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": 2022-06-14 11:23
(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 +0 (+2 905) +0 (+2)
CZ Czechia +459 (+61) +0 (+0)
DE Germany +0 (+38 664) +0 (+30)
HU Hungary +0 (+0) +0 (+0)
PL Poland +321 (+45) +9 (+0)
SK Slovakia, [gov], [okr]+206 (+28) +3 (+0)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Australia/Oceania 43 789 847 14.67% 12.00% 7.68%
2 Europe 756 513 313 7.07% 2.17% 2.07%
3 North America 597 658 595 1.47% 2.01% 1.52%
4 South America 440 920 772 1.47% 1.14% 0.99%
5 Asia 4 700 205 500 0.97% 0.35% 0.30%
6 Africa 1 402 366 450 0.07% 0.05% 0.03%

COVID-19, Relative Mortality rate from positive cases in Regions

N.RegionPopulationMortality last
120 days
Mortality last
30 days
New positive cases
last 30 days
1 Africa 1 402 366 450 0.99% (0.83)% (0.05)%
2 North America 597 658 595 1.01% 0.42% 2.01%
3 South America 440 920 772 0.77% 0.42% 1.14%
4 Europe 756 513 313 0.28% 0.41% 2.17%
5 Asia 4 700 205 500 0.23% 0.22% 0.35%
6 Australia/Oceania 43 789 847 0.09% 0.15% 12.00%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 440 920 772 1 304 837 2.959
2 Europe 756 513 313 1 849 043 2.444
3 North America 597 658 595 1 443 299 2.415
4 Australia/Oceania 43 789 847 13 387 0.306
5 Asia 4 700 205 500 1 429 806 0.304
6 Africa 1 402 366 450 255 421 0.182

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 TW Taiwan 23 900 579 12.48% 37.41% 33.19%
2 Australia/Oceania NZ New Zealand 5 002 100 24.42% 16.25% 14.45%
3 Europe PT Portugal 10 138 920 17.24% 25.87% 13.55%
4 Australia/Oceania AU Australia 26 075 142 19.44% 16.81% 10.00%
5 South America PR Puerto Rico 3 193 694 7.44% 14.06% 7.26%
6 Asia IL Israel 9 326 000 7.99% 3.77% 6.73%
7 Asia SG Singapore 5 939 801 14.72% 6.96% 6.49%
8 Europe DE Germany 84 304 782 16.95% 4.97% 6.21%
9 Europe FR France 65 554 307 11.98% 3.97% 5.45%
10 Europe GR Greece 10 324 103 12.95% 4.48% 5.00%
11 Europe AT Austria 9 106 310 22.71% 3.86% 4.68%
12 Europe IT Italy 60 289 007 9.22% 4.20% 4.24%
13 North America PA Panama 4 446 824 3.19% 7.21% 3.69%
14 South America CL Chile 19 435 247 6.03% 3.95% 3.25%
15 Africa BW Botswana 2 443 936 2.04% 0.69% 2.61%
16 North America US USA 334 776 423 2.13% 3.20% 2.51%
17 Asia KR South Korea 51 354 960 32.78% 3.56% 2.14%
18 Europe DK Denmark 5 831 858 14.03% 1.22% 2.01%
19 Europe SI Slovenia 2 079 493 8.66% 1.70% 1.64%
20 South America BR Brazil 215 497 163 1.82% 1.28% 1.56%
21 Asia QA Qatar 2 807 805 0.78% 0.95% 1.51%
22 Asia JP Japan 125 723 891 4.10% 2.30% 1.43%
23 Europe FI Finland 5 557 453 9.35% 2.70% 1.32%
24 Asia AE Arab Emirates 10 122 743 0.50% 0.66% 1.24%
25 Europe NL Netherlands 17 208 579 13.77% 0.82% 0.97%
26 Asia HK Hong Kong 7 615 239 15.72% 0.61% 0.95%
27 Europe BE Belgium 11 687 686 6.19% 1.54% 0.89%
28 Europe IE Ireland 5 045 028 6.40% 2.78% 0.77%
29 Europe HR Croatia 4 056 066 3.01% 0.86% 0.74%
30 Europe LT Lithuania 2 648 498 9.22% 0.55% 0.63%
31 Asia MY Malaysia 33 172 274 4.49% 0.63% 0.62%
32 Europe GB United Kingdom 68 579 336 5.79% 1.05% 0.62%
33 Asia KW Kuwait 4 393 366 0.84% 0.32% 0.59%
34 Asia MN Mongolia 3 380 931 1.17% 0.60% 0.53%
35 Europe NO Norway 5 503 661 7.24% 0.49% 0.49%
36 North America JM Jamaica 2 986 295 0.44% 1.01% 0.49%
37 North America CA Canada 38 385 559 1.82% 0.75% 0.45%
38 Asia TH Thailand 70 140 482 2.68% 0.65% 0.42%
39 Europe ES Spain 46 789 983 3.59% 2.42% 0.38%
40 Asia LB Lebanon 6 766 038 1.25% 0.19% 0.34%
41 Europe RS Serbia 8 668 966 2.07% 0.37% 0.34%
42 Asia SA Saudi Arabia 35 867 993 0.14% 0.23% 0.32%
43 Europe SK Slovakia 5 464 783 9.91% 0.32% 0.32%
44 Europe CZ Czechia 10 747 604 4.82% 0.28% 0.31%
45 Europe HU Hungary 9 612 671 2.35% 0.48% 0.29%
46 Africa NA Namibia 2 630 367 0.32% 0.76% 0.29%
47 Europe RU Russia 146 056 108 2.79% 0.33% 0.28%
48 North America DO Dominican R. 11 059 420 0.18% 0.32% 0.27%
49 Africa MA Morocco 37 761 188 0.06% 0.11% 0.26%
50 Africa ZA South Africa 60 762 580 0.55% 0.60% 0.26%
51 Europe MK North Macedonia 2 083 208 1.23% 0.37% 0.26%
52 North America GT Guatemala 18 559 873 0.72% 0.34% 0.26%
53 Europe BG Bulgaria 6 846 797 1.90% 0.33% 0.25%
54 Asia GE Georgia 3 974 283 5.14% 0.23% 0.22%
55 Europe AL Albania 2 871 689 0.30% 0.17% 0.20%
56 South America BO Bolivia 11 982 608 0.23% 0.19% 0.19%
57 Europe RO Romania 18 988 290 1.85% 0.21% 0.19%
58 South America EC Ecuador 18 163 935 0.51% 0.32% 0.18%
59 Europe CH Switzerland 8 777 680 12.53% 1.28% 0.18%
60 Europe SE Sweden 10 221 702 1.06% 0.23% 0.17%
61 South America PE Peru 33 864 868 0.45% 0.20% 0.14%
62 Asia VN Vietnam 99 041 436 8.30% 0.15% 0.11%
63 North America MX Mexico 131 566 572 0.17% 0.14% 0.11%
64 North America SV El Salvador 6 549 835 0.44% 0.12% 0.10%
65 Africa TN Tunisia 12 059 066 0.65% 0.08% 0.09%
66 Asia OM Oman 5 359 090 0.47% 0.03% 0.09%
67 Africa ZM Zambia 19 384 745 0.07% 0.05% 0.07%
68 Europe PL Poland 37 766 035 1.58% 0.07% 0.06%
69 Asia IN India 1 406 384 242 0.04% 0.03% 0.06%
70 Europe BA Bosnia and Herzegovina 3 241 159 0.44% 0.07% 0.06%
71 Asia IQ Iraq 41 977 141 0.13% 0.04% 0.05%
72 Africa LS Lesotho 2 175 268 0.06% 0.09% 0.04%
73 Africa ZW Zimbabwe 15 283 591 0.15% 0.13% 0.04%
74 Asia PH Philippines 112 416 830 0.05% 0.02% 0.03%
75 Africa GA Gabon 2 327 828 0.01% 0.02% 0.03%
76 Africa KE Kenya 56 073 862 0.01% 0.02% 0.02%
77 Asia ID Indonesia 279 147 249 0.45% 0.02% 0.02%
78 Africa ET Ethiopia 120 499 230 0.01% 0.02% 0.02%
79 Asia IR Iran 86 083 213 0.50% 0.03% 0.02%
80 Africa RW Rwanda 13 576 353 0.01% 0.01% 0.02%
81 Asia AF Afghanistan 40 632 673 0.03% 0.02% 0.02%
82 Africa MZ Mozambique 32 957 580 0.01% 0.01% 0.02%
83 North America HN Honduras 10 210 881 0.20% 0.05% 0.02%
84 Asia LA Laos 7 480 827 0.95% 0.04% 0.02%
85 North America CU Cuba 11 313 177 0.40% 0.04% 0.01%
86 Asia AZ Azerbaijan 10 316 866 0.53% 0.01% 0.01%
87 Africa SO Somalia 16 755 128 0.00% 0.00% 0.01%
88 Africa GW Guinea-Bissau 2 058 422 0.02% 0.02% 0.01%
89 South America VE Venezuela 28 279 333 0.07% 0.02% 0.01%
90 North America NI Nicaragua 6 777 797 0.01% 0.01% 0.01%
91 Africa CI Ivory Coast 27 648 050 0.00% 0.01% 0.01%
92 Asia KZ Kazakhstan 19 213 392 0.09% 0.01% 0.01%
93 Africa TG Togo 8 655 912 0.01% 0.01% 0.01%
94 Africa MR Mauritania 4 887 233 0.01% 0.03% 0.01%
95 Africa LY Libya 7 052 961 0.50% 0.01% 0.01%
96 Asia LK Sri Lanka 21 587 805 0.17% 0.01% 0.01%
97 Asia UZ Uzbekistan 34 412 290 0.02% 0.01% 0.01%
98 Africa BI Burundi 12 579 153 0.03% 0.03% 0.01%
99 Asia BD Bangladesh 167 879 547 0.03% 0.00% 0.01%
100 Australia/Oceania PG Papua New Guinea 9 276 518 0.06% 0.03% 0.01%
101 Africa MW Malawi 20 090 863 0.01% 0.00% 0.01%
102 Asia PK Pakistan 229 230 939 0.02% 0.00% 0.00%
103 Africa UG Uganda 48 548 800 0.00% 0.00% 0.00%
104 Asia NP Nepal 30 155 659 0.02% 0.00% 0.00%
105 Africa DZ Algeria 45 390 507 0.01% 0.00% 0.00%
106 Asia SY Syria 18 327 090 0.02% 0.00% 0.00%
107 Africa NG Nigeria 216 071 476 0.00% 0.00% 0.00%
108 Africa SS South Sudan 11 448 890 0.01% 0.00% 0.00%
109 Africa SN Senegal 17 601 640 0.00% 0.00% 0.00%
110 Asia MM Myanmar 55 118 982 0.12% 0.00% 0.00%
111 Africa SD Sudan 45 839 520 0.01% 0.00% 0.00%
112 Africa ML Mali 21 384 618 0.00% 0.00% 0.00%
113 Europe MD Moldova 4 015 739 0.84% 0.11% 0.00%
114 Africa BF Burkina Faso 22 017 453 0.00% 0.00% 0.00%
115 Asia YE Yemen 31 102 983 0.00% 0.00% 0.00%
116 South America PY Paraguay 7 302 885 0.42% 0.07% 0.00%
117 Africa LR Liberia 5 288 769 0.00% 0.00% 0.00%
118 South America UY Uruguay 3 497 135 4.83% 3.71% 0.00%
119 South America AR Argentina 46 002 135 1.14% 1.52% 0.00%
120 Europe UA Ukraine 43 223 130 1.13% 0.08% 0.00%
121 Africa ER Eritrea 3 641 853 0.00% 0.00% 0.00%
122 Africa AO Angola 34 853 471 0.00% 0.00% 0.00%
123 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
124 Africa TZ Tanzania 63 041 475 0.00% 0.01% 0.00%
125 Africa EG Egypt 106 086 832 0.06% 0.00% 0.00%
126 Asia KH Cambodia 17 168 838 0.08% 0.00% 0.00%
127 Asia TR Turkey 86 103 597 2.60% 0.10% 0.00%
128 Asia AM Armenia 2 974 010 0.56% 0.01% 0.00%
129 Asia KG Kyrgyzstan 6 733 469 0.01% 0.00% 0.00%
130 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
131 Asia TJ Tajikistan 9 954 095 0.00% 0.00% 0.00%
132 Asia JO Jordan 10 400 076 2.37% 0.05% 0.00%
133 Africa TD Chad 17 342 051 0.00% 0.00% 0.00%
134 North America CR Costa Rica 5 184 562 2.85% 2.99% 0.00%
135 South America CO Colombia 51 937 378 0.19% 0.11% 0.00%
136 Africa NE Niger 25 909 734 0.00% 0.00% 0.00%
137 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
138 Africa CM Cameroon 27 830 381 0.00% 0.00% 0.00%
139 Africa SL Sierra Leone 8 292 350 0.00% 0.00% 0.00%
140 Africa CG Congo 5 782 115 0.01% 0.01% 0.00%
141 Africa CF Central African R. 4 993 027 0.00% 0.00% 0.00%
142 North America HT Haiti 11 672 793 0.01% 0.01% 0.00%
143 Europe BY Belarus 9 443 281 1.69% 0.00% 0.00%
144 Africa CD DR Congo 94 853 927 0.00% 0.01% 0.00%
145 Africa MG Madagascar 29 074 832 0.01% 0.00% 0.00%
146 Asia PS Palestine 5 331 948 0.00% 0.00% 0.00%
147 Africa BJ Benin 12 740 457 0.00% 0.01% 0.00%
148 Africa GN Guinea 13 825 236 0.00% 0.00% 0.00%
149 Africa GM Gambia 2 548 640 0.00% 0.00% 0.00%
150 Africa GH Ghana 32 333 890 0.01% 0.01% 0.00%

COVID-19, Relative Mortality rate from positive cases in Countries

Filtered where Population more then 2 million, [All Countries] | Compare with [DEATHS]! and with [FATALITY RATE]
N.RegionCDCountryPopulationMortality last
120 days
Mortality last
30 days
New positive cases
last 30 days
1 Africa EG Egypt 106 086 832 1.86% (27.57)% (0.00)%
2 Africa SD Sudan 45 839 520 36.05% (5.00)% (0.00)%
3 Africa TZ Tanzania 63 041 475 2.84% (3.49)% (0.01)%
4 Africa MW Malawi 20 090 863 3.98% (3.48)% (0.00)%
5 North America NI Nicaragua 6 777 797 2.22% (3.45)% (0.01)%
6 Africa TN Tunisia 12 059 066 1.54% (3.38)% (0.08)%
7 Asia AZ Azerbaijan 10 316 866 0.68% (2.99)% (0.01)%
8 North America GT Guatemala 18 559 873 1.05% 2.89% 0.34%
9 Europe MD Moldova 4 015 739 1.17% 2.58% 0.11%
10 Asia LK Sri Lanka 21 587 805 1.57% (2.28)% (0.01)%
11 Europe BG Bulgaria 6 846 797 1.64% 2.27% 0.33%
12 Asia ID Indonesia 279 147 249 0.74% (2.23)% (0.02)%
13 Africa BW Botswana 2 443 936 0.20% 2.22% 0.69%
14 Europe NO Norway 5 503 661 0.29% 2.15% 0.49%
15 Europe BA Bosnia and Herzegovina 3 241 159 3.53% (2.11)% (0.07)%
16 Europe PL Poland 37 766 035 1.00% (2.00)% (0.07)%
17 South America PY Paraguay 7 302 885 2.16% 1.94% 0.07%
18 Europe RU Russia 146 056 108 0.73% 1.89% 0.33%
19 South America PE Peru 33 864 868 2.20% 1.77% 0.20%
20 Asia AM Armenia 2 974 010 1.39% 1.74% 0.01%
21 Asia IR Iran 86 083 213 1.17% 1.68% 0.03%
22 Africa ML Mali 21 384 618 2.09% 1.63% 0.00%
23 Asia LB Lebanon 6 766 038 0.47% 1.62% 0.19%
24 Europe SE Sweden 10 221 702 1.12% 1.60% 0.23%
25 Europe SK Slovakia 5 464 783 0.30% 1.47% 0.32%
26 Europe HU Hungary 9 612 671 1.39% 1.37% 0.48%
27 Asia AF Afghanistan 40 632 673 1.48% 1.30% 0.02%
28 Europe UA Ukraine 43 223 130 0.79% 1.29% 0.08%
29 Africa MG Madagascar 29 074 832 2.00% 1.24% 0.00%
30 North America CA Canada 38 385 559 0.83% 1.21% 0.75%
31 North America JM Jamaica 2 986 295 2.62% 1.01% 1.01%
32 Africa UG Uganda 48 548 800 1.03% 0.94% 0.00%
33 Europe RO Romania 18 988 290 0.81% 0.91% 0.21%
34 Africa MZ Mozambique 32 957 580 1.03% 0.89% 0.01%
35 Europe MK North Macedonia 2 083 208 1.53% 0.88% 0.37%
36 Europe HR Croatia 4 056 066 1.00% 0.88% 0.86%
37 Australia/Oceania PG Papua New Guinea 9 276 518 0.69% 0.86% 0.03%
38 South America VE Venezuela 28 279 333 0.63% 0.86% 0.02%
39 Europe DK Denmark 5 831 858 0.20% 0.81% 1.22%
40 Africa SN Senegal 17 601 640 1.07% 0.80% 0.00%
41 Asia IN India 1 406 384 242 1.73% 0.68% 0.03%
42 Europe GB United Kingdom 68 579 336 0.42% 0.66% 1.05%
43 Asia GE Georgia 3 974 283 0.37% 0.64% 0.23%
44 Africa ZW Zimbabwe 15 283 591 0.61% 0.64% 0.13%
45 Europe LT Lithuania 2 648 498 0.33% 0.62% 0.55%
46 Asia TH Thailand 70 140 482 0.40% 0.61% 0.65%
47 Europe RS Serbia 8 668 966 0.67% 0.60% 0.37%
48 Asia KZ Kazakhstan 19 213 392 0.67% 0.57% 0.01%
49 Africa ZA South Africa 60 762 580 1.31% 0.56% 0.60%
50 South America BO Bolivia 11 982 608 1.69% 0.49% 0.19%
51 South America BR Brazil 215 497 163 0.63% 0.47% 1.28%
52 Asia BD Bangladesh 167 879 547 0.34% 0.45% 0.00%
53 Europe SI Slovenia 2 079 493 0.45% 0.45% 1.70%
54 Europe GR Greece 10 324 103 0.37% 0.43% 4.48%
55 Europe CZ Czechia 10 747 604 0.33% 0.41% 0.28%
56 North America HN Honduras 10 210 881 1.11% 0.38% 0.05%
57 Asia SA Saudi Arabia 35 867 993 0.32% 0.35% 0.23%
58 Asia HK Hong Kong 7 615 239 0.76% 0.32% 0.61%
59 South America EC Ecuador 18 163 935 0.52% 0.32% 0.32%
60 Europe ES Spain 46 789 983 0.37% 0.32% 2.42%
61 North America SV El Salvador 6 549 835 0.51% 0.30% 0.12%
62 Europe IT Italy 60 289 007 0.28% 0.30% 4.20%
63 South America CO Colombia 51 937 378 1.88% 0.30% 0.11%
64 North America US USA 334 776 423 1.04% 0.30% 3.20%
65 Asia OM Oman 5 359 090 0.15% 0.29% 0.03%
66 Africa CD DR Congo 94 853 927 0.69% 0.28% 0.01%
67 Africa ZM Zambia 19 384 745 0.35% 0.28% 0.05%
68 Europe BE Belgium 11 687 686 0.26% 0.27% 1.54%
69 Africa NG Nigeria 216 071 476 0.16% 0.26% 0.00%
70 Asia TR Turkey 86 103 597 0.30% 0.25% 0.10%
71 North America MX Mexico 131 566 572 2.02% 0.24% 0.14%
72 Africa NA Namibia 2 630 367 0.57% 0.22% 0.76%
73 Europe FR France 65 554 307 0.16% 0.22% 3.97%
74 Asia IQ Iraq 41 977 141 0.64% 0.21% 0.04%
75 Africa MA Morocco 37 761 188 1.30% 0.21% 0.11%
76 Africa LS Lesotho 2 175 268 0.23% 0.20% 0.09%
77 Asia LA Laos 7 480 827 0.22% 0.19% 0.04%
78 South America CL Chile 19 435 247 1.26% 0.19% 3.95%
79 Europe FI Finland 5 557 453 0.39% 0.19% 2.70%
80 Asia PK Pakistan 229 230 939 0.86% 0.18% 0.00%
81 Asia MY Malaysia 33 172 274 0.22% 0.17% 0.63%
82 Asia PH Philippines 112 416 830 6.73% 0.17% 0.02%
83 North America CR Costa Rica 5 184 562 0.41% 0.17% 2.99%
84 Australia/Oceania NZ New Zealand 5 002 100 0.10% 0.17% 16.25%
85 Europe IE Ireland 5 045 028 0.25% 0.16% 2.78%
86 Asia JO Jordan 10 400 076 0.15% 0.15% 0.05%
87 Africa ET Ethiopia 120 499 230 1.06% 0.15% 0.02%
88 Asia TW Taiwan 23 900 579 0.14% 0.15% 37.41%
89 South America UY Uruguay 3 497 135 0.24% 0.14% 3.71%
90 South America PR Puerto Rico 3 193 694 0.18% 0.14% 14.06%
91 Europe PT Portugal 10 138 920 0.16% 0.13% 25.87%
92 South America AR Argentina 46 002 135 0.25% 0.13% 1.52%
93 Africa KE Kenya 56 073 862 0.57% 0.11% 0.02%
94 Europe AT Austria 9 106 310 0.11% 0.11% 3.86%
95 Europe NL Netherlands 17 208 579 0.03% 0.11% 0.82%
96 Asia KR South Korea 51 354 960 0.10% 0.11% 3.56%
97 North America PA Panama 4 446 824 0.24% 0.10% 7.21%
98 Australia/Oceania AU Australia 26 075 142 0.09% 0.10% 16.81%
99 Asia JP Japan 125 723 891 0.19% 0.10% 2.30%
100 Asia IL Israel 9 326 000 0.12% 0.08% 3.77%
101 Europe CH Switzerland 8 777 680 0.06% 0.05% 1.28%
102 Asia MN Mongolia 3 380 931 0.06% 0.04% 0.60%
103 Europe DE Germany 84 304 782 0.10% 0.04% 4.97%
104 North America DO Dominican R. 11 059 420 0.14% 0.04% 0.32%
105 Asia VN Vietnam 99 041 436 0.05% 0.03% 0.15%
106 Asia SG Singapore 5 939 801 0.05% 0.03% 6.96%
107 Asia AE Arab Emirates 10 122 743 0.04% 0.03% 0.66%
108 Asia QA Qatar 2 807 805 0.09% 0.00% 0.95%
109 Asia KW Kuwait 4 393 366 0.06% 0.00% 0.32%
110 Europe AL Albania 2 871 689 0.70% 0.00% 0.17%
111 North America CU Cuba 11 313 177 0.11% 0.00% 0.04%
112 Africa MR Mauritania 4 887 233 1.34% 0.00% 0.03%
113 Africa BI Burundi 12 579 153 0.00% 0.00% 0.03%
114 Africa GA Gabon 2 327 828 0.38% 0.00% 0.02%
115 Africa GW Guinea-Bissau 2 058 422 1.35% 0.00% 0.02%
116 Africa RW Rwanda 13 576 353 0.82% 0.00% 0.01%
117 Africa BJ Benin 12 740 457 0.00% 0.00% 0.01%
118 Africa LY Libya 7 052 961 0.56% 0.00% 0.01%
119 North America HT Haiti 11 672 793 2.33% 0.00% 0.01%
120 Africa TG Togo 8 655 912 0.37% 0.00% 0.01%
121 Africa CI Ivory Coast 27 648 050 0.72% 0.00% 0.01%
122 Africa GH Ghana 32 333 890 0.18% 0.00% 0.01%
123 Asia UZ Uzbekistan 34 412 290 0.35% 0.00% 0.01%
124 Africa CG Congo 5 782 115 2.98% 0.00% 0.01%
125 Africa GN Guinea 13 825 236 1.10% 0.00% 0.00%
126 Africa SO Somalia 16 755 128 4.22% 0.00% 0.00%
127 Asia NP Nepal 30 155 659 0.47% 0.00% 0.00%
128 Africa SS South Sudan 11 448 890 0.13% 0.00% 0.00%
129 Africa AO Angola 34 853 471 0.14% 0.00% 0.00%
130 Asia MM Myanmar 55 118 982 0.16% 0.00% 0.00%
131 Africa ER Eritrea 3 641 853 0.00% 0.00% 0.00%
132 Africa DZ Algeria 45 390 507 1.84% 0.00% 0.00%
133 Asia SY Syria 18 327 090 3.04% 0.00% 0.00%
134 Africa LR Liberia 5 288 769 3.57% 0.00% 0.00%
135 Africa NE Niger 25 909 734 2.01% 0.00% 0.00%
136 Africa CF Central African R. 4 993 027 0.00% 0.00% 0.00%
137 Africa GM Gambia 2 548 640 0.00% 0.00% 0.00%
138 Asia YE Yemen 31 102 983 8.20% 0.00% 0.00%
139 Africa TD Chad 17 342 051 1.47% 0.00% 0.00%
140 Africa CM Cameroon 27 830 381 0.94% 0.00% 0.00%
141 Europe BY Belarus 9 443 281 0.35% 0.00% 0.00%
142 Asia KH Cambodia 17 168 838 0.28% 0.00% 0.00%
143 Africa BF Burkina Faso 22 017 453 4.17% 0.00% 0.00%
144 Asia KG Kyrgyzstan 6 733 469 4.11% 0.00% 0.00%
145 Africa SL Sierra Leone 8 292 350 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 Asia TJ Tajikistan 9 954 095 0.00% 0.00% 0.00%
149 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
150 Asia PS Palestine 5 331 948 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 33 864 868 213 303 6.299
2 Europe BG Bulgaria 6 846 797 37 204 5.434
3 Europe BA Bosnia and Herzegovina 3 241 159 15 793 4.873
4 Europe HU Hungary 9 612 671 46 571 4.845
5 Europe MK North Macedonia 2 083 208 9 316 4.472
6 Asia GE Georgia 3 974 283 16 835 4.236
7 Europe HR Croatia 4 056 066 16 019 3.949
8 Europe SI Slovenia 2 079 493 7 805 3.753
9 Europe CZ Czechia 10 747 604 40 302 3.750
10 Europe SK Slovakia 5 464 783 20 119 3.682
11 Europe RO Romania 18 988 290 65 714 3.461
12 Europe LT Lithuania 2 648 498 9 155 3.457
13 South America BR Brazil 215 497 163 667 700 3.098
14 Europe PL Poland 37 766 035 116 380 3.082
15 North America US USA 334 776 423 1 000 967 2.990
16 South America CL Chile 19 435 247 58 050 2.987
17 Europe GR Greece 10 324 103 30 020 2.908
18 Asia AM Armenia 2 974 010 8 625 2.900
19 Europe MD Moldova 4 015 739 11 554 2.877
20 South America AR Argentina 46 002 135 128 973 2.804
21 Europe IT Italy 60 289 007 167 432 2.777
22 Europe BE Belgium 11 687 686 31 816 2.722
23 South America CO Colombia 51 937 378 139 867 2.693
24 Europe GB United Kingdom 68 579 336 179 102 2.612
25 Europe RU Russia 146 056 108 380 137 2.603
26 South America PY Paraguay 7 302 885 18 911 2.590
27 Europe UA Ukraine 43 223 130 108 605 2.513
28 North America MX Mexico 131 566 572 325 066 2.471
29 Africa TN Tunisia 12 059 066 28 648 2.376
30 Europe PT Portugal 10 138 920 23 531 2.321
31 Europe ES Spain 46 789 983 107 108 2.289
32 Europe FR France 65 554 307 145 520 2.220
33 Europe AT Austria 9 106 310 19 969 2.193
34 South America UY Uruguay 3 497 135 7 262 2.077
35 South America EC Ecuador 18 163 935 35 649 1.963
36 North America PA Panama 4 446 824 8 292 1.865
37 Europe SE Sweden 10 221 702 19 049 1.864
38 Europe RS Serbia 8 668 966 16 101 1.857
39 South America BO Bolivia 11 982 608 21 950 1.832
40 Africa ZA South Africa 60 762 580 101 502 1.671
41 Europe DE Germany 84 304 782 139 837 1.659
42 North America CR Costa Rica 5 184 562 8 525 1.644
43 Asia IR Iran 86 083 213 141 352 1.642
44 Asia LB Lebanon 6 766 038 10 446 1.544
45 Africa NA Namibia 2 630 367 4 042 1.537
46 Europe CH Switzerland 8 777 680 13 267 1.511
47 Europe IE Ireland 5 045 028 7 416 1.470
48 South America PR Puerto Rico 3 193 694 4 427 1.386
49 Asia JO Jordan 10 400 076 14 068 1.353
50 Europe NL Netherlands 17 208 579 22 332 1.298
51 Asia HK Hong Kong 7 615 239 9 390 1.233
52 Europe AL Albania 2 871 689 3 497 1.218
53 Asia IL Israel 9 326 000 10 882 1.167
54 Asia TR Turkey 86 103 597 98 969 1.149
55 Africa BW Botswana 2 443 936 2 701 1.105
56 Europe DK Denmark 5 831 858 6 414 1.100
57 North America CA Canada 38 385 559 41 356 1.077
58 Asia MY Malaysia 33 172 274 35 716 1.077
59 North America HN Honduras 10 210 881 10 902 1.068
60 North America JM Jamaica 2 986 295 3 080 1.031
61 Asia KZ Kazakhstan 19 213 392 19 017 0.990
62 North America GT Guatemala 18 559 873 18 250 0.983
63 Asia AZ Azerbaijan 10 316 866 9 715 0.942
64 Africa LY Libya 7 052 961 6 430 0.912
65 Europe FI Finland 5 557 453 4 714 0.848
66 Asia OM Oman 5 359 090 4 260 0.795
67 Asia LK Sri Lanka 21 587 805 16 519 0.765
68 North America CU Cuba 11 313 177 8 529 0.754
69 Europe BY Belarus 9 443 281 6 978 0.739
70 North America SV El Salvador 6 549 835 4 134 0.631
71 Asia MN Mongolia 3 380 931 2 115 0.626
72 Asia IQ Iraq 41 977 141 25 223 0.601
73 Europe NO Norway 5 503 661 3 210 0.583
74 Asia KW Kuwait 4 393 366 2 555 0.582
75 Asia ID Indonesia 279 147 249 156 652 0.561
76 Asia PH Philippines 112 416 830 60 461 0.538
77 Asia KR South Korea 51 354 960 24 390 0.475
78 Asia KG Kyrgyzstan 6 733 469 2 991 0.444
79 Asia VN Vietnam 99 041 436 43 083 0.435
80 Asia TH Thailand 70 140 482 30 368 0.433
81 Africa MA Morocco 37 761 188 16 082 0.426
82 Asia NP Nepal 30 155 659 11 952 0.396
83 North America DO Dominican R. 11 059 420 4 379 0.396
84 Asia IN India 1 406 384 242 524 777 0.373
85 Africa ZW Zimbabwe 15 283 591 5 515 0.361
86 Asia MM Myanmar 55 118 982 19 434 0.353
87 Australia/Oceania AU Australia 26 075 142 8 988 0.345
88 Africa LS Lesotho 2 175 268 699 0.321
89 Australia/Oceania NZ New Zealand 5 002 100 1 286 0.257
90 Asia SA Saudi Arabia 35 867 993 9 175 0.256
91 Asia JP Japan 125 723 891 30 910 0.246
92 Asia QA Qatar 2 807 805 677 0.241
93 Asia SG Singapore 5 939 801 1 398 0.235
94 Africa EG Egypt 106 086 832 24 720 0.233
95 Asia AE Arab Emirates 10 122 743 2 305 0.228
96 Africa ZM Zambia 19 384 745 3 989 0.206
97 South America VE Venezuela 28 279 333 5 722 0.202
98 Africa MR Mauritania 4 887 233 982 0.201
99 Asia AF Afghanistan 40 632 673 7 710 0.190
100 Asia TW Taiwan 23 900 579 4 403 0.184
101 Asia KH Cambodia 17 168 838 3 056 0.178
102 Asia BD Bangladesh 167 879 547 29 131 0.173
103 Asia SY Syria 18 327 090 3 150 0.172
104 Africa DZ Algeria 45 390 507 6 875 0.151
105 Africa GM Gambia 2 548 640 365 0.143
106 Asia PK Pakistan 229 230 939 30 381 0.133
107 Africa MW Malawi 20 090 863 2 642 0.132
108 Africa GA Gabon 2 327 828 304 0.131
109 Africa SN Senegal 17 601 640 1 967 0.112
110 Africa SD Sudan 45 839 520 4 950 0.108
111 Africa RW Rwanda 13 576 353 1 459 0.107
112 Asia LA Laos 7 480 827 757 0.101
113 Africa KE Kenya 56 073 862 5 651 0.101
114 Africa GW Guinea-Bissau 2 058 422 171 0.083
115 Africa SO Somalia 16 755 128 1 361 0.081
116 Africa UG Uganda 48 548 800 3 603 0.074
117 North America HT Haiti 11 672 793 835 0.071
118 Australia/Oceania PG Papua New Guinea 9 276 518 658 0.071
119 Africa CM Cameroon 27 830 381 1 930 0.069
120 Asia YE Yemen 31 102 983 2 149 0.069
121 Africa MZ Mozambique 32 957 580 2 206 0.067
122 Africa CG Congo 5 782 115 385 0.067
123 Africa ET Ethiopia 120 499 230 7 517 0.062
124 Africa LR Liberia 5 288 769 294 0.056
125 Africa AO Angola 34 853 471 1 900 0.054
126 Africa MG Madagascar 29 074 832 1 396 0.048
127 Asia UZ Uzbekistan 34 412 290 1 637 0.048
128 Africa GH Ghana 32 333 890 1 445 0.045
129 North America NI Nicaragua 6 777 797 240 0.035
130 Africa ML Mali 21 384 618 736 0.034
131 Africa GN Guinea 13 825 236 442 0.032
132 Africa TG Togo 8 655 912 273 0.032
133 Africa CI Ivory Coast 27 648 050 799 0.029
134 Africa ER Eritrea 3 641 853 103 0.028
135 Africa CF Central African R. 4 993 027 113 0.023
136 Africa BF Burkina Faso 22 017 453 384 0.017
137 Africa SL Sierra Leone 8 292 350 125 0.015
138 Africa NG Nigeria 216 071 476 3 144 0.015
139 Africa CD DR Congo 94 853 927 1 345 0.014
140 Africa TZ Tanzania 63 041 475 840 0.013
141 Africa BJ Benin 12 740 457 163 0.013
142 Africa SS South Sudan 11 448 890 138 0.012
143 Africa NE Niger 25 909 734 310 0.012
144 Africa TD Chad 17 342 051 193 0.011
145 Africa BI Burundi 12 579 153 15 0.001
146 Asia CN China 1 439 323 776 0 0.000
147 Asia KP North Korea 25 660 000 0 0.000
148 Asia TJ Tajikistan 9 954 095 0 0.000
149 Europe TM Turkmenistan 6 118 000 0 0.000
150 Asia PS Palestine 5 331 948 0 0.000

Elhalálozási adatok hozzávetőleges értékei 2018/2019:
 *  Abortusz: 56 millió, Szív és érrendszer: 17,9 millió, Rákbetegség: 9,6 millió.

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

(2021-02-02 ...)

* Azelastine: [1], [2] , [*], [3], nálunk Szlovákiában, mint Allergodil, orr spray ismert. (5ml recept nélkül vásárolható)
* Cistus creticus (Cystus pandalis): [4], [5] nálunk, mint ViroStop ismert, torokspray (de van orrspay és tabletta is) Cistus a Vironal
* Artemisinin + Zinc: [6] egynyáriüröm kivonat, tabletta (Nagyon jó többfajta rákbetegségre is, de konzultálni kell az orvossal, ha más gyógyszereket is szedünk).
* Inosine pranobex: [9]
* Melatonin [10] , Quercetin (Kvercetín) [8] , Fluvoxamine [11] , NAC, N-acetylcysteín
* Ivermectin: [7] , [Ivermectin Triple Therapy Protocol for COVID-19 to Australian GP] , [Prof. Marik] , [SK, konečne] _
Ivermectin statisztikai adatok: [Epidemiologic Analyses on COVID-19 and Ivermectin] , [Dr. Thomas Borody, Australia] , [CZ]
[FLCCC, Ivermectin video], [A sok tesztelés nem segít], [FLCCC, Ivermectin] , [SK] , [Ivermectin, Vitamin D, Melatonin] , [Tanulmányok] , [ivmmeta.com]

Allergodil ViroStop D3 Artemisinin Artemisinin Zinc Melatonin Quercetin Ivermectin Inosine Galmektin

Az aktív prevenció abban van, hogy az Allergodil és a ViroStop meggátolja a vírus elszaporodását az orr és a száj nyálkahártyán. Mindezt "in-vitro" bizonyították. Az Allergodilt elegendő naponta egyszer (reggel) használni prevenciónak (de lehet többször is). A ViroStop-ot érdemes naponta többször is használni. A többi gyógyszer inkább csak akkor kell, ha a vírus mégis valahogyan nagyobb mennyiségben bejutna a szervezetünkbe, akkor az már fel legyen rá készülve. (Természetesen itt nem említek meg olyan alapvető dolgokat, mint a C vitamín, Aspirin, B1 stb.) Sajnos, relatíve kevés tanulmány foglalkozik az aktív megelőzéssel. Statistic Általában bizonyított COVID pozitív betegeken kísérleteznek, viszont a legjobb, ha el sem kapjuk ezt a betegséget, tehát meggátoljuk, hogy bejusson a szervezetünkbe. Az Ivermectint szintén használhatjuk preventíve, nagyon sok orvos már javasolja főleg időseknek. Tatiana Betáková (Szlovák Tudományos Akadémia): "Kérdés az, hogy a vírus továbbra is fog szaporodni a mi nyálkahártyankon, ha be leszünk oltva? Ezt még nem tudjuk, azért az oltás után is javasolva lesz a maszk viselése, hogy másokat ne fertőzzünk meg."
(This information has been compiled based on thousands of scientific studies. Anyone can check this here: [Google Scholar], [FLCCC Alliance] , [Protocol PDF] , [Hatásos gyógymód])
[Az oltás megoldás lesz?], [Mi történt Izraelben? PDF] ([PDF translate]) és [Israel CZ] , [Angliai jelentés] , [USA adatok] , [Furcsa eredmények] , [Agyi karosodások a covid után] , [Németországi adatok]
Mi mindent csináltak rosszul a COVID-19 kapcsán, mert nálunk is az történt, ami az USA-ban: [Link 1. video] vagy [Link 2. video] , [Link 3. cikk] , [DOC. MUDR. TÖRÖK az Ivermectinről] , [Ivermectin tapasztalatok] , [EU adatok a gyógyszerek mellékhatásairól, köztük a COVID vakcinák is]

Egy tudós (specialista a vakcinákra):
[Figyelmezteti a világot a lehetséges következményekre] , [VACCINATION WARNING]
HU: [G. V. Bossche figyelmeztésének rövid kivonata]
SK: [Varovanie od G. V. Bossche v skratke]
[Dr. Tenpenny, mRNA]
Latest SPR Covid Updates

Az Európa Tanács (ET) a 2361 (2021) állásfoglalásban úgy határozott, hogy betiltja a tagállamok oltási kötelezettségeinek előírását.
EU-tagállamok kötelesek:
7.3.1 annak biztosítása, hogy az állampolgárok tájékoztatást kapjanak arról, hogy az oltás NEM kötelező, és hogy senkit sem politikai, társadalmi vagy egyéb módon nem kényszerítenek oltásra, hacsak nem akarják
7.3.2 annak biztosítása, hogy senkit ne érjen hátrányos megkülönböztetés, mert esetleges egészségügyi kockázatok miatt nem oltották be, vagy nem oltották be
7.1.5 független kompenzációs programok létrehozása az oltásokkal szemben az aránytalan és az oltásokkal okozott károk megtérítése érdekében

STOP VACCINATION - Why?

DR. ZELENKO
Prof. RNDr. Jaroslav Turánek, CSc. DSc.
Dr. Robert Malone, inventor of mRNA technology
Prof. MUDr. Jiří Beran, CSc.


SK: [Pravidelné a celoplošné testovanie?]
2021-02-17
Jeden z najrenomovanejších lekárskych časopisov na svete „The Lancet“ publikuje štúdiu, ktorá ukazuje, že PCR test je na detekciu SARS-CoV-2 nepoužiteľný: I-MASK

"Väčšina ľudí infikovaných SARS-CoV-2 je nákazlivá po dobu 4–8 dní. Všeobecne sa nezistí, že by vzorky obsahovali kultúrne pozitívny (potenciálne nákazlivý) vírus po 9. dni po objavení sa symptómov, pričom väčšina prenosu nastala pred 5. dňom."

Uvedené platí aj pre antigenové aj pre protilátkové testy. Pred nástupom príznakov ochorenia 5 až 8 dní ešte nič nezistia, ale práve v tomto období pacient najviac infikuje svoje okolie. Na základe týchto informácií je úplne zbytočné robiť pravidelné plošné testovanie, ako je to na Slovenku. Zvyšuje sa iba nákaza. Potvrdenia vydané na jeden týždeň (covid negative) sú nanič.
Niektorí ľudia už museli absolvovať 48 testov, aby mohli chodiť do roboty. Neviem ako to "naši odborníci" odôvodňujú, ale je to proti zdravému rozumu a vyhadzovaniu peňazí. Nikde vo svete to takto nerobia, iba na Slovensku. (Asi naši "odborníci" majú patent na rozum.) [Dr. Horáková vrátila štátné vyznamenanie] , [Ivermectin na Slovensku video] , [News]
Čo všetko robili zle "odborníci", lebo to isté, čo sa stalo v USA, stalo sa aj u nás: [Link 1.] alebo [Link 2.] , [Link 3. text]

Je dôležité vedieť, že pacient môže žiadať od lekára liečenie pomocou Ivermectinu (po celom Slovensku aj v nemocniciach) v prípade COVID-19.

Kiszámolt értékek

New Cases, az új esteket százalékos értékei:
case120 = 100 * ws_case_120_days / ws_population
case30 = (120/30) * 100 * ws_case_30_days / ws_population
case7 = (120/7) * 100 * ws_case_7_days / ws_population

Relative Mortality számolása:
mortality120 = 100 * ws_death_120_days / (ws_case_127_days - ws_case_7_days)
mortality30 = 100 * ws_death_30_days / (ws_case_37_days - ws_case_7_days)

Ahol, ws_case_7_days (30,37,120,127), mindig az utolsó leadott jelentéstől kiszámított esetek száma, tehát
- ha Hungary utolsó jelentése 2021-02-10 volt, akkor onnan van számolva neki a 7,30,37,120,127 napos új esetek száma
- ha Szlovákia utolsó jelentése 2021-02-11 volt , akkor onnan van számolva neki a 7,30,37,120,127 napos új esetek száma
Ez azt jelenti, hogy lehet egy napos eltérés Szlovákia es Hungary kiszámolt értékei közt, de ezzel nem igen lehet semmit kezdeni.
Tekintettel arra, hogy a mortalitást 30 napra számolom, az ebből következő eltéres mértéke igen kicsi.
Itt sajnos probléma van USA és JAPAN esetében is, mivel más időzónában vannak, és mindenki máskor adja le a jelentést.
A WHO ezért 1-2 napos késéssel közli az adatokat. Ezen a weboldalon a WorldoMeter-től is aktualizálom az adatokat, melyek néhány ország esetében csak 1 napos vagy fél napos késéssel jönnek.
A kiszámolt értekek szempontjábol viszont ennek nincs nagy jelentősége, mert az eltérés igen kicsi a 30 napos átlagokat illetően.

Nagyon érdekes, ha ezeket az adatokat összehasonlítjuk "Our World in Data" által kiszámolt elhalálozási adatokkal.
Ott ugyanis az összes átlagon felüli elhalálozást veszik, nem csak a COVID-19 betegekét, amiből következtetni lehet a valódi elhalálozás mértékére, ami a COVID-19 kapcsán történik (függetlenül attól, hogy mit mondanak a COVID-19 kimutatások az adott országban). Az eltérő értékeknek több oka is lehet, például kevesebb ember kap színvonalas orvosi ellátást, vagy egyéb okok (mint például a kimutatások pontalansága) stb. Az is nagyon érdekes, ha összehasonlítjuk Izrael mortalitási adatatit más országokéval pl. Szlovákiával, akkor látható, hogy Izreaelben sokkal jobb eredményeket érnek el. Ez a vakcinázást megelőzően is igaz.

OurWorldInData: "https://github.com/owid/covid-19-data/tree/master/public/data", Slovakia: "https://github.com/Institut-Zdravotnych-Analyz/covid19-data"