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": 2021-07-31 22:39
(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 +538 (+514) +0 (+0)
CZ Czechia +140 (+207) +0 (+0)
DE Germany +1 816 (+2 598) +10 (+30)
HU Hungary +0 (+64) +0 (+1)
PL Poland +153 (+153) +2 (+2)
SK Slovakia, [gov], [okr]+66 (+44) +4 (+0)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 South America 437 834 662 3.22% 2.23% 1.45%
2 Europe 756 124 270 1.49% 1.65% 1.26%
3 North America 593 650 393 1.05% 1.18% 1.22%
4 Asia 4 670 998 850 0.70% 0.47% 0.44%
5 Australia/Oceania 43 338 238 0.10% 0.24% 0.23%
6 Africa 1 374 400 488 0.17% 0.31% 0.23%

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 437 834 662 3.01% 3.87% 2.23%
2 Africa 1 374 400 488 2.39% 2.70% 0.31%
3 Asia 4 670 998 850 1.40% 2.18% 0.47%
4 North America 593 650 393 1.75% 1.36% 1.18%
5 Australia/Oceania 43 338 238 0.94% 1.14% 0.24%
6 Europe 756 124 270 1.69% 1.04% 1.65%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 437 834 662 1 084 048 2.476
2 North America 593 650 393 915 143 1.542
3 Europe 756 124 270 1 131 121 1.496
4 Asia 4 670 998 850 880 746 0.189
5 Africa 1 374 400 488 167 611 0.122
6 Australia/Oceania 43 338 238 1 648 0.038

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 Africa BW Botswana 2 402 605 2.65% 5.34% 7.29%
2 North America CU Cuba 11 319 161 2.49% 5.90% 6.29%
3 Asia GE Georgia 3 980 909 3.30% 4.72% 5.74%
4 Asia MY Malaysia 32 811 983 2.18% 3.78% 4.25%
5 Asia KZ Kazakhstan 19 018 299 1.65% 2.77% 3.67%
6 Asia MN Mongolia 3 335 025 4.54% 5.39% 3.39%
7 Europe ES Spain 46 774 302 2.32% 4.90% 3.36%
8 Europe GB United Kingdom 68 270 129 2.09% 5.69% 3.36%
9 Africa LY Libya 6 971 764 1.19% 2.85% 3.35%
10 Asia IR Iran 85 149 163 2.21% 2.69% 2.67%
11 Africa TN Tunisia 11 951 687 2.74% 5.43% 2.65%
12 Asia IL Israel 9 326 000 0.42% 1.36% 2.61%
13 Europe FR France 65 429 176 2.18% 1.59% 2.33%
14 South America AR Argentina 45 642 150 5.53% 3.72% 2.26%
15 Europe IE Ireland 4 997 127 1.22% 1.97% 2.16%
16 Europe GR Greece 10 368 119 2.10% 2.41% 2.15%
17 Asia IQ Iraq 41 191 025 1.77% 2.34% 2.14%
18 Europe PT Portugal 10 164 639 1.35% 3.15% 2.11%
19 Europe NL Netherlands 17 175 733 3.35% 3.95% 2.07%
20 Asia TH Thailand 69 988 732 0.76% 1.70% 1.97%
21 Asia OM Oman 5 245 888 2.63% 2.51% 1.95%
22 Africa NA Namibia 2 590 333 2.83% 4.30% 1.84%
23 South America BR Brazil 214 186 368 3.27% 2.31% 1.80%
24 North America CR Costa Rica 5 144 185 3.60% 2.85% 1.78%
25 South America CO Colombia 51 466 439 4.55% 4.14% 1.77%
26 Asia KW Kuwait 4 338 465 3.73% 3.56% 1.77%
27 North America PA Panama 4 387 767 1.74% 2.62% 1.76%
28 Asia TR Turkey 85 315 528 2.70% 1.10% 1.72%
29 North America US USA 333 093 143 1.27% 1.32% 1.42%
30 Europe RU Russia 146 001 924 1.13% 1.87% 1.37%
31 Africa ZA South Africa 60 112 931 1.42% 2.86% 1.36%
32 Asia AE Arab Emirates 10 018 939 2.12% 1.73% 1.31%
33 North America HN Honduras 10 073 907 1.03% 1.23% 1.30%
34 Asia KG Kyrgyzstan 6 639 861 1.09% 2.08% 1.25%
35 Asia ID Indonesia 276 635 762 0.65% 1.62% 1.22%
36 Africa MA Morocco 37 381 174 0.27% 0.69% 1.21%
37 South America PR Puerto Rico 3 193 694 1.18% 0.55% 1.20%
38 Asia LB Lebanon 6 792 467 1.27% 0.78% 1.14%
39 North America GT Guatemala 18 271 521 0.90% 1.42% 1.04%
40 Europe DK Denmark 5 814 180 1.42% 1.37% 1.02%
41 Africa ZW Zimbabwe 15 095 525 0.44% 1.42% 0.89%
42 North America MX Mexico 130 390 343 0.41% 0.80% 0.84%
43 Europe FI Finland 5 549 998 0.49% 0.67% 0.83%
44 Europe LT Lithuania 2 681 250 2.39% 0.48% 0.80%
45 Asia MM Myanmar 54 802 585 0.27% 0.95% 0.76%
46 Europe BY Belarus 9 445 972 1.27% 1.09% 0.75%
47 Asia JO Jordan 10 312 137 1.45% 0.64% 0.74%
48 Asia BD Bangladesh 166 455 064 0.36% 0.72% 0.69%
49 Europe IT Italy 60 365 948 1.20% 0.47% 0.68%
50 Europe BE Belgium 11 643 962 1.92% 1.11% 0.67%
51 Asia NP Nepal 29 699 747 1.39% 0.67% 0.67%
52 Asia VN Vietnam 98 281 263 0.12% 0.42% 0.60%
53 South America PY Paraguay 7 226 775 3.26% 1.59% 0.58%
54 Asia LK Sri Lanka 21 509 978 0.97% 0.76% 0.57%
55 Asia AM Armenia 2 969 212 1.17% 0.59% 0.57%
56 South America BO Bolivia 11 844 236 1.67% 1.10% 0.56%
57 South America CL Chile 19 292 837 3.16% 1.17% 0.52%
58 Asia PH Philippines 111 149 482 0.73% 0.57% 0.52%
59 Europe SE Sweden 10 167 084 3.00% 0.34% 0.49%
60 Africa MR Mauritania 4 780 681 0.14% 0.33% 0.48%
61 Europe CH Switzerland 8 722 770 1.26% 0.58% 0.47%
62 Asia QA Qatar 2 807 805 1.60% 0.51% 0.45%
63 Africa MZ Mozambique 32 193 807 0.15% 0.49% 0.44%
64 Africa RW Rwanda 13 296 547 0.33% 0.85% 0.43%
65 North America SV El Salvador 6 521 459 0.33% 0.43% 0.43%
66 Asia JP Japan 126 058 811 0.33% 0.30% 0.43%
67 South America UY Uruguay 3 486 702 7.89% 1.44% 0.42%
68 Europe NO Norway 5 466 879 0.74% 0.38% 0.40%
69 Africa LS Lesotho 2 160 532 0.10% 0.31% 0.39%
70 Asia KH Cambodia 16 967 753 0.43% 0.58% 0.38%
71 North America JM Jamaica 2 975 091 0.43% 0.30% 0.38%
72 Africa GM Gambia 2 489 421 0.09% 0.26% 0.38%
73 Africa SN Senegal 17 216 952 0.12% 0.38% 0.37%
74 Asia AZ Azerbaijan 10 237 543 0.76% 0.23% 0.36%
75 Europe AT Austria 9 061 746 1.17% 0.31% 0.36%
76 Europe HR Croatia 4 077 945 2.13% 0.32% 0.32%
77 South America PE Peru 33 465 698 1.66% 0.64% 0.32%
78 Europe SI Slovenia 2 079 246 1.96% 0.31% 0.31%
79 South America VE Venezuela 28 349 033 0.50% 0.43% 0.30%
80 Asia SA Saudi Arabia 35 396 603 0.37% 0.39% 0.30%
81 South America EC Ecuador 17 931 028 0.86% 0.56% 0.30%
82 Africa ZM Zambia 18 935 680 0.56% 0.82% 0.28%
83 Asia LA Laos 7 389 060 0.07% 0.18% 0.28%
84 Africa DZ Algeria 44 701 619 0.11% 0.24% 0.27%
85 Africa MW Malawi 19 659 952 0.09% 0.29% 0.27%
86 Asia KR South Korea 51 316 749 0.18% 0.29% 0.25%
87 Europe RS Serbia 8 699 402 1.33% 0.20% 0.25%
88 North America DO Dominican R. 10 964 974 0.80% 0.57% 0.25%
89 Asia IN India 1 394 605 426 1.38% 0.32% 0.24%
90 Europe BG Bulgaria 6 891 984 1.13% 0.15% 0.21%
91 Europe MD Moldova 4 023 851 0.68% 0.22% 0.21%
92 Asia UZ Uzbekistan 33 990 675 0.13% 0.19% 0.20%
93 Asia SG Singapore 5 899 877 0.07% 0.14% 0.19%
94 Europe DE Germany 84 072 622 1.08% 0.16% 0.17%
95 Africa GW Guinea-Bissau 2 017 898 0.03% 0.10% 0.17%
96 Europe MK North Macedonia 2 083 282 1.19% 0.10% 0.15%
97 Africa GH Ghana 31 769 201 0.04% 0.09% 0.15%
98 Africa KE Kenya 55 042 384 0.12% 0.12% 0.13%
99 Europe CZ Czechia 10 730 394 1.18% 0.21% 0.13%
100 Asia PK Pakistan 225 498 161 0.15% 0.11% 0.13%
101 North America CA Canada 38 098 354 1.17% 0.14% 0.12%
102 Europe UA Ukraine 43 450 212 1.24% 0.14% 0.11%
103 Asia AF Afghanistan 39 869 084 0.22% 0.26% 0.09%
104 Africa BI Burundi 12 270 120 0.03% 0.05% 0.09%
105 Africa TG Togo 8 486 878 0.06% 0.07% 0.09%
106 Europe AL Albania 2 874 408 0.26% 0.06% 0.08%
107 Europe SK Slovakia 5 462 493 0.53% 0.07% 0.08%
108 Europe BA Bosnia and Herzegovina 3 258 795 1.05% 0.07% 0.08%
109 North America NI Nicaragua 6 709 335 0.03% 0.07% 0.07%
110 Europe RO Romania 19 099 182 0.65% 0.04% 0.06%
111 Australia/Oceania AU Australia 25 818 165 0.02% 0.04% 0.06%
112 Europe HU Hungary 9 633 893 1.44% 0.05% 0.06%
113 Africa UG Uganda 47 287 644 0.11% 0.11% 0.05%
114 Asia PS Palestine 5 228 642 0.00% 0.01% 0.04%
115 Africa CM Cameroon 27 254 503 0.13% 0.02% 0.04%
116 Africa GN Guinea 13 514 607 0.04% 0.04% 0.04%
117 Africa GA Gabon 2 282 073 0.25% 0.07% 0.04%
118 Australia/Oceania PG Papua New Guinea 9 129 039 0.12% 0.02% 0.03%
119 Africa AO Angola 33 961 015 0.06% 0.04% 0.03%
120 Africa CG Congo 5 663 755 0.06% 0.05% 0.03%
121 Africa CD DR Congo 92 477 515 0.02% 0.04% 0.03%
122 Europe PL Poland 37 801 912 1.31% 0.03% 0.03%
123 Africa SS South Sudan 11 334 900 0.01% 0.01% 0.02%
124 Africa CI Ivory Coast 27 078 801 0.02% 0.02% 0.02%
125 North America HT Haiti 11 552 042 0.06% 0.05% 0.02%
126 Africa ET Ethiopia 118 017 563 0.06% 0.01% 0.02%
127 Africa ER Eritrea 3 599 197 0.09% 0.06% 0.01%
128 Asia TJ Tajikistan 9 767 516 0.00% 0.00% 0.01%
129 Africa NG Nigeria 211 618 923 0.00% 0.01% 0.01%
130 Africa SO Somalia 16 368 393 0.03% 0.01% 0.01%
131 Africa SL Sierra Leone 8 151 140 0.03% 0.03% 0.01%
132 Africa BJ Benin 12 463 627 0.01% 0.00% 0.01%
133 Asia TW Taiwan 23 863 237 0.06% 0.01% 0.01%
134 Asia SY Syria 17 956 644 0.04% 0.01% 0.01%
135 Africa LR Liberia 5 185 207 0.06% 0.13% 0.00%
136 Africa TZ Tanzania 61 557 275 0.00% 0.00% 0.00%
137 Africa EG Egypt 104 407 309 0.08% 0.01% 0.00%
138 Africa MG Madagascar 28 454 297 0.07% 0.01% 0.00%
139 Asia YE Yemen 30 530 919 0.01% 0.00% 0.00%
140 Africa BF Burkina Faso 21 517 590 0.00% 0.00% 0.00%
141 Australia/Oceania NZ New Zealand 5 002 100 0.01% 0.01% 0.00%
142 Africa NE Niger 25 143 758 0.00% 0.00% 0.00%
143 Asia HK Hong Kong 7 562 460 0.01% 0.00% 0.00%
144 Africa ML Mali 20 875 763 0.02% 0.00% 0.00%
145 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
146 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
147 Africa TD Chad 16 930 869 0.00% 0.00% 0.00%
148 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
149 Africa CF Central African R. 4 919 984 0.04% 0.00% 0.00%
150 Africa SD Sudan 44 947 622 0.01% 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 South America EC Ecuador 17 931 028 9.00% 31.34% 0.56%
2 Asia YE Yemen 30 530 919 14.67% (12.38)% (0.00)%
3 Asia TW Taiwan 23 863 237 5.34% (10.78)% (0.01)%
4 Africa UG Uganda 47 287 644 4.48% 9.15% 0.11%
5 Europe BA Bosnia and Herzegovina 3 258 795 6.70% (7.84)% (0.07)%
6 Africa MG Madagascar 28 454 297 2.75% (7.83)% (0.01)%
7 Europe PL Poland 37 801 912 3.05% (7.69)% (0.03)%
8 Africa SO Somalia 16 368 393 5.82% (7.42)% (0.01)%
9 Europe BG Bulgaria 6 891 984 4.78% 6.48% 0.15%
10 Africa EG Egypt 104 407 309 5.19% (6.42)% (0.01)%
11 North America JM Jamaica 2 975 091 4.00% 5.66% 0.30%
12 South America PE Peru 33 465 698 8.64% 5.64% 0.64%
13 Asia SY Syria 17 956 644 8.14% (5.57)% (0.01)%
14 South America PY Paraguay 7 226 775 4.27% 5.19% 1.59%
15 North America HT Haiti 11 552 042 4.02% (4.89)% (0.05)%
16 Asia AF Afghanistan 39 869 084 4.70% 4.81% 0.26%
17 Asia MM Myanmar 54 802 585 4.42% 4.62% 0.95%
18 Africa ML Mali 20 875 763 2.97% (4.26)% (0.00)%
19 Australia/Oceania PG Papua New Guinea 9 129 039 1.05% (4.23)% (0.02)%
20 Europe RO Romania 19 099 182 4.28% (3.71)% (0.04)%
21 Africa NA Namibia 2 590 333 3.32% 3.70% 4.30%
22 South America CL Chile 19 292 837 1.83% 3.45% 1.17%
23 Africa SD Sudan 44 947 622 12.34% (3.34)% (0.00)%
24 Europe SK Slovakia 5 462 493 7.22% (3.19)% (0.07)%
25 North America SV El Salvador 6 521 459 2.84% 3.18% 0.43%
26 Europe UA Ukraine 43 450 212 3.04% 3.17% 0.14%
27 Africa MW Malawi 19 659 952 3.23% 3.05% 0.29%
28 Africa ZW Zimbabwe 15 095 525 3.10% 2.99% 1.42%
29 Europe RU Russia 146 001 924 3.58% 2.95% 1.87%
30 Asia ID Indonesia 276 635 762 3.01% 2.93% 1.62%
31 Africa BJ Benin 12 463 627 1.19% (2.88)% (0.00)%
32 Africa GN Guinea 13 514 607 1.43% (2.85)% (0.04)%
33 Asia KH Cambodia 16 967 753 1.92% 2.80% 0.58%
34 Africa GM Gambia 2 489 421 2.52% 2.78% 0.26%
35 North America MX Mexico 130 390 343 7.15% 2.75% 0.80%
36 Africa AO Angola 33 961 015 2.34% (2.73)% (0.04)%
37 Europe HU Hungary 9 633 893 4.51% (2.70)% (0.05)%
38 Africa LS Lesotho 2 160 532 2.58% 2.63% 0.31%
39 Africa TN Tunisia 11 951 687 3.28% 2.46% 5.43%
40 Europe MD Moldova 4 023 851 3.42% 2.45% 0.22%
41 Asia LK Sri Lanka 21 509 978 1.78% 2.42% 0.76%
42 South America BR Brazil 214 186 368 3.15% 2.41% 2.31%
43 South America BO Bolivia 11 844 236 2.73% 2.39% 1.10%
44 North America HN Honduras 10 073 907 3.07% 2.35% 1.23%
45 Europe DE Germany 84 072 622 1.45% 2.22% 0.16%
46 South America AR Argentina 45 642 150 1.92% 2.12% 3.72%
47 Africa ZM Zambia 18 935 680 2.05% 2.11% 0.82%
48 Asia AM Armenia 2 969 212 2.62% 2.10% 0.59%
49 Africa ET Ethiopia 118 017 563 1.78% (2.05)% (0.01)%
50 Africa ZA South Africa 60 112 931 2.19% 2.04% 2.86%
51 Asia OM Oman 5 245 888 1.55% 2.00% 2.51%
52 Asia BD Bangladesh 166 455 064 1.96% 1.99% 0.72%
53 Africa MR Mauritania 4 780 681 1.73% 1.96% 0.33%
54 South America CO Colombia 51 466 439 2.40% 1.95% 4.14%
55 Africa GW Guinea-Bissau 2 017 898 2.22% 1.94% 0.10%
56 North America CA Canada 38 098 354 0.75% 1.92% 0.14%
57 Africa SS South Sudan 11 334 900 0.81% 1.90% 0.01%
58 Africa DZ Algeria 44 701 619 2.43% 1.89% 0.24%
59 Europe MK North Macedonia 2 083 282 5.17% 1.88% 0.10%
60 Asia IN India 1 394 605 426 1.33% 1.85% 0.32%
61 South America UY Uruguay 3 486 702 1.70% 1.79% 1.44%
62 Asia PK Pakistan 225 498 161 2.40% 1.77% 0.11%
63 Europe RS Serbia 8 699 402 1.19% 1.73% 0.20%
64 Africa TG Togo 8 486 878 0.75% 1.72% 0.07%
65 Asia PH Philippines 111 149 482 1.68% 1.71% 0.57%
66 Africa SL Sierra Leone 8 151 140 1.78% 1.65% 0.03%
67 Africa KE Kenya 55 042 384 2.47% 1.64% 0.12%
68 Africa NE Niger 25 143 758 1.25% 1.64% 0.00%
69 Africa CG Congo 5 663 755 1.20% 1.60% 0.05%
70 Asia JO Jordan 10 312 137 1.59% 1.57% 0.64%
71 Africa BF Burkina Faso 21 517 590 2.18% 1.56% 0.00%
72 North America GT Guatemala 18 271 521 2.16% 1.55% 1.42%
73 Africa BW Botswana 2 402 605 1.80% 1.50% 5.34%
74 Europe HR Croatia 4 077 945 2.30% 1.45% 0.32%
75 Africa MZ Mozambique 32 193 807 1.46% 1.44% 0.49%
76 Asia HK Hong Kong 7 562 460 1.31% 1.43% 0.00%
77 Africa GA Gabon 2 282 073 0.67% 1.42% 0.07%
78 Asia NP Nepal 29 699 747 1.69% 1.35% 0.67%
79 Europe LT Lithuania 2 681 250 1.20% 1.33% 0.48%
80 Asia KZ Kazakhstan 19 018 299 1.12% 1.29% 2.77%
81 Africa CD DR Congo 92 477 515 1.49% 1.29% 0.04%
82 South America VE Venezuela 28 349 033 1.34% 1.27% 0.43%
83 Asia MY Malaysia 32 811 983 1.14% 1.26% 3.78%
84 Africa ER Eritrea 3 599 197 0.73% 1.24% 0.06%
85 Africa RW Rwanda 13 296 547 1.15% 1.22% 0.85%
86 Africa LR Liberia 5 185 207 1.88% 1.17% 0.13%
87 Africa SN Senegal 17 216 952 1.51% 1.16% 0.38%
88 Asia GE Georgia 3 980 909 1.63% 1.15% 4.72%
89 Asia IR Iran 85 149 163 1.49% 1.06% 2.69%
90 Africa CI Ivory Coast 27 078 801 1.09% 1.06% 0.02%
91 Europe BY Belarus 9 445 972 0.94% 1.06% 1.09%
92 Africa CM Cameroon 27 254 503 1.44% 1.02% 0.02%
93 Asia SA Saudi Arabia 35 396 603 1.18% 1.01% 0.39%
94 Asia TH Thailand 69 988 732 0.99% 1.00% 1.70%
95 South America PR Puerto Rico 3 193 694 1.22% 0.97% 0.55%
96 Asia AZ Azerbaijan 10 237 543 1.60% 0.95% 0.23%
97 Africa MA Morocco 37 381 174 1.13% 0.94% 0.69%
98 North America CU Cuba 11 319 161 0.86% 0.89% 5.90%
99 Europe IT Italy 60 365 948 2.15% 0.85% 0.47%
100 North America CR Costa Rica 5 144 185 1.11% 0.81% 2.85%
101 North America US USA 333 093 143 1.28% 0.77% 1.32%
102 North America PA Panama 4 387 767 0.89% 0.77% 2.62%
103 Asia KG Kyrgyzstan 6 639 861 1.17% 0.77% 2.08%
104 Asia UZ Uzbekistan 33 990 675 0.56% 0.76% 0.19%
105 Asia TR Turkey 85 315 528 0.79% 0.74% 1.10%
106 Asia KW Kuwait 4 338 465 0.59% 0.73% 3.56%
107 Africa LY Libya 6 971 764 1.05% 0.71% 2.85%
108 Africa NG Nigeria 211 618 923 0.99% 0.67% 0.01%
109 North America DO Dominican R. 10 964 974 0.70% 0.65% 0.57%
110 Europe CZ Czechia 10 730 394 1.89% 0.63% 0.21%
111 Europe SI Slovenia 2 079 246 0.77% 0.62% 0.31%
112 Asia VN Vietnam 98 281 263 0.58% 0.60% 0.42%
113 Africa GH Ghana 31 769 201 0.83% 0.58% 0.09%
114 Asia IQ Iraq 41 191 025 0.57% 0.56% 2.34%
115 Asia JP Japan 126 058 811 1.50% 0.52% 0.30%
116 Australia/Oceania AU Australia 25 818 165 0.36% 0.50% 0.04%
117 Asia LB Lebanon 6 792 467 1.59% 0.48% 0.78%
118 North America NI Nicaragua 6 709 335 0.87% 0.47% 0.07%
119 Asia MN Mongolia 3 335 025 0.53% 0.43% 5.39%
120 Europe GR Greece 10 368 119 2.13% 0.42% 2.41%
121 Europe AT Austria 9 061 746 0.96% 0.38% 0.31%
122 Europe FR France 65 429 176 0.97% 0.31% 1.59%
123 Europe PT Portugal 10 164 639 0.36% 0.29% 3.15%
124 Asia QA Qatar 2 807 805 0.62% 0.27% 0.51%
125 Asia AE Arab Emirates 10 018 939 0.20% 0.25% 1.73%
126 Asia IL Israel 9 326 000 0.83% 0.22% 1.36%
127 Asia KR South Korea 51 316 749 0.41% 0.20% 0.29%
128 Europe BE Belgium 11 643 962 0.85% 0.18% 1.11%
129 Europe SE Sweden 10 167 084 0.32% 0.15% 0.34%
130 Europe IE Ireland 4 997 127 0.53% 0.13% 1.97%
131 Asia LA Laos 7 389 060 0.14% 0.13% 0.18%
132 Europe GB United Kingdom 68 270 129 0.20% 0.13% 5.69%
133 Africa BI Burundi 12 270 120 0.08% 0.11% 0.05%
134 Europe NO Norway 5 466 879 0.28% 0.09% 0.38%
135 Europe CH Switzerland 8 722 770 0.38% 0.09% 0.58%
136 Europe ES Spain 46 774 302 0.42% 0.07% 4.90%
137 Europe DK Denmark 5 814 180 0.15% 0.07% 1.37%
138 Asia SG Singapore 5 899 877 0.19% 0.07% 0.14%
139 Europe FI Finland 5 549 998 0.47% 0.06% 0.67%
140 Europe NL Netherlands 17 175 733 0.21% 0.04% 3.95%
141 Europe AL Albania 2 874 408 2.14% 0.00% 0.06%
142 Australia/Oceania NZ New Zealand 5 002 100 0.00% 0.00% 0.01%
143 Africa TD Chad 16 930 869 1.99% 0.00% 0.00%
144 Africa CF Central African R. 4 919 984 1.50% 0.00% 0.00%
145 Asia PS Palestine 5 228 642 0.00% 0.00% 0.01%
146 Asia TJ Tajikistan 9 767 516 0.00% 0.00% 0.00%
147 Africa TZ Tanzania 61 557 275 0.00% 0.00% 0.00%
148 Asia KP North Korea 25 660 000 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 33 465 698 196 050 5.858
2 Europe HU Hungary 9 633 893 30 026 3.117
3 Europe BA Bosnia and Herzegovina 3 258 795 9 687 2.973
4 Europe CZ Czechia 10 730 394 30 362 2.829
5 Europe BG Bulgaria 6 891 984 18 206 2.642
6 Europe MK North Macedonia 2 083 282 5 491 2.636
7 South America BR Brazil 214 186 368 551 388 2.574
8 South America CO Colombia 51 466 439 119 488 2.322
9 Europe SK Slovakia 5 462 493 12 538 2.295
10 South America AR Argentina 45 642 150 104 578 2.291
11 Europe SI Slovenia 2 079 246 4 762 2.290
12 Europe BE Belgium 11 643 962 25 236 2.167
13 Europe IT Italy 60 365 948 128 011 2.121
14 South America PY Paraguay 7 226 775 14 754 2.042
15 Europe HR Croatia 4 077 945 8 254 2.024
16 Europe PL Poland 37 801 912 75 254 1.991
17 Europe GB United Kingdom 68 270 129 129 374 1.895
18 North America MX Mexico 130 390 343 239 054 1.833
19 South America CL Chile 19 292 837 35 233 1.826
20 North America US USA 333 093 143 606 475 1.821
21 Europe RO Romania 19 099 182 34 277 1.795
22 South America EC Ecuador 17 931 028 31 468 1.755
23 Europe ES Spain 46 774 302 81 367 1.740
24 Europe PT Portugal 10 164 639 17 324 1.704
25 South America UY Uruguay 3 486 702 5 942 1.704
26 Europe FR France 65 429 176 110 725 1.692
27 Europe LT Lithuania 2 681 250 4 413 1.646
28 Africa TN Tunisia 11 951 687 19 210 1.607
29 Europe MD Moldova 4 023 851 6 247 1.552
30 Asia AM Armenia 2 969 212 4 603 1.550
31 North America PA Panama 4 387 767 6 778 1.545
32 South America BO Bolivia 11 844 236 17 702 1.495
33 Asia GE Georgia 3 980 909 5 778 1.451
34 Europe SE Sweden 10 167 084 14 655 1.441
35 Europe GR Greece 10 368 119 12 928 1.247
36 Europe UA Ukraine 43 450 212 52 906 1.218
37 Europe CH Switzerland 8 722 770 10 334 1.185
38 Africa ZA South Africa 60 112 931 70 722 1.177
39 Asia LB Lebanon 6 792 467 7 898 1.163
40 Europe AT Austria 9 061 746 10 531 1.162
41 Africa NA Namibia 2 590 333 2 916 1.126
42 Europe DE Germany 84 072 622 91 596 1.089
43 Europe RU Russia 146 001 924 156 970 1.075
44 Asia IR Iran 85 149 163 89 765 1.054
45 Europe NL Netherlands 17 175 733 17 810 1.037
46 Europe IE Ireland 4 997 127 5 026 1.006
47 North America CR Costa Rica 5 144 185 4 998 0.972
48 Asia JO Jordan 10 312 137 9 991 0.969
49 Europe AL Albania 2 874 408 2 456 0.854
50 Europe RS Serbia 8 699 402 7 110 0.817
51 South America PR Puerto Rico 3 193 694 2 569 0.804
52 North America HN Honduras 10 073 907 7 691 0.763
53 Asia OM Oman 5 245 888 3 788 0.722
54 North America CA Canada 38 098 354 26 559 0.697
55 Asia IL Israel 9 326 000 6 473 0.694
56 Africa BW Botswana 2 402 605 1 485 0.618
57 Asia TR Turkey 85 315 528 51 127 0.599
58 North America GT Guatemala 18 271 521 10 217 0.559
59 Asia KW Kuwait 4 338 465 2 304 0.531
60 Africa LY Libya 6 971 764 3 462 0.497
61 Asia AZ Azerbaijan 10 237 543 5 012 0.490
62 Asia KZ Kazakhstan 19 018 299 9 077 0.477
63 Asia IQ Iraq 41 191 025 18 480 0.449
64 Europe DK Denmark 5 814 180 2 547 0.438
65 North America SV El Salvador 6 521 459 2 593 0.398
66 North America JM Jamaica 2 975 091 1 182 0.397
67 Europe BY Belarus 9 445 972 3 422 0.362
68 North America DO Dominican R. 10 964 974 3 952 0.360
69 Asia KG Kyrgyzstan 6 639 861 2 302 0.347
70 Asia NP Nepal 29 699 747 9 814 0.330
71 Asia ID Indonesia 276 635 762 90 467 0.327
72 Asia IN India 1 394 605 426 422 564 0.303
73 Asia MY Malaysia 32 811 983 8 569 0.261
74 Africa MA Morocco 37 381 174 9 691 0.259
75 Asia PH Philippines 111 149 482 27 485 0.247
76 Asia MN Mongolia 3 335 025 795 0.238
77 Asia SA Saudi Arabia 35 396 603 8 200 0.232
78 North America CU Cuba 11 319 161 2 557 0.226
79 Africa ZW Zimbabwe 15 095 525 3 349 0.222
80 Asia QA Qatar 2 807 805 600 0.214
81 Asia LK Sri Lanka 21 509 978 4 194 0.195
82 Asia AE Arab Emirates 10 018 939 1 935 0.193
83 Europe FI Finland 5 549 998 978 0.176
84 Africa ZM Zambia 18 935 680 3 329 0.176
85 Africa LS Lesotho 2 160 532 363 0.168
86 Asia AF Afghanistan 39 869 084 6 605 0.166
87 Africa EG Egypt 104 407 309 16 502 0.158
88 Asia MM Myanmar 54 802 585 8 602 0.157
89 Europe NO Norway 5 466 879 799 0.146
90 South America VE Venezuela 28 349 033 3 527 0.124
91 Asia BD Bangladesh 166 455 064 20 234 0.122
92 Asia JP Japan 126 058 811 15 162 0.120
93 Africa MR Mauritania 4 780 681 547 0.114
94 Asia SY Syria 17 956 644 1 910 0.106
95 Asia PK Pakistan 225 498 161 23 152 0.103
96 Africa DZ Algeria 44 701 619 4 142 0.093
97 Africa GM Gambia 2 489 421 212 0.085
98 Africa MW Malawi 19 659 952 1 566 0.080
99 Asia KH Cambodia 16 967 753 1 346 0.079
100 Africa SN Senegal 17 216 952 1 320 0.077
101 Africa GA Gabon 2 282 073 164 0.072
102 Africa KE Kenya 55 042 384 3 887 0.071
103 Asia TH Thailand 69 988 732 4 575 0.065
104 Africa SD Sudan 44 947 622 2 776 0.062
105 Africa RW Rwanda 13 296 547 782 0.059
106 Africa UG Uganda 47 287 644 2 619 0.055
107 Africa CM Cameroon 27 254 503 1 334 0.049
108 Africa SO Somalia 16 368 393 798 0.049
109 North America HT Haiti 11 552 042 540 0.047
110 Asia YE Yemen 30 530 919 1 374 0.045
111 Africa MZ Mozambique 32 193 807 1 368 0.043
112 Asia KR South Korea 51 316 749 2 089 0.041
113 Africa GW Guinea-Bissau 2 017 898 75 0.037
114 Africa ET Ethiopia 118 017 563 4 376 0.037
115 Australia/Oceania AU Australia 25 818 165 921 0.036
116 Africa MG Madagascar 28 454 297 945 0.033
117 Asia TW Taiwan 23 863 237 787 0.033
118 Africa CG Congo 5 663 755 177 0.031
119 Africa AO Angola 33 961 015 999 0.029
120 North America NI Nicaragua 6 709 335 195 0.029
121 Africa LR Liberia 5 185 207 148 0.029
122 Asia HK Hong Kong 7 562 460 212 0.028
123 Africa GH Ghana 31 769 201 823 0.026
124 Africa ML Mali 20 875 763 531 0.025
125 Asia UZ Uzbekistan 33 990 675 861 0.025
126 Australia/Oceania PG Papua New Guinea 9 129 039 192 0.021
127 Africa CF Central African R. 4 919 984 98 0.020
128 Africa TG Togo 8 486 878 150 0.018
129 Africa GN Guinea 13 514 607 208 0.015
130 Africa SL Sierra Leone 8 151 140 119 0.015
131 Africa CI Ivory Coast 27 078 801 328 0.012
132 Africa CD DR Congo 92 477 515 1 038 0.011
133 Africa SS South Sudan 11 334 900 119 0.011
134 Africa TD Chad 16 930 869 174 0.010
135 Africa NG Nigeria 211 618 923 2 142 0.010
136 Africa ER Eritrea 3 599 197 34 0.009
137 Africa BJ Benin 12 463 627 107 0.009
138 Africa BF Burkina Faso 21 517 590 169 0.008
139 Africa NE Niger 25 143 758 195 0.008
140 Asia SG Singapore 5 899 877 37 0.006
141 Asia VN Vietnam 98 281 263 524 0.005
142 Australia/Oceania NZ New Zealand 5 002 100 26 0.005
143 Asia LA Laos 7 389 060 6 0.001
144 Africa BI Burundi 12 270 120 9 0.001
145 Asia PS Palestine 5 228 642 2 0.000
146 Africa TZ Tanzania 61 557 275 21 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 9 767 516 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"