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": 2022-08-13 11:29
(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 +5 478 (+5 728) +16 (+15)
CZ Czechia +2 194 (+1 931) +5 (+7)
DE Germany +0 (+45 859) +0 (+137)
HU Hungary +0 (+0) +0 (+0)
PL Poland +4 642 (+4 223) +22 (+14)
SK Slovakia, [gov], [okr]+776 (+611) +7 (+9)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Australia/Oceania 43 872 888 12.81% 12.68% 8.02%
2 Europe 756 586 716 4.19% 4.50% 2.99%
3 North America 598 097 256 2.38% 3.06% 2.33%
4 South America 441 503 059 1.54% 2.04% 1.52%
5 Asia 4 705 716 189 0.55% 1.06% 1.11%
6 Africa 1 407 643 045 0.06% 0.04% 0.02%

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 441 503 059 0.44% 0.59% 2.04%
2 Africa 1 407 643 045 0.49% (0.55)% (0.04)%
3 North America 598 097 256 0.40% 0.44% 3.06%
4 Europe 756 586 716 0.25% 0.32% 4.50%
5 Australia/Oceania 43 872 888 0.14% 0.27% 12.68%
6 Asia 4 705 716 189 0.16% 0.13% 1.06%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 441 503 059 1 324 723 3.001
2 Europe 756 586 716 1 890 772 2.499
3 North America 598 097 256 1 474 622 2.466
4 Australia/Oceania 43 872 888 18 472 0.421
5 Asia 4 705 716 189 1 449 321 0.308
6 Africa 1 407 643 045 257 263 0.183

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 KR South Korea 51 362 170 9.99% 20.21% 28.46%
2 Asia JP Japan 125 660 699 6.44% 17.11% 19.69%
3 Europe GR Greece 10 315 798 11.99% 19.67% 16.69%
4 Asia SG Singapore 5 947 333 10.67% 15.40% 12.62%
5 Australia/Oceania AU Australia 26 123 629 17.93% 17.78% 11.05%
6 Asia TW Taiwan 23 907 624 20.23% 11.34% 10.83%
7 Australia/Oceania NZ New Zealand 5 002 100 17.18% 16.51% 10.79%
8 South America PR Puerto Rico 3 193 694 12.22% 9.47% 10.65%
9 Europe RS Serbia 8 663 224 2.36% 6.95% 8.47%
10 Europe SI Slovenia 2 079 540 5.15% 9.00% 8.13%
11 Europe AT Austria 9 114 718 8.89% 11.89% 7.55%
12 Asia HK Hong Kong 7 625 198 2.77% 6.66% 6.83%
13 South America CL Chile 19 462 117 4.29% 5.23% 6.31%
14 Asia MN Mongolia 3 389 593 1.37% 4.26% 6.13%
15 Europe DE Germany 84 348 586 9.56% 9.54% 5.80%
16 Europe IT Italy 60 274 489 9.83% 11.12% 5.79%
17 Asia GE Georgia 3 973 033 1.47% 4.36% 5.49%
18 Europe LT Lithuania 2 642 319 2.37% 4.81% 5.49%
19 North America CR Costa Rica 5 192 180 4.10% 3.73% 4.39%
20 Europe MD Moldova 4 014 209 0.89% 2.87% 4.33%
21 Europe FR France 65 577 917 9.97% 8.95% 4.24%
22 Europe RO Romania 18 967 367 1.43% 4.22% 3.98%
23 North America US USA 334 776 423 3.48% 4.45% 3.73%
24 Europe AL Albania 2 871 176 1.61% 4.14% 3.54%
25 Europe DK Denmark 5 835 193 2.70% 3.58% 3.25%
26 Europe HU Hungary 9 608 667 1.31% 2.69% 3.22%
27 South America PE Peru 33 940 183 1.33% 3.68% 3.19%
28 Europe PT Portugal 10 134 067 14.84% 4.22% 3.10%
29 Asia VN Vietnam 99 184 865 1.05% 2.44% 2.98%
30 Europe FI Finland 5 558 860 4.47% 4.67% 2.95%
31 South America BO Bolivia 12 008 716 1.44% 4.12% 2.82%
32 Europe HR Croatia 4 051 938 2.15% 3.64% 2.79%
33 Asia IL Israel 9 326 000 6.31% 5.36% 2.74%
34 Asia QA Qatar 2 807 805 1.92% 3.76% 2.68%
35 Europe MK North Macedonia 2 083 194 1.23% 3.23% 2.65%
36 North America PA Panama 4 457 967 4.33% 2.53% 2.28%
37 Europe BG Bulgaria 6 838 271 1.12% 2.55% 2.19%
38 Europe CZ Czechia 10 750 852 1.22% 2.36% 1.99%
39 Asia LB Lebanon 6 761 052 1.42% 3.64% 1.95%
40 Europe RU Russia 146 066 332 0.55% 1.03% 1.88%
41 Europe BE Belgium 11 695 936 4.07% 3.77% 1.85%
42 Europe CH Switzerland 8 788 040 4.67% 5.41% 1.78%
43 Asia MY Malaysia 33 240 253 1.10% 1.49% 1.60%
44 South America AR Argentina 46 070 057 1.21% 1.53% 1.57%
45 Europe BA Bosnia and Herzegovina 3 237 831 0.44% 1.29% 1.51%
46 Europe SK Slovakia 5 465 215 1.19% 1.74% 1.43%
47 North America GT Guatemala 18 614 279 1.23% 2.39% 1.40%
48 Europe NL Netherlands 17 214 776 2.04% 2.37% 1.28%
49 South America BR Brazil 215 744 483 1.81% 2.07% 1.24%
50 Europe PL Poland 37 759 266 0.36% 0.96% 1.13%
51 Asia KZ Kazakhstan 19 250 201 0.36% 1.32% 1.07%
52 Asia AM Armenia 2 974 915 0.20% 0.66% 1.07%
53 Europe SE Sweden 10 232 007 0.55% 1.01% 1.06%
54 Asia AE Arab Emirates 10 142 329 1.06% 1.37% 0.93%
55 Asia JO Jordan 10 416 668 0.25% 0.70% 0.90%
56 Europe GB United Kingdom 68 637 677 2.45% 2.05% 0.88%
57 Europe IE Ireland 5 054 066 2.76% 1.84% 0.88%
58 South America UY Uruguay 3 499 104 2.25% 0.92% 0.83%
59 Europe ES Spain 46 792 941 3.27% 2.18% 0.69%
60 Africa TN Tunisia 12 079 327 0.83% 1.73% 0.65%
61 Asia IR Iran 86 259 448 0.30% 0.92% 0.53%
62 Asia AZ Azerbaijan 10 331 833 0.11% 0.40% 0.52%
63 North America JM Jamaica 2 988 409 0.62% 0.47% 0.51%
64 Asia PH Philippines 112 655 952 0.13% 0.36% 0.50%
65 North America HN Honduras 10 236 725 0.25% 0.64% 0.47%
66 North America MX Mexico 131 788 502 0.86% 1.37% 0.45%
67 South America CO Colombia 52 026 235 0.37% 0.62% 0.44%
68 Asia TH Thailand 70 169 115 0.89% 0.37% 0.37%
69 North America DO Dominican R. 11 077 240 0.50% 0.51% 0.32%
70 Europe NO Norway 5 510 601 0.70% 0.43% 0.30%
71 Asia PS Palestine 5 351 440 0.02% 0.06% 0.28%
72 Asia ID Indonesia 279 621 115 0.08% 0.22% 0.23%
73 Asia KG Kyrgyzstan 6 751 130 0.05% 0.20% 0.23%
74 Asia NP Nepal 30 241 681 0.05% 0.16% 0.18%
75 Asia OM Oman 5 380 449 0.16% 0.42% 0.16%
76 North America CA Canada 38 439 749 1.23% 1.40% 0.16%
77 Europe UA Ukraine 43 180 284 0.09% 0.09% 0.15%
78 Asia IN India 1 408 606 661 0.09% 0.16% 0.14%
79 Asia LA Laos 7 498 141 0.18% 0.10% 0.14%
80 Africa BI Burundi 12 637 461 0.07% 0.16% 0.14%
81 Asia KW Kuwait 4 403 724 0.57% 0.65% 0.13%
82 South America VE Venezuela 28 266 183 0.06% 0.16% 0.12%
83 Africa LY Libya 7 068 281 0.06% 0.21% 0.10%
84 North America CU Cuba 11 312 048 0.09% 0.10% 0.10%
85 Asia LK Sri Lanka 21 602 489 0.02% 0.06% 0.09%
86 Asia IQ Iraq 42 125 465 0.31% 0.57% 0.07%
87 South America PY Paraguay 7 317 246 0.86% 2.04% 0.07%
88 Africa ZA South Africa 60 885 155 0.44% 0.05% 0.06%
89 Asia AF Afghanistan 40 776 746 0.02% 0.05% 0.06%
90 Asia SA Saudi Arabia 35 956 935 0.17% 0.11% 0.04%
91 Africa DZ Algeria 45 520 486 0.01% 0.02% 0.03%
92 Africa MA Morocco 37 832 888 0.26% 0.19% 0.03%
93 Africa GM Gambia 2 559 814 0.01% 0.03% 0.03%
94 Asia PK Pakistan 229 935 237 0.01% 0.03% 0.03%
95 Africa CI Ivory Coast 27 755 455 0.02% 0.03% 0.02%
96 Asia KH Cambodia 17 206 778 0.01% 0.02% 0.02%
97 Africa TG Togo 8 687 806 0.02% 0.03% 0.02%
98 Africa SN Senegal 17 674 222 0.01% 0.03% 0.02%
99 North America NI Nicaragua 6 790 714 0.01% 0.01% 0.02%
100 Asia SY Syria 18 396 986 0.00% 0.01% 0.02%
101 Africa MR Mauritania 4 907 337 0.08% 0.09% 0.02%
102 Asia BD Bangladesh 168 148 317 0.03% 0.04% 0.01%
103 Africa ER Eritrea 3 649 901 0.01% 0.03% 0.01%
104 Asia UZ Uzbekistan 34 491 840 0.02% 0.02% 0.01%
105 Africa TZ Tanzania 63 321 513 0.01% 0.01% 0.01%
106 Africa NA Namibia 2 637 920 0.32% 0.03% 0.01%
107 Africa MZ Mozambique 33 101 688 0.01% 0.01% 0.01%
108 Africa MW Malawi 20 172 167 0.01% 0.02% 0.01%
109 Africa ZW Zimbabwe 15 319 075 0.06% 0.01% 0.01%
110 Africa ZM Zambia 19 469 475 0.06% 0.05% 0.01%
111 Africa NG Nigeria 216 911 580 0.00% 0.01% 0.01%
112 Africa CF Central African R. 5 006 809 0.01% 0.01% 0.01%
113 Africa UG Uganda 48 786 754 0.01% 0.01% 0.01%
114 Africa RW Rwanda 13 629 146 0.02% 0.02% 0.01%
115 Africa ET Ethiopia 120 967 469 0.02% 0.01% 0.00%
116 Australia/Oceania PG Papua New Guinea 9 304 344 0.01% 0.00% 0.00%
117 Africa EG Egypt 106 403 723 0.00% 0.00% 0.00%
118 Africa KE Kenya 56 268 481 0.03% 0.01% 0.00%
119 Asia MM Myanmar 55 178 680 0.00% 0.00% 0.00%
120 Africa MG Madagascar 29 191 914 0.01% 0.01% 0.00%
121 Africa GH Ghana 32 440 435 0.02% 0.01% 0.00%
122 Africa BF Burkina Faso 22 111 767 0.00% 0.00% 0.00%
123 Asia YE Yemen 31 210 920 0.00% 0.00% 0.00%
124 Africa LS Lesotho 2 178 048 0.06% 0.01% 0.00%
125 Africa GA Gabon 2 336 461 0.04% 0.07% 0.00%
126 Africa LR Liberia 5 308 309 0.00% 0.01% 0.00%
127 Africa AO Angola 35 021 859 0.01% 0.01% 0.00%
128 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
129 Asia TR Turkey 86 252 289 1.53% 4.63% 0.00%
130 South America EC Ecuador 18 207 879 0.60% 1.17% 0.00%
131 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
132 Asia TJ Tajikistan 9 989 298 0.00% 0.00% 0.00%
133 Africa TD Chad 17 419 633 0.00% 0.00% 0.00%
134 North America SV El Salvador 6 555 189 0.44% 0.60% 0.00%
135 Africa NE Niger 26 054 257 0.00% 0.00% 0.00%
136 Africa SS South Sudan 11 470 397 0.00% 0.00% 0.00%
137 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
138 Africa SO Somalia 16 828 097 0.00% 0.00% 0.00%
139 Africa CM Cameroon 27 939 038 0.00% 0.01% 0.00%
140 Africa SL Sierra Leone 8 318 993 0.00% 0.00% 0.00%
141 Africa CG Congo 5 804 447 0.01% 0.01% 0.00%
142 North America HT Haiti 11 695 576 0.02% 0.02% 0.00%
143 Africa CD DR Congo 95 302 307 0.01% 0.00% 0.00%
144 Europe BY Belarus 9 442 773 0.24% 0.00% 0.00%
145 Africa GW Guinea-Bissau 2 066 068 0.01% 0.01% 0.00%
146 Africa SD Sudan 46 007 802 0.00% 0.00% 0.00%
147 Africa BW Botswana 2 451 734 0.80% 0.10% 0.00%
148 Africa ML Mali 21 480 629 0.00% 0.00% 0.00%
149 Africa GN Guinea 13 883 845 0.01% 0.00% 0.00%
150 Africa BJ Benin 12 792 689 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 Africa EG Egypt 106 403 723 4.53% (7.39)% (0.00)%
2 Asia YE Yemen 31 210 920 6.02% (4.76)% (0.00)%
3 Europe NO Norway 5 510 601 2.47% 4.63% 0.43%
4 Africa ML Mali 21 480 629 1.41% (3.77)% (0.00)%
5 Asia LK Sri Lanka 21 602 489 2.92% (3.72)% (0.06)%
6 Africa GW Guinea-Bissau 2 066 068 1.43% (3.57)% (0.01)%
7 Africa SL Sierra Leone 8 318 993 1.64% (3.45)% (0.00)%
8 Africa ZW Zimbabwe 15 319 075 1.32% (3.19)% (0.01)%
9 Africa MW Malawi 20 172 167 2.25% (2.11)% (0.02)%
10 Africa LS Lesotho 2 178 048 0.56% 1.96% 0.01%
11 North America JM Jamaica 2 988 409 1.67% 1.72% 0.47%
12 Africa GN Guinea 13 883 845 0.62% 1.68% 0.00%
13 Australia/Oceania PG Papua New Guinea 9 304 344 1.02% 1.64% 0.00%
14 Africa NA Namibia 2 637 920 0.59% 1.63% 0.03%
15 Europe BA Bosnia and Herzegovina 3 237 831 1.65% 1.52% 1.29%
16 Africa SD Sudan 46 007 802 2.86% 1.40% 0.00%
17 Asia TH Thailand 70 169 115 0.67% 1.34% 0.37%
18 Europe SE Sweden 10 232 007 1.51% 1.16% 1.01%
19 Asia SY Syria 18 396 986 1.09% 1.15% 0.01%
20 South America CO Colombia 52 026 235 0.75% 0.96% 0.62%
21 Africa TG Togo 8 687 806 0.74% 0.94% 0.03%
22 Europe HR Croatia 4 051 938 0.88% 0.90% 3.64%
23 Africa MG Madagascar 29 191 914 0.78% 0.85% 0.01%
24 Africa ZA South Africa 60 885 155 0.67% 0.82% 0.05%
25 Europe GB United Kingdom 68 637 677 0.74% 0.81% 2.05%
26 Europe UA Ukraine 43 180 284 1.13% 0.72% 0.09%
27 Africa AO Angola 35 021 859 0.49% 0.68% 0.01%
28 Asia IR Iran 86 259 448 0.80% 0.67% 0.92%
29 North America CA Canada 38 439 749 0.87% 0.66% 1.40%
30 Asia AZ Azerbaijan 10 331 833 0.71% 0.65% 0.40%
31 Europe ES Spain 46 792 941 0.46% 0.65% 2.18%
32 Asia AF Afghanistan 40 776 746 0.86% 0.63% 0.05%
33 Europe RU Russia 146 066 332 1.39% 0.55% 1.03%
34 Europe SK Slovakia 5 465 215 0.77% 0.54% 1.74%
35 South America UY Uruguay 3 499 104 0.29% 0.53% 0.92%
36 South America PY Paraguay 7 317 246 0.90% 0.52% 2.04%
37 South America BR Brazil 215 744 483 0.50% 0.52% 2.07%
38 Europe BG Bulgaria 6 838 271 1.00% 0.50% 2.55%
39 Europe HU Hungary 9 608 667 0.90% 0.50% 2.69%
40 Asia PK Pakistan 229 935 237 0.47% 0.49% 0.03%
41 Africa CI Ivory Coast 27 755 455 0.46% 0.49% 0.03%
42 Africa TN Tunisia 12 079 327 0.66% 0.48% 1.73%
43 Africa BW Botswana 2 451 734 0.42% 0.47% 0.10%
44 Europe DK Denmark 5 835 193 0.51% 0.46% 3.58%
45 Europe CZ Czechia 10 750 852 0.44% 0.45% 2.36%
46 South America CL Chile 19 462 117 0.35% 0.43% 5.23%
47 Asia BD Bangladesh 168 148 317 0.34% 0.43% 0.04%
48 Europe PL Poland 37 759 266 0.82% 0.41% 0.96%
49 Africa RW Rwanda 13 629 146 0.27% 0.40% 0.02%
50 South America PE Peru 33 940 183 0.59% 0.39% 3.68%
51 Asia PH Philippines 112 655 952 0.92% 0.38% 0.36%
52 Africa ET Ethiopia 120 967 469 0.27% 0.38% 0.01%
53 Europe MD Moldova 4 014 209 0.69% 0.38% 2.87%
54 Europe IE Ireland 5 054 066 0.38% 0.38% 1.84%
55 Europe MK North Macedonia 2 083 194 0.60% 0.35% 3.23%
56 Australia/Oceania NZ New Zealand 5 002 100 0.23% 0.34% 16.51%
57 Asia NP Nepal 30 241 681 0.31% 0.34% 0.16%
58 North America GT Guatemala 18 614 279 0.81% 0.34% 2.39%
59 Africa MA Morocco 37 832 888 0.21% 0.34% 0.19%
60 North America US USA 334 776 423 0.39% 0.34% 4.45%
61 Europe SI Slovenia 2 079 540 0.41% 0.33% 9.00%
62 Asia SA Saudi Arabia 35 956 935 0.34% 0.33% 0.11%
63 Asia AM Armenia 2 974 915 0.38% 0.33% 0.66%
64 Africa MR Mauritania 4 907 337 0.25% 0.31% 0.09%
65 South America VE Venezuela 28 266 183 0.45% 0.30% 0.16%
66 Africa MZ Mozambique 33 101 688 0.41% 0.29% 0.01%
67 North America MX Mexico 131 788 502 0.28% 0.29% 1.37%
68 Europe RO Romania 18 967 367 0.43% 0.29% 4.22%
69 Asia ID Indonesia 279 621 115 0.67% 0.28% 0.22%
70 North America HN Honduras 10 236 725 0.28% 0.27% 0.64%
71 Africa CM Cameroon 27 939 038 0.51% 0.26% 0.01%
72 Asia IN India 1 408 606 661 0.48% 0.26% 0.16%
73 North America SV El Salvador 6 555 189 0.32% 0.25% 0.60%
74 Europe PT Portugal 10 134 067 0.17% 0.24% 4.22%
75 North America CR Costa Rica 5 192 180 0.21% 0.23% 3.73%
76 Europe GR Greece 10 315 798 0.27% 0.23% 19.67%
77 South America PR Puerto Rico 3 193 694 0.17% 0.23% 9.47%
78 Europe RS Serbia 8 663 224 0.30% 0.22% 6.95%
79 Europe FI Finland 5 558 860 0.43% 0.22% 4.67%
80 Africa ZM Zambia 19 469 475 0.38% 0.22% 0.05%
81 Europe BE Belgium 11 695 936 0.23% 0.21% 3.77%
82 Asia MY Malaysia 33 240 253 0.17% 0.21% 1.49%
83 Asia TW Taiwan 23 907 624 0.18% 0.21% 11.34%
84 Asia MM Myanmar 55 178 680 0.05% 0.21% 0.00%
85 Europe IT Italy 60 274 489 0.20% 0.20% 11.12%
86 Africa KE Kenya 56 268 481 0.17% 0.18% 0.01%
87 Australia/Oceania AU Australia 26 123 629 0.12% 0.18% 17.78%
88 South America AR Argentina 46 070 057 0.21% 0.18% 1.53%
89 North America PA Panama 4 457 967 0.14% 0.18% 2.53%
90 Europe LT Lithuania 2 642 319 0.35% 0.17% 4.81%
91 Asia IL Israel 9 326 000 0.13% 0.16% 5.36%
92 Africa DZ Algeria 45 520 486 0.17% 0.16% 0.02%
93 Africa GA Gabon 2 336 461 0.30% 0.15% 0.07%
94 Europe AL Albania 2 871 176 0.16% 0.15% 4.14%
95 North America HT Haiti 11 695 576 0.15% 0.15% 0.02%
96 Africa CD DR Congo 95 302 307 0.97% 0.15% 0.00%
97 Asia JO Jordan 10 416 668 0.17% 0.14% 0.70%
98 Africa GH Ghana 32 440 435 0.18% 0.13% 0.01%
99 Africa LY Libya 7 068 281 0.13% 0.12% 0.21%
100 Europe FR France 65 577 917 0.12% 0.12% 8.95%
101 South America BO Bolivia 12 008 716 0.14% 0.12% 4.12%
102 Asia LB Lebanon 6 761 052 0.23% 0.12% 3.64%
103 Asia HK Hong Kong 7 625 198 0.29% 0.12% 6.66%
104 Europe AT Austria 9 114 718 0.12% 0.10% 11.89%
105 Europe NL Netherlands 17 214 776 0.10% 0.10% 2.37%
106 South America EC Ecuador 18 207 879 0.27% 0.09% 1.17%
107 Africa NG Nigeria 216 911 580 0.07% 0.09% 0.01%
108 Asia GE Georgia 3 973 033 0.20% 0.08% 4.36%
109 Asia IQ Iraq 42 125 465 0.11% 0.08% 0.57%
110 Africa UG Uganda 48 786 754 0.66% 0.08% 0.01%
111 Europe DE Germany 84 348 586 0.09% 0.08% 9.54%
112 Asia JP Japan 125 660 699 0.09% 0.08% 17.11%
113 Asia KW Kuwait 4 403 724 0.03% 0.07% 0.65%
114 Europe CH Switzerland 8 788 040 0.07% 0.06% 5.41%
115 Asia TR Turkey 86 252 289 0.09% 0.05% 4.63%
116 Asia SG Singapore 5 947 333 0.04% 0.05% 15.40%
117 Asia KR South Korea 51 362 170 0.09% 0.04% 20.21%
118 Asia AE Arab Emirates 10 142 329 0.03% 0.03% 1.37%
119 Asia KZ Kazakhstan 19 250 201 0.03% 0.02% 1.32%
120 Asia MN Mongolia 3 389 593 0.04% 0.02% 4.26%
121 North America DO Dominican R. 11 077 240 0.02% 0.01% 0.51%
122 Asia QA Qatar 2 807 805 0.01% 0.00% 3.76%
123 Asia VN Vietnam 99 184 865 0.02% 0.00% 2.44%
124 Asia OM Oman 5 380 449 0.05% 0.00% 0.42%
125 Asia KG Kyrgyzstan 6 751 130 0.00% 0.00% 0.20%
126 Africa BI Burundi 12 637 461 0.00% 0.00% 0.16%
127 Asia LA Laos 7 498 141 0.23% 0.00% 0.10%
128 North America CU Cuba 11 312 048 0.07% 0.00% 0.10%
129 Africa GM Gambia 2 559 814 1.45% 0.00% 0.03%
130 Africa ER Eritrea 3 649 901 0.00% 0.00% 0.03%
131 Africa SN Senegal 17 674 222 0.19% 0.00% 0.03%
132 Asia UZ Uzbekistan 34 491 840 0.00% 0.00% 0.02%
133 Asia KH Cambodia 17 206 778 0.09% 0.00% 0.02%
134 Africa CG Congo 5 804 447 0.13% 0.00% 0.01%
135 Africa TZ Tanzania 63 321 513 0.94% 0.00% 0.01%
136 North America NI Nicaragua 6 790 714 2.40% 0.00% 0.01%
137 Africa CF Central African R. 5 006 809 0.00% 0.00% 0.01%
138 Africa LR Liberia 5 308 309 0.00% 0.00% 0.01%
139 Africa SO Somalia 16 828 097 0.00% 0.00% 0.00%
140 Africa BJ Benin 12 792 689 0.00% 0.00% 0.00%
141 Africa SS South Sudan 11 470 397 0.00% 0.00% 0.00%
142 Africa TD Chad 17 419 633 1.11% 0.00% 0.00%
143 Africa NE Niger 26 054 257 1.01% 0.00% 0.00%
144 Asia PS Palestine 5 351 440 0.00% 0.00% 0.06%
145 Africa BF Burkina Faso 22 111 767 1.52% 0.00% 0.00%
146 Europe BY Belarus 9 442 773 0.86% 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 9 989 298 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 33 940 183 214 860 6.330
2 Europe BG Bulgaria 6 838 271 37 485 5.482
3 Europe BA Bosnia and Herzegovina 3 237 831 15 942 4.924
4 Europe HU Hungary 9 608 667 46 966 4.888
5 Europe MK North Macedonia 2 083 194 9 404 4.514
6 Asia GE Georgia 3 973 033 16 877 4.248
7 Europe HR Croatia 4 051 938 16 472 4.065
8 Europe SI Slovenia 2 079 540 8 021 3.857
9 Europe CZ Czechia 10 750 852 40 624 3.779
10 Europe SK Slovakia 5 465 215 20 296 3.714
11 Europe RO Romania 18 967 367 66 311 3.496
12 Europe LT Lithuania 2 642 319 9 230 3.493
13 South America BR Brazil 215 744 483 681 078 3.157
14 Europe PL Poland 37 759 266 116 773 3.093
15 South America CL Chile 19 462 117 59 930 3.079
16 Europe GR Greece 10 315 798 31 722 3.075
17 North America US USA 334 776 423 1 025 353 3.063
18 Europe MD Moldova 4 014 209 11 662 2.905
19 Asia AM Armenia 2 974 915 8 637 2.903
20 Europe IT Italy 60 274 489 173 853 2.884
21 South America AR Argentina 46 070 057 129 440 2.810
22 Europe BE Belgium 11 695 936 32 364 2.767
23 South America CO Colombia 52 026 235 141 075 2.712
24 Europe GB United Kingdom 68 637 677 186 087 2.711
25 South America PY Paraguay 7 317 246 19 297 2.637
26 Europe RU Russia 146 066 332 383 071 2.623
27 Europe UA Ukraine 43 180 284 108 743 2.518
28 North America MX Mexico 131 788 502 328 509 2.493
29 Europe PT Portugal 10 134 067 24 723 2.440
30 Africa TN Tunisia 12 079 327 29 153 2.413
31 Europe ES Spain 46 792 941 111 449 2.382
32 Europe FR France 65 577 917 149 596 2.281
33 Europe AT Austria 9 114 718 20 485 2.248
34 South America UY Uruguay 3 499 104 7 423 2.121
35 South America EC Ecuador 18 207 879 35 811 1.967
36 Europe SE Sweden 10 232 007 19 528 1.909
37 Europe RS Serbia 8 663 224 16 424 1.896
38 North America PA Panama 4 457 967 8 434 1.892
39 South America BO Bolivia 12 008 716 22 119 1.842
40 Europe DE Germany 84 348 586 145 698 1.727
41 North America CR Costa Rica 5 192 180 8 774 1.690
42 Africa ZA South Africa 60 885 155 101 982 1.675
43 Asia IR Iran 86 259 448 142 722 1.655
44 Asia LB Lebanon 6 761 052 10 558 1.562
45 Africa NA Namibia 2 637 920 4 073 1.544
46 Europe CH Switzerland 8 788 040 13 474 1.533
47 Europe IE Ireland 5 054 066 7 743 1.532
48 South America PR Puerto Rico 3 193 694 4 820 1.509
49 Asia JO Jordan 10 416 668 14 090 1.353
50 Europe NL Netherlands 17 214 776 22 542 1.310
51 Asia HK Hong Kong 7 625 198 9 559 1.254
52 Europe AL Albania 2 871 176 3 562 1.241
53 Asia IL Israel 9 326 000 11 483 1.231
54 Europe DK Denmark 5 835 193 6 792 1.164
55 Asia TR Turkey 86 252 289 99 678 1.156
56 Africa BW Botswana 2 451 734 2 770 1.130
57 North America CA Canada 38 439 749 42 938 1.117
58 Asia MY Malaysia 33 240 253 36 070 1.085
59 North America JM Jamaica 2 988 409 3 219 1.077
60 North America HN Honduras 10 236 725 10 954 1.070
61 North America GT Guatemala 18 614 279 19 185 1.031
62 Asia KZ Kazakhstan 19 250 201 19 030 0.989
63 Europe FI Finland 5 558 860 5 350 0.962
64 Asia AZ Azerbaijan 10 331 833 9 768 0.945
65 Africa LY Libya 7 068 281 6 434 0.910
66 Asia OM Oman 5 380 449 4 628 0.860
67 Asia LK Sri Lanka 21 602 489 16 614 0.769
68 North America CU Cuba 11 312 048 8 529 0.754
69 Europe BY Belarus 9 442 773 7 118 0.754
70 Europe NO Norway 5 510 601 3 834 0.696
71 North America SV El Salvador 6 555 189 4 217 0.643
72 Asia MN Mongolia 3 389 593 2 123 0.626
73 Asia IQ Iraq 42 125 465 25 326 0.601
74 Asia KW Kuwait 4 403 724 2 562 0.582
75 Asia ID Indonesia 279 621 115 157 189 0.562
76 Asia PH Philippines 112 655 952 60 944 0.541
77 Australia/Oceania NZ New Zealand 5 002 100 2 554 0.511
78 Asia KR South Korea 51 362 170 25 566 0.498
79 Australia/Oceania AU Australia 26 123 629 12 742 0.488
80 Asia TH Thailand 70 169 115 31 798 0.453
81 Asia KG Kyrgyzstan 6 751 130 2 991 0.443
82 Asia VN Vietnam 99 184 865 43 096 0.434
83 Africa MA Morocco 37 832 888 16 263 0.430
84 Asia NP Nepal 30 241 681 11 984 0.396
85 North America DO Dominican R. 11 077 240 4 384 0.396
86 Asia TW Taiwan 23 907 624 9 413 0.394
87 Asia IN India 1 408 606 661 526 996 0.374
88 Africa ZW Zimbabwe 15 319 075 5 587 0.365
89 Asia MM Myanmar 55 178 680 19 435 0.352
90 Africa LS Lesotho 2 178 048 704 0.323
91 Asia JP Japan 125 660 699 34 763 0.277
92 Asia SG Singapore 5 947 333 1 552 0.261
93 Asia SA Saudi Arabia 35 956 935 9 265 0.258
94 Asia QA Qatar 2 807 805 681 0.242
95 Africa EG Egypt 106 403 723 24 781 0.233
96 Asia AE Arab Emirates 10 142 329 2 338 0.231
97 Africa ZM Zambia 19 469 475 4 015 0.206
98 South America VE Venezuela 28 266 183 5 772 0.204
99 Africa MR Mauritania 4 907 337 992 0.202
100 Asia AF Afghanistan 40 776 746 7 753 0.190
101 Asia KH Cambodia 17 206 778 3 056 0.178
102 Asia BD Bangladesh 168 148 317 29 312 0.174
103 Asia SY Syria 18 396 986 3 156 0.172
104 Africa DZ Algeria 45 520 486 6 878 0.151
105 Africa GM Gambia 2 559 814 368 0.144
106 Asia PK Pakistan 229 935 237 30 511 0.133
107 Africa MW Malawi 20 172 167 2 670 0.132
108 Africa GA Gabon 2 336 461 306 0.131
109 Africa SN Senegal 17 674 222 1 968 0.111
110 Africa SD Sudan 46 007 802 4 960 0.108
111 Africa RW Rwanda 13 629 146 1 466 0.108
112 Asia LA Laos 7 498 141 757 0.101
113 Africa KE Kenya 56 268 481 5 673 0.101
114 Africa GW Guinea-Bissau 2 066 068 174 0.084
115 Africa SO Somalia 16 828 097 1 361 0.081
116 Africa UG Uganda 48 786 754 3 627 0.074
117 North America HT Haiti 11 695 576 838 0.072
118 Australia/Oceania PG Papua New Guinea 9 304 344 663 0.071
119 Africa CM Cameroon 27 939 038 1 933 0.069
120 Asia YE Yemen 31 210 920 2 152 0.069
121 Africa MZ Mozambique 33 101 688 2 218 0.067
122 Africa CG Congo 5 804 447 386 0.067
123 Africa ET Ethiopia 120 967 469 7 569 0.063
124 Africa LR Liberia 5 308 309 294 0.055
125 Africa AO Angola 35 021 859 1 917 0.055
126 Africa MG Madagascar 29 191 914 1 409 0.048
127 Asia UZ Uzbekistan 34 491 840 1 637 0.048
128 Africa GH Ghana 32 440 435 1 458 0.045
129 North America NI Nicaragua 6 790 714 244 0.036
130 Africa ML Mali 21 480 629 739 0.034
131 Africa TG Togo 8 687 806 281 0.032
132 Africa GN Guinea 13 883 845 447 0.032
133 Africa CI Ivory Coast 27 755 455 815 0.029
134 Africa ER Eritrea 3 649 901 103 0.028
135 Africa CF Central African R. 5 006 809 113 0.023
136 Africa BF Burkina Faso 22 111 767 387 0.018
137 Africa SL Sierra Leone 8 318 993 126 0.015
138 Africa CD DR Congo 95 302 307 1 391 0.015
139 Africa NG Nigeria 216 911 580 3 147 0.015
140 Africa TZ Tanzania 63 321 513 841 0.013
141 Africa BJ Benin 12 792 689 163 0.013
142 Africa SS South Sudan 11 470 397 138 0.012
143 Africa NE Niger 26 054 257 311 0.012
144 Africa TD Chad 17 419 633 193 0.011
145 Africa BI Burundi 12 637 461 15 0.001
146 Asia PS Palestine 5 351 440 3 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 9 989 298 0 0.000
150 Europe TM Turkmenistan 6 118 000 0 0.000

Elhalálozási adatok hozzávetőleges értékei 2018/2019:
 *  Abortusz: 56 millió, Szív és érrendszer: 17,9 millió, Rákbetegség: 9,6 millió.

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

(2021-02-02 ...)

* 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"