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": 2021-12-02 11:15
(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 +8 882 (+10 367) +72 (+61)
CZ Czechia +21 126 (+21 987) +67 (+107)
DE Germany +0 (+71 887) +0 (+415)
HU Hungary +10 466 (+11 152) +218 (+192)
PL Poland +27 356 (+29 062) +502 (+571)
SK Slovakia, [gov], [okr]+7 853 (+9 534) +103 (+85)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Europe 756 275 975 2.95% 4.97% 5.61%
2 North America 595 213 342 2.67% 1.92% 1.82%
3 South America 439 038 051 0.78% 0.52% 0.54%
4 Australia/Oceania 43 515 449 0.62% 0.49% 0.50%
5 Asia 4 682 387 607 0.41% 0.23% 0.22%
6 Africa 1 385 305 453 0.14% 0.05% 0.06%

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 Africa 1 385 305 453 2.37% (3.55)% (0.05)%
2 South America 439 038 051 2.43% 2.65% 0.52%
3 Asia 4 682 387 607 1.49% 2.00% 0.23%
4 North America 595 213 342 1.46% 1.78% 1.92%
5 Europe 756 275 975 1.37% 1.65% 4.97%
6 Australia/Oceania 43 515 449 1.05% 1.26% 0.49%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 439 038 051 1 185 188 2.700
2 North America 595 213 342 1 166 715 1.960
3 Europe 756 275 975 1 421 914 1.880
4 Asia 4 682 387 607 1 211 262 0.259
5 Africa 1 385 305 453 223 768 0.162
6 Australia/Oceania 43 515 449 4 489 0.103

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 Europe CZ Czechia 10 737 105 4.83% 15.62% 20.90%
2 Europe SK Slovakia 5 463 386 5.58% 15.34% 17.44%
3 Europe NL Netherlands 17 188 541 4.60% 12.15% 14.95%
4 Europe AT Austria 9 079 123 5.63% 14.73% 13.96%
5 Europe BE Belgium 11 661 012 5.59% 13.64% 13.28%
6 Europe HR Croatia 4 069 414 6.14% 14.00% 13.12%
7 Europe HU Hungary 9 625 618 3.27% 10.32% 12.06%
8 Europe SI Slovenia 2 079 343 7.86% 16.52% 11.86%
9 Asia GE Georgia 3 978 325 10.58% 12.76% 11.69%
10 Europe IE Ireland 5 015 805 5.44% 9.87% 10.85%
11 Europe DK Denmark 5 821 073 2.98% 7.10% 8.86%
12 Europe DE Germany 84 163 150 2.61% 6.45% 8.19%
13 Europe GB United Kingdom 68 390 701 6.37% 6.90% 7.58%
14 Europe LT Lithuania 2 668 479 7.12% 9.18% 7.47%
15 Europe PL Poland 37 787 922 1.89% 5.94% 7.35%
16 Europe GR Greece 10 350 956 4.27% 7.63% 7.19%
17 Europe CH Switzerland 8 744 181 3.38% 6.33% 6.92%
18 Europe FR France 65 477 969 2.22% 3.33% 6.26%
19 Europe NO Norway 5 481 222 2.35% 4.34% 5.27%
20 Asia JO Jordan 10 346 428 1.79% 3.65% 5.09%
21 Europe PT Portugal 10 154 610 1.75% 2.39% 3.69%
22 Europe BG Bulgaria 6 874 364 3.94% 5.16% 3.64%
23 Asia TR Turkey 85 622 825 3.53% 3.53% 3.32%
24 Europe UA Ukraine 43 361 664 2.79% 4.69% 3.14%
25 Europe RS Serbia 8 687 534 6.15% 4.99% 3.07%
26 North America US USA 333 749 517 3.97% 3.11% 2.98%
27 Europe RU Russia 146 023 052 2.29% 3.04% 2.76%
28 Asia LB Lebanon 6 782 161 1.60% 1.79% 2.60%
29 Europe IT Italy 60 335 946 1.13% 1.78% 2.53%
30 Asia SG Singapore 5 915 445 3.39% 4.41% 2.48%
31 Europe BA Bosnia and Herzegovina 3 251 918 2.16% 2.66% 2.45%
32 Europe MK North Macedonia 2 083 253 2.85% 2.55% 2.21%
33 Asia LA Laos 7 424 843 0.92% 1.84% 2.14%
34 Europe ES Spain 46 780 416 1.31% 1.34% 2.11%
35 Europe BY Belarus 9 444 922 2.20% 2.31% 2.08%
36 Europe SE Sweden 10 188 382 1.02% 1.24% 2.07%
37 Asia AZ Azerbaijan 10 268 474 2.38% 2.24% 1.92%
38 Asia AM Armenia 2 971 083 3.65% 3.90% 1.87%
39 Asia MY Malaysia 32 952 474 4.48% 1.97% 1.84%
40 Europe MD Moldova 4 020 688 2.60% 2.52% 1.78%
41 Europe FI Finland 5 552 905 1.41% 1.97% 1.76%
42 Asia VN Vietnam 98 577 682 1.09% 1.32% 1.68%
43 Asia MN Mongolia 3 352 926 6.35% 2.53% 1.52%
44 Europe AL Albania 2 873 348 2.33% 2.04% 1.43%
45 South America CL Chile 19 348 368 0.75% 1.40% 1.34%
46 South America BO Bolivia 11 898 193 0.54% 0.83% 1.04%
47 Europe RO Romania 19 055 941 3.66% 2.64% 0.99%
48 Asia KR South Korea 51 331 649 0.49% 0.70% 0.95%
49 North America CA Canada 38 210 346 0.94% 0.80% 0.94%
50 Asia TH Thailand 70 047 905 2.07% 1.13% 0.92%
51 Africa LY Libya 7 003 425 1.64% 0.87% 0.91%
52 South America UY Uruguay 3 490 770 0.52% 0.67% 0.77%
53 Africa ZA South Africa 60 366 253 0.84% 0.36% 0.75%
54 Asia QA Qatar 2 807 805 0.60% 0.60% 0.67%
55 Asia IL Israel 9 326 000 4.95% 0.65% 0.67%
56 Australia/Oceania AU Australia 25 918 370 0.68% 0.62% 0.65%
57 North America PA Panama 4 410 796 0.93% 0.47% 0.59%
58 Asia IR Iran 85 513 384 2.50% 0.88% 0.58%
59 Asia KZ Kazakhstan 19 094 373 2.09% 0.73% 0.58%
60 South America CO Colombia 51 650 076 0.52% 0.52% 0.56%
61 South America BR Brazil 214 697 495 1.00% 0.53% 0.53%
62 South America PE Peru 33 621 349 0.36% 0.41% 0.50%
63 South America AR Argentina 45 782 522 0.84% 0.36% 0.47%
64 North America SV El Salvador 6 532 524 0.49% 0.39% 0.46%
65 North America DO Dominican R. 11 001 802 0.59% 0.91% 0.42%
66 Australia/Oceania NZ New Zealand 5 002 100 0.18% 0.41% 0.38%
67 Asia LK Sri Lanka 21 540 326 1.14% 0.42% 0.35%
68 South America VE Venezuela 28 321 854 0.44% 0.35% 0.31%
69 Africa BW Botswana 2 418 722 3.30% 1.40% 0.29%
70 South America PR Puerto Rico 3 193 694 1.26% 0.40% 0.28%
71 South America EC Ecuador 18 021 847 0.22% 0.21% 0.23%
72 North America GT Guatemala 18 383 960 1.33% 0.36% 0.22%
73 Asia IQ Iraq 41 497 561 1.02% 0.25% 0.21%
74 North America JM Jamaica 2 979 460 1.27% 0.29% 0.21%
75 North America CR Costa Rica 5 159 930 3.03% 0.49% 0.19%
76 Africa ZW Zimbabwe 15 168 859 0.15% 0.06% 0.18%
77 North America CU Cuba 11 316 828 4.85% 0.35% 0.18%
78 Africa MR Mauritania 4 822 230 0.27% 0.16% 0.16%
79 South America PY Paraguay 7 256 453 0.14% 0.11% 0.16%
80 Africa TN Tunisia 11 993 558 0.98% 0.16% 0.14%
81 North America MX Mexico 130 848 998 0.72% 0.20% 0.14%
82 Africa GA Gabon 2 299 914 0.52% 0.32% 0.14%
83 Africa EG Egypt 105 062 217 0.07% 0.10% 0.11%
84 Asia KG Kyrgyzstan 6 676 362 0.26% 0.12% 0.10%
85 Australia/Oceania PG Papua New Guinea 9 186 546 0.19% 0.23% 0.09%
86 Asia NP Nepal 29 877 524 0.40% 0.12% 0.09%
87 Asia MM Myanmar 54 925 960 0.38% 0.15% 0.08%
88 Asia AE Arab Emirates 10 059 416 0.56% 0.08% 0.08%
89 Asia IN India 1 399 198 423 0.20% 0.09% 0.08%
90 Asia UZ Uzbekistan 34 155 079 0.18% 0.08% 0.07%
91 Asia PH Philippines 111 643 668 1.09% 0.15% 0.07%
92 Asia KW Kuwait 4 359 873 0.30% 0.06% 0.07%
93 Asia SY Syria 18 101 095 0.12% 0.10% 0.07%
94 North America HN Honduras 10 127 318 0.76% 0.10% 0.06%
95 Africa ER Eritrea 3 615 830 0.02% 0.06% 0.06%
96 North America HT Haiti 11 599 128 0.04% 0.05% 0.06%
97 Africa LS Lesotho 2 166 278 0.38% 0.03% 0.06%
98 Africa NA Namibia 2 605 944 0.36% 0.04% 0.05%
99 Africa DZ Algeria 44 970 242 0.08% 0.04% 0.05%
100 Africa SD Sudan 45 295 406 0.01% 0.02% 0.05%
101 Africa CG Congo 5 709 908 0.10% 0.09% 0.04%
102 Africa BF Burkina Faso 21 712 505 0.01% 0.02% 0.04%
103 Africa MA Morocco 37 529 355 0.82% 0.04% 0.04%
104 Africa ML Mali 21 074 185 0.01% 0.03% 0.03%
105 Africa CM Cameroon 27 479 060 0.09% 0.07% 0.02%
106 Asia KH Cambodia 17 046 163 0.24% 0.04% 0.02%
107 Asia PK Pakistan 226 953 710 0.11% 0.02% 0.02%
108 North America NI Nicaragua 6 736 031 0.09% 0.03% 0.02%
109 Asia OM Oman 5 290 029 0.13% 0.02% 0.02%
110 Africa MG Madagascar 28 696 267 0.01% 0.01% 0.02%
111 Asia BD Bangladesh 167 010 523 0.16% 0.02% 0.01%
112 Africa ET Ethiopia 118 985 257 0.08% 0.02% 0.01%
113 Asia ID Indonesia 277 615 084 0.27% 0.02% 0.01%
114 Asia AF Afghanistan 40 166 836 0.02% 0.01% 0.01%
115 Africa SS South Sudan 11 379 349 0.01% 0.01% 0.01%
116 Africa BI Burundi 12 390 624 0.10% 0.01% 0.01%
117 Africa UG Uganda 47 779 415 0.07% 0.01% 0.01%
118 Africa KE Kenya 55 444 596 0.09% 0.01% 0.01%
119 Asia JP Japan 125 928 213 0.61% 0.01% 0.01%
120 Africa TG Togo 8 552 791 0.12% 0.01% 0.01%
121 Asia SA Saudi Arabia 35 580 416 0.06% 0.01% 0.01%
122 Africa RW Rwanda 13 405 654 0.21% 0.02% 0.01%
123 Africa NE Niger 25 442 440 0.01% 0.01% 0.01%
124 Africa ZM Zambia 19 110 787 0.07% 0.01% 0.01%
125 Asia HK Hong Kong 7 583 040 0.01% 0.01% 0.01%
126 Africa CI Ivory Coast 27 300 772 0.04% 0.01% 0.01%
127 Africa AO Angola 34 309 017 0.06% 0.01% 0.01%
128 Africa MZ Mozambique 32 491 630 0.08% 0.00% 0.01%
129 Africa SO Somalia 16 519 195 0.05% 0.02% 0.01%
130 Africa MW Malawi 19 827 980 0.04% 0.00% 0.01%
131 Asia TW Taiwan 23 877 798 0.00% 0.00% 0.01%
132 Africa CD DR Congo 93 404 166 0.01% 0.00% 0.01%
133 Africa NG Nigeria 213 355 138 0.02% 0.00% 0.00%
134 Africa GW Guinea-Bissau 2 033 700 0.09% 0.06% 0.00%
135 Africa GN Guinea 13 635 732 0.04% 0.00% 0.00%
136 Asia YE Yemen 30 753 988 0.01% 0.00% 0.00%
137 Africa LR Liberia 5 225 590 0.01% 0.00% 0.00%
138 Africa SN Senegal 17 366 956 0.06% 0.00% 0.00%
139 Africa BJ Benin 12 571 573 0.13% 0.00% 0.00%
140 Africa TZ Tanzania 62 136 020 0.04% 0.00% 0.00%
141 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
142 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
143 Asia TJ Tajikistan 9 840 270 0.00% 0.00% 0.00%
144 Africa TD Chad 17 091 204 0.00% 0.00% 0.00%
145 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
146 Africa SL Sierra Leone 8 206 203 0.00% 0.00% 0.00%
147 Africa CF Central African R. 4 948 466 0.09% 0.01% 0.00%
148 Asia PS Palestine 5 268 925 0.00% 0.00% 0.00%
149 Africa GM Gambia 2 512 513 0.07% 0.00% 0.00%
150 Africa GH Ghana 31 989 394 0.08% 0.01% 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 Asia YE Yemen 30 753 988 19.32% (21.58)% (0.00)%
2 Africa TD Chad 17 091 204 5.15% (15.79)% (0.00)%
3 South America PY Paraguay 7 256 453 11.09% 13.45% 0.11%
4 Africa SO Somalia 16 519 195 6.58% (12.26)% (0.02)%
5 Africa BF Burkina Faso 21 712 505 5.96% (9.99)% (0.02)%
6 Africa SN Senegal 17 366 956 3.18% (9.09)% (0.00)%
7 Africa SD Sudan 45 295 406 8.24% (8.88)% (0.02)%
8 Asia PH Philippines 111 643 668 1.61% 7.88% 0.15%
9 Africa NE Niger 25 442 440 4.93% (7.31)% (0.01)%
10 Asia KH Cambodia 17 046 163 3.23% (7.23)% (0.04)%
11 Africa NA Namibia 2 605 944 4.17% (6.86)% (0.04)%
12 Africa EG Egypt 105 062 217 5.80% 6.64% 0.10%
13 Africa GM Gambia 2 512 513 4.33% (6.25)% (0.00)%
14 North America JM Jamaica 2 979 460 3.08% 6.18% 0.29%
15 North America HT Haiti 11 599 128 3.66% (5.02)% (0.05)%
16 North America HN Honduras 10 127 318 2.87% 4.82% 0.10%
17 Europe BA Bosnia and Herzegovina 3 251 918 4.47% 4.65% 2.66%
18 Europe RO Romania 19 055 941 3.25% 4.30% 2.64%
19 North America MX Mexico 130 848 998 4.43% 4.28% 0.20%
20 Africa DZ Algeria 44 970 242 3.85% (4.27)% (0.04)%
21 Europe MD Moldova 4 020 688 2.84% 4.24% 2.52%
22 Europe BG Bulgaria 6 874 364 3.99% 3.95% 5.16%
23 Africa MW Malawi 19 827 980 5.00% (3.92)% (0.00)%
24 North America GT Guatemala 18 383 960 2.10% 3.89% 0.36%
25 Africa CG Congo 5 709 908 3.10% (3.86)% (0.09)%
26 Africa ET Ethiopia 118 985 257 2.59% (3.78)% (0.02)%
27 Africa ML Mali 21 074 185 2.99% (3.66)% (0.03)%
28 Africa MZ Mozambique 32 491 630 1.16% (3.61)% (0.00)%
29 Africa TZ Tanzania 62 136 020 2.76% (3.42)% (0.00)%
30 Africa LS Lesotho 2 166 278 3.23% (3.38)% (0.03)%
31 Asia KG Kyrgyzstan 6 676 362 1.69% 3.35% 0.12%
32 Africa ER Eritrea 3 615 830 3.41% (3.30)% (0.06)%
33 Europe MK North Macedonia 2 083 253 3.67% 3.21% 2.55%
34 Europe RU Russia 146 023 052 3.54% 3.19% 3.04%
35 Asia SA Saudi Arabia 35 580 416 1.97% (3.19)% (0.01)%
36 Asia IN India 1 399 198 423 1.44% (3.16)% (0.09)%
37 Europe UA Ukraine 43 361 664 3.00% 3.15% 4.69%
38 Asia AM Armenia 2 971 083 2.81% 3.11% 3.90%
39 Asia SY Syria 18 101 095 3.87% 3.11% 0.10%
40 South America PE Peru 33 621 349 3.90% 3.09% 0.41%
41 South America EC Ecuador 18 021 847 3.90% 3.07% 0.21%
42 Africa NG Nigeria 213 355 138 1.94% (3.02)% (0.00)%
43 Asia ID Indonesia 277 615 084 4.43% (2.99)% (0.02)%
44 Africa TN Tunisia 11 993 558 3.61% 2.73% 0.16%
45 Africa ZW Zimbabwe 15 168 859 3.22% (2.64)% (0.06)%
46 Asia LK Sri Lanka 21 540 326 3.75% 2.60% 0.42%
47 North America CR Costa Rica 5 159 930 1.35% 2.57% 0.49%
48 Africa GH Ghana 31 989 394 1.29% (2.56)% (0.01)%
49 Africa KE Kenya 55 444 596 2.40% (2.54)% (0.01)%
50 Asia AF Afghanistan 40 166 836 4.12% (2.51)% (0.01)%
51 Australia/Oceania PG Papua New Guinea 9 186 546 2.08% 2.49% 0.23%
52 North America SV El Salvador 6 532 524 3.45% 2.42% 0.39%
53 Africa UG Uganda 47 779 415 1.53% (2.39)% (0.01)%
54 Africa ZA South Africa 60 366 253 3.02% 2.29% 0.36%
55 Africa GW Guinea-Bissau 2 033 700 3.25% (2.28)% (0.06)%
56 South America BR Brazil 214 697 495 2.47% 2.27% 0.53%
57 Africa LY Libya 7 003 425 1.44% 2.26% 0.87%
58 Asia IQ Iraq 41 497 561 1.00% 2.23% 0.25%
59 Africa MA Morocco 37 529 355 1.34% (2.07)% (0.04)%
60 Asia PK Pakistan 226 953 710 1.92% (2.05)% (0.02)%
61 South America CO Colombia 51 650 076 2.31% 2.03% 0.52%
62 Africa MR Mauritania 4 822 230 1.78% 2.01% 0.16%
63 Europe HU Hungary 9 625 618 1.98% 1.96% 10.32%
64 Africa AO Angola 34 309 017 3.10% 1.91% 0.01%
65 Africa CM Cameroon 27 479 060 1.90% 1.81% 0.07%
66 Africa CI Ivory Coast 27 300 772 3.11% 1.77% 0.01%
67 Asia KZ Kazakhstan 19 094 373 1.78% 1.77% 0.73%
68 Europe PL Poland 37 787 922 1.70% 1.69% 5.94%
69 Africa GN Guinea 13 635 732 2.72% 1.65% 0.00%
70 South America AR Argentina 45 782 522 2.29% 1.64% 0.36%
71 Asia GE Georgia 3 978 325 1.50% 1.61% 12.76%
72 Asia BD Bangladesh 167 010 523 1.74% 1.59% 0.02%
73 Asia MM Myanmar 54 925 960 3.56% 1.58% 0.15%
74 Africa GA Gabon 2 299 914 0.97% 1.56% 0.32%
75 Asia IR Iran 85 513 384 1.63% 1.54% 0.88%
76 Africa CD DR Congo 93 404 166 0.72% 1.48% 0.00%
77 Africa ZM Zambia 19 110 787 1.43% 1.30% 0.01%
78 North America US USA 333 749 517 1.24% 1.30% 3.11%
79 Africa RW Rwanda 13 405 654 1.40% 1.30% 0.02%
80 Asia AZ Azerbaijan 10 268 474 1.20% 1.29% 2.24%
81 Asia VN Vietnam 98 577 682 2.25% 1.26% 1.32%
82 Europe RS Serbia 8 687 534 0.89% 1.26% 4.99%
83 Europe HR Croatia 4 069 414 1.23% 1.25% 14.00%
84 Europe GR Greece 10 350 956 1.24% 1.24% 7.63%
85 South America BO Bolivia 11 898 193 2.14% 1.21% 0.83%
86 Europe LT Lithuania 2 668 479 1.30% 1.19% 9.18%
87 Asia KR South Korea 51 331 649 0.68% 1.11% 0.70%
88 Asia NP Nepal 29 877 524 1.20% 1.10% 0.12%
89 South America PR Puerto Rico 3 193 694 1.59% 1.08% 0.40%
90 Europe AL Albania 2 873 348 0.99% 1.07% 2.04%
91 Asia UZ Uzbekistan 34 155 079 0.78% 1.03% 0.08%
92 North America PA Panama 4 410 796 1.14% 1.02% 0.47%
93 North America CA Canada 38 210 346 0.90% 1.02% 0.80%
94 South America VE Venezuela 28 321 854 1.21% 0.99% 0.35%
95 Asia LB Lebanon 6 782 161 0.78% 0.93% 1.79%
96 Asia MN Mongolia 3 352 926 0.50% 0.91% 2.53%
97 Asia JP Japan 125 928 213 0.37% 0.91% 0.01%
98 Asia MY Malaysia 32 952 474 1.34% 0.90% 1.97%
99 Africa MG Madagascar 28 696 267 1.43% 0.89% 0.01%
100 South America CL Chile 19 348 368 1.97% 0.88% 1.40%
101 South America UY Uruguay 3 490 770 0.90% 0.86% 0.67%
102 Europe IT Italy 60 335 946 0.92% 0.86% 1.78%
103 Europe SK Slovakia 5 463 386 0.83% 0.84% 15.34%
104 Asia TR Turkey 85 622 825 0.84% 0.80% 3.53%
105 Europe BY Belarus 9 444 922 0.79% 0.79% 2.31%
106 Asia JO Jordan 10 346 428 0.97% 0.77% 3.65%
107 Europe CZ Czechia 10 737 105 0.72% 0.72% 15.62%
108 Asia TH Thailand 70 047 905 0.99% 0.68% 1.13%
109 Europe PT Portugal 10 154 610 0.61% 0.66% 2.39%
110 Australia/Oceania AU Australia 25 918 370 0.65% 0.65% 0.62%
111 North America NI Nicaragua 6 736 031 0.30% 0.64% 0.03%
112 Asia OM Oman 5 290 029 2.48% 0.60% 0.02%
113 Europe DE Germany 84 163 150 0.58% 0.58% 6.45%
114 Asia TW Taiwan 23 877 798 6.10% 0.57% 0.00%
115 Asia IL Israel 9 326 000 0.36% 0.53% 0.65%
116 Asia AE Arab Emirates 10 059 416 0.28% 0.53% 0.08%
117 Africa CF Central African R. 4 948 466 0.07% 0.53% 0.01%
118 Europe SI Slovenia 2 079 343 0.54% 0.47% 16.52%
119 Asia KW Kuwait 4 359 873 0.64% 0.47% 0.06%
120 North America CU Cuba 11 316 828 0.87% 0.45% 0.35%
121 Europe ES Spain 46 780 416 0.72% 0.45% 1.34%
122 Africa TG Togo 8 552 791 0.81% 0.45% 0.01%
123 Europe FR France 65 477 969 0.43% 0.43% 3.33%
124 Europe FI Finland 5 552 905 0.45% 0.41% 1.97%
125 Europe GB United Kingdom 68 390 701 0.36% 0.38% 6.90%
126 Asia LA Laos 7 424 843 0.28% 0.38% 1.84%
127 Asia SG Singapore 5 915 445 0.36% 0.37% 4.41%
128 Europe SE Sweden 10 188 382 0.50% 0.37% 1.24%
129 Europe AT Austria 9 079 123 0.36% 0.34% 14.73%
130 Australia/Oceania NZ New Zealand 5 002 100 0.23% 0.32% 0.41%
131 Europe NO Norway 5 481 222 0.23% 0.28% 4.34%
132 Europe BE Belgium 11 661 012 0.32% 0.28% 13.64%
133 North America DO Dominican R. 11 001 802 0.38% 0.27% 0.91%
134 Europe IE Ireland 5 015 805 0.27% 0.25% 9.87%
135 Europe NL Netherlands 17 188 541 0.25% 0.24% 12.15%
136 Europe CH Switzerland 8 744 181 0.27% 0.23% 6.33%
137 Europe DK Denmark 5 821 073 0.24% 0.23% 7.10%
138 Africa BW Botswana 2 418 722 0.83% 0.12% 1.40%
139 Asia QA Qatar 2 807 805 0.06% 0.00% 0.60%
140 Africa SS South Sudan 11 379 349 0.77% 0.00% 0.01%
141 Africa BI Burundi 12 390 624 0.03% 0.00% 0.01%
142 Asia HK Hong Kong 7 583 040 0.23% 0.00% 0.01%
143 Africa BJ Benin 12 571 573 0.32% 0.00% 0.00%
144 Africa LR Liberia 5 225 590 33.49% 0.00% 0.00%
145 Africa SL Sierra Leone 8 206 203 0.58% 0.00% 0.00%
146 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
147 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
148 Asia TJ Tajikistan 9 840 270 0.00% 0.00% 0.00%
149 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
150 Asia PS Palestine 5 268 925 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 33 621 349 201 144 5.983
2 Europe BG Bulgaria 6 874 364 28 542 4.152
3 Europe BA Bosnia and Herzegovina 3 251 918 12 628 3.883
4 Europe MK North Macedonia 2 083 253 7 592 3.644
5 Europe HU Hungary 9 625 618 34 931 3.629
6 Europe CZ Czechia 10 737 105 33 253 3.097
7 Asia GE Georgia 3 978 325 12 191 3.064
8 Europe RO Romania 19 055 941 56 608 2.971
9 South America BR Brazil 214 697 495 614 642 2.863
10 Europe HR Croatia 4 069 414 10 967 2.695
11 Europe SI Slovenia 2 079 343 5 566 2.677
12 Europe SK Slovakia 5 463 386 14 606 2.673
13 Asia AM Armenia 2 971 083 7 631 2.568
14 South America AR Argentina 45 782 522 116 562 2.546
15 Europe LT Lithuania 2 668 479 6 779 2.540
16 South America CO Colombia 51 650 076 128 531 2.489
17 North America US USA 333 749 517 776 501 2.327
18 Europe BE Belgium 11 661 012 27 072 2.322
19 Europe MD Moldova 4 020 688 9 141 2.273
20 South America PY Paraguay 7 256 453 16 471 2.270
21 North America MX Mexico 130 848 998 294 132 2.248
22 Europe PL Poland 37 787 922 84 655 2.240
23 Europe IT Italy 60 335 946 133 921 2.220
24 Europe GB United Kingdom 68 390 701 145 140 2.122
25 Africa TN Tunisia 11 993 558 25 376 2.116
26 Europe UA Ukraine 43 361 664 87 057 2.008
27 South America CL Chile 19 348 368 38 356 1.982
28 Europe RU Russia 146 023 052 277 640 1.901
29 Europe ES Spain 46 780 416 88 080 1.883
30 South America EC Ecuador 18 021 847 33 250 1.845
31 Europe PT Portugal 10 154 610 18 458 1.818
32 Europe FR France 65 477 969 116 751 1.783
33 Europe GR Greece 10 350 956 18 234 1.762
34 South America UY Uruguay 3 490 770 6 130 1.756
35 North America PA Panama 4 410 796 7 364 1.669
36 South America BO Bolivia 11 898 193 19 188 1.613
37 Asia IR Iran 85 513 384 129 912 1.519
38 Africa ZA South Africa 60 366 253 89 871 1.489
39 Europe SE Sweden 10 188 382 15 151 1.487
40 North America CR Costa Rica 5 159 930 7 293 1.413
41 Africa NA Namibia 2 605 944 3 573 1.371
42 Europe RS Serbia 8 687 534 11 744 1.352
43 Europe AT Austria 9 079 123 12 136 1.337
44 Asia LB Lebanon 6 782 161 8 735 1.288
45 Europe CH Switzerland 8 744 181 11 106 1.270
46 Europe DE Germany 84 163 150 102 205 1.214
47 Europe IE Ireland 5 015 805 5 707 1.138
48 Europe NL Netherlands 17 188 541 19 459 1.132
49 Asia JO Jordan 10 346 428 11 633 1.124
50 Europe AL Albania 2 873 348 3 101 1.079
51 North America HN Honduras 10 127 318 10 406 1.028
52 South America PR Puerto Rico 3 193 694 3 270 1.024
53 Africa BW Botswana 2 418 722 2 418 1.000
54 Asia KZ Kazakhstan 19 094 373 17 856 0.935
55 Asia MY Malaysia 32 952 474 30 474 0.925
56 Asia TR Turkey 85 622 825 77 038 0.900
57 Asia IL Israel 9 326 000 8 199 0.879
58 North America GT Guatemala 18 383 960 15 941 0.867
59 North America JM Jamaica 2 979 460 2 396 0.804
60 Africa LY Libya 7 003 425 5 466 0.780
61 Asia OM Oman 5 290 029 4 113 0.777
62 North America CA Canada 38 210 346 29 697 0.777
63 Asia AZ Azerbaijan 10 268 474 7 884 0.768
64 North America CU Cuba 11 316 828 8 305 0.734
65 Asia LK Sri Lanka 21 540 326 14 372 0.667
66 North America SV El Salvador 6 532 524 3 777 0.578
67 Asia MN Mongolia 3 352 926 1 935 0.577
68 Asia IQ Iraq 41 497 561 23 844 0.575
69 Asia KW Kuwait 4 359 873 2 465 0.565
70 Europe BY Belarus 9 444 922 5 097 0.540
71 Asia ID Indonesia 277 615 084 143 840 0.518
72 Europe DK Denmark 5 821 073 2 909 0.500
73 Asia PH Philippines 111 643 668 48 585 0.435
74 Asia KG Kyrgyzstan 6 676 362 2 752 0.412
75 Africa MA Morocco 37 529 355 14 779 0.394
76 Asia NP Nepal 29 877 524 11 529 0.386
77 North America DO Dominican R. 11 001 802 4 210 0.383
78 Asia MM Myanmar 54 925 960 19 111 0.348
79 Asia IN India 1 399 198 423 469 724 0.336
80 Africa ZW Zimbabwe 15 168 859 4 707 0.310
81 Africa LS Lesotho 2 166 278 663 0.306
82 Asia TH Thailand 70 047 905 20 847 0.298
83 Asia VN Vietnam 98 577 682 25 448 0.258
84 Asia SA Saudi Arabia 35 580 416 8 837 0.248
85 Europe FI Finland 5 552 905 1 356 0.244
86 Asia QA Qatar 2 807 805 611 0.218
87 Asia AE Arab Emirates 10 059 416 2 148 0.213
88 Africa EG Egypt 105 062 217 20 537 0.196
89 Europe NO Norway 5 481 222 1 060 0.193
90 Africa ZM Zambia 19 110 787 3 667 0.192
91 Asia AF Afghanistan 40 166 836 7 309 0.182
92 South America VE Venezuela 28 321 854 5 150 0.182
93 Africa MR Mauritania 4 822 230 835 0.173
94 Asia KH Cambodia 17 046 163 2 945 0.173
95 Asia BD Bangladesh 167 010 523 27 983 0.168
96 Asia SY Syria 18 101 095 2 755 0.152
97 Asia JP Japan 125 928 213 18 362 0.146
98 Africa GM Gambia 2 512 513 342 0.136
99 Africa DZ Algeria 44 970 242 6 076 0.135
100 Asia PK Pakistan 226 953 710 28 736 0.127
101 Asia SG Singapore 5 915 445 726 0.123
102 Africa GA Gabon 2 299 914 279 0.121
103 Africa MW Malawi 19 827 980 2 306 0.116
104 Africa SN Senegal 17 366 956 1 885 0.108
105 Africa RW Rwanda 13 405 654 1 343 0.100
106 Africa KE Kenya 55 444 596 5 335 0.096
107 Africa SO Somalia 16 519 195 1 327 0.080
108 Australia/Oceania AU Australia 25 918 370 2 016 0.078
109 Africa GW Guinea-Bissau 2 033 700 148 0.073
110 Asia KR South Korea 51 331 649 3 705 0.072
111 Africa SD Sudan 45 295 406 3 159 0.070
112 Africa UG Uganda 47 779 415 3 252 0.068
113 Africa CM Cameroon 27 479 060 1 804 0.066
114 North America HT Haiti 11 599 128 746 0.064
115 Asia YE Yemen 30 753 988 1 950 0.063
116 Africa CG Congo 5 709 908 354 0.062
117 Australia/Oceania PG Papua New Guinea 9 186 546 550 0.060
118 Africa MZ Mozambique 32 491 630 1 941 0.060
119 Africa ET Ethiopia 118 985 257 6 771 0.057
120 Africa LR Liberia 5 225 590 287 0.055
121 Africa AO Angola 34 309 017 1 735 0.051
122 Asia UZ Uzbekistan 34 155 079 1 409 0.041
123 Africa GH Ghana 31 989 394 1 209 0.038
124 Asia TW Taiwan 23 877 798 848 0.035
125 Africa MG Madagascar 28 696 267 967 0.034
126 North America NI Nicaragua 6 736 031 213 0.032
127 Africa ML Mali 21 074 185 610 0.029
128 Africa GN Guinea 13 635 732 387 0.028
129 Africa TG Togo 8 552 791 243 0.028
130 Asia HK Hong Kong 7 583 040 213 0.028
131 Africa CI Ivory Coast 27 300 772 704 0.026
132 Asia LA Laos 7 424 843 178 0.024
133 Africa CF Central African R. 4 948 466 101 0.020
134 Africa ER Eritrea 3 615 830 60 0.017
135 Africa SL Sierra Leone 8 206 203 121 0.015
136 Africa NG Nigeria 213 355 138 2 978 0.014
137 Africa BF Burkina Faso 21 712 505 286 0.013
138 Africa BJ Benin 12 571 573 161 0.013
139 Africa CD DR Congo 93 404 166 1 107 0.012
140 Africa SS South Sudan 11 379 349 133 0.012
141 Africa TZ Tanzania 62 136 020 730 0.012
142 Africa TD Chad 17 091 204 181 0.011
143 Africa NE Niger 25 442 440 259 0.010
144 Australia/Oceania NZ New Zealand 5 002 100 44 0.009
145 Africa BI Burundi 12 390 624 14 0.001
146 Asia PS Palestine 5 268 925 4 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 9 840 270 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"