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": 2021-06-23 17:49
(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 +117 (+58) +2 (+4)
CZ Czechia +131 (+121) +0 (+1)
DE Germany +264 (+688) +19 (+75)
HU Hungary +91 (+54) +8 (+4)
PL Poland +165 (+185) +35 (+29)
SK Slovakia, [gov], [okr]+35 (+59) +0 (+6)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 South America 437 465 879 3.27% 3.70% 3.67%
2 Europe 756 077 780 1.89% 0.67% 0.55%
3 North America 593 171 428 1.17% 0.52% 0.34%
4 Asia 4 667 508 747 0.64% 0.46% 0.30%
5 Africa 1 371 058 643 0.10% 0.14% 0.19%
6 Australia/Oceania 43 285 997 0.05% 0.04% 0.05%

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 North America 593 171 428 2.17% 4.01% 0.52%
2 South America 437 465 879 3.22% 3.48% 3.70%
3 Africa 1 371 058 643 2.74% 3.00% 0.14%
4 Europe 756 077 780 1.95% 2.90% 0.67%
5 Asia 4 667 508 747 1.28% 2.66% 0.46%
6 Australia/Oceania 43 285 997 0.93% (0.73)% (0.04)%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 437 465 879 975 220 2.229
2 North America 593 171 428 890 830 1.502
3 Europe 756 077 780 1 094 123 1.447
4 Asia 4 667 508 747 764 990 0.164
5 Africa 1 371 058 643 138 489 0.101
6 Australia/Oceania 43 285 997 1 406 0.033

COVID-19, New Cases in Countries

Filtered where Population more then 2 million, [All Countries] | Compare with [CASES]
N.RegionCDCountryPopulationLast 120 daysLast 30 daysLast 7 days
1 Asia MN Mongolia 3 329 539 2.80% 5.20% 7.74%
2 South America UY Uruguay 3 485 455 8.68% 10.72% 7.20%
3 South America CO Colombia 51 410 163 3.35% 5.72% 5.61%
4 Africa NA Namibia 2 585 549 1.43% 3.37% 5.11%
5 South America AR Argentina 45 599 133 4.85% 6.71% 5.05%
6 South America BR Brazil 214 029 732 3.65% 3.59% 4.15%
7 Asia KW Kuwait 4 331 905 3.60% 3.86% 3.95%
8 Asia OM Oman 5 232 360 2.11% 3.04% 3.77%
9 South America PY Paraguay 7 217 680 3.53% 4.23% 3.17%
10 South America CL Chile 19 275 819 3.72% 3.95% 2.95%
11 North America CR Costa Rica 5 139 361 2.91% 3.93% 2.85%
12 Africa BW Botswana 2 397 666 1.64% 1.95% 2.70%
13 North America PA Panama 4 380 710 1.32% 1.88% 2.36%
14 Africa ZA South Africa 60 035 300 0.55% 1.33% 2.09%
15 Asia AE Arab Emirates 10 006 535 2.41% 2.31% 2.07%
16 Africa TN Tunisia 11 938 855 1.31% 1.67% 1.88%
17 Asia MY Malaysia 32 768 929 1.27% 2.31% 1.77%
18 Europe GB United Kingdom 68 233 180 0.76% 1.08% 1.64%
19 South America BO Bolivia 11 827 701 1.51% 2.46% 1.63%
20 Asia GE Georgia 3 981 700 2.28% 2.21% 1.61%
21 Africa ZM Zambia 18 882 018 0.30% 0.83% 1.51%
22 North America CU Cuba 11 319 877 1.09% 1.28% 1.32%
23 South America PE Peru 33 417 999 2.23% 1.30% 1.31%
24 Europe PT Portugal 10 167 712 0.67% 0.84% 1.27%
25 Asia IQ Iraq 41 097 086 1.51% 1.22% 1.23%
26 Europe RU Russia 145 995 449 0.80% 0.94% 1.19%
27 Asia IR Iran 85 037 547 1.79% 1.29% 1.14%
28 Asia KG Kyrgyzstan 6 628 675 0.46% 0.82% 1.13%
29 North America DO Dominican R. 10 953 688 0.75% 1.23% 1.11%
30 Asia LK Sri Lanka 21 500 678 0.75% 1.39% 0.88%
31 Europe BY Belarus 9 446 293 1.40% 1.08% 0.84%
32 North America HN Honduras 10 057 539 0.87% 0.83% 0.81%
33 North America GT Guatemala 18 237 064 0.61% 0.75% 0.76%
34 South America EC Ecuador 17 903 196 0.96% 0.63% 0.73%
35 Asia TR Turkey 85 221 356 3.20% 0.89% 0.69%
36 Europe IE Ireland 4 991 403 1.07% 0.83% 0.64%
37 Asia KZ Kazakhstan 18 994 986 1.10% 0.81% 0.62%
38 Asia NP Nepal 29 645 266 1.18% 1.40% 0.57%
39 Asia QA Qatar 2 807 805 2.14% 0.79% 0.56%
40 Asia PH Philippines 110 998 038 0.72% 0.66% 0.56%
41 Asia AF Afghanistan 39 777 838 0.13% 0.40% 0.53%
42 Asia ID Indonesia 276 335 647 0.26% 0.35% 0.51%
43 Europe NL Netherlands 17 171 808 3.61% 1.26% 0.51%
44 Asia TH Thailand 69 970 599 0.28% 0.53% 0.49%
45 South America VE Venezuela 28 357 362 0.44% 0.55% 0.47%
46 Europe DK Denmark 5 812 068 1.46% 1.27% 0.45%
47 Europe GR Greece 10 373 379 2.30% 1.12% 0.44%
48 Asia JO Jordan 10 301 629 3.68% 0.64% 0.43%
49 Asia IN India 1 393 197 894 1.36% 0.93% 0.42%
50 Asia KH Cambodia 16 943 724 0.25% 0.41% 0.39%
51 Europe NO Norway 5 462 484 1.12% 0.64% 0.39%
52 Europe FR France 65 414 223 3.27% 0.89% 0.37%
53 Europe SI Slovenia 2 079 217 3.47% 1.03% 0.37%
54 North America SV El Salvador 6 518 068 0.27% 0.27% 0.35%
55 Asia SA Saudi Arabia 35 340 273 0.28% 0.39% 0.35%
56 Europe ES Spain 46 772 428 1.40% 0.83% 0.35%
57 Africa LY Libya 6 962 061 0.87% 0.44% 0.35%
58 North America MX Mexico 130 249 787 0.34% 0.26% 0.32%
59 Africa UG Uganda 47 136 940 0.07% 0.24% 0.28%
60 Europe BE Belgium 11 638 738 2.75% 1.01% 0.27%
61 Asia AM Armenia 2 968 639 1.81% 0.32% 0.26%
62 Africa RW Rwanda 13 263 111 0.10% 0.13% 0.26%
63 Asia BD Bangladesh 166 284 843 0.19% 0.17% 0.26%
64 Europe LT Lithuania 2 685 164 3.06% 1.09% 0.25%
65 North America CA Canada 38 064 034 1.48% 0.55% 0.25%
66 Africa ZW Zimbabwe 15 073 052 0.04% 0.10% 0.22%
67 Asia LB Lebanon 6 795 625 2.75% 0.30% 0.21%
68 Africa ER Eritrea 3 594 099 0.08% 0.17% 0.21%
69 North America US USA 332 891 997 1.58% 0.49% 0.20%
70 Europe IT Italy 60 375 142 2.38% 0.41% 0.19%
71 South America PR Puerto Rico 3 193 694 1.28% 0.30% 0.19%
72 Europe UA Ukraine 43 477 348 2.11% 0.43% 0.18%
73 North America JM Jamaica 2 973 752 0.94% 0.23% 0.18%
74 Africa LR Liberia 5 172 831 0.02% 0.07% 0.17%
75 Europe HR Croatia 4 080 560 2.91% 0.51% 0.17%
76 Europe AT Austria 9 056 421 2.24% 0.37% 0.16%
77 Africa LS Lesotho 2 158 771 0.03% 0.06% 0.16%
78 Europe FI Finland 5 549 107 0.73% 0.21% 0.16%
79 Africa CG Congo 5 649 611 0.07% 0.07% 0.15%
80 Europe RS Serbia 8 703 038 3.17% 0.27% 0.14%
81 Europe MD Moldova 4 024 820 1.96% 0.15% 0.13%
82 Asia JP Japan 126 098 833 0.29% 0.22% 0.12%
83 Asia UZ Uzbekistan 33 940 294 0.08% 0.10% 0.12%
84 Africa MA Morocco 37 335 763 0.12% 0.11% 0.12%
85 Europe BG Bulgaria 6 897 383 2.65% 0.26% 0.12%
86 Africa KE Kenya 54 919 126 0.14% 0.08% 0.11%
87 Europe CZ Czechia 10 728 338 4.64% 0.30% 0.11%
88 Europe DE Germany 84 044 880 1.58% 0.34% 0.10%
89 Asia KR South Korea 51 312 183 0.13% 0.12% 0.10%
90 Europe BA Bosnia and Herzegovina 3 260 903 2.34% 0.19% 0.09%
91 Africa SL Sierra Leone 8 134 266 0.01% 0.04% 0.09%
92 Europe HU Hungary 9 636 429 4.16% 0.25% 0.09%
93 Asia MM Myanmar 54 764 776 0.01% 0.04% 0.09%
94 Europe CH Switzerland 8 716 208 1.71% 0.55% 0.09%
95 Europe SE Sweden 10 160 557 4.39% 0.89% 0.09%
96 Africa DZ Algeria 44 619 299 0.05% 0.08% 0.08%
97 Africa MR Mauritania 4 767 949 0.07% 0.10% 0.08%
98 Asia IL Israel 9 326 000 0.86% 0.03% 0.08%
99 Europe SK Slovakia 5 462 219 1.77% 0.18% 0.07%
100 Asia PS Palestine 5 216 297 0.00% 0.02% 0.07%
101 Asia TW Taiwan 23 858 775 0.06% 0.16% 0.06%
102 North America NI Nicaragua 6 701 154 0.02% 0.04% 0.06%
103 Africa MZ Mozambique 32 102 539 0.05% 0.03% 0.06%
104 Europe MK North Macedonia 2 083 291 2.70% 0.11% 0.06%
105 Asia AZ Azerbaijan 10 228 065 1.00% 0.12% 0.05%
106 Australia/Oceania PG Papua New Guinea 9 111 416 0.18% 0.08% 0.05%
107 Asia PK Pakistan 225 052 106 0.17% 0.09% 0.05%
108 Africa EG Egypt 104 206 611 0.09% 0.09% 0.05%
109 Africa SN Senegal 17 170 983 0.05% 0.03% 0.05%
110 North America HT Haiti 11 537 613 0.04% 0.11% 0.05%
111 Africa AO Angola 33 854 369 0.05% 0.06% 0.04%
112 Europe PL Poland 37 806 199 3.25% 0.14% 0.04%
113 Europe RO Romania 19 112 434 1.56% 0.10% 0.04%
114 Africa CD DR Congo 92 193 541 0.01% 0.03% 0.04%
115 Asia VN Vietnam 98 190 424 0.01% 0.03% 0.04%
116 Asia SG Singapore 5 895 106 0.04% 0.04% 0.04%
117 Africa MW Malawi 19 608 460 0.02% 0.01% 0.03%
118 Africa BI Burundi 12 233 192 0.03% 0.02% 0.03%
119 Asia SY Syria 17 912 377 0.06% 0.02% 0.03%
120 Africa GW Guinea-Bissau 2 013 056 0.04% 0.02% 0.03%
121 Africa GM Gambia 2 482 345 0.06% 0.01% 0.02%
122 Africa GH Ghana 31 701 723 0.05% 0.02% 0.02%
123 Africa GA Gabon 2 276 606 0.48% 0.11% 0.02%
124 Europe AL Albania 2 874 733 1.09% 0.04% 0.02%
125 Africa TG Togo 8 466 679 0.09% 0.02% 0.02%
126 Africa SS South Sudan 11 321 278 0.04% 0.00% 0.02%
127 Africa ET Ethiopia 117 721 012 0.10% 0.02% 0.01%
128 Africa CF Central African R. 4 911 255 0.04% 0.00% 0.01%
129 Africa GN Guinea 13 477 487 0.06% 0.01% 0.01%
130 Africa CM Cameroon 27 185 688 0.17% 0.05% 0.01%
131 Africa MG Madagascar 28 380 145 0.08% 0.02% 0.01%
132 Africa CI Ivory Coast 27 010 778 0.06% 0.02% 0.01%
133 Asia LA Laos 7 378 094 0.03% 0.01% 0.01%
134 Africa SD Sudan 44 841 043 0.01% 0.01% 0.01%
135 Australia/Oceania AU Australia 25 787 457 0.01% 0.01% 0.01%
136 Australia/Oceania NZ New Zealand 5 002 100 0.01% 0.00% 0.00%
137 Asia TJ Tajikistan 9 745 221 0.00% 0.00% 0.00%
138 Africa SO Somalia 16 322 179 0.05% 0.01% 0.00%
139 Asia HK Hong Kong 7 556 153 0.01% 0.00% 0.00%
140 Africa BJ Benin 12 430 547 0.02% 0.00% 0.00%
141 Asia YE Yemen 30 462 559 0.02% 0.00% 0.00%
142 Africa NE Niger 25 052 226 0.00% 0.00% 0.00%
143 Africa ML Mali 20 814 956 0.03% 0.00% 0.00%
144 Africa BF Burkina Faso 21 457 858 0.01% 0.00% 0.00%
145 Africa TZ Tanzania 61 379 918 0.00% 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 Africa TD Chad 16 881 734 0.01% 0.00% 0.00%
149 Africa NG Nigeria 211 086 857 0.01% 0.00% 0.00%
150 Asia CN China 1 439 323 776 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 Europe BA Bosnia and Herzegovina 3 260 903 5.89% 22.34% 0.19%
2 Europe MK North Macedonia 2 083 291 4.10% 18.85% 0.11%
3 Asia YE Yemen 30 462 559 15.59% (14.83)% (0.00)%
4 North America MX Mexico 130 249 787 11.09% 13.15% 0.26%
5 Africa SD Sudan 44 841 043 13.85% (10.56)% (0.01)%
6 Asia SY Syria 17 912 377 8.47% (9.78)% (0.02)%
7 South America PE Peru 33 417 999 9.44% 8.40% 1.30%
8 Europe PL Poland 37 806 199 2.53% 8.39% 0.14%
9 Europe BG Bulgaria 6 897 383 4.25% 7.77% 0.26%
10 Europe RO Romania 19 112 434 3.46% 6.79% 0.10%
11 Africa ML Mali 20 814 956 2.89% (6.38)% (0.00)%
12 Europe SK Slovakia 5 462 219 5.23% 5.85% 0.18%
13 North America JM Jamaica 2 973 752 2.12% 5.78% 0.23%
14 Africa MG Madagascar 28 380 145 2.71% (5.64)% (0.02)%
15 Africa GM Gambia 2 482 345 2.22% (5.26)% (0.01)%
16 Africa ZW Zimbabwe 15 073 052 4.65% (5.23)% (0.10)%
17 Asia AF Afghanistan 39 777 838 4.95% 5.03% 0.40%
18 Asia TW Taiwan 23 858 775 4.73% 5.00% 0.16%
19 Africa BF Burkina Faso 21 457 858 1.59% (4.84)% (0.00)%
20 Europe MD Moldova 4 024 820 2.78% 4.77% 0.15%
21 Europe HU Hungary 9 636 429 3.70% 4.72% 0.25%
22 Africa MW Malawi 19 608 460 2.76% (4.55)% (0.01)%
23 Africa TN Tunisia 11 938 855 4.26% 4.18% 1.67%
24 South America PY Paraguay 7 217 680 3.43% 4.15% 4.23%
25 Africa EG Egypt 104 206 611 5.46% (3.99)% (0.09)%
26 Africa KE Kenya 54 919 126 2.26% (3.94)% (0.08)%
27 Europe RU Russia 145 995 449 4.02% 3.84% 0.94%
28 Europe UA Ukraine 43 477 348 2.82% 3.81% 0.43%
29 South America EC Ecuador 17 903 196 3.35% 3.80% 0.63%
30 Africa NG Nigeria 211 086 857 1.26% (3.61)% (0.00)%
31 Asia AM Armenia 2 968 639 2.44% 3.56% 0.32%
32 Europe HR Croatia 4 080 560 2.25% 3.38% 0.51%
33 North America SV El Salvador 6 518 068 3.06% 3.13% 0.27%
34 Asia ID Indonesia 276 335 647 2.88% 3.00% 0.35%
35 North America HN Honduras 10 057 539 3.18% 2.94% 0.83%
36 South America BR Brazil 214 029 732 3.37% 2.93% 3.59%
37 Africa LR Liberia 5 172 831 1.94% (2.81)% (0.07)%
38 Africa NA Namibia 2 585 549 2.60% 2.79% 3.37%
39 South America BO Bolivia 11 827 701 2.68% 2.77% 2.46%
40 Asia PK Pakistan 225 052 106 2.48% (2.68)% (0.09)%
41 Europe RS Serbia 8 703 038 0.91% 2.61% 0.27%
42 Africa CM Cameroon 27 185 688 1.63% (2.61)% (0.05)%
43 Africa ET Ethiopia 117 721 012 1.57% (2.57)% (0.02)%
44 Africa TD Chad 16 881 734 3.05% (2.56)% (0.00)%
45 North America HT Haiti 11 537 613 2.72% 2.53% 0.11%
46 Africa DZ Algeria 44 619 299 2.91% (2.52)% (0.08)%
47 Europe DE Germany 84 044 880 1.61% 2.52% 0.34%
48 Africa CG Congo 5 649 611 1.06% (2.43)% (0.07)%
49 Africa SO Somalia 16 322 179 5.94% (2.37)% (0.01)%
50 Europe IT Italy 60 375 142 2.06% 2.36% 0.41%
51 South America PR Puerto Rico 3 193 694 1.39% 2.34% 0.30%
52 Africa SN Senegal 17 170 983 3.19% (2.33)% (0.03)%
53 South America CO Colombia 51 410 163 2.60% 2.33% 5.72%
54 Asia BD Bangladesh 166 284 843 1.80% 2.32% 0.17%
55 Asia JP Japan 126 098 833 1.93% 2.28% 0.22%
56 Africa LS Lesotho 2 158 771 6.13% (2.26)% (0.06)%
57 Africa AO Angola 33 854 369 2.22% (2.24)% (0.06)%
58 Europe AL Albania 2 874 733 2.00% (2.20)% (0.04)%
59 Asia IL Israel 9 326 000 0.76% (2.19)% (0.03)%
60 North America US USA 332 891 997 1.65% 2.17% 0.49%
61 Africa ZA South Africa 60 035 300 3.67% 2.17% 1.33%
62 Asia GE Georgia 3 981 700 1.93% 2.17% 2.21%
63 North America GT Guatemala 18 237 064 2.25% 2.15% 0.75%
64 Asia PH Philippines 110 998 038 1.50% 2.07% 0.66%
65 Asia LB Lebanon 6 795 625 1.70% 2.03% 0.30%
66 Europe CZ Czechia 10 728 338 1.90% 2.03% 0.30%
67 Europe GR Greece 10 373 379 2.56% 2.02% 1.12%
68 Africa CD DR Congo 92 193 541 1.58% 1.92% 0.03%
69 Africa BJ Benin 12 430 547 1.10% 1.92% 0.00%
70 Asia AZ Azerbaijan 10 228 065 1.71% 1.92% 0.12%
71 South America AR Argentina 45 599 133 1.80% 1.85% 6.71%
72 Asia IN India 1 393 197 894 1.24% 1.82% 0.93%
73 Africa ZM Zambia 18 882 018 1.45% 1.82% 0.83%
74 Africa MR Mauritania 4 767 949 1.49% 1.81% 0.10%
75 Africa GW Guinea-Bissau 2 013 056 2.50% 1.75% 0.02%
76 Africa MZ Mozambique 32 102 539 1.21% 1.74% 0.03%
77 Asia KG Kyrgyzstan 6 628 675 1.84% 1.67% 0.82%
78 Asia KH Cambodia 16 943 724 1.15% 1.58% 0.41%
79 Asia LK Sri Lanka 21 500 678 1.40% 1.58% 1.39%
80 Africa BW Botswana 2 397 666 1.85% 1.58% 1.95%
81 Africa UG Uganda 47 136 940 1.48% 1.55% 0.24%
82 Asia NP Nepal 29 645 266 1.72% 1.55% 1.40%
83 Asia MM Myanmar 54 764 776 1.47% 1.54% 0.04%
84 Asia JO Jordan 10 301 629 1.29% 1.52% 0.64%
85 South America CL Chile 19 275 819 1.62% 1.51% 3.95%
86 Asia IR Iran 85 037 547 1.54% 1.50% 1.29%
87 Africa SL Sierra Leone 8 134 266 0.80% 1.45% 0.04%
88 Asia OM Oman 5 232 360 1.18% 1.45% 3.04%
89 Europe LT Lithuania 2 685 164 1.38% 1.43% 1.09%
90 South America UY Uruguay 3 485 455 1.61% 1.43% 10.72%
91 Africa GN Guinea 13 477 487 0.95% 1.36% 0.01%
92 Asia TR Turkey 85 221 356 0.77% 1.32% 0.89%
93 Asia SA Saudi Arabia 35 340 273 1.29% 1.26% 0.39%
94 Africa MA Morocco 37 335 763 1.49% 1.25% 0.11%
95 North America CR Costa Rica 5 139 361 1.19% 1.19% 3.93%
96 South America VE Venezuela 28 357 362 1.37% 1.19% 0.55%
97 Europe AT Austria 9 056 421 1.00% 1.16% 0.37%
98 North America CA Canada 38 064 034 0.77% 1.16% 0.55%
99 Asia MY Malaysia 32 768 929 0.85% 1.13% 2.31%
100 Africa RW Rwanda 13 263 111 1.14% 1.12% 0.13%
101 Asia KZ Kazakhstan 18 994 986 2.09% 1.10% 0.81%
102 Europe FR France 65 414 223 1.14% 1.01% 0.89%
103 Europe FI Finland 5 549 107 0.55% 0.97% 0.21%
104 Asia TH Thailand 69 970 599 0.90% 0.97% 0.53%
105 Africa GA Gabon 2 276 606 0.67% 0.96% 0.11%
106 Europe BY Belarus 9 446 293 0.83% 0.92% 1.08%
107 Africa CI Ivory Coast 27 010 778 0.73% 0.88% 0.02%
108 North America NI Nicaragua 6 701 154 1.53% 0.84% 0.04%
109 Africa NE Niger 25 052 226 3.04% 0.83% 0.00%
110 North America PA Panama 4 380 710 1.30% 0.82% 1.88%
111 North America CU Cuba 11 319 877 0.71% 0.81% 1.28%
112 Africa LY Libya 6 962 061 1.71% 0.80% 0.44%
113 Africa TG Togo 8 466 679 0.60% 0.80% 0.02%
114 Europe SI Slovenia 2 079 217 0.83% 0.76% 1.03%
115 Africa GH Ghana 31 701 723 1.15% 0.70% 0.02%
116 Australia/Oceania PG Papua New Guinea 9 111 416 1.03% 0.66% 0.08%
117 Europe BE Belgium 11 638 738 0.91% 0.62% 1.01%
118 Asia MN Mongolia 3 329 539 0.57% 0.62% 5.20%
119 Africa ER Eritrea 3 594 099 0.57% 0.60% 0.17%
120 Asia QA Qatar 2 807 805 0.53% 0.60% 0.79%
121 Asia IQ Iraq 41 097 086 0.59% 0.58% 1.22%
122 Asia UZ Uzbekistan 33 940 294 0.39% 0.53% 0.10%
123 North America DO Dominican R. 10 953 688 0.90% 0.48% 1.23%
124 Europe ES Spain 46 772 428 1.12% 0.44% 0.83%
125 Africa CF Central African R. 4 911 255 1.66% 0.43% 0.00%
126 Asia KR South Korea 51 312 183 0.67% 0.42% 0.12%
127 Asia KW Kuwait 4 331 905 0.55% 0.37% 3.86%
128 Europe CH Switzerland 8 716 208 0.49% 0.35% 0.55%
129 Asia VN Vietnam 98 190 424 0.34% 0.32% 0.03%
130 Europe PT Portugal 10 167 712 1.45% 0.30% 0.84%
131 Asia SG Singapore 5 895 106 0.20% 0.27% 0.04%
132 Africa BI Burundi 12 233 192 0.15% 0.27% 0.02%
133 Europe NL Netherlands 17 171 808 0.39% 0.25% 1.26%
134 Asia LA Laos 7 378 094 0.15% 0.23% 0.01%
135 Europe GB United Kingdom 68 233 180 1.37% 0.21% 1.08%
136 Europe SE Sweden 10 160 557 0.36% 0.20% 0.89%
137 Asia AE Arab Emirates 10 006 535 0.25% 0.20% 2.31%
138 Europe NO Norway 5 462 484 0.30% 0.11% 0.64%
139 Europe DK Denmark 5 812 068 0.22% 0.09% 1.27%
140 Europe IE Ireland 4 991 403 1.41% 0.00% 0.83%
141 Australia/Oceania AU Australia 25 787 457 0.07% 0.00% 0.01%
142 Africa SS South Sudan 11 321 278 0.56% 0.00% 0.00%
143 Australia/Oceania NZ New Zealand 5 002 100 0.00% 0.00% 0.00%
144 Asia HK Hong Kong 7 556 153 1.20% 0.00% 0.00%
145 Asia PS Palestine 5 216 297 0.00% 0.00% 0.02%
146 Asia TJ Tajikistan 9 745 221 0.00% 0.00% 0.00%
147 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
148 Africa TZ Tanzania 61 379 918 0.00% 0.00% 0.00%
149 Europe TM Turkmenistan 6 118 000 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 33 417 999 190 463 5.699
2 Europe HU Hungary 9 636 429 29 883 3.101
3 Europe BA Bosnia and Herzegovina 3 260 903 9 640 2.956
4 Europe CZ Czechia 10 728 338 30 280 2.822
5 Europe MK North Macedonia 2 083 291 5 475 2.628
6 Europe BG Bulgaria 6 897 383 17 998 2.609
7 South America BR Brazil 214 029 732 502 880 2.350
8 Europe SK Slovakia 5 462 219 12 500 2.288
9 Europe SI Slovenia 2 079 217 4 741 2.280
10 Europe BE Belgium 11 638 738 25 139 2.160
11 Europe IT Italy 60 375 142 127 301 2.108
12 Europe HR Croatia 4 080 560 8 184 2.006
13 Europe PL Poland 37 806 199 74 864 1.980
14 South America AR Argentina 45 599 133 89 533 1.964
15 South America CO Colombia 51 410 163 99 949 1.944
16 Europe GB United Kingdom 68 233 180 127 995 1.876
17 North America US USA 332 891 997 596 021 1.790
18 North America MX Mexico 130 249 787 231 412 1.777
19 Europe ES Spain 46 772 428 80 664 1.725
20 Europe RO Romania 19 112 434 32 402 1.695
21 Europe FR France 65 414 223 109 891 1.680
22 Europe PT Portugal 10 167 712 17 068 1.679
23 South America CL Chile 19 275 819 31 558 1.637
24 Europe LT Lithuania 2 685 164 4 367 1.626
25 South America PY Paraguay 7 217 680 11 627 1.611
26 Europe MD Moldova 4 024 820 6 172 1.534
27 Asia AM Armenia 2 968 639 4 500 1.516
28 South America UY Uruguay 3 485 455 5 275 1.513
29 North America PA Panama 4 380 710 6 474 1.478
30 Europe SE Sweden 10 160 557 14 575 1.435
31 South America BO Bolivia 11 827 701 16 078 1.359
32 Asia GE Georgia 3 981 700 5 187 1.303
33 Europe GR Greece 10 373 379 12 562 1.211
34 Europe UA Ukraine 43 477 348 52 102 1.198
35 South America EC Ecuador 17 903 196 21 304 1.190
36 Africa TN Tunisia 11 938 855 14 143 1.185
37 Europe CH Switzerland 8 716 208 10 267 1.178
38 Asia LB Lebanon 6 795 625 7 826 1.152
39 Europe AT Austria 9 056 421 10 419 1.151
40 Europe DE Germany 84 044 880 90 414 1.076
41 Europe NL Netherlands 17 171 808 17 730 1.032
42 Europe IE Ireland 4 991 403 4 941 0.990
43 Africa ZA South Africa 60 035 300 58 999 0.983
44 Asia IR Iran 85 037 547 83 077 0.977
45 Asia JO Jordan 10 301 629 9 675 0.939
46 Europe RU Russia 145 995 449 130 349 0.893
47 North America CR Costa Rica 5 139 361 4 489 0.874
48 Europe AL Albania 2 874 733 2 454 0.854
49 Europe RS Serbia 8 703 038 7 004 0.805
50 South America PR Puerto Rico 3 193 694 2 540 0.795
51 Asia IL Israel 9 326 000 6 428 0.689
52 North America CA Canada 38 064 034 26 125 0.686
53 North America HN Honduras 10 057 539 6 794 0.675
54 Asia TR Turkey 85 221 356 49 242 0.578
55 Asia OM Oman 5 232 360 2 744 0.524
56 Asia AZ Azerbaijan 10 228 065 4 964 0.485
57 North America GT Guatemala 18 237 064 8 695 0.477
58 Africa NA Namibia 2 585 549 1 206 0.466
59 Africa LY Libya 6 962 061 3 176 0.456
60 Europe DK Denmark 5 812 068 2 530 0.435
61 Asia KW Kuwait 4 331 905 1 881 0.434
62 Asia IQ Iraq 41 097 086 16 918 0.412
63 Asia KZ Kazakhstan 18 994 986 7 666 0.404
64 Africa BW Botswana 2 397 666 940 0.392
65 North America SV El Salvador 6 518 068 2 337 0.358
66 North America JM Jamaica 2 973 752 1 036 0.348
67 North America DO Dominican R. 10 953 688 3 767 0.344
68 Europe BY Belarus 9 446 293 3 053 0.323
69 Asia NP Nepal 29 645 266 8 853 0.299
70 Asia KG Kyrgyzstan 6 628 675 1 945 0.293
71 Asia IN India 1 393 197 894 388 829 0.279
72 Africa MA Morocco 37 335 763 9 241 0.247
73 Asia SA Saudi Arabia 35 340 273 7 690 0.218
74 Asia PH Philippines 110 998 038 23 740 0.214
75 Asia QA Qatar 2 807 805 585 0.208
76 Asia ID Indonesia 276 335 647 55 259 0.200
77 Asia AE Arab Emirates 10 006 535 1 763 0.176
78 Europe FI Finland 5 549 107 969 0.175
79 Africa LS Lesotho 2 158 771 329 0.152
80 Africa EG Egypt 104 206 611 15 866 0.152
81 Europe NO Norway 5 462 484 792 0.145
82 Asia MY Malaysia 32 768 929 4 491 0.137
83 Asia MN Mongolia 3 329 539 446 0.134
84 Asia LK Sri Lanka 21 500 678 2 595 0.121
85 Asia JP Japan 126 098 833 14 465 0.115
86 Africa ZW Zimbabwe 15 073 052 1 678 0.111
87 Asia AF Afghanistan 39 777 838 4 305 0.108
88 South America VE Venezuela 28 357 362 2 959 0.104
89 North America CU Cuba 11 319 877 1 169 0.103
90 Asia SY Syria 17 912 377 1 848 0.103
91 Africa MR Mauritania 4 767 949 482 0.101
92 Asia PK Pakistan 225 052 106 22 016 0.098
93 Africa ZM Zambia 18 882 018 1 694 0.090
94 Asia BD Bangladesh 166 284 843 13 711 0.083
95 Africa DZ Algeria 44 619 299 3 640 0.082
96 Africa GM Gambia 2 482 345 181 0.073
97 Africa GA Gabon 2 276 606 156 0.069
98 Africa SN Senegal 17 170 983 1 158 0.067
99 Africa KE Kenya 54 919 126 3 479 0.063
100 Africa SD Sudan 44 841 043 2 748 0.061
101 Asia MM Myanmar 54 764 776 3 267 0.060
102 Africa MW Malawi 19 608 460 1 170 0.060
103 Africa CM Cameroon 27 185 688 1 317 0.048
104 Africa SO Somalia 16 322 179 775 0.048
105 Asia YE Yemen 30 462 559 1 355 0.044
106 Asia KR South Korea 51 312 183 2 005 0.039
107 Africa ET Ethiopia 117 721 012 4 287 0.036
108 Australia/Oceania AU Australia 25 787 457 910 0.035
109 Africa GW Guinea-Bissau 2 013 056 69 0.034
110 North America HT Haiti 11 537 613 374 0.032
111 Africa MG Madagascar 28 380 145 903 0.032
112 Africa CG Congo 5 649 611 164 0.029
113 Africa RW Rwanda 13 263 111 382 0.029
114 North America NI Nicaragua 6 701 154 190 0.028
115 Asia HK Hong Kong 7 556 153 210 0.028
116 Africa MZ Mozambique 32 102 539 852 0.026
117 Asia KH Cambodia 16 943 724 447 0.026
118 Africa AO Angola 33 854 369 866 0.026
119 Africa ML Mali 20 814 956 524 0.025
120 Asia TW Taiwan 23 858 775 599 0.025
121 Africa GH Ghana 31 701 723 793 0.025
122 Asia TH Thailand 69 970 599 1 709 0.024
123 Asia UZ Uzbekistan 33 940 294 720 0.021
124 Africa CF Central African R. 4 911 255 98 0.020
125 Australia/Oceania PG Papua New Guinea 9 111 416 173 0.019
126 Africa LR Liberia 5 172 831 95 0.018
127 Africa TG Togo 8 466 679 128 0.015
128 Africa UG Uganda 47 136 940 694 0.015
129 Africa GN Guinea 13 477 487 167 0.012
130 Africa CI Ivory Coast 27 010 778 309 0.011
131 Africa SL Sierra Leone 8 134 266 84 0.010
132 Africa TD Chad 16 881 734 174 0.010
133 Africa SS South Sudan 11 321 278 115 0.010
134 Africa NG Nigeria 211 086 857 2 117 0.010
135 Africa CD DR Congo 92 193 541 882 0.010
136 Africa BJ Benin 12 430 547 104 0.008
137 Africa BF Burkina Faso 21 457 858 168 0.008
138 Africa NE Niger 25 052 226 193 0.008
139 Africa ER Eritrea 3 594 099 21 0.006
140 Asia SG Singapore 5 895 106 34 0.006
141 Australia/Oceania NZ New Zealand 5 002 100 26 0.005
142 Africa BI Burundi 12 233 192 8 0.001
143 Asia VN Vietnam 98 190 424 66 0.001
144 Asia LA Laos 7 378 094 3 0.000
145 Africa TZ Tanzania 61 379 918 21 0.000
146 Asia PS Palestine 5 216 297 1 0.000
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 9 745 221 0 0.000
150 Europe TM Turkmenistan 6 118 000 0 0.000

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

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

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

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"