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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": 2022-01-24 13:33
(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	+25 610 (+22 453)	+9 (+6)
CZ	Czechia	+12 889 (+18 344)	+4 (+17)
DE	Germany	+0 (+75 280)	+0 (+31)
HU	Hungary	+39 928 (+0)	+122 (+0)
PL	Poland	+29 100 (+34 085)	+2 (+25)
SK	Slovakia, [gov], [okr]	+3 503 (+7 608)	+32 (+31)

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

N.	Region	Population	Last 120 days	Last 30 days	Last 7 days
1	Europe	756 340 814	6.98%	14.97%	15.64%
2	North America	595 881 376	4.87%	12.64%	10.72%
3	Australia/Oceania	43 588 815	3.57%	12.19%	8.65%
4	South America	439 552 404	1.62%	4.87%	6.41%
5	Asia	4 687 255 385	0.39%	0.82%	1.19%
6	Africa	1 389 966 446	0.17%	0.34%	0.23%

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	1 389 966 446	1.14%	0.86%	0.34%
2	Asia	4 687 255 385	1.01%	0.47%	0.82%
3	Europe	756 340 814	0.79%	0.38%	14.97%
4	North America	595 881 376	0.76%	0.33%	12.64%
5	South America	439 552 404	0.89%	0.32%	4.87%
6	Australia/Oceania	43 588 815	0.19%	0.08%	12.19%

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	439 552 404	1 205 333	2.742‰
2	North America	595 881 376	1 256 178	2.108‰
3	Europe	756 340 814	1 588 241	2.100‰
4	Asia	4 687 255 385	1 272 717	0.272‰
5	Africa	1 389 966 446	236 068	0.170‰
6	Australia/Oceania	43 588 815	5 566	0.128‰

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	IL	Israel	9 326 000	10.18%	36.47%	74.08%
2	Europe	DK	Denmark	5 824 020	16.42%	41.90%	53.25%
3	Europe	FR	France	65 498 824	13.32%	41.34%	44.06%
4	Europe	PT	Portugal	10 150 323	10.23%	33.07%	37.19%
5	Europe	SI	Slovenia	2 079 384	13.89%	23.80%	36.79%
6	Europe	SE	Sweden	10 197 485	5.82%	18.76%	34.22%
7	Europe	BE	Belgium	11 668 299	12.16%	21.11%	32.08%
8	Europe	CH	Switzerland	8 753 333	11.47%	28.25%	30.63%
9	Europe	ES	Spain	46 783 030	8.30%	27.32%	25.65%
10	South America	UY	Uruguay	3 492 509	4.69%	16.72%	25.44%
11	Europe	IT	Italy	60 323 122	8.12%	26.45%	24.16%
12	South America	PR	Puerto Rico	3 193 694	7.76%	28.61%	22.79%
13	Europe	NL	Netherlands	17 194 015	10.42%	17.36%	21.68%
14	Europe	AT	Austria	9 086 551	9.09%	13.21%	21.29%
15	Europe	NO	Norway	5 487 352	7.24%	15.39%	19.70%
16	Europe	LT	Lithuania	2 663 020	10.29%	13.28%	18.35%
17	Europe	CZ	Czechia	10 739 974	9.57%	10.17%	18.29%
18	South America	AR	Argentina	45 842 519	4.94%	18.21%	18.21%
19	North America	US	USA	334 030 063	7.73%	20.09%	16.95%
20	Asia	GE	Georgia	3 977 221	10.87%	11.66%	16.95%
21	Europe	HU	Hungary	9 622 081	6.46%	8.48%	16.60%
22	North America	PA	Panama	4 420 639	3.26%	11.24%	16.36%
23	Europe	HR	Croatia	4 065 767	11.22%	16.27%	15.94%
24	Europe	GR	Greece	10 343 620	10.73%	26.69%	15.51%
25	Europe	RS	Serbia	8 682 461	7.00%	10.38%	15.28%
26	Europe	FI	Finland	5 554 147	5.19%	14.40%	14.26%
27	Australia/Oceania	AU	Australia	25 961 200	5.76%	20.16%	14.02%
28	Europe	GB	United Kingdom	68 442 235	11.77%	22.19%	11.70%
29	Europe	DE	Germany	84 201 843	5.15%	7.38%	10.91%
30	Asia	QA	Qatar	2 807 805	2.88%	9.91%	10.88%
31	South America	PE	Peru	33 687 878	1.79%	5.98%	10.82%
32	Europe	BG	Bulgaria	6 866 833	5.41%	7.61%	10.76%
33	North America	CR	Costa Rica	5 166 659	2.28%	4.84%	10.03%
34	Europe	IE	Ireland	5 023 789	14.89%	35.12%	9.96%
35	Europe	BA	Bosnia and Herzegovina	3 248 979	3.01%	5.08%	8.96%
36	Asia	KZ	Kazakhstan	19 126 888	1.35%	2.81%	8.41%
37	Europe	SK	Slovakia	5 463 768	9.13%	6.01%	8.37%
38	Asia	KW	Kuwait	4 369 023	1.66%	6.35%	7.32%
39	Asia	TR	Turkey	85 754 170	4.42%	7.16%	6.89%
40	Asia	LB	Lebanon	6 777 757	3.32%	8.12%	6.76%
41	Europe	PL	Poland	37 781 943	4.15%	4.54%	6.75%
42	Europe	RO	Romania	19 037 459	4.14%	3.66%	6.54%
43	Europe	MK	North Macedonia	2 083 241	3.01%	5.69%	6.32%
44	Europe	AL	Albania	2 872 895	2.64%	5.01%	6.28%
45	Europe	MD	Moldova	4 019 336	2.85%	2.87%	5.98%
46	South America	BO	Bolivia	11 921 255	2.43%	7.23%	5.67%
47	South America	PY	Paraguay	7 269 138	0.84%	3.07%	5.55%
48	Africa	TN	Tunisia	12 011 455	0.99%	3.39%	5.16%
49	North America	CA	Canada	38 258 213	3.29%	9.55%	4.93%
50	South America	CL	Chile	19 372 103	1.45%	2.78%	4.92%
51	South America	CO	Colombia	51 728 566	1.36%	4.14%	4.61%
52	North America	DO	Dominican R.	11 017 543	1.55%	4.15%	4.49%
53	Africa	BW	Botswana	2 425 610	2.89%	6.47%	4.43%
54	North America	JM	Jamaica	2 981 327	1.21%	3.41%	4.33%
55	South America	BR	Brazil	214 915 961	1.01%	2.37%	4.19%
56	Asia	JO	Jordan	10 361 084	2.95%	2.86%	3.87%
57	South America	EC	Ecuador	18 060 665	0.68%	2.04%	3.86%
58	Europe	UA	Ukraine	43 323 817	3.32%	1.76%	2.89%
59	Asia	SG	Singapore	5 922 099	3.63%	1.60%	2.66%
60	Asia	NP	Nepal	29 953 509	0.38%	1.04%	2.58%
61	Europe	RU	Russia	146 032 083	2.49%	1.87%	2.54%
62	Asia	JP	Japan	125 872 394	0.30%	1.06%	2.54%
63	North America	CU	Cuba	11 315 830	1.48%	1.80%	2.44%
64	Asia	AE	Arab Emirates	10 076 717	0.84%	2.84%	2.44%
65	Asia	OM	Oman	5 308 896	0.31%	1.12%	2.42%
66	Asia	PH	Philippines	111 854 893	0.79%	1.83%	2.21%
67	Asia	MN	Mongolia	3 360 577	3.53%	3.01%	2.15%
68	Asia	IN	India	1 401 161 559	0.37%	1.17%	1.83%
69	North America	MX	Mexico	131 045 037	0.65%	1.72%	1.76%
70	Asia	AM	Armenia	2 971 883	3.10%	0.84%	1.65%
71	Africa	LY	Libya	7 016 958	0.97%	1.09%	1.58%
72	Asia	VN	Vietnam	98 704 378	1.38%	1.98%	1.49%
73	Europe	BY	Belarus	9 444 474	2.06%	1.35%	1.34%
74	Asia	SA	Saudi Arabia	35 658 981	0.27%	1.02%	1.32%
75	Asia	IQ	Iraq	41 628 580	0.36%	0.48%	1.15%
76	Africa	MA	Morocco	37 592 691	0.39%	1.26%	1.13%
77	Asia	KR	South Korea	51 338 018	0.83%	0.97%	1.03%
78	Asia	KG	Kyrgyzstan	6 691 963	0.24%	0.59%	0.97%
79	Asia	TH	Thailand	70 073 197	1.15%	0.92%	0.92%
80	Asia	AZ	Azerbaijan	10 281 695	1.47%	0.68%	0.89%
81	Asia	LA	Laos	7 440 138	1.44%	1.30%	0.89%
82	Asia	MY	Malaysia	33 012 522	1.94%	1.08%	0.85%
83	North America	GT	Guatemala	18 432 019	0.62%	0.77%	0.81%
84	Africa	MR	Mauritania	4 839 988	0.44%	1.36%	0.67%
85	Asia	PS	Palestine	5 286 143	0.04%	0.15%	0.65%
86	Africa	GA	Gabon	2 307 540	0.73%	1.36%	0.64%
87	Africa	NA	Namibia	2 612 616	1.06%	2.20%	0.56%
88	South America	VE	Venezuela	28 310 238	0.36%	0.28%	0.53%
89	North America	HN	Honduras	10 150 147	0.25%	0.28%	0.53%
90	Asia	BD	Bangladesh	167 247 937	0.07%	0.20%	0.45%
91	Africa	ZA	South Africa	60 474 528	1.12%	1.20%	0.44%
92	Asia	IR	Iran	85 669 059	0.84%	0.28%	0.41%
93	Africa	ZM	Zambia	19 185 632	0.48%	1.49%	0.38%
94	Africa	GM	Gambia	2 522 383	0.07%	0.24%	0.31%
95	Asia	UZ	Uzbekistan	34 225 348	0.12%	0.16%	0.30%
96	Africa	CM	Cameroon	27 575 039	0.10%	0.08%	0.28%
97	Africa	RW	Rwanda	13 452 288	0.23%	0.70%	0.28%
98	Asia	LK	Sri Lanka	21 553 297	0.40%	0.31%	0.25%
99	Africa	DZ	Algeria	45 085 057	0.07%	0.15%	0.25%
100	Africa	GW	Guinea-Bissau	2 040 454	0.06%	0.16%	0.23%
101	Africa	LS	Lesotho	2 168 734	0.81%	1.09%	0.23%
102	Asia	PK	Pakistan	227 575 840	0.05%	0.11%	0.22%
103	Africa	ZW	Zimbabwe	15 200 203	0.65%	0.66%	0.19%
104	Africa	ER	Eritrea	3 622 939	0.07%	0.15%	0.14%
105	Africa	MZ	Mozambique	32 618 926	0.22%	0.70%	0.13%
106	Australia/Oceania	NZ	New Zealand	5 002 100	0.23%	0.13%	0.12%
107	Africa	SN	Senegal	17 431 071	0.06%	0.22%	0.12%
108	Africa	AO	Angola	34 457 759	0.12%	0.30%	0.11%
109	Africa	SD	Sudan	45 444 056	0.03%	0.07%	0.11%
110	Africa	GH	Ghana	32 083 509	0.09%	0.26%	0.11%
111	Africa	MG	Madagascar	28 799 689	0.04%	0.12%	0.10%
112	Africa	EG	Egypt	105 342 137	0.10%	0.10%	0.09%
113	Africa	BI	Burundi	12 442 129	0.16%	0.45%	0.08%
114	Africa	CG	Congo	5 729 635	0.16%	0.28%	0.07%
115	Asia	HK	Hong Kong	7 591 837	0.01%	0.03%	0.07%
116	Africa	ML	Mali	21 158 994	0.07%	0.18%	0.07%
117	Asia	ID	Indonesia	278 033 665	0.03%	0.03%	0.07%
118	Africa	GN	Guinea	13 687 504	0.04%	0.14%	0.07%
119	Africa	CF	Central African R.	4 960 640	0.04%	0.12%	0.07%
120	Africa	MW	Malawi	19 899 799	0.11%	0.28%	0.06%
121	Africa	KE	Kenya	55 616 509	0.13%	0.30%	0.06%
122	Africa	ET	Ethiopia	119 398 868	0.10%	0.24%	0.05%
123	Africa	TG	Togo	8 580 963	0.13%	0.41%	0.05%
124	Africa	TZ	Tanzania	62 383 386	0.01%	0.04%	0.05%
125	North America	HT	Haiti	11 619 253	0.06%	0.08%	0.05%
126	Africa	UG	Uganda	47 989 608	0.08%	0.22%	0.05%
127	Africa	SL	Sierra Leone	8 229 738	0.01%	0.04%	0.04%
128	Africa	BJ	Benin	12 617 712	0.03%	0.04%	0.04%
129	Africa	BF	Burkina Faso	21 795 816	0.03%	0.06%	0.04%
130	Asia	TW	Taiwan	23 884 021	0.01%	0.02%	0.04%
131	Africa	CD	DR Congo	93 800 235	0.03%	0.06%	0.04%
132	Asia	AF	Afghanistan	40 294 100	0.01%	0.02%	0.03%
133	Africa	TD	Chad	17 159 734	0.01%	0.03%	0.03%
134	Africa	CI	Ivory Coast	27 395 647	0.07%	0.24%	0.03%
135	Africa	LR	Liberia	5 242 850	0.03%	0.10%	0.03%
136	Africa	SS	South Sudan	11 398 347	0.04%	0.10%	0.03%
137	Asia	MM	Myanmar	54 978 693	0.14%	0.03%	0.02%
138	Asia	YE	Yemen	30 849 332	0.01%	0.01%	0.02%
139	Asia	KH	Cambodia	17 079 678	0.07%	0.01%	0.02%
140	North America	NI	Nicaragua	6 747 441	0.04%	0.01%	0.01%
141	Asia	SY	Syria	18 162 836	0.10%	0.02%	0.01%
142	Africa	NG	Nigeria	214 097 230	0.02%	0.03%	0.01%
143	Africa	NE	Niger	25 570 103	0.01%	0.02%	0.01%
144	Asia	TJ	Tajikistan	9 871 366	0.00%	0.00%	0.01%
145	Australia/Oceania	PG	Papua New Guinea	9 211 126	0.19%	0.02%	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	North America	SV	El Salvador	6 537 253	0.33%	0.11%	0.00%
149	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
150	Africa	SO	Somalia	16 583 651	0.03%	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	Asia	YE	Yemen	30 849 332	19.27%	(8.96)%	(0.01)%
2	Asia	SY	Syria	18 162 836	3.74%	(8.53)%	(0.02)%
3	Asia	AF	Afghanistan	40 294 100	4.45%	(3.79)%	(0.02)%
4	Europe	RU	Russia	146 032 083	3.41%	3.43%	1.87%
5	North America	NI	Nicaragua	6 747 441	0.48%	(3.13)%	(0.01)%
6	Europe	UA	Ukraine	43 323 817	3.08%	2.81%	1.76%
7	Africa	EG	Egypt	105 342 137	4.94%	(2.75)%	(0.10)%
8	Europe	BA	Bosnia and Herzegovina	3 248 979	4.18%	2.72%	5.08%
9	Europe	PL	Poland	37 781 943	1.97%	2.45%	4.54%
10	Asia	LK	Sri Lanka	21 553 297	2.80%	2.23%	0.31%
11	Europe	BG	Bulgaria	6 866 833	3.57%	2.13%	7.61%
12	Africa	MG	Madagascar	28 799 689	1.88%	2.08%	0.12%
13	Asia	KH	Cambodia	17 079 678	4.60%	(2.05)%	(0.01)%
14	Africa	DZ	Algeria	45 085 057	2.82%	2.04%	0.15%
15	Europe	HU	Hungary	9 622 081	2.03%	2.03%	8.48%
16	Asia	AM	Armenia	2 971 883	2.95%	1.96%	0.84%
17	Europe	MD	Moldova	4 019 336	3.02%	1.92%	2.87%
18	Africa	NE	Niger	25 570 103	3.90%	1.83%	0.02%
19	Asia	AZ	Azerbaijan	10 281 695	1.39%	1.82%	0.68%
20	Africa	SD	Sudan	45 444 056	4.28%	1.76%	0.07%
21	Asia	IR	Iran	85 669 059	1.61%	1.64%	0.28%
22	Europe	SK	Slovakia	5 463 768	1.05%	1.63%	6.01%
23	Africa	LY	Libya	7 016 958	1.95%	1.61%	1.09%
24	Africa	ER	Eritrea	3 622 939	2.19%	1.61%	0.15%
25	Australia/Oceania	PG	Papua New Guinea	9 211 126	2.12%	1.48%	0.02%
26	Africa	NA	Namibia	2 612 616	1.36%	1.43%	2.20%
27	Asia	ID	Indonesia	278 033 665	3.37%	1.35%	0.03%
28	Asia	GE	Georgia	3 977 221	1.45%	1.32%	11.66%
29	Europe	BY	Belarus	9 444 474	0.90%	1.27%	1.35%
30	North America	SV	El Salvador	6 537 253	2.81%	1.23%	0.11%
31	Europe	MK	North Macedonia	2 083 241	2.70%	1.22%	5.69%
32	Africa	ZW	Zimbabwe	15 200 203	0.69%	1.13%	0.66%
33	South America	EC	Ecuador	18 060 665	1.85%	1.12%	2.04%
34	Africa	ZA	South Africa	60 474 528	1.02%	1.12%	1.20%
35	Asia	MM	Myanmar	54 978 693	2.05%	1.11%	0.03%
36	Asia	VN	Vietnam	98 704 378	1.34%	1.10%	1.98%
37	Africa	BF	Burkina Faso	21 795 816	2.92%	1.09%	0.06%
38	Africa	CM	Cameroon	27 575 039	2.06%	1.05%	0.08%
39	Asia	KR	South Korea	51 338 018	0.99%	0.98%	0.97%
40	Africa	MW	Malawi	19 899 799	1.08%	0.98%	0.28%
41	South America	PY	Paraguay	7 269 138	2.02%	0.93%	3.07%
42	Asia	JO	Jordan	10 361 084	0.82%	0.92%	2.86%
43	Africa	GW	Guinea-Bissau	2 040 454	2.05%	0.91%	0.16%
44	Europe	RO	Romania	19 037 459	3.06%	0.90%	3.66%
45	Asia	KG	Kyrgyzstan	6 691 963	1.92%	0.84%	0.59%
46	Africa	CD	DR Congo	93 800 235	0.79%	0.76%	0.06%
47	Europe	HR	Croatia	4 065 767	1.12%	0.75%	16.27%
48	Asia	LA	Laos	7 440 138	0.47%	0.72%	1.30%
49	North America	HN	Honduras	10 150 147	3.22%	0.71%	0.28%
50	Asia	IQ	Iraq	41 628 580	1.56%	0.66%	0.48%
51	North America	JM	Jamaica	2 981 327	2.45%	0.66%	3.41%
52	Africa	UG	Uganda	47 989 608	0.89%	0.66%	0.22%
53	North America	HT	Haiti	11 619 253	2.57%	0.66%	0.08%
54	Europe	LT	Lithuania	2 663 020	1.10%	0.65%	13.28%
55	North America	MX	Mexico	131 045 037	2.55%	0.65%	1.72%
56	South America	VE	Venezuela	28 310 238	1.01%	0.63%	0.28%
57	Asia	UZ	Uzbekistan	34 225 348	0.83%	0.62%	0.16%
58	Africa	CF	Central African R.	4 960 640	0.45%	0.59%	0.12%
59	Europe	CZ	Czechia	10 739 974	0.71%	0.58%	10.17%
60	Asia	PH	Philippines	111 854 893	1.84%	0.58%	1.83%
61	Asia	MY	Malaysia	33 012 522	0.92%	0.57%	1.08%
62	Africa	TN	Tunisia	12 011 455	1.32%	0.57%	3.39%
63	Africa	ML	Mali	21 158 994	1.17%	0.56%	0.18%
64	South America	CL	Chile	19 372 103	0.89%	0.56%	2.78%
65	Africa	GN	Guinea	13 687 504	0.71%	0.52%	0.14%
66	Europe	DE	Germany	84 201 843	0.60%	0.50%	7.38%
67	South America	BO	Bolivia	11 921 255	0.70%	0.50%	7.23%
68	South America	PE	Peru	33 687 878	1.20%	0.50%	5.98%
69	South America	BR	Brazil	214 915 961	1.50%	0.49%	2.37%
70	South America	CO	Colombia	51 728 566	0.97%	0.49%	4.14%
71	Africa	AO	Angola	34 457 759	0.96%	0.49%	0.30%
72	Asia	KZ	Kazakhstan	19 126 888	1.46%	0.48%	2.81%
73	Africa	TD	Chad	17 159 734	0.72%	0.47%	0.03%
74	Africa	TZ	Tanzania	62 383 386	0.13%	0.47%	0.04%
75	Africa	GM	Gambia	2 522 383	1.04%	0.46%	0.24%
76	Africa	NG	Nigeria	214 097 230	0.91%	0.46%	0.03%
77	Africa	GH	Ghana	32 083 509	0.78%	0.45%	0.26%
78	Asia	PK	Pakistan	227 575 840	1.48%	0.45%	0.11%
79	Europe	RS	Serbia	8 682 461	0.90%	0.43%	10.38%
80	North America	GT	Guatemala	18 432 019	2.39%	0.42%	0.77%
81	Africa	ET	Ethiopia	119 398 868	1.48%	0.40%	0.24%
82	Europe	AL	Albania	2 872 895	0.94%	0.39%	5.01%
83	Africa	MR	Mauritania	4 839 988	0.77%	0.39%	1.36%
84	Asia	IN	India	1 401 161 559	1.07%	0.35%	1.17%
85	Asia	LB	Lebanon	6 777 757	0.57%	0.35%	8.12%
86	Europe	GR	Greece	10 343 620	0.76%	0.34%	26.69%
87	Africa	CI	Ivory Coast	27 395 647	0.85%	0.34%	0.24%
88	Africa	SN	Senegal	17 431 071	0.70%	0.34%	0.22%
89	Asia	TR	Turkey	85 754 170	0.62%	0.33%	7.16%
90	Africa	KE	Kenya	55 616 509	0.63%	0.32%	0.30%
91	Africa	RW	Rwanda	13 452 288	0.58%	0.32%	0.70%
92	Asia	BD	Bangladesh	167 247 937	0.96%	0.32%	0.20%
93	Asia	TH	Thailand	70 073 197	0.67%	0.32%	0.92%
94	Africa	LS	Lesotho	2 168 734	1.67%	0.31%	1.09%
95	Africa	MZ	Mozambique	32 618 926	0.35%	0.30%	0.70%
96	Africa	BW	Botswana	2 425 610	0.26%	0.30%	6.47%
97	North America	US	USA	334 030 063	0.70%	0.29%	20.09%
98	North America	CR	Costa Rica	5 166 659	1.28%	0.28%	4.84%
99	Africa	ZM	Zambia	19 185 632	0.27%	0.24%	1.49%
100	Africa	MA	Morocco	37 592 691	0.68%	0.23%	1.26%
101	North America	CA	Canada	38 258 213	0.38%	0.22%	9.55%
102	Europe	SI	Slovenia	2 079 384	0.54%	0.22%	23.80%
103	Africa	SL	Sierra Leone	8 229 738	0.40%	0.22%	0.04%
104	Africa	TG	Togo	8 580 963	0.38%	0.21%	0.41%
105	North America	PA	Panama	4 420 639	0.36%	0.19%	11.24%
106	Europe	IT	Italy	60 323 122	0.30%	0.19%	26.45%
107	Africa	GA	Gabon	2 307 540	0.69%	0.18%	1.36%
108	Africa	BJ	Benin	12 617 712	0.20%	0.18%	0.04%
109	Asia	OM	Oman	5 308 896	0.35%	0.17%	1.12%
110	Africa	SO	Somalia	16 583 651	4.50%	0.17%	0.03%
111	Asia	NP	Nepal	29 953 509	0.72%	0.17%	1.04%
112	Asia	SG	Singapore	5 922 099	0.36%	0.16%	1.60%
113	South America	PR	Puerto Rico	3 193 694	0.23%	0.16%	28.61%
114	Asia	MN	Mongolia	3 360 577	0.66%	0.16%	3.01%
115	Europe	BE	Belgium	11 668 299	0.26%	0.15%	21.11%
116	Europe	AT	Austria	9 086 551	0.37%	0.14%	13.21%
117	Europe	GB	United Kingdom	68 442 235	0.22%	0.13%	22.19%
118	Europe	FI	Finland	5 554 147	0.29%	0.12%	14.40%
119	Africa	SS	South Sudan	11 398 347	0.34%	0.11%	0.10%
120	Australia/Oceania	NZ	New Zealand	5 002 100	0.23%	0.11%	0.13%
121	North America	CU	Cuba	11 315 830	0.58%	0.11%	1.80%
122	Europe	SE	Sweden	10 197 485	0.19%	0.11%	18.76%
123	South America	UY	Uruguay	3 492 509	0.19%	0.11%	16.72%
124	South America	AR	Argentina	45 842 519	0.21%	0.10%	18.21%
125	Europe	FR	France	65 498 824	0.16%	0.10%	41.34%
126	Africa	CG	Congo	5 729 635	1.89%	0.10%	0.28%
127	Europe	PT	Portugal	10 150 323	0.19%	0.09%	33.07%
128	Asia	TW	Taiwan	23 884 021	0.57%	0.09%	0.02%
129	Europe	ES	Spain	46 783 030	0.15%	0.09%	27.32%
130	Europe	NO	Norway	5 487 352	0.16%	0.09%	15.39%
131	Asia	AE	Arab Emirates	10 076 717	0.16%	0.09%	2.84%
132	Europe	NL	Netherlands	17 194 015	0.19%	0.09%	17.36%
133	Europe	CH	Switzerland	8 753 333	0.18%	0.08%	28.25%
134	Africa	LR	Liberia	5 242 850	0.36%	0.08%	0.10%
135	Asia	SA	Saudi Arabia	35 658 981	0.32%	0.07%	1.02%
136	Europe	DK	Denmark	5 824 020	0.11%	0.07%	41.90%
137	Australia/Oceania	AU	Australia	25 961 200	0.13%	0.07%	20.16%
138	Asia	JP	Japan	125 872 394	0.50%	0.07%	1.06%
139	North America	DO	Dominican R.	11 017 543	0.17%	0.05%	4.15%
140	Europe	IE	Ireland	5 023 789	0.12%	0.04%	35.12%
141	Asia	QA	Qatar	2 807 805	0.05%	0.04%	9.91%
142	Asia	IL	Israel	9 326 000	0.12%	0.03%	36.47%
143	Asia	KW	Kuwait	4 369 023	0.07%	0.03%	6.35%
144	Africa	BI	Burundi	12 442 129	0.00%	0.00%	0.45%
145	Asia	HK	Hong Kong	7 591 837	0.00%	0.00%	0.03%
146	Asia	PS	Palestine	5 286 143	0.00%	0.00%	0.15%
147	Asia	TJ	Tajikistan	9 871 366	0.00%	0.00%	0.00%
148	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
149	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
150	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%

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

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

N.	Region	CD	Country	Population	Deaths	*1000Deaths/Pop.**
1	South America	PE	Peru	33 687 878	203 932	6.054‰
2	Europe	BG	Bulgaria	6 866 833	32 546	4.740‰
3	Europe	BA	Bosnia and Herzegovina	3 248 979	13 951	4.294‰
4	Europe	HU	Hungary	9 622 081	40 944	4.255‰
5	Europe	MK	North Macedonia	2 083 241	8 186	3.929‰
6	Asia	GE	Georgia	3 977 221	14 662	3.687‰
7	Europe	CZ	Czechia	10 739 974	37 001	3.445‰
8	Europe	HR	Croatia	4 065 767	13 336	3.280‰
9	Europe	SK	Slovakia	5 463 768	17 609	3.223‰
10	Europe	RO	Romania	19 037 459	59 468	3.124‰
11	Europe	SI	Slovenia	2 079 384	6 234	2.998‰
12	Europe	LT	Lithuania	2 663 020	7 729	2.902‰
13	South America	BR	Brazil	214 915 961	622 021	2.894‰
14	Europe	PL	Poland	37 781 943	103 628	2.743‰
15	Asia	AM	Armenia	2 971 883	8 026	2.701‰
16	Europe	MD	Moldova	4 019 336	10 497	2.612‰
17	South America	AR	Argentina	45 842 519	118 693	2.589‰
18	North America	US	USA	334 030 063	852 908	2.553‰
19	South America	CO	Colombia	51 728 566	131 654	2.545‰
20	Europe	BE	Belgium	11 668 299	28 759	2.465‰
21	Europe	IT	Italy	60 323 122	142 817	2.368‰
22	South America	PY	Paraguay	7 269 138	16 904	2.325‰
23	North America	MX	Mexico	131 045 037	302 210	2.306‰
24	Europe	UA	Ukraine	43 323 817	99 060	2.287‰
25	Europe	GB	United Kingdom	68 442 235	153 277	2.240‰
26	Europe	RU	Russia	146 032 083	325 431	2.228‰
27	Europe	GR	Greece	10 343 620	22 452	2.171‰
28	Africa	TN	Tunisia	12 011 455	25 899	2.156‰
29	South America	CL	Chile	19 372 103	39 471	2.038‰
30	Europe	ES	Spain	46 783 030	91 599	1.958‰
31	Europe	PT	Portugal	10 150 323	19 477	1.919‰
32	Europe	FR	France	65 498 824	125 528	1.917‰
33	South America	EC	Ecuador	18 060 665	34 232	1.895‰
34	South America	UY	Uruguay	3 492 509	6 263	1.793‰
35	South America	BO	Bolivia	11 921 255	20 461	1.716‰
36	North America	PA	Panama	4 420 639	7 569	1.712‰
37	Africa	ZA	South Africa	60 474 528	93 900	1.553‰
38	Asia	IR	Iran	85 669 059	132 180	1.543‰
39	Europe	SE	Sweden	10 197 485	15 631	1.533‰
40	Europe	RS	Serbia	8 682 461	13 213	1.522‰
41	Europe	AT	Austria	9 086 551	13 510	1.487‰
42	Africa	NA	Namibia	2 612 616	3 864	1.479‰
43	North America	CR	Costa Rica	5 166 659	7 434	1.439‰
44	Asia	LB	Lebanon	6 777 757	9 442	1.393‰
45	Europe	CH	Switzerland	8 753 333	12 142	1.387‰
46	Europe	DE	Germany	84 201 843	116 516	1.384‰
47	Asia	JO	Jordan	10 361 084	13 039	1.258‰
48	Europe	NL	Netherlands	17 194 015	21 189	1.232‰
49	Europe	IE	Ireland	5 023 789	6 087	1.212‰
50	Europe	AL	Albania	2 872 895	3 294	1.147‰
51	South America	PR	Puerto Rico	3 193 694	3 593	1.125‰
52	Africa	BW	Botswana	2 425 610	2 544	1.049‰
53	North America	HN	Honduras	10 150 147	10 458	1.030‰
54	Asia	TR	Turkey	85 754 170	85 604	0.998‰
55	Asia	MY	Malaysia	33 012 522	31 863	0.965‰
56	Asia	KZ	Kazakhstan	19 126 888	18 357	0.960‰
57	Asia	IL	Israel	9 326 000	8 393	0.900‰
58	North America	GT	Guatemala	18 432 019	16 208	0.879‰
59	North America	JM	Jamaica	2 981 327	2 583	0.866‰
60	Africa	LY	Libya	7 016 958	5 904	0.841‰
61	North America	CA	Canada	38 258 213	32 103	0.839‰
62	Asia	AZ	Azerbaijan	10 281 695	8 577	0.834‰
63	Asia	OM	Oman	5 308 896	4 126	0.777‰
64	North America	CU	Cuba	11 315 830	8 357	0.739‰
65	Asia	LK	Sri Lanka	21 553 297	15 270	0.709‰
66	Europe	BY	Belarus	9 444 474	5 898	0.625‰
67	Europe	DK	Denmark	5 824 020	3 562	0.612‰
68	Asia	MN	Mongolia	3 360 577	2 016	0.600‰
69	North America	SV	El Salvador	6 537 253	3 844	0.588‰
70	Asia	IQ	Iraq	41 628 580	24 276	0.583‰
71	Asia	KW	Kuwait	4 369 023	2 481	0.568‰
72	Asia	ID	Indonesia	278 033 665	144 215	0.519‰
73	Asia	PH	Philippines	111 854 893	53 200	0.476‰
74	Asia	KG	Kyrgyzstan	6 691 963	2 845	0.425‰
75	Africa	MA	Morocco	37 592 691	15 044	0.400‰
76	Asia	NP	Nepal	29 953 509	11 639	0.389‰
77	North America	DO	Dominican R.	11 017 543	4 276	0.388‰
78	Asia	VN	Vietnam	98 704 378	36 431	0.369‰
79	Asia	MM	Myanmar	54 978 693	19 308	0.351‰
80	Asia	IN	India	1 401 161 559	488 870	0.349‰
81	Africa	ZW	Zimbabwe	15 200 203	5 282	0.347‰
82	Europe	FI	Finland	5 554 147	1 815	0.327‰
83	Africa	LS	Lesotho	2 168 734	690	0.318‰
84	Asia	TH	Thailand	70 073 197	22 013	0.314‰
85	Europe	NO	Norway	5 487 352	1 414	0.258‰
86	Asia	SA	Saudi Arabia	35 658 981	8 916	0.250‰
87	Asia	QA	Qatar	2 807 805	633	0.225‰
88	Asia	AE	Arab Emirates	10 076 717	2 209	0.219‰
89	Africa	EG	Egypt	105 342 137	22 276	0.211‰
90	Africa	ZM	Zambia	19 185 632	3 884	0.202‰
91	South America	VE	Venezuela	28 310 238	5 395	0.191‰
92	Africa	MR	Mauritania	4 839 988	919	0.190‰
93	Asia	AF	Afghanistan	40 294 100	7 386	0.183‰
94	Asia	KH	Cambodia	17 079 678	3 015	0.176‰
95	Asia	BD	Bangladesh	167 247 937	28 195	0.169‰
96	Asia	SY	Syria	18 162 836	2 959	0.163‰
97	Asia	JP	Japan	125 872 394	18 485	0.147‰
98	Africa	DZ	Algeria	45 085 057	6 467	0.143‰
99	Asia	SG	Singapore	5 922 099	846	0.143‰
100	Africa	GM	Gambia	2 522 383	347	0.138‰
101	Africa	GA	Gabon	2 307 540	299	0.130‰
102	Asia	PK	Pakistan	227 575 840	29 050	0.128‰
103	Asia	KR	South Korea	51 338 018	6 526	0.127‰
104	Africa	MW	Malawi	19 899 799	2 506	0.126‰
105	Australia/Oceania	AU	Australia	25 961 200	2 954	0.114‰
106	Africa	SN	Senegal	17 431 071	1 919	0.110‰
107	Africa	RW	Rwanda	13 452 288	1 422	0.106‰
108	Africa	KE	Kenya	55 616 509	5 543	0.100‰
109	Africa	SO	Somalia	16 583 651	1 335	0.081‰
110	Africa	GW	Guinea-Bissau	2 040 454	154	0.075‰
111	Africa	SD	Sudan	45 444 056	3 393	0.075‰
112	Africa	UG	Uganda	47 989 608	3 472	0.072‰
113	Asia	LA	Laos	7 440 138	509	0.068‰
114	Africa	CM	Cameroon	27 575 039	1 867	0.068‰
115	North America	HT	Haiti	11 619 253	780	0.067‰
116	Africa	MZ	Mozambique	32 618 926	2 150	0.066‰
117	Africa	CG	Congo	5 729 635	371	0.065‰
118	Australia/Oceania	PG	Papua New Guinea	9 211 126	596	0.065‰
119	Asia	YE	Yemen	30 849 332	1 995	0.065‰
120	Africa	ET	Ethiopia	119 398 868	7 220	0.060‰
121	Africa	LR	Liberia	5 242 850	288	0.055‰
122	Africa	AO	Angola	34 457 759	1 883	0.055‰
123	Asia	UZ	Uzbekistan	34 225 348	1 534	0.045‰
124	Africa	GH	Ghana	32 083 509	1 367	0.043‰
125	Africa	MG	Madagascar	28 799 689	1 169	0.041‰
126	Asia	TW	Taiwan	23 884 021	851	0.036‰
127	Africa	ML	Mali	21 158 994	705	0.033‰
128	North America	NI	Nicaragua	6 747 441	219	0.033‰
129	Africa	TG	Togo	8 580 963	266	0.031‰
130	Africa	GN	Guinea	13 687 504	412	0.030‰
131	Asia	HK	Hong Kong	7 591 837	213	0.028‰
132	Africa	CI	Ivory Coast	27 395 647	765	0.028‰
133	Africa	ER	Eritrea	3 622 939	91	0.025‰
134	Africa	CF	Central African R.	4 960 640	109	0.022‰
135	Africa	BF	Burkina Faso	21 795 816	353	0.016‰
136	Africa	SL	Sierra Leone	8 229 738	125	0.015‰
137	Africa	NG	Nigeria	214 097 230	3 123	0.015‰
138	Africa	CD	DR Congo	93 800 235	1 278	0.014‰
139	Africa	BJ	Benin	12 617 712	163	0.013‰
140	Africa	TZ	Tanzania	62 383 386	753	0.012‰
141	Africa	SS	South Sudan	11 398 347	137	0.012‰
142	Africa	NE	Niger	25 570 103	296	0.012‰
143	Africa	TD	Chad	17 159 734	185	0.011‰
144	Australia/Oceania	NZ	New Zealand	5 002 100	52	0.010‰
145	Asia	PS	Palestine	5 286 143	7	0.001‰
146	Africa	BI	Burundi	12 442 129	14	0.001‰
147	Asia	CN	China	1 439 323 776	0	0.000‰
148	Asia	KP	North Korea	25 660 000	0	0.000‰
149	Asia	TJ	Tajikistan	9 871 366	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"