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": 2021-11-29 13:27
(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 +8 526 (+10 478) +37 (+39)
CZ Czechia +9 292 (+12 518) +51 (+78)
DE Germany +0 (+38 444) +0 (+71)
HU Hungary +27 830 (+0) +460 (+0)
PL Poland +13 115 (+20 594) +18 (+51)
SK Slovakia, [gov], [okr]+5 054 (+7 575) +67 (+46)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Europe 756 272 303 2.76% 4.34% 4.12%
2 North America 595 175 527 2.65% 1.69% 1.31%
3 South America 439 008 935 0.79% 0.48% 0.32%
4 Australia/Oceania 43 511 317 0.61% 0.46% 0.32%
5 Asia 4 682 112 071 0.42% 0.22% 0.17%
6 Africa 1 385 041 623 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 1 385 041 623 2.39% (3.97)% (0.05)%
2 South America 439 008 935 2.40% 2.34% 0.48%
3 Asia 4 682 112 071 1.49% 1.89% 0.22%
4 North America 595 175 527 1.46% 1.85% 1.69%
5 Europe 756 272 303 1.34% 1.61% 4.34%
6 Australia/Oceania 43 511 317 1.05% 1.28% 0.46%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 439 008 935 1 182 988 2.695
2 North America 595 175 527 1 160 522 1.950
3 Europe 756 272 303 1 401 995 1.854
4 Asia 4 682 112 071 1 204 145 0.257
5 Africa 1 385 041 623 222 989 0.161
6 Australia/Oceania 43 511 317 4 445 0.102

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 10 736 943 3.96% 12.69% 15.23%
2 Europe SK Slovakia 5 463 364 4.82% 12.93% 13.05%
3 Europe BE Belgium 11 660 599 4.76% 11.33% 12.88%
4 Europe HU Hungary 9 625 818 2.98% 9.69% 12.65%
5 Europe NL Netherlands 17 188 231 4.02% 10.25% 11.39%
6 Europe AT Austria 9 078 703 5.08% 13.21% 11.33%
7 Europe SI Slovenia 2 079 340 7.36% 15.60% 9.59%
8 Europe HR Croatia 4 069 620 5.56% 12.54% 8.28%
9 Asia GE Georgia 3 978 387 10.33% 11.80% 8.23%
10 Europe IE Ireland 5 015 353 5.04% 8.63% 7.41%
11 Europe DK Denmark 5 820 906 2.65% 5.95% 6.19%
12 Europe DE Germany 84 160 960 2.28% 5.27% 6.17%
13 Europe LT Lithuania 2 668 788 6.83% 8.84% 5.60%
14 Europe GR Greece 10 351 371 4.02% 6.85% 5.49%
15 Europe GB United Kingdom 68 387 784 6.15% 6.32% 5.36%
16 Europe PL Poland 37 788 261 1.56% 4.82% 5.28%
17 Europe CH Switzerland 8 743 663 2.95% 4.69% 4.02%
18 Europe FR France 65 476 789 2.02% 2.36% 3.43%
19 Europe NO Norway 5 480 875 2.10% 3.47% 3.15%
20 Europe BG Bulgaria 6 874 790 3.79% 5.09% 3.08%
21 Asia JO Jordan 10 345 598 1.56% 2.80% 2.89%
22 Europe UA Ukraine 43 363 807 2.66% 4.62% 2.60%
23 Asia TR Turkey 85 615 390 3.47% 3.33% 2.54%
24 Europe RS Serbia 8 687 821 6.03% 5.25% 2.52%
25 Europe PT Portugal 10 154 853 1.65% 1.86% 2.34%
26 Europe FI Finland 5 552 834 1.40% 1.92% 2.31%
27 Europe BA Bosnia and Herzegovina 3 252 085 2.04% 2.69% 2.22%
28 North America US USA 333 733 637 3.90% 2.72% 2.15%
29 Asia SG Singapore 5 915 068 3.29% 4.56% 2.13%
30 Europe RU Russia 146 022 541 2.22% 2.91% 2.00%
31 Asia AM Armenia 2 971 038 3.60% 4.10% 1.64%
32 Europe ES Spain 46 780 268 1.46% 0.97% 1.59%
33 Europe IT Italy 60 336 672 1.05% 1.45% 1.58%
34 Europe MK North Macedonia 2 083 254 2.77% 2.38% 1.56%
35 Europe SE Sweden 10 187 866 0.96% 1.12% 1.53%
36 Asia VN Vietnam 98 570 511 1.05% 1.10% 1.52%
37 Europe BY Belarus 9 444 948 2.14% 2.20% 1.46%
38 Asia LA Laos 7 423 978 0.83% 1.59% 1.41%
39 Asia MY Malaysia 32 949 075 4.55% 1.85% 1.39%
40 Europe AL Albania 2 873 374 2.28% 2.00% 1.38%
41 Asia AZ Azerbaijan 10 267 726 2.32% 2.15% 1.37%
42 Asia MN Mongolia 3 352 493 6.39% 2.64% 1.35%
43 Europe MD Moldova 4 020 764 2.53% 2.52% 1.29%
44 South America CL Chile 19 347 024 0.71% 1.31% 0.97%
45 Asia LB Lebanon 6 782 411 1.51% 1.35% 0.97%
46 Europe RO Romania 19 056 987 3.62% 3.03% 0.93%
47 Africa LY Libya 7 002 659 1.74% 0.81% 0.74%
48 Africa ZA South Africa 60 360 124 0.84% 0.22% 0.72%
49 Asia TH Thailand 70 046 474 2.12% 1.12% 0.70%
50 Asia KZ Kazakhstan 19 092 532 2.27% 0.82% 0.65%
51 South America BO Bolivia 11 896 887 0.51% 0.70% 0.62%
52 Asia KR South Korea 51 331 289 0.46% 0.57% 0.60%
53 North America CA Canada 38 207 636 0.91% 0.70% 0.52%
54 North America DO Dominican R. 11 000 911 0.58% 0.93% 0.48%
55 Asia QA Qatar 2 807 805 0.59% 0.54% 0.45%
56 South America PR Puerto Rico 3 193 694 1.35% 0.44% 0.44%
57 South America UY Uruguay 3 490 672 0.49% 0.63% 0.44%
58 Australia/Oceania AU Australia 25 915 946 0.66% 0.57% 0.42%
59 North America CR Costa Rica 5 159 549 3.18% 0.69% 0.40%
60 South America CO Colombia 51 645 633 0.54% 0.46% 0.40%
61 Asia IR Iran 85 504 572 2.60% 0.88% 0.39%
62 North America PA Panama 4 410 239 0.96% 0.42% 0.38%
63 South America PE Peru 33 617 584 0.36% 0.36% 0.34%
64 Australia/Oceania NZ New Zealand 5 002 100 0.17% 0.39% 0.33%
65 Africa BW Botswana 2 418 332 3.84% 1.48% 0.33%
66 Asia IL Israel 9 326 000 5.02% 0.63% 0.33%
67 Asia LK Sri Lanka 21 539 591 1.16% 0.39% 0.30%
68 South America BR Brazil 214 685 129 1.01% 0.50% 0.28%
69 North America GT Guatemala 18 381 240 1.35% 0.38% 0.26%
70 South America VE Venezuela 28 322 512 0.44% 0.33% 0.22%
71 Africa GA Gabon 2 299 483 0.52% 0.40% 0.21%
72 South America AR Argentina 45 779 126 0.88% 0.30% 0.20%
73 North America JM Jamaica 2 979 354 1.28% 0.30% 0.17%
74 North America CU Cuba 11 316 884 5.10% 0.40% 0.16%
75 South America EC Ecuador 18 019 649 0.23% 0.19% 0.16%
76 Asia IQ Iraq 41 490 144 1.09% 0.24% 0.16%
77 Africa MR Mauritania 4 821 224 0.28% 0.15% 0.13%
78 North America MX Mexico 130 837 902 0.74% 0.18% 0.12%
79 Asia PS Palestine 5 267 950 0.01% 0.03% 0.12%
80 Australia/Oceania PG Papua New Guinea 9 185 155 0.19% 0.24% 0.09%
81 Asia NP Nepal 29 873 223 0.41% 0.11% 0.08%
82 Africa TN Tunisia 11 992 545 1.03% 0.15% 0.08%
83 Asia KG Kyrgyzstan 6 675 479 0.29% 0.12% 0.08%
84 North America HN Honduras 10 126 026 0.85% 0.12% 0.07%
85 Asia PH Philippines 111 631 712 1.11% 0.18% 0.07%
86 Asia MM Myanmar 54 922 975 0.40% 0.15% 0.07%
87 South America PY Paraguay 7 255 735 0.14% 0.09% 0.06%
88 Africa EG Egypt 105 046 372 0.07% 0.09% 0.06%
89 Asia AE Arab Emirates 10 058 437 0.61% 0.08% 0.06%
90 Asia IN India 1 399 087 302 0.21% 0.09% 0.05%
91 Asia UZ Uzbekistan 34 151 101 0.18% 0.08% 0.05%
92 Africa ER Eritrea 3 615 427 0.02% 0.05% 0.05%
93 Africa NA Namibia 2 605 566 0.39% 0.04% 0.04%
94 Asia KW Kuwait 4 359 355 0.41% 0.06% 0.04%
95 Asia SY Syria 18 097 600 0.12% 0.11% 0.04%
96 Africa CM Cameroon 27 473 627 0.09% 0.09% 0.04%
97 Africa CG Congo 5 708 791 0.10% 0.14% 0.04%
98 Africa DZ Algeria 44 963 743 0.09% 0.03% 0.03%
99 North America SV El Salvador 6 532 256 0.48% 0.29% 0.03%
100 Africa MG Madagascar 28 690 413 0.00% 0.01% 0.02%
101 North America NI Nicaragua 6 735 385 0.09% 0.03% 0.02%
102 Africa ML Mali 21 069 384 0.01% 0.02% 0.02%
103 Africa ZW Zimbabwe 15 167 085 0.16% 0.02% 0.02%
104 Africa MA Morocco 37 525 770 0.87% 0.04% 0.02%
105 Asia KH Cambodia 17 044 266 0.25% 0.04% 0.02%
106 Asia OM Oman 5 288 961 0.17% 0.02% 0.02%
107 Africa SO Somalia 16 515 547 0.05% 0.02% 0.01%
108 North America HT Haiti 11 597 988 0.04% 0.04% 0.01%
109 Africa CF Central African R. 4 947 777 0.09% 0.02% 0.01%
110 Africa LS Lesotho 2 166 139 0.41% 0.03% 0.01%
111 Asia PK Pakistan 226 918 495 0.11% 0.02% 0.01%
112 Asia AF Afghanistan 40 159 632 0.02% 0.01% 0.01%
113 Africa SS South Sudan 11 378 273 0.01% 0.01% 0.01%
114 Asia ID Indonesia 277 591 391 0.29% 0.02% 0.01%
115 Africa SD Sudan 45 286 992 0.01% 0.01% 0.01%
116 Africa RW Rwanda 13 403 014 0.22% 0.02% 0.01%
117 Asia BD Bangladesh 166 997 084 0.19% 0.01% 0.01%
118 Africa ET Ethiopia 118 961 845 0.08% 0.02% 0.01%
119 Africa NE Niger 25 435 214 0.01% 0.01% 0.01%
120 Africa GH Ghana 31 984 067 0.09% 0.01% 0.01%
121 Africa TG Togo 8 551 196 0.13% 0.01% 0.01%
122 Asia SA Saudi Arabia 35 575 968 0.07% 0.01% 0.01%
123 Africa BI Burundi 12 387 708 0.11% 0.01% 0.01%
124 Africa AO Angola 34 300 597 0.07% 0.01% 0.01%
125 Africa KE Kenya 55 434 865 0.09% 0.01% 0.01%
126 Asia JP Japan 125 931 373 0.64% 0.01% 0.01%
127 Asia HK Hong Kong 7 582 542 0.01% 0.00% 0.01%
128 Asia TW Taiwan 23 877 446 0.00% 0.00% 0.01%
129 Africa CD DR Congo 93 381 747 0.01% 0.00% 0.01%
130 Africa CI Ivory Coast 27 295 402 0.04% 0.01% 0.01%
131 Africa GN Guinea 13 632 802 0.04% 0.00% 0.01%
132 Africa ZM Zambia 19 106 551 0.07% 0.01% 0.01%
133 Africa NG Nigeria 213 313 133 0.02% 0.00% 0.00%
134 Africa GW Guinea-Bissau 2 033 318 0.10% 0.06% 0.00%
135 Asia YE Yemen 30 748 591 0.01% 0.00% 0.00%
136 Africa TZ Tanzania 62 122 018 0.04% 0.00% 0.00%
137 Africa MZ Mozambique 32 484 425 0.09% 0.00% 0.00%
138 Africa SN Senegal 17 363 327 0.07% 0.00% 0.00%
139 Africa MW Malawi 19 823 915 0.05% 0.00% 0.00%
140 Africa GM Gambia 2 511 954 0.09% 0.00% 0.00%
141 Africa BF Burkina Faso 21 707 789 0.01% 0.01% 0.00%
142 Africa LR Liberia 5 224 613 0.01% 0.00% 0.00%
143 Africa UG Uganda 47 767 518 0.07% 0.01% 0.00%
144 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
145 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
146 Asia TJ Tajikistan 9 838 510 0.00% 0.00% 0.00%
147 Africa TD Chad 17 087 325 0.00% 0.00% 0.00%
148 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
149 Africa SL Sierra Leone 8 204 871 0.00% 0.00% 0.00%
150 Africa BJ Benin 12 568 962 0.13% 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 Asia YE Yemen 30 748 591 19.31% (21.97)% (0.00)%
2 Africa MG Madagascar 28 690 413 2.01% (8.00)% (0.01)%
3 Africa SN Senegal 17 363 327 3.06% (7.95)% (0.00)%
4 South America PY Paraguay 7 255 735 10.47% (7.77)% (0.09)%
5 Africa NE Niger 25 435 214 4.75% (7.41)% (0.01)%
6 Africa SO Somalia 16 515 547 6.78% (7.40)% (0.02)%
7 Africa BF Burkina Faso 21 707 789 4.86% (6.75)% (0.01)%
8 Asia PH Philippines 111 631 712 1.57% 6.74% 0.18%
9 Asia KH Cambodia 17 044 266 3.19% (6.29)% (0.04)%
10 Africa EG Egypt 105 046 372 5.46% (5.87)% (0.09)%
11 Africa ZA South Africa 60 360 124 3.16% 5.70% 0.22%
12 North America JM Jamaica 2 979 354 3.04% 5.59% 0.30%
13 Africa MW Malawi 19 823 915 4.86% (5.17)% (0.00)%
14 Africa GM Gambia 2 511 954 4.60% (5.00)% (0.00)%
15 North America GT Guatemala 18 381 240 2.11% 4.74% 0.38%
16 North America MX Mexico 130 837 902 4.41% 4.70% 0.18%
17 Africa SD Sudan 45 286 992 7.43% (4.64)% (0.01)%
18 North America HN Honduras 10 126 026 2.84% 4.57% 0.12%
19 Europe BA Bosnia and Herzegovina 3 252 085 4.36% 4.48% 2.69%
20 North America HT Haiti 11 597 988 3.37% (4.24)% (0.04)%
21 Africa DZ Algeria 44 963 743 3.73% (4.10)% (0.03)%
22 Europe RO Romania 19 056 987 3.18% 3.96% 3.03%
23 Europe MD Moldova 4 020 764 2.76% 3.95% 2.52%
24 Europe BG Bulgaria 6 874 790 3.90% 3.76% 5.09%
25 Africa MZ Mozambique 32 484 425 1.18% (3.75)% (0.00)%
26 Africa CG Congo 5 708 791 3.07% 3.63% 0.14%
27 Asia AF Afghanistan 40 159 632 4.37% (3.45)% (0.01)%
28 Africa ML Mali 21 069 384 2.95% (3.42)% (0.02)%
29 Africa ER Eritrea 3 615 427 3.38% (3.36)% (0.05)%
30 Africa ET Ethiopia 118 961 845 2.54% (3.29)% (0.02)%
31 Africa CM Cameroon 27 473 627 1.88% (3.24)% (0.09)%
32 Africa LS Lesotho 2 166 139 3.29% (3.09)% (0.03)%
33 Africa GH Ghana 31 984 067 1.26% (3.08)% (0.01)%
34 Asia SA Saudi Arabia 35 575 968 1.82% (3.04)% (0.01)%
35 Africa NA Namibia 2 605 566 3.97% (2.98)% (0.04)%
36 Europe MK North Macedonia 2 083 254 3.59% 2.97% 2.38%
37 Asia ID Indonesia 277 591 391 4.42% (2.95)% (0.02)%
38 Europe RU Russia 146 022 541 3.46% 2.94% 2.91%
39 Asia KG Kyrgyzstan 6 675 479 1.57% 2.94% 0.12%
40 Asia AM Armenia 2 971 038 2.71% 2.89% 4.10%
41 Europe UA Ukraine 43 363 807 2.88% 2.88% 4.62%
42 Asia IN India 1 399 087 302 1.38% (2.77)% (0.09)%
43 South America PE Peru 33 617 584 3.87% 2.75% 0.36%
44 Africa ZW Zimbabwe 15 167 085 3.22% (2.74)% (0.02)%
45 Asia SY Syria 18 097 600 3.80% 2.73% 0.11%
46 Africa CI Ivory Coast 27 295 402 3.12% (2.73)% (0.01)%
47 Africa CD DR Congo 93 381 747 0.74% (2.72)% (0.00)%
48 Africa KE Kenya 55 434 865 2.42% (2.71)% (0.01)%
49 North America SV El Salvador 6 532 256 3.41% 2.66% 0.29%
50 Africa TN Tunisia 11 992 545 3.74% 2.64% 0.15%
51 Africa TD Chad 17 087 325 0.70% (2.63)% (0.00)%
52 Africa TZ Tanzania 62 122 018 2.76% (2.59)% (0.00)%
53 Australia/Oceania PG Papua New Guinea 9 185 155 2.10% 2.46% 0.24%
54 Asia LK Sri Lanka 21 539 591 3.76% 2.45% 0.39%
55 North America CR Costa Rica 5 159 549 1.34% 2.45% 0.69%
56 Africa LY Libya 7 002 659 1.39% 2.39% 0.81%
57 Africa NG Nigeria 213 313 133 1.94% (2.35)% (0.00)%
58 Africa GW Guinea-Bissau 2 033 318 3.23% (2.31)% (0.06)%
59 Africa GN Guinea 13 632 802 2.92% (2.25)% (0.00)%
60 Asia IQ Iraq 41 490 144 0.96% 2.16% 0.24%
61 Africa MA Morocco 37 525 770 1.33% (2.09)% (0.04)%
62 South America BR Brazil 214 685 129 2.44% 2.02% 0.50%
63 Africa UG Uganda 47 767 518 1.65% (2.00)% (0.01)%
64 Europe HU Hungary 9 625 818 1.99% 1.98% 9.69%
65 South America EC Ecuador 18 019 649 3.79% 1.93% 0.19%
66 Africa AO Angola 34 300 597 3.10% 1.89% 0.01%
67 South America CO Colombia 51 645 633 2.31% 1.83% 0.46%
68 Asia PK Pakistan 226 918 495 1.90% 1.80% 0.02%
69 Africa MR Mauritania 4 821 224 1.74% 1.74% 0.15%
70 Asia KZ Kazakhstan 19 092 532 1.83% 1.69% 0.82%
71 Asia MM Myanmar 54 922 975 3.75% 1.62% 0.15%
72 Asia BD Bangladesh 166 997 084 1.72% 1.60% 0.01%
73 Africa ZM Zambia 19 106 551 1.50% 1.52% 0.01%
74 Africa GA Gabon 2 299 483 0.97% 1.48% 0.40%
75 Asia GE Georgia 3 978 387 1.46% 1.48% 11.80%
76 South America AR Argentina 45 779 126 2.23% 1.46% 0.30%
77 Africa RW Rwanda 13 403 014 1.41% 1.45% 0.02%
78 Europe PL Poland 37 788 261 1.55% 1.45% 4.82%
79 Asia IR Iran 85 504 572 1.60% 1.44% 0.88%
80 North America US USA 333 733 637 1.23% 1.32% 2.72%
81 South America PR Puerto Rico 3 193 694 1.55% 1.26% 0.44%
82 Asia VN Vietnam 98 570 511 2.33% 1.23% 1.10%
83 Asia AZ Azerbaijan 10 267 726 1.17% 1.18% 2.15%
84 Europe LT Lithuania 2 668 788 1.28% 1.16% 8.84%
85 Europe GR Greece 10 351 371 1.19% 1.15% 6.85%
86 Europe RS Serbia 8 687 821 0.85% 1.13% 5.25%
87 Europe HR Croatia 4 069 620 1.14% 1.12% 12.54%
88 Asia NP Nepal 29 873 223 1.18% 1.11% 0.11%
89 Europe AL Albania 2 873 374 0.97% 1.03% 2.00%
90 Asia JP Japan 125 931 373 0.37% 0.99% 0.01%
91 South America BO Bolivia 11 896 887 2.11% 0.96% 0.70%
92 Asia KR South Korea 51 331 289 0.60% 0.95% 0.57%
93 North America PA Panama 4 410 239 1.15% 0.94% 0.42%
94 Asia MN Mongolia 3 352 493 0.49% 0.93% 2.64%
95 South America VE Venezuela 28 322 512 1.21% 0.93% 0.33%
96 North America CA Canada 38 207 636 0.88% 0.91% 0.70%
97 Asia UZ Uzbekistan 34 151 101 0.76% 0.87% 0.08%
98 Asia LB Lebanon 6 782 411 0.74% 0.85% 1.35%
99 Asia MY Malaysia 32 949 075 1.33% 0.84% 1.85%
100 South America CL Chile 19 347 024 2.07% 0.80% 1.31%
101 South America UY Uruguay 3 490 672 0.93% 0.78% 0.63%
102 Europe IT Italy 60 336 672 0.89% 0.78% 1.45%
103 Europe SK Slovakia 5 463 364 0.77% 0.76% 12.93%
104 Asia TR Turkey 85 615 390 0.83% 0.76% 3.33%
105 Europe BY Belarus 9 444 948 0.78% 0.73% 2.20%
106 Asia JO Jordan 10 345 598 0.95% 0.68% 2.80%
107 Europe CZ Czechia 10 736 943 0.68% 0.68% 12.69%
108 Asia TH Thailand 70 046 474 1.00% 0.66% 1.12%
109 Europe PT Portugal 10 154 853 0.60% 0.63% 1.86%
110 Australia/Oceania AU Australia 25 915 946 0.64% 0.62% 0.57%
111 Asia TW Taiwan 23 877 446 6.14% 0.60% 0.00%
112 Asia KW Kuwait 4 359 355 0.67% 0.58% 0.06%
113 North America NI Nicaragua 6 735 385 0.29% 0.58% 0.03%
114 Europe ES Spain 46 780 268 0.66% 0.55% 0.97%
115 Africa CF Central African R. 4 947 777 0.07% 0.53% 0.02%
116 Asia OM Oman 5 288 961 2.61% 0.53% 0.02%
117 Europe DE Germany 84 160 960 0.55% 0.52% 5.27%
118 Asia IL Israel 9 326 000 0.36% 0.48% 0.63%
119 Europe FI Finland 5 552 834 0.44% 0.44% 1.92%
120 Europe SE Sweden 10 187 866 0.51% 0.43% 1.12%
121 North America CU Cuba 11 316 884 0.87% 0.43% 0.40%
122 Europe SI Slovenia 2 079 340 0.50% 0.42% 15.60%
123 Asia AE Arab Emirates 10 058 437 0.27% 0.39% 0.08%
124 Africa TG Togo 8 551 196 0.82% 0.39% 0.01%
125 Europe FR France 65 476 789 0.42% 0.38% 2.36%
126 Asia SG Singapore 5 915 068 0.35% 0.36% 4.56%
127 Europe GB United Kingdom 68 387 784 0.36% 0.35% 6.32%
128 Europe NO Norway 5 480 875 0.23% 0.34% 3.47%
129 Asia LA Laos 7 423 978 0.25% 0.32% 1.59%
130 Australia/Oceania NZ New Zealand 5 002 100 0.22% 0.30% 0.39%
131 Europe BE Belgium 11 660 599 0.33% 0.29% 11.33%
132 Europe AT Austria 9 078 703 0.33% 0.29% 13.21%
133 North America DO Dominican R. 11 000 911 0.37% 0.25% 0.93%
134 Europe NL Netherlands 17 188 231 0.23% 0.22% 10.25%
135 Europe CH Switzerland 8 743 663 0.26% 0.22% 4.69%
136 Europe IE Ireland 5 015 353 0.26% 0.21% 8.63%
137 Europe DK Denmark 5 820 906 0.22% 0.18% 5.95%
138 Africa BW Botswana 2 418 332 0.91% 0.13% 1.48%
139 Asia QA Qatar 2 807 805 0.06% 0.03% 0.54%
140 Africa SS South Sudan 11 378 273 0.87% 0.00% 0.01%
141 Africa BI Burundi 12 387 708 0.03% 0.00% 0.01%
142 Asia HK Hong Kong 7 582 542 0.23% 0.00% 0.00%
143 Africa BJ Benin 12 568 962 0.32% 0.00% 0.00%
144 Africa LR Liberia 5 224 613 32.94% 0.00% 0.00%
145 Africa SL Sierra Leone 8 204 871 1.00% 0.00% 0.00%
146 Asia PS Palestine 5 267 950 0.00% 0.00% 0.03%
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 9 838 510 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 33 617 584 200 998 5.979
2 Europe BG Bulgaria 6 874 790 27 949 4.065
3 Europe BA Bosnia and Herzegovina 3 252 085 12 412 3.817
4 Europe MK North Macedonia 2 083 254 7 511 3.605
5 Europe HU Hungary 9 625 818 34 326 3.566
6 Europe CZ Czechia 10 736 943 32 694 3.045
7 Asia GE Georgia 3 978 387 11 857 2.980
8 Europe RO Romania 19 056 987 55 921 2.934
9 South America BR Brazil 214 685 129 613 417 2.857
10 Europe SI Slovenia 2 079 340 5 479 2.635
11 Europe HR Croatia 4 069 620 10 636 2.614
12 Europe SK Slovakia 5 463 364 14 244 2.607
13 South America AR Argentina 45 779 126 116 470 2.544
14 Asia AM Armenia 2 971 038 7 480 2.518
15 Europe LT Lithuania 2 668 788 6 667 2.498
16 South America CO Colombia 51 645 633 128 279 2.484
17 North America US USA 333 733 637 771 631 2.312
18 Europe BE Belgium 11 660 599 26 793 2.298
19 South America PY Paraguay 7 255 735 16 367 2.256
20 North America MX Mexico 130 837 902 293 224 2.241
21 Europe MD Moldova 4 020 764 9 000 2.238
22 Europe IT Italy 60 336 672 133 533 2.213
23 Europe PL Poland 37 788 261 82 625 2.187
24 Africa TN Tunisia 11 992 545 25 356 2.114
25 Europe GB United Kingdom 68 387 784 144 484 2.113
26 South America CL Chile 19 347 024 38 249 1.977
27 Europe UA Ukraine 43 363 807 84 446 1.947
28 Europe ES Spain 46 780 268 87 931 1.880
29 Europe RU Russia 146 022 541 271 501 1.859
30 South America EC Ecuador 18 019 649 33 128 1.838
31 Europe PT Portugal 10 154 853 18 397 1.812
32 Europe FR France 65 476 789 116 337 1.777
33 South America UY Uruguay 3 490 672 6 123 1.754
34 Europe GR Greece 10 351 371 17 791 1.719
35 North America PA Panama 4 410 239 7 359 1.669
36 South America BO Bolivia 11 896 887 19 111 1.606
37 Asia IR Iran 85 504 572 129 362 1.513
38 Africa ZA South Africa 60 360 124 89 777 1.487
39 Europe SE Sweden 10 187 866 15 142 1.486
40 North America CR Costa Rica 5 159 549 7 280 1.411
41 Africa NA Namibia 2 605 566 3 572 1.371
42 Europe RS Serbia 8 687 821 11 484 1.322
43 Europe AT Austria 9 078 703 11 862 1.307
44 Asia LB Lebanon 6 782 411 8 684 1.280
45 Europe CH Switzerland 8 743 663 11 023 1.261
46 Europe DE Germany 84 160 960 100 547 1.195
47 Europe IE Ireland 5 015 353 5 652 1.127
48 Europe NL Netherlands 17 188 231 19 203 1.117
49 Asia JO Jordan 10 345 598 11 465 1.108
50 Europe AL Albania 2 873 374 3 072 1.069
51 North America HN Honduras 10 126 026 10 402 1.027
52 South America PR Puerto Rico 3 193 694 3 266 1.023
53 Africa BW Botswana 2 418 332 2 416 0.999
54 Asia KZ Kazakhstan 19 092 532 17 765 0.930
55 Asia MY Malaysia 32 949 075 30 224 0.917
56 Asia TR Turkey 85 615 390 76 053 0.888
57 Asia IL Israel 9 326 000 8 189 0.878
58 North America GT Guatemala 18 381 240 15 896 0.865
59 North America JM Jamaica 2 979 354 2 370 0.795
60 Asia OM Oman 5 288 961 4 113 0.778
61 Africa LY Libya 7 002 659 5 435 0.776
62 North America CA Canada 38 207 636 29 585 0.774
63 Asia AZ Azerbaijan 10 267 726 7 754 0.755
64 North America CU Cuba 11 316 884 8 299 0.733
65 Asia LK Sri Lanka 21 539 591 14 259 0.662
66 North America SV El Salvador 6 532 256 3 766 0.577
67 Asia IQ Iraq 41 490 144 23 769 0.573
68 Asia MN Mongolia 3 352 493 1 913 0.571
69 Asia KW Kuwait 4 359 355 2 465 0.566
70 Europe BY Belarus 9 444 948 5 023 0.532
71 Asia ID Indonesia 277 591 391 143 807 0.518
72 Europe DK Denmark 5 820 906 2 850 0.490
73 Asia PH Philippines 111 631 712 48 016 0.430
74 Asia KG Kyrgyzstan 6 675 479 2 739 0.410
75 Africa MA Morocco 37 525 770 14 770 0.394
76 Asia NP Nepal 29 873 223 11 519 0.386
77 North America DO Dominican R. 11 000 911 4 197 0.382
78 Asia MM Myanmar 54 922 975 19 067 0.347
79 Asia IN India 1 399 087 302 467 704 0.334
80 Africa ZW Zimbabwe 15 167 085 4 704 0.310
81 Africa LS Lesotho 2 166 139 662 0.306
82 Asia TH Thailand 70 046 474 20 672 0.295
83 Asia VN Vietnam 98 570 511 24 580 0.249
84 Asia SA Saudi Arabia 35 575 968 8 830 0.248
85 Europe FI Finland 5 552 834 1 331 0.240
86 Asia QA Qatar 2 807 805 611 0.218
87 Asia AE Arab Emirates 10 058 437 2 145 0.213
88 Africa ZM Zambia 19 106 551 3 667 0.192
89 Africa EG Egypt 105 046 372 20 151 0.192
90 Europe NO Norway 5 480 875 1 050 0.192
91 Asia AF Afghanistan 40 159 632 7 307 0.182
92 South America VE Venezuela 28 322 512 5 111 0.180
93 Asia KH Cambodia 17 044 266 2 922 0.171
94 Africa MR Mauritania 4 821 224 825 0.171
95 Asia BD Bangladesh 166 997 084 27 973 0.168
96 Asia SY Syria 18 097 600 2 725 0.151
97 Asia JP Japan 125 931 373 18 353 0.146
98 Africa GM Gambia 2 511 954 342 0.136
99 Africa DZ Algeria 44 963 743 6 047 0.135
100 Asia PK Pakistan 226 918 495 28 690 0.126
101 Africa GA Gabon 2 299 483 276 0.120
102 Asia SG Singapore 5 915 068 692 0.117
103 Africa MW Malawi 19 823 915 2 305 0.116
104 Africa SN Senegal 17 363 327 1 885 0.109
105 Africa RW Rwanda 13 403 014 1 341 0.100
106 Africa KE Kenya 55 434 865 5 333 0.096
107 Africa SO Somalia 16 515 547 1 324 0.080
108 Australia/Oceania AU Australia 25 915 946 1 981 0.076
109 Africa GW Guinea-Bissau 2 033 318 148 0.073
110 Africa SD Sudan 45 286 992 3 114 0.069
111 Africa UG Uganda 47 767 518 3 251 0.068
112 Asia KR South Korea 51 331 289 3 472 0.068
113 Africa CM Cameroon 27 473 627 1 791 0.065
114 Asia YE Yemen 30 748 591 1 944 0.063
115 North America HT Haiti 11 597 988 723 0.062
116 Africa CG Congo 5 708 791 349 0.061
117 Africa MZ Mozambique 32 484 425 1 940 0.060
118 Australia/Oceania PG Papua New Guinea 9 185 155 545 0.059
119 Africa ET Ethiopia 118 961 845 6 718 0.057
120 Africa LR Liberia 5 224 613 287 0.055
121 Africa AO Angola 34 300 597 1 732 0.051
122 Asia UZ Uzbekistan 34 151 101 1 394 0.041
123 Africa GH Ghana 31 984 067 1 209 0.038
124 Asia TW Taiwan 23 877 446 848 0.035
125 Africa MG Madagascar 28 690 413 967 0.034
126 North America NI Nicaragua 6 735 385 212 0.032
127 Africa ML Mali 21 069 384 603 0.029
128 Africa GN Guinea 13 632 802 387 0.028
129 Africa TG Togo 8 551 196 243 0.028
130 Asia HK Hong Kong 7 582 542 213 0.028
131 Africa CI Ivory Coast 27 295 402 704 0.026
132 Africa CF Central African R. 4 947 777 101 0.020
133 Asia LA Laos 7 423 978 150 0.020
134 Africa ER Eritrea 3 615 427 58 0.016
135 Africa SL Sierra Leone 8 204 871 121 0.015
136 Africa NG Nigeria 213 313 133 2 976 0.014
137 Africa BJ Benin 12 568 962 161 0.013
138 Africa BF Burkina Faso 21 707 789 265 0.012
139 Africa TZ Tanzania 62 122 018 730 0.012
140 Africa CD DR Congo 93 381 747 1 104 0.012
141 Africa SS South Sudan 11 378 273 133 0.012
142 Africa TD Chad 17 087 325 175 0.010
143 Africa NE Niger 25 435 214 251 0.010
144 Australia/Oceania NZ New Zealand 5 002 100 42 0.008
145 Africa BI Burundi 12 387 708 14 0.001
146 Asia PS Palestine 5 267 950 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 9 838 510 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"