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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": 2022-06-14 11:23
(For some countries, the data from the WHO and from "Our World in Data by Johns Hopkins University" and from "WorldoMeter" are completely different, such as: Israel.)
What can help, is at the bottom of this page. I recommend searching here "Global literature on coronavirus disease" or here "Google Scholar".

COVID-19, Selected Countries by WorldoMeter

Our World in Data, (2 days late data visualization) [CASES], [DEATHS], [VACCINATION]

CD	Country	New Cases	New Deaths
AT	Austria	+0 (+2 905)	+0 (+2)
CZ	Czechia	+459 (+61)	+0 (+0)
DE	Germany	+0 (+38 664)	+0 (+30)
HU	Hungary	+0 (+0)	+0 (+0)
PL	Poland	+321 (+45)	+9 (+0)
SK	Slovakia, [gov], [okr]	+206 (+28)	+3 (+0)

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

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

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

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

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	440 920 772	1 304 837	2.959‰
2	Europe	756 513 313	1 849 043	2.444‰
3	North America	597 658 595	1 443 299	2.415‰
4	Australia/Oceania	43 789 847	13 387	0.306‰
5	Asia	4 700 205 500	1 429 806	0.304‰
6	Africa	1 402 366 450	255 421	0.182‰

COVID-19, New Cases in Countries

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

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

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

Filtered where Population more then 2 million, [All Countries] | Compare with [DEATHS]! and with [FATALITY RATE]

N.	Region	CD	Country	Population	Mortality last 120 days	Mortality last 30 days	New positive cases last 30 days
1	Africa	EG	Egypt	106 086 832	1.86%	(27.57)%	(0.00)%
2	Africa	SD	Sudan	45 839 520	36.05%	(5.00)%	(0.00)%
3	Africa	TZ	Tanzania	63 041 475	2.84%	(3.49)%	(0.01)%
4	Africa	MW	Malawi	20 090 863	3.98%	(3.48)%	(0.00)%
5	North America	NI	Nicaragua	6 777 797	2.22%	(3.45)%	(0.01)%
6	Africa	TN	Tunisia	12 059 066	1.54%	(3.38)%	(0.08)%
7	Asia	AZ	Azerbaijan	10 316 866	0.68%	(2.99)%	(0.01)%
8	North America	GT	Guatemala	18 559 873	1.05%	2.89%	0.34%
9	Europe	MD	Moldova	4 015 739	1.17%	2.58%	0.11%
10	Asia	LK	Sri Lanka	21 587 805	1.57%	(2.28)%	(0.01)%
11	Europe	BG	Bulgaria	6 846 797	1.64%	2.27%	0.33%
12	Asia	ID	Indonesia	279 147 249	0.74%	(2.23)%	(0.02)%
13	Africa	BW	Botswana	2 443 936	0.20%	2.22%	0.69%
14	Europe	NO	Norway	5 503 661	0.29%	2.15%	0.49%
15	Europe	BA	Bosnia and Herzegovina	3 241 159	3.53%	(2.11)%	(0.07)%
16	Europe	PL	Poland	37 766 035	1.00%	(2.00)%	(0.07)%
17	South America	PY	Paraguay	7 302 885	2.16%	1.94%	0.07%
18	Europe	RU	Russia	146 056 108	0.73%	1.89%	0.33%
19	South America	PE	Peru	33 864 868	2.20%	1.77%	0.20%
20	Asia	AM	Armenia	2 974 010	1.39%	1.74%	0.01%
21	Asia	IR	Iran	86 083 213	1.17%	1.68%	0.03%
22	Africa	ML	Mali	21 384 618	2.09%	1.63%	0.00%
23	Asia	LB	Lebanon	6 766 038	0.47%	1.62%	0.19%
24	Europe	SE	Sweden	10 221 702	1.12%	1.60%	0.23%
25	Europe	SK	Slovakia	5 464 783	0.30%	1.47%	0.32%
26	Europe	HU	Hungary	9 612 671	1.39%	1.37%	0.48%
27	Asia	AF	Afghanistan	40 632 673	1.48%	1.30%	0.02%
28	Europe	UA	Ukraine	43 223 130	0.79%	1.29%	0.08%
29	Africa	MG	Madagascar	29 074 832	2.00%	1.24%	0.00%
30	North America	CA	Canada	38 385 559	0.83%	1.21%	0.75%
31	North America	JM	Jamaica	2 986 295	2.62%	1.01%	1.01%
32	Africa	UG	Uganda	48 548 800	1.03%	0.94%	0.00%
33	Europe	RO	Romania	18 988 290	0.81%	0.91%	0.21%
34	Africa	MZ	Mozambique	32 957 580	1.03%	0.89%	0.01%
35	Europe	MK	North Macedonia	2 083 208	1.53%	0.88%	0.37%
36	Europe	HR	Croatia	4 056 066	1.00%	0.88%	0.86%
37	Australia/Oceania	PG	Papua New Guinea	9 276 518	0.69%	0.86%	0.03%
38	South America	VE	Venezuela	28 279 333	0.63%	0.86%	0.02%
39	Europe	DK	Denmark	5 831 858	0.20%	0.81%	1.22%
40	Africa	SN	Senegal	17 601 640	1.07%	0.80%	0.00%
41	Asia	IN	India	1 406 384 242	1.73%	0.68%	0.03%
42	Europe	GB	United Kingdom	68 579 336	0.42%	0.66%	1.05%
43	Asia	GE	Georgia	3 974 283	0.37%	0.64%	0.23%
44	Africa	ZW	Zimbabwe	15 283 591	0.61%	0.64%	0.13%
45	Europe	LT	Lithuania	2 648 498	0.33%	0.62%	0.55%
46	Asia	TH	Thailand	70 140 482	0.40%	0.61%	0.65%
47	Europe	RS	Serbia	8 668 966	0.67%	0.60%	0.37%
48	Asia	KZ	Kazakhstan	19 213 392	0.67%	0.57%	0.01%
49	Africa	ZA	South Africa	60 762 580	1.31%	0.56%	0.60%
50	South America	BO	Bolivia	11 982 608	1.69%	0.49%	0.19%
51	South America	BR	Brazil	215 497 163	0.63%	0.47%	1.28%
52	Asia	BD	Bangladesh	167 879 547	0.34%	0.45%	0.00%
53	Europe	SI	Slovenia	2 079 493	0.45%	0.45%	1.70%
54	Europe	GR	Greece	10 324 103	0.37%	0.43%	4.48%
55	Europe	CZ	Czechia	10 747 604	0.33%	0.41%	0.28%
56	North America	HN	Honduras	10 210 881	1.11%	0.38%	0.05%
57	Asia	SA	Saudi Arabia	35 867 993	0.32%	0.35%	0.23%
58	Asia	HK	Hong Kong	7 615 239	0.76%	0.32%	0.61%
59	South America	EC	Ecuador	18 163 935	0.52%	0.32%	0.32%
60	Europe	ES	Spain	46 789 983	0.37%	0.32%	2.42%
61	North America	SV	El Salvador	6 549 835	0.51%	0.30%	0.12%
62	Europe	IT	Italy	60 289 007	0.28%	0.30%	4.20%
63	South America	CO	Colombia	51 937 378	1.88%	0.30%	0.11%
64	North America	US	USA	334 776 423	1.04%	0.30%	3.20%
65	Asia	OM	Oman	5 359 090	0.15%	0.29%	0.03%
66	Africa	CD	DR Congo	94 853 927	0.69%	0.28%	0.01%
67	Africa	ZM	Zambia	19 384 745	0.35%	0.28%	0.05%
68	Europe	BE	Belgium	11 687 686	0.26%	0.27%	1.54%
69	Africa	NG	Nigeria	216 071 476	0.16%	0.26%	0.00%
70	Asia	TR	Turkey	86 103 597	0.30%	0.25%	0.10%
71	North America	MX	Mexico	131 566 572	2.02%	0.24%	0.14%
72	Africa	NA	Namibia	2 630 367	0.57%	0.22%	0.76%
73	Europe	FR	France	65 554 307	0.16%	0.22%	3.97%
74	Asia	IQ	Iraq	41 977 141	0.64%	0.21%	0.04%
75	Africa	MA	Morocco	37 761 188	1.30%	0.21%	0.11%
76	Africa	LS	Lesotho	2 175 268	0.23%	0.20%	0.09%
77	Asia	LA	Laos	7 480 827	0.22%	0.19%	0.04%
78	South America	CL	Chile	19 435 247	1.26%	0.19%	3.95%
79	Europe	FI	Finland	5 557 453	0.39%	0.19%	2.70%
80	Asia	PK	Pakistan	229 230 939	0.86%	0.18%	0.00%
81	Asia	MY	Malaysia	33 172 274	0.22%	0.17%	0.63%
82	Asia	PH	Philippines	112 416 830	6.73%	0.17%	0.02%
83	North America	CR	Costa Rica	5 184 562	0.41%	0.17%	2.99%
84	Australia/Oceania	NZ	New Zealand	5 002 100	0.10%	0.17%	16.25%
85	Europe	IE	Ireland	5 045 028	0.25%	0.16%	2.78%
86	Asia	JO	Jordan	10 400 076	0.15%	0.15%	0.05%
87	Africa	ET	Ethiopia	120 499 230	1.06%	0.15%	0.02%
88	Asia	TW	Taiwan	23 900 579	0.14%	0.15%	37.41%
89	South America	UY	Uruguay	3 497 135	0.24%	0.14%	3.71%
90	South America	PR	Puerto Rico	3 193 694	0.18%	0.14%	14.06%
91	Europe	PT	Portugal	10 138 920	0.16%	0.13%	25.87%
92	South America	AR	Argentina	46 002 135	0.25%	0.13%	1.52%
93	Africa	KE	Kenya	56 073 862	0.57%	0.11%	0.02%
94	Europe	AT	Austria	9 106 310	0.11%	0.11%	3.86%
95	Europe	NL	Netherlands	17 208 579	0.03%	0.11%	0.82%
96	Asia	KR	South Korea	51 354 960	0.10%	0.11%	3.56%
97	North America	PA	Panama	4 446 824	0.24%	0.10%	7.21%
98	Australia/Oceania	AU	Australia	26 075 142	0.09%	0.10%	16.81%
99	Asia	JP	Japan	125 723 891	0.19%	0.10%	2.30%
100	Asia	IL	Israel	9 326 000	0.12%	0.08%	3.77%
101	Europe	CH	Switzerland	8 777 680	0.06%	0.05%	1.28%
102	Asia	MN	Mongolia	3 380 931	0.06%	0.04%	0.60%
103	Europe	DE	Germany	84 304 782	0.10%	0.04%	4.97%
104	North America	DO	Dominican R.	11 059 420	0.14%	0.04%	0.32%
105	Asia	VN	Vietnam	99 041 436	0.05%	0.03%	0.15%
106	Asia	SG	Singapore	5 939 801	0.05%	0.03%	6.96%
107	Asia	AE	Arab Emirates	10 122 743	0.04%	0.03%	0.66%
108	Asia	QA	Qatar	2 807 805	0.09%	0.00%	0.95%
109	Asia	KW	Kuwait	4 393 366	0.06%	0.00%	0.32%
110	Europe	AL	Albania	2 871 689	0.70%	0.00%	0.17%
111	North America	CU	Cuba	11 313 177	0.11%	0.00%	0.04%
112	Africa	MR	Mauritania	4 887 233	1.34%	0.00%	0.03%
113	Africa	BI	Burundi	12 579 153	0.00%	0.00%	0.03%
114	Africa	GA	Gabon	2 327 828	0.38%	0.00%	0.02%
115	Africa	GW	Guinea-Bissau	2 058 422	1.35%	0.00%	0.02%
116	Africa	RW	Rwanda	13 576 353	0.82%	0.00%	0.01%
117	Africa	BJ	Benin	12 740 457	0.00%	0.00%	0.01%
118	Africa	LY	Libya	7 052 961	0.56%	0.00%	0.01%
119	North America	HT	Haiti	11 672 793	2.33%	0.00%	0.01%
120	Africa	TG	Togo	8 655 912	0.37%	0.00%	0.01%
121	Africa	CI	Ivory Coast	27 648 050	0.72%	0.00%	0.01%
122	Africa	GH	Ghana	32 333 890	0.18%	0.00%	0.01%
123	Asia	UZ	Uzbekistan	34 412 290	0.35%	0.00%	0.01%
124	Africa	CG	Congo	5 782 115	2.98%	0.00%	0.01%
125	Africa	GN	Guinea	13 825 236	1.10%	0.00%	0.00%
126	Africa	SO	Somalia	16 755 128	4.22%	0.00%	0.00%
127	Asia	NP	Nepal	30 155 659	0.47%	0.00%	0.00%
128	Africa	SS	South Sudan	11 448 890	0.13%	0.00%	0.00%
129	Africa	AO	Angola	34 853 471	0.14%	0.00%	0.00%
130	Asia	MM	Myanmar	55 118 982	0.16%	0.00%	0.00%
131	Africa	ER	Eritrea	3 641 853	0.00%	0.00%	0.00%
132	Africa	DZ	Algeria	45 390 507	1.84%	0.00%	0.00%
133	Asia	SY	Syria	18 327 090	3.04%	0.00%	0.00%
134	Africa	LR	Liberia	5 288 769	3.57%	0.00%	0.00%
135	Africa	NE	Niger	25 909 734	2.01%	0.00%	0.00%
136	Africa	CF	Central African R.	4 993 027	0.00%	0.00%	0.00%
137	Africa	GM	Gambia	2 548 640	0.00%	0.00%	0.00%
138	Asia	YE	Yemen	31 102 983	8.20%	0.00%	0.00%
139	Africa	TD	Chad	17 342 051	1.47%	0.00%	0.00%
140	Africa	CM	Cameroon	27 830 381	0.94%	0.00%	0.00%
141	Europe	BY	Belarus	9 443 281	0.35%	0.00%	0.00%
142	Asia	KH	Cambodia	17 168 838	0.28%	0.00%	0.00%
143	Africa	BF	Burkina Faso	22 017 453	4.17%	0.00%	0.00%
144	Asia	KG	Kyrgyzstan	6 733 469	4.11%	0.00%	0.00%
145	Africa	SL	Sierra Leone	8 292 350	0.00%	0.00%	0.00%
146	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
147	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
148	Asia	TJ	Tajikistan	9 954 095	0.00%	0.00%	0.00%
149	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
150	Asia	PS	Palestine	5 331 948	0.00%	0.00%	0.00%

COVID-19, Total Mortality rate (from population) in Countries

Filtered where Population more then 2 million, [All Countries] | Compare with [DEATHS] ! and with [CUMULATIVE DEATHS]

N.	Region	CD	Country	Population	Deaths	*1000Deaths/Pop.**
1	South America	PE	Peru	33 864 868	213 303	6.299‰
2	Europe	BG	Bulgaria	6 846 797	37 204	5.434‰
3	Europe	BA	Bosnia and Herzegovina	3 241 159	15 793	4.873‰
4	Europe	HU	Hungary	9 612 671	46 571	4.845‰
5	Europe	MK	North Macedonia	2 083 208	9 316	4.472‰
6	Asia	GE	Georgia	3 974 283	16 835	4.236‰
7	Europe	HR	Croatia	4 056 066	16 019	3.949‰
8	Europe	SI	Slovenia	2 079 493	7 805	3.753‰
9	Europe	CZ	Czechia	10 747 604	40 302	3.750‰
10	Europe	SK	Slovakia	5 464 783	20 119	3.682‰
11	Europe	RO	Romania	18 988 290	65 714	3.461‰
12	Europe	LT	Lithuania	2 648 498	9 155	3.457‰
13	South America	BR	Brazil	215 497 163	667 700	3.098‰
14	Europe	PL	Poland	37 766 035	116 380	3.082‰
15	North America	US	USA	334 776 423	1 000 967	2.990‰
16	South America	CL	Chile	19 435 247	58 050	2.987‰
17	Europe	GR	Greece	10 324 103	30 020	2.908‰
18	Asia	AM	Armenia	2 974 010	8 625	2.900‰
19	Europe	MD	Moldova	4 015 739	11 554	2.877‰
20	South America	AR	Argentina	46 002 135	128 973	2.804‰
21	Europe	IT	Italy	60 289 007	167 432	2.777‰
22	Europe	BE	Belgium	11 687 686	31 816	2.722‰
23	South America	CO	Colombia	51 937 378	139 867	2.693‰
24	Europe	GB	United Kingdom	68 579 336	179 102	2.612‰
25	Europe	RU	Russia	146 056 108	380 137	2.603‰
26	South America	PY	Paraguay	7 302 885	18 911	2.590‰
27	Europe	UA	Ukraine	43 223 130	108 605	2.513‰
28	North America	MX	Mexico	131 566 572	325 066	2.471‰
29	Africa	TN	Tunisia	12 059 066	28 648	2.376‰
30	Europe	PT	Portugal	10 138 920	23 531	2.321‰
31	Europe	ES	Spain	46 789 983	107 108	2.289‰
32	Europe	FR	France	65 554 307	145 520	2.220‰
33	Europe	AT	Austria	9 106 310	19 969	2.193‰
34	South America	UY	Uruguay	3 497 135	7 262	2.077‰
35	South America	EC	Ecuador	18 163 935	35 649	1.963‰
36	North America	PA	Panama	4 446 824	8 292	1.865‰
37	Europe	SE	Sweden	10 221 702	19 049	1.864‰
38	Europe	RS	Serbia	8 668 966	16 101	1.857‰
39	South America	BO	Bolivia	11 982 608	21 950	1.832‰
40	Africa	ZA	South Africa	60 762 580	101 502	1.671‰
41	Europe	DE	Germany	84 304 782	139 837	1.659‰
42	North America	CR	Costa Rica	5 184 562	8 525	1.644‰
43	Asia	IR	Iran	86 083 213	141 352	1.642‰
44	Asia	LB	Lebanon	6 766 038	10 446	1.544‰
45	Africa	NA	Namibia	2 630 367	4 042	1.537‰
46	Europe	CH	Switzerland	8 777 680	13 267	1.511‰
47	Europe	IE	Ireland	5 045 028	7 416	1.470‰
48	South America	PR	Puerto Rico	3 193 694	4 427	1.386‰
49	Asia	JO	Jordan	10 400 076	14 068	1.353‰
50	Europe	NL	Netherlands	17 208 579	22 332	1.298‰
51	Asia	HK	Hong Kong	7 615 239	9 390	1.233‰
52	Europe	AL	Albania	2 871 689	3 497	1.218‰
53	Asia	IL	Israel	9 326 000	10 882	1.167‰
54	Asia	TR	Turkey	86 103 597	98 969	1.149‰
55	Africa	BW	Botswana	2 443 936	2 701	1.105‰
56	Europe	DK	Denmark	5 831 858	6 414	1.100‰
57	North America	CA	Canada	38 385 559	41 356	1.077‰
58	Asia	MY	Malaysia	33 172 274	35 716	1.077‰
59	North America	HN	Honduras	10 210 881	10 902	1.068‰
60	North America	JM	Jamaica	2 986 295	3 080	1.031‰
61	Asia	KZ	Kazakhstan	19 213 392	19 017	0.990‰
62	North America	GT	Guatemala	18 559 873	18 250	0.983‰
63	Asia	AZ	Azerbaijan	10 316 866	9 715	0.942‰
64	Africa	LY	Libya	7 052 961	6 430	0.912‰
65	Europe	FI	Finland	5 557 453	4 714	0.848‰
66	Asia	OM	Oman	5 359 090	4 260	0.795‰
67	Asia	LK	Sri Lanka	21 587 805	16 519	0.765‰
68	North America	CU	Cuba	11 313 177	8 529	0.754‰
69	Europe	BY	Belarus	9 443 281	6 978	0.739‰
70	North America	SV	El Salvador	6 549 835	4 134	0.631‰
71	Asia	MN	Mongolia	3 380 931	2 115	0.626‰
72	Asia	IQ	Iraq	41 977 141	25 223	0.601‰
73	Europe	NO	Norway	5 503 661	3 210	0.583‰
74	Asia	KW	Kuwait	4 393 366	2 555	0.582‰
75	Asia	ID	Indonesia	279 147 249	156 652	0.561‰
76	Asia	PH	Philippines	112 416 830	60 461	0.538‰
77	Asia	KR	South Korea	51 354 960	24 390	0.475‰
78	Asia	KG	Kyrgyzstan	6 733 469	2 991	0.444‰
79	Asia	VN	Vietnam	99 041 436	43 083	0.435‰
80	Asia	TH	Thailand	70 140 482	30 368	0.433‰
81	Africa	MA	Morocco	37 761 188	16 082	0.426‰
82	Asia	NP	Nepal	30 155 659	11 952	0.396‰
83	North America	DO	Dominican R.	11 059 420	4 379	0.396‰
84	Asia	IN	India	1 406 384 242	524 777	0.373‰
85	Africa	ZW	Zimbabwe	15 283 591	5 515	0.361‰
86	Asia	MM	Myanmar	55 118 982	19 434	0.353‰
87	Australia/Oceania	AU	Australia	26 075 142	8 988	0.345‰
88	Africa	LS	Lesotho	2 175 268	699	0.321‰
89	Australia/Oceania	NZ	New Zealand	5 002 100	1 286	0.257‰
90	Asia	SA	Saudi Arabia	35 867 993	9 175	0.256‰
91	Asia	JP	Japan	125 723 891	30 910	0.246‰
92	Asia	QA	Qatar	2 807 805	677	0.241‰
93	Asia	SG	Singapore	5 939 801	1 398	0.235‰
94	Africa	EG	Egypt	106 086 832	24 720	0.233‰
95	Asia	AE	Arab Emirates	10 122 743	2 305	0.228‰
96	Africa	ZM	Zambia	19 384 745	3 989	0.206‰
97	South America	VE	Venezuela	28 279 333	5 722	0.202‰
98	Africa	MR	Mauritania	4 887 233	982	0.201‰
99	Asia	AF	Afghanistan	40 632 673	7 710	0.190‰
100	Asia	TW	Taiwan	23 900 579	4 403	0.184‰
101	Asia	KH	Cambodia	17 168 838	3 056	0.178‰
102	Asia	BD	Bangladesh	167 879 547	29 131	0.173‰
103	Asia	SY	Syria	18 327 090	3 150	0.172‰
104	Africa	DZ	Algeria	45 390 507	6 875	0.151‰
105	Africa	GM	Gambia	2 548 640	365	0.143‰
106	Asia	PK	Pakistan	229 230 939	30 381	0.133‰
107	Africa	MW	Malawi	20 090 863	2 642	0.132‰
108	Africa	GA	Gabon	2 327 828	304	0.131‰
109	Africa	SN	Senegal	17 601 640	1 967	0.112‰
110	Africa	SD	Sudan	45 839 520	4 950	0.108‰
111	Africa	RW	Rwanda	13 576 353	1 459	0.107‰
112	Asia	LA	Laos	7 480 827	757	0.101‰
113	Africa	KE	Kenya	56 073 862	5 651	0.101‰
114	Africa	GW	Guinea-Bissau	2 058 422	171	0.083‰
115	Africa	SO	Somalia	16 755 128	1 361	0.081‰
116	Africa	UG	Uganda	48 548 800	3 603	0.074‰
117	North America	HT	Haiti	11 672 793	835	0.071‰
118	Australia/Oceania	PG	Papua New Guinea	9 276 518	658	0.071‰
119	Africa	CM	Cameroon	27 830 381	1 930	0.069‰
120	Asia	YE	Yemen	31 102 983	2 149	0.069‰
121	Africa	MZ	Mozambique	32 957 580	2 206	0.067‰
122	Africa	CG	Congo	5 782 115	385	0.067‰
123	Africa	ET	Ethiopia	120 499 230	7 517	0.062‰
124	Africa	LR	Liberia	5 288 769	294	0.056‰
125	Africa	AO	Angola	34 853 471	1 900	0.054‰
126	Africa	MG	Madagascar	29 074 832	1 396	0.048‰
127	Asia	UZ	Uzbekistan	34 412 290	1 637	0.048‰
128	Africa	GH	Ghana	32 333 890	1 445	0.045‰
129	North America	NI	Nicaragua	6 777 797	240	0.035‰
130	Africa	ML	Mali	21 384 618	736	0.034‰
131	Africa	GN	Guinea	13 825 236	442	0.032‰
132	Africa	TG	Togo	8 655 912	273	0.032‰
133	Africa	CI	Ivory Coast	27 648 050	799	0.029‰
134	Africa	ER	Eritrea	3 641 853	103	0.028‰
135	Africa	CF	Central African R.	4 993 027	113	0.023‰
136	Africa	BF	Burkina Faso	22 017 453	384	0.017‰
137	Africa	SL	Sierra Leone	8 292 350	125	0.015‰
138	Africa	NG	Nigeria	216 071 476	3 144	0.015‰
139	Africa	CD	DR Congo	94 853 927	1 345	0.014‰
140	Africa	TZ	Tanzania	63 041 475	840	0.013‰
141	Africa	BJ	Benin	12 740 457	163	0.013‰
142	Africa	SS	South Sudan	11 448 890	138	0.012‰
143	Africa	NE	Niger	25 909 734	310	0.012‰
144	Africa	TD	Chad	17 342 051	193	0.011‰
145	Africa	BI	Burundi	12 579 153	15	0.001‰
146	Asia	CN	China	1 439 323 776	0	0.000‰
147	Asia	KP	North Korea	25 660 000	0	0.000‰
148	Asia	TJ	Tajikistan	9 954 095	0	0.000‰
149	Europe	TM	Turkmenistan	6 118 000	0	0.000‰
150	Asia	PS	Palestine	5 331 948	0	0.000‰

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

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

(2021-02-02 ...)

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

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"