Menu Új írások

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": 2022-09-27 21:02
(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	+10 654 (+5 994)	+10 (+1)
CZ	Czechia	+4 735 (+281)	+0 (+11)
DE	Germany	+0 (+89 282)	+0 (+118)
HU	Hungary	+0 (+0)	+0 (+0)
PL	Poland	+6 484 (+729)	+25 (+0)
SK	Slovakia, [gov], [okr]	+442 (+78)	+3 (+2)

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

N.	Region	Population	Last 120 days	Last 30 days	Last 7 days
1	Europe	756 641 771	3.53%	1.48%	0.59%
2	North America	598 699 588	2.25%	0.88%	0.18%
3	Asia	4 709 849 202	0.64%	0.46%	0.17%
4	Australia/Oceania	43 935 166	8.14%	1.60%	0.17%
5	South America	441 939 772	1.50%	0.41%	0.12%
6	Africa	1 411 600 485	0.04%	0.01%	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	South America	441 939 772	0.43%	0.88%	0.41%
2	North America	598 699 588	0.37%	0.61%	0.88%
3	Australia/Oceania	43 935 166	0.21%	0.59%	1.60%
4	Africa	1 411 600 485	0.49%	(0.58)%	(0.01)%
5	Europe	756 641 771	0.25%	0.40%	1.48%
6	Asia	4 709 849 202	0.14%	0.22%	0.46%

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	441 939 772	1 332 413	3.015‰
2	Europe	756 641 771	1 911 725	2.527‰
3	North America	598 699 588	1 492 614	2.493‰
4	Australia/Oceania	43 935 166	20 620	0.469‰
5	Asia	4 709 849 202	1 469 688	0.312‰
6	Africa	1 411 600 485	257 667	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	23 912 908	18.28%	18.45%	20.15%
2	Asia	HK	Hong Kong	7 632 666	7.09%	12.54%	7.60%
3	Asia	GE	Georgia	3 972 095	2.67%	5.18%	5.52%
4	South America	PR	Puerto Rico	3 193 694	10.55%	6.70%	5.06%
5	Europe	SI	Slovenia	2 079 575	5.89%	4.82%	3.18%
6	North America	CR	Costa Rica	5 197 894	4.61%	2.82%	2.69%
7	Europe	AT	Austria	9 121 024	8.07%	3.36%	2.00%
8	Europe	HU	Hungary	9 605 664	1.55%	2.23%	1.84%
9	Europe	DE	Germany	84 381 438	7.45%	2.51%	1.81%
10	Europe	LT	Lithuania	2 637 684	2.90%	2.35%	1.41%
11	Asia	KR	South Korea	51 367 577	11.78%	8.99%	1.31%
12	Europe	IT	Italy	60 263 602	7.82%	2.06%	1.28%
13	Europe	BE	Belgium	11 702 123	3.22%	1.52%	1.22%
14	Asia	IL	Israel	9 326 000	5.59%	1.21%	1.10%
15	North America	PA	Panama	4 466 324	3.98%	1.56%	0.93%
16	Asia	AM	Armenia	2 975 594	0.60%	1.14%	0.82%
17	North America	CA	Canada	38 480 391	0.97%	0.91%	0.82%
18	South America	UY	Uruguay	3 500 580	2.14%	0.87%	0.81%
19	Europe	CZ	Czechia	10 753 287	1.37%	1.18%	0.75%
20	Asia	JP	Japan	125 613 305	9.12%	6.66%	0.69%
21	Asia	JO	Jordan	10 429 112	0.44%	0.82%	0.56%
22	Europe	CH	Switzerland	8 795 811	4.39%	0.92%	0.55%
23	Europe	RS	Serbia	8 658 917	3.52%	2.40%	0.54%
24	Australia/Oceania	NZ	New Zealand	5 002 100	11.95%	2.27%	0.48%
25	Asia	SG	Singapore	5 952 983	9.53%	2.13%	0.46%
26	Asia	TR	Turkey	86 363 808	2.08%	1.50%	0.45%
27	Europe	RU	Russia	146 073 999	1.28%	2.16%	0.43%
28	Europe	SE	Sweden	10 239 736	0.66%	0.74%	0.40%
29	Asia	QA	Qatar	2 807 805	2.46%	1.49%	0.40%
30	Europe	DK	Denmark	5 837 695	2.52%	0.93%	0.32%
31	Europe	PL	Poland	37 754 189	0.58%	0.64%	0.29%
32	South America	AR	Argentina	46 120 998	1.22%	0.56%	0.29%
33	Europe	BG	Bulgaria	6 831 877	1.25%	0.61%	0.28%
34	Europe	NL	Netherlands	17 219 424	1.84%	0.40%	0.26%
35	Europe	IE	Ireland	5 060 845	2.14%	0.54%	0.26%
36	Europe	GB	United Kingdom	68 681 433	1.97%	0.64%	0.24%
37	Europe	HR	Croatia	4 048 842	2.09%	0.95%	0.22%
38	Europe	FI	Finland	5 559 915	3.46%	1.86%	0.22%
39	Europe	FR	France	65 595 624	7.59%	0.78%	0.20%
40	North America	DO	Dominican R.	11 090 604	0.55%	0.25%	0.17%
41	South America	CL	Chile	19 482 269	4.49%	1.66%	0.17%
42	Europe	RO	Romania	18 951 674	1.77%	0.73%	0.17%
43	Europe	SK	Slovakia	5 465 539	0.89%	0.32%	0.14%
44	Europe	PT	Portugal	10 130 428	7.75%	1.45%	0.14%
45	Asia	KZ	Kazakhstan	19 277 809	0.45%	0.31%	0.13%
46	Africa	BW	Botswana	2 457 583	0.80%	0.06%	0.13%
47	Australia/Oceania	AU	Australia	26 159 993	11.09%	2.10%	0.11%
48	North America	MX	Mexico	131 954 950	0.97%	0.23%	0.10%
49	Asia	MN	Mongolia	3 396 089	1.66%	0.49%	0.09%
50	North America	US	USA	335 049 756	3.22%	1.25%	0.09%
51	Europe	ES	Spain	46 795 160	2.04%	0.32%	0.08%
52	South America	EC	Ecuador	18 240 838	0.69%	0.33%	0.07%
53	Europe	MK	North Macedonia	2 083 183	1.44%	0.42%	0.07%
54	Asia	MY	Malaysia	33 291 238	0.91%	0.41%	0.06%
55	Asia	AE	Arab Emirates	10 157 018	1.12%	0.29%	0.06%
56	South America	PY	Paraguay	7 328 016	0.90%	0.16%	0.05%
57	South America	BR	Brazil	215 929 973	1.66%	0.30%	0.05%
58	South America	CO	Colombia	52 092 877	0.40%	0.14%	0.05%
59	Europe	BA	Bosnia and Herzegovina	3 235 336	0.60%	0.26%	0.05%
60	Asia	LB	Lebanon	6 757 312	1.68%	0.30%	0.04%
61	North America	HN	Honduras	10 256 108	0.30%	0.30%	0.04%
62	Africa	ZM	Zambia	19 533 022	0.06%	0.02%	0.04%
63	Europe	NO	Norway	5 515 806	0.51%	0.10%	0.03%
64	North America	JM	Jamaica	2 989 995	0.48%	0.19%	0.03%
65	Asia	VN	Vietnam	99 292 436	0.73%	0.17%	0.03%
66	Asia	AZ	Azerbaijan	10 343 058	0.24%	0.25%	0.02%
67	Asia	PH	Philippines	112 835 294	0.19%	0.13%	0.02%
68	Asia	KG	Kyrgyzstan	6 764 377	0.07%	0.03%	0.02%
69	Africa	SO	Somalia	16 882 823	0.00%	0.00%	0.02%
70	North America	NI	Nicaragua	6 800 402	0.01%	0.01%	0.02%
71	Africa	GH	Ghana	32 520 343	0.02%	0.00%	0.02%
72	Asia	ID	Indonesia	279 976 514	0.12%	0.08%	0.01%
73	Africa	GA	Gabon	2 342 935	0.05%	0.01%	0.01%
74	Asia	LA	Laos	7 511 127	0.07%	0.07%	0.01%
75	South America	PE	Peru	33 996 669	1.61%	0.37%	0.01%
76	Asia	TH	Thailand	70 190 589	0.32%	0.13%	0.01%
77	Asia	MM	Myanmar	55 223 453	0.01%	0.02%	0.01%
78	South America	BO	Bolivia	12 028 297	1.64%	0.24%	0.01%
79	Asia	BD	Bangladesh	168 349 895	0.04%	0.01%	0.01%
80	Europe	AL	Albania	2 870 791	1.88%	0.39%	0.01%
81	Asia	AF	Afghanistan	40 884 801	0.04%	0.04%	0.01%
82	Asia	IR	Iran	86 391 625	0.36%	0.10%	0.01%
83	North America	HT	Haiti	11 712 663	0.03%	0.03%	0.01%
84	Africa	CI	Ivory Coast	27 836 009	0.02%	0.01%	0.01%
85	Asia	SA	Saudi Arabia	36 023 641	0.13%	0.02%	0.01%
86	Africa	BI	Burundi	12 681 192	0.06%	0.01%	0.01%
87	Africa	ZA	South Africa	60 977 086	0.10%	0.02%	0.01%
88	Africa	TG	Togo	8 711 726	0.02%	0.01%	0.01%
89	North America	GT	Guatemala	18 655 084	1.35%	0.31%	0.01%
90	Africa	GM	Gambia	2 568 194	0.02%	0.02%	0.01%
91	Australia/Oceania	PG	Papua New Guinea	9 325 214	0.01%	0.00%	0.00%
92	Africa	NG	Nigeria	217 541 658	0.00%	0.00%	0.00%
93	Asia	IN	India	1 410 273 474	0.10%	0.03%	0.00%
94	Africa	CF	Central African R.	5 017 145	0.01%	0.00%	0.00%
95	Asia	LK	Sri Lanka	21 613 502	0.03%	0.01%	0.00%
96	Asia	UZ	Uzbekistan	34 551 503	0.01%	0.00%	0.00%
97	Africa	UG	Uganda	48 965 219	0.01%	0.00%	0.00%
98	Africa	KE	Kenya	56 414 444	0.03%	0.00%	0.00%
99	Asia	NP	Nepal	30 306 197	0.07%	0.03%	0.00%
100	Africa	NE	Niger	26 162 650	0.00%	0.00%	0.00%
101	Africa	MZ	Mozambique	33 209 769	0.01%	0.00%	0.00%
102	Africa	SN	Senegal	17 728 659	0.01%	0.00%	0.00%
103	Africa	MR	Mauritania	4 922 415	0.07%	0.00%	0.00%
104	Asia	YE	Yemen	31 291 872	0.00%	0.00%	0.00%
105	Africa	BF	Burkina Faso	22 182 502	0.00%	0.00%	0.00%
106	Africa	LS	Lesotho	2 180 133	0.05%	0.01%	0.00%
107	Africa	LR	Liberia	5 322 964	0.01%	0.02%	0.00%
108	South America	VE	Venezuela	28 256 320	0.07%	0.03%	0.00%
109	Africa	ET	Ethiopia	121 318 649	0.02%	0.00%	0.00%
110	Asia	PK	Pakistan	230 463 460	0.02%	0.01%	0.00%
111	Asia	KW	Kuwait	4 411 493	0.57%	0.12%	0.00%
112	Africa	ER	Eritrea	3 655 937	0.01%	0.00%	0.00%
113	Europe	UA	Ukraine	43 148 150	0.15%	0.39%	0.00%
114	Africa	EG	Egypt	106 641 391	0.00%	0.00%	0.00%
115	Africa	AO	Angola	35 148 150	0.01%	0.00%	0.00%
116	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
117	Africa	TZ	Tanzania	63 531 541	0.01%	0.00%	0.00%
118	Asia	KH	Cambodia	17 235 233	0.01%	0.00%	0.00%
119	Asia	OM	Oman	5 396 468	0.16%	0.06%	0.00%
120	Africa	TN	Tunisia	12 094 522	0.86%	0.18%	0.00%
121	Africa	DZ	Algeria	45 617 970	0.01%	0.00%	0.00%
122	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
123	Asia	TJ	Tajikistan	10 015 701	0.00%	0.00%	0.00%
124	Africa	TD	Chad	17 477 819	0.00%	0.00%	0.00%
125	North America	CU	Cuba	11 311 201	0.05%	0.02%	0.00%
126	Asia	SY	Syria	18 449 407	0.01%	0.00%	0.00%
127	Asia	IQ	Iraq	42 236 708	0.31%	0.07%	0.00%
128	North America	SV	El Salvador	6 559 204	0.61%	0.67%	0.00%
129	Africa	NA	Namibia	2 643 585	0.24%	0.01%	0.00%
130	Africa	SS	South Sudan	11 486 528	0.00%	0.00%	0.00%
131	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
132	Africa	CM	Cameroon	28 020 530	0.01%	0.00%	0.00%
133	Africa	SL	Sierra Leone	8 338 976	0.00%	0.00%	0.00%
134	Africa	CG	Congo	5 821 197	0.01%	0.00%	0.00%
135	Africa	MW	Malawi	20 233 145	0.01%	0.00%	0.00%
136	Africa	CD	DR Congo	95 638 591	0.00%	0.00%	0.00%
137	Europe	BY	Belarus	9 442 392	0.12%	0.00%	0.00%
138	Africa	GW	Guinea-Bissau	2 071 802	0.03%	0.06%	0.00%
139	Africa	SD	Sudan	46 134 014	0.00%	0.00%	0.00%
140	Africa	ML	Mali	21 552 636	0.01%	0.02%	0.00%
141	Asia	PS	Palestine	5 366 059	0.00%	0.00%	0.00%
142	Europe	GR	Greece	10 309 569	12.31%	8.69%	0.00%
143	Africa	RW	Rwanda	13 668 741	0.02%	0.00%	0.00%
144	Africa	MG	Madagascar	29 279 726	0.01%	0.00%	0.00%
145	Africa	ZW	Zimbabwe	15 345 688	0.03%	0.00%	0.00%
146	Africa	GN	Guinea	13 927 802	0.01%	0.01%	0.00%
147	Africa	BJ	Benin	12 831 863	0.01%	0.01%	0.00%
148	Europe	MD	Moldova	4 013 061	1.51%	2.72%	0.00%
149	Africa	MA	Morocco	37 886 664	0.26%	0.00%	0.00%
150	Africa	LY	Libya	7 079 771	0.07%	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	CD	DR Congo	95 638 591	1.64%	(12.78)%	(0.00)%
2	Asia	YE	Yemen	31 291 872	5.36%	(8.33)%	(0.00)%
3	South America	PY	Paraguay	7 328 016	0.99%	3.70%	0.16%
4	Africa	EG	Egypt	106 641 391	7.12%	(3.38)%	(0.00)%
5	Asia	LK	Sri Lanka	21 613 502	3.21%	(3.13)%	(0.01)%
6	Africa	NA	Namibia	2 643 585	0.64%	(2.91)%	(0.01)%
7	Europe	NO	Norway	5 515 806	2.83%	(2.59)%	(0.10)%
8	Africa	MR	Mauritania	4 922 415	0.29%	(2.13)%	(0.00)%
9	Europe	BA	Bosnia and Herzegovina	3 235 336	1.60%	1.89%	0.26%
10	North America	HT	Haiti	11 712 663	0.75%	1.78%	0.03%
11	South America	CO	Colombia	52 092 877	0.90%	1.77%	0.14%
12	North America	JM	Jamaica	2 989 995	1.43%	1.74%	0.19%
13	Asia	IR	Iran	86 391 625	0.94%	1.64%	0.10%
14	Asia	PH	Philippines	112 835 294	0.87%	1.52%	0.13%
15	Asia	SA	Saudi Arabia	36 023 641	0.34%	1.50%	0.02%
16	Europe	ES	Spain	46 795 160	0.62%	1.31%	0.32%
17	Europe	SE	Sweden	10 239 736	1.55%	1.26%	0.74%
18	Europe	GB	United Kingdom	68 681 433	0.79%	1.24%	0.64%
19	Africa	BW	Botswana	2 457 583	0.46%	1.23%	0.06%
20	Europe	HR	Croatia	4 048 842	0.96%	1.14%	0.95%
21	Africa	ZW	Zimbabwe	15 345 688	1.55%	1.14%	0.00%
22	North America	CA	Canada	38 480 391	1.02%	1.13%	0.91%
23	Africa	GN	Guinea	13 927 802	0.71%	1.10%	0.01%
24	Europe	SK	Slovakia	5 465 539	0.66%	1.09%	0.32%
25	Europe	IE	Ireland	5 060 845	0.37%	1.05%	0.54%
26	Asia	TH	Thailand	70 190 589	1.02%	1.01%	0.13%
27	Africa	ZA	South Africa	60 977 086	1.16%	0.96%	0.02%
28	South America	PE	Peru	33 996 669	0.54%	0.91%	0.37%
29	Africa	MW	Malawi	20 233 145	1.92%	0.89%	0.00%
30	North America	GT	Guatemala	18 655 084	0.61%	0.85%	0.31%
31	Africa	TN	Tunisia	12 094 522	0.64%	0.84%	0.18%
32	Europe	MK	North Macedonia	2 083 183	0.66%	0.74%	0.42%
33	Africa	TG	Togo	8 711 726	0.69%	0.70%	0.01%
34	Africa	MA	Morocco	37 886 664	0.20%	0.69%	0.00%
35	Africa	MZ	Mozambique	33 209 769	0.45%	0.69%	0.00%
36	Europe	HU	Hungary	9 605 664	0.70%	0.66%	2.23%
37	Africa	CI	Ivory Coast	27 836 009	0.47%	0.63%	0.01%
38	Africa	GM	Gambia	2 568 194	1.70%	0.59%	0.02%
39	South America	VE	Venezuela	28 256 320	0.43%	0.57%	0.03%
40	South America	BR	Brazil	215 929 973	0.49%	0.56%	0.30%
41	Asia	AZ	Azerbaijan	10 343 058	0.59%	0.56%	0.25%
42	North America	MX	Mexico	131 954 950	0.32%	0.55%	0.23%
43	Asia	PK	Pakistan	230 463 460	0.53%	0.52%	0.01%
44	Europe	BG	Bulgaria	6 831 877	0.62%	0.49%	0.61%
45	Europe	DK	Denmark	5 837 695	0.42%	0.47%	0.93%
46	South America	UY	Uruguay	3 500 580	0.31%	0.42%	0.87%
47	Africa	TZ	Tanzania	63 531 541	0.11%	0.42%	0.00%
48	Europe	RO	Romania	18 951 674	0.35%	0.42%	0.73%
49	Africa	NE	Niger	26 162 650	0.53%	0.41%	0.00%
50	Australia/Oceania	NZ	New Zealand	5 002 100	0.29%	0.41%	2.27%
51	Asia	NP	Nepal	30 306 197	0.32%	0.40%	0.03%
52	Asia	ID	Indonesia	279 976 514	0.36%	0.40%	0.08%
53	Europe	BE	Belgium	11 702 123	0.24%	0.38%	1.52%
54	North America	HN	Honduras	10 256 108	0.30%	0.37%	0.30%
55	South America	EC	Ecuador	18 240 838	0.21%	0.36%	0.33%
56	Europe	PL	Poland	37 754 189	0.46%	0.36%	0.64%
57	Australia/Oceania	AU	Australia	26 159 993	0.19%	0.35%	2.10%
58	North America	US	USA	335 049 756	0.36%	0.33%	1.25%
59	Africa	NG	Nigeria	217 541 658	0.13%	0.33%	0.00%
60	Europe	MD	Moldova	4 013 061	0.43%	0.32%	2.72%
61	South America	CL	Chile	19 482 269	0.32%	0.32%	1.66%
62	Europe	UA	Ukraine	43 148 150	0.59%	0.31%	0.39%
63	Asia	LB	Lebanon	6 757 312	0.19%	0.31%	0.30%
64	South America	AR	Argentina	46 120 998	0.18%	0.30%	0.56%
65	Europe	GR	Greece	10 309 569	0.24%	0.30%	8.69%
66	South America	PR	Puerto Rico	3 193 694	0.21%	0.29%	6.70%
67	Africa	GW	Guinea-Bissau	2 071 802	0.69%	0.29%	0.06%
68	North America	CR	Costa Rica	5 197 894	0.20%	0.28%	2.82%
69	Europe	FR	France	65 595 624	0.12%	0.28%	0.78%
70	Asia	IN	India	1 410 273 474	0.26%	0.28%	0.03%
71	Asia	AM	Armenia	2 975 594	0.29%	0.28%	1.14%
72	Asia	IQ	Iraq	42 236 708	0.10%	0.28%	0.07%
73	Europe	RS	Serbia	8 658 917	0.25%	0.27%	2.40%
74	Europe	CZ	Czechia	10 753 287	0.43%	0.27%	1.18%
75	Africa	LY	Libya	7 079 771	0.14%	0.27%	0.01%
76	Asia	AF	Afghanistan	40 884 801	0.53%	0.26%	0.04%
77	Africa	ET	Ethiopia	121 318 649	0.27%	0.25%	0.00%
78	Africa	KE	Kenya	56 414 444	0.18%	0.25%	0.00%
79	Europe	IT	Italy	60 263 602	0.20%	0.24%	2.06%
80	Europe	FI	Finland	5 559 915	0.53%	0.23%	1.86%
81	Asia	BD	Bangladesh	168 349 895	0.33%	0.23%	0.01%
82	Africa	UG	Uganda	48 965 219	0.63%	0.22%	0.00%
83	Asia	IL	Israel	9 326 000	0.15%	0.22%	1.21%
84	Asia	MM	Myanmar	55 223 453	0.21%	0.21%	0.02%
85	North America	PA	Panama	4 466 324	0.15%	0.20%	1.56%
86	Asia	TR	Turkey	86 363 808	0.12%	0.19%	1.50%
87	Asia	MY	Malaysia	33 291 238	0.20%	0.19%	0.41%
88	South America	BO	Bolivia	12 028 297	0.14%	0.18%	0.24%
89	Europe	PT	Portugal	10 130 428	0.19%	0.18%	1.45%
90	Asia	HK	Hong Kong	7 632 666	0.15%	0.18%	12.54%
91	Europe	RU	Russia	146 073 999	0.35%	0.15%	2.16%
92	Asia	JP	Japan	125 613 305	0.11%	0.12%	6.66%
93	Europe	SI	Slovenia	2 079 575	0.32%	0.12%	4.82%
94	Africa	DZ	Algeria	45 617 970	0.09%	0.12%	0.00%
95	Asia	TW	Taiwan	23 912 908	0.19%	0.11%	18.45%
96	Asia	JO	Jordan	10 429 112	0.11%	0.10%	0.82%
97	North America	SV	El Salvador	6 559 204	0.25%	0.10%	0.67%
98	Europe	NL	Netherlands	17 219 424	0.09%	0.09%	0.40%
99	Europe	AL	Albania	2 870 791	0.16%	0.09%	0.39%
100	Europe	AT	Austria	9 121 024	0.11%	0.08%	3.36%
101	Asia	MN	Mongolia	3 396 089	0.03%	0.07%	0.49%
102	Asia	KZ	Kazakhstan	19 277 809	0.04%	0.07%	0.31%
103	Europe	LT	Lithuania	2 637 684	0.20%	0.06%	2.35%
104	Asia	KR	South Korea	51 367 577	0.06%	0.05%	8.99%
105	Europe	DE	Germany	84 381 438	0.11%	0.05%	2.51%
106	Asia	GE	Georgia	3 972 095	0.09%	0.04%	5.18%
107	Africa	ZM	Zambia	19 533 022	0.27%	0.04%	0.02%
108	Asia	SG	Singapore	5 952 983	0.04%	0.04%	2.13%
109	Asia	VN	Vietnam	99 292 436	0.01%	0.04%	0.17%
110	Europe	CH	Switzerland	8 795 811	0.07%	0.02%	0.92%
111	Asia	AE	Arab Emirates	10 157 018	0.03%	0.02%	0.29%
112	Asia	QA	Qatar	2 807 805	0.01%	0.01%	1.49%
113	North America	DO	Dominican R.	11 090 604	0.01%	0.00%	0.25%
114	Asia	KW	Kuwait	4 411 493	0.03%	0.00%	0.12%
115	Asia	LA	Laos	7 511 127	0.02%	0.00%	0.07%
116	Asia	OM	Oman	5 396 468	0.01%	0.00%	0.06%
117	Asia	KG	Kyrgyzstan	6 764 377	0.00%	0.00%	0.03%
118	North America	CU	Cuba	11 311 201	0.02%	0.00%	0.02%
119	Africa	ML	Mali	21 552 636	0.41%	0.00%	0.02%
120	Africa	LR	Liberia	5 322 964	0.00%	0.00%	0.02%
121	North America	NI	Nicaragua	6 800 402	1.57%	0.00%	0.01%
122	Africa	LS	Lesotho	2 180 133	0.56%	0.00%	0.01%
123	Africa	GA	Gabon	2 342 935	0.19%	0.00%	0.01%
124	Africa	BJ	Benin	12 831 863	0.00%	0.00%	0.01%
125	Africa	BI	Burundi	12 681 192	0.00%	0.00%	0.01%
126	Asia	SY	Syria	18 449 407	1.01%	0.00%	0.00%
127	Africa	AO	Angola	35 148 150	0.46%	0.00%	0.00%
128	Africa	SN	Senegal	17 728 659	0.09%	0.00%	0.00%
129	Asia	KH	Cambodia	17 235 233	0.00%	0.00%	0.00%
130	Africa	GH	Ghana	32 520 343	0.19%	0.00%	0.00%
131	Asia	UZ	Uzbekistan	34 551 503	0.00%	0.00%	0.00%
132	Australia/Oceania	PG	Papua New Guinea	9 325 214	2.54%	0.00%	0.00%
133	Africa	RW	Rwanda	13 668 741	0.28%	0.00%	0.00%
134	Africa	ER	Eritrea	3 655 937	0.00%	0.00%	0.00%
135	Africa	TD	Chad	17 477 819	0.00%	0.00%	0.00%
136	Africa	SD	Sudan	46 134 014	2.18%	0.00%	0.00%
137	Africa	MG	Madagascar	29 279 726	0.71%	0.00%	0.00%
138	Africa	CF	Central African R.	5 017 145	0.00%	0.00%	0.00%
139	Africa	SL	Sierra Leone	8 338 976	0.00%	0.00%	0.00%
140	Africa	CM	Cameroon	28 020 530	0.29%	0.00%	0.00%
141	Africa	SO	Somalia	16 882 823	0.00%	0.00%	0.00%
142	Africa	BF	Burkina Faso	22 182 502	1.31%	0.00%	0.00%
143	Europe	BY	Belarus	9 442 392	1.23%	0.00%	0.00%
144	Africa	CG	Congo	5 821 197	0.14%	0.00%	0.00%
145	Africa	SS	South Sudan	11 486 528	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	10 015 701	0.00%	0.00%	0.00%
149	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
150	Asia	PS	Palestine	5 366 059	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	33 996 669	216 146	6.358‰
2	Europe	BG	Bulgaria	6 831 877	37 661	5.513‰
3	Europe	BA	Bosnia and Herzegovina	3 235 336	16 100	4.976‰
4	Europe	HU	Hungary	9 605 664	47 367	4.931‰
5	Europe	MK	North Macedonia	2 083 183	9 512	4.566‰
6	Asia	GE	Georgia	3 972 095	16 900	4.255‰
7	Europe	HR	Croatia	4 048 842	16 812	4.152‰
8	Europe	SI	Slovenia	2 079 575	8 185	3.936‰
9	Europe	CZ	Czechia	10 753 287	40 918	3.805‰
10	Europe	SK	Slovakia	5 465 539	20 420	3.736‰
11	Europe	RO	Romania	18 951 674	66 867	3.528‰
12	Europe	LT	Lithuania	2 637 684	9 295	3.524‰
13	Europe	GR	Greece	10 309 569	32 757	3.177‰
14	South America	BR	Brazil	215 929 973	684 874	3.172‰
15	South America	CL	Chile	19 482 269	60 814	3.122‰
16	Europe	PL	Poland	37 754 189	117 305	3.107‰
17	North America	US	USA	335 049 756	1 039 676	3.103‰
18	Europe	MD	Moldova	4 013 061	11 783	2.936‰
19	Europe	IT	Italy	60 263 602	176 306	2.926‰
20	Asia	AM	Armenia	2 975 594	8 673	2.915‰
21	South America	AR	Argentina	46 120 998	129 830	2.815‰
22	Europe	BE	Belgium	11 702 123	32 605	2.786‰
23	Europe	GB	United Kingdom	68 681 433	189 026	2.752‰
24	South America	CO	Colombia	52 092 877	141 708	2.720‰
25	South America	PY	Paraguay	7 328 016	19 530	2.665‰
26	Europe	RU	Russia	146 073 999	385 631	2.640‰
27	Europe	UA	Ukraine	43 148 150	108 885	2.523‰
28	North America	MX	Mexico	131 954 950	329 761	2.499‰
29	Europe	PT	Portugal	10 130 428	24 928	2.461‰
30	Europe	ES	Spain	46 795 160	113 148	2.418‰
31	Africa	TN	Tunisia	12 094 522	29 238	2.417‰
32	Europe	FR	France	65 595 624	151 031	2.303‰
33	Europe	AT	Austria	9 121 024	20 722	2.272‰
34	South America	UY	Uruguay	3 500 580	7 462	2.132‰
35	South America	EC	Ecuador	18 240 838	35 876	1.967‰
36	Europe	SE	Sweden	10 239 736	20 006	1.954‰
37	Europe	RS	Serbia	8 658 917	16 843	1.945‰
38	North America	PA	Panama	4 466 324	8 487	1.900‰
39	South America	BO	Bolivia	12 028 297	22 218	1.847‰
40	Europe	DE	Germany	84 381 438	148 507	1.760‰
41	North America	CR	Costa Rica	5 197 894	8 913	1.715‰
42	Africa	ZA	South Africa	60 977 086	102 129	1.675‰
43	Asia	IR	Iran	86 391 625	144 206	1.669‰
44	South America	PR	Puerto Rico	3 193 694	5 034	1.576‰
45	Asia	LB	Lebanon	6 757 312	10 648	1.576‰
46	Europe	IE	Ireland	5 060 845	7 870	1.555‰
47	Africa	NA	Namibia	2 643 585	4 077	1.542‰
48	Europe	CH	Switzerland	8 795 811	13 539	1.539‰
49	Asia	JO	Jordan	10 429 112	14 114	1.353‰
50	Asia	HK	Hong Kong	7 632 666	10 134	1.328‰
51	Europe	NL	Netherlands	17 219 424	22 616	1.313‰
52	Asia	IL	Israel	9 326 000	11 687	1.253‰
53	Europe	AL	Albania	2 870 791	3 586	1.249‰
54	Europe	DK	Denmark	5 837 695	6 986	1.197‰
55	Asia	TR	Turkey	86 363 808	101 068	1.170‰
56	North America	CA	Canada	38 480 391	44 347	1.153‰
57	Africa	BW	Botswana	2 457 583	2 781	1.132‰
58	North America	JM	Jamaica	2 989 995	3 285	1.099‰
59	Asia	MY	Malaysia	33 291 238	36 292	1.090‰
60	North America	HN	Honduras	10 256 108	10 989	1.071‰
61	North America	GT	Guatemala	18 655 084	19 672	1.054‰
62	Europe	FI	Finland	5 559 915	5 768	1.037‰
63	Asia	KZ	Kazakhstan	19 277 809	19 047	0.988‰
64	Asia	AZ	Azerbaijan	10 343 058	9 861	0.953‰
65	Africa	LY	Libya	7 079 771	6 437	0.909‰
66	Asia	OM	Oman	5 396 468	4 628	0.858‰
67	Asia	LK	Sri Lanka	21 613 502	16 732	0.774‰
68	North America	CU	Cuba	11 311 201	8 530	0.754‰
69	Europe	BY	Belarus	9 442 392	7 118	0.754‰
70	Europe	NO	Norway	5 515 806	4 004	0.726‰
71	North America	SV	El Salvador	6 559 204	4 228	0.645‰
72	Asia	MN	Mongolia	3 396 089	2 130	0.627‰
73	Asia	IQ	Iraq	42 236 708	25 348	0.600‰
74	Australia/Oceania	NZ	New Zealand	5 002 100	2 962	0.592‰
75	Asia	KW	Kuwait	4 411 493	2 563	0.581‰
76	Asia	ID	Indonesia	279 976 514	157 828	0.564‰
77	Asia	PH	Philippines	112 835 294	62 372	0.553‰
78	Australia/Oceania	AU	Australia	26 159 993	14 443	0.552‰
79	Asia	KR	South Korea	51 367 577	27 559	0.536‰
80	Asia	TH	Thailand	70 190 589	32 574	0.464‰
81	Asia	TW	Taiwan	23 912 908	10 912	0.456‰
82	Asia	KG	Kyrgyzstan	6 764 377	2 991	0.442‰
83	Asia	VN	Vietnam	99 292 436	43 131	0.434‰
84	Africa	MA	Morocco	37 886 664	16 276	0.430‰
85	Asia	NP	Nepal	30 306 197	12 015	0.397‰
86	North America	DO	Dominican R.	11 090 604	4 384	0.395‰
87	Asia	IN	India	1 410 273 474	528 217	0.375‰
88	Africa	ZW	Zimbabwe	15 345 688	5 596	0.365‰
89	Asia	MM	Myanmar	55 223 453	19 442	0.352‰
90	Asia	JP	Japan	125 613 305	42 882	0.341‰
91	Africa	LS	Lesotho	2 180 133	704	0.323‰
92	Asia	SG	Singapore	5 952 983	1 607	0.270‰
93	Asia	SA	Saudi Arabia	36 023 641	9 320	0.259‰
94	Asia	QA	Qatar	2 807 805	682	0.243‰
95	Africa	EG	Egypt	106 641 391	24 796	0.233‰
96	Asia	AE	Arab Emirates	10 157 018	2 343	0.231‰
97	Africa	ZM	Zambia	19 533 022	4 017	0.206‰
98	South America	VE	Venezuela	28 256 320	5 809	0.206‰
99	Africa	MR	Mauritania	4 922 415	993	0.202‰
100	Asia	AF	Afghanistan	40 884 801	7 789	0.191‰
101	Asia	KH	Cambodia	17 235 233	3 056	0.177‰
102	Asia	BD	Bangladesh	168 349 895	29 336	0.174‰
103	Asia	SY	Syria	18 449 407	3 163	0.171‰
104	Africa	DZ	Algeria	45 617 970	6 879	0.151‰
105	Africa	GM	Gambia	2 568 194	372	0.145‰
106	Asia	PK	Pakistan	230 463 460	30 599	0.133‰
107	Africa	MW	Malawi	20 233 145	2 675	0.132‰
108	Africa	GA	Gabon	2 342 935	306	0.131‰
109	Africa	SN	Senegal	17 728 659	1 968	0.111‰
110	Africa	SD	Sudan	46 134 014	4 961	0.107‰
111	Africa	RW	Rwanda	13 668 741	1 466	0.107‰
112	Asia	LA	Laos	7 511 127	757	0.101‰
113	Africa	KE	Kenya	56 414 444	5 674	0.101‰
114	Africa	GW	Guinea-Bissau	2 071 802	175	0.085‰
115	Africa	SO	Somalia	16 882 823	1 361	0.081‰
116	Africa	UG	Uganda	48 965 219	3 628	0.074‰
117	North America	HT	Haiti	11 712 663	857	0.073‰
118	Australia/Oceania	PG	Papua New Guinea	9 325 214	664	0.071‰
119	Africa	CM	Cameroon	28 020 530	1 935	0.069‰
120	Asia	YE	Yemen	31 291 872	2 155	0.069‰
121	Africa	MZ	Mozambique	33 209 769	2 222	0.067‰
122	Africa	CG	Congo	5 821 197	386	0.066‰
123	Africa	ET	Ethiopia	121 318 649	7 572	0.062‰
124	Africa	LR	Liberia	5 322 964	294	0.055‰
125	Africa	AO	Angola	35 148 150	1 917	0.054‰
126	Africa	MG	Madagascar	29 279 726	1 410	0.048‰
127	Asia	UZ	Uzbekistan	34 551 503	1 637	0.047‰
128	Africa	GH	Ghana	32 520 343	1 459	0.045‰
129	North America	NI	Nicaragua	6 800 402	244	0.036‰
130	Africa	ML	Mali	21 552 636	739	0.034‰
131	Africa	TG	Togo	8 711 726	284	0.033‰
132	Africa	GN	Guinea	13 927 802	449	0.032‰
133	Africa	CI	Ivory Coast	27 836 009	822	0.029‰
134	Africa	ER	Eritrea	3 655 937	103	0.028‰
135	Africa	CF	Central African R.	5 017 145	113	0.022‰
136	Africa	BF	Burkina Faso	22 182 502	387	0.017‰
137	Africa	SL	Sierra Leone	8 338 976	125	0.015‰
138	Africa	CD	DR Congo	95 638 591	1 422	0.015‰
139	Africa	NG	Nigeria	217 541 658	3 154	0.015‰
140	Africa	TZ	Tanzania	63 531 541	845	0.013‰
141	Africa	BJ	Benin	12 831 863	163	0.013‰
142	Africa	SS	South Sudan	11 486 528	138	0.012‰
143	Africa	NE	Niger	26 162 650	312	0.012‰
144	Africa	TD	Chad	17 477 819	193	0.011‰
145	Africa	BI	Burundi	12 681 192	15	0.001‰
146	Asia	PS	Palestine	5 366 059	3	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	10 015 701	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"