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": 2021-09-21 15:29
(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 +1 240 (+1 399) +22 (+1)
CZ Czechia +489 (+184) +4 (+1)
DE Germany +0 (+5 303) +0 (+47)
HU Hungary +289 (+1 072) +5 (+13)
PL Poland +711 (+361) +15 (+0)
SK Slovakia, [gov], [okr]+880 (+114) +7 (+4)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 North America 594 305 826 1.94% 3.30% 1.65%
2 Europe 756 187 886 1.47% 1.74% 1.10%
3 Australia/Oceania 43 409 727 0.32% 0.59% 0.44%
4 South America 438 339 308 2.22% 0.73% 0.30%
5 Asia 4 675 774 781 0.52% 0.52% 0.28%
6 Africa 1 378 973 540 0.25% 0.19% 0.11%

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 438 339 308 2.65% 3.50% 0.73%
2 Africa 1 378 973 540 2.28% 2.98% 0.19%
3 Asia 4 675 774 781 1.71% 1.84% 0.52%
4 North America 594 305 826 1.34% 1.53% 3.30%
5 Europe 756 187 886 1.21% 1.45% 1.74%
6 Australia/Oceania 43 409 727 1.02% 1.32% 0.59%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 438 339 308 1 147 281 2.617
2 North America 594 305 826 1 016 125 1.710
3 Europe 756 187 886 1 201 624 1.589
4 Asia 4 675 774 781 1 088 600 0.233
5 Africa 1 378 973 540 205 557 0.149
6 Australia/Oceania 43 409 727 2 712 0.063

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 IL Israel 9 326 000 4.24% 10.70% 9.38%
2 Asia MN Mongolia 3 342 532 7.14% 11.89% 9.19%
3 Europe RS Serbia 8 694 425 1.65% 5.17% 5.95%
4 Africa BW Botswana 2 409 364 4.97% 4.54% 5.79%
5 North America CU Cuba 11 318 183 5.76% 7.45% 4.71%
6 Europe SI Slovenia 2 079 287 1.45% 3.57% 4.45%
7 Asia GE Georgia 3 979 825 6.44% 7.99% 3.96%
8 Asia MY Malaysia 32 870 898 4.72% 6.43% 3.56%
9 Europe LT Lithuania 2 675 894 1.63% 3.15% 3.20%
10 Europe GB United Kingdom 68 320 692 4.26% 5.35% 2.97%
11 Europe HR Croatia 4 074 367 0.90% 2.05% 2.37%
12 North America US USA 333 368 397 2.58% 4.79% 2.35%
13 North America CR Costa Rica 5 150 788 3.87% 4.68% 2.33%
14 Asia TR Turkey 85 444 394 1.88% 2.80% 2.24%
15 Asia KZ Kazakhstan 19 050 201 2.66% 3.22% 2.15%
16 Europe AL Albania 2 873 964 1.00% 3.07% 2.02%
17 Europe BG Bulgaria 6 884 595 0.94% 2.34% 1.99%
18 Europe MD Moldova 4 022 524 0.63% 1.57% 1.93%
19 Europe RO Romania 19 081 049 0.37% 1.16% 1.77%
20 Europe GR Greece 10 360 922 2.24% 2.64% 1.73%
21 Europe IE Ireland 5 004 960 2.34% 3.28% 1.69%
22 Asia AM Armenia 2 969 997 1.03% 2.01% 1.60%
23 Europe BA Bosnia and Herzegovina 3 255 911 0.67% 1.92% 1.59%
24 Europe MK North Macedonia 2 083 270 1.47% 3.38% 1.56%
25 Asia IR Iran 85 301 901 3.01% 3.54% 1.56%
26 Europe AT Austria 9 069 033 0.88% 1.98% 1.52%
27 South America PR Puerto Rico 3 193 694 1.28% 2.35% 1.51%
28 Europe BY Belarus 9 445 532 1.34% 1.86% 1.35%
29 North America JM Jamaica 2 976 923 1.03% 2.34% 1.31%
30 Asia TH Thailand 70 013 547 1.90% 2.34% 1.30%
31 Africa LY Libya 6 985 041 2.10% 2.08% 1.15%
32 Asia PH Philippines 111 356 721 1.02% 1.79% 1.12%
33 Asia AZ Azerbaijan 10 250 514 1.32% 3.10% 1.11%
34 Asia SG Singapore 5 906 406 0.24% 0.63% 1.01%
35 North America GT Guatemala 18 318 673 1.50% 1.93% 0.96%
36 Europe SE Sweden 10 176 015 0.81% 1.08% 0.94%
37 Europe CH Switzerland 8 731 749 1.51% 2.92% 0.93%
38 Europe SK Slovakia 5 462 867 0.24% 0.59% 0.91%
39 Europe RU Russia 146 010 784 1.54% 1.39% 0.91%
40 Europe UA Ukraine 43 413 079 0.37% 0.63% 0.88%
41 Europe DE Germany 84 110 585 0.57% 1.25% 0.85%
42 Europe NO Norway 5 472 894 1.06% 2.33% 0.84%
43 North America HN Honduras 10 096 305 1.22% 1.15% 0.83%
44 Europe NL Netherlands 17 181 104 2.07% 1.51% 0.82%
45 Africa UG Uganda 47 493 871 0.16% 0.20% 0.81%
46 Europe BE Belgium 11 651 112 1.41% 1.74% 0.80%
47 Asia VN Vietnam 98 405 568 0.67% 1.35% 0.75%
48 Asia LK Sri Lanka 21 522 704 1.55% 2.05% 0.74%
49 Europe FI Finland 5 551 217 0.81% 1.02% 0.73%
50 Europe FR France 65 449 638 1.87% 1.85% 0.73%
51 North America CA Canada 38 145 318 0.54% 1.02% 0.72%
52 Asia JO Jordan 10 326 517 0.79% 0.90% 0.71%
53 Africa GA Gabon 2 289 555 0.16% 0.37% 0.65%
54 Asia PS Palestine 5 245 535 0.04% 0.15% 0.65%
55 Asia IQ Iraq 41 319 572 1.94% 1.46% 0.63%
56 Europe PT Portugal 10 160 433 2.11% 1.67% 0.61%
57 Asia LB Lebanon 6 788 145 1.14% 1.46% 0.59%
58 Europe IT Italy 60 353 366 0.72% 0.97% 0.46%
59 Australia/Oceania AU Australia 25 860 187 0.20% 0.60% 0.45%
60 North America MX Mexico 130 582 682 0.88% 1.07% 0.44%
61 Africa ZA South Africa 60 219 163 2.06% 1.29% 0.40%
62 North America PA Panama 4 397 424 2.03% 1.09% 0.40%
63 Europe DK Denmark 5 817 071 1.39% 1.19% 0.38%
64 South America AR Argentina 45 701 016 3.76% 0.96% 0.38%
65 Europe ES Spain 46 776 866 2.69% 1.10% 0.37%
66 Asia AE Arab Emirates 10 035 914 1.75% 0.93% 0.36%
67 South America BR Brazil 214 400 711 2.33% 0.96% 0.34%
68 Europe CZ Czechia 10 733 209 0.25% 0.31% 0.34%
69 Asia QA Qatar 2 807 805 0.71% 0.67% 0.34%
70 Africa MA Morocco 37 443 314 1.05% 1.13% 0.32%
71 Africa BI Burundi 12 320 654 0.10% 0.20% 0.30%
72 Europe HU Hungary 9 630 423 0.16% 0.28% 0.28%
73 Asia JP Japan 126 004 044 0.75% 1.23% 0.28%
74 South America UY Uruguay 3 488 408 3.59% 0.39% 0.28%
75 Asia KH Cambodia 17 000 635 0.45% 0.33% 0.27%
76 Asia NP Nepal 29 774 298 0.89% 0.49% 0.27%
77 South America VE Venezuela 28 337 635 0.46% 0.40% 0.26%
78 Asia KR South Korea 51 322 998 0.29% 0.37% 0.26%
79 Asia MM Myanmar 54 854 323 0.55% 0.52% 0.25%
80 Africa BJ Benin 12 508 895 0.11% 0.36% 0.22%
81 Africa RW Rwanda 13 342 302 0.51% 0.36% 0.21%
82 Asia LA Laos 7 404 066 0.22% 0.34% 0.19%
83 South America BO Bolivia 11 866 863 1.25% 0.35% 0.19%
84 South America CO Colombia 51 543 448 3.35% 0.40% 0.18%
85 North America DO Dominican R. 10 980 418 0.65% 0.26% 0.18%
86 Africa NA Namibia 2 596 880 2.84% 0.48% 0.16%
87 South America PE Peru 33 530 971 0.72% 0.29% 0.15%
88 South America CL Chile 19 316 124 1.64% 0.27% 0.14%
89 Africa ZW Zimbabwe 15 126 278 0.59% 0.14% 0.14%
90 Europe PL Poland 37 796 045 0.08% 0.11% 0.13%
91 Australia/Oceania PG Papua New Guinea 9 153 155 0.04% 0.06% 0.13%
92 North America NI Nicaragua 6 720 530 0.07% 0.10% 0.13%
93 Asia UZ Uzbekistan 34 059 619 0.20% 0.22% 0.12%
94 Asia IN India 1 396 531 521 0.47% 0.27% 0.11%
95 Africa MR Mauritania 4 798 105 0.34% 0.30% 0.11%
96 Africa LR Liberia 5 202 142 0.07% 0.04% 0.10%
97 Africa TG Togo 8 514 519 0.13% 0.24% 0.10%
98 Asia KW Kuwait 4 347 442 2.57% 0.27% 0.09%
99 Asia KG Kyrgyzstan 6 655 168 1.13% 0.22% 0.09%
100 Asia ID Indonesia 277 046 446 0.87% 0.30% 0.09%
101 Africa ET Ethiopia 118 423 370 0.05% 0.12% 0.08%
102 Africa AO Angola 34 106 951 0.06% 0.07% 0.08%
103 Africa GW Guinea-Bissau 2 024 525 0.11% 0.17% 0.08%
104 Asia PK Pakistan 226 108 553 0.14% 0.17% 0.08%
105 Africa CM Cameroon 27 348 672 0.03% 0.04% 0.08%
106 Asia BD Bangladesh 166 687 998 0.45% 0.19% 0.07%
107 Africa SO Somalia 16 431 633 0.03% 0.06% 0.07%
108 Africa TN Tunisia 11 969 246 2.93% 1.52% 0.07%
109 Asia SY Syria 18 017 220 0.03% 0.08% 0.07%
110 Asia OM Oman 5 264 399 1.77% 0.17% 0.06%
111 South America EC Ecuador 17 969 113 0.48% 0.16% 0.06%
112 Africa KE Kenya 55 211 053 0.14% 0.12% 0.05%
113 South America PY Paraguay 7 239 221 1.78% 0.11% 0.04%
114 Africa EG Egypt 104 681 948 0.04% 0.03% 0.04%
115 Africa ZM Zambia 19 009 112 0.61% 0.08% 0.04%
116 Africa DZ Algeria 44 814 267 0.17% 0.09% 0.03%
117 Africa CI Ivory Coast 27 171 886 0.04% 0.08% 0.03%
118 Africa MZ Mozambique 32 318 701 0.25% 0.09% 0.03%
119 Africa GN Guinea 13 565 401 0.05% 0.05% 0.03%
120 Australia/Oceania NZ New Zealand 5 002 100 0.03% 0.08% 0.02%
121 North America HT Haiti 11 571 788 0.07% 0.02% 0.02%
122 Africa GM Gambia 2 499 105 0.16% 0.07% 0.02%
123 Africa SS South Sudan 11 353 540 0.01% 0.02% 0.02%
124 Asia SA Saudi Arabia 35 473 686 0.30% 0.05% 0.02%
125 Africa GH Ghana 31 861 540 0.10% 0.13% 0.02%
126 Asia AF Afghanistan 39 993 948 0.22% 0.02% 0.02%
127 Africa NG Nigeria 212 347 013 0.02% 0.03% 0.02%
128 Africa MW Malawi 19 730 416 0.14% 0.04% 0.01%
129 Africa CF Central African R. 4 931 928 0.09% 0.01% 0.01%
130 Asia YE Yemen 30 624 464 0.01% 0.01% 0.01%
131 Africa ER Eritrea 3 606 172 0.08% 0.01% 0.01%
132 Africa SN Senegal 17 279 857 0.19% 0.04% 0.01%
133 Africa CD DR Congo 92 866 111 0.03% 0.01% 0.01%
134 Africa BF Burkina Faso 21 599 329 0.00% 0.01% 0.00%
135 Asia HK Hong Kong 7 571 090 0.00% 0.01% 0.00%
136 Asia TW Taiwan 23 869 343 0.05% 0.00% 0.00%
137 Africa ML Mali 20 958 972 0.00% 0.01% 0.00%
138 Africa TD Chad 16 998 106 0.00% 0.00% 0.00%
139 Africa NE Niger 25 269 012 0.00% 0.00% 0.00%
140 Africa SL Sierra Leone 8 174 231 0.03% 0.00% 0.00%
141 Africa SD Sudan 45 093 467 0.01% 0.00% 0.00%
142 Africa LS Lesotho 2 162 942 0.17% 0.01% 0.00%
143 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
144 Africa TZ Tanzania 61 799 974 0.00% 0.00% 0.00%
145 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
146 Asia TJ Tajikistan 9 798 026 0.00% 0.00% 0.00%
147 North America SV El Salvador 6 526 099 0.42% 0.43% 0.00%
148 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
149 Africa CG Congo 5 683 109 0.04% 0.02% 0.00%
150 Africa MG Madagascar 28 555 768 0.01% 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 South America PY Paraguay 7 239 221 5.35% 21.16% 0.11%
2 Asia YE Yemen 30 624 464 16.60% (17.70)% (0.01)%
3 Africa LR Liberia 5 202 142 5.50% (17.04)% (0.04)%
4 Africa SD Sudan 45 093 467 7.84% (12.66)% (0.00)%
5 Africa SO Somalia 16 431 633 7.46% (7.59)% (0.06)%
6 Africa MW Malawi 19 730 416 4.09% (6.02)% (0.04)%
7 Africa SN Senegal 17 279 857 2.19% (5.99)% (0.04)%
8 Africa UG Uganda 47 493 871 4.86% 5.82% 0.20%
9 Africa GM Gambia 2 499 105 3.95% (5.51)% (0.07)%
10 Asia AF Afghanistan 39 993 948 4.83% (5.50)% (0.02)%
11 Africa ER Eritrea 3 606 172 0.92% (5.36)% (0.01)%
12 Africa NA Namibia 2 596 880 3.57% 5.01% 0.48%
13 Africa DZ Algeria 44 814 267 3.00% (5.00)% (0.09)%
14 Africa ZW Zimbabwe 15 126 278 3.39% 4.98% 0.14%
15 Asia TW Taiwan 23 869 343 5.76% (4.88)% (0.00)%
16 South America EC Ecuador 17 969 113 13.00% 4.58% 0.16%
17 Asia SY Syria 18 017 220 6.46% (4.43)% (0.08)%
18 Asia ID Indonesia 277 046 446 3.74% 4.36% 0.30%
19 South America CL Chile 19 316 124 2.45% 4.28% 0.27%
20 Africa AO Angola 34 106 951 3.35% (4.21)% (0.07)%
21 North America MX Mexico 130 582 682 4.29% 4.08% 1.07%
22 Europe BG Bulgaria 6 884 595 4.26% 3.84% 2.34%
23 South America PE Peru 33 530 971 6.69% 3.83% 0.29%
24 Europe RU Russia 146 010 784 3.53% 3.72% 1.39%
25 Africa EG Egypt 104 681 948 4.68% (3.47)% (0.03)%
26 Asia LK Sri Lanka 21 522 704 3.09% 3.34% 2.05%
27 Africa GW Guinea-Bissau 2 024 525 2.80% 3.29% 0.17%
28 Europe BA Bosnia and Herzegovina 3 255 911 5.53% 3.24% 1.92%
29 Europe MK North Macedonia 2 083 270 3.68% 3.24% 3.38%
30 Australia/Oceania PG Papua New Guinea 9 153 155 1.36% (3.24)% (0.06)%
31 Asia MM Myanmar 54 854 323 4.70% 3.19% 0.52%
32 Africa ML Mali 20 958 972 3.90% (3.08)% (0.01)%
33 Africa GN Guinea 13 565 401 2.97% (3.03)% (0.05)%
34 Africa TN Tunisia 11 969 246 3.35% 2.79% 1.52%
35 Africa CI Ivory Coast 27 171 886 2.18% (2.69)% (0.08)%
36 South America AR Argentina 45 701 016 2.09% 2.66% 0.96%
37 South America BO Bolivia 11 866 863 2.88% 2.63% 0.35%
38 Europe RO Romania 19 081 049 3.36% 2.62% 1.16%
39 Europe UA Ukraine 43 413 079 3.30% 2.59% 0.63%
40 North America SV El Salvador 6 526 099 3.05% 2.57% 0.43%
41 Asia VN Vietnam 98 405 568 2.68% 2.54% 1.35%
42 South America CO Colombia 51 543 448 2.27% 2.53% 0.40%
43 Africa ZA South Africa 60 219 163 2.41% 2.48% 1.29%
44 Africa NE Niger 25 269 012 1.51% (2.42)% (0.00)%
45 Asia AM Armenia 2 969 997 2.51% 2.41% 2.01%
46 North America HN Honduras 10 096 305 2.62% 2.37% 1.15%
47 Africa MG Madagascar 28 555 768 5.32% (2.33)% (0.00)%
48 South America BR Brazil 214 400 711 2.60% 2.25% 0.96%
49 Asia SA Saudi Arabia 35 473 686 1.24% (2.24)% (0.05)%
50 Africa NG Nigeria 212 347 013 1.73% (2.24)% (0.03)%
51 North America JM Jamaica 2 976 923 2.93% 2.09% 2.34%
52 Africa KE Kenya 55 211 053 2.43% 2.08% 0.12%
53 Asia KH Cambodia 17 000 635 2.47% 2.08% 0.33%
54 North America HT Haiti 11 571 788 4.03% (2.04)% (0.02)%
55 Asia PK Pakistan 226 108 553 2.07% 1.98% 0.17%
56 Asia OM Oman 5 264 399 1.87% 1.94% 0.17%
57 Asia KG Kyrgyzstan 6 655 168 1.08% 1.94% 0.22%
58 Europe PL Poland 37 796 045 6.48% 1.89% 0.11%
59 Asia KZ Kazakhstan 19 050 201 1.58% 1.80% 3.22%
60 Africa MR Mauritania 4 798 105 1.88% 1.76% 0.30%
61 Africa CF Central African R. 4 931 928 0.07% 1.72% 0.01%
62 Africa CM Cameroon 27 348 672 1.85% 1.71% 0.04%
63 South America PR Puerto Rico 3 193 694 1.53% 1.69% 2.35%
64 Asia GE Georgia 3 979 825 1.52% 1.66% 7.99%
65 Europe MD Moldova 4 022 524 2.32% 1.64% 1.57%
66 Asia BD Bangladesh 166 687 998 1.96% 1.64% 0.19%
67 Asia IR Iran 85 301 901 1.47% 1.62% 3.54%
68 North America GT Guatemala 18 318 673 1.83% 1.56% 1.93%
69 Africa ET Ethiopia 118 423 370 1.77% 1.55% 0.12%
70 Europe HU Hungary 9 630 423 3.29% 1.48% 0.28%
71 Europe LT Lithuania 2 675 894 1.34% 1.47% 3.15%
72 Asia MY Malaysia 32 870 898 1.34% 1.43% 6.43%
73 Africa MA Morocco 37 443 314 1.19% 1.38% 1.13%
74 Africa RW Rwanda 13 342 302 1.27% 1.36% 0.36%
75 South America VE Venezuela 28 337 635 1.32% 1.27% 0.40%
76 Europe GR Greece 10 360 922 1.09% 1.25% 2.64%
77 Asia TH Thailand 70 013 547 1.12% 1.19% 2.34%
78 Asia JO Jordan 10 326 517 1.46% 1.18% 0.90%
79 Africa GH Ghana 31 861 540 1.04% 1.12% 0.13%
80 Asia TR Turkey 85 444 394 0.95% 1.09% 2.80%
81 Asia NP Nepal 29 774 298 1.42% 1.08% 0.49%
82 Africa MZ Mozambique 32 318 701 1.36% 1.07% 0.09%
83 Africa ZM Zambia 19 009 112 2.05% 1.07% 0.08%
84 Europe HR Croatia 4 074 367 1.63% 1.06% 2.05%
85 North America PA Panama 4 397 424 0.91% 1.04% 1.09%
86 Africa LY Libya 6 985 041 0.96% 1.04% 2.08%
87 Asia AZ Azerbaijan 10 250 514 1.06% 1.01% 3.10%
88 Africa CG Congo 5 683 109 1.40% 0.98% 0.02%
89 Africa BW Botswana 2 409 364 1.38% 0.95% 4.54%
90 North America CR Costa Rica 5 150 788 1.02% 0.93% 4.68%
91 Asia IN India 1 396 531 521 1.69% 0.90% 0.27%
92 North America US USA 333 368 397 0.95% 0.89% 4.79%
93 North America CU Cuba 11 318 183 0.92% 0.89% 7.45%
94 Asia PH Philippines 111 356 721 1.47% 0.88% 1.79%
95 Asia HK Hong Kong 7 571 090 0.93% 0.87% 0.01%
96 Asia IQ Iraq 41 319 572 0.68% 0.87% 1.46%
97 Europe IT Italy 60 353 366 1.11% 0.85% 0.97%
98 South America UY Uruguay 3 488 408 1.50% 0.83% 0.39%
99 Europe ES Spain 46 776 866 0.39% 0.81% 1.10%
100 Africa GA Gabon 2 289 555 0.90% 0.75% 0.37%
101 Asia UZ Uzbekistan 34 059 619 0.74% 0.73% 0.22%
102 Africa LS Lesotho 2 162 942 2.29% 0.73% 0.01%
103 Asia KW Kuwait 4 347 442 0.59% 0.73% 0.27%
104 Africa TG Togo 8 514 519 0.84% 0.69% 0.24%
105 Europe BY Belarus 9 445 532 0.94% 0.69% 1.86%
106 Asia LB Lebanon 6 788 145 0.70% 0.67% 1.46%
107 North America CA Canada 38 145 318 0.96% 0.57% 1.02%
108 Europe RS Serbia 8 694 425 0.79% 0.54% 5.17%
109 Europe SK Slovakia 5 462 867 2.42% 0.51% 0.59%
110 Africa CD DR Congo 92 866 111 1.13% 0.51% 0.01%
111 North America DO Dominican R. 10 980 418 0.55% 0.49% 0.26%
112 Europe PT Portugal 10 160 433 0.41% 0.48% 1.67%
113 Europe FR France 65 449 638 0.47% 0.46% 1.85%
114 Australia/Oceania AU Australia 25 860 187 0.51% 0.44% 0.60%
115 Europe AL Albania 2 873 964 0.50% 0.42% 3.07%
116 Africa BF Burkina Faso 21 599 329 1.27% 0.36% 0.01%
117 Europe CZ Czechia 10 733 209 0.68% 0.35% 0.31%
118 Europe DE Germany 84 110 585 1.12% 0.35% 1.25%
119 Asia KR South Korea 51 322 998 0.32% 0.34% 0.37%
120 Europe GB United Kingdom 68 320 692 0.25% 0.32% 5.35%
121 Asia IL Israel 9 326 000 0.33% 0.30% 10.70%
122 Europe AT Austria 9 069 033 0.41% 0.30% 1.98%
123 Asia JP Japan 126 004 044 0.49% 0.28% 1.23%
124 Europe BE Belgium 11 651 112 0.36% 0.28% 1.74%
125 Europe SI Slovenia 2 079 287 0.46% 0.28% 3.57%
126 North America NI Nicaragua 6 720 530 0.42% 0.26% 0.10%
127 Europe DK Denmark 5 817 071 0.13% 0.25% 1.19%
128 Africa BJ Benin 12 508 895 0.38% 0.25% 0.36%
129 Asia SG Singapore 5 906 406 0.27% 0.23% 0.63%
130 Europe IE Ireland 5 004 960 0.21% 0.22% 3.28%
131 Europe NL Netherlands 17 181 104 0.15% 0.21% 1.51%
132 Europe SE Sweden 10 176 015 0.25% 0.20% 1.08%
133 Africa SS South Sudan 11 353 540 0.58% 0.19% 0.02%
134 Europe CH Switzerland 8 731 749 0.21% 0.19% 2.92%
135 Asia AE Arab Emirates 10 035 914 0.23% 0.18% 0.93%
136 Asia MN Mongolia 3 342 532 0.34% 0.14% 11.89%
137 Europe FI Finland 5 551 217 0.19% 0.12% 1.02%
138 Australia/Oceania NZ New Zealand 5 002 100 0.08% 0.10% 0.08%
139 Europe NO Norway 5 472 894 0.10% 0.09% 2.33%
140 Asia LA Laos 7 404 066 0.09% 0.07% 0.34%
141 Asia QA Qatar 2 807 805 0.28% 0.05% 0.67%
142 Africa BI Burundi 12 320 654 0.06% 0.04% 0.20%
143 Africa SL Sierra Leone 8 174 231 1.84% 0.00% 0.00%
144 Africa TD Chad 16 998 106 0.82% 0.00% 0.00%
145 Asia PS Palestine 5 245 535 0.00% 0.00% 0.15%
146 Africa TZ Tanzania 61 799 974 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 9 798 026 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 33 530 971 198 890 5.931
2 Europe BA Bosnia and Herzegovina 3 255 911 10 205 3.134
3 Europe HU Hungary 9 630 423 30 128 3.128
4 Europe MK North Macedonia 2 083 270 6 379 3.062
5 Europe BG Bulgaria 6 884 595 20 014 2.907
6 Europe CZ Czechia 10 733 209 30 431 2.835
7 South America BR Brazil 214 400 711 588 845 2.747
8 South America AR Argentina 45 701 016 114 059 2.496
9 South America CO Colombia 51 543 448 125 782 2.440
10 Europe SI Slovenia 2 079 287 4 812 2.314
11 Europe SK Slovakia 5 462 867 12 576 2.302
12 South America PY Paraguay 7 239 221 16 122 2.227
13 Europe BE Belgium 11 651 112 25 501 2.189
14 Europe IT Italy 60 353 366 130 211 2.158
15 Asia GE Georgia 3 979 825 8 492 2.134
16 Europe HR Croatia 4 074 367 8 493 2.084
17 North America MX Mexico 130 582 682 270 175 2.069
18 Africa TN Tunisia 11 969 246 24 261 2.027
19 Europe PL Poland 37 796 045 75 488 1.997
20 North America US USA 333 368 397 663 175 1.989
21 Europe GB United Kingdom 68 320 692 134 854 1.974
22 South America CL Chile 19 316 124 37 301 1.931
23 Europe RO Romania 19 081 049 35 488 1.860
24 Europe ES Spain 46 776 866 85 779 1.834
25 South America EC Ecuador 17 969 113 32 564 1.812
26 Europe LT Lithuania 2 675 894 4 781 1.787
27 Europe PT Portugal 10 160 433 17 895 1.761
28 Europe FR France 65 449 638 113 833 1.739
29 South America UY Uruguay 3 488 408 6 045 1.733
30 Asia AM Armenia 2 969 997 5 119 1.724
31 Europe MD Moldova 4 022 524 6 579 1.635
32 North America PA Panama 4 397 424 7 163 1.629
33 South America BO Bolivia 11 866 863 18 621 1.569
34 Europe SE Sweden 10 176 015 14 754 1.450
35 Africa ZA South Africa 60 219 163 85 821 1.425
36 Europe GR Greece 10 360 922 14 393 1.389
37 Asia IR Iran 85 301 901 116 451 1.365
38 Europe RU Russia 146 010 784 197 438 1.352
39 Africa NA Namibia 2 596 880 3 450 1.329
40 Europe UA Ukraine 43 413 079 54 887 1.264
41 Asia LB Lebanon 6 788 145 8 222 1.211
42 Europe CH Switzerland 8 731 749 10 554 1.209
43 Europe AT Austria 9 069 033 10 672 1.177
44 North America CR Costa Rica 5 150 788 5 922 1.150
45 Europe DE Germany 84 110 585 92 904 1.105
46 Europe NL Netherlands 17 181 104 18 102 1.054
47 Europe IE Ireland 5 004 960 5 179 1.035
48 Asia JO Jordan 10 326 517 10 582 1.025
49 Africa BW Botswana 2 409 364 2 354 0.977
50 South America PR Puerto Rico 3 193 694 3 055 0.957
51 North America HN Honduras 10 096 305 9 415 0.932
52 Europe AL Albania 2 873 964 2 570 0.894
53 Europe RS Serbia 8 694 425 7 702 0.886
54 Asia IL Israel 9 326 000 7 555 0.810
55 Asia KZ Kazakhstan 19 050 201 15 031 0.789
56 Asia OM Oman 5 264 399 4 092 0.777
57 North America CA Canada 38 145 318 27 344 0.717
58 Asia TR Turkey 85 444 394 61 134 0.716
59 North America GT Guatemala 18 318 673 12 928 0.706
60 Asia MY Malaysia 32 870 898 22 656 0.689
61 Africa LY Libya 6 985 041 4 496 0.644
62 Asia AZ Azerbaijan 10 250 514 6 249 0.610
63 North America JM Jamaica 2 976 923 1 771 0.595
64 North America CU Cuba 11 318 183 6 661 0.589
65 Asia KW Kuwait 4 347 442 2 436 0.560
66 Asia LK Sri Lanka 21 522 704 11 910 0.553
67 Asia IQ Iraq 41 319 572 21 725 0.526
68 Asia ID Indonesia 277 046 446 140 309 0.506
69 North America SV El Salvador 6 526 099 3 077 0.471
70 Europe DK Denmark 5 817 071 2 622 0.451
71 Europe BY Belarus 9 445 532 3 978 0.421
72 Asia KG Kyrgyzstan 6 655 168 2 585 0.388
73 Asia NP Nepal 29 774 298 11 017 0.370
74 Africa MA Morocco 37 443 314 13 777 0.368
75 North America DO Dominican R. 10 980 418 4 026 0.367
76 Asia PH Philippines 111 356 721 36 158 0.325
77 Asia IN India 1 396 531 521 444 248 0.318
78 Asia MM Myanmar 54 854 323 17 000 0.310
79 Asia MN Mongolia 3 342 532 1 023 0.306
80 Africa ZW Zimbabwe 15 126 278 4 562 0.302
81 Asia SA Saudi Arabia 35 473 686 8 650 0.244
82 Asia TH Thailand 70 013 547 15 267 0.218
83 Asia QA Qatar 2 807 805 604 0.215
84 Asia AE Arab Emirates 10 035 914 2 070 0.206
85 Africa ZM Zambia 19 009 112 3 636 0.191
86 Europe FI Finland 5 551 217 1 051 0.189
87 Africa LS Lesotho 2 162 942 403 0.186
88 Asia AF Afghanistan 39 993 948 7 188 0.180
89 Asia VN Vietnam 98 405 568 16 665 0.169
90 Asia BD Bangladesh 166 687 998 27 173 0.163
91 Africa EG Egypt 104 681 948 16 930 0.162
92 Africa MR Mauritania 4 798 105 761 0.159
93 Europe NO Norway 5 472 894 841 0.154
94 South America VE Venezuela 28 337 635 4 255 0.150
95 Asia JP Japan 126 004 044 17 059 0.135
96 Africa GM Gambia 2 499 105 332 0.133
97 Africa DZ Algeria 44 814 267 5 666 0.126
98 Asia KH Cambodia 17 000 635 2 095 0.123
99 Asia PK Pakistan 226 108 553 27 085 0.120
100 Asia SY Syria 18 017 220 2 106 0.117
101 Africa MW Malawi 19 730 416 2 254 0.114
102 Africa SN Senegal 17 279 857 1 844 0.107
103 Africa KE Kenya 55 211 053 4 967 0.090
104 Africa RW Rwanda 13 342 302 1 198 0.090
105 Africa GA Gabon 2 289 555 175 0.076
106 Africa UG Uganda 47 493 871 3 122 0.066
107 Africa SO Somalia 16 431 633 1 057 0.064
108 Africa GW Guinea-Bissau 2 024 525 130 0.064
109 Africa SD Sudan 45 093 467 2 834 0.063
110 Africa MZ Mozambique 32 318 701 1 902 0.059
111 Africa LR Liberia 5 202 142 283 0.054
112 Asia YE Yemen 30 624 464 1 618 0.053
113 North America HT Haiti 11 571 788 596 0.051
114 Africa CM Cameroon 27 348 672 1 368 0.050
115 Asia KR South Korea 51 322 998 2 393 0.047
116 Australia/Oceania AU Australia 25 860 187 1 139 0.044
117 Africa ET Ethiopia 118 423 370 5 093 0.043
118 Africa AO Angola 34 106 951 1 389 0.041
119 Asia TW Taiwan 23 869 343 840 0.035
120 Asia UZ Uzbekistan 34 059 619 1 184 0.035
121 Africa GH Ghana 31 861 540 1 102 0.035
122 Africa MG Madagascar 28 555 768 956 0.034
123 Africa CG Congo 5 683 109 183 0.032
124 North America NI Nicaragua 6 720 530 202 0.030
125 Asia HK Hong Kong 7 571 090 213 0.028
126 Africa GN Guinea 13 565 401 375 0.028
127 Africa ML Mali 20 958 972 545 0.026
128 Africa TG Togo 8 514 519 213 0.025
129 Australia/Oceania PG Papua New Guinea 9 153 155 215 0.024
130 Africa CF Central African R. 4 931 928 100 0.020
131 Africa CI Ivory Coast 27 171 886 549 0.020
132 Africa SL Sierra Leone 8 174 231 121 0.015
133 Africa NG Nigeria 212 347 013 2 653 0.013
134 Africa BJ Benin 12 508 895 146 0.012
135 Africa CD DR Congo 92 866 111 1 068 0.011
136 Africa ER Eritrea 3 606 172 40 0.011
137 Africa SS South Sudan 11 353 540 121 0.011
138 Asia SG Singapore 5 906 406 61 0.010
139 Africa TD Chad 16 998 106 174 0.010
140 Africa BF Burkina Faso 21 599 329 172 0.008
141 Africa NE Niger 25 269 012 201 0.008
142 Australia/Oceania NZ New Zealand 5 002 100 27 0.005
143 Asia PS Palestine 5 245 535 17 0.003
144 Asia LA Laos 7 404 066 16 0.002
145 Africa BI Burundi 12 320 654 12 0.001
146 Africa TZ Tanzania 61 799 974 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 9 798 026 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"