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": 2021-10-17 09:28
(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 (+2 397) +0 (+10)
CZ Czechia +1 157 (+1 789) +3 (+8)
DE Germany +0 (+8 515) +0 (+28)
HU Hungary +0 (+0) +0 (+0)
PL Poland +0 (+3 236) +0 (+44)
SK Slovakia, [gov], [okr]+0 (+1 941) +0 (+17)

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

N.RegionPopulationLast 120 daysLast 30 daysLast 7 days
1 Europe 756 219 696 1.83% 2.08% 2.16%
2 North America 594 633 539 2.42% 2.45% 1.51%
3 Australia/Oceania 43 445 471 0.48% 0.72% 0.66%
4 South America 438 591 631 1.57% 0.72% 0.38%
5 Asia 4 678 162 745 0.50% 0.35% 0.25%
6 Africa 1 381 260 066 0.24% 0.10% 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 Africa 1 381 260 066 2.30% (3.46)% (0.10)%
2 South America 438 591 631 2.61% 2.76% 0.72%
3 North America 594 633 539 1.40% 2.11% 2.45%
4 Europe 756 219 696 1.25% 1.93% 2.08%
5 Asia 4 678 162 745 1.63% 1.64% 0.35%
6 Australia/Oceania 43 445 471 1.11% 1.46% 0.72%

COVID-19, Total Mortality from population of Regions

N.RegionPopulationDeaths1000*Deaths/Pop.
1 South America 438 591 631 1 165 722 2.658
2 North America 594 633 539 1 088 934 1.831
3 Europe 756 219 696 1 258 017 1.664
4 Asia 4 678 162 745 1 142 260 0.244
5 Africa 1 381 260 066 215 498 0.156
6 Australia/Oceania 43 445 471 3 559 0.082

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 GE Georgia 3 979 283 7.51% 6.58% 10.00%
2 Europe LT Lithuania 2 673 216 3.27% 7.77% 8.78%
3 Europe RO Romania 19 071 982 1.92% 6.42% 8.01%
4 Europe RS Serbia 8 691 936 3.70% 8.80% 7.29%
5 Europe GB United Kingdom 68 345 973 5.49% 5.98% 6.02%
6 Asia MN Mongolia 3 346 285 7.20% 7.48% 5.69%
7 Asia SG Singapore 5 909 670 1.34% 4.52% 5.08%
8 Asia AM Armenia 2 970 389 1.88% 3.78% 4.48%
9 Europe SI Slovenia 2 079 307 2.38% 4.97% 4.47%
10 Europe BG Bulgaria 6 880 900 1.67% 3.33% 3.97%
11 Europe HR Croatia 4 072 579 1.66% 3.77% 3.69%
12 Asia TR Turkey 85 508 828 2.62% 3.89% 3.67%
13 Europe IE Ireland 5 008 876 2.94% 3.24% 3.44%
14 Europe MD Moldova 4 021 861 1.44% 3.47% 3.42%
15 Europe UA Ukraine 43 394 513 0.91% 2.62% 3.20%
16 Europe SK Slovakia 5 463 055 0.81% 2.52% 3.16%
17 North America CR Costa Rica 5 154 089 3.95% 4.17% 2.68%
18 North America CU Cuba 11 317 694 6.77% 5.46% 2.40%
19 Asia MY Malaysia 32 900 356 5.14% 3.98% 2.34%
20 Europe GR Greece 10 357 323 2.57% 2.49% 2.33%
21 North America US USA 333 506 023 3.32% 3.55% 2.21%
22 Europe BY Belarus 9 445 312 1.68% 2.43% 2.20%
23 Europe AT Austria 9 072 677 1.35% 2.33% 2.20%
24 Europe RU Russia 146 015 214 1.82% 1.98% 2.15%
25 Europe BA Bosnia and Herzegovina 3 254 469 1.18% 2.49% 2.01%
26 Europe BE Belgium 11 654 687 1.68% 2.02% 1.99%
27 Europe NL Netherlands 17 183 790 2.11% 1.43% 1.89%
28 Asia IL Israel 9 326 000 5.10% 4.47% 1.83%
29 Asia TH Thailand 70 025 954 2.23% 1.85% 1.52%
30 Europe AL Albania 2 873 741 1.55% 2.33% 1.46%
31 Europe MK North Macedonia 2 083 264 1.96% 2.09% 1.46%
32 Asia IR Iran 85 378 270 3.14% 1.80% 1.40%
33 Asia AZ Azerbaijan 10 257 000 1.57% 1.30% 1.26%
34 Asia KZ Kazakhstan 19 066 152 2.77% 1.45% 1.21%
35 Europe DK Denmark 5 818 516 1.31% 0.94% 1.18%
36 Europe CZ Czechia 10 734 616 0.38% 0.81% 1.18%
37 Africa GA Gabon 2 293 296 0.37% 1.08% 1.15%
38 Europe FI Finland 5 551 826 1.00% 1.06% 1.09%
39 Europe DE Germany 84 129 567 0.76% 1.13% 1.07%
40 Europe HU Hungary 9 628 688 0.27% 0.70% 1.02%
41 Africa BW Botswana 2 412 743 4.88% 2.69% 1.01%
42 Africa LY Libya 6 991 680 2.27% 1.27% 0.93%
43 Europe CH Switzerland 8 736 238 1.73% 1.54% 0.93%
44 Asia JO Jordan 10 333 707 0.89% 1.06% 0.90%
45 Australia/Oceania AU Australia 25 881 197 0.42% 0.89% 0.88%
46 Asia PH Philippines 111 460 341 1.22% 1.44% 0.79%
47 North America CA Canada 38 168 800 0.70% 1.18% 0.74%
48 Asia LA Laos 7 411 569 0.39% 0.71% 0.72%
49 Europe SE Sweden 10 180 481 0.75% 0.77% 0.71%
50 Asia LB Lebanon 6 785 984 1.31% 1.00% 0.67%
51 Europe PL Poland 37 793 112 0.15% 0.43% 0.67%
52 Europe FR France 65 459 869 1.85% 0.81% 0.66%
53 Europe NO Norway 5 475 901 1.21% 1.11% 0.64%
54 Europe PT Portugal 10 158 330 2.12% 0.75% 0.63%
55 North America DO Dominican R. 10 988 140 0.50% 0.53% 0.61%
56 North America JM Jamaica 2 977 839 1.26% 1.21% 0.61%
57 North America GT Guatemala 18 342 249 1.68% 1.39% 0.57%
58 South America CL Chile 19 327 768 0.84% 0.45% 0.55%
59 South America VE Venezuela 28 331 937 0.47% 0.54% 0.48%
60 South America BR Brazil 214 507 883 1.82% 1.07% 0.47%
61 North America HN Honduras 10 107 504 1.19% 0.66% 0.46%
62 South America PR Puerto Rico 3 193 694 1.36% 0.73% 0.43%
63 Europe IT Italy 60 347 076 0.77% 0.59% 0.42%
64 Asia IQ Iraq 41 383 846 1.82% 0.62% 0.39%
65 North America PA Panama 4 402 253 1.78% 0.60% 0.39%
66 North America MX Mexico 130 678 852 0.98% 0.62% 0.39%
67 Asia VN Vietnam 98 467 720 0.86% 0.82% 0.37%
68 South America UY Uruguay 3 489 261 1.20% 0.39% 0.36%
69 Asia LK Sri Lanka 21 529 068 1.36% 0.55% 0.32%
70 Europe ES Spain 46 778 148 2.61% 0.47% 0.31%
71 Asia KR South Korea 51 326 122 0.37% 0.46% 0.31%
72 Australia/Oceania PG Papua New Guinea 9 165 213 0.08% 0.24% 0.31%
73 South America BO Bolivia 11 878 176 0.74% 0.32% 0.30%
74 Asia QA Qatar 2 807 805 0.62% 0.40% 0.28%
75 South America CO Colombia 51 581 952 2.17% 0.33% 0.27%
76 Asia MM Myanmar 54 880 192 0.62% 0.31% 0.21%
77 South America PE Peru 33 563 608 0.50% 0.28% 0.21%
78 Africa CG Congo 5 692 787 0.06% 0.13% 0.21%
79 Africa CM Cameroon 27 395 756 0.07% 0.19% 0.19%
80 Asia KH Cambodia 17 017 076 0.44% 0.33% 0.16%
81 Africa NA Namibia 2 600 153 2.35% 0.27% 0.15%
82 South America AR Argentina 45 730 448 2.29% 0.32% 0.15%
83 Asia NP Nepal 29 811 574 0.62% 0.29% 0.14%
84 Asia SY Syria 18 047 508 0.07% 0.18% 0.14%
85 Asia AE Arab Emirates 10 044 401 1.30% 0.28% 0.12%
86 Asia KG Kyrgyzstan 6 662 821 0.98% 0.13% 0.12%
87 Asia UZ Uzbekistan 34 094 090 0.22% 0.16% 0.11%
88 Africa TN Tunisia 11 978 025 2.77% 0.40% 0.11%
89 Africa ZA South Africa 60 272 279 1.86% 0.28% 0.11%
90 Australia/Oceania NZ New Zealand 5 002 100 0.04% 0.07% 0.11%
91 North America NI Nicaragua 6 726 128 0.09% 0.11% 0.11%
92 Asia IN India 1 397 494 569 0.30% 0.19% 0.10%
93 Africa MA Morocco 37 474 385 1.11% 0.32% 0.10%
94 Asia PS Palestine 5 253 981 0.01% 0.02% 0.09%
95 Africa MR Mauritania 4 806 817 0.34% 0.12% 0.08%
96 Asia KW Kuwait 4 351 931 1.75% 0.12% 0.07%
97 South America EC Ecuador 17 988 156 0.39% 0.15% 0.07%
98 Africa EG Egypt 104 819 267 0.04% 0.08% 0.07%
99 Africa AO Angola 34 179 919 0.07% 0.13% 0.07%
100 Africa ZW Zimbabwe 15 141 654 0.60% 0.13% 0.06%
101 Africa ET Ethiopia 118 626 274 0.07% 0.10% 0.06%
102 Africa RW Rwanda 13 365 179 0.52% 0.14% 0.06%
103 Africa BI Burundi 12 345 921 0.12% 0.11% 0.05%
104 Africa GH Ghana 31 907 710 0.11% 0.07% 0.05%
105 Asia JP Japan 125 976 661 0.74% 0.16% 0.05%
106 Africa LS Lesotho 2 164 146 0.49% 1.31% 0.04%
107 Asia PK Pakistan 226 413 748 0.14% 0.08% 0.04%
108 Africa SO Somalia 16 463 253 0.04% 0.07% 0.04%
109 North America HT Haiti 11 581 660 0.05% 0.06% 0.04%
110 Asia OM Oman 5 273 654 1.20% 0.06% 0.04%
111 Asia ID Indonesia 277 251 787 0.81% 0.07% 0.03%
112 Africa BJ Benin 12 531 529 0.13% 0.10% 0.03%
113 South America PY Paraguay 7 245 443 0.81% 0.05% 0.03%
114 Asia BD Bangladesh 166 804 466 0.43% 0.06% 0.03%
115 Africa DZ Algeria 44 870 592 0.16% 0.04% 0.02%
116 Africa KE Kenya 55 295 388 0.13% 0.05% 0.02%
117 Africa CF Central African R. 4 937 900 0.09% 0.01% 0.02%
118 Africa SD Sudan 45 166 389 0.01% 0.01% 0.02%
119 Africa TG Togo 8 528 340 0.14% 0.08% 0.02%
120 Africa CI Ivory Coast 27 218 428 0.05% 0.04% 0.02%
121 Africa BF Burkina Faso 21 640 198 0.01% 0.01% 0.02%
122 Africa UG Uganda 47 596 984 0.12% 0.21% 0.02%
123 Asia SA Saudi Arabia 35 512 227 0.21% 0.02% 0.02%
124 Africa ER Eritrea 3 609 659 0.04% 0.01% 0.01%
125 Asia AF Afghanistan 40 056 379 0.14% 0.01% 0.01%
126 Africa SS South Sudan 11 362 860 0.01% 0.02% 0.01%
127 Africa ML Mali 21 000 577 0.01% 0.01% 0.01%
128 Africa GN Guinea 13 590 799 0.05% 0.01% 0.01%
129 Africa ZM Zambia 19 045 828 0.44% 0.03% 0.01%
130 Asia YE Yemen 30 671 236 0.01% 0.01% 0.01%
131 Africa NG Nigeria 212 711 058 0.02% 0.01% 0.01%
132 Asia HK Hong Kong 7 575 406 0.01% 0.01% 0.01%
133 Africa MZ Mozambique 32 381 148 0.24% 0.02% 0.01%
134 Africa GW Guinea-Bissau 2 027 838 0.11% 0.02% 0.01%
135 Africa GM Gambia 2 503 947 0.16% 0.01% 0.01%
136 Africa NE Niger 25 331 639 0.00% 0.00% 0.00%
137 Africa MW Malawi 19 765 647 0.14% 0.01% 0.00%
138 Asia TW Taiwan 23 872 396 0.01% 0.00% 0.00%
139 Africa CD DR Congo 93 060 408 0.02% 0.00% 0.00%
140 Africa LR Liberia 5 210 609 0.06% 0.01% 0.00%
141 Africa TZ Tanzania 61 921 324 0.04% 0.16% 0.00%
142 Africa TD Chad 17 031 725 0.00% 0.00% 0.00%
143 Africa SN Senegal 17 311 310 0.18% 0.01% 0.00%
144 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
145 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
146 Asia TJ Tajikistan 9 813 281 0.00% 0.00% 0.00%
147 North America SV El Salvador 6 528 419 0.48% 0.49% 0.00%
148 Asia CN China 1 439 323 776 0.00% 0.00% 0.00%
149 Africa SL Sierra Leone 8 185 777 0.02% 0.00% 0.00%
150 Africa MG Madagascar 28 606 504 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 LR Liberia 5 210 609 5.50% (56.94)% (0.01)%
2 Africa SD Sudan 45 166 389 9.22% (16.73)% (0.01)%
3 Asia YE Yemen 30 671 236 17.88% (15.79)% (0.01)%
4 Africa GW Guinea-Bissau 2 027 838 3.10% (8.14)% (0.02)%
5 South America PY Paraguay 7 245 443 6.54% (8.12)% (0.05)%
6 Asia SA Saudi Arabia 35 512 227 1.32% (6.21)% (0.02)%
7 Africa MW Malawi 19 765 647 4.14% (6.06)% (0.01)%
8 Africa GM Gambia 2 503 947 4.02% (6.00)% (0.01)%
9 Africa SN Senegal 17 311 310 2.23% (5.81)% (0.01)%
10 North America MX Mexico 130 678 852 4.15% 5.45% 0.62%
11 South America EC Ecuador 17 988 156 15.10% 5.37% 0.15%
12 Africa BF Burkina Faso 21 640 198 3.59% (5.29)% (0.01)%
13 Africa SO Somalia 16 463 253 6.62% (5.01)% (0.07)%
14 Africa EG Egypt 104 819 267 5.17% (4.64)% (0.08)%
15 Africa ER Eritrea 3 609 659 1.32% (4.60)% (0.01)%
16 Europe BA Bosnia and Herzegovina 3 254 469 4.27% 4.59% 2.49%
17 Europe BG Bulgaria 6 880 900 4.16% 4.37% 3.33%
18 Africa NA Namibia 2 600 153 3.69% 4.16% 0.27%
19 Africa DZ Algeria 44 870 592 3.14% (4.14)% (0.04)%
20 Europe MK North Macedonia 2 083 264 3.67% 4.14% 2.09%
21 North America HT Haiti 11 581 660 4.31% (4.05)% (0.06)%
22 Africa ZA South Africa 60 272 279 2.55% 4.02% 0.28%
23 North America SV El Salvador 6 528 419 3.49% 4.00% 0.49%
24 Asia ID Indonesia 277 251 787 3.81% (3.98)% (0.07)%
25 Africa CI Ivory Coast 27 218 428 2.80% (3.88)% (0.04)%
26 Europe RU Russia 146 015 214 3.62% 3.82% 1.98%
27 Africa LS Lesotho 2 164 146 3.11% 3.58% 1.31%
28 Asia SY Syria 18 047 508 4.50% 3.58% 0.18%
29 South America PE Peru 33 563 608 5.33% 3.57% 0.28%
30 Asia AF Afghanistan 40 056 379 4.81% (3.46)% (0.01)%
31 North America HN Honduras 10 107 504 2.69% 3.37% 0.66%
32 Africa ET Ethiopia 118 626 274 2.36% (3.31)% (0.10)%
33 Asia LK Sri Lanka 21 529 068 3.60% 3.30% 0.55%
34 South America AR Argentina 45 730 448 2.32% 3.22% 0.32%
35 Africa CG Congo 5 692 787 2.09% 3.13% 0.13%
36 Asia TW Taiwan 23 872 396 8.66% (3.11)% (0.00)%
37 Asia KH Cambodia 17 017 076 2.87% 3.11% 0.33%
38 Africa KE Kenya 55 295 388 2.32% (2.80)% (0.05)%
39 Africa TZ Tanzania 61 921 324 2.76% 2.74% 0.16%
40 North America JM Jamaica 2 977 839 2.89% 2.71% 1.21%
41 Asia MM Myanmar 54 880 192 4.51% 2.63% 0.31%
42 Asia AM Armenia 2 970 389 2.55% 2.58% 3.78%
43 Europe RO Romania 19 071 982 3.31% 2.53% 6.42%
44 Africa ML Mali 21 000 577 2.96% (2.49)% (0.01)%
45 Africa AO Angola 34 179 919 3.24% 2.44% 0.13%
46 Europe UA Ukraine 43 394 513 2.63% 2.43% 2.62%
47 Africa TN Tunisia 11 978 025 3.24% 2.29% 0.40%
48 South America PR Puerto Rico 3 193 694 1.54% 2.25% 0.73%
49 South America CO Colombia 51 581 952 2.19% 2.19% 0.33%
50 South America BR Brazil 214 507 883 2.44% 2.16% 1.07%
51 Europe PL Poland 37 793 112 2.85% 2.14% 0.43%
52 South America BO Bolivia 11 878 176 2.80% 2.13% 0.32%
53 Asia KG Kyrgyzstan 6 662 821 1.02% 2.09% 0.13%
54 Asia KZ Kazakhstan 19 066 152 1.73% 1.95% 1.45%
55 Africa GN Guinea 13 590 799 3.05% 1.95% 0.01%
56 Asia PK Pakistan 226 413 748 1.98% 1.93% 0.08%
57 Africa MA Morocco 37 474 385 1.27% 1.85% 0.32%
58 Europe MD Moldova 4 021 861 2.00% 1.83% 3.47%
59 Europe HU Hungary 9 628 688 1.93% 1.78% 0.70%
60 Asia VN Vietnam 98 467 720 2.54% 1.77% 0.82%
61 Africa RW Rwanda 13 365 179 1.32% 1.70% 0.14%
62 Africa ZW Zimbabwe 15 141 654 3.26% 1.70% 0.13%
63 Asia BD Bangladesh 166 804 466 1.93% 1.70% 0.06%
64 Africa CD DR Congo 93 060 408 1.00% 1.68% 0.00%
65 Asia IR Iran 85 378 270 1.53% 1.68% 1.80%
66 Asia GE Georgia 3 979 283 1.52% 1.66% 6.58%
67 Africa CM Cameroon 27 395 756 1.55% 1.63% 0.19%
68 Africa NE Niger 25 331 639 1.70% 1.62% 0.00%
69 North America GT Guatemala 18 342 249 1.83% 1.60% 1.39%
70 Africa SS South Sudan 11 362 860 1.06% 1.58% 0.02%
71 South America CL Chile 19 327 768 3.16% 1.56% 0.45%
72 Africa NG Nigeria 212 711 058 1.67% 1.51% 0.01%
73 Australia/Oceania PG Papua New Guinea 9 165 213 1.61% 1.51% 0.24%
74 North America PA Panama 4 402 253 0.98% 1.50% 0.60%
75 Asia KW Kuwait 4 351 931 0.70% 1.48% 0.12%
76 Europe GR Greece 10 357 323 1.07% 1.46% 2.49%
77 Africa LY Libya 6 991 680 1.07% 1.46% 1.27%
78 North America CR Costa Rica 5 154 089 1.13% 1.45% 4.17%
79 Africa MR Mauritania 4 806 817 1.87% 1.45% 0.12%
80 Europe LT Lithuania 2 673 216 1.40% 1.41% 7.77%
81 Asia AZ Azerbaijan 10 257 000 1.14% 1.33% 1.30%
82 Asia MY Malaysia 32 900 356 1.39% 1.31% 3.98%
83 North America US USA 333 506 023 1.09% 1.25% 3.55%
84 Africa ZM Zambia 19 045 828 2.08% 1.24% 0.03%
85 Asia IQ Iraq 41 383 846 0.76% 1.24% 0.62%
86 Europe IT Italy 60 347 076 0.93% 1.22% 0.59%
87 Asia OM Oman 5 273 654 2.01% 1.18% 0.06%
88 Europe AL Albania 2 873 741 0.82% 1.17% 2.33%
89 South America VE Venezuela 28 331 937 1.33% 1.16% 0.54%
90 Africa GH Ghana 31 907 710 1.10% 1.15% 0.07%
91 Europe ES Spain 46 778 148 0.44% 1.13% 0.47%
92 Europe HR Croatia 4 072 579 1.19% 1.10% 3.77%
93 Asia JP Japan 125 976 661 0.40% 1.09% 0.16%
94 Africa TG Togo 8 528 340 0.90% 1.04% 0.08%
95 Asia LB Lebanon 6 785 984 0.68% 1.03% 1.00%
96 Asia NP Nepal 29 811 574 1.33% 1.00% 0.29%
97 Africa MZ Mozambique 32 381 148 1.36% 0.98% 0.02%
98 Asia JO Jordan 10 333 707 1.34% 0.98% 1.06%
99 Asia IN India 1 397 494 569 1.45% 0.97% 0.19%
100 Europe SK Slovakia 5 463 055 1.00% 0.95% 2.52%
101 Asia PH Philippines 111 460 341 1.25% 0.88% 1.44%
102 Asia TH Thailand 70 025 954 1.09% 0.86% 1.85%
103 North America CA Canada 38 168 800 0.92% 0.85% 1.18%
104 Europe PT Portugal 10 158 330 0.47% 0.85% 0.75%
105 Asia TR Turkey 85 508 828 0.87% 0.77% 3.89%
106 North America CU Cuba 11 317 694 0.91% 0.73% 5.46%
107 Asia UZ Uzbekistan 34 094 090 0.76% 0.70% 0.16%
108 Europe BY Belarus 9 445 312 0.89% 0.69% 2.43%
109 Europe DE Germany 84 129 567 0.70% 0.68% 1.13%
110 Australia/Oceania AU Australia 25 881 197 0.63% 0.67% 0.89%
111 Europe RS Serbia 8 691 936 0.70% 0.67% 8.80%
112 Europe FR France 65 459 869 0.42% 0.67% 0.81%
113 Africa GA Gabon 2 293 296 0.77% 0.63% 1.08%
114 Asia MN Mongolia 3 346 285 0.42% 0.62% 7.48%
115 Africa UG Uganda 47 596 984 3.90% 0.61% 0.21%
116 South America UY Uruguay 3 489 261 1.53% 0.56% 0.39%
117 Africa MG Madagascar 28 606 504 3.73% 0.54% 0.01%
118 Europe SE Sweden 10 180 481 0.38% 0.53% 0.77%
119 Europe SI Slovenia 2 079 307 0.50% 0.51% 4.97%
120 Europe CZ Czechia 10 734 616 0.45% 0.48% 0.81%
121 Europe AT Austria 9 072 677 0.39% 0.47% 2.33%
122 Europe DK Denmark 5 818 516 0.20% 0.47% 0.94%
123 North America DO Dominican R. 10 988 140 0.59% 0.47% 0.53%
124 Asia AE Arab Emirates 10 044 401 0.26% 0.44% 0.28%
125 Europe BE Belgium 11 654 687 0.33% 0.42% 2.02%
126 Asia KR South Korea 51 326 122 0.35% 0.41% 0.46%
127 Europe GB United Kingdom 68 345 973 0.29% 0.36% 5.98%
128 Europe IE Ireland 5 008 876 0.23% 0.32% 3.24%
129 Europe CH Switzerland 8 736 238 0.25% 0.31% 1.54%
130 Asia IL Israel 9 326 000 0.33% 0.30% 4.47%
131 Asia SG Singapore 5 909 670 0.29% 0.29% 4.52%
132 Africa BW Botswana 2 412 743 1.22% 0.27% 2.69%
133 Europe FI Finland 5 551 826 0.26% 0.25% 1.06%
134 Europe NL Netherlands 17 183 790 0.15% 0.24% 1.43%
135 North America NI Nicaragua 6 726 128 0.30% 0.20% 0.11%
136 Asia LA Laos 7 411 569 0.13% 0.19% 0.71%
137 Africa BJ Benin 12 531 529 0.36% 0.18% 0.10%
138 Europe NO Norway 5 475 901 0.14% 0.14% 1.11%
139 Australia/Oceania NZ New Zealand 5 002 100 0.10% 0.13% 0.07%
140 Asia QA Qatar 2 807 805 0.14% 0.09% 0.40%
141 Africa BI Burundi 12 345 921 0.04% 0.04% 0.11%
142 Africa CF Central African R. 4 937 900 0.05% 0.00% 0.01%
143 Asia HK Hong Kong 7 575 406 0.78% 0.00% 0.01%
144 Africa TD Chad 17 031 725 0.00% 0.00% 0.00%
145 Africa SL Sierra Leone 8 185 777 1.82% 0.00% 0.00%
146 Asia PS Palestine 5 253 981 0.00% 0.00% 0.02%
147 Asia KP North Korea 25 660 000 0.00% 0.00% 0.00%
148 Europe TM Turkmenistan 6 118 000 0.00% 0.00% 0.00%
149 Asia TJ Tajikistan 9 813 281 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 33 563 608 199 770 5.952
2 Europe BA Bosnia and Herzegovina 3 254 469 11 078 3.404
3 Europe MK North Macedonia 2 083 264 6 909 3.316
4 Europe BG Bulgaria 6 880 900 22 145 3.218
5 Europe HU Hungary 9 628 688 30 351 3.152
6 Europe CZ Czechia 10 734 616 30 531 2.844
7 South America BR Brazil 214 507 883 602 046 2.807
8 South America AR Argentina 45 730 448 115 585 2.527
9 South America CO Colombia 51 581 952 126 760 2.457
10 Europe SI Slovenia 2 079 307 4 967 2.389
11 Asia GE Georgia 3 979 283 9 424 2.368
12 Europe SK Slovakia 5 463 055 12 833 2.349
13 South America PY Paraguay 7 245 443 16 208 2.237
14 Europe BE Belgium 11 654 687 25 747 2.209
15 Europe HR Croatia 4 072 579 8 877 2.180
16 Europe IT Italy 60 347 076 131 475 2.179
17 Europe RO Romania 19 071 982 41 480 2.175
18 North America MX Mexico 130 678 852 283 506 2.170
19 North America US USA 333 506 023 715 643 2.146
20 Africa TN Tunisia 11 978 025 25 056 2.092
21 Europe GB United Kingdom 68 345 973 138 385 2.025
22 Europe LT Lithuania 2 673 216 5 404 2.022
23 Europe PL Poland 37 793 112 76 111 2.014
24 South America CL Chile 19 327 768 37 586 1.945
25 Asia AM Armenia 2 970 389 5 737 1.931
26 Europe ES Spain 46 778 148 86 917 1.858
27 South America EC Ecuador 17 988 156 32 848 1.826
28 Europe MD Moldova 4 021 861 7 171 1.783
29 Europe PT Portugal 10 158 330 18 081 1.780
30 Europe FR France 65 459 869 114 885 1.755
31 South America UY Uruguay 3 489 261 6 066 1.738
32 North America PA Panama 4 402 253 7 278 1.653
33 South America BO Bolivia 11 878 176 18 819 1.584
34 Europe RU Russia 146 015 214 222 315 1.522
35 Europe GR Greece 10 357 323 15 320 1.479
36 Africa ZA South Africa 60 272 279 88 531 1.469
37 Europe SE Sweden 10 180 481 14 926 1.466
38 Asia IR Iran 85 378 270 123 679 1.449
39 Europe UA Ukraine 43 394 513 60 356 1.391
40 Africa NA Namibia 2 600 153 3 534 1.359
41 North America CR Costa Rica 5 154 089 6 744 1.309
42 Asia LB Lebanon 6 785 984 8 406 1.239
43 Europe CH Switzerland 8 736 238 10 726 1.228
44 Europe AT Austria 9 072 677 10 913 1.203
45 Europe DE Germany 84 129 567 94 554 1.124
46 Europe NL Netherlands 17 183 790 18 236 1.061
47 Europe IE Ireland 5 008 876 5 306 1.059
48 Asia JO Jordan 10 333 707 10 847 1.050
49 Europe RS Serbia 8 691 936 9 002 1.036
50 South America PR Puerto Rico 3 193 694 3 201 1.002
51 North America HN Honduras 10 107 504 10 078 0.997
52 Africa BW Botswana 2 412 743 2 386 0.989
53 Europe AL Albania 2 873 741 2 800 0.974
54 Asia KZ Kazakhstan 19 066 152 16 618 0.872
55 Asia IL Israel 9 326 000 7 985 0.856
56 Asia MY Malaysia 32 900 356 27 769 0.844
57 Asia TR Turkey 85 508 828 67 256 0.786
58 Asia OM Oman 5 273 654 4 103 0.778
59 North America GT Guatemala 18 342 249 14 209 0.775
60 North America CA Canada 38 168 800 28 381 0.744
61 North America CU Cuba 11 317 694 8 013 0.708
62 North America JM Jamaica 2 977 839 2 090 0.702
63 Africa LY Libya 6 991 680 4 849 0.694
64 Asia AZ Azerbaijan 10 257 000 6 720 0.655
65 Asia LK Sri Lanka 21 529 068 13 452 0.625
66 Asia KW Kuwait 4 351 931 2 456 0.564
67 Asia IQ Iraq 41 383 846 22 706 0.549
68 North America SV El Salvador 6 528 419 3 448 0.528
69 Asia ID Indonesia 277 251 787 142 892 0.515
70 Europe BY Belarus 9 445 312 4 370 0.463
71 Europe DK Denmark 5 818 516 2 677 0.460
72 Asia MN Mongolia 3 346 285 1 454 0.434
73 Asia KG Kyrgyzstan 6 662 821 2 631 0.395
74 Africa MA Morocco 37 474 385 14 504 0.387
75 Asia NP Nepal 29 811 574 11 278 0.378
76 North America DO Dominican R. 10 988 140 4 084 0.372
77 Asia PH Philippines 111 460 341 40 377 0.362
78 Asia MM Myanmar 54 880 192 18 287 0.333
79 Asia IN India 1 397 494 569 451 814 0.323
80 Africa ZW Zimbabwe 15 141 654 4 657 0.308
81 Africa LS Lesotho 2 164 146 655 0.303
82 Asia TH Thailand 70 025 954 18 191 0.260
83 Asia SA Saudi Arabia 35 512 227 8 757 0.247
84 Asia QA Qatar 2 807 805 607 0.216
85 Asia VN Vietnam 98 467 720 21 038 0.214
86 Asia AE Arab Emirates 10 044 401 2 117 0.211
87 Europe FI Finland 5 551 826 1 113 0.201
88 Africa ZM Zambia 19 045 828 3 658 0.192
89 Asia AF Afghanistan 40 056 379 7 238 0.181
90 Africa EG Egypt 104 819 267 17 848 0.170
91 Asia BD Bangladesh 166 804 466 27 743 0.166
92 South America VE Venezuela 28 331 937 4 681 0.165
93 Africa MR Mauritania 4 806 817 787 0.164
94 Europe NO Norway 5 475 901 884 0.161
95 Asia KH Cambodia 17 017 076 2 608 0.153
96 Asia JP Japan 125 976 661 18 078 0.143
97 Africa GM Gambia 2 503 947 339 0.135
98 Asia SY Syria 18 047 508 2 375 0.132
99 Africa DZ Algeria 44 870 592 5 867 0.131
100 Asia PK Pakistan 226 413 748 28 218 0.125
101 Africa MW Malawi 19 765 647 2 292 0.116
102 Africa SN Senegal 17 311 310 1 869 0.108
103 Africa RW Rwanda 13 365 179 1 313 0.098
104 Africa KE Kenya 55 295 388 5 207 0.094
105 Africa GA Gabon 2 293 296 209 0.091
106 Africa SO Somalia 16 463 253 1 180 0.072
107 Africa GW Guinea-Bissau 2 027 838 141 0.070
108 Africa UG Uganda 47 596 984 3 182 0.067
109 Africa SD Sudan 45 166 389 2 980 0.066
110 Africa MZ Mozambique 32 381 148 1 924 0.059
111 Asia YE Yemen 30 671 236 1 797 0.059
112 Australia/Oceania AU Australia 25 881 197 1 512 0.058
113 North America HT Haiti 11 581 660 657 0.057
114 Africa CM Cameroon 27 395 756 1 550 0.057
115 Africa LR Liberia 5 210 609 286 0.055
116 Africa ET Ethiopia 118 626 274 6 169 0.052
117 Asia KR South Korea 51 326 122 2 642 0.051
118 Africa AO Angola 34 179 919 1 655 0.048
119 Africa CG Congo 5 692 787 222 0.039
120 Asia UZ Uzbekistan 34 094 090 1 285 0.038
121 Asia SG Singapore 5 909 670 216 0.037
122 Africa GH Ghana 31 907 710 1 165 0.036
123 Asia TW Taiwan 23 872 396 846 0.035
124 Africa MG Madagascar 28 606 504 960 0.034
125 North America NI Nicaragua 6 726 128 206 0.031
126 Australia/Oceania PG Papua New Guinea 9 165 213 266 0.029
127 Africa GN Guinea 13 590 799 385 0.028
128 Asia HK Hong Kong 7 575 406 213 0.028
129 Africa TG Togo 8 528 340 237 0.028
130 Africa ML Mali 21 000 577 557 0.026
131 Africa CI Ivory Coast 27 218 428 673 0.025
132 Africa CF Central African R. 4 937 900 100 0.020
133 Africa SL Sierra Leone 8 185 777 121 0.015
134 Africa NG Nigeria 212 711 058 2 796 0.013
135 Africa BJ Benin 12 531 529 161 0.013
136 Africa ER Eritrea 3 609 659 44 0.012
137 Africa TZ Tanzania 61 921 324 724 0.012
138 Africa CD DR Congo 93 060 408 1 089 0.012
139 Africa SS South Sudan 11 362 860 130 0.011
140 Africa TD Chad 17 031 725 174 0.010
141 Africa BF Burkina Faso 21 640 198 203 0.009
142 Africa NE Niger 25 331 639 204 0.008
143 Australia/Oceania NZ New Zealand 5 002 100 28 0.006
144 Asia LA Laos 7 411 569 38 0.005
145 Asia PS Palestine 5 253 981 9 0.002
146 Africa BI Burundi 12 345 921 14 0.001
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 9 813 281 0 0.000
150 Europe TM Turkmenistan 6 118 000 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.

* ÚV lámpa (neon) használata a helységekben.
* 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"