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": 2021-04-12 19:11
(For some countries, the data from the WHO and from "Our World in Data by Johns Hopkins University" and from "WorldoMeter" are completely different, such as: Israel.)
What can help, is at the bottom of this page. I recommend searching here "Global literature on coronavirus disease" or here "Google Scholar".

COVID-19, Selected Countries by WorldoMeter

Our World in Data, (2 days late data visualization) [CASES][DEATHS], [VACCINATION]
CDCountryNew CasesNew Deaths
AT Austria +1 943 (+2 252) +19 (+25)
CZ Czechia +976 (+2 201) +43 (+77)
DE Germany +7 696 (+16 738) +71 (+106)
HU Hungary +5 077 (+6 296) +291 (+206)
PL Poland +12 013 (+21 706) +61 (+244)
SK Slovakia, [gov], [okr]+106 (+589) +65 (+78)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 South America 436 767 137 2.42% 3.09% 3.36%
2 Europe 755 989 693 2.90% 3.00% 2.67%
3 North America 592 263 912 2.93% 1.43% 1.27%
4 Asia 4 660 767 516 0.26% 0.44% 0.66%
5 Africa 1 364 726 727 0.15% 0.10% 0.10%
6 Australia/Oceania 43 187 012 0.03% 0.07% 0.07%

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 436 767 137 2.50% 3.94% 3.09%
2 Africa 1 364 726 727 2.93% (3.30)% (0.10)%
3 North America 592 263 912 2.03% 2.68% 1.43%
4 Europe 755 989 693 2.23% 2.15% 3.00%
5 Asia 4 660 767 516 1.23% 1.19% 0.44%
6 Australia/Oceania 43 187 012 1.07% (0.97)% (0.07)%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 North America 592 263 912 814 356 1.375
2 South America 436 767 137 592 812 1.357
3 Europe 755 989 693 952 469 1.260
4 Asia 4 660 767 516 441 148 0.095
5 Africa 1 364 726 727 115 915 0.085
6 Australia/Oceania 43 187 012 1 288 0.030

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 South America UY Uruguay 3 483 093 3.80% 8.44% 13.44%
2 Asia TR Turkey 85 042 925 2.40% 4.69% 7.30%
3 Europe HU Hungary 9 641 234 4.61% 9.03% 6.29%
4 Europe PL Poland 37 814 322 3.86% 7.38% 6.26%
5 Europe MK North Macedonia 2 083 307 3.30% 5.91% 6.19%
6 Europe FR France 65 385 892 4.06% 6.32% 6.12%
7 Asia JO Jordan 10 281 719 3.97% 7.82% 5.51%
8 Europe HR Croatia 4 085 513 2.95% 4.16% 5.36%
9 Europe SE Sweden 10 148 191 5.29% 5.92% 5.13%
10 Europe SI Slovenia 2 079 160 6.29% 5.24% 5.02%
11 South America AR Argentina 45 517 627 2.25% 2.88% 4.88%
12 Europe RS Serbia 8 709 929 4.37% 6.18% 4.88%
13 Europe BG Bulgaria 6 907 614 2.79% 5.57% 4.71%
14 Europe NL Netherlands 17 164 371 4.35% 4.77% 4.71%
15 South America CL Chile 19 243 575 2.63% 4.09% 4.43%
16 Europe CZ Czechia 10 724 441 9.34% 7.05% 4.37%
17 Europe LT Lithuania 2 692 579 4.88% 3.24% 4.18%
18 Europe UA Ukraine 43 528 763 2.22% 3.76% 4.14%
19 Europe BA Bosnia and Herzegovina 3 264 896 2.55% 5.07% 4.09%
20 Asia LB Lebanon 6 801 609 5.15% 4.93% 4.07%
21 Asia QA Qatar 2 807 805 1.75% 2.96% 4.04%
22 Asia KW Kuwait 4 319 474 2.34% 3.69% 3.93%
23 South America BR Brazil 213 732 948 3.08% 3.99% 3.67%
24 Europe AT Austria 9 046 331 2.84% 3.94% 3.47%
25 South America PY Paraguay 7 200 447 1.97% 3.21% 3.40%
26 Europe GR Greece 10 383 345 1.65% 3.02% 3.29%
27 Asia AM Armenia 2 967 553 1.86% 3.35% 3.24%
28 South America PE Peru 33 327 621 1.97% 2.90% 3.21%
29 Europe BE Belgium 11 628 838 2.72% 4.06% 3.14%
30 Asia IR Iran 84 826 064 1.15% 1.61% 2.84%
31 South America CO Colombia 51 303 536 2.17% 1.80% 2.82%
32 Europe RO Romania 19 137 541 2.37% 3.24% 2.76%
33 Europe MD Moldova 4 026 657 2.88% 3.93% 2.73%
34 Europe IT Italy 60 392 563 3.21% 3.89% 2.71%
35 Europe CH Switzerland 8 703 776 2.74% 2.32% 2.68%
36 Asia MN Mongolia 3 319 145 0.42% 1.35% 2.41%
37 Asia AE Arab Emirates 9 983 033 3.01% 2.47% 2.36%
38 Asia AZ Azerbaijan 10 210 105 1.15% 1.79% 2.35%
39 South America PR Puerto Rico 3 193 694 1.63% 1.40% 2.33%
40 North America CA Canada 37 999 006 1.59% 1.61% 2.31%
41 Europe DE Germany 83 992 315 2.01% 2.13% 2.29%
42 Asia IQ Iraq 40 919 097 0.86% 1.71% 2.15%
43 Asia OM Oman 5 206 730 0.84% 1.86% 2.08%
44 Asia GE Georgia 3 983 201 2.49% 1.41% 2.02%
45 Europe SK Slovakia 5 461 701 4.40% 2.56% 1.81%
46 Europe NO Norway 5 454 156 1.14% 1.78% 1.74%
47 Africa TN Tunisia 11 914 543 1.36% 1.05% 1.70%
48 North America US USA 332 510 877 4.53% 2.05% 1.70%
49 Europe BY Belarus 9 446 902 1.88% 1.51% 1.52%
50 North America CR Costa Rica 5 130 219 1.42% 1.11% 1.37%
51 Africa LY Libya 6 943 676 1.12% 1.39% 1.34%
52 Africa BW Botswana 2 388 308 1.26% 1.44% 1.29%
53 Europe DK Denmark 5 808 065 2.17% 1.41% 1.27%
54 Asia PH Philippines 110 711 091 0.38% 0.91% 1.08%
55 South America EC Ecuador 17 850 462 0.81% 1.07% 1.07%
56 Asia IN India 1 390 530 992 0.26% 0.61% 1.06%
57 Europe AL Albania 2 875 349 2.80% 1.69% 1.04%
58 North America CU Cuba 11 321 232 0.68% 0.94% 1.04%
59 Europe ES Spain 46 768 878 3.37% 1.28% 1.03%
60 North America JM Jamaica 2 971 216 1.04% 1.75% 0.99%
61 South America BO Bolivia 11 796 372 1.14% 0.81% 0.98%
62 Europe IE Ireland 4 980 557 3.32% 1.21% 0.96%
63 Asia PS Palestine 5 192 907 0.05% 0.21% 0.90%
64 North America PA Panama 4 367 339 3.91% 1.06% 0.89%
65 Asia KZ Kazakhstan 18 950 814 0.68% 0.90% 0.84%
66 North America HN Honduras 10 026 526 0.81% 0.73% 0.74%
67 Europe RU Russia 145 983 181 1.37% 0.74% 0.71%
68 North America GT Guatemala 18 171 777 0.41% 0.46% 0.70%
69 Europe PT Portugal 10 173 535 4.74% 0.55% 0.65%
70 Europe FI Finland 5 547 419 0.92% 1.17% 0.65%
71 Africa GA Gabon 2 266 246 0.50% 0.76% 0.58%
72 South America VE Venezuela 28 373 143 0.24% 0.41% 0.56%
73 Africa NA Namibia 2 576 485 1.14% 0.74% 0.53%
74 North America DO Dominican R. 10 932 304 0.95% 0.44% 0.51%
75 Asia BD Bangladesh 165 962 319 0.12% 0.32% 0.50%
76 Asia MY Malaysia 32 687 354 0.85% 0.48% 0.50%
77 Europe GB United Kingdom 68 163 171 3.68% 0.73% 0.44%
78 North America MX Mexico 129 983 471 0.80% 0.38% 0.33%
79 Australia/Oceania PG Papua New Guinea 9 078 024 0.09% 0.29% 0.29%
80 Asia JP Japan 126 174 664 0.26% 0.19% 0.28%
81 Asia SA Saudi Arabia 35 233 544 0.11% 0.19% 0.28%
82 North America SV El Salvador 6 511 643 0.37% 0.22% 0.28%
83 Asia IL Israel 9 197 590 5.21% 0.79% 0.27%
84 Asia KG Kyrgyzstan 6 607 481 0.19% 0.20% 0.26%
85 Asia PK Pakistan 224 206 949 0.13% 0.21% 0.25%
86 Africa CM Cameroon 27 055 300 0.12% 0.27% 0.22%
87 Africa KE Kenya 54 685 584 0.10% 0.25% 0.21%
88 Asia ID Indonesia 275 767 009 0.35% 0.23% 0.21%
89 Africa ET Ethiopia 117 159 125 0.10% 0.20% 0.20%
90 Africa ZA South Africa 59 888 210 1.18% 0.21% 0.19%
91 Africa MA Morocco 37 249 722 0.28% 0.15% 0.18%
92 Asia KH Cambodia 16 898 196 0.02% 0.08% 0.18%
93 Africa TG Togo 8 428 407 0.10% 0.19% 0.17%
94 Africa MG Madagascar 28 239 647 0.04% 0.11% 0.15%
95 Asia KR South Korea 51 303 532 0.13% 0.12% 0.15%
96 Asia LK Sri Lanka 21 483 057 0.29% 0.15% 0.13%
97 Asia NP Nepal 29 542 041 0.11% 0.07% 0.13%
98 Africa CG Congo 5 622 812 0.07% 0.05% 0.12%
99 Africa RW Rwanda 13 199 759 0.13% 0.11% 0.12%
100 Africa ML Mali 20 699 744 0.03% 0.06% 0.11%
101 Asia TH Thailand 69 936 240 0.04% 0.04% 0.10%
102 Africa GM Gambia 2 468 937 0.07% 0.12% 0.10%
103 Africa ZM Zambia 18 780 343 0.38% 0.12% 0.09%
104 Africa EG Egypt 103 826 342 0.09% 0.08% 0.09%
105 Asia SY Syria 17 828 502 0.06% 0.09% 0.08%
106 Africa CF Central African R. 4 894 717 0.01% 0.04% 0.08%
107 Africa SO Somalia 16 234 617 0.05% 0.09% 0.07%
108 Asia UZ Uzbekistan 33 844 834 0.03% 0.05% 0.07%
109 Africa ER Eritrea 3 584 441 0.08% 0.05% 0.06%
110 Asia SG Singapore 5 886 067 0.04% 0.04% 0.05%
111 Africa GN Guinea 13 407 156 0.06% 0.10% 0.05%
112 Africa AO Angola 33 652 304 0.02% 0.03% 0.04%
113 Africa ZW Zimbabwe 15 030 471 0.17% 0.02% 0.04%
114 Africa DZ Algeria 44 463 324 0.06% 0.03% 0.04%
115 Africa SN Senegal 17 083 884 0.13% 0.07% 0.04%
116 Africa MZ Mozambique 31 929 609 0.16% 0.06% 0.03%
117 Africa BI Burundi 12 163 222 0.02% 0.02% 0.03%
118 Asia YE Yemen 30 333 035 0.01% 0.03% 0.03%
119 Africa MR Mauritania 4 743 824 0.18% 0.05% 0.03%
120 Africa CI Ivory Coast 26 881 892 0.09% 0.13% 0.03%
121 Africa GH Ghana 31 573 869 0.12% 0.06% 0.03%
122 Africa BJ Benin 12 367 868 0.04% 0.03% 0.03%
123 Australia/Oceania NZ New Zealand 5 002 100 0.01% 0.01% 0.03%
124 Asia AF Afghanistan 39 604 950 0.02% 0.01% 0.02%
125 Africa MW Malawi 19 510 895 0.14% 0.02% 0.02%
126 Africa GW Guinea-Bissau 2 003 881 0.06% 0.06% 0.02%
127 Africa BF Burkina Faso 21 344 682 0.04% 0.01% 0.01%
128 North America NI Nicaragua 6 685 654 0.01% 0.01% 0.01%
129 Africa SS South Sudan 11 295 469 0.06% 0.04% 0.01%
130 North America HT Haiti 11 510 273 0.03% 0.01% 0.01%
131 Africa UG Uganda 46 851 395 0.03% 0.01% 0.01%
132 Australia/Oceania AU Australia 25 729 274 0.01% 0.00% 0.01%
133 Africa NG Nigeria 210 078 731 0.04% 0.01% 0.01%
134 Africa CD DR Congo 91 655 486 0.02% 0.01% 0.01%
135 Africa TD Chad 16 788 636 0.02% 0.01% 0.00%
136 Africa SL Sierra Leone 8 102 294 0.02% 0.00% 0.00%
137 Asia HK Hong Kong 7 544 203 0.00% 0.00% 0.00%
138 Asia MM Myanmar 54 693 139 0.07% 0.00% 0.00%
139 Asia VN Vietnam 98 018 310 0.00% 0.00% 0.00%
140 Africa LR Liberia 5 149 383 0.01% 0.00% 0.00%
141 Africa NE Niger 24 878 798 0.01% 0.00% 0.00%
142 Africa LS Lesotho 2 155 435 0.40% 0.03% 0.00%
143 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
144 Africa TZ Tanzania 61 043 872 0.00% 0.00% 0.00%
145 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
146 Asia TJ Tajikistan 9 702 976 0.00% 0.00% 0.00%
147 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
148 Asia TW Taiwan 23 850 320 0.00% 0.00% 0.00%
149 Africa SD Sudan 44 639 104 0.02% 0.01% 0.00%
150 Asia LA Laos 7 357 317 0.00% 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 30 333 035 16.32% (15.54)% (0.03)%
2 North America MX Mexico 129 983 471 8.62% 10.25% 0.38%
3 Africa SD Sudan 44 639 104 5.79% (9.51)% (0.01)%
4 Asia SY Syria 17 828 502 7.87% (8.15)% (0.09)%
5 Asia AF Afghanistan 39 604 950 6.18% (7.64)% (0.01)%
6 Africa SO Somalia 16 234 617 6.67% (6.79)% (0.09)%
7 Africa ZA South Africa 59 888 210 4.07% 6.50% 0.21%
8 Africa EG Egypt 103 826 342 6.38% (6.27)% (0.08)%
9 Africa ZW Zimbabwe 15 030 471 4.69% (6.22)% (0.02)%
10 Europe SK Slovakia 5 461 701 3.80% 5.06% 2.56%
11 Europe BA Bosnia and Herzegovina 3 264 896 5.05% 4.94% 5.07%
12 Africa CF Central African R. 4 894 717 3.41% (4.44)% (0.04)%
13 Europe RU Russia 145 983 181 2.65% 4.17% 0.74%
14 Africa TN Tunisia 11 914 543 3.47% 4.07% 1.05%
15 Africa GW Guinea-Bissau 2 003 881 1.80% (3.90)% (0.06)%
16 Africa MW Malawi 19 510 895 3.41% (3.76)% (0.02)%
17 South America BR Brazil 213 732 948 2.65% 3.60% 3.99%
18 Africa MG Madagascar 28 239 647 2.96% 3.47% 0.11%
19 Europe BG Bulgaria 6 907 614 4.58% 3.41% 5.57%
20 Africa SN Senegal 17 083 884 3.22% (3.36)% (0.07)%
21 Europe MK North Macedonia 2 083 307 3.18% 3.36% 5.91%
22 Africa LS Lesotho 2 155 435 3.16% (3.23)% (0.03)%
23 North America SV El Salvador 6 511 643 3.47% 3.06% 0.22%
24 Europe HU Hungary 9 641 234 3.81% 3.01% 9.03%
25 Africa NE Niger 24 878 798 3.44% (2.99)% (0.00)%
26 Africa TD Chad 16 788 636 2.26% (2.96)% (0.01)%
27 Africa DZ Algeria 44 463 324 1.82% (2.77)% (0.03)%
28 South America CO Colombia 51 303 536 2.48% 2.75% 1.80%
29 North America HN Honduras 10 026 526 2.27% 2.73% 0.73%
30 Europe MD Moldova 4 026 657 2.38% 2.69% 3.93%
31 South America PE Peru 33 327 621 2.98% 2.69% 2.90%
32 North America NI Nicaragua 6 685 654 2.60% (2.67)% (0.01)%
33 Asia ID Indonesia 275 767 009 2.48% 2.61% 0.23%
34 Europe GR Greece 10 383 345 3.34% 2.61% 3.02%
35 Europe UA Ukraine 43 528 763 2.35% 2.53% 3.76%
36 South America PY Paraguay 7 200 447 2.14% 2.48% 3.21%
37 North America GT Guatemala 18 171 777 3.71% 2.47% 0.46%
38 South America EC Ecuador 17 850 462 2.47% 2.47% 1.07%
39 Europe RO Romania 19 137 541 2.54% 2.45% 3.24%
40 South America BO Bolivia 11 796 372 2.65% 2.42% 0.81%
41 Africa ML Mali 20 699 744 3.99% (2.41)% (0.06)%
42 Asia AM Armenia 2 967 553 2.28% 2.19% 3.35%
43 Africa NA Namibia 2 576 485 1.37% 2.12% 0.74%
44 Africa AO Angola 33 652 304 2.64% (2.12)% (0.03)%
45 Asia GE Georgia 3 983 201 1.72% 2.10% 1.41%
46 Africa BW Botswana 2 388 308 1.94% 2.09% 1.44%
47 Africa GM Gambia 2 468 937 2.66% 2.07% 0.12%
48 Europe CZ Czechia 10 724 441 1.81% 1.97% 7.05%
49 Europe IT Italy 60 392 563 2.57% 1.97% 3.89%
50 Europe HR Croatia 4 085 513 2.84% 1.95% 4.16%
51 Europe AL Albania 2 875 349 1.57% 1.94% 1.69%
52 Asia PK Pakistan 224 206 949 2.43% 1.94% 0.21%
53 Asia JP Japan 126 174 664 2.10% 1.88% 0.19%
54 Africa LY Libya 6 943 676 2.00% 1.87% 1.39%
55 Asia AZ Azerbaijan 10 210 105 1.56% 1.84% 1.79%
56 Europe PT Portugal 10 173 535 2.27% 1.75% 0.55%
57 Asia KG Kyrgyzstan 6 607 481 1.55% 1.70% 0.20%
58 Europe PL Poland 37 814 322 2.57% 1.67% 7.38%
59 Europe IE Ireland 4 980 557 1.62% 1.67% 1.21%
60 Europe LT Lithuania 2 692 579 1.84% 1.67% 3.24%
61 South America AR Argentina 45 517 627 1.82% 1.62% 2.88%
62 Africa CD DR Congo 91 655 486 2.63% 1.61% 0.01%
63 Asia KH Cambodia 16 898 196 1.25% 1.61% 0.08%
64 South America CL Chile 19 243 575 1.82% 1.60% 4.09%
65 Asia LB Lebanon 6 801 609 1.60% 1.56% 4.93%
66 Africa GH Ghana 31 573 869 1.11% 1.55% 0.06%
67 North America US USA 332 510 877 1.62% 1.51% 2.05%
68 Asia SA Saudi Arabia 35 233 544 2.11% 1.49% 0.19%
69 North America PA Panama 4 367 339 1.56% 1.47% 1.06%
70 South America VE Venezuela 28 373 143 1.35% 1.47% 0.41%
71 Africa MA Morocco 37 249 722 1.90% 1.46% 0.15%
72 Africa CM Cameroon 27 055 300 1.40% 1.44% 0.27%
73 North America DO Dominican R. 10 932 304 0.96% 1.44% 0.44%
74 Africa KE Kenya 54 685 584 1.53% 1.44% 0.25%
75 Asia BD Bangladesh 165 962 319 1.69% 1.39% 0.32%
76 South America UY Uruguay 3 483 093 1.23% 1.37% 8.44%
77 Africa RW Rwanda 13 199 759 1.58% 1.37% 0.11%
78 Africa ET Ethiopia 117 159 125 1.36% 1.35% 0.20%
79 Asia IR Iran 84 826 064 1.39% 1.33% 1.61%
80 North America CR Costa Rica 5 130 219 1.50% 1.32% 1.11%
81 Africa BF Burkina Faso 21 344 682 0.85% 1.29% 0.01%
82 Europe DE Germany 83 992 315 3.29% 1.27% 2.13%
83 Asia TW Taiwan 23 850 320 1.20% 1.23% 0.00%
84 North America JM Jamaica 2 971 216 1.36% 1.21% 1.75%
85 Africa MR Mauritania 4 743 824 2.69% 1.21% 0.05%
86 Europe GB United Kingdom 68 163 171 2.40% 1.20% 0.73%
87 Asia NP Nepal 29 542 041 3.58% 1.20% 0.07%
88 Africa CG Congo 5 622 812 0.97% 1.20% 0.05%
89 Asia JO Jordan 10 281 719 1.13% 1.19% 7.82%
90 Africa MZ Mozambique 31 929 609 1.25% 1.09% 0.06%
91 Asia PH Philippines 110 711 091 1.74% 1.09% 0.91%
92 Europe ES Spain 46 768 878 1.62% 1.05% 1.28%
93 Asia MM Myanmar 54 693 139 2.12% 1.04% 0.00%
94 Africa ZM Zambia 18 780 343 1.21% 1.03% 0.12%
95 South America PR Puerto Rico 3 193 694 1.66% 1.01% 1.40%
96 Africa NG Nigeria 210 078 731 0.92% 0.99% 0.01%
97 Africa BJ Benin 12 367 868 1.15% 0.97% 0.03%
98 Asia KZ Kazakhstan 18 950 814 1.00% 0.91% 0.90%
99 Asia IL Israel 9 197 590 0.67% 0.89% 0.79%
100 Europe FR France 65 385 892 1.63% 0.89% 6.32%
101 Europe AT Austria 9 046 331 1.97% 0.88% 3.94%
102 Australia/Oceania PG Papua New Guinea 9 078 024 0.96% 0.87% 0.29%
103 Asia LK Sri Lanka 21 483 057 0.67% 0.83% 0.15%
104 Europe BE Belgium 11 628 838 1.72% 0.81% 4.06%
105 Asia IN India 1 390 530 992 0.91% 0.81% 0.61%
106 Africa GN Guinea 13 407 156 0.77% 0.81% 0.10%
107 Europe BY Belarus 9 446 902 0.60% 0.80% 1.51%
108 North America HT Haiti 11 510 273 0.56% 0.79% 0.01%
109 Asia OM Oman 5 206 730 0.76% 0.79% 1.86%
110 Europe RS Serbia 8 709 929 0.86% 0.77% 6.18%
111 Asia KR South Korea 51 303 532 1.74% 0.75% 0.12%
112 Africa GA Gabon 2 266 246 0.60% 0.74% 0.76%
113 North America CA Canada 37 999 006 1.67% 0.74% 1.61%
114 Africa ER Eritrea 3 584 441 0.37% 0.73% 0.05%
115 Europe SI Slovenia 2 079 160 1.61% 0.70% 5.24%
116 Asia IQ Iraq 40 919 097 0.69% 0.66% 1.71%
117 Asia KW Kuwait 4 319 474 0.53% 0.64% 3.69%
118 Asia TR Turkey 85 042 925 0.94% 0.63% 4.69%
119 Africa TG Togo 8 428 407 0.61% 0.61% 0.19%
120 Africa UG Uganda 46 851 395 0.62% 0.59% 0.01%
121 Africa SS South Sudan 11 295 469 0.73% 0.54% 0.04%
122 Europe CH Switzerland 8 703 776 1.54% 0.52% 2.32%
123 Africa BI Burundi 12 163 222 0.23% 0.48% 0.02%
124 Africa CI Ivory Coast 26 881 892 0.56% 0.46% 0.13%
125 Europe FI Finland 5 547 419 0.80% 0.46% 1.17%
126 Europe NL Netherlands 17 164 371 0.90% 0.39% 4.77%
127 Asia QA Qatar 2 807 805 0.21% 0.39% 2.96%
128 North America CU Cuba 11 321 232 0.46% 0.38% 0.94%
129 Asia TH Thailand 69 936 240 0.15% 0.36% 0.04%
130 Asia UZ Uzbekistan 33 844 834 0.22% 0.33% 0.05%
131 Asia MY Malaysia 32 687 354 0.33% 0.30% 0.48%
132 Asia MN Mongolia 3 319 145 0.25% 0.27% 1.35%
133 Europe DK Denmark 5 808 065 1.06% 0.26% 1.41%
134 Europe SE Sweden 10 148 191 1.04% 0.26% 5.92%
135 Asia AE Arab Emirates 9 983 033 0.31% 0.24% 2.47%
136 Asia SG Singapore 5 886 067 0.04% 0.21% 0.04%
137 Europe NO Norway 5 454 156 0.51% 0.21% 1.78%
138 Australia/Oceania NZ New Zealand 5 002 100 0.23% 0.00% 0.01%
139 Australia/Oceania AU Australia 25 729 274 0.07% 0.00% 0.00%
140 Africa SL Sierra Leone 8 102 294 0.26% 0.00% 0.00%
141 Africa LR Liberia 5 149 383 0.50% 0.00% 0.00%
142 Asia VN Vietnam 98 018 310 0.00% 0.00% 0.00%
143 Asia LA Laos 7 357 317 0.00% 0.00% 0.00%
144 Asia PS Palestine 5 192 907 0.00% 0.00% 0.21%
145 Asia HK Hong Kong 7 544 203 0.00% 0.00% 0.00%
146 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
147 Africa TZ Tanzania 61 043 872 0.00% 0.00% 0.00%
148 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
149 Asia TJ Tajikistan 9 702 976 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 Europe CZ Czechia 10 724 441 27 851 2.597
2 Europe HU Hungary 9 641 234 23 708 2.459
3 Europe BA Bosnia and Herzegovina 3 264 896 7 436 2.278
4 Europe SI Slovenia 2 079 160 4 415 2.123
5 Europe BG Bulgaria 6 907 614 14 418 2.087
6 Europe MK North Macedonia 2 083 307 4 228 2.030
7 Europe BE Belgium 11 628 838 23 473 2.018
8 Europe SK Slovakia 5 461 701 10 630 1.946
9 Europe IT Italy 60 392 563 114 281 1.892
10 Europe GB United Kingdom 68 163 171 127 093 1.865
11 North America US USA 332 510 877 554 849 1.669
12 Europe PT Portugal 10 173 535 16 912 1.662
13 South America BR Brazil 213 732 948 350 542 1.640
14 South America PE Peru 33 327 621 54 519 1.636
15 Europe ES Spain 46 768 878 76 179 1.629
16 North America MX Mexico 129 983 471 207 146 1.594
17 Europe HR Croatia 4 085 513 6 333 1.550
18 Europe PL Poland 37 814 322 58 482 1.547
19 Europe FR France 65 385 892 98 132 1.501
20 North America PA Panama 4 367 339 6 160 1.411
21 Europe LT Lithuania 2 692 579 3 696 1.373
22 Europe SE Sweden 10 148 191 13 621 1.342
23 Europe MD Moldova 4 026 657 5 390 1.339
24 Europe RO Romania 19 137 541 25 119 1.313
25 South America CO Colombia 51 303 536 65 564 1.278
26 South America CL Chile 19 243 575 24 346 1.265
27 Asia AM Armenia 2 967 553 3 753 1.265
28 South America AR Argentina 45 517 627 57 482 1.263
29 Europe CH Switzerland 8 703 776 9 754 1.121
30 South America BO Bolivia 11 796 372 12 437 1.054
31 Europe AT Austria 9 046 331 9 412 1.040
32 Asia LB Lebanon 6 801 609 6 672 0.981
33 Europe NL Netherlands 17 164 371 16 774 0.977
34 Asia GE Georgia 3 983 201 3 883 0.975
35 South America EC Ecuador 17 850 462 17 293 0.969
36 Europe IE Ireland 4 980 557 4 785 0.961
37 Europe DE Germany 83 992 315 78 424 0.934
38 Africa ZA South Africa 59 888 210 53 322 0.890
39 Europe GR Greece 10 383 345 8 909 0.858
40 Europe UA Ukraine 43 528 763 37 301 0.857
41 Europe AL Albania 2 875 349 2 314 0.805
42 Africa TN Tunisia 11 914 543 9 293 0.780
43 Asia IR Iran 84 826 064 64 506 0.760
44 Asia JO Jordan 10 281 719 7 790 0.758
45 Europe RU Russia 145 983 181 103 263 0.707
46 Asia IL Israel 9 197 590 6 299 0.685
47 South America PR Puerto Rico 3 193 694 2 152 0.674
48 South America PY Paraguay 7 200 447 4 776 0.663
49 Europe RS Serbia 8 709 929 5 738 0.659
50 North America CA Canada 37 999 006 23 279 0.613
51 North America CR Costa Rica 5 130 219 3 018 0.588
52 North America HN Honduras 10 026 526 4 800 0.479
53 Europe DK Denmark 5 808 065 2 441 0.420
54 South America UY Uruguay 3 483 093 1 411 0.405
55 Africa LY Libya 6 943 676 2 812 0.405
56 Asia TR Turkey 85 042 925 33 939 0.399
57 North America GT Guatemala 18 171 777 7 005 0.386
58 Asia AZ Azerbaijan 10 210 105 3 908 0.383
59 Asia IQ Iraq 40 919 097 14 713 0.360
60 Asia OM Oman 5 206 730 1 760 0.338
61 Asia KW Kuwait 4 319 474 1 407 0.326
62 North America SV El Salvador 6 511 643 2 051 0.315
63 North America DO Dominican R. 10 932 304 3 389 0.310
64 Africa BW Botswana 2 388 308 636 0.266
65 Europe BY Belarus 9 446 902 2 353 0.249
66 Africa MA Morocco 37 249 722 8 900 0.239
67 Asia KG Kyrgyzstan 6 607 481 1 525 0.231
68 North America JM Jamaica 2 971 216 673 0.227
69 Africa NA Namibia 2 576 485 569 0.221
70 Asia KZ Kazakhstan 18 950 814 3 812 0.201
71 Asia SA Saudi Arabia 35 233 544 6 758 0.192
72 Europe FI Finland 5 547 419 868 0.157
73 Asia ID Indonesia 275 767 009 42 569 0.154
74 Asia AE Arab Emirates 9 983 033 1 531 0.153
75 Africa LS Lesotho 2 155 435 315 0.146
76 Asia PH Philippines 110 711 091 14 948 0.135
77 Europe NO Norway 5 454 156 687 0.126
78 Asia IN India 1 390 530 992 169 739 0.122
79 Africa EG Egypt 103 826 342 12 445 0.120
80 Asia QA Qatar 2 807 805 333 0.119
81 Asia NP Nepal 29 542 041 3 052 0.103
82 Africa ZW Zimbabwe 15 030 471 1 538 0.102
83 Africa MR Mauritania 4 743 824 450 0.095
84 Asia SY Syria 17 828 502 1 378 0.077
85 Asia JP Japan 126 174 664 9 400 0.074
86 Africa DZ Algeria 44 463 324 3 130 0.070
87 Asia PK Pakistan 224 206 949 15 387 0.069
88 Africa GM Gambia 2 468 937 168 0.068
89 Africa ZM Zambia 18 780 343 1 227 0.065
90 Asia AF Afghanistan 39 604 950 2 521 0.064
91 Africa SN Senegal 17 083 884 1 078 0.063
92 South America VE Venezuela 28 373 143 1 758 0.062
93 Asia BD Bangladesh 165 962 319 9 744 0.059
94 Asia MM Myanmar 54 693 139 3 206 0.059
95 Africa MW Malawi 19 510 895 1 128 0.058
96 Africa GA Gabon 2 266 246 127 0.056
97 Africa SD Sudan 44 639 104 2 063 0.046
98 Africa KE Kenya 54 685 584 2 350 0.043
99 North America CU Cuba 11 321 232 461 0.041
100 Asia MY Malaysia 32 687 354 1 325 0.041
101 Africa SO Somalia 16 234 617 605 0.037
102 Australia/Oceania AU Australia 25 729 274 909 0.035
103 Asia YE Yemen 30 333 035 1 051 0.035
104 Asia KR South Korea 51 303 532 1 770 0.035
105 Africa GW Guinea-Bissau 2 003 881 66 0.033
106 Africa CM Cameroon 27 055 300 851 0.032
107 Asia LK Sri Lanka 21 483 057 595 0.028
108 Africa ET Ethiopia 117 159 125 3 174 0.027
109 North America NI Nicaragua 6 685 654 179 0.027
110 Africa MZ Mozambique 31 929 609 791 0.025
111 Africa CG Congo 5 622 812 137 0.024
112 Africa GH Ghana 31 573 869 754 0.024
113 Africa RW Rwanda 13 199 759 315 0.024
114 North America HT Haiti 11 510 273 252 0.022
115 Africa ML Mali 20 699 744 408 0.020
116 Asia UZ Uzbekistan 33 844 834 634 0.019
117 Africa MG Madagascar 28 239 647 499 0.018
118 Africa LR Liberia 5 149 383 85 0.017
119 Africa AO Angola 33 652 304 553 0.016
120 Africa CF Central African R. 4 894 717 74 0.015
121 Africa TG Togo 8 428 407 116 0.014
122 Africa GN Guinea 13 407 156 135 0.010
123 Africa SS South Sudan 11 295 469 114 0.010
124 Africa TD Chad 16 788 636 167 0.010
125 Africa NG Nigeria 210 078 731 2 060 0.010
126 Africa SL Sierra Leone 8 102 294 79 0.010
127 Africa CI Ivory Coast 26 881 892 264 0.010
128 Asia TJ Tajikistan 9 702 976 90 0.009
129 Africa CD DR Congo 91 655 486 745 0.008
130 Africa NE Niger 24 878 798 189 0.008
131 Australia/Oceania PG Papua New Guinea 9 078 024 69 0.008
132 Africa BJ Benin 12 367 868 93 0.007
133 Africa UG Uganda 46 851 395 337 0.007
134 Africa BF Burkina Faso 21 344 682 152 0.007
135 Asia MN Mongolia 3 319 145 23 0.007
136 Australia/Oceania NZ New Zealand 5 002 100 26 0.005
137 Asia SG Singapore 5 886 067 30 0.005
138 Asia PS Palestine 5 192 907 23 0.004
139 Africa ER Eritrea 3 584 441 10 0.003
140 Asia KH Cambodia 16 898 196 30 0.002
141 Asia TH Thailand 69 936 240 97 0.001
142 Africa BI Burundi 12 163 222 6 0.001
143 Asia TW Taiwan 23 850 320 11 0.001
144 Asia VN Vietnam 98 018 310 35 0.000
145 Africa TZ Tanzania 61 043 872 21 0.000
146 Asia CN China 1 439 323 776 0 0.000
147 Asia KP North Korea 25 660 000 0 0.000
148 Europe TM Turkmenistan 6 118 000 0 0.000
149 Asia LA Laos 7 357 317 0 0.000
150 Asia HK Hong Kong 7 544 203 0 0.000

Elhalálozási adatok hozzávetőleges értékei 2018: Abortusz: 56 millió, Rákbetegség: 9,6 millió.

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

* ÚV lámpa (neon) használata a helységekben.
* Azelastine: [1], [2] , [*] 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)
* 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]

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

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"