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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": 2022-01-22 13:32
(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 (+0)	+0 (+0)
CZ	Czechia	+26 597 (+26 923)	+9 (+18)
DE	Germany	+0 (+138 634)	+0 (+175)
HU	Hungary	+0 (+15 957)	+0 (+65)
PL	Poland	+40 876 (+36 667)	+193 (+248)
SK	Slovakia, [gov], [okr]	+6 478 (+7 035)	+35 (+57)

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

N.	Region	Population	Last 120 days	Last 30 days	Last 7 days
1	Europe	756 338 364	7.07%	15.61%	20.24%
2	North America	595 856 169	5.03%	13.45%	16.50%
3	Australia/Oceania	43 586 060	3.61%	12.47%	13.72%
4	South America	439 532 990	1.67%	5.07%	9.54%
5	Asia	4 687 071 694	0.40%	0.84%	1.58%
6	Africa	1 389 790 554	0.17%	0.37%	0.32%

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	1 389 790 554	1.20%	0.88%	0.37%
2	Asia	4 687 071 694	1.07%	0.59%	0.84%
3	Europe	756 338 364	0.83%	0.43%	15.61%
4	South America	439 532 990	1.03%	0.42%	5.07%
5	North America	595 856 169	0.82%	0.40%	13.45%
6	Australia/Oceania	43 586 060	0.22%	0.09%	12.47%

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	439 532 990	1 205 661	2.743‰
2	North America	595 856 169	1 258 691	2.112‰
3	Europe	756 338 364	1 589 331	2.101‰
4	Asia	4 687 071 694	1 272 780	0.272‰
5	Africa	1 389 790 554	236 141	0.170‰
6	Australia/Oceania	43 586 060	5 577	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	10.46%	37.37%	84.27%
2	Europe	DK	Denmark	5 823 908	16.51%	43.62%	69.62%
3	Europe	FR	France	65 498 037	13.49%	43.07%	62.43%
4	Europe	PT	Portugal	10 150 485	10.38%	34.50%	51.27%
5	Europe	SI	Slovenia	2 079 382	14.05%	24.54%	49.29%
6	South America	UY	Uruguay	3 492 443	4.81%	17.27%	35.45%
7	Europe	BE	Belgium	11 668 024	12.60%	22.72%	35.43%
8	Europe	IT	Italy	60 323 606	8.20%	27.35%	35.26%
9	Europe	SE	Sweden	10 197 141	5.82%	18.76%	34.22%
10	North America	PA	Panama	4 420 267	3.38%	11.80%	28.88%
11	South America	AR	Argentina	45 840 255	5.06%	18.85%	28.86%
12	Europe	CH	Switzerland	8 752 988	11.66%	28.56%	28.70%
13	Europe	NO	Norway	5 487 121	7.48%	16.66%	28.16%
14	Europe	NL	Netherlands	17 193 809	10.39%	17.77%	27.69%
15	North America	US	USA	334 019 477	7.98%	21.41%	26.26%
16	Europe	AT	Austria	9 086 270	8.87%	12.40%	26.08%
17	Europe	ES	Spain	46 782 931	8.60%	27.90%	25.82%
18	Europe	LT	Lithuania	2 663 226	10.50%	14.15%	24.19%
19	Europe	HR	Croatia	4 065 905	11.38%	17.36%	23.83%
20	Europe	CZ	Czechia	10 739 865	9.70%	11.03%	23.12%
21	South America	PR	Puerto Rico	3 193 694	7.76%	28.61%	22.79%
22	Australia/Oceania	AU	Australia	25 959 584	5.82%	20.64%	22.53%
23	Asia	GE	Georgia	3 977 262	11.01%	12.38%	22.23%
24	Europe	GR	Greece	10 343 896	10.85%	27.57%	21.58%
25	Europe	RS	Serbia	8 682 653	7.20%	10.69%	20.82%
26	Europe	IE	Ireland	5 023 488	14.97%	36.75%	19.24%
27	Europe	GB	United Kingdom	68 440 290	11.90%	23.74%	16.11%
28	Asia	QA	Qatar	2 807 805	2.89%	9.98%	15.84%
29	South America	PE	Peru	33 685 367	1.82%	6.11%	15.72%
30	Europe	FI	Finland	5 554 100	5.19%	14.40%	14.26%
31	Europe	BG	Bulgaria	6 867 117	5.55%	8.19%	14.21%
32	Europe	DE	Germany	84 200 383	5.25%	7.96%	13.96%
33	Europe	HU	Hungary	9 622 214	6.05%	6.97%	13.26%
34	South America	BO	Bolivia	11 920 384	2.49%	7.57%	11.99%
35	Asia	KW	Kuwait	4 368 678	1.67%	6.41%	11.04%
36	Europe	SK	Slovakia	5 463 753	9.22%	6.65%	10.63%
37	North America	CR	Costa Rica	5 166 405	2.35%	5.31%	10.51%
38	Asia	LB	Lebanon	6 777 923	3.33%	8.30%	9.49%
39	Asia	TR	Turkey	85 749 213	4.49%	7.37%	9.39%
40	Europe	MK	North Macedonia	2 083 241	3.09%	5.93%	9.31%
41	Europe	AL	Albania	2 872 912	2.73%	5.23%	9.19%
42	Europe	RO	Romania	19 038 156	4.26%	3.85%	8.79%
43	Europe	BA	Bosnia and Herzegovina	3 249 090	3.06%	5.33%	8.65%
44	Europe	PL	Poland	37 782 168	4.19%	4.94%	8.43%
45	Asia	KZ	Kazakhstan	19 125 661	1.35%	2.81%	8.41%
46	Africa	TN	Tunisia	12 010 779	1.03%	3.50%	7.94%
47	North America	CA	Canada	38 256 407	3.34%	10.01%	7.92%
48	South America	PY	Paraguay	7 268 659	0.86%	3.14%	7.55%
49	Europe	MD	Moldova	4 019 387	2.94%	3.10%	7.53%
50	South America	CO	Colombia	51 725 604	1.37%	4.21%	7.11%
51	South America	CL	Chile	19 371 207	1.47%	2.88%	6.76%
52	North America	DO	Dominican R.	11 016 949	1.59%	4.31%	6.44%
53	South America	BR	Brazil	214 907 717	1.07%	2.54%	6.15%
54	North America	JM	Jamaica	2 981 257	1.22%	3.42%	5.02%
55	Asia	JO	Jordan	10 360 531	2.96%	3.01%	4.73%
56	Asia	MN	Mongolia	3 360 288	3.69%	3.13%	4.70%
57	Africa	BW	Botswana	2 425 350	2.89%	6.47%	4.43%
58	South America	EC	Ecuador	18 059 200	0.71%	2.17%	4.03%
59	Europe	UA	Ukraine	43 325 246	3.38%	1.95%	3.72%
60	Asia	AE	Arab Emirates	10 076 064	0.85%	2.95%	3.56%
61	North America	CU	Cuba	11 315 868	1.62%	1.80%	3.50%
62	Asia	PH	Philippines	111 846 922	0.82%	1.85%	3.46%
63	Asia	JP	Japan	125 874 500	0.30%	1.07%	3.22%
64	Asia	NP	Nepal	29 950 642	0.38%	1.04%	3.18%
65	Europe	RU	Russia	146 031 742	2.51%	1.99%	3.18%
66	Asia	SG	Singapore	5 921 848	3.68%	1.62%	3.09%
67	Asia	OM	Oman	5 308 184	0.28%	1.01%	2.56%
68	North America	MX	Mexico	131 037 639	0.68%	1.83%	2.52%
69	Asia	IN	India	1 401 087 479	0.38%	1.18%	2.51%
70	Asia	VN	Vietnam	98 699 597	1.40%	2.12%	2.07%
71	Asia	AM	Armenia	2 971 853	3.17%	0.91%	2.03%
72	Africa	MA	Morocco	37 590 301	0.40%	1.31%	1.96%
73	Asia	SA	Saudi Arabia	35 656 016	0.27%	1.03%	1.85%
74	Europe	BY	Belarus	9 444 491	2.10%	1.48%	1.80%
75	Africa	LY	Libya	7 016 448	0.97%	1.12%	1.64%
76	North America	GT	Guatemala	18 430 206	0.66%	0.84%	1.54%
77	Asia	IQ	Iraq	41 623 636	0.38%	0.51%	1.49%
78	Asia	KG	Kyrgyzstan	6 691 375	0.25%	0.61%	1.48%
79	Asia	TH	Thailand	70 072 243	1.19%	0.96%	1.31%
80	Asia	LA	Laos	7 439 561	1.45%	1.45%	1.28%
81	Asia	KR	South Korea	51 337 777	0.84%	1.06%	1.28%
82	Asia	MY	Malaysia	33 010 256	2.02%	1.17%	1.18%
83	Africa	MR	Mauritania	4 839 318	0.44%	1.38%	1.17%
84	Asia	AZ	Azerbaijan	10 281 196	1.49%	0.71%	1.04%
85	South America	VE	Venezuela	28 310 676	0.37%	0.30%	0.76%
86	Africa	ZA	South Africa	60 470 442	1.13%	1.48%	0.69%
87	North America	HN	Honduras	10 149 286	0.25%	0.31%	0.69%
88	Africa	ZM	Zambia	19 182 807	0.48%	1.64%	0.62%
89	Africa	NA	Namibia	2 612 364	1.06%	2.21%	0.60%
90	Africa	GA	Gabon	2 307 252	0.74%	1.36%	0.56%
91	Asia	BD	Bangladesh	167 238 978	0.07%	0.19%	0.52%
92	Asia	PS	Palestine	5 285 493	0.03%	0.11%	0.48%
93	Asia	IR	Iran	85 663 184	0.87%	0.29%	0.46%
94	Africa	RW	Rwanda	13 450 528	0.23%	0.74%	0.41%
95	Asia	UZ	Uzbekistan	34 222 696	0.12%	0.17%	0.41%
96	Asia	LK	Sri Lanka	21 552 807	0.41%	0.34%	0.36%
97	Africa	GW	Guinea-Bissau	2 040 199	0.06%	0.16%	0.32%
98	North America	SV	El Salvador	6 537 075	0.34%	0.16%	0.31%
99	Africa	GM	Gambia	2 522 010	0.07%	0.24%	0.31%
100	Africa	CG	Congo	5 728 890	0.16%	0.27%	0.29%
101	Africa	DZ	Algeria	45 080 724	0.07%	0.15%	0.28%
102	Africa	CM	Cameroon	27 571 417	0.10%	0.08%	0.28%
103	Asia	PK	Pakistan	227 552 363	0.05%	0.11%	0.27%
104	Africa	ZW	Zimbabwe	15 199 020	0.65%	0.75%	0.26%
105	Africa	LS	Lesotho	2 168 641	0.81%	1.09%	0.23%
106	Africa	MZ	Mozambique	32 614 122	0.22%	0.70%	0.22%
107	Africa	SN	Senegal	17 428 651	0.06%	0.22%	0.21%
108	Africa	ER	Eritrea	3 622 671	0.07%	0.15%	0.16%
109	Australia/Oceania	NZ	New Zealand	5 002 100	0.23%	0.15%	0.16%
110	Africa	EG	Egypt	105 331 574	0.10%	0.10%	0.13%
111	Africa	ML	Mali	21 155 793	0.07%	0.19%	0.12%
112	Africa	AO	Angola	34 452 146	0.12%	0.35%	0.12%
113	Africa	GH	Ghana	32 079 958	0.09%	0.27%	0.11%
114	Africa	MW	Malawi	19 897 089	0.11%	0.33%	0.11%
115	Africa	TG	Togo	8 579 900	0.13%	0.42%	0.11%
116	Africa	SD	Sudan	45 438 446	0.03%	0.07%	0.11%
117	Africa	MG	Madagascar	28 795 787	0.04%	0.12%	0.10%
118	Africa	ET	Ethiopia	119 383 260	0.10%	0.26%	0.10%
119	Africa	KE	Kenya	55 610 021	0.13%	0.35%	0.10%
120	Africa	UG	Uganda	47 981 676	0.08%	0.25%	0.09%
121	North America	HT	Haiti	11 618 493	0.06%	0.08%	0.09%
122	Africa	BI	Burundi	12 440 185	0.16%	0.43%	0.08%
123	Asia	ID	Indonesia	278 017 870	0.03%	0.03%	0.08%
124	Africa	CI	Ivory Coast	27 392 067	0.07%	0.25%	0.07%
125	Africa	CF	Central African R.	4 960 180	0.04%	0.12%	0.07%
126	Africa	GN	Guinea	13 685 550	0.04%	0.14%	0.07%
127	Africa	TZ	Tanzania	62 374 052	0.01%	0.04%	0.05%
128	Africa	BF	Burkina Faso	21 792 672	0.03%	0.06%	0.04%
129	Africa	SL	Sierra Leone	8 228 850	0.01%	0.05%	0.04%
130	Africa	BJ	Benin	12 615 970	0.03%	0.04%	0.04%
131	Asia	AF	Afghanistan	40 289 298	0.01%	0.02%	0.04%
132	Africa	CD	DR Congo	93 785 289	0.03%	0.06%	0.04%
133	Asia	TW	Taiwan	23 883 787	0.01%	0.02%	0.03%
134	Africa	TD	Chad	17 157 148	0.01%	0.03%	0.03%
135	Africa	LR	Liberia	5 242 199	0.03%	0.10%	0.03%
136	Africa	SS	South Sudan	11 397 630	0.04%	0.10%	0.03%
137	Asia	MM	Myanmar	54 976 703	0.14%	0.03%	0.02%
138	Asia	KH	Cambodia	17 078 413	0.08%	0.01%	0.02%
139	Asia	SY	Syria	18 160 506	0.11%	0.02%	0.02%
140	Asia	HK	Hong Kong	7 591 505	0.01%	0.02%	0.02%
141	Asia	YE	Yemen	30 845 734	0.01%	0.01%	0.02%
142	North America	NI	Nicaragua	6 747 011	0.04%	0.01%	0.01%
143	Africa	NE	Niger	25 565 285	0.01%	0.02%	0.01%
144	Africa	NG	Nigeria	214 069 227	0.02%	0.04%	0.01%
145	Asia	TJ	Tajikistan	9 870 193	0.00%	0.00%	0.00%
146	Australia/Oceania	PG	Papua New Guinea	9 210 199	0.19%	0.02%	0.00%
147	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
148	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
149	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
150	Africa	SO	Somalia	16 581 219	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	30 845 734	19.27%	(8.96)%	(0.01)%
2	Asia	SY	Syria	18 160 506	3.81%	(8.71)%	(0.02)%
3	Asia	AF	Afghanistan	40 289 298	4.53%	(4.72)%	(0.02)%
4	Europe	RU	Russia	146 031 742	3.48%	3.76%	1.99%
5	North America	NI	Nicaragua	6 747 011	0.48%	(3.13)%	(0.01)%
6	Europe	UA	Ukraine	43 325 246	3.10%	3.09%	1.95%
7	Africa	EG	Egypt	105 331 574	5.06%	2.94%	0.10%
8	Asia	KH	Cambodia	17 078 413	4.51%	(2.66)%	(0.01)%
9	Europe	PL	Poland	37 782 168	2.02%	2.63%	4.94%
10	Europe	BA	Bosnia and Herzegovina	3 249 090	4.08%	2.53%	5.33%
11	Asia	LK	Sri Lanka	21 552 807	2.89%	2.45%	0.34%
12	Europe	BG	Bulgaria	6 867 117	3.66%	2.40%	8.19%
13	Africa	DZ	Algeria	45 080 724	3.00%	2.30%	0.15%
14	Europe	MD	Moldova	4 019 387	3.05%	2.29%	3.10%
15	Europe	HU	Hungary	9 622 214	2.09%	2.23%	6.97%
16	Asia	AM	Armenia	2 971 853	2.95%	2.13%	0.91%
17	Africa	MG	Madagascar	28 795 787	1.88%	2.08%	0.12%
18	Africa	NE	Niger	25 565 285	3.95%	(2.02)%	(0.02)%
19	Asia	AZ	Azerbaijan	10 281 196	1.39%	2.00%	0.71%
20	North America	SV	El Salvador	6 537 075	2.97%	1.82%	0.16%
21	Asia	IR	Iran	85 663 184	1.63%	1.79%	0.29%
22	Africa	SD	Sudan	45 438 446	4.28%	1.76%	0.07%
23	Africa	ER	Eritrea	3 622 671	2.25%	1.73%	0.15%
24	Africa	LY	Libya	7 016 448	1.98%	1.69%	1.12%
25	Europe	SK	Slovakia	5 463 753	1.06%	1.67%	6.65%
26	Asia	GE	Georgia	3 977 262	1.49%	1.56%	12.38%
27	Asia	ID	Indonesia	278 017 870	3.44%	1.50%	0.03%
28	Australia/Oceania	PG	Papua New Guinea	9 210 199	2.12%	1.48%	0.02%
29	Europe	MK	North Macedonia	2 083 241	2.85%	1.44%	5.93%
30	Africa	NA	Namibia	2 612 364	1.43%	1.43%	2.21%
31	Europe	BY	Belarus	9 444 491	0.91%	1.34%	1.48%
32	Asia	MM	Myanmar	54 976 703	2.10%	1.24%	0.03%
33	South America	PY	Paraguay	7 268 659	2.54%	1.24%	3.14%
34	Asia	KG	Kyrgyzstan	6 691 375	2.21%	1.23%	0.61%
35	Europe	RO	Romania	19 038 156	3.13%	1.21%	3.85%
36	Asia	VN	Vietnam	98 699 597	1.38%	1.16%	2.12%
37	Africa	BF	Burkina Faso	21 792 672	2.92%	1.09%	0.06%
38	Africa	ZW	Zimbabwe	15 199 020	0.70%	1.06%	0.75%
39	Asia	KR	South Korea	51 337 777	1.01%	1.05%	1.06%
40	Africa	CM	Cameroon	27 571 417	2.06%	1.05%	0.08%
41	Africa	ZA	South Africa	60 470 442	1.07%	1.05%	1.48%
42	South America	EC	Ecuador	18 059 200	1.75%	1.04%	2.17%
43	North America	HN	Honduras	10 149 286	3.03%	1.01%	0.31%
44	Asia	JO	Jordan	10 360 531	0.84%	0.99%	3.01%
45	Africa	MW	Malawi	19 897 089	1.13%	0.98%	0.33%
46	Asia	IQ	Iraq	41 623 636	1.62%	0.96%	0.51%
47	Africa	GW	Guinea-Bissau	2 040 199	2.34%	0.89%	0.16%
48	North America	HT	Haiti	11 618 493	2.70%	0.88%	0.08%
49	Europe	HR	Croatia	4 065 905	1.15%	0.86%	17.36%
50	Asia	UZ	Uzbekistan	34 222 696	0.88%	0.85%	0.17%
51	South America	VE	Venezuela	28 310 676	1.05%	0.85%	0.30%
52	Africa	TN	Tunisia	12 010 779	1.70%	0.82%	3.50%
53	South America	CL	Chile	19 371 207	0.97%	0.80%	2.88%
54	Asia	PH	Philippines	111 846 922	1.92%	0.80%	1.85%
55	North America	MX	Mexico	131 037 639	2.74%	0.78%	1.83%
56	Africa	CD	DR Congo	93 785 289	0.79%	0.76%	0.06%
57	Europe	LT	Lithuania	2 663 226	1.14%	0.75%	14.15%
58	Asia	LA	Laos	7 439 561	0.47%	0.75%	1.45%
59	South America	PE	Peru	33 685 367	1.54%	0.71%	6.11%
60	South America	BR	Brazil	214 907 717	1.68%	0.69%	2.54%
61	North America	JM	Jamaica	2 981 257	2.45%	0.69%	3.42%
62	South America	BO	Bolivia	11 920 384	0.85%	0.66%	7.57%
63	Asia	MY	Malaysia	33 010 256	0.96%	0.65%	1.17%
64	Africa	UG	Uganda	47 981 676	0.92%	0.65%	0.25%
65	Europe	CZ	Czechia	10 739 865	0.72%	0.65%	11.03%
66	Asia	PK	Pakistan	227 552 363	1.62%	0.63%	0.11%
67	Africa	ML	Mali	21 155 793	1.21%	0.61%	0.19%
68	South America	CO	Colombia	51 725 604	1.11%	0.61%	4.21%
69	North America	GT	Guatemala	18 430 206	2.38%	0.61%	0.84%
70	Africa	CF	Central African R.	4 960 180	0.45%	0.59%	0.12%
71	Europe	DE	Germany	84 200 383	0.62%	0.56%	7.96%
72	Europe	RS	Serbia	8 682 653	0.93%	0.54%	10.69%
73	Africa	AO	Angola	34 452 146	1.02%	0.53%	0.35%
74	Africa	GN	Guinea	13 685 550	0.68%	0.50%	0.14%
75	Asia	KZ	Kazakhstan	19 125 661	1.46%	0.48%	2.81%
76	Asia	IN	India	1 401 087 479	1.23%	0.47%	1.18%
77	Africa	TD	Chad	17 157 148	0.72%	0.47%	0.03%
78	Africa	TZ	Tanzania	62 374 052	0.13%	0.47%	0.04%
79	Africa	GM	Gambia	2 522 010	1.04%	0.46%	0.24%
80	Europe	AL	Albania	2 872 912	1.00%	0.46%	5.23%
81	Asia	BD	Bangladesh	167 238 978	1.15%	0.45%	0.19%
82	Africa	MR	Mauritania	4 839 318	0.82%	0.44%	1.38%
83	Africa	GH	Ghana	32 079 958	0.79%	0.44%	0.27%
84	Africa	NG	Nigeria	214 069 227	0.92%	0.44%	0.04%
85	Africa	ET	Ethiopia	119 383 260	1.54%	0.43%	0.26%
86	Africa	SL	Sierra Leone	8 228 850	0.40%	0.42%	0.05%
87	Asia	LB	Lebanon	6 777 923	0.61%	0.41%	8.30%
88	Africa	SN	Senegal	17 428 651	0.82%	0.40%	0.22%
89	Asia	TH	Thailand	70 072 243	0.69%	0.39%	0.96%
90	Europe	GR	Greece	10 343 896	0.78%	0.38%	27.57%
91	Asia	TR	Turkey	85 749 213	0.65%	0.38%	7.37%
92	North America	US	USA	334 019 477	0.76%	0.36%	21.41%
93	Africa	RW	Rwanda	13 450 528	0.65%	0.35%	0.74%
94	Africa	CI	Ivory Coast	27 392 067	0.90%	0.35%	0.25%
95	Africa	LS	Lesotho	2 168 641	1.67%	0.31%	1.09%
96	Africa	MZ	Mozambique	32 614 122	0.36%	0.30%	0.70%
97	Africa	BW	Botswana	2 425 350	0.26%	0.30%	6.47%
98	Africa	MA	Morocco	37 590 301	0.80%	0.29%	1.31%
99	Africa	KE	Kenya	55 610 021	0.68%	0.29%	0.35%
100	Asia	NP	Nepal	29 950 642	0.86%	0.29%	1.04%
101	North America	PA	Panama	4 420 267	0.49%	0.27%	11.80%
102	North America	CR	Costa Rica	5 166 405	1.24%	0.27%	5.31%
103	Europe	SI	Slovenia	2 079 382	0.57%	0.26%	24.54%
104	North America	CA	Canada	38 256 407	0.41%	0.25%	10.01%
105	Africa	ZM	Zambia	19 182 807	0.28%	0.24%	1.64%
106	Europe	IT	Italy	60 323 606	0.33%	0.22%	27.35%
107	Africa	TG	Togo	8 579 900	0.44%	0.22%	0.42%
108	Asia	OM	Oman	5 308 184	0.45%	0.21%	1.01%
109	Asia	MN	Mongolia	3 360 288	0.68%	0.20%	3.13%
110	Europe	AT	Austria	9 086 270	0.40%	0.20%	12.40%
111	Africa	GA	Gabon	2 307 252	0.68%	0.19%	1.36%
112	Asia	SG	Singapore	5 921 848	0.36%	0.18%	1.62%
113	Africa	BJ	Benin	12 615 970	0.20%	0.18%	0.04%
114	Australia/Oceania	NZ	New Zealand	5 002 100	0.23%	0.17%	0.15%
115	Africa	SO	Somalia	16 581 219	4.50%	0.17%	0.03%
116	South America	PR	Puerto Rico	3 193 694	0.23%	0.16%	28.61%
117	Europe	GB	United Kingdom	68 440 290	0.23%	0.15%	23.74%
118	Europe	BE	Belgium	11 668 024	0.25%	0.14%	22.72%
119	South America	UY	Uruguay	3 492 443	0.23%	0.14%	17.27%
120	South America	AR	Argentina	45 840 255	0.26%	0.13%	18.85%
121	North America	CU	Cuba	11 315 868	0.60%	0.13%	1.80%
122	Europe	FR	France	65 498 037	0.18%	0.12%	43.07%
123	Africa	CG	Congo	5 728 890	2.06%	0.12%	0.27%
124	Europe	FI	Finland	5 554 100	0.29%	0.12%	14.40%
125	Africa	SS	South Sudan	11 397 630	0.34%	0.11%	0.10%
126	Europe	SE	Sweden	10 197 141	0.19%	0.11%	18.76%
127	Europe	PT	Portugal	10 150 485	0.21%	0.11%	34.50%
128	Europe	NL	Netherlands	17 193 809	0.20%	0.11%	17.77%
129	Asia	TW	Taiwan	23 883 787	0.61%	0.10%	0.02%
130	Asia	AE	Arab Emirates	10 076 064	0.18%	0.10%	2.95%
131	Asia	JP	Japan	125 874 500	0.66%	0.09%	1.07%
132	Europe	NO	Norway	5 487 121	0.17%	0.09%	16.66%
133	Europe	ES	Spain	46 782 931	0.15%	0.09%	27.90%
134	Asia	SA	Saudi Arabia	35 656 016	0.40%	0.09%	1.03%
135	Europe	DK	Denmark	5 823 908	0.12%	0.08%	43.62%
136	Africa	LR	Liberia	5 242 199	0.36%	0.08%	0.10%
137	Australia/Oceania	AU	Australia	25 959 584	0.15%	0.08%	20.64%
138	Europe	CH	Switzerland	8 752 988	0.17%	0.08%	28.56%
139	North America	DO	Dominican R.	11 016 949	0.18%	0.07%	4.31%
140	Europe	IE	Ireland	5 023 488	0.12%	0.04%	36.75%
141	Asia	QA	Qatar	2 807 805	0.05%	0.04%	9.98%
142	Asia	KW	Kuwait	4 368 678	0.08%	0.04%	6.41%
143	Asia	IL	Israel	9 326 000	0.13%	0.03%	37.37%
144	Africa	BI	Burundi	12 440 185	0.00%	0.00%	0.43%
145	Asia	HK	Hong Kong	7 591 505	0.00%	0.00%	0.02%
146	Asia	PS	Palestine	5 285 493	0.00%	0.00%	0.11%
147	Asia	TJ	Tajikistan	9 870 193	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	33 685 367	203 876	6.052‰
2	Europe	BG	Bulgaria	6 867 117	32 604	4.748‰
3	Europe	BA	Bosnia and Herzegovina	3 249 090	13 984	4.304‰
4	Europe	HU	Hungary	9 622 214	40 822	4.242‰
5	Europe	MK	North Macedonia	2 083 241	8 177	3.925‰
6	Asia	GE	Georgia	3 977 262	14 673	3.689‰
7	Europe	CZ	Czechia	10 739 865	37 006	3.446‰
8	Europe	HR	Croatia	4 065 905	13 335	3.280‰
9	Europe	SK	Slovakia	5 463 753	17 612	3.223‰
10	Europe	RO	Romania	19 038 156	59 472	3.124‰
11	Europe	SI	Slovenia	2 079 382	6 228	2.995‰
12	Europe	LT	Lithuania	2 663 226	7 739	2.906‰
13	South America	BR	Brazil	214 907 717	622 251	2.895‰
14	Europe	PL	Poland	37 782 168	103 819	2.748‰
15	Asia	AM	Armenia	2 971 853	8 026	2.701‰
16	Europe	MD	Moldova	4 019 387	10 501	2.613‰
17	South America	AR	Argentina	45 840 255	118 788	2.591‰
18	North America	US	USA	334 019 477	855 111	2.560‰
19	South America	CO	Colombia	51 725 604	131 634	2.545‰
20	Europe	BE	Belgium	11 668 024	28 780	2.467‰
21	Europe	IT	Italy	60 323 606	142 963	2.370‰
22	South America	PY	Paraguay	7 268 659	16 910	2.326‰
23	North America	MX	Mexico	131 037 639	302 443	2.308‰
24	Europe	UA	Ukraine	43 325 246	99 129	2.288‰
25	Europe	GB	United Kingdom	68 440 290	153 490	2.243‰
26	Europe	RU	Russia	146 031 742	325 433	2.228‰
27	Europe	GR	Greece	10 343 896	22 476	2.173‰
28	Africa	TN	Tunisia	12 010 779	25 912	2.157‰
29	South America	CL	Chile	19 371 207	39 474	2.038‰
30	Europe	ES	Spain	46 782 931	91 741	1.961‰
31	Europe	PT	Portugal	10 150 485	19 496	1.921‰
32	Europe	FR	France	65 498 037	125 646	1.918‰
33	South America	EC	Ecuador	18 059 200	34 240	1.896‰
34	South America	UY	Uruguay	3 492 443	6 270	1.795‰
35	South America	BO	Bolivia	11 920 384	20 505	1.720‰
36	North America	PA	Panama	4 420 267	7 563	1.711‰
37	Africa	ZA	South Africa	60 470 442	93 949	1.554‰
38	Asia	IR	Iran	85 663 184	132 182	1.543‰
39	Europe	SE	Sweden	10 197 141	15 631	1.533‰
40	Europe	RS	Serbia	8 682 653	13 211	1.522‰
41	Africa	NA	Namibia	2 612 364	3 882	1.486‰
42	Europe	AT	Austria	9 086 270	13 501	1.486‰
43	North America	CR	Costa Rica	5 166 405	7 444	1.441‰
44	Asia	LB	Lebanon	6 777 923	9 444	1.393‰
45	Europe	CH	Switzerland	8 752 988	12 145	1.387‰
46	Europe	DE	Germany	84 200 383	116 660	1.385‰
47	Asia	JO	Jordan	10 360 531	13 034	1.258‰
48	Europe	NL	Netherlands	17 193 809	21 200	1.233‰
49	Europe	IE	Ireland	5 023 488	6 087	1.212‰
50	Europe	AL	Albania	2 872 912	3 292	1.146‰
51	South America	PR	Puerto Rico	3 193 694	3 593	1.125‰
52	Africa	BW	Botswana	2 425 350	2 544	1.049‰
53	North America	HN	Honduras	10 149 286	10 471	1.032‰
54	Asia	TR	Turkey	85 749 213	85 600	0.998‰
55	Asia	MY	Malaysia	33 010 256	31 869	0.965‰
56	Asia	KZ	Kazakhstan	19 125 661	18 357	0.960‰
57	Asia	IL	Israel	9 326 000	8 372	0.898‰
58	North America	GT	Guatemala	18 430 206	16 225	0.880‰
59	North America	JM	Jamaica	2 981 257	2 568	0.861‰
60	Africa	LY	Libya	7 016 448	5 907	0.842‰
61	North America	CA	Canada	38 256 407	32 157	0.841‰
62	Asia	AZ	Azerbaijan	10 281 196	8 581	0.835‰
63	Asia	OM	Oman	5 308 184	4 125	0.777‰
64	North America	CU	Cuba	11 315 868	8 353	0.738‰
65	Asia	LK	Sri Lanka	21 552 807	15 272	0.709‰
66	Europe	BY	Belarus	9 444 491	5 899	0.625‰
67	Europe	DK	Denmark	5 823 908	3 571	0.613‰
68	Asia	MN	Mongolia	3 360 288	2 016	0.600‰
69	North America	SV	El Salvador	6 537 075	3 844	0.588‰
70	Asia	IQ	Iraq	41 623 636	24 277	0.583‰
71	Asia	KW	Kuwait	4 368 678	2 481	0.568‰
72	Asia	ID	Indonesia	278 017 870	144 206	0.519‰
73	Asia	PH	Philippines	111 846 922	53 250	0.476‰
74	Asia	KG	Kyrgyzstan	6 691 375	2 846	0.425‰
75	Africa	MA	Morocco	37 590 301	15 060	0.401‰
76	Asia	NP	Nepal	29 950 642	11 651	0.389‰
77	North America	DO	Dominican R.	11 016 949	4 279	0.388‰
78	Asia	VN	Vietnam	98 699 597	36 419	0.369‰
79	Asia	MM	Myanmar	54 976 703	19 308	0.351‰
80	Asia	IN	India	1 401 087 479	488 885	0.349‰
81	Africa	ZW	Zimbabwe	15 199 020	5 288	0.348‰
82	Europe	FI	Finland	5 554 100	1 815	0.327‰
83	Africa	LS	Lesotho	2 168 641	690	0.318‰
84	Asia	TH	Thailand	70 072 243	22 019	0.314‰
85	Europe	NO	Norway	5 487 121	1 415	0.258‰
86	Asia	SA	Saudi Arabia	35 656 016	8 916	0.250‰
87	Asia	QA	Qatar	2 807 805	633	0.225‰
88	Asia	AE	Arab Emirates	10 076 064	2 208	0.219‰
89	Africa	EG	Egypt	105 331 574	22 267	0.211‰
90	Africa	ZM	Zambia	19 182 807	3 884	0.203‰
91	South America	VE	Venezuela	28 310 676	5 396	0.191‰
92	Africa	MR	Mauritania	4 839 318	920	0.190‰
93	Asia	AF	Afghanistan	40 289 298	7 387	0.183‰
94	Asia	KH	Cambodia	17 078 413	3 015	0.176‰
95	Asia	BD	Bangladesh	167 238 978	28 197	0.169‰
96	Asia	SY	Syria	18 160 506	2 959	0.163‰
97	Asia	JP	Japan	125 874 500	18 478	0.147‰
98	Africa	DZ	Algeria	45 080 724	6 468	0.143‰
99	Asia	SG	Singapore	5 921 848	846	0.143‰
100	Africa	GM	Gambia	2 522 010	347	0.138‰
101	Africa	GA	Gabon	2 307 252	300	0.130‰
102	Asia	PK	Pakistan	227 552 363	29 054	0.128‰
103	Asia	KR	South Korea	51 337 777	6 529	0.127‰
104	Africa	MW	Malawi	19 897 089	2 507	0.126‰
105	Australia/Oceania	AU	Australia	25 959 584	2 960	0.114‰
106	Africa	SN	Senegal	17 428 651	1 921	0.110‰
107	Africa	RW	Rwanda	13 450 528	1 428	0.106‰
108	Africa	KE	Kenya	55 610 021	5 528	0.099‰
109	Africa	SO	Somalia	16 581 219	1 335	0.081‰
110	Africa	GW	Guinea-Bissau	2 040 199	153	0.075‰
111	Africa	SD	Sudan	45 438 446	3 393	0.075‰
112	Africa	UG	Uganda	47 981 676	3 463	0.072‰
113	Asia	LA	Laos	7 439 561	514	0.069‰
114	Africa	CM	Cameroon	27 571 417	1 867	0.068‰
115	North America	HT	Haiti	11 618 493	780	0.067‰
116	Africa	MZ	Mozambique	32 614 122	2 149	0.066‰
117	Africa	CG	Congo	5 728 890	371	0.065‰
118	Australia/Oceania	PG	Papua New Guinea	9 210 199	596	0.065‰
119	Asia	YE	Yemen	30 845 734	1 995	0.065‰
120	Africa	ET	Ethiopia	119 383 260	7 226	0.060‰
121	Africa	LR	Liberia	5 242 199	288	0.055‰
122	Africa	AO	Angola	34 452 146	1 884	0.055‰
123	Asia	UZ	Uzbekistan	34 222 696	1 536	0.045‰
124	Africa	GH	Ghana	32 079 958	1 357	0.042‰
125	Africa	MG	Madagascar	28 795 787	1 169	0.041‰
126	Asia	TW	Taiwan	23 883 787	851	0.036‰
127	Africa	ML	Mali	21 155 793	704	0.033‰
128	North America	NI	Nicaragua	6 747 011	219	0.033‰
129	Africa	TG	Togo	8 579 900	266	0.031‰
130	Africa	GN	Guinea	13 685 550	410	0.030‰
131	Asia	HK	Hong Kong	7 591 505	213	0.028‰
132	Africa	CI	Ivory Coast	27 392 067	764	0.028‰
133	Africa	ER	Eritrea	3 622 671	90	0.025‰
134	Africa	CF	Central African R.	4 960 180	109	0.022‰
135	Africa	BF	Burkina Faso	21 792 672	353	0.016‰
136	Africa	SL	Sierra Leone	8 228 850	125	0.015‰
137	Africa	NG	Nigeria	214 069 227	3 124	0.015‰
138	Africa	CD	DR Congo	93 785 289	1 278	0.014‰
139	Africa	BJ	Benin	12 615 970	163	0.013‰
140	Africa	TZ	Tanzania	62 374 052	753	0.012‰
141	Africa	SS	South Sudan	11 397 630	137	0.012‰
142	Africa	NE	Niger	25 565 285	295	0.011‰
143	Africa	TD	Chad	17 157 148	185	0.011‰
144	Australia/Oceania	NZ	New Zealand	5 002 100	52	0.010‰
145	Africa	BI	Burundi	12 440 185	14	0.001‰
146	Asia	PS	Palestine	5 285 493	5	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	9 870 193	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"