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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": 2022-08-03 14:57
(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]

CD	Country	New Cases	New Deaths
AT	Austria	+8 475 (+6 638)	+11 (+22)
CZ	Czechia	+3 079 (+3 440)	+5 (+13)
DE	Germany	+0 (+87 681)	+0 (+210)
HU	Hungary	+21 840 (+0)	+96 (+0)
PL	Poland	+4 479 (+5 641)	+16 (+22)
SK	Slovakia, [gov], [okr]	+1 078 (+934)	+4 (+5)

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

N.	Region	Population	Last 120 days	Last 30 days	Last 7 days
1	North America	598 024 150	1.98%	2.87%	2.76%
2	Australia/Oceania	43 859 049	12.28%	9.06%	2.02%
3	Europe	756 574 482	4.37%	4.47%	1.37%
4	South America	441 406 008	1.29%	1.62%	0.66%
5	Asia	4 704 797 741	0.43%	0.43%	0.31%
6	Africa	1 406 763 609	0.05%	0.05%	0.01%

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

N.	Region	Population	Mortality last 120 days	Mortality last 30 days	New positive cases last 30 days
1	Africa	1 406 763 609	0.50%	(0.59)%	(0.05)%
2	South America	441 406 008	0.42%	0.43%	1.62%
3	North America	598 024 150	0.49%	0.40%	2.87%
4	Europe	756 574 482	0.23%	0.17%	4.47%
5	Australia/Oceania	43 859 049	0.11%	0.15%	9.06%
6	Asia	4 704 797 741	0.17%	0.13%	0.43%

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	441 406 008	1 317 013	2.984‰
2	Europe	756 574 482	1 871 931	2.474‰
3	North America	598 024 150	1 461 980	2.445‰
4	Australia/Oceania	43 859 049	16 092	0.367‰
5	Asia	4 704 797 741	1 440 518	0.306‰
6	Africa	1 406 763 609	256 765	0.182‰

COVID-19, New Cases in Countries

Filtered where Population more then 2 million, [All Countries] | Compare with [CASES]

N.	Region	CD	Country	Population	Last 120 days	Last 30 days	Last 7 days
1	Europe	GR	Greece	10 317 182	12.94%	18.73%	24.66%
2	Asia	TW	Taiwan	23 906 450	19.36%	12.69%	11.03%
3	South America	PR	Puerto Rico	3 193 694	10.93%	10.60%	9.70%
4	Asia	HK	Hong Kong	7 623 538	2.46%	5.78%	7.19%
5	Asia	IL	Israel	9 326 000	6.70%	8.65%	4.61%
6	North America	US	USA	334 776 423	2.91%	4.24%	4.57%
7	Asia	TR	Turkey	86 227 507	0.91%	1.98%	4.50%
8	Asia	KR	South Korea	51 360 968	9.60%	6.24%	4.00%
9	Europe	HU	Hungary	9 609 334	1.17%	1.86%	3.90%
10	North America	PA	Panama	4 456 110	4.04%	3.39%	3.84%
11	South America	PY	Paraguay	7 314 852	0.57%	1.94%	3.51%
12	Asia	GE	Georgia	3 973 241	0.77%	1.60%	3.37%
13	Europe	BE	Belgium	11 694 561	5.15%	5.92%	3.34%
14	Asia	SG	Singapore	5 946 078	8.97%	12.05%	2.95%
15	Australia/Oceania	AU	Australia	26 115 548	17.15%	12.05%	2.69%
16	Asia	JP	Japan	125 671 231	3.38%	5.04%	2.67%
17	Europe	IE	Ireland	5 052 560	4.66%	4.22%	2.67%
18	Europe	GB	United Kingdom	68 627 954	3.83%	3.82%	2.35%
19	Australia/Oceania	NZ	New Zealand	5 002 100	16.57%	15.03%	2.29%
20	Europe	IT	Italy	60 276 909	9.38%	11.70%	1.84%
21	Europe	DE	Germany	84 341 285	9.87%	8.76%	1.78%
22	Europe	AT	Austria	9 113 317	8.57%	9.47%	1.59%
23	South America	AR	Argentina	46 058 736	0.96%	1.08%	1.48%
24	Europe	SI	Slovenia	2 079 532	4.50%	5.37%	1.46%
25	South America	EC	Ecuador	18 200 555	0.47%	0.92%	1.44%
26	Europe	MD	Moldova	4 014 464	0.37%	0.67%	1.43%
27	Europe	FR	France	65 573 982	10.94%	11.85%	1.42%
28	Europe	RS	Serbia	8 664 181	1.12%	2.17%	1.37%
29	South America	UY	Uruguay	3 498 775	2.57%	1.81%	1.19%
30	Asia	KZ	Kazakhstan	19 244 066	0.11%	0.42%	1.13%
31	North America	CA	Canada	38 430 718	1.46%	0.81%	1.11%
32	Europe	SE	Sweden	10 230 290	0.52%	0.77%	0.98%
33	Asia	AM	Armenia	2 974 765	0.11%	0.33%	0.83%
34	Europe	RO	Romania	18 970 854	0.72%	1.49%	0.82%
35	South America	CO	Colombia	52 011 425	0.27%	0.71%	0.81%
36	South America	BO	Bolivia	12 004 365	0.74%	2.05%	0.76%
37	Europe	LT	Lithuania	2 643 349	2.06%	2.04%	0.76%
38	Europe	HR	Croatia	4 052 626	1.78%	2.34%	0.75%
39	Europe	AL	Albania	2 871 261	0.64%	1.32%	0.72%
40	Asia	MN	Mongolia	3 388 150	0.48%	0.80%	0.71%
41	Europe	PT	Portugal	10 134 876	15.21%	4.61%	0.69%
42	Asia	QA	Qatar	2 807 805	1.33%	2.13%	0.51%
43	Europe	CZ	Czechia	10 750 310	1.19%	1.18%	0.49%
44	Europe	BG	Bulgaria	6 839 692	0.77%	1.23%	0.49%
45	North America	DO	Dominican R.	11 074 270	0.42%	0.92%	0.48%
46	South America	PE	Peru	33 927 630	0.73%	1.91%	0.47%
47	South America	CL	Chile	19 457 638	3.48%	2.94%	0.44%
48	Asia	OM	Oman	5 376 889	0.10%	0.21%	0.43%
49	Europe	DK	Denmark	5 834 637	2.55%	3.04%	0.41%
50	Asia	JO	Jordan	10 413 903	0.17%	0.26%	0.40%
51	North America	HN	Honduras	10 232 418	0.16%	0.37%	0.40%
52	Europe	SK	Slovakia	5 465 143	1.45%	1.03%	0.34%
53	Asia	LB	Lebanon	6 761 883	0.82%	1.96%	0.34%
54	Africa	LY	Libya	7 065 728	0.03%	0.10%	0.34%
55	Europe	NL	Netherlands	17 213 743	2.23%	2.43%	0.33%
56	North America	MX	Mexico	131 751 514	0.61%	1.23%	0.28%
57	South America	BR	Brazil	215 703 263	1.62%	1.88%	0.27%
58	Europe	BA	Bosnia and Herzegovina	3 238 386	0.22%	0.49%	0.25%
59	Europe	CH	Switzerland	8 786 314	4.32%	5.17%	0.24%
60	Asia	MY	Malaysia	33 228 923	1.17%	0.85%	0.22%
61	North America	GT	Guatemala	18 605 212	0.91%	1.75%	0.21%
62	Europe	PL	Poland	37 760 394	0.20%	0.35%	0.20%
63	Asia	IR	Iran	86 230 076	0.15%	0.28%	0.19%
64	Europe	ES	Spain	46 792 448	3.20%	2.73%	0.18%
65	Asia	AE	Arab Emirates	10 139 064	0.85%	1.08%	0.17%
66	Europe	RU	Russia	146 064 628	0.42%	0.25%	0.17%
67	Europe	MK	North Macedonia	2 083 196	0.71%	1.41%	0.15%
68	Africa	TN	Tunisia	12 075 950	0.64%	2.09%	0.12%
69	Asia	AZ	Azerbaijan	10 329 338	0.04%	0.10%	0.09%
70	Africa	BI	Burundi	12 627 743	0.04%	0.04%	0.09%
71	Asia	KG	Kyrgyzstan	6 748 187	0.01%	0.04%	0.07%
72	Europe	NO	Norway	5 509 445	0.80%	0.38%	0.07%
73	Asia	TH	Thailand	70 164 343	1.16%	0.22%	0.06%
74	Africa	ZA	South Africa	60 864 725	0.48%	0.09%	0.06%
75	Europe	UA	Ukraine	43 187 425	0.17%	0.04%	0.06%
76	Asia	IQ	Iraq	42 100 744	0.23%	0.60%	0.05%
77	Asia	PH	Philippines	112 616 098	0.06%	0.13%	0.05%
78	North America	JM	Jamaica	2 988 057	0.54%	0.24%	0.04%
79	Asia	ID	Indonesia	279 542 137	0.05%	0.09%	0.04%
80	Asia	VN	Vietnam	99 160 960	0.91%	0.07%	0.04%
81	Asia	NP	Nepal	30 227 344	0.02%	0.05%	0.03%
82	South America	VE	Venezuela	28 268 374	0.04%	0.07%	0.03%
83	Africa	GW	Guinea-Bissau	2 064 793	0.01%	0.01%	0.02%
84	Africa	GM	Gambia	2 557 951	0.00%	0.01%	0.02%
85	Asia	IN	India	1 408 236 258	0.06%	0.09%	0.02%
86	Africa	MA	Morocco	37 820 938	0.24%	0.31%	0.02%
87	Asia	LA	Laos	7 495 255	0.35%	0.02%	0.02%
88	Africa	ZW	Zimbabwe	15 313 161	0.07%	0.03%	0.02%
89	Africa	NA	Namibia	2 636 661	0.33%	0.07%	0.01%
90	Africa	MG	Madagascar	29 172 400	0.01%	0.02%	0.01%
91	Asia	AF	Afghanistan	40 752 734	0.02%	0.02%	0.01%
92	Asia	SA	Saudi Arabia	35 942 111	0.15%	0.10%	0.01%
93	Asia	LK	Sri Lanka	21 600 042	0.01%	0.01%	0.01%
94	Africa	ER	Eritrea	3 648 560	0.01%	0.01%	0.01%
95	North America	CU	Cuba	11 312 236	0.12%	0.04%	0.01%
96	Asia	PK	Pakistan	229 817 854	0.01%	0.02%	0.01%
97	North America	NI	Nicaragua	6 788 561	0.01%	0.01%	0.01%
98	Africa	SS	South Sudan	11 466 813	0.00%	0.00%	0.01%
99	Africa	AO	Angola	34 993 794	0.01%	0.02%	0.01%
100	Africa	MW	Malawi	20 158 617	0.01%	0.01%	0.01%
101	Africa	MR	Mauritania	4 903 986	0.07%	0.14%	0.01%
102	Africa	CI	Ivory Coast	27 737 554	0.01%	0.02%	0.01%
103	Africa	ZM	Zambia	19 455 353	0.06%	0.07%	0.01%
104	Asia	BD	Bangladesh	168 103 522	0.03%	0.05%	0.00%
105	Africa	EG	Egypt	106 350 908	0.01%	0.00%	0.00%
106	Asia	KH	Cambodia	17 200 455	0.00%	0.01%	0.00%
107	Africa	DZ	Algeria	45 498 823	0.00%	0.01%	0.00%
108	Africa	NG	Nigeria	216 771 563	0.00%	0.00%	0.00%
109	Asia	SY	Syria	18 385 337	0.00%	0.00%	0.00%
110	Africa	SN	Senegal	17 662 125	0.01%	0.01%	0.00%
111	Africa	CF	Central African R.	5 004 512	0.01%	0.00%	0.00%
112	Africa	LR	Liberia	5 305 052	0.00%	0.00%	0.00%
113	Asia	UZ	Uzbekistan	34 478 582	0.01%	0.02%	0.00%
114	Australia/Oceania	PG	Papua New Guinea	9 299 707	0.01%	0.00%	0.00%
115	Africa	KE	Kenya	56 236 044	0.02%	0.02%	0.00%
116	Africa	TG	Togo	8 682 490	0.01%	0.02%	0.00%
117	Africa	MZ	Mozambique	33 077 670	0.01%	0.02%	0.00%
118	Africa	SO	Somalia	16 815 935	0.00%	0.00%	0.00%
119	Africa	SL	Sierra Leone	8 314 553	0.00%	0.00%	0.00%
120	Africa	SD	Sudan	45 979 755	0.00%	0.00%	0.00%
121	Asia	YE	Yemen	31 192 930	0.00%	0.00%	0.00%
122	Africa	BF	Burkina Faso	22 096 048	0.00%	0.00%	0.00%
123	Africa	LS	Lesotho	2 177 585	0.05%	0.02%	0.00%
124	Africa	GA	Gabon	2 335 022	0.03%	0.09%	0.00%
125	Europe	FI	Finland	5 558 625	5.49%	2.46%	0.00%
126	Africa	ET	Ethiopia	120 889 430	0.02%	0.01%	0.00%
127	Africa	UG	Uganda	48 747 095	0.01%	0.01%	0.00%
128	Asia	KW	Kuwait	4 401 998	0.46%	0.72%	0.00%
129	Africa	TZ	Tanzania	63 274 840	0.00%	0.01%	0.00%
130	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
131	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
132	Asia	TJ	Tajikistan	9 983 431	0.00%	0.00%	0.00%
133	Africa	TD	Chad	17 406 702	0.00%	0.00%	0.00%
134	North America	CR	Costa Rica	5 190 911	2.47%	4.27%	0.00%
135	Africa	NE	Niger	26 030 170	0.00%	0.00%	0.00%
136	North America	SV	El Salvador	6 554 297	0.30%	0.69%	0.00%
137	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
138	Africa	CM	Cameroon	27 920 928	0.00%	0.00%	0.00%
139	Africa	CG	Congo	5 800 725	0.01%	0.03%	0.00%
140	North America	HT	Haiti	11 691 779	0.01%	0.03%	0.00%
141	Asia	MM	Myanmar	55 168 730	0.00%	0.00%	0.00%
142	Africa	CD	DR Congo	95 227 577	0.01%	0.00%	0.00%
143	Europe	BY	Belarus	9 442 858	0.42%	0.47%	0.00%
144	Africa	ML	Mali	21 464 627	0.00%	0.00%	0.00%
145	Africa	BW	Botswana	2 450 435	0.72%	0.52%	0.00%
146	Asia	PS	Palestine	5 348 192	0.00%	0.00%	0.00%
147	Africa	RW	Rwanda	13 620 347	0.02%	0.02%	0.00%
148	Africa	GN	Guinea	13 874 077	0.01%	0.01%	0.00%
149	Africa	BJ	Benin	12 783 983	0.01%	0.00%	0.00%
150	Africa	GH	Ghana	32 422 677	0.02%	0.03%	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.	Region	CD	Country	Population	Mortality last 120 days	Mortality last 30 days	New positive cases last 30 days
1	Africa	EG	Egypt	106 350 908	2.07%	(16.09)%	(0.00)%
2	Africa	GM	Gambia	2 557 951	7.50%	(15.79)%	(0.01)%
3	Africa	GW	Guinea-Bissau	2 064 793	1.18%	(3.85)%	(0.01)%
4	Asia	LK	Sri Lanka	21 600 042	1.67%	(3.26)%	(0.01)%
5	North America	NI	Nicaragua	6 788 561	2.58%	(2.27)%	(0.01)%
6	Africa	LS	Lesotho	2 177 585	0.43%	(2.22)%	(0.02)%
7	Europe	NO	Norway	5 509 445	1.71%	2.03%	0.38%
8	Africa	NA	Namibia	2 636 661	0.59%	1.78%	0.07%
9	Africa	ZW	Zimbabwe	15 313 161	1.11%	1.71%	0.03%
10	Africa	ZA	South Africa	60 864 725	0.69%	1.52%	0.09%
11	Africa	CD	DR Congo	95 227 577	0.96%	1.50%	0.00%
12	Europe	UA	Ukraine	43 187 425	0.95%	1.46%	0.04%
13	Africa	SD	Sudan	45 979 755	3.75%	1.38%	0.00%
14	North America	JM	Jamaica	2 988 057	1.73%	1.37%	0.24%
15	Europe	BY	Belarus	9 442 858	0.75%	1.25%	0.47%
16	Africa	MW	Malawi	20 158 617	2.08%	1.18%	0.01%
17	North America	CA	Canada	38 430 718	0.84%	0.88%	0.81%
18	Europe	BA	Bosnia and Herzegovina	3 238 386	1.58%	0.87%	0.49%
19	Europe	RU	Russia	146 064 628	1.65%	0.85%	0.25%
20	Europe	SE	Sweden	10 230 290	1.64%	0.84%	0.77%
21	Europe	MD	Moldova	4 014 464	1.35%	0.81%	0.67%
22	Asia	TH	Thailand	70 164 343	0.55%	0.74%	0.22%
23	Asia	AZ	Azerbaijan	10 329 338	0.96%	0.72%	0.10%
24	Europe	HU	Hungary	9 609 334	1.17%	0.71%	1.86%
25	Asia	AF	Afghanistan	40 752 734	1.02%	0.68%	0.02%
26	Africa	RW	Rwanda	13 620 347	0.31%	0.64%	0.02%
27	South America	PY	Paraguay	7 314 852	1.74%	0.62%	1.94%
28	Africa	GN	Guinea	13 874 077	0.55%	0.61%	0.01%
29	Africa	MG	Madagascar	29 172 400	0.88%	0.57%	0.02%
30	Africa	ET	Ethiopia	120 889 430	0.26%	0.56%	0.01%
31	South America	CO	Colombia	52 011 425	0.73%	0.55%	0.71%
32	Africa	AO	Angola	34 993 794	0.37%	0.51%	0.02%
33	Africa	UG	Uganda	48 747 095	0.75%	0.47%	0.01%
34	Europe	HR	Croatia	4 052 626	0.74%	0.44%	2.34%
35	Asia	PK	Pakistan	229 817 854	0.42%	0.43%	0.02%
36	Europe	GB	United Kingdom	68 627 954	0.51%	0.42%	3.82%
37	Asia	IR	Iran	86 230 076	0.91%	0.39%	0.28%
38	North America	HN	Honduras	10 232 418	0.37%	0.39%	0.37%
39	Africa	TN	Tunisia	12 075 950	0.65%	0.38%	2.09%
40	Africa	TG	Togo	8 682 490	0.51%	0.36%	0.02%
41	North America	SV	El Salvador	6 554 297	0.33%	0.35%	0.69%
42	South America	UY	Uruguay	3 498 775	0.25%	0.35%	1.81%
43	Africa	GA	Gabon	2 335 022	0.42%	0.35%	0.09%
44	North America	US	USA	334 776 423	0.50%	0.34%	4.24%
45	Europe	ES	Spain	46 792 448	0.38%	0.34%	2.73%
46	South America	VE	Venezuela	28 268 374	0.61%	0.33%	0.07%
47	South America	BR	Brazil	215 703 263	0.45%	0.33%	1.88%
48	Europe	BG	Bulgaria	6 839 692	1.26%	0.32%	1.23%
49	South America	CL	Chile	19 457 638	0.34%	0.31%	2.94%
50	Africa	ZM	Zambia	19 455 353	0.38%	0.30%	0.07%
51	Africa	KE	Kenya	56 236 044	0.16%	0.29%	0.02%
52	Europe	SK	Slovakia	5 465 143	0.65%	0.29%	1.03%
53	North America	GT	Guatemala	18 605 212	0.89%	0.28%	1.75%
54	Europe	MK	North Macedonia	2 083 196	0.71%	0.26%	1.41%
55	Asia	BD	Bangladesh	168 103 522	0.28%	0.26%	0.05%
56	South America	EC	Ecuador	18 200 555	0.52%	0.25%	0.92%
57	Europe	PL	Poland	37 760 394	1.21%	0.25%	0.35%
58	South America	PR	Puerto Rico	3 193 694	0.17%	0.24%	10.60%
59	Asia	TW	Taiwan	23 906 450	0.18%	0.23%	12.69%
60	South America	PE	Peru	33 927 630	0.66%	0.22%	1.91%
61	Europe	IE	Ireland	5 052 560	0.28%	0.21%	4.22%
62	Africa	CG	Congo	5 800 725	0.33%	0.21%	0.03%
63	Europe	DK	Denmark	5 834 637	0.47%	0.21%	3.04%
64	Africa	LY	Libya	7 065 728	1.11%	0.20%	0.10%
65	Africa	GH	Ghana	32 422 677	0.17%	0.20%	0.03%
66	Asia	ID	Indonesia	279 542 137	0.99%	0.19%	0.09%
67	Africa	MZ	Mozambique	33 077 670	0.37%	0.19%	0.02%
68	Australia/Oceania	NZ	New Zealand	5 002 100	0.17%	0.18%	15.03%
69	Europe	RO	Romania	18 970 854	0.53%	0.18%	1.49%
70	Asia	SA	Saudi Arabia	35 942 111	0.34%	0.18%	0.10%
71	North America	PA	Panama	4 456 110	0.14%	0.18%	3.39%
72	Europe	PT	Portugal	10 134 876	0.17%	0.18%	4.61%
73	North America	MX	Mexico	131 751 514	0.23%	0.17%	1.23%
74	Asia	AM	Armenia	2 974 765	0.47%	0.17%	0.33%
75	Asia	GE	Georgia	3 973 241	0.60%	0.17%	1.60%
76	Africa	MA	Morocco	37 820 938	0.16%	0.17%	0.31%
77	Africa	CI	Ivory Coast	27 737 554	0.38%	0.17%	0.02%
78	Asia	IN	India	1 408 236 258	0.56%	0.17%	0.09%
79	South America	AR	Argentina	46 058 736	0.21%	0.17%	1.08%
80	Europe	CZ	Czechia	10 750 310	0.35%	0.16%	1.18%
81	Europe	RS	Serbia	8 664 181	0.36%	0.16%	2.17%
82	Asia	PH	Philippines	112 616 098	1.99%	0.15%	0.13%
83	Europe	BE	Belgium	11 694 561	0.23%	0.14%	5.92%
84	Asia	MY	Malaysia	33 228 923	0.16%	0.14%	0.85%
85	Europe	AL	Albania	2 871 261	0.15%	0.14%	1.32%
86	Africa	BW	Botswana	2 450 435	0.37%	0.14%	0.52%
87	Europe	GR	Greece	10 317 182	0.27%	0.14%	18.73%
88	Europe	LT	Lithuania	2 643 349	0.37%	0.14%	2.04%
89	Asia	IL	Israel	9 326 000	0.12%	0.14%	8.65%
90	Europe	SI	Slovenia	2 079 532	0.36%	0.13%	5.37%
91	Asia	HK	Hong Kong	7 623 538	0.65%	0.12%	5.78%
92	Europe	FI	Finland	5 558 625	0.41%	0.12%	2.46%
93	Australia/Oceania	AU	Australia	26 115 548	0.10%	0.11%	12.05%
94	North America	HT	Haiti	11 691 779	0.54%	0.10%	0.03%
95	Europe	IT	Italy	60 276 909	0.18%	0.10%	11.70%
96	Africa	MR	Mauritania	4 903 986	0.12%	0.08%	0.14%
97	Asia	TR	Turkey	86 227 507	0.25%	0.08%	1.98%
98	Africa	NG	Nigeria	216 771 563	0.10%	0.08%	0.00%
99	Asia	LB	Lebanon	6 761 883	0.32%	0.07%	1.96%
100	South America	BO	Bolivia	12 004 365	0.12%	0.07%	2.05%
101	Europe	FR	France	65 573 982	0.10%	0.06%	11.85%
102	Asia	NP	Nepal	30 227 344	0.07%	0.06%	0.05%
103	Europe	AT	Austria	9 113 317	0.12%	0.05%	9.47%
104	Europe	NL	Netherlands	17 213 743	0.08%	0.05%	2.43%
105	Asia	IQ	Iraq	42 100 744	0.10%	0.05%	0.60%
106	Asia	JO	Jordan	10 413 903	0.26%	0.04%	0.26%
107	Asia	KZ	Kazakhstan	19 244 066	0.14%	0.04%	0.42%
108	Asia	KR	South Korea	51 360 968	0.11%	0.04%	6.24%
109	Europe	DE	Germany	84 341 285	0.07%	0.04%	8.76%
110	Asia	JP	Japan	125 671 231	0.08%	0.04%	5.04%
111	Europe	CH	Switzerland	8 786 314	0.06%	0.03%	5.17%
112	Asia	SG	Singapore	5 946 078	0.04%	0.03%	12.05%
113	Asia	AE	Arab Emirates	10 139 064	0.03%	0.02%	1.08%
114	Asia	VN	Vietnam	99 160 960	0.03%	0.02%	0.07%
115	Asia	MN	Mongolia	3 388 150	0.07%	0.02%	0.80%
116	Asia	KW	Kuwait	4 401 998	0.01%	0.01%	0.72%
117	Asia	QA	Qatar	2 807 805	0.01%	0.01%	2.13%
118	North America	CR	Costa Rica	5 190 911	0.20%	0.00%	4.27%
119	North America	DO	Dominican R.	11 074 270	0.02%	0.00%	0.92%
120	Asia	OM	Oman	5 376 889	0.24%	0.00%	0.21%
121	Africa	BI	Burundi	12 627 743	0.00%	0.00%	0.04%
122	Asia	KG	Kyrgyzstan	6 748 187	1.41%	0.00%	0.04%
123	North America	CU	Cuba	11 312 236	0.07%	0.00%	0.04%
124	Asia	LA	Laos	7 495 255	0.18%	0.00%	0.02%
125	Asia	UZ	Uzbekistan	34 478 582	0.00%	0.00%	0.02%
126	Africa	ER	Eritrea	3 648 560	0.00%	0.00%	0.01%
127	Africa	SN	Senegal	17 662 125	0.28%	0.00%	0.01%
128	Africa	TZ	Tanzania	63 274 840	1.49%	0.00%	0.01%
129	Asia	KH	Cambodia	17 200 455	0.20%	0.00%	0.01%
130	Africa	DZ	Algeria	45 498 823	0.10%	0.00%	0.01%
131	Africa	BJ	Benin	12 783 983	0.00%	0.00%	0.00%
132	Africa	SO	Somalia	16 815 935	0.00%	0.00%	0.00%
133	Asia	SY	Syria	18 385 337	1.41%	0.00%	0.00%
134	Australia/Oceania	PG	Papua New Guinea	9 299 707	1.28%	0.00%	0.00%
135	Africa	BF	Burkina Faso	22 096 048	2.54%	0.00%	0.00%
136	Asia	MM	Myanmar	55 168 730	0.04%	0.00%	0.00%
137	Africa	SS	South Sudan	11 466 813	0.00%	0.00%	0.00%
138	Africa	SL	Sierra Leone	8 314 553	0.00%	0.00%	0.00%
139	Africa	CF	Central African R.	5 004 512	0.00%	0.00%	0.00%
140	Africa	ML	Mali	21 464 627	1.22%	0.00%	0.00%
141	Africa	LR	Liberia	5 305 052	0.00%	0.00%	0.00%
142	Asia	YE	Yemen	31 192 930	13.73%	0.00%	0.00%
143	Africa	NE	Niger	26 030 170	0.99%	0.00%	0.00%
144	Africa	TD	Chad	17 406 702	1.85%	0.00%	0.00%
145	Africa	CM	Cameroon	27 920 928	0.60%	0.00%	0.00%
146	Asia	PS	Palestine	5 348 192	0.00%	0.00%	0.00%
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	9 983 431	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.	Region	CD	Country	Population	Deaths	*1000Deaths/Pop.**
1	South America	PE	Peru	33 927 630	213 937	6.306‰
2	Europe	BG	Bulgaria	6 839 692	37 329	5.458‰
3	Europe	BA	Bosnia and Herzegovina	3 238 386	15 840	4.891‰
4	Europe	HU	Hungary	9 609 334	46 832	4.874‰
5	Europe	MK	North Macedonia	2 083 196	9 353	4.490‰
6	Asia	GE	Georgia	3 973 241	16 854	4.242‰
7	Europe	HR	Croatia	4 052 626	16 202	3.998‰
8	Europe	SI	Slovenia	2 079 532	7 881	3.790‰
9	Europe	CZ	Czechia	10 750 310	40 385	3.757‰
10	Europe	SK	Slovakia	5 465 143	20 197	3.696‰
11	Europe	LT	Lithuania	2 643 349	9 198	3.480‰
12	Europe	RO	Romania	18 970 854	65 879	3.473‰
13	South America	BR	Brazil	215 703 263	676 488	3.136‰
14	Europe	PL	Poland	37 760 394	116 514	3.086‰
15	South America	CL	Chile	19 457 638	59 223	3.044‰
16	North America	US	USA	334 776 423	1 015 897	3.035‰
17	Europe	GR	Greece	10 317 182	30 707	2.976‰
18	Asia	AM	Armenia	2 974 765	8 628	2.900‰
19	Europe	MD	Moldova	4 014 464	11 592	2.888‰
20	Europe	IT	Italy	60 276 909	170 717	2.832‰
21	South America	AR	Argentina	46 058 736	129 202	2.805‰
22	Europe	BE	Belgium	11 694 561	32 118	2.746‰
23	South America	CO	Colombia	52 011 425	140 365	2.699‰
24	Europe	GB	United Kingdom	68 627 954	182 727	2.663‰
25	Europe	RU	Russia	146 064 628	382 123	2.616‰
26	South America	PY	Paraguay	7 314 852	19 083	2.609‰
27	Europe	UA	Ukraine	43 187 425	108 699	2.517‰
28	North America	MX	Mexico	131 751 514	326 897	2.481‰
29	Europe	PT	Portugal	10 134 876	24 527	2.420‰
30	Africa	TN	Tunisia	12 075 950	28 951	2.397‰
31	Europe	ES	Spain	46 792 448	109 642	2.343‰
32	Europe	FR	France	65 573 982	147 926	2.256‰
33	Europe	AT	Austria	9 113 317	20 237	2.221‰
34	South America	UY	Uruguay	3 498 775	7 387	2.111‰
35	South America	EC	Ecuador	18 200 555	35 781	1.966‰
36	North America	PA	Panama	4 456 110	8 395	1.884‰
37	Europe	SE	Sweden	10 230 290	19 249	1.882‰
38	Europe	RS	Serbia	8 664 181	16 203	1.870‰
39	South America	BO	Bolivia	12 004 365	22 002	1.833‰
40	Europe	DE	Germany	84 341 285	143 271	1.699‰
41	Africa	ZA	South Africa	60 864 725	101 942	1.675‰
42	North America	CR	Costa Rica	5 190 911	8 525	1.642‰
43	Asia	IR	Iran	86 230 076	141 606	1.642‰
44	Asia	LB	Lebanon	6 761 883	10 498	1.552‰
45	Africa	NA	Namibia	2 636 661	4 069	1.543‰
46	Europe	CH	Switzerland	8 786 314	13 387	1.524‰
47	Europe	IE	Ireland	5 052 560	7 620	1.508‰
48	South America	PR	Puerto Rico	3 193 694	4 708	1.474‰
49	Asia	JO	Jordan	10 413 903	14 070	1.351‰
50	Europe	NL	Netherlands	17 213 743	22 453	1.304‰
51	Asia	HK	Hong Kong	7 623 538	9 520	1.249‰
52	Europe	AL	Albania	2 871 261	3 519	1.226‰
53	Asia	IL	Israel	9 326 000	11 407	1.223‰
54	Asia	TR	Turkey	86 227 507	99 184	1.150‰
55	Europe	DK	Denmark	5 834 637	6 586	1.129‰
56	Africa	BW	Botswana	2 450 435	2 752	1.123‰
57	North America	CA	Canada	38 430 718	42 148	1.097‰
58	Asia	MY	Malaysia	33 228 923	35 896	1.080‰
59	North America	HN	Honduras	10 232 418	10 937	1.069‰
60	North America	JM	Jamaica	2 988 057	3 175	1.063‰
61	North America	GT	Guatemala	18 605 212	18 873	1.014‰
62	Asia	KZ	Kazakhstan	19 244 066	19 020	0.988‰
63	Asia	AZ	Azerbaijan	10 329 338	9 733	0.942‰
64	Africa	LY	Libya	7 065 728	6 431	0.910‰
65	Europe	FI	Finland	5 558 625	5 012	0.902‰
66	Asia	OM	Oman	5 376 889	4 628	0.861‰
67	Asia	LK	Sri Lanka	21 600 042	16 542	0.766‰
68	North America	CU	Cuba	11 312 236	8 529	0.754‰
69	Europe	BY	Belarus	9 442 858	7 118	0.754‰
70	Europe	NO	Norway	5 509 445	3 596	0.653‰
71	North America	SV	El Salvador	6 554 297	4 186	0.639‰
72	Asia	MN	Mongolia	3 388 150	2 119	0.625‰
73	Asia	IQ	Iraq	42 100 744	25 279	0.600‰
74	Asia	KW	Kuwait	4 401 998	2 556	0.581‰
75	Asia	ID	Indonesia	279 542 137	156 898	0.561‰
76	Asia	PH	Philippines	112 616 098	60 654	0.539‰
77	Asia	KR	South Korea	51 360 968	24 851	0.484‰
78	Asia	TH	Thailand	70 164 343	31 105	0.443‰
79	Asia	KG	Kyrgyzstan	6 748 187	2 991	0.443‰
80	Asia	VN	Vietnam	99 160 960	43 091	0.435‰
81	Africa	MA	Morocco	37 820 938	16 202	0.428‰
82	Australia/Oceania	AU	Australia	26 115 548	11 033	0.422‰
83	North America	DO	Dominican R.	11 074 270	4 383	0.396‰
84	Asia	NP	Nepal	30 227 344	11 954	0.396‰
85	Australia/Oceania	NZ	New Zealand	5 002 100	1 918	0.383‰
86	Asia	TW	Taiwan	23 906 450	9 026	0.378‰
87	Asia	IN	India	1 408 236 258	525 917	0.373‰
88	Africa	ZW	Zimbabwe	15 313 161	5 570	0.364‰
89	Asia	MM	Myanmar	55 168 730	19 434	0.352‰
90	Africa	LS	Lesotho	2 177 585	702	0.322‰
91	Asia	SA	Saudi Arabia	35 942 111	9 236	0.257‰
92	Asia	JP	Japan	125 671 231	31 860	0.254‰
93	Asia	SG	Singapore	5 946 078	1 488	0.250‰
94	Asia	QA	Qatar	2 807 805	680	0.242‰
95	Africa	EG	Egypt	106 350 908	24 750	0.233‰
96	Asia	AE	Arab Emirates	10 139 064	2 328	0.230‰
97	Africa	ZM	Zambia	19 455 353	4 013	0.206‰
98	South America	VE	Venezuela	28 268 374	5 753	0.203‰
99	Africa	MR	Mauritania	4 903 986	986	0.201‰
100	Asia	AF	Afghanistan	40 752 734	7 737	0.190‰
101	Asia	KH	Cambodia	17 200 455	3 056	0.178‰
102	Asia	BD	Bangladesh	168 103 522	29 259	0.174‰
103	Asia	SY	Syria	18 385 337	3 150	0.171‰
104	Africa	DZ	Algeria	45 498 823	6 875	0.151‰
105	Africa	GM	Gambia	2 557 951	368	0.144‰
106	Asia	PK	Pakistan	229 817 854	30 461	0.133‰
107	Africa	MW	Malawi	20 158 617	2 651	0.132‰
108	Africa	GA	Gabon	2 335 022	306	0.131‰
109	Africa	SN	Senegal	17 662 125	1 968	0.111‰
110	Africa	SD	Sudan	45 979 755	4 956	0.108‰
111	Africa	RW	Rwanda	13 620 347	1 466	0.108‰
112	Asia	LA	Laos	7 495 255	757	0.101‰
113	Africa	KE	Kenya	56 236 044	5 670	0.101‰
114	Africa	GW	Guinea-Bissau	2 064 793	173	0.084‰
115	Africa	SO	Somalia	16 815 935	1 361	0.081‰
116	Africa	UG	Uganda	48 747 095	3 626	0.074‰
117	North America	HT	Haiti	11 691 779	838	0.072‰
118	Australia/Oceania	PG	Papua New Guinea	9 299 707	662	0.071‰
119	Africa	CM	Cameroon	27 920 928	1 931	0.069‰
120	Asia	YE	Yemen	31 192 930	2 149	0.069‰
121	Africa	MZ	Mozambique	33 077 670	2 215	0.067‰
122	Africa	CG	Congo	5 800 725	386	0.067‰
123	Africa	ET	Ethiopia	120 889 430	7 564	0.063‰
124	Africa	LR	Liberia	5 305 052	294	0.055‰
125	Africa	AO	Angola	34 993 794	1 912	0.055‰
126	Africa	MG	Madagascar	29 172 400	1 406	0.048‰
127	Asia	UZ	Uzbekistan	34 478 582	1 637	0.048‰
128	Africa	GH	Ghana	32 422 677	1 456	0.045‰
129	North America	NI	Nicaragua	6 788 561	244	0.036‰
130	Africa	ML	Mali	21 464 627	737	0.034‰
131	Africa	GN	Guinea	13 874 077	445	0.032‰
132	Africa	TG	Togo	8 682 490	277	0.032‰
133	Africa	CI	Ivory Coast	27 737 554	808	0.029‰
134	Africa	ER	Eritrea	3 648 560	103	0.028‰
135	Africa	CF	Central African R.	5 004 512	113	0.023‰
136	Africa	BF	Burkina Faso	22 096 048	387	0.018‰
137	Africa	SL	Sierra Leone	8 314 553	125	0.015‰
138	Africa	CD	DR Congo	95 227 577	1 390	0.015‰
139	Africa	NG	Nigeria	216 771 563	3 146	0.015‰
140	Africa	TZ	Tanzania	63 274 840	841	0.013‰
141	Africa	BJ	Benin	12 783 983	163	0.013‰
142	Africa	SS	South Sudan	11 466 813	138	0.012‰
143	Africa	NE	Niger	26 030 170	311	0.012‰
144	Africa	TD	Chad	17 406 702	193	0.011‰
145	Asia	PS	Palestine	5 348 192	8	0.002‰
146	Africa	BI	Burundi	12 627 743	15	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	9 983 431	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.

(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]

Ivermectin 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. 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:

"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"