Menu Tarot Kapcsolat

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": 2021-04-16 11:20
(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	+2 416 (+2 678)	+30 (+34)
CZ	Czechia	+3 238 (+3 710)	+38 (+80)
DE	Germany	+0 (+30 634)	+0 (+328)
HU	Hungary	+5 216 (+5 307)	+241 (+256)
PL	Poland	+17 847 (+21 129)	+595 (+683)
SK	Slovakia, [gov], [okr]	+636 (+843)	+93 (+79)

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

N.	Region	Population	Last 120 days	Last 30 days	Last 7 days
1	South America	436 805 957	2.49%	3.27%	3.70%
2	Europe	755 994 592	2.89%	3.06%	2.80%
3	North America	592 314 330	2.86%	1.58%	1.78%
4	Asia	4 661 134 894	0.28%	0.51%	0.75%
5	Africa	1 365 078 505	0.15%	0.10%	0.10%
6	Australia/Oceania	43 192 513	0.03%	0.07%	0.06%

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	436 805 957	2.56%	4.11%	3.27%
2	Africa	1 365 078 505	2.95%	3.28%	0.10%
3	North America	592 314 330	2.08%	2.74%	1.58%
4	Europe	755 994 592	2.21%	2.22%	3.06%
5	Asia	4 661 134 894	1.20%	1.14%	0.51%
6	Australia/Oceania	43 192 513	1.05%	(1.02)%	(0.07)%

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	436 805 957	609 552	1.395‰
2	North America	592 314 330	822 699	1.389‰
3	Europe	755 994 592	968 673	1.281‰
4	Asia	4 661 134 894	450 243	0.097‰
5	Africa	1 365 078 505	117 345	0.086‰
6	Australia/Oceania	43 192 513	1 302	0.030‰

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	South America	UY	Uruguay	3 483 224	4.12%	9.30%	13.22%
2	Asia	TR	Turkey	85 052 838	2.54%	5.53%	8.00%
3	Europe	HU	Hungary	9 640 967	4.67%	8.70%	6.47%
4	Europe	FR	France	65 387 466	4.19%	6.55%	6.45%
5	Europe	HR	Croatia	4 085 238	2.97%	4.80%	6.35%
6	Europe	SE	Sweden	10 148 878	5.29%	6.31%	6.04%
7	Europe	PL	Poland	37 813 871	3.94%	7.44%	5.99%
8	South America	AR	Argentina	45 522 155	2.40%	3.53%	5.80%
9	Europe	SI	Slovenia	2 079 164	6.23%	5.48%	5.37%
10	Europe	NL	Netherlands	17 164 784	4.31%	4.92%	5.11%
11	Europe	MK	North Macedonia	2 083 306	3.33%	5.97%	5.03%
12	Europe	LT	Lithuania	2 692 167	4.67%	3.66%	4.61%
13	South America	CL	Chile	19 245 367	2.73%	4.18%	4.49%
14	Europe	RS	Serbia	8 709 547	4.27%	5.91%	4.30%
15	Asia	QA	Qatar	2 807 805	1.87%	3.24%	4.15%
16	Asia	KW	Kuwait	4 320 165	2.46%	3.79%	4.05%
17	Asia	JO	Jordan	10 282 825	4.00%	7.15%	3.95%
18	South America	BR	Brazil	213 749 436	3.14%	4.04%	3.91%
19	Asia	LB	Lebanon	6 801 277	5.20%	4.79%	3.87%
20	Europe	UA	Ukraine	43 525 906	2.27%	3.97%	3.84%
21	South America	PR	Puerto Rico	3 193 694	1.69%	1.80%	3.83%
22	Europe	CZ	Czechia	10 724 658	9.27%	6.34%	3.82%
23	Europe	BG	Bulgaria	6 907 046	2.85%	5.51%	3.82%
24	South America	PY	Paraguay	7 201 405	2.04%	3.39%	3.66%
25	Europe	BA	Bosnia and Herzegovina	3 264 674	2.59%	5.06%	3.62%
26	South America	CO	Colombia	51 309 459	2.22%	2.19%	3.56%
27	Asia	AM	Armenia	2 967 613	1.90%	3.63%	3.43%
28	South America	PE	Peru	33 332 642	2.06%	3.05%	3.35%
29	Asia	IR	Iran	84 837 813	1.22%	1.91%	3.27%
30	Europe	GR	Greece	10 382 792	1.74%	3.24%	3.27%
31	Europe	AT	Austria	9 046 892	2.82%	3.89%	3.26%
32	Asia	MN	Mongolia	3 319 723	0.54%	1.77%	3.18%
33	Europe	IT	Italy	60 391 595	3.21%	3.76%	3.08%
34	Europe	DE	Germany	83 995 236	2.02%	2.43%	3.02%
35	Asia	OM	Oman	5 208 154	0.96%	2.20%	2.85%
36	Europe	BE	Belgium	11 629 388	2.75%	4.07%	2.83%
37	North America	CA	Canada	38 002 618	1.61%	1.84%	2.71%
38	Asia	GE	Georgia	3 983 117	2.31%	1.73%	2.64%
39	Asia	AZ	Azerbaijan	10 211 103	1.09%	2.06%	2.52%
40	North America	US	USA	332 532 050	4.41%	2.28%	2.52%
41	Europe	RO	Romania	19 136 146	2.34%	3.17%	2.39%
42	Europe	CH	Switzerland	8 704 466	2.61%	2.41%	2.33%
43	Asia	AE	Arab Emirates	9 984 338	3.03%	2.45%	2.28%
44	Asia	IQ	Iraq	40 928 986	0.92%	1.84%	2.24%
45	North America	CR	Costa Rica	5 130 727	1.41%	1.28%	2.21%
46	Europe	MD	Moldova	4 026 555	2.83%	3.69%	2.14%
47	Europe	ES	Spain	46 769 075	3.40%	1.61%	1.87%
48	Africa	TN	Tunisia	11 915 894	1.38%	1.23%	1.81%
49	Africa	BW	Botswana	2 388 828	1.31%	1.67%	1.70%
50	Europe	SK	Slovakia	5 461 730	4.31%	2.36%	1.63%
51	Europe	NO	Norway	5 454 619	1.18%	1.81%	1.53%
52	Europe	BY	Belarus	9 446 869	1.84%	1.52%	1.49%
53	Europe	DK	Denmark	5 808 288	1.94%	1.43%	1.38%
54	Asia	KZ	Kazakhstan	18 953 268	0.75%	1.13%	1.38%
55	South America	EC	Ecuador	17 853 392	0.85%	1.18%	1.33%
56	Asia	IN	India	1 390 679 153	0.30%	0.76%	1.25%
57	Asia	PH	Philippines	110 727 033	0.41%	0.98%	1.17%
58	Africa	LY	Libya	6 944 698	1.12%	1.35%	1.09%
59	North America	CU	Cuba	11 321 156	0.71%	0.97%	1.04%
60	South America	BO	Bolivia	11 798 112	1.16%	0.85%	1.02%
61	Europe	AL	Albania	2 875 315	2.73%	1.48%	0.97%
62	North America	JM	Jamaica	2 971 357	1.05%	1.53%	0.94%
63	Europe	IE	Ireland	4 981 160	3.32%	1.18%	0.92%
64	North America	PA	Panama	4 368 082	3.72%	1.03%	0.85%
65	Europe	FI	Finland	5 547 512	0.93%	1.12%	0.77%
66	North America	HN	Honduras	10 028 249	0.82%	0.74%	0.76%
67	Africa	NA	Namibia	2 576 989	1.12%	0.73%	0.75%
68	Europe	RU	Russia	145 983 862	1.32%	0.73%	0.71%
69	Asia	MY	Malaysia	32 691 886	0.86%	0.52%	0.66%
70	North America	GT	Guatemala	18 175 404	0.42%	0.50%	0.65%
71	Europe	PT	Portugal	10 173 212	4.63%	0.57%	0.63%
72	Asia	PS	Palestine	5 194 206	0.03%	0.13%	0.57%
73	North America	DO	Dominican R.	10 933 492	0.94%	0.47%	0.57%
74	Africa	GA	Gabon	2 266 822	0.51%	0.71%	0.53%
75	South America	VE	Venezuela	28 372 266	0.25%	0.45%	0.49%
76	Asia	BD	Bangladesh	165 980 237	0.13%	0.35%	0.43%
77	Europe	GB	United Kingdom	68 167 060	3.53%	0.66%	0.41%
78	Asia	KG	Kyrgyzstan	6 608 658	0.20%	0.26%	0.41%
79	North America	MX	Mexico	129 998 266	0.79%	0.38%	0.38%
80	North America	SV	El Salvador	6 512 000	0.38%	0.26%	0.35%
81	Asia	JP	Japan	126 170 451	0.26%	0.21%	0.32%
82	Asia	SA	Saudi Arabia	35 239 473	0.12%	0.22%	0.31%
83	Africa	CM	Cameroon	27 062 544	0.13%	0.34%	0.28%
84	Asia	IL	Israel	9 197 590	5.13%	0.62%	0.26%
85	Asia	PK	Pakistan	224 253 902	0.13%	0.23%	0.26%
86	Australia/Oceania	PG	Papua New Guinea	9 079 879	0.09%	0.30%	0.26%
87	Africa	ZA	South Africa	59 896 382	1.13%	0.21%	0.23%
88	Asia	ID	Indonesia	275 798 600	0.35%	0.23%	0.23%
89	Africa	MG	Madagascar	28 247 452	0.04%	0.13%	0.23%
90	Asia	TH	Thailand	69 938 149	0.05%	0.07%	0.20%
91	Africa	KE	Kenya	54 698 558	0.10%	0.25%	0.19%
92	Africa	ET	Ethiopia	117 190 341	0.10%	0.20%	0.19%
93	Africa	MA	Morocco	37 254 502	0.26%	0.16%	0.18%
94	Asia	NP	Nepal	29 547 776	0.11%	0.09%	0.17%
95	Asia	KH	Cambodia	16 900 725	0.03%	0.09%	0.16%
96	Asia	KR	South Korea	51 304 013	0.13%	0.12%	0.15%
97	Africa	TG	Togo	8 430 534	0.11%	0.20%	0.15%
98	Asia	LK	Sri Lanka	21 484 036	0.29%	0.14%	0.13%
99	Africa	ML	Mali	20 706 145	0.03%	0.07%	0.12%
100	Africa	EG	Egypt	103 847 468	0.09%	0.08%	0.09%
101	Africa	SO	Somalia	16 239 481	0.05%	0.09%	0.09%
102	Africa	GM	Gambia	2 469 682	0.08%	0.11%	0.09%
103	Africa	ZM	Zambia	18 785 992	0.38%	0.11%	0.09%
104	Africa	GN	Guinea	13 411 064	0.06%	0.10%	0.08%
105	Asia	SY	Syria	17 833 162	0.06%	0.09%	0.08%
106	Africa	RW	Rwanda	13 203 279	0.13%	0.11%	0.08%
107	Asia	UZ	Uzbekistan	33 850 137	0.03%	0.06%	0.08%
108	Africa	BI	Burundi	12 167 109	0.02%	0.03%	0.06%
109	Asia	SG	Singapore	5 886 569	0.04%	0.04%	0.05%
110	Africa	ER	Eritrea	3 584 978	0.08%	0.05%	0.04%
111	Africa	AO	Angola	33 663 530	0.02%	0.03%	0.04%
112	Africa	ZW	Zimbabwe	15 032 836	0.17%	0.02%	0.04%
113	Africa	DZ	Algeria	44 471 990	0.06%	0.03%	0.04%
114	Africa	SN	Senegal	17 088 723	0.13%	0.06%	0.04%
115	Africa	GW	Guinea-Bissau	2 004 390	0.06%	0.05%	0.04%
116	Asia	YE	Yemen	30 340 231	0.01%	0.04%	0.03%
117	Africa	MZ	Mozambique	31 939 216	0.16%	0.05%	0.03%
118	Asia	AF	Afghanistan	39 614 554	0.02%	0.02%	0.03%
119	Africa	MR	Mauritania	4 745 164	0.15%	0.05%	0.03%
120	Africa	GH	Ghana	31 580 972	0.12%	0.04%	0.02%
121	Africa	CF	Central African R.	4 895 636	0.01%	0.04%	0.02%
122	Africa	CI	Ivory Coast	26 889 052	0.09%	0.11%	0.02%
123	Africa	SS	South Sudan	11 296 903	0.06%	0.03%	0.01%
124	Africa	MW	Malawi	19 516 315	0.14%	0.02%	0.01%
125	Africa	BJ	Benin	12 371 351	0.04%	0.04%	0.01%
126	Africa	BF	Burkina Faso	21 350 969	0.04%	0.01%	0.01%
127	Australia/Oceania	NZ	New Zealand	5 002 100	0.01%	0.01%	0.01%
128	North America	NI	Nicaragua	6 686 515	0.01%	0.01%	0.01%
129	Africa	SD	Sudan	44 650 323	0.02%	0.02%	0.01%
130	North America	HT	Haiti	11 511 792	0.03%	0.01%	0.01%
131	Africa	UG	Uganda	46 867 258	0.03%	0.01%	0.01%
132	Australia/Oceania	AU	Australia	25 732 506	0.01%	0.01%	0.01%
133	Africa	TD	Chad	16 793 808	0.02%	0.01%	0.01%
134	Africa	SL	Sierra Leone	8 104 071	0.02%	0.00%	0.01%
135	Africa	CD	DR Congo	91 685 378	0.02%	0.01%	0.01%
136	Africa	NG	Nigeria	210 134 738	0.04%	0.01%	0.00%
137	Africa	NE	Niger	24 888 432	0.01%	0.00%	0.00%
138	Africa	LS	Lesotho	2 155 620	0.39%	0.03%	0.00%
139	Asia	VN	Vietnam	98 027 872	0.00%	0.00%	0.00%
140	Africa	LR	Liberia	5 150 686	0.01%	0.00%	0.00%
141	Asia	HK	Hong Kong	7 544 866	0.00%	0.00%	0.00%
142	Asia	TW	Taiwan	23 850 790	0.00%	0.00%	0.00%
143	Asia	MM	Myanmar	54 697 119	0.06%	0.00%	0.00%
144	Asia	LA	Laos	7 358 471	0.00%	0.00%	0.00%
145	Africa	TZ	Tanzania	61 062 542	0.00%	0.00%	0.00%
146	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
147	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
148	Asia	TJ	Tajikistan	9 705 323	0.00%	0.00%	0.00%
149	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
150	Africa	CG	Congo	5 624 301	0.07%	0.05%	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	30 340 231	16.08%	(15.31)%	(0.04)%
2	Africa	SD	Sudan	44 650 323	6.46%	(12.00)%	(0.02)%
3	North America	MX	Mexico	129 998 266	8.95%	11.99%	0.38%
4	Asia	SY	Syria	17 833 162	7.67%	(8.07)%	(0.09)%
5	Africa	SO	Somalia	16 239 481	7.23%	(7.82)%	(0.09)%
6	Asia	AF	Afghanistan	39 614 554	6.13%	(6.84)%	(0.02)%
7	Africa	ZA	South Africa	59 896 382	4.09%	6.23%	0.21%
8	Africa	EG	Egypt	103 847 468	6.36%	(6.02)%	(0.08)%
9	Africa	ZW	Zimbabwe	15 032 836	4.76%	(5.88)%	(0.02)%
10	Europe	SK	Slovakia	5 461 730	3.90%	5.61%	2.36%
11	Europe	BA	Bosnia and Herzegovina	3 264 674	5.02%	4.88%	5.06%
12	Europe	RU	Russia	145 983 862	2.71%	4.20%	0.73%
13	Africa	GW	Guinea-Bissau	2 004 390	1.80%	(4.06)%	(0.05)%
14	Africa	TN	Tunisia	11 915 894	3.47%	3.98%	1.23%
15	South America	BR	Brazil	213 749 436	2.75%	3.87%	4.04%
16	Africa	MW	Malawi	19 516 315	3.42%	(3.80)%	(0.02)%
17	Africa	NE	Niger	24 888 432	3.54%	(3.59)%	(0.00)%
18	Europe	BG	Bulgaria	6 907 046	4.48%	3.38%	5.51%
19	Europe	HU	Hungary	9 640 967	3.91%	3.26%	8.70%
20	Africa	LS	Lesotho	2 155 620	3.17%	(3.26)%	(0.03)%
21	Europe	MK	North Macedonia	2 083 306	3.14%	3.25%	5.97%
22	Africa	TD	Chad	16 793 808	2.29%	(3.23)%	(0.01)%
23	Africa	MG	Madagascar	28 247 452	2.98%	3.18%	0.13%
24	Africa	SN	Senegal	17 088 723	3.25%	(3.17)%	(0.06)%
25	Africa	CF	Central African R.	4 895 636	2.32%	(2.89)%	(0.04)%
26	North America	HN	Honduras	10 028 249	2.35%	2.86%	0.74%
27	South America	PE	Peru	33 332 642	3.01%	2.85%	3.05%
28	Africa	BW	Botswana	2 388 828	2.13%	2.81%	1.67%
29	South America	CO	Colombia	51 309 459	2.51%	2.80%	2.19%
30	North America	SV	El Salvador	6 512 000	3.43%	2.78%	0.26%
31	Africa	DZ	Algeria	44 471 990	1.83%	(2.77)%	(0.03)%
32	Asia	ID	Indonesia	275 798 600	2.48%	2.70%	0.23%
33	South America	PY	Paraguay	7 201 405	2.22%	2.67%	3.39%
34	South America	EC	Ecuador	17 853 392	2.51%	2.64%	1.18%
35	North America	NI	Nicaragua	6 686 515	2.59%	(2.63)%	(0.01)%
36	South America	BO	Bolivia	11 798 112	2.69%	2.61%	0.85%
37	Europe	RO	Romania	19 136 146	2.59%	2.60%	3.17%
38	Europe	GR	Greece	10 382 792	3.19%	2.59%	3.24%
39	Africa	NA	Namibia	2 576 989	1.46%	2.59%	0.73%
40	Europe	MD	Moldova	4 026 555	2.41%	2.56%	3.69%
41	Europe	UA	Ukraine	43 525 906	2.39%	2.48%	3.97%
42	Africa	ML	Mali	20 706 145	3.65%	(2.40)%	(0.07)%
43	North America	GT	Guatemala	18 175 404	3.54%	2.40%	0.50%
44	Asia	AM	Armenia	2 967 613	2.22%	2.16%	3.63%
45	Africa	GM	Gambia	2 469 682	2.63%	2.11%	0.11%
46	Europe	IT	Italy	60 391 595	2.54%	2.10%	3.76%
47	Asia	PK	Pakistan	224 253 902	2.45%	2.02%	0.23%
48	Europe	CZ	Czechia	10 724 658	1.81%	1.97%	6.34%
49	Europe	AL	Albania	2 875 315	1.57%	1.94%	1.48%
50	Europe	HR	Croatia	4 085 238	2.80%	1.93%	4.80%
51	Europe	PL	Poland	37 813 871	2.56%	1.88%	7.44%
52	Asia	KG	Kyrgyzstan	6 608 658	1.66%	1.86%	0.26%
53	Asia	GE	Georgia	3 983 117	1.81%	1.85%	1.73%
54	Africa	LY	Libya	6 944 698	2.00%	1.83%	1.35%
55	Africa	CM	Cameroon	27 062 544	1.46%	1.80%	0.34%
56	Asia	AZ	Azerbaijan	10 211 103	1.63%	1.78%	2.06%
57	Africa	AO	Angola	33 663 530	2.44%	1.76%	0.03%
58	Europe	IE	Ireland	4 981 160	1.63%	1.70%	1.18%
59	Asia	JP	Japan	126 170 451	2.08%	1.68%	0.21%
60	South America	AR	Argentina	45 522 155	1.77%	1.64%	3.53%
61	South America	CL	Chile	19 245 367	1.81%	1.59%	4.18%
62	North America	US	USA	332 532 050	1.65%	1.58%	2.28%
63	Europe	PT	Portugal	10 173 212	2.25%	1.58%	0.57%
64	South America	UY	Uruguay	3 483 224	1.32%	1.54%	9.30%
65	Asia	LB	Lebanon	6 801 277	1.60%	1.52%	4.79%
66	Africa	KE	Kenya	54 698 558	1.54%	1.49%	0.25%
67	Europe	LT	Lithuania	2 692 167	1.84%	1.48%	3.66%
68	Africa	GH	Ghana	31 580 972	1.14%	1.46%	0.04%
69	Asia	KH	Cambodia	16 900 725	1.14%	1.45%	0.09%
70	North America	PA	Panama	4 368 082	1.57%	1.45%	1.03%
71	North America	JM	Jamaica	2 971 357	1.39%	1.44%	1.53%
72	South America	VE	Venezuela	28 372 266	1.34%	1.42%	0.45%
73	Asia	IR	Iran	84 837 813	1.37%	1.42%	1.91%
74	Africa	MA	Morocco	37 254 502	1.94%	1.41%	0.16%
75	North America	CR	Costa Rica	5 130 727	1.52%	1.40%	1.28%
76	Africa	BF	Burkina Faso	21 350 969	0.86%	1.39%	0.01%
77	Asia	SA	Saudi Arabia	35 239 473	1.94%	1.39%	0.22%
78	North America	DO	Dominican R.	10 933 492	0.98%	1.37%	0.47%
79	Africa	RW	Rwanda	13 203 279	1.56%	1.33%	0.11%
80	Europe	DE	Germany	83 995 236	3.24%	1.33%	2.43%
81	Asia	TW	Taiwan	23 850 790	1.21%	1.32%	0.00%
82	Asia	BD	Bangladesh	165 980 237	1.61%	1.30%	0.35%
83	Africa	ET	Ethiopia	117 190 341	1.35%	1.29%	0.20%
84	Africa	BJ	Benin	12 371 351	1.18%	1.27%	0.04%
85	Africa	MR	Mauritania	4 745 164	2.73%	1.27%	0.05%
86	Africa	CD	DR Congo	91 685 378	2.60%	1.24%	0.01%
87	Asia	NP	Nepal	29 547 776	3.82%	1.23%	0.09%
88	Asia	PH	Philippines	110 727 033	1.76%	1.20%	0.98%
89	Asia	JO	Jordan	10 282 825	1.13%	1.20%	7.15%
90	South America	PR	Puerto Rico	3 193 694	1.70%	1.12%	1.80%
91	Africa	MZ	Mozambique	31 939 216	1.25%	1.11%	0.05%
92	Europe	GB	United Kingdom	68 167 060	2.40%	1.11%	0.66%
93	Europe	ES	Spain	46 769 075	1.60%	1.03%	1.61%
94	Asia	KZ	Kazakhstan	18 953 268	1.02%	0.99%	1.13%
95	Africa	NG	Nigeria	210 134 738	0.93%	0.99%	0.01%
96	Asia	IL	Israel	9 197 590	0.68%	0.98%	0.62%
97	Europe	AT	Austria	9 046 892	1.86%	0.94%	3.89%
98	Africa	ZM	Zambia	18 785 992	1.21%	0.94%	0.11%
99	Africa	GN	Guinea	13 411 064	0.80%	0.93%	0.10%
100	Asia	LK	Sri Lanka	21 484 036	0.70%	0.93%	0.14%
101	Australia/Oceania	PG	Papua New Guinea	9 079 879	1.03%	0.91%	0.30%
102	North America	HT	Haiti	11 511 792	0.53%	0.90%	0.01%
103	Asia	OM	Oman	5 208 154	0.80%	0.89%	2.20%
104	Europe	FR	France	65 387 466	1.57%	0.88%	6.55%
105	Europe	BY	Belarus	9 446 869	0.61%	0.82%	1.52%
106	Europe	BE	Belgium	11 629 388	1.61%	0.80%	4.07%
107	Europe	RS	Serbia	8 709 547	0.87%	0.79%	5.91%
108	Asia	IN	India	1 390 679 153	0.87%	0.78%	0.76%
109	Asia	KR	South Korea	51 304 013	1.70%	0.72%	0.12%
110	Africa	UG	Uganda	46 867 258	0.71%	0.70%	0.01%
111	North America	CA	Canada	38 002 618	1.63%	0.69%	1.84%
112	Africa	SS	South Sudan	11 296 903	0.73%	0.69%	0.03%
113	Africa	ER	Eritrea	3 584 978	0.36%	0.67%	0.05%
114	Africa	CG	Congo	5 624 301	0.92%	0.66%	0.05%
115	Africa	GA	Gabon	2 266 822	0.60%	0.66%	0.71%
116	Europe	SI	Slovenia	2 079 164	1.49%	0.64%	5.48%
117	Asia	IQ	Iraq	40 928 986	0.67%	0.63%	1.84%
118	Africa	TG	Togo	8 430 534	0.61%	0.61%	0.20%
119	Asia	TR	Turkey	85 052 838	0.91%	0.61%	5.53%
120	Asia	KW	Kuwait	4 320 165	0.53%	0.61%	3.79%
121	Asia	MM	Myanmar	54 697 119	2.17%	0.60%	0.00%
122	Africa	CI	Ivory Coast	26 889 052	0.59%	0.59%	0.11%
123	Europe	CH	Switzerland	8 704 466	1.46%	0.47%	2.41%
124	Europe	FI	Finland	5 547 512	0.78%	0.47%	1.12%
125	Asia	QA	Qatar	2 807 805	0.25%	0.46%	3.24%
126	North America	CU	Cuba	11 321 156	0.48%	0.44%	0.97%
127	Africa	BI	Burundi	12 167 109	0.22%	0.44%	0.03%
128	Europe	NL	Netherlands	17 164 784	0.88%	0.38%	4.92%
129	Asia	MY	Malaysia	32 691 886	0.33%	0.35%	0.52%
130	Asia	MN	Mongolia	3 319 723	0.29%	0.33%	1.77%
131	Australia/Oceania	AU	Australia	25 732 506	0.14%	0.31%	0.01%
132	Asia	UZ	Uzbekistan	33 850 137	0.23%	0.31%	0.06%
133	Europe	SE	Sweden	10 148 878	0.99%	0.27%	6.31%
134	Europe	DK	Denmark	5 808 288	1.10%	0.26%	1.43%
135	Europe	NO	Norway	5 454 619	0.49%	0.26%	1.81%
136	Asia	AE	Arab Emirates	9 984 338	0.31%	0.22%	2.45%
137	Asia	TH	Thailand	69 938 149	0.14%	0.21%	0.07%
138	Asia	SG	Singapore	5 886 569	0.04%	0.00%	0.04%
139	Australia/Oceania	NZ	New Zealand	5 002 100	0.21%	0.00%	0.01%
140	Africa	SL	Sierra Leone	8 104 071	0.26%	0.00%	0.00%
141	Africa	LR	Liberia	5 150 686	0.51%	0.00%	0.00%
142	Asia	VN	Vietnam	98 027 872	0.00%	0.00%	0.00%
143	Asia	LA	Laos	7 358 471	0.00%	0.00%	0.00%
144	Asia	PS	Palestine	5 194 206	0.00%	0.00%	0.13%
145	Asia	HK	Hong Kong	7 544 866	0.00%	0.00%	0.00%
146	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
147	Africa	TZ	Tanzania	61 062 542	0.00%	0.00%	0.00%
148	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
149	Asia	TJ	Tajikistan	9 705 323	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	Europe	CZ	Czechia	10 724 658	28 267	2.636‰
2	Europe	HU	Hungary	9 640 967	24 762	2.568‰
3	Europe	BA	Bosnia and Herzegovina	3 264 674	7 702	2.359‰
4	Europe	BG	Bulgaria	6 907 046	14 979	2.169‰
5	Europe	SI	Slovenia	2 079 164	4 421	2.126‰
6	Europe	MK	North Macedonia	2 083 306	4 357	2.091‰
7	Europe	BE	Belgium	11 629 388	23 636	2.032‰
8	Europe	SK	Slovakia	5 461 730	10 970	2.009‰
9	Europe	IT	Italy	60 391 595	115 937	1.920‰
10	Europe	GB	United Kingdom	68 167 060	127 191	1.866‰
11	South America	BR	Brazil	213 749 436	362 199	1.694‰
12	North America	US	USA	332 532 050	559 133	1.681‰
13	South America	PE	Peru	33 332 642	55 826	1.675‰
14	Europe	PT	Portugal	10 173 212	16 933	1.665‰
15	Europe	ES	Spain	46 769 075	76 882	1.644‰
16	North America	MX	Mexico	129 998 266	210 695	1.621‰
17	Europe	PL	Poland	37 813 871	61 207	1.619‰
18	Europe	HR	Croatia	4 085 238	6 442	1.577‰
19	Europe	FR	France	65 387 466	99 441	1.521‰
20	North America	PA	Panama	4 368 082	6 179	1.415‰
21	Europe	LT	Lithuania	2 692 167	3 737	1.388‰
22	Europe	MD	Moldova	4 026 555	5 493	1.364‰
23	Europe	SE	Sweden	10 148 878	13 756	1.355‰
24	Europe	RO	Romania	19 136 146	25 800	1.348‰
25	South America	CO	Colombia	51 309 459	66 862	1.303‰
26	Asia	AM	Armenia	2 967 613	3 835	1.292‰
27	South America	CL	Chile	19 245 367	24 766	1.287‰
28	South America	AR	Argentina	45 522 155	58 557	1.286‰
29	Europe	CH	Switzerland	8 704 466	9 800	1.126‰
30	South America	BO	Bolivia	11 798 112	12 580	1.066‰
31	Europe	AT	Austria	9 046 892	9 560	1.057‰
32	Asia	LB	Lebanon	6 801 277	6 809	1.001‰
33	Asia	GE	Georgia	3 983 117	3 916	0.983‰
34	Europe	NL	Netherlands	17 164 784	16 862	0.982‰
35	South America	EC	Ecuador	17 853 392	17 489	0.980‰
36	Europe	IE	Ireland	4 981 160	4 820	0.968‰
37	Europe	DE	Germany	83 995 236	79 709	0.949‰
38	Europe	UA	Ukraine	43 525 906	39 096	0.898‰
39	Africa	ZA	South Africa	59 896 382	53 571	0.894‰
40	Europe	GR	Greece	10 382 792	9 239	0.890‰
41	Europe	AL	Albania	2 875 315	2 335	0.812‰
42	Africa	TN	Tunisia	11 915 894	9 553	0.802‰
43	Asia	JO	Jordan	10 282 825	8 057	0.783‰
44	Asia	IR	Iran	84 837 813	65 680	0.774‰
45	Europe	RU	Russia	145 983 862	104 795	0.718‰
46	South America	PY	Paraguay	7 201 405	5 048	0.701‰
47	Asia	IL	Israel	9 197 590	6 315	0.687‰
48	South America	PR	Puerto Rico	3 193 694	2 174	0.681‰
49	Europe	RS	Serbia	8 709 547	5 881	0.675‰
50	North America	CA	Canada	38 002 618	23 447	0.617‰
51	North America	CR	Costa Rica	5 130 727	3 055	0.595‰
52	North America	HN	Honduras	10 028 249	4 897	0.488‰
53	South America	UY	Uruguay	3 483 224	1 674	0.481‰
54	Europe	DK	Denmark	5 808 288	2 449	0.422‰
55	Africa	LY	Libya	6 944 698	2 873	0.414‰
56	Asia	TR	Turkey	85 052 838	35 031	0.412‰
57	Asia	AZ	Azerbaijan	10 211 103	4 045	0.396‰
58	North America	GT	Guatemala	18 175 404	7 088	0.390‰
59	Asia	IQ	Iraq	40 928 986	14 885	0.364‰
60	Asia	OM	Oman	5 208 154	1 821	0.350‰
61	Asia	KW	Kuwait	4 320 165	1 428	0.331‰
62	North America	SV	El Salvador	6 512 000	2 068	0.318‰
63	North America	DO	Dominican R.	10 933 492	3 405	0.311‰
64	Africa	BW	Botswana	2 388 828	671	0.281‰
65	Europe	BY	Belarus	9 446 869	2 393	0.253‰
66	Africa	MA	Morocco	37 254 502	8 927	0.240‰
67	North America	JM	Jamaica	2 971 357	697	0.235‰
68	Asia	KG	Kyrgyzstan	6 608 658	1 544	0.234‰
69	Africa	NA	Namibia	2 576 989	596	0.231‰
70	Asia	KZ	Kazakhstan	18 953 268	3 963	0.209‰
71	Asia	SA	Saudi Arabia	35 239 473	6 791	0.193‰
72	Europe	FI	Finland	5 547 512	881	0.159‰
73	Asia	ID	Indonesia	275 798 600	43 073	0.156‰
74	Asia	AE	Arab Emirates	9 984 338	1 545	0.155‰
75	Africa	LS	Lesotho	2 155 620	315	0.146‰
76	Asia	PH	Philippines	110 727 033	15 592	0.141‰
77	Europe	NO	Norway	5 454 619	707	0.130‰
78	Asia	QA	Qatar	2 807 805	357	0.127‰
79	Asia	IN	India	1 390 679 153	173 123	0.125‰
80	Africa	EG	Egypt	103 847 468	12 611	0.121‰
81	Asia	NP	Nepal	29 547 776	3 066	0.104‰
82	Africa	ZW	Zimbabwe	15 032 836	1 550	0.103‰
83	Africa	MR	Mauritania	4 745 164	452	0.095‰
84	Asia	SY	Syria	17 833 162	1 414	0.079‰
85	Asia	JP	Japan	126 170 451	9 500	0.075‰
86	Africa	DZ	Algeria	44 471 990	3 144	0.071‰
87	Asia	PK	Pakistan	224 253 902	15 864	0.071‰
88	Africa	GM	Gambia	2 469 682	170	0.069‰
89	Africa	ZM	Zambia	18 785 992	1 230	0.066‰
90	South America	VE	Venezuela	28 372 266	1 834	0.065‰
91	Asia	AF	Afghanistan	39 614 554	2 537	0.064‰
92	Africa	SN	Senegal	17 088 723	1 085	0.064‰
93	Asia	BD	Bangladesh	165 980 237	10 081	0.061‰
94	Asia	MM	Myanmar	54 697 119	3 206	0.059‰
95	Africa	MW	Malawi	19 516 315	1 134	0.058‰
96	Africa	GA	Gabon	2 266 822	129	0.057‰
97	Africa	SD	Sudan	44 650 323	2 194	0.049‰
98	Africa	KE	Kenya	54 698 558	2 424	0.044‰
99	North America	CU	Cuba	11 321 156	491	0.043‰
100	Asia	MY	Malaysia	32 691 886	1 355	0.041‰
101	Africa	SO	Somalia	16 239 481	656	0.040‰
102	Asia	YE	Yemen	30 340 231	1 098	0.036‰
103	Australia/Oceania	AU	Australia	25 732 506	910	0.035‰
104	Asia	KR	South Korea	51 304 013	1 790	0.035‰
105	Africa	CM	Cameroon	27 062 544	919	0.034‰
106	Africa	GW	Guinea-Bissau	2 004 390	66	0.033‰
107	Asia	LK	Sri Lanka	21 484 036	608	0.028‰
108	Africa	ET	Ethiopia	117 190 341	3 287	0.028‰
109	North America	NI	Nicaragua	6 686 515	180	0.027‰
110	Africa	MZ	Mozambique	31 939 216	794	0.025‰
111	Africa	CG	Congo	5 624 301	137	0.024‰
112	Africa	GH	Ghana	31 580 972	766	0.024‰
113	Africa	RW	Rwanda	13 203 279	321	0.024‰
114	North America	HT	Haiti	11 511 792	252	0.022‰
115	Africa	ML	Mali	20 706 145	421	0.020‰
116	Asia	UZ	Uzbekistan	33 850 137	635	0.019‰
117	Africa	MG	Madagascar	28 247 452	527	0.019‰
118	Africa	AO	Angola	33 663 530	557	0.017‰
119	Africa	LR	Liberia	5 150 686	85	0.017‰
120	Africa	CF	Central African R.	4 895 636	74	0.015‰
121	Africa	TG	Togo	8 430 534	117	0.014‰
122	Asia	MN	Mongolia	3 319 723	35	0.011‰
123	Africa	GN	Guinea	13 411 064	138	0.010‰
124	Africa	SS	South Sudan	11 296 903	114	0.010‰
125	Africa	CI	Ivory Coast	26 889 052	271	0.010‰
126	Africa	TD	Chad	16 793 808	168	0.010‰
127	Africa	NG	Nigeria	210 134 738	2 061	0.010‰
128	Africa	SL	Sierra Leone	8 104 071	79	0.010‰
129	Asia	TJ	Tajikistan	9 705 323	90	0.009‰
130	Australia/Oceania	PG	Papua New Guinea	9 079 879	82	0.009‰
131	Africa	CD	DR Congo	91 685 378	745	0.008‰
132	Africa	BJ	Benin	12 371 351	96	0.008‰
133	Africa	NE	Niger	24 888 432	190	0.008‰
134	Africa	BF	Burkina Faso	21 350 969	154	0.007‰
135	Africa	UG	Uganda	46 867 258	338	0.007‰
136	Australia/Oceania	NZ	New Zealand	5 002 100	26	0.005‰
137	Asia	SG	Singapore	5 886 569	30	0.005‰
138	Africa	ER	Eritrea	3 584 978	10	0.003‰
139	Asia	PS	Palestine	5 194 206	14	0.003‰
140	Asia	KH	Cambodia	16 900 725	37	0.002‰
141	Asia	TH	Thailand	69 938 149	97	0.001‰
142	Africa	BI	Burundi	12 167 109	6	0.001‰
143	Asia	TW	Taiwan	23 850 790	11	0.001‰
144	Asia	VN	Vietnam	98 027 872	35	0.000‰
145	Africa	TZ	Tanzania	61 062 542	21	0.000‰
146	Asia	CN	China	1 439 323 776	0	0.000‰
147	Asia	KP	North Korea	25 660 000	0	0.000‰
148	Europe	TM	Turkmenistan	6 118 000	0	0.000‰
149	Asia	LA	Laos	7 358 471	0	0.000‰
150	Asia	HK	Hong Kong	7 544 866	0	0.000‰

Elhalálozási adatok hozzávetőleges értékei 2018: Abortusz: 56 millió, Rákbetegség: 9,6 millió.

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

* ÚV lámpa (neon) használata a helységekben.
* Azelastine: [1], [2] , [*] 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)
* 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]

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

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"