Czechia 10 733 371 0.26% 0.39% 0.48%
71 South America AR Argentina 45 704 412 3.63% 0.92% 0.47%
72 Asia KH Cambodia 17 002 532 0.47% 0.39% 0.47%
73 South America VE Venezuela 28 336 978 0.47% 0.45% 0.47%
74 Asia AE Arab Emirates 10 036 893 1.72% 0.90% 0.46%
75 Asia KR South Korea 51 323 358 0.31% 0.42% 0.44%
76 South America UY Uruguay 3 488 506 3.33% 0.44% 0.44%
77 Asia MM Myanmar 54 857 308 0.57% 0.55% 0.40%
78 Asia NP Nepal 29 778 599 0.83% 0.50% 0.39%
79 Africa ZA South Africa 60 225 292 2.06% 1.18% 0.38%
80 South America CO Colombia 51 547 891 3.25% 0.41% 0.35%
81 Asia JP Japan 126 000 885 0.76% 1.11% 0.33%
82 South America CL Chile 19 317 467 1.58% 0.30% 0.32%
83 South America PE Peru 33 534 737 0.71% 0.32% 0.32%
84 North America DO Dominican R. 10 981 309 0.64% 0.29% 0.29%
85 Africa NA Namibia 2 597 257 2.82% 0.45% 0.29%
86 South America BO Bolivia 11 868 168 1.20% 0.37% 0.29%
87 Europe PL Poland 37 795 707 0.08% 0.15% 0.23%
88 Asia IN India 1 396 642 642 0.44% 0.30% 0.22%
89 Asia UZ Uzbekistan 34 063 596 0.21% 0.23% 0.19%
90 Africa RW Rwanda 13 344 941 0.52% 0.35% 0.17%
91 Asia SY Syria 18 020 715 0.04% 0.10% 0.17%
92 Asia KW Kuwait 4 347 960 2.49% 0.25% 0.16%
93 Asia KG Kyrgyzstan 6 656 051 1.12% 0.21% 0.14%
94 South America EC Ecuador 17 971 310 0.48% 0.18% 0.13%
95 North America NI Nicaragua 6 721 176 0.07% 0.13% 0.13%
96 Africa ZW Zimbabwe 15 128 052 0.59% 0.14% 0.13%
97 Asia PK Pakistan 226 143 767 0.14% 0.18% 0.13%
98 Africa MR Mauritania 4 799 110 0.34% 0.28% 0.13%
99 Asia ID Indonesia 277 070 139 0.87% 0.26% 0.12%
100 Africa GH Ghana 31 866 868 0.10% 0.13% 0.11%
101 Africa SO Somalia 16 435 281 0.03% 0.07% 0.11%
102 Asia BD Bangladesh 166 701 437 0.45% 0.18% 0.10%
103 Africa TG Togo 8 516 114 0.13% 0.22% 0.10%
104 Africa ET Ethiopia 118 446 782 0.05% 0.13% 0.09%
105 Africa CG Congo 5 684 226 0.04% 0.04% 0.09%
106 Australia/Oceania PG Papua New Guinea 9 154 546 0.04% 0.06% 0.09%
107 Asia OM Oman 5 265 467 1.72% 0.15% 0.08%
108 Africa EG Egypt 104 697 792 0.04% 0.05% 0.08%
109 South America PY Paraguay 7 239 939 1.67% 0.10% 0.06%
110 Africa AO Angola 34 115 371 0.06% 0.08% 0.06%
111 Africa LR Liberia 5 203 119 0.07% 0.03% 0.06%
112 Africa KE Kenya 55 220 784 0.14% 0.12% 0.05%
113 Africa BI Burundi 12 323 569 0.10% 0.16% 0.05%
114 Africa CI Ivory Coast 27 177 256 0.04% 0.08% 0.05%
115 Australia/Oceania NZ New Zealand 5 002 100 0.03% 0.08% 0.04%
116 Africa MG Madagascar 28 561 623 0.01% 0.01% 0.04%
117 Africa DZ Algeria 44 820 766 0.17% 0.08% 0.04%
118 Africa GW Guinea-Bissau 2 024 907 0.12% 0.10% 0.02%
119 Africa ZM Zambia 19 013 349 0.60% 0.07% 0.02%
120 North America HT Haiti 11 572 927 0.06% 0.02% 0.02%
121 Asia SA Saudi Arabia 35 478 133 0.29% 0.05% 0.02%
122 Africa GM Gambia 2 499 664 0.16% 0.07% 0.02%
123 Africa UG Uganda 47 505 768 0.16% 0.20% 0.02%
124 Africa MZ Mozambique 32 325 906 0.25% 0.08% 0.02%
125 Africa GN Guinea 13 568 332 0.05% 0.04% 0.02%
126 Asia YE Yemen 30 629 861 0.01% 0.02% 0.02%
127 Asia AF Afghanistan 40 001 151 0.22% 0.02% 0.02%
128 Africa NG Nigeria 212 389 018 0.02% 0.03% 0.01%
129 Africa MW Malawi 19 734 481 0.14% 0.03% 0.01%
130 Africa SS South Sudan 11 354 615 0.01% 0.02% 0.01%
131 Africa SN Senegal 17 283 486 0.19% 0.04% 0.01%
132 Africa CF Central African R. 4 932 617 0.09% 0.01% 0.01%
133 Africa BF Burkina Faso 21 604 044 0.00% 0.01% 0.01%
134 Africa SD Sudan 45 101 881 0.01% 0.00% 0.01%
135 Africa ML Mali 20 963 773 0.00% 0.01% 0.01%
136 Africa ER Eritrea 3 606 574 0.08% 0.01% 0.01%
137 Asia HK Hong Kong 7 571 588 0.00% 0.01% 0.01%
138 Asia TW Taiwan 23 869 696 0.04% 0.00% 0.00%
139 Africa NE Niger 25 276 238 0.00% 0.00% 0.00%
140 Africa CD DR Congo 92 888 530 0.03% 0.01% 0.00%
141 Africa LS Lesotho 2 163 081 0.17% 0.00% 0.00%
142 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
143 Africa TZ Tanzania 61 813 976 0.00% 0.00% 0.00%
144 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
145 Asia TJ Tajikistan 9 799 786 0.00% 0.00% 0.00%
146 Africa TD Chad 17 001 985 0.00% 0.00% 0.00%
147 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
148 Africa CM Cameroon 27 354 105 0.03% 0.04% 0.00%
149 Africa SL Sierra Leone 8 175 563 0.03% 0.00% 0.00%
150 Africa BJ Benin 12 511 506 0.11% 0.29% 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 South America PY Paraguay 7 239 939 5.34% 20.77% 0.10%
2 Asia YE Yemen 30 629 861 17.86% (19.83)% (0.02)%
3 Africa LR Liberia 5 203 119 5.48% (17.35)% (0.03)%
4 Africa SD Sudan 45 101 881 7.81% (16.45)% (0.00)%
5 Africa SO Somalia 16 435 281 8.31% (7.93)% (0.07)%
6 Africa LS Lesotho 2 163 081 2.14% (6.98)% (0.00)%
7 Africa NA Namibia 2 597 257 3.61% 6.24% 0.45%
8 Africa MW Malawi 19 734 481 4.11% (6.00)% (0.03)%
9 Africa SN Senegal 17 283 486 2.19% (5.94)% (0.04)%
10 Africa GM Gambia 2 499 664 3.98% (5.83)% (0.07)%
11 Africa MG Madagascar 28 561 623 5.81% (5.56)% (0.01)%
12 Asia SY Syria 18 020 715 6.92% 5.45% 0.10%
13 South America EC Ecuador 17 971 310 13.20% 5.41% 0.18%
14 Asia AF Afghanistan 40 001 151 4.82% (5.13)% (0.02)%
15 Africa DZ Algeria 44 820 766 3.03% (5.03)% (0.08)%
16 Africa ER Eritrea 3 606 574 0.93% (5.00)% (0.01)%
17 Asia TW Taiwan 23 869 696 5.88% (4.74)% (0.00)%
18 South America CL Chile 19 317 467 2.55% 4.58% 0.30%
19 North America MX Mexico 130 593 779 4.44% 4.57% 1.12%
20 Asia ID Indonesia 277 070 139 3.77% 4.32% 0.26%
21 Europe RU Russia 146 011 295 3.64% 4.18% 1.57%
22 Europe BG Bulgaria 6 884 168 4.32% 4.16% 2.58%
23 Africa EG Egypt 104 697 792 4.85% (4.13)% (0.05)%
24 South America PE Peru 33 534 737 6.55% 4.10% 0.32%
25 Africa ZW Zimbabwe 15 128 052 3.37% 4.07% 0.14%
26 Africa CG Congo 5 684 226 1.71% (3.96)% (0.04)%
27 Africa AO Angola 34 115 371 3.40% (3.92)% (0.08)%
28 North America HT Haiti 11 572 927 3.88% (3.72)% (0.02)%
29 Europe BA Bosnia and Herzegovina 3 255 745 5.51% 3.70% 2.43%
30 Europe MK North Macedonia 2 083 269 3.87% 3.69% 3.50%
31 Asia LK Sri Lanka 21 523 439 3.21% 3.42% 1.90%
32 Australia/Oceania PG Papua New Guinea 9 154 546 1.62% (3.42)% (0.06)%
33 Asia MM Myanmar 54 857 308 4.75% 3.38% 0.55%
34 Europe RO Romania 19 080 003 9.57% 3.25% 1.70%
35 Africa GN Guinea 13 568 332 2.97% (3.19)% (0.04)%
36 North America SV El Salvador 6 526 367 3.26% 3.08% 0.57%
37 Africa CI Ivory Coast 27 177 256 2.31% (2.86)% (0.08)%
38 Africa ML Mali 20 963 773 3.88% (2.82)% (0.01)%
39 Asia SA Saudi Arabia 35 478 133 1.26% (2.82)% (0.05)%
40 South America AR Argentina 45 704 412 2.13% 2.82% 0.92%
41 South America BO Bolivia 11 868 168 2.87% 2.81% 0.37%
42 Europe UA Ukraine 43 410 937 3.19% 2.74% 0.95%
43 Asia AM Armenia 2 970 042 2.62% 2.67% 2.36%
44 Africa TN Tunisia 11 970 259 3.33% 2.64% 1.86%
45 North America HN Honduras 10 097 597 2.67% 2.63% 1.25%
46 South America BR Brazil 214 413 077 2.64% 2.63% 1.28%
47 South America CO Colombia 51 547 891 2.25% 2.63% 0.41%
48 Africa GW Guinea-Bissau 2 024 907 2.69% (2.60)% (0.10)%
49 Africa ZA South Africa 60 225 292 2.42% 2.58% 1.18%
50 Asia VN Vietnam 98 412 739 2.76% 2.48% 1.46%
51 Africa NE Niger 25 276 238 1.55% (2.45)% (0.00)%
52 Asia KH Cambodia 17 002 532 2.53% 2.28% 0.39%
53 Africa NG Nigeria 212 389 018 1.69% (2.18)% (0.03)%
54 Asia KG Kyrgyzstan 6 656 051 1.07% 2.14% 0.21%
55 Asia PK Pakistan 226 143 767 2.11% 2.11% 0.18%
56 North America JM Jamaica 2 977 029 2.88% 2.07% 2.41%
57 Europe PL Poland 37 795 707 5.99% 2.07% 0.15%
58 Africa KE Kenya 55 220 784 2.44% 2.04% 0.12%
59 South America PR Puerto Rico 3 193 694 1.55% 1.95% 1.86%
60 Asia GE Georgia 3 979 763 1.58% 1.89% 7.61%
61 Africa MR Mauritania 4 799 110 1.88% 1.85% 0.28%
62 Asia OM Oman 5 265 467 1.88% 1.83% 0.15%
63 Asia KZ Kazakhstan 19 052 041 1.65% 1.80% 2.69%
64 Asia IR Iran 85 310 713 1.52% 1.76% 3.46%
65 Asia BD Bangladesh 166 701 437 1.97% 1.74% 0.18%
66 Africa CF Central African R. 4 932 617 0.07% 1.72% 0.01%
67 Europe LT Lithuania 2 675 585 1.45% 1.68% 4.09%
68 Asia MY Malaysia 32 874 297 1.42% 1.67% 6.85%
69 Europe MD Moldova 4 022 448 2.25% 1.66% 2.12%
70 Africa ET Ethiopia 118 446 782 1.79% 1.64% 0.13%
71 North America GT Guatemala 18 321 394 1.84% 1.56% 2.03%
72 Africa MA Morocco 37 446 899 1.25% 1.50% 1.11%
73 Europe HU Hungary 9 630 223 2.96% 1.48% 0.36%
74 South America VE Venezuela 28 336 978 1.35% 1.42% 0.45%
75 Africa SS South Sudan 11 354 615 1.14% 1.41% 0.02%
76 Europe GR Greece 10 360 506 1.11% 1.40% 2.82%
77 Africa RW Rwanda 13 344 941 1.28% 1.34% 0.35%
78 Africa GH Ghana 31 866 868 1.15% 1.32% 0.13%
79 Asia JO Jordan 10 327 347 1.50% 1.32% 1.01%
80 Asia TH Thailand 70 014 978 1.14% 1.24% 2.48%
81 Europe HR Croatia 4 074 161 1.58% 1.18% 2.63%
82 Asia TR Turkey 85 451 829 0.97% 1.16% 3.31%
83 North America PA Panama 4 397 982 0.91% 1.16% 1.10%
84 North America CR Costa Rica 5 151 169 1.08% 1.15% 5.49%
85 Africa LY Libya 6 985 807 1.00% 1.14% 2.07%
86 North America US USA 333 384 277 1.03% 1.09% 5.37%
87 Asia AZ Azerbaijan 10 251 263 1.11% 1.09% 3.10%
88 Asia NP Nepal 29 778 599 1.40% 1.09% 0.50%
89 Africa ZM Zambia 19 013 349 2.05% 1.06% 0.07%
90 Africa CM Cameroon 27 354 105 1.13% 1.01% 0.04%
91 Europe IT Italy 60 352 641 1.09% 0.98% 1.03%
92 Africa BF Burkina Faso 21 604 044 1.38% 0.98% 0.01%
93 North America CU Cuba 11 318 126 0.95% 0.98% 8.12%
94 Asia IQ Iraq 41 326 988 0.70% 0.95% 1.43%
95 Asia IN India 1 396 642 642 1.72% 0.94% 0.30%
96 Africa MZ Mozambique 32 325 906 1.35% 0.94% 0.08%
97 Asia PH Philippines 111 368 677 1.49% 0.92% 2.03%
98 Europe ES Spain 46 777 014 0.42% 0.92% 1.05%
99 Asia HK Hong Kong 7 571 588 0.93% 0.91% 0.01%
100 Asia KW Kuwait 4 347 960 0.60% 0.89% 0.25%
101 South America UY Uruguay 3 488 506 1.47% 0.88% 0.44%
102 Asia LB Lebanon 6 787 896 0.72% 0.79% 1.57%
103 Asia UZ Uzbekistan 34 063 596 0.76% 0.78% 0.23%
104 Europe BY Belarus 9 445 506 0.96% 0.74% 2.23%
105 North America CA Canada 38 148 028 1.00% 0.69% 1.22%
106 Africa UG Uganda 47 505 768 3.52% 0.69% 0.20%
107 Africa TG Togo 8 516 114 0.82% 0.68% 0.22%
108 Africa GA Gabon 2 289 987 0.80% 0.65% 0.42%
109 Africa BW Botswana 2 409 754 1.30% 0.63% 4.25%
110 Europe RS Serbia 8 694 138 0.81% 0.63% 6.75%
111 Europe SK Slovakia 5 462 889 2.13% 0.62% 0.91%
112 Europe AL Albania 2 873 938 0.57% 0.54% 3.53%
113 Australia/Oceania AU Australia 25 862 611 0.57% 0.53% 0.72%
114 Europe PT Portugal 10 160 191 0.42% 0.53% 1.66%
115 Africa CD DR Congo 92 888 530 1.12% 0.50% 0.01%
116 Europe FR France 65 450 818 0.47% 0.47% 1.81%
117 Europe CZ Czechia 10 733 371 0.68% 0.44% 0.39%
118 Europe DE Germany 84 112 776 1.07% 0.43% 1.39%
119 Europe GB United Kingdom 68 323 609 0.28% 0.39% 5.92%
120 Asia KR South Korea 51 323 358 0.33% 0.37% 0.42%
121 North America DO Dominican R. 10 981 309 0.55% 0.37% 0.29%
122 Europe AT Austria 9 069 454 0.41% 0.35% 2.32%
123 Asia JP Japan 126 000 885 0.49% 0.35% 1.11%
124 Europe SE Sweden 10 176 531 0.29% 0.34% 1.19%
125 Europe DK Denmark 5 817 238 0.15% 0.33% 1.13%
126 Europe BE Belgium 11 651 525 0.36% 0.32% 1.96%
127 Europe SI Slovenia 2 079 289 0.47% 0.30% 4.44%
128 Asia IL Israel 9 326 000 0.32% 0.29% 10.43%
129 Europe IE Ireland 5 005 412 0.23% 0.28% 3.55%
130 North America NI Nicaragua 6 721 176 0.38% 0.24% 0.13%
131 Europe NL Netherlands 17 181 414 0.15% 0.24% 1.59%
132 Asia SG Singapore 5 906 782 0.29% 0.23% 1.09%
133 Asia MN Mongolia 3 342 965 0.38% 0.23% 11.16%
134 Europe CH Switzerland 8 732 267 0.23% 0.22% 2.98%
135 Asia AE Arab Emirates 10 036 893 0.23% 0.21% 0.90%
136 Africa BJ Benin 12 511 506 0.34% 0.15% 0.29%
137 Europe FI Finland 5 551 287 0.21% 0.14% 1.04%
138 Europe NO Norway 5 473 241 0.11% 0.11% 2.43%
139 Australia/Oceania NZ New Zealand 5 002 100 0.07% 0.09% 0.08%
140 Asia LA Laos 7 404 932 0.09% 0.07% 0.40%
141 Asia QA Qatar 2 807 805 0.25% 0.06% 0.67%
142 Africa BI Burundi 12 323 569 0.05% 0.03% 0.16%
143 Africa SL Sierra Leone 8 175 563 1.84% 0.00% 0.00%
144 Africa TD Chad 17 001 985 0.85% 0.00% 0.00%
145 Asia PS Palestine 5 246 509 0.00% 0.00% 0.16%
146 Africa TZ Tanzania 61 813 976 3.38% 0.00% 0.00%
147 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
148 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
149 Asia TJ Tajikistan 9 799 786 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 33 534 737 199 108 5.937
2 Europe BA Bosnia and Herzegovina 3 255 745 10 379 3.188
3 Europe MK North Macedonia 2 083 269 6 539 3.139
4 Europe HU Hungary 9 630 223 30 151 3.131
5 Europe BG Bulgaria 6 884 168 20 350 2.956
6 Europe CZ Czechia 10 733 371 30 450 2.837
7 South America BR Brazil 214 413 077 592 101 2.761
8 South America AR Argentina 45 704 412 114 667 2.509
9 South America CO Colombia 51 547 891 125 988 2.444
10 Europe SI Slovenia 2 079 289 4 832 2.324
11 Europe SK Slovakia 5 462 889 12 594 2.305
12 South America PY Paraguay 7 239 939 16 137 2.229
13 Asia GE Georgia 3 979 763 8 749 2.198
14 Europe BE Belgium 11 651 525 25 543 2.192
15 Europe IT Italy 60 352 641 130 551 2.163
16 Europe HR Croatia 4 074 161 8 566 2.103
17 North America MX Mexico 130 593 779 273 328 2.093
18 Africa TN Tunisia 11 970 259 24 676 2.061
19 North America US USA 333 384 277 675 702 2.027
20 Europe PL Poland 37 795 707 75 551 1.999
21 Europe GB United Kingdom 68 323 609 135 803 1.988
22 South America CL Chile 19 317 467 37 410 1.937
23 Europe RO Romania 19 080 003 35 964 1.885
24 Europe ES Spain 46 777 014 86 185 1.843
25 Europe LT Lithuania 2 675 585 4 880 1.824
26 South America EC Ecuador 17 971 310 32 661 1.817
27 Europe PT Portugal 10 160 191 17 938 1.766
28 Asia AM Armenia 2 970 042 5 216 1.756
29 Europe FR France 65 450 818 114 195 1.745
30 South America UY Uruguay 3 488 506 6 049 1.734
31 Europe MD Moldova 4 022 448 6 649 1.653
32 North America PA Panama 4 397 982 7 187 1.634
33 South America BO Bolivia 11 868 168 18 679 1.574
34 Europe SE Sweden 10 176 531 14 809 1.455
35 Africa ZA South Africa 60 225 292 86 371 1.434
36 Europe GR Greece 10 360 506 14 606 1.410
37 Asia IR Iran 85 310 713 118 508 1.389
38 Europe RU Russia 146 011 295 202 273 1.385
39 Africa NA Namibia 2 597 257 3 481 1.340
40 Europe UA Ukraine 43 410 937 55 424 1.277
41 Asia LB Lebanon 6 787 896 8 260 1.217
42 Europe CH Switzerland 8 732 267 10 591 1.213
43 North America CR Costa Rica 5 151 169 6 138 1.192
44 Europe AT Austria 9 069 454 10 717 1.182
45 Europe DE Germany 84 112 776 93 315 1.109
46 Europe NL Netherlands 17 181 414 18 144 1.056
47 Europe IE Ireland 5 005 412 5 209 1.041
48 Asia JO Jordan 10 327 347 10 645 1.031
49 Africa BW Botswana 2 409 754 2 360 0.979
50 South America PR Puerto Rico 3 193 694 3 105 0.972
51 North America HN Honduras 10 097 597 9 595 0.950
52 Europe RS Serbia 8 694 138 7 926 0.912
53 Europe AL Albania 2 873 938 2 609 0.908
54 Asia IL Israel 9 326 000 7 611 0.816
55 Asia KZ Kazakhstan 19 052 041 15 503 0.814
56 Asia OM Oman 5 265 467 4 093 0.777
57 Asia MY Malaysia 32 874 297 24 681 0.751
58 Asia TR Turkey 85 451 829 62 524 0.732
59 North America CA Canada 38 148 028 27 532 0.722
60 North America GT Guatemala 18 321 394 13 171 0.719
61 Africa LY Libya 6 985 807 4 579 0.655
62 Asia AZ Azerbaijan 10 251 263 6 394 0.624
63 North America CU Cuba 11 318 126 7 048 0.623
64 North America JM Jamaica 2 977 029 1 809 0.608
65 Asia LK Sri Lanka 21 523 439 12 448 0.578
66 Asia KW Kuwait 4 347 960 2 443 0.562
67 Asia IQ Iraq 41 326 988 21 993 0.532
68 Asia ID Indonesia 277 070 139 141 258 0.510
69 North America SV El Salvador 6 526 367 3 150 0.483
70 Europe DK Denmark 5 817 238 2 638 0.454
71 Europe BY Belarus 9 445 506 4 054 0.429
72 Asia KG Kyrgyzstan 6 656 051 2 597 0.390
73 Africa MA Morocco 37 446 899 14 076 0.376
74 Asia NP Nepal 29 778 599 11 081 0.372
75 North America DO Dominican R. 10 981 309 4 031 0.367
76 Asia PH Philippines 111 368 677 37 228 0.334
77 Asia MN Mongolia 3 342 965 1 098 0.329
78 Asia IN India 1 396 642 642 446 050 0.319
79 Asia MM Myanmar 54 857 308 17 343 0.316
80 Africa ZW Zimbabwe 15 128 052 4 577 0.303
81 Asia SA Saudi Arabia 35 478 133 8 684 0.245
82 Asia TH Thailand 70 014 978 16 016 0.229
83 Asia QA Qatar 2 807 805 604 0.215
84 Asia AE Arab Emirates 10 036 893 2 083 0.207
85 Africa ZM Zambia 19 013 349 3 641 0.192
86 Europe FI Finland 5 551 287 1 062 0.191
87 Africa LS Lesotho 2 163 081 403 0.186
88 Asia VN Vietnam 98 412 739 18 017 0.183
89 Asia AF Afghanistan 40 001 151 7 199 0.180
90 Asia BD Bangladesh 166 701 437 27 337 0.164
91 Africa EG Egypt 104 697 792 17 074 0.163
92 Africa MR Mauritania 4 799 110 766 0.160
93 Europe NO Norway 5 473 241 850 0.155
94 South America VE Venezuela 28 336 978 4 346 0.153
95 Asia JP Japan 126 000 885 17 375 0.138
96 Africa GM Gambia 2 499 664 333 0.133
97 Asia KH Cambodia 17 002 532 2 175 0.128
98 Africa DZ Algeria 44 820 766 5 718 0.128
99 Asia PK Pakistan 226 143 767 27 424 0.121
100 Asia SY Syria 18 020 715 2 172 0.120
101 Africa MW Malawi 19 734 481 2 265 0.115
102 Africa SN Senegal 17 283 486 1 849 0.107
103 Africa RW Rwanda 13 344 941 1 223 0.092
104 Africa KE Kenya 55 220 784 5 022 0.091
105 Africa GA Gabon 2 289 987 176 0.077
106 Africa SO Somalia 16 435 281 1 099 0.067
107 Africa UG Uganda 47 505 768 3 134 0.066
108 Africa GW Guinea-Bissau 2 024 907 130 0.064
109 Africa SD Sudan 45 101 881 2 848 0.063
110 Africa MZ Mozambique 32 325 906 1 904 0.059
111 Africa LR Liberia 5 203 119 283 0.054
112 Asia YE Yemen 30 629 861 1 664 0.054
113 North America HT Haiti 11 572 927 607 0.052
114 Africa CM Cameroon 27 354 105 1 368 0.050
115 Asia KR South Korea 51 323 358 2 434 0.047
116 Australia/Oceania AU Australia 25 862 611 1 198 0.046
117 Africa ET Ethiopia 118 446 782 5 201 0.044
118 Africa AO Angola 34 115 371 1 435 0.042
119 Africa GH Ghana 31 866 868 1 134 0.036
120 Asia UZ Uzbekistan 34 063 596 1 212 0.036
121 Asia TW Taiwan 23 869 696 841 0.035
122 Africa CG Congo 5 684 226 191 0.034
123 Africa MG Madagascar 28 561 623 958 0.034
124 North America NI Nicaragua 6 721 176 203 0.030
125 Asia HK Hong Kong 7 571 588 213 0.028
126 Africa GN Guinea 13 568 332 376 0.028
127 Africa ML Mali 20 963 773 545 0.026
128 Africa TG Togo 8 516 114 215 0.025
129 Australia/Oceania PG Papua New Guinea 9 154 546 225 0.025
130 Africa CI Ivory Coast 27 177 256 572 0.021
131 Africa CF Central African R. 4 932 617 100 0.020
132 Africa SL Sierra Leone 8 175 563 121 0.015
133 Africa NG Nigeria 212 389 018 2 663 0.013
134 Asia SG Singapore 5 906 782 70 0.012
135 Africa BJ Benin 12 511 506 146 0.012
136 Africa CD DR Congo 92 888 530 1 068 0.011
137 Africa SS South Sudan 11 354 615 128 0.011
138 Africa ER Eritrea 3 606 574 40 0.011
139 Africa TD Chad 17 001 985 174 0.010
140 Africa BF Burkina Faso 21 604 044 174 0.008
141 Africa NE Niger 25 276 238 201 0.008
142 Australia/Oceania NZ New Zealand 5 002 100 27 0.005
143 Asia PS Palestine 5 246 509 12 0.002
144 Asia LA Laos 7 404 932 16 0.002
145 Africa BI Burundi 12 323 569 12 0.001
146 Africa TZ Tanzania 61 813 976 50 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 9 799 786 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] , [*], [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"