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": 2021-05-10 16:56
(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 +820 (+1 026) +10 (+8)
CZ Czechia +381 (+721) +13 (+24)
DE Germany +4 041 (+8 290) +42 (+119)
HU Hungary +677 (+1 145) +91 (+98)
PL Poland +2 032 (+3 851) +22 (+147)
SK Slovakia, [gov], [okr]+311 (+80) +32 (+29)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 South America 437 038 871 2.76% 3.40% 3.03%
2 Europe 756 023 952 2.59% 2.17% 1.55%
3 Asia 4 663 339 167 0.48% 1.13% 1.22%
4 North America 592 616 840 2.14% 1.44% 1.06%
5 Africa 1 367 189 143 0.12% 0.09% 0.08%
6 Australia/Oceania 43 225 507 0.04% 0.05% 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 South America 437 038 871 2.77% 4.02% 3.40%
2 Africa 1 367 189 143 2.93% (3.71)% (0.09)%
3 Europe 756 023 952 2.16% 2.54% 2.17%
4 North America 592 616 840 2.21% 2.13% 1.44%
5 Australia/Oceania 43 225 507 1.02% (1.48)% (0.05)%
6 Asia 4 663 339 167 1.12% 1.25% 1.13%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 437 038 871 703 330 1.609
2 North America 592 616 840 850 582 1.435
3 Europe 756 023 952 1 036 077 1.370
4 Asia 4 663 339 167 560 576 0.120
5 Africa 1 367 189 143 124 702 0.091
6 Australia/Oceania 43 225 507 1 347 0.031

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 3 484 011 5.56% 10.03% 8.42%
2 Europe LT Lithuania 2 689 695 3.52% 4.95% 5.27%
3 Europe NL Netherlands 17 167 263 4.04% 5.24% 5.19%
4 South America AR Argentina 45 549 324 3.13% 5.76% 5.11%
5 Europe SE Sweden 10 153 000 5.11% 6.23% 4.86%
6 North America CR Costa Rica 5 133 774 1.74% 3.56% 4.84%
7 Asia GE Georgia 3 982 617 2.09% 3.49% 4.10%
8 Europe HR Croatia 4 083 587 3.06% 5.27% 3.87%
9 South America CO Colombia 51 345 002 2.40% 3.85% 3.61%
10 South America PY Paraguay 7 207 149 2.52% 3.67% 3.50%
11 Europe SI Slovenia 2 079 182 5.16% 4.06% 3.46%
12 Asia NP Nepal 29 582 184 0.44% 1.56% 3.42%
13 Asia KW Kuwait 4 324 308 3.03% 3.77% 3.36%
14 Asia IN India 1 391 568 121 0.87% 2.68% 3.21%
15 Europe FR France 65 396 910 4.53% 4.79% 3.19%
16 Asia MN Mongolia 3 323 187 1.30% 3.75% 3.19%
17 Asia TR Turkey 85 112 315 3.19% 6.04% 3.14%
18 South America BR Brazil 213 848 364 3.32% 3.44% 3.13%
19 Europe BE Belgium 11 632 688 3.02% 3.16% 2.77%
20 South America CL Chile 19 256 115 3.13% 3.76% 2.70%
21 Europe GR Greece 10 379 470 2.10% 2.74% 2.57%
22 Asia IR Iran 84 908 308 1.62% 2.97% 2.51%
23 Asia QA Qatar 2 807 805 2.33% 3.26% 2.47%
24 North America CA Canada 38 024 294 1.67% 2.57% 2.38%
25 Asia AE Arab Emirates 9 992 172 3.08% 2.24% 2.09%
26 South America PE Peru 33 362 768 2.44% 2.72% 2.04%
27 Europe DE Germany 84 012 757 1.92% 2.59% 2.01%
28 Europe CH Switzerland 8 708 610 2.18% 2.45% 1.96%
29 Europe IT Italy 60 385 788 3.07% 2.48% 1.89%
30 Europe DK Denmark 5 809 622 1.35% 1.57% 1.83%
31 Europe CZ Czechia 10 725 956 7.59% 2.52% 1.73%
32 Europe RS Serbia 8 707 250 3.93% 2.94% 1.69%
33 Europe AT Austria 9 050 255 2.75% 2.59% 1.62%
34 Asia IQ Iraq 40 988 315 1.25% 1.97% 1.61%
35 South America PR Puerto Rico 3 193 694 1.65% 3.03% 1.57%
36 South America BO Bolivia 11 808 555 1.24% 1.29% 1.55%
37 Europe HU Hungary 9 639 365 4.67% 3.26% 1.47%
38 Europe UA Ukraine 43 508 768 2.32% 2.59% 1.43%
39 Asia OM Oman 5 216 697 1.34% 2.46% 1.42%
40 Europe BY Belarus 9 446 666 1.67% 1.49% 1.36%
41 Asia AM Armenia 2 967 975 1.93% 2.32% 1.35%
42 Asia MY Malaysia 32 719 078 0.94% 1.02% 1.35%
43 Europe PL Poland 37 811 163 3.83% 2.99% 1.33%
44 North America US USA 332 659 090 3.17% 1.94% 1.31%
45 Africa TN Tunisia 11 923 998 1.37% 1.74% 1.30%
46 South America EC Ecuador 17 870 970 1.01% 1.29% 1.25%
47 Europe BG Bulgaria 6 903 636 2.92% 2.32% 1.24%
48 Asia JO Jordan 10 289 462 4.02% 2.36% 1.18%
49 Asia LB Lebanon 6 799 282 4.67% 2.41% 1.17%
50 Asia KZ Kazakhstan 18 967 992 0.98% 1.60% 1.15%
51 Europe BA Bosnia and Herzegovina 3 263 343 2.63% 2.35% 1.13%
52 Asia LK Sri Lanka 21 489 910 0.36% 0.58% 1.13%
53 North America CU Cuba 11 320 705 0.90% 1.11% 1.10%
54 Europe MK North Macedonia 2 083 301 3.26% 2.68% 1.10%
55 Africa BW Botswana 2 391 948 1.35% 1.12% 1.06%
56 North America HN Honduras 10 038 587 0.92% 1.01% 1.04%
57 Europe NO Norway 5 457 395 1.13% 1.01% 1.00%
58 North America PA Panama 4 372 539 2.15% 0.86% 0.90%
59 Europe ES Spain 46 770 258 3.10% 1.81% 0.85%
60 Asia AZ Azerbaijan 10 217 089 1.01% 1.76% 0.85%
61 Europe SK Slovakia 5 461 902 3.31% 1.12% 0.80%
62 Africa NA Namibia 2 580 010 0.87% 0.76% 0.78%
63 Europe IE Ireland 4 984 775 2.23% 0.95% 0.74%
64 Europe RO Romania 19 127 777 2.08% 1.41% 0.74%
65 Asia PH Philippines 110 822 682 0.56% 0.94% 0.72%
66 Europe RU Russia 145 987 952 1.02% 0.70% 0.67%
67 North America DO Dominican R. 10 940 620 0.83% 0.55% 0.64%
68 Europe MD Moldova 4 025 943 2.57% 1.26% 0.60%
69 Asia KG Kyrgyzstan 6 615 723 0.25% 0.52% 0.60%
70 Africa LY Libya 6 950 826 1.09% 0.75% 0.51%
71 Asia JP Japan 126 145 174 0.28% 0.44% 0.50%
72 North America GT Guatemala 18 197 167 0.50% 0.72% 0.49%
73 North America JM Jamaica 2 972 202 1.12% 0.65% 0.49%
74 South America VE Venezuela 28 367 006 0.32% 0.50% 0.46%
75 Asia KH Cambodia 16 915 901 0.11% 0.37% 0.44%
76 Europe FI Finland 5 548 075 0.90% 0.52% 0.39%
77 Europe GB United Kingdom 68 190 397 1.96% 0.40% 0.37%
78 Europe PT Portugal 10 171 271 3.57% 0.51% 0.36%
79 Africa ZA South Africa 59 945 412 0.64% 0.27% 0.36%
80 Asia TH Thailand 69 949 602 0.11% 0.31% 0.34%
81 Asia SA Saudi Arabia 35 275 050 0.18% 0.34% 0.34%
82 Europe AL Albania 2 875 110 2.39% 0.55% 0.29%
83 North America SV El Salvador 6 514 142 0.33% 0.29% 0.28%
84 Africa GA Gabon 2 270 275 0.61% 0.56% 0.27%
85 Africa CM Cameroon 27 106 006 0.18% 0.26% 0.26%
86 Asia ID Indonesia 275 988 146 0.32% 0.23% 0.23%
87 Asia PK Pakistan 224 535 621 0.16% 0.26% 0.21%
88 North America MX Mexico 130 087 038 0.66% 0.30% 0.20%
89 Australia/Oceania PG Papua New Guinea 9 091 010 0.13% 0.19% 0.18%
90 Africa CG Congo 5 633 234 0.07% 0.08% 0.14%
91 Asia UZ Uzbekistan 33 881 957 0.05% 0.12% 0.14%
92 Asia KR South Korea 51 306 896 0.12% 0.15% 0.14%
93 Africa EG Egypt 103 974 224 0.09% 0.11% 0.13%
94 Asia BD Bangladesh 166 087 745 0.15% 0.24% 0.12%
95 Asia PS Palestine 5 202 003 0.01% 0.02% 0.10%
96 Africa KE Kenya 54 776 405 0.12% 0.14% 0.10%
97 Africa CF Central African R. 4 901 149 0.03% 0.10% 0.09%
98 Africa MA Morocco 37 283 183 0.17% 0.14% 0.09%
99 Africa AO Angola 33 730 885 0.03% 0.07% 0.09%
100 Africa MG Madagascar 28 294 285 0.08% 0.17% 0.08%
101 Asia AF Afghanistan 39 672 184 0.02% 0.05% 0.08%
102 Africa MR Mauritania 4 753 206 0.07% 0.06% 0.08%
103 Asia LA Laos 7 365 397 0.02% 0.07% 0.08%
104 Africa ET Ethiopia 117 377 636 0.11% 0.13% 0.06%
105 Asia IL Israel 9 197 590 3.84% 0.14% 0.06%
106 Africa DZ Algeria 44 523 981 0.05% 0.05% 0.06%
107 Africa SO Somalia 16 268 669 0.06% 0.05% 0.05%
108 Africa RW Rwanda 13 224 396 0.12% 0.07% 0.05%
109 Africa GN Guinea 13 434 507 0.07% 0.06% 0.05%
110 Asia SY Syria 17 861 120 0.06% 0.08% 0.05%
111 Asia SG Singapore 5 889 582 0.04% 0.05% 0.04%
112 Africa TG Togo 8 443 291 0.11% 0.07% 0.04%
113 Africa ER Eritrea 3 588 197 0.06% 0.04% 0.03%
114 Africa ZM Zambia 18 819 883 0.35% 0.05% 0.03%
115 Africa LS Lesotho 2 156 732 0.38% 0.01% 0.03%
116 Africa SN Senegal 17 117 756 0.12% 0.03% 0.03%
117 Africa GM Gambia 2 474 151 0.08% 0.06% 0.02%
118 North America NI Nicaragua 6 691 682 0.01% 0.01% 0.02%
119 Africa BI Burundi 12 190 433 0.03% 0.04% 0.02%
120 Africa CI Ivory Coast 26 932 014 0.09% 0.02% 0.02%
121 Africa SD Sudan 44 717 636 0.02% 0.02% 0.02%
122 Africa ML Mali 20 744 549 0.03% 0.05% 0.02%
123 Africa ZW Zimbabwe 15 047 030 0.12% 0.03% 0.02%
124 Africa UG Uganda 46 962 440 0.01% 0.01% 0.01%
125 Africa MZ Mozambique 31 996 859 0.15% 0.02% 0.01%
126 Africa GH Ghana 31 623 590 0.12% 0.02% 0.01%
127 North America HT Haiti 11 520 906 0.03% 0.01% 0.01%
128 Asia YE Yemen 30 383 405 0.01% 0.02% 0.01%
129 Africa SS South Sudan 11 305 506 0.06% 0.01% 0.01%
130 Africa BJ Benin 12 392 243 0.04% 0.01% 0.01%
131 Asia VN Vietnam 98 085 243 0.00% 0.00% 0.01%
132 Australia/Oceania AU Australia 25 751 901 0.01% 0.01% 0.01%
133 Australia/Oceania NZ New Zealand 5 002 100 0.01% 0.01% 0.01%
134 Africa MW Malawi 19 548 837 0.13% 0.01% 0.01%
135 Africa CD DR Congo 91 864 730 0.01% 0.01% 0.01%
136 Africa BF Burkina Faso 21 388 695 0.03% 0.01% 0.01%
137 Africa LR Liberia 5 158 502 0.01% 0.00% 0.01%
138 Africa TD Chad 16 824 841 0.01% 0.01% 0.01%
139 Africa NE Niger 24 946 242 0.01% 0.00% 0.01%
140 Asia TW Taiwan 23 853 608 0.00% 0.00% 0.00%
141 Asia MM Myanmar 54 720 998 0.02% 0.00% 0.00%
142 Africa GW Guinea-Bissau 2 007 449 0.06% 0.01% 0.00%
143 Africa NG Nigeria 210 470 780 0.03% 0.00% 0.00%
144 Africa SL Sierra Leone 8 114 728 0.02% 0.00% 0.00%
145 Asia HK Hong Kong 7 548 850 0.00% 0.00% 0.00%
146 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
147 Africa TZ Tanzania 61 174 557 0.00% 0.00% 0.00%
148 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
149 Asia TJ Tajikistan 9 719 405 0.00% 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 Africa LS Lesotho 2 156 732 3.30% (16.00)% (0.01)%
2 Asia YE Yemen 30 383 405 15.59% (14.47)% (0.02)%
3 North America MX Mexico 130 087 038 9.52% 12.14% 0.30%
4 Africa SD Sudan 44 717 636 9.32% (10.49)% (0.02)%
5 Europe SK Slovakia 5 461 902 4.68% 8.41% 1.12%
6 Asia SY Syria 17 861 120 7.88% (7.95)% (0.08)%
7 Europe BA Bosnia and Herzegovina 3 263 343 5.24% 6.05% 2.35%
8 Africa EG Egypt 103 974 224 6.49% 5.91% 0.11%
9 Africa MW Malawi 19 548 837 3.41% (5.91)% (0.01)%
10 Africa SO Somalia 16 268 669 6.71% (5.89)% (0.05)%
11 Europe HU Hungary 9 639 365 3.96% 5.24% 3.26%
12 Europe BG Bulgaria 6 903 636 4.37% 4.78% 2.32%
13 Asia AF Afghanistan 39 672 184 5.55% (4.78)% (0.05)%
14 Europe MK North Macedonia 2 083 301 3.60% 4.73% 2.68%
15 Africa ZA South Africa 59 945 412 4.42% 4.53% 0.27%
16 Europe RO Romania 19 127 777 2.95% 4.42% 1.41%
17 Europe RU Russia 145 987 952 3.25% 4.24% 0.70%
18 Africa TN Tunisia 11 923 998 3.70% 4.10% 1.74%
19 South America PE Peru 33 362 768 3.26% 4.04% 2.72%
20 Africa DZ Algeria 44 523 981 2.35% (4.03)% (0.05)%
21 South America BR Brazil 213 848 364 3.11% 3.98% 3.44%
22 North America HT Haiti 11 520 906 0.84% (3.92)% (0.01)%
23 North America HN Honduras 10 038 587 2.62% 3.92% 1.01%
24 South America EC Ecuador 17 870 970 2.92% 3.73% 1.29%
25 South America PY Paraguay 7 207 149 2.71% 3.72% 3.67%
26 Europe MD Moldova 4 025 943 2.67% 3.37% 1.26%
27 Asia ID Indonesia 275 988 146 2.51% 3.05% 0.23%
28 Europe PL Poland 37 811 163 2.61% 3.04% 2.99%
29 Africa NA Namibia 2 580 010 1.81% 3.01% 0.76%
30 Europe GR Greece 10 379 470 2.81% 2.98% 2.74%
31 Africa ZW Zimbabwe 15 047 030 4.59% (2.98)% (0.03)%
32 Africa SN Senegal 17 117 756 3.15% (2.85)% (0.03)%
33 Europe UA Ukraine 43 508 768 2.64% 2.75% 2.59%
34 South America CO Colombia 51 345 002 2.61% 2.68% 3.85%
35 Africa ML Mali 20 744 549 3.06% (2.64)% (0.05)%
36 Asia AM Armenia 2 967 975 2.32% 2.52% 2.32%
37 Africa KE Kenya 54 776 405 1.87% 2.49% 0.14%
38 North America JM Jamaica 2 972 202 1.50% 2.46% 0.65%
39 Asia PK Pakistan 224 535 621 2.40% 2.40% 0.26%
40 South America BO Bolivia 11 808 555 2.68% 2.39% 1.29%
41 North America NI Nicaragua 6 691 682 2.54% (2.33)% (0.01)%
42 North America SV El Salvador 6 514 142 3.25% 2.31% 0.29%
43 Europe CZ Czechia 10 725 956 1.85% 2.29% 2.52%
44 Europe IT Italy 60 385 788 2.33% 2.23% 2.48%
45 Europe HR Croatia 4 083 587 2.56% 2.17% 5.27%
46 North America GT Guatemala 18 197 167 3.00% 2.16% 0.72%
47 Africa GM Gambia 2 474 151 2.38% (2.05)% (0.06)%
48 Europe AL Albania 2 875 110 1.63% 2.00% 0.55%
49 Asia IL Israel 9 197 590 0.68% 2.00% 0.14%
50 Asia TW Taiwan 23 853 608 1.50% 2.00% 0.00%
51 Africa BW Botswana 2 391 948 2.08% 1.95% 1.12%
52 South America UY Uruguay 3 484 011 1.56% 1.94% 10.03%
53 Africa BF Burkina Faso 21 388 695 1.14% 1.89% 0.01%
54 Asia KG Kyrgyzstan 6 615 723 1.94% 1.88% 0.52%
55 Africa MG Madagascar 28 294 285 2.32% 1.87% 0.17%
56 Africa AO Angola 33 730 885 2.31% 1.86% 0.07%
57 Africa NE Niger 24 946 242 4.31% 1.79% 0.00%
58 Africa CM Cameroon 27 106 006 1.59% 1.76% 0.26%
59 Asia IR Iran 84 908 308 1.45% 1.73% 2.97%
60 Africa CI Ivory Coast 26 932 014 0.64% 1.70% 0.02%
61 Africa MZ Mozambique 31 996 859 1.25% 1.70% 0.02%
62 Asia BD Bangladesh 166 087 745 1.69% 1.70% 0.24%
63 Asia LB Lebanon 6 799 282 1.73% 1.68% 2.41%
64 Africa ET Ethiopia 117 377 636 1.43% 1.65% 0.13%
65 Africa CF Central African R. 4 901 149 2.07% 1.63% 0.10%
66 Asia JO Jordan 10 289 462 1.22% 1.61% 2.36%
67 South America AR Argentina 45 549 324 1.68% 1.59% 5.76%
68 Africa TD Chad 16 824 841 2.41% 1.57% 0.01%
69 Africa CD DR Congo 91 864 730 1.34% 1.54% 0.01%
70 Africa GH Ghana 31 623 590 1.19% 1.54% 0.02%
71 Africa LY Libya 6 950 826 1.94% 1.54% 0.75%
72 Asia AZ Azerbaijan 10 217 089 1.77% 1.52% 1.76%
73 South America CL Chile 19 256 115 1.70% 1.52% 3.76%
74 South America VE Venezuela 28 367 006 1.43% 1.49% 0.50%
75 Asia GE Georgia 3 982 617 1.83% 1.47% 3.49%
76 Africa BJ Benin 12 392 243 1.23% 1.38% 0.01%
77 Asia PH Philippines 110 822 682 1.55% 1.35% 0.94%
78 Africa GW Guinea-Bissau 2 007 449 1.71% 1.33% 0.01%
79 Africa MA Morocco 37 283 183 1.96% 1.28% 0.14%
80 Asia NP Nepal 29 582 184 2.49% 1.26% 1.56%
81 Asia JP Japan 126 145 174 1.90% 1.24% 0.44%
82 Europe IE Ireland 4 984 775 1.69% 1.22% 0.95%
83 North America PA Panama 4 372 539 1.65% 1.20% 0.86%
84 Asia SA Saudi Arabia 35 275 050 1.39% 1.20% 0.34%
85 Europe DE Germany 84 012 757 2.68% 1.19% 2.59%
86 Europe LT Lithuania 2 689 695 1.84% 1.19% 4.95%
87 North America US USA 332 659 090 1.73% 1.14% 1.94%
88 Europe BE Belgium 11 632 688 1.25% 1.13% 3.16%
89 Asia LK Sri Lanka 21 489 910 0.85% 1.12% 0.58%
90 Australia/Oceania PG Papua New Guinea 9 091 010 1.07% 1.11% 0.19%
91 Africa CG Congo 5 633 234 1.07% 1.10% 0.08%
92 Africa MR Mauritania 4 753 206 1.91% 1.10% 0.06%
93 Europe RS Serbia 8 707 250 0.86% 1.10% 2.94%
94 Asia MM Myanmar 54 720 998 2.24% 1.10% 0.00%
95 North America CR Costa Rica 5 133 774 1.32% 1.08% 3.56%
96 Europe AT Austria 9 050 255 1.37% 1.08% 2.59%
97 North America DO Dominican R. 10 940 620 1.17% 1.05% 0.55%
98 Africa ZM Zambia 18 819 883 1.13% 1.05% 0.05%
99 Asia IN India 1 391 568 121 0.98% 1.01% 2.68%
100 Asia OM Oman 5 216 697 0.89% 0.99% 2.46%
101 South America PR Puerto Rico 3 193 694 1.41% 0.92% 3.03%
102 Asia KZ Kazakhstan 18 967 992 0.95% 0.92% 1.60%
103 North America CU Cuba 11 320 705 0.61% 0.91% 1.11%
104 Europe FR France 65 396 910 1.30% 0.88% 4.79%
105 Africa GN Guinea 13 434 507 0.81% 0.88% 0.06%
106 Africa UG Uganda 46 962 440 0.72% 0.86% 0.01%
107 Europe BY Belarus 9 446 666 0.69% 0.82% 1.49%
108 Europe GB United Kingdom 68 190 397 2.70% 0.80% 0.40%
109 Asia KH Cambodia 16 915 901 0.84% 0.79% 0.37%
110 Africa RW Rwanda 13 224 396 1.32% 0.78% 0.07%
111 Asia TH Thailand 69 949 602 0.56% 0.77% 0.31%
112 Europe SI Slovenia 2 079 182 1.14% 0.75% 4.06%
113 Asia QA Qatar 2 807 805 0.42% 0.73% 3.26%
114 Europe ES Spain 46 770 258 1.50% 0.67% 1.81%
115 Asia TR Turkey 85 112 315 0.77% 0.65% 6.04%
116 Europe FI Finland 5 548 075 0.66% 0.63% 0.52%
117 Europe PT Portugal 10 171 271 2.25% 0.61% 0.51%
118 Africa SS South Sudan 11 305 506 0.75% 0.61% 0.01%
119 Asia KW Kuwait 4 324 308 0.56% 0.60% 3.77%
120 Asia KR South Korea 51 306 896 1.24% 0.58% 0.15%
121 North America CA Canada 38 024 294 1.23% 0.58% 2.57%
122 Africa ER Eritrea 3 588 197 0.26% 0.55% 0.04%
123 Africa GA Gabon 2 270 275 0.57% 0.54% 0.56%
124 Asia MY Malaysia 32 719 078 0.38% 0.54% 1.02%
125 Asia IQ Iraq 40 988 315 0.60% 0.53% 1.97%
126 Europe NO Norway 5 457 395 0.46% 0.53% 1.01%
127 Asia MN Mongolia 3 323 187 0.45% 0.51% 3.75%
128 Africa TG Togo 8 443 291 0.56% 0.37% 0.07%
129 Africa NG Nigeria 210 470 780 0.95% 0.33% 0.00%
130 Europe CH Switzerland 8 708 610 0.97% 0.33% 2.45%
131 Asia UZ Uzbekistan 33 881 957 0.30% 0.33% 0.12%
132 Europe DK Denmark 5 809 622 1.14% 0.29% 1.57%
133 Europe NL Netherlands 17 167 263 0.73% 0.28% 5.24%
134 Europe SE Sweden 10 153 000 0.70% 0.24% 6.23%
135 Australia/Oceania AU Australia 25 751 901 0.07% 0.20% 0.01%
136 Asia AE Arab Emirates 9 992 172 0.29% 0.15% 2.24%
137 Asia SG Singapore 5 889 582 0.08% 0.13% 0.05%
138 Asia LA Laos 7 365 397 0.00% 0.00% 0.07%
139 Africa BI Burundi 12 190 433 0.12% 0.00% 0.04%
140 Australia/Oceania NZ New Zealand 5 002 100 0.23% 0.00% 0.01%
141 Africa LR Liberia 5 158 502 0.67% 0.00% 0.00%
142 Africa SL Sierra Leone 8 114 728 0.13% 0.00% 0.00%
143 Asia VN Vietnam 98 085 243 0.00% 0.00% 0.00%
144 Asia PS Palestine 5 202 003 0.00% 0.00% 0.02%
145 Asia HK Hong Kong 7 548 850 0.00% 0.00% 0.00%
146 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
147 Africa TZ Tanzania 61 174 557 0.00% 0.00% 0.00%
148 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
149 Asia TJ Tajikistan 9 719 405 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 HU Hungary 9 639 365 28 693 2.977
2 Europe CZ Czechia 10 725 956 29 680 2.767
3 Europe BA Bosnia and Herzegovina 3 263 343 8 839 2.709
4 Europe BG Bulgaria 6 903 636 16 929 2.452
5 Europe MK North Macedonia 2 083 301 5 093 2.445
6 Europe SI Slovenia 2 079 182 4 612 2.218
7 Europe SK Slovakia 5 461 902 12 051 2.206
8 Europe BE Belgium 11 632 688 24 551 2.111
9 Europe IT Italy 60 385 788 122 833 2.034
10 South America BR Brazil 213 848 364 420 048 1.964
11 South America PE Peru 33 362 768 63 796 1.912
12 Europe GB United Kingdom 68 190 397 127 605 1.871
13 Europe PL Poland 37 811 163 70 034 1.852
14 Europe HR Croatia 4 083 587 7 503 1.837
15 North America US USA 332 659 090 575 341 1.730
16 Europe ES Spain 46 770 258 78 726 1.683
17 North America MX Mexico 130 087 038 218 714 1.681
18 Europe PT Portugal 10 171 271 16 992 1.671
19 Europe FR France 65 396 910 105 659 1.616
20 Europe RO Romania 19 127 777 28 971 1.515
21 South America CO Colombia 51 345 002 77 362 1.507
22 Europe LT Lithuania 2 689 695 4 044 1.504
23 Europe MD Moldova 4 025 943 5 952 1.478
24 South America AR Argentina 45 549 324 67 155 1.474
25 North America PA Panama 4 372 539 6 264 1.433
26 Asia AM Armenia 2 967 975 4 249 1.432
27 South America CL Chile 19 256 115 27 138 1.409
28 Europe SE Sweden 10 153 000 14 173 1.396
29 Europe CH Switzerland 8 708 610 10 061 1.155
30 South America BO Bolivia 11 808 555 13 205 1.118
31 Europe AT Austria 9 050 255 10 120 1.118
32 Asia LB Lebanon 6 799 282 7 486 1.101
33 Asia GE Georgia 3 982 617 4 305 1.081
34 South America EC Ecuador 17 870 970 19 222 1.076
35 Europe UA Ukraine 43 508 768 46 512 1.069
36 Europe GR Greece 10 379 470 11 029 1.063
37 Europe NL Netherlands 17 167 263 17 336 1.010
38 Europe DE Germany 84 012 757 84 817 1.010
39 Europe IE Ireland 4 984 775 4 923 0.988
40 South America PY Paraguay 7 207 149 7 054 0.979
41 Africa TN Tunisia 11 923 998 11 429 0.959
42 Africa ZA South Africa 59 945 412 54 735 0.913
43 Asia JO Jordan 10 289 462 9 092 0.884
44 Asia IR Iran 84 908 308 74 875 0.882
45 South America UY Uruguay 3 484 011 3 072 0.882
46 Europe AL Albania 2 875 110 2 412 0.839
47 Europe RU Russia 145 987 952 113 647 0.778
48 Europe RS Serbia 8 707 250 6 557 0.753
49 South America PR Puerto Rico 3 193 694 2 367 0.741
50 Asia IL Israel 9 197 590 6 377 0.693
51 North America CR Costa Rica 5 133 774 3 365 0.655
52 North America CA Canada 38 024 294 24 587 0.647
53 North America HN Honduras 10 038 587 5 633 0.561
54 Asia TR Turkey 85 112 315 43 029 0.506
55 Asia AZ Azerbaijan 10 217 089 4 684 0.458
56 Africa LY Libya 6 950 826 3 065 0.441
57 Europe DK Denmark 5 809 622 2 497 0.430
58 North America GT Guatemala 18 197 167 7 711 0.424
59 Asia OM Oman 5 216 697 2 101 0.403
60 Asia IQ Iraq 40 988 315 15 770 0.385
61 Asia KW Kuwait 4 324 308 1 645 0.380
62 North America SV El Salvador 6 514 142 2 154 0.331
63 North America DO Dominican R. 10 940 620 3 532 0.323
64 Africa BW Botswana 2 391 948 734 0.307
65 Europe BY Belarus 9 446 666 2 632 0.279
66 North America JM Jamaica 2 972 202 806 0.271
67 Africa NA Namibia 2 580 010 689 0.267
68 Asia KG Kyrgyzstan 6 615 723 1 660 0.251
69 Africa MA Morocco 37 283 183 9 072 0.243
70 Asia KZ Kazakhstan 18 967 992 4 542 0.239
71 Asia SA Saudi Arabia 35 275 050 7 072 0.201
72 Asia QA Qatar 2 807 805 508 0.181
73 Asia IN India 1 391 568 121 244 871 0.176
74 Asia ID Indonesia 275 988 146 47 048 0.171
75 Europe FI Finland 5 548 075 922 0.166
76 Asia PH Philippines 110 822 682 18 359 0.166
77 Asia AE Arab Emirates 9 992 172 1 612 0.161
78 Africa LS Lesotho 2 156 732 319 0.148
79 Europe NO Norway 5 457 395 767 0.141
80 Africa EG Egypt 103 974 224 13 904 0.134
81 Asia NP Nepal 29 582 184 3 771 0.128
82 Africa ZW Zimbabwe 15 047 030 1 576 0.105
83 Africa MR Mauritania 4 753 206 456 0.096
84 Asia SY Syria 17 861 120 1 657 0.093
85 Asia JP Japan 126 145 174 10 876 0.086
86 Asia PK Pakistan 224 535 621 18 875 0.084
87 South America VE Venezuela 28 367 006 2 274 0.080
88 Africa DZ Algeria 44 523 981 3 328 0.075
89 Asia BD Bangladesh 166 087 745 11 916 0.072
90 Africa GM Gambia 2 474 151 175 0.071
91 Asia AF Afghanistan 39 672 184 2 698 0.068
92 Africa ZM Zambia 18 819 883 1 257 0.067
93 Africa SN Senegal 17 117 756 1 118 0.065
94 North America CU Cuba 11 320 705 732 0.065
95 Africa GA Gabon 2 270 275 143 0.063
96 Africa MW Malawi 19 548 837 1 153 0.059
97 Asia MM Myanmar 54 720 998 3 210 0.059
98 Africa KE Kenya 54 776 405 2 895 0.053
99 Africa SD Sudan 44 717 636 2 365 0.053
100 Asia MY Malaysia 32 719 078 1 674 0.051
101 Asia MN Mongolia 3 323 187 168 0.051
102 Africa SO Somalia 16 268 669 747 0.046
103 Africa CM Cameroon 27 106 006 1 144 0.042
104 Asia YE Yemen 30 383 405 1 272 0.042
105 Asia LK Sri Lanka 21 489 910 801 0.037
106 Asia KR South Korea 51 306 896 1 875 0.036
107 Australia/Oceania AU Australia 25 751 901 910 0.035
108 Africa GW Guinea-Bissau 2 007 449 67 0.033
109 Africa ET Ethiopia 117 377 636 3 888 0.033
110 North America NI Nicaragua 6 691 682 183 0.027
111 Africa CG Congo 5 633 234 148 0.026
112 Africa MZ Mozambique 31 996 859 823 0.026
113 Africa MG Madagascar 28 294 285 723 0.026
114 Africa RW Rwanda 13 224 396 338 0.026
115 Africa GH Ghana 31 623 590 783 0.025
116 Africa ML Mali 20 744 549 500 0.024
117 North America HT Haiti 11 520 906 263 0.023
118 Asia UZ Uzbekistan 33 881 957 662 0.020
119 Africa CF Central African R. 4 901 149 93 0.019
120 Africa AO Angola 33 730 885 633 0.019
121 Africa LR Liberia 5 158 502 85 0.017
122 Africa TG Togo 8 443 291 124 0.015
123 Australia/Oceania PG Papua New Guinea 9 091 010 121 0.013
124 Africa GN Guinea 13 434 507 150 0.011
125 Africa CI Ivory Coast 26 932 014 291 0.011
126 Africa SS South Sudan 11 305 506 116 0.010
127 Africa TD Chad 16 824 841 171 0.010
128 Africa NG Nigeria 210 470 780 2 065 0.010
129 Africa SL Sierra Leone 8 114 728 79 0.010
130 Asia TJ Tajikistan 9 719 405 90 0.009
131 Africa CD DR Congo 91 864 730 772 0.008
132 Africa BJ Benin 12 392 243 100 0.008
133 Africa NE Niger 24 946 242 192 0.008
134 Africa BF Burkina Faso 21 388 695 162 0.008
135 Asia KH Cambodia 16 915 901 126 0.007
136 Africa UG Uganda 46 962 440 346 0.007
137 Asia TH Thailand 69 949 602 421 0.006
138 Asia SG Singapore 5 889 582 31 0.005
139 Australia/Oceania NZ New Zealand 5 002 100 26 0.005
140 Africa ER Eritrea 3 588 197 12 0.003
141 Asia PS Palestine 5 202 003 7 0.001
142 Africa BI Burundi 12 190 433 6 0.001
143 Asia TW Taiwan 23 853 608 12 0.001
144 Asia VN Vietnam 98 085 243 35 0.000
145 Africa TZ Tanzania 61 174 557 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 7 365 397 0 0.000
150 Asia HK Hong Kong 7 548 850 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]

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"