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": 2021-05-10 16:56
(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	+820 (+1 026)	+10 (+8)
CZ	Czechia	+381 (+721)	+13 (+24)
DE	Germany	+4 041 (+8 290)	+42 (+119)
HU	Hungary	+677 (+1 145)	+91 (+98)
PL	Poland	+2 032 (+3 851)	+22 (+147)
SK	Slovakia, [gov], [okr]	+311 (+80)	+32 (+29)

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

N.	Region	Population	Last 120 days	Last 30 days	Last 7 days
1	South America	437 038 871	2.76%	3.40%	3.03%
2	Europe	756 023 952	2.59%	2.17%	1.55%
3	Asia	4 663 339 167	0.48%	1.13%	1.22%
4	North America	592 616 840	2.14%	1.44%	1.06%
5	Africa	1 367 189 143	0.12%	0.09%	0.08%
6	Australia/Oceania	43 225 507	0.04%	0.05%	0.05%

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	437 038 871	2.77%	4.02%	3.40%
2	Africa	1 367 189 143	2.93%	(3.71)%	(0.09)%
3	Europe	756 023 952	2.16%	2.54%	2.17%
4	North America	592 616 840	2.21%	2.13%	1.44%
5	Australia/Oceania	43 225 507	1.02%	(1.48)%	(0.05)%
6	Asia	4 663 339 167	1.12%	1.25%	1.13%

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	437 038 871	703 330	1.609‰
2	North America	592 616 840	850 582	1.435‰
3	Europe	756 023 952	1 036 077	1.370‰
4	Asia	4 663 339 167	560 576	0.120‰
5	Africa	1 367 189 143	124 702	0.091‰
6	Australia/Oceania	43 225 507	1 347	0.031‰

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	3 484 011	5.56%	10.03%	8.42%
2	Europe	LT	Lithuania	2 689 695	3.52%	4.95%	5.27%
3	Europe	NL	Netherlands	17 167 263	4.04%	5.24%	5.19%
4	South America	AR	Argentina	45 549 324	3.13%	5.76%	5.11%
5	Europe	SE	Sweden	10 153 000	5.11%	6.23%	4.86%
6	North America	CR	Costa Rica	5 133 774	1.74%	3.56%	4.84%
7	Asia	GE	Georgia	3 982 617	2.09%	3.49%	4.10%
8	Europe	HR	Croatia	4 083 587	3.06%	5.27%	3.87%
9	South America	CO	Colombia	51 345 002	2.40%	3.85%	3.61%
10	South America	PY	Paraguay	7 207 149	2.52%	3.67%	3.50%
11	Europe	SI	Slovenia	2 079 182	5.16%	4.06%	3.46%
12	Asia	NP	Nepal	29 582 184	0.44%	1.56%	3.42%
13	Asia	KW	Kuwait	4 324 308	3.03%	3.77%	3.36%
14	Asia	IN	India	1 391 568 121	0.87%	2.68%	3.21%
15	Europe	FR	France	65 396 910	4.53%	4.79%	3.19%
16	Asia	MN	Mongolia	3 323 187	1.30%	3.75%	3.19%
17	Asia	TR	Turkey	85 112 315	3.19%	6.04%	3.14%
18	South America	BR	Brazil	213 848 364	3.32%	3.44%	3.13%
19	Europe	BE	Belgium	11 632 688	3.02%	3.16%	2.77%
20	South America	CL	Chile	19 256 115	3.13%	3.76%	2.70%
21	Europe	GR	Greece	10 379 470	2.10%	2.74%	2.57%
22	Asia	IR	Iran	84 908 308	1.62%	2.97%	2.51%
23	Asia	QA	Qatar	2 807 805	2.33%	3.26%	2.47%
24	North America	CA	Canada	38 024 294	1.67%	2.57%	2.38%
25	Asia	AE	Arab Emirates	9 992 172	3.08%	2.24%	2.09%
26	South America	PE	Peru	33 362 768	2.44%	2.72%	2.04%
27	Europe	DE	Germany	84 012 757	1.92%	2.59%	2.01%
28	Europe	CH	Switzerland	8 708 610	2.18%	2.45%	1.96%
29	Europe	IT	Italy	60 385 788	3.07%	2.48%	1.89%
30	Europe	DK	Denmark	5 809 622	1.35%	1.57%	1.83%
31	Europe	CZ	Czechia	10 725 956	7.59%	2.52%	1.73%
32	Europe	RS	Serbia	8 707 250	3.93%	2.94%	1.69%
33	Europe	AT	Austria	9 050 255	2.75%	2.59%	1.62%
34	Asia	IQ	Iraq	40 988 315	1.25%	1.97%	1.61%
35	South America	PR	Puerto Rico	3 193 694	1.65%	3.03%	1.57%
36	South America	BO	Bolivia	11 808 555	1.24%	1.29%	1.55%
37	Europe	HU	Hungary	9 639 365	4.67%	3.26%	1.47%
38	Europe	UA	Ukraine	43 508 768	2.32%	2.59%	1.43%
39	Asia	OM	Oman	5 216 697	1.34%	2.46%	1.42%
40	Europe	BY	Belarus	9 446 666	1.67%	1.49%	1.36%
41	Asia	AM	Armenia	2 967 975	1.93%	2.32%	1.35%
42	Asia	MY	Malaysia	32 719 078	0.94%	1.02%	1.35%
43	Europe	PL	Poland	37 811 163	3.83%	2.99%	1.33%
44	North America	US	USA	332 659 090	3.17%	1.94%	1.31%
45	Africa	TN	Tunisia	11 923 998	1.37%	1.74%	1.30%
46	South America	EC	Ecuador	17 870 970	1.01%	1.29%	1.25%
47	Europe	BG	Bulgaria	6 903 636	2.92%	2.32%	1.24%
48	Asia	JO	Jordan	10 289 462	4.02%	2.36%	1.18%
49	Asia	LB	Lebanon	6 799 282	4.67%	2.41%	1.17%
50	Asia	KZ	Kazakhstan	18 967 992	0.98%	1.60%	1.15%
51	Europe	BA	Bosnia and Herzegovina	3 263 343	2.63%	2.35%	1.13%
52	Asia	LK	Sri Lanka	21 489 910	0.36%	0.58%	1.13%
53	North America	CU	Cuba	11 320 705	0.90%	1.11%	1.10%
54	Europe	MK	North Macedonia	2 083 301	3.26%	2.68%	1.10%
55	Africa	BW	Botswana	2 391 948	1.35%	1.12%	1.06%
56	North America	HN	Honduras	10 038 587	0.92%	1.01%	1.04%
57	Europe	NO	Norway	5 457 395	1.13%	1.01%	1.00%
58	North America	PA	Panama	4 372 539	2.15%	0.86%	0.90%
59	Europe	ES	Spain	46 770 258	3.10%	1.81%	0.85%
60	Asia	AZ	Azerbaijan	10 217 089	1.01%	1.76%	0.85%
61	Europe	SK	Slovakia	5 461 902	3.31%	1.12%	0.80%
62	Africa	NA	Namibia	2 580 010	0.87%	0.76%	0.78%
63	Europe	IE	Ireland	4 984 775	2.23%	0.95%	0.74%
64	Europe	RO	Romania	19 127 777	2.08%	1.41%	0.74%
65	Asia	PH	Philippines	110 822 682	0.56%	0.94%	0.72%
66	Europe	RU	Russia	145 987 952	1.02%	0.70%	0.67%
67	North America	DO	Dominican R.	10 940 620	0.83%	0.55%	0.64%
68	Europe	MD	Moldova	4 025 943	2.57%	1.26%	0.60%
69	Asia	KG	Kyrgyzstan	6 615 723	0.25%	0.52%	0.60%
70	Africa	LY	Libya	6 950 826	1.09%	0.75%	0.51%
71	Asia	JP	Japan	126 145 174	0.28%	0.44%	0.50%
72	North America	GT	Guatemala	18 197 167	0.50%	0.72%	0.49%
73	North America	JM	Jamaica	2 972 202	1.12%	0.65%	0.49%
74	South America	VE	Venezuela	28 367 006	0.32%	0.50%	0.46%
75	Asia	KH	Cambodia	16 915 901	0.11%	0.37%	0.44%
76	Europe	FI	Finland	5 548 075	0.90%	0.52%	0.39%
77	Europe	GB	United Kingdom	68 190 397	1.96%	0.40%	0.37%
78	Europe	PT	Portugal	10 171 271	3.57%	0.51%	0.36%
79	Africa	ZA	South Africa	59 945 412	0.64%	0.27%	0.36%
80	Asia	TH	Thailand	69 949 602	0.11%	0.31%	0.34%
81	Asia	SA	Saudi Arabia	35 275 050	0.18%	0.34%	0.34%
82	Europe	AL	Albania	2 875 110	2.39%	0.55%	0.29%
83	North America	SV	El Salvador	6 514 142	0.33%	0.29%	0.28%
84	Africa	GA	Gabon	2 270 275	0.61%	0.56%	0.27%
85	Africa	CM	Cameroon	27 106 006	0.18%	0.26%	0.26%
86	Asia	ID	Indonesia	275 988 146	0.32%	0.23%	0.23%
87	Asia	PK	Pakistan	224 535 621	0.16%	0.26%	0.21%
88	North America	MX	Mexico	130 087 038	0.66%	0.30%	0.20%
89	Australia/Oceania	PG	Papua New Guinea	9 091 010	0.13%	0.19%	0.18%
90	Africa	CG	Congo	5 633 234	0.07%	0.08%	0.14%
91	Asia	UZ	Uzbekistan	33 881 957	0.05%	0.12%	0.14%
92	Asia	KR	South Korea	51 306 896	0.12%	0.15%	0.14%
93	Africa	EG	Egypt	103 974 224	0.09%	0.11%	0.13%
94	Asia	BD	Bangladesh	166 087 745	0.15%	0.24%	0.12%
95	Asia	PS	Palestine	5 202 003	0.01%	0.02%	0.10%
96	Africa	KE	Kenya	54 776 405	0.12%	0.14%	0.10%
97	Africa	CF	Central African R.	4 901 149	0.03%	0.10%	0.09%
98	Africa	MA	Morocco	37 283 183	0.17%	0.14%	0.09%
99	Africa	AO	Angola	33 730 885	0.03%	0.07%	0.09%
100	Africa	MG	Madagascar	28 294 285	0.08%	0.17%	0.08%
101	Asia	AF	Afghanistan	39 672 184	0.02%	0.05%	0.08%
102	Africa	MR	Mauritania	4 753 206	0.07%	0.06%	0.08%
103	Asia	LA	Laos	7 365 397	0.02%	0.07%	0.08%
104	Africa	ET	Ethiopia	117 377 636	0.11%	0.13%	0.06%
105	Asia	IL	Israel	9 197 590	3.84%	0.14%	0.06%
106	Africa	DZ	Algeria	44 523 981	0.05%	0.05%	0.06%
107	Africa	SO	Somalia	16 268 669	0.06%	0.05%	0.05%
108	Africa	RW	Rwanda	13 224 396	0.12%	0.07%	0.05%
109	Africa	GN	Guinea	13 434 507	0.07%	0.06%	0.05%
110	Asia	SY	Syria	17 861 120	0.06%	0.08%	0.05%
111	Asia	SG	Singapore	5 889 582	0.04%	0.05%	0.04%
112	Africa	TG	Togo	8 443 291	0.11%	0.07%	0.04%
113	Africa	ER	Eritrea	3 588 197	0.06%	0.04%	0.03%
114	Africa	ZM	Zambia	18 819 883	0.35%	0.05%	0.03%
115	Africa	LS	Lesotho	2 156 732	0.38%	0.01%	0.03%
116	Africa	SN	Senegal	17 117 756	0.12%	0.03%	0.03%
117	Africa	GM	Gambia	2 474 151	0.08%	0.06%	0.02%
118	North America	NI	Nicaragua	6 691 682	0.01%	0.01%	0.02%
119	Africa	BI	Burundi	12 190 433	0.03%	0.04%	0.02%
120	Africa	CI	Ivory Coast	26 932 014	0.09%	0.02%	0.02%
121	Africa	SD	Sudan	44 717 636	0.02%	0.02%	0.02%
122	Africa	ML	Mali	20 744 549	0.03%	0.05%	0.02%
123	Africa	ZW	Zimbabwe	15 047 030	0.12%	0.03%	0.02%
124	Africa	UG	Uganda	46 962 440	0.01%	0.01%	0.01%
125	Africa	MZ	Mozambique	31 996 859	0.15%	0.02%	0.01%
126	Africa	GH	Ghana	31 623 590	0.12%	0.02%	0.01%
127	North America	HT	Haiti	11 520 906	0.03%	0.01%	0.01%
128	Asia	YE	Yemen	30 383 405	0.01%	0.02%	0.01%
129	Africa	SS	South Sudan	11 305 506	0.06%	0.01%	0.01%
130	Africa	BJ	Benin	12 392 243	0.04%	0.01%	0.01%
131	Asia	VN	Vietnam	98 085 243	0.00%	0.00%	0.01%
132	Australia/Oceania	AU	Australia	25 751 901	0.01%	0.01%	0.01%
133	Australia/Oceania	NZ	New Zealand	5 002 100	0.01%	0.01%	0.01%
134	Africa	MW	Malawi	19 548 837	0.13%	0.01%	0.01%
135	Africa	CD	DR Congo	91 864 730	0.01%	0.01%	0.01%
136	Africa	BF	Burkina Faso	21 388 695	0.03%	0.01%	0.01%
137	Africa	LR	Liberia	5 158 502	0.01%	0.00%	0.01%
138	Africa	TD	Chad	16 824 841	0.01%	0.01%	0.01%
139	Africa	NE	Niger	24 946 242	0.01%	0.00%	0.01%
140	Asia	TW	Taiwan	23 853 608	0.00%	0.00%	0.00%
141	Asia	MM	Myanmar	54 720 998	0.02%	0.00%	0.00%
142	Africa	GW	Guinea-Bissau	2 007 449	0.06%	0.01%	0.00%
143	Africa	NG	Nigeria	210 470 780	0.03%	0.00%	0.00%
144	Africa	SL	Sierra Leone	8 114 728	0.02%	0.00%	0.00%
145	Asia	HK	Hong Kong	7 548 850	0.00%	0.00%	0.00%
146	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
147	Africa	TZ	Tanzania	61 174 557	0.00%	0.00%	0.00%
148	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
149	Asia	TJ	Tajikistan	9 719 405	0.00%	0.00%	0.00%
150	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%

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

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

N.	Region	CD	Country	Population	Mortality last 120 days	Mortality last 30 days	New positive cases last 30 days
1	Africa	LS	Lesotho	2 156 732	3.30%	(16.00)%	(0.01)%
2	Asia	YE	Yemen	30 383 405	15.59%	(14.47)%	(0.02)%
3	North America	MX	Mexico	130 087 038	9.52%	12.14%	0.30%
4	Africa	SD	Sudan	44 717 636	9.32%	(10.49)%	(0.02)%
5	Europe	SK	Slovakia	5 461 902	4.68%	8.41%	1.12%
6	Asia	SY	Syria	17 861 120	7.88%	(7.95)%	(0.08)%
7	Europe	BA	Bosnia and Herzegovina	3 263 343	5.24%	6.05%	2.35%
8	Africa	EG	Egypt	103 974 224	6.49%	5.91%	0.11%
9	Africa	MW	Malawi	19 548 837	3.41%	(5.91)%	(0.01)%
10	Africa	SO	Somalia	16 268 669	6.71%	(5.89)%	(0.05)%
11	Europe	HU	Hungary	9 639 365	3.96%	5.24%	3.26%
12	Europe	BG	Bulgaria	6 903 636	4.37%	4.78%	2.32%
13	Asia	AF	Afghanistan	39 672 184	5.55%	(4.78)%	(0.05)%
14	Europe	MK	North Macedonia	2 083 301	3.60%	4.73%	2.68%
15	Africa	ZA	South Africa	59 945 412	4.42%	4.53%	0.27%
16	Europe	RO	Romania	19 127 777	2.95%	4.42%	1.41%
17	Europe	RU	Russia	145 987 952	3.25%	4.24%	0.70%
18	Africa	TN	Tunisia	11 923 998	3.70%	4.10%	1.74%
19	South America	PE	Peru	33 362 768	3.26%	4.04%	2.72%
20	Africa	DZ	Algeria	44 523 981	2.35%	(4.03)%	(0.05)%
21	South America	BR	Brazil	213 848 364	3.11%	3.98%	3.44%
22	North America	HT	Haiti	11 520 906	0.84%	(3.92)%	(0.01)%
23	North America	HN	Honduras	10 038 587	2.62%	3.92%	1.01%
24	South America	EC	Ecuador	17 870 970	2.92%	3.73%	1.29%
25	South America	PY	Paraguay	7 207 149	2.71%	3.72%	3.67%
26	Europe	MD	Moldova	4 025 943	2.67%	3.37%	1.26%
27	Asia	ID	Indonesia	275 988 146	2.51%	3.05%	0.23%
28	Europe	PL	Poland	37 811 163	2.61%	3.04%	2.99%
29	Africa	NA	Namibia	2 580 010	1.81%	3.01%	0.76%
30	Europe	GR	Greece	10 379 470	2.81%	2.98%	2.74%
31	Africa	ZW	Zimbabwe	15 047 030	4.59%	(2.98)%	(0.03)%
32	Africa	SN	Senegal	17 117 756	3.15%	(2.85)%	(0.03)%
33	Europe	UA	Ukraine	43 508 768	2.64%	2.75%	2.59%
34	South America	CO	Colombia	51 345 002	2.61%	2.68%	3.85%
35	Africa	ML	Mali	20 744 549	3.06%	(2.64)%	(0.05)%
36	Asia	AM	Armenia	2 967 975	2.32%	2.52%	2.32%
37	Africa	KE	Kenya	54 776 405	1.87%	2.49%	0.14%
38	North America	JM	Jamaica	2 972 202	1.50%	2.46%	0.65%
39	Asia	PK	Pakistan	224 535 621	2.40%	2.40%	0.26%
40	South America	BO	Bolivia	11 808 555	2.68%	2.39%	1.29%
41	North America	NI	Nicaragua	6 691 682	2.54%	(2.33)%	(0.01)%
42	North America	SV	El Salvador	6 514 142	3.25%	2.31%	0.29%
43	Europe	CZ	Czechia	10 725 956	1.85%	2.29%	2.52%
44	Europe	IT	Italy	60 385 788	2.33%	2.23%	2.48%
45	Europe	HR	Croatia	4 083 587	2.56%	2.17%	5.27%
46	North America	GT	Guatemala	18 197 167	3.00%	2.16%	0.72%
47	Africa	GM	Gambia	2 474 151	2.38%	(2.05)%	(0.06)%
48	Europe	AL	Albania	2 875 110	1.63%	2.00%	0.55%
49	Asia	IL	Israel	9 197 590	0.68%	2.00%	0.14%
50	Asia	TW	Taiwan	23 853 608	1.50%	2.00%	0.00%
51	Africa	BW	Botswana	2 391 948	2.08%	1.95%	1.12%
52	South America	UY	Uruguay	3 484 011	1.56%	1.94%	10.03%
53	Africa	BF	Burkina Faso	21 388 695	1.14%	1.89%	0.01%
54	Asia	KG	Kyrgyzstan	6 615 723	1.94%	1.88%	0.52%
55	Africa	MG	Madagascar	28 294 285	2.32%	1.87%	0.17%
56	Africa	AO	Angola	33 730 885	2.31%	1.86%	0.07%
57	Africa	NE	Niger	24 946 242	4.31%	1.79%	0.00%
58	Africa	CM	Cameroon	27 106 006	1.59%	1.76%	0.26%
59	Asia	IR	Iran	84 908 308	1.45%	1.73%	2.97%
60	Africa	CI	Ivory Coast	26 932 014	0.64%	1.70%	0.02%
61	Africa	MZ	Mozambique	31 996 859	1.25%	1.70%	0.02%
62	Asia	BD	Bangladesh	166 087 745	1.69%	1.70%	0.24%
63	Asia	LB	Lebanon	6 799 282	1.73%	1.68%	2.41%
64	Africa	ET	Ethiopia	117 377 636	1.43%	1.65%	0.13%
65	Africa	CF	Central African R.	4 901 149	2.07%	1.63%	0.10%
66	Asia	JO	Jordan	10 289 462	1.22%	1.61%	2.36%
67	South America	AR	Argentina	45 549 324	1.68%	1.59%	5.76%
68	Africa	TD	Chad	16 824 841	2.41%	1.57%	0.01%
69	Africa	CD	DR Congo	91 864 730	1.34%	1.54%	0.01%
70	Africa	GH	Ghana	31 623 590	1.19%	1.54%	0.02%
71	Africa	LY	Libya	6 950 826	1.94%	1.54%	0.75%
72	Asia	AZ	Azerbaijan	10 217 089	1.77%	1.52%	1.76%
73	South America	CL	Chile	19 256 115	1.70%	1.52%	3.76%
74	South America	VE	Venezuela	28 367 006	1.43%	1.49%	0.50%
75	Asia	GE	Georgia	3 982 617	1.83%	1.47%	3.49%
76	Africa	BJ	Benin	12 392 243	1.23%	1.38%	0.01%
77	Asia	PH	Philippines	110 822 682	1.55%	1.35%	0.94%
78	Africa	GW	Guinea-Bissau	2 007 449	1.71%	1.33%	0.01%
79	Africa	MA	Morocco	37 283 183	1.96%	1.28%	0.14%
80	Asia	NP	Nepal	29 582 184	2.49%	1.26%	1.56%
81	Asia	JP	Japan	126 145 174	1.90%	1.24%	0.44%
82	Europe	IE	Ireland	4 984 775	1.69%	1.22%	0.95%
83	North America	PA	Panama	4 372 539	1.65%	1.20%	0.86%
84	Asia	SA	Saudi Arabia	35 275 050	1.39%	1.20%	0.34%
85	Europe	DE	Germany	84 012 757	2.68%	1.19%	2.59%
86	Europe	LT	Lithuania	2 689 695	1.84%	1.19%	4.95%
87	North America	US	USA	332 659 090	1.73%	1.14%	1.94%
88	Europe	BE	Belgium	11 632 688	1.25%	1.13%	3.16%
89	Asia	LK	Sri Lanka	21 489 910	0.85%	1.12%	0.58%
90	Australia/Oceania	PG	Papua New Guinea	9 091 010	1.07%	1.11%	0.19%
91	Africa	CG	Congo	5 633 234	1.07%	1.10%	0.08%
92	Africa	MR	Mauritania	4 753 206	1.91%	1.10%	0.06%
93	Europe	RS	Serbia	8 707 250	0.86%	1.10%	2.94%
94	Asia	MM	Myanmar	54 720 998	2.24%	1.10%	0.00%
95	North America	CR	Costa Rica	5 133 774	1.32%	1.08%	3.56%
96	Europe	AT	Austria	9 050 255	1.37%	1.08%	2.59%
97	North America	DO	Dominican R.	10 940 620	1.17%	1.05%	0.55%
98	Africa	ZM	Zambia	18 819 883	1.13%	1.05%	0.05%
99	Asia	IN	India	1 391 568 121	0.98%	1.01%	2.68%
100	Asia	OM	Oman	5 216 697	0.89%	0.99%	2.46%
101	South America	PR	Puerto Rico	3 193 694	1.41%	0.92%	3.03%
102	Asia	KZ	Kazakhstan	18 967 992	0.95%	0.92%	1.60%
103	North America	CU	Cuba	11 320 705	0.61%	0.91%	1.11%
104	Europe	FR	France	65 396 910	1.30%	0.88%	4.79%
105	Africa	GN	Guinea	13 434 507	0.81%	0.88%	0.06%
106	Africa	UG	Uganda	46 962 440	0.72%	0.86%	0.01%
107	Europe	BY	Belarus	9 446 666	0.69%	0.82%	1.49%
108	Europe	GB	United Kingdom	68 190 397	2.70%	0.80%	0.40%
109	Asia	KH	Cambodia	16 915 901	0.84%	0.79%	0.37%
110	Africa	RW	Rwanda	13 224 396	1.32%	0.78%	0.07%
111	Asia	TH	Thailand	69 949 602	0.56%	0.77%	0.31%
112	Europe	SI	Slovenia	2 079 182	1.14%	0.75%	4.06%
113	Asia	QA	Qatar	2 807 805	0.42%	0.73%	3.26%
114	Europe	ES	Spain	46 770 258	1.50%	0.67%	1.81%
115	Asia	TR	Turkey	85 112 315	0.77%	0.65%	6.04%
116	Europe	FI	Finland	5 548 075	0.66%	0.63%	0.52%
117	Europe	PT	Portugal	10 171 271	2.25%	0.61%	0.51%
118	Africa	SS	South Sudan	11 305 506	0.75%	0.61%	0.01%
119	Asia	KW	Kuwait	4 324 308	0.56%	0.60%	3.77%
120	Asia	KR	South Korea	51 306 896	1.24%	0.58%	0.15%
121	North America	CA	Canada	38 024 294	1.23%	0.58%	2.57%
122	Africa	ER	Eritrea	3 588 197	0.26%	0.55%	0.04%
123	Africa	GA	Gabon	2 270 275	0.57%	0.54%	0.56%
124	Asia	MY	Malaysia	32 719 078	0.38%	0.54%	1.02%
125	Asia	IQ	Iraq	40 988 315	0.60%	0.53%	1.97%
126	Europe	NO	Norway	5 457 395	0.46%	0.53%	1.01%
127	Asia	MN	Mongolia	3 323 187	0.45%	0.51%	3.75%
128	Africa	TG	Togo	8 443 291	0.56%	0.37%	0.07%
129	Africa	NG	Nigeria	210 470 780	0.95%	0.33%	0.00%
130	Europe	CH	Switzerland	8 708 610	0.97%	0.33%	2.45%
131	Asia	UZ	Uzbekistan	33 881 957	0.30%	0.33%	0.12%
132	Europe	DK	Denmark	5 809 622	1.14%	0.29%	1.57%
133	Europe	NL	Netherlands	17 167 263	0.73%	0.28%	5.24%
134	Europe	SE	Sweden	10 153 000	0.70%	0.24%	6.23%
135	Australia/Oceania	AU	Australia	25 751 901	0.07%	0.20%	0.01%
136	Asia	AE	Arab Emirates	9 992 172	0.29%	0.15%	2.24%
137	Asia	SG	Singapore	5 889 582	0.08%	0.13%	0.05%
138	Asia	LA	Laos	7 365 397	0.00%	0.00%	0.07%
139	Africa	BI	Burundi	12 190 433	0.12%	0.00%	0.04%
140	Australia/Oceania	NZ	New Zealand	5 002 100	0.23%	0.00%	0.01%
141	Africa	LR	Liberia	5 158 502	0.67%	0.00%	0.00%
142	Africa	SL	Sierra Leone	8 114 728	0.13%	0.00%	0.00%
143	Asia	VN	Vietnam	98 085 243	0.00%	0.00%	0.00%
144	Asia	PS	Palestine	5 202 003	0.00%	0.00%	0.02%
145	Asia	HK	Hong Kong	7 548 850	0.00%	0.00%	0.00%
146	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
147	Africa	TZ	Tanzania	61 174 557	0.00%	0.00%	0.00%
148	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
149	Asia	TJ	Tajikistan	9 719 405	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	HU	Hungary	9 639 365	28 693	2.977‰
2	Europe	CZ	Czechia	10 725 956	29 680	2.767‰
3	Europe	BA	Bosnia and Herzegovina	3 263 343	8 839	2.709‰
4	Europe	BG	Bulgaria	6 903 636	16 929	2.452‰
5	Europe	MK	North Macedonia	2 083 301	5 093	2.445‰
6	Europe	SI	Slovenia	2 079 182	4 612	2.218‰
7	Europe	SK	Slovakia	5 461 902	12 051	2.206‰
8	Europe	BE	Belgium	11 632 688	24 551	2.111‰
9	Europe	IT	Italy	60 385 788	122 833	2.034‰
10	South America	BR	Brazil	213 848 364	420 048	1.964‰
11	South America	PE	Peru	33 362 768	63 796	1.912‰
12	Europe	GB	United Kingdom	68 190 397	127 605	1.871‰
13	Europe	PL	Poland	37 811 163	70 034	1.852‰
14	Europe	HR	Croatia	4 083 587	7 503	1.837‰
15	North America	US	USA	332 659 090	575 341	1.730‰
16	Europe	ES	Spain	46 770 258	78 726	1.683‰
17	North America	MX	Mexico	130 087 038	218 714	1.681‰
18	Europe	PT	Portugal	10 171 271	16 992	1.671‰
19	Europe	FR	France	65 396 910	105 659	1.616‰
20	Europe	RO	Romania	19 127 777	28 971	1.515‰
21	South America	CO	Colombia	51 345 002	77 362	1.507‰
22	Europe	LT	Lithuania	2 689 695	4 044	1.504‰
23	Europe	MD	Moldova	4 025 943	5 952	1.478‰
24	South America	AR	Argentina	45 549 324	67 155	1.474‰
25	North America	PA	Panama	4 372 539	6 264	1.433‰
26	Asia	AM	Armenia	2 967 975	4 249	1.432‰
27	South America	CL	Chile	19 256 115	27 138	1.409‰
28	Europe	SE	Sweden	10 153 000	14 173	1.396‰
29	Europe	CH	Switzerland	8 708 610	10 061	1.155‰
30	South America	BO	Bolivia	11 808 555	13 205	1.118‰
31	Europe	AT	Austria	9 050 255	10 120	1.118‰
32	Asia	LB	Lebanon	6 799 282	7 486	1.101‰
33	Asia	GE	Georgia	3 982 617	4 305	1.081‰
34	South America	EC	Ecuador	17 870 970	19 222	1.076‰
35	Europe	UA	Ukraine	43 508 768	46 512	1.069‰
36	Europe	GR	Greece	10 379 470	11 029	1.063‰
37	Europe	NL	Netherlands	17 167 263	17 336	1.010‰
38	Europe	DE	Germany	84 012 757	84 817	1.010‰
39	Europe	IE	Ireland	4 984 775	4 923	0.988‰
40	South America	PY	Paraguay	7 207 149	7 054	0.979‰
41	Africa	TN	Tunisia	11 923 998	11 429	0.959‰
42	Africa	ZA	South Africa	59 945 412	54 735	0.913‰
43	Asia	JO	Jordan	10 289 462	9 092	0.884‰
44	Asia	IR	Iran	84 908 308	74 875	0.882‰
45	South America	UY	Uruguay	3 484 011	3 072	0.882‰
46	Europe	AL	Albania	2 875 110	2 412	0.839‰
47	Europe	RU	Russia	145 987 952	113 647	0.778‰
48	Europe	RS	Serbia	8 707 250	6 557	0.753‰
49	South America	PR	Puerto Rico	3 193 694	2 367	0.741‰
50	Asia	IL	Israel	9 197 590	6 377	0.693‰
51	North America	CR	Costa Rica	5 133 774	3 365	0.655‰
52	North America	CA	Canada	38 024 294	24 587	0.647‰
53	North America	HN	Honduras	10 038 587	5 633	0.561‰
54	Asia	TR	Turkey	85 112 315	43 029	0.506‰
55	Asia	AZ	Azerbaijan	10 217 089	4 684	0.458‰
56	Africa	LY	Libya	6 950 826	3 065	0.441‰
57	Europe	DK	Denmark	5 809 622	2 497	0.430‰
58	North America	GT	Guatemala	18 197 167	7 711	0.424‰
59	Asia	OM	Oman	5 216 697	2 101	0.403‰
60	Asia	IQ	Iraq	40 988 315	15 770	0.385‰
61	Asia	KW	Kuwait	4 324 308	1 645	0.380‰
62	North America	SV	El Salvador	6 514 142	2 154	0.331‰
63	North America	DO	Dominican R.	10 940 620	3 532	0.323‰
64	Africa	BW	Botswana	2 391 948	734	0.307‰
65	Europe	BY	Belarus	9 446 666	2 632	0.279‰
66	North America	JM	Jamaica	2 972 202	806	0.271‰
67	Africa	NA	Namibia	2 580 010	689	0.267‰
68	Asia	KG	Kyrgyzstan	6 615 723	1 660	0.251‰
69	Africa	MA	Morocco	37 283 183	9 072	0.243‰
70	Asia	KZ	Kazakhstan	18 967 992	4 542	0.239‰
71	Asia	SA	Saudi Arabia	35 275 050	7 072	0.201‰
72	Asia	QA	Qatar	2 807 805	508	0.181‰
73	Asia	IN	India	1 391 568 121	244 871	0.176‰
74	Asia	ID	Indonesia	275 988 146	47 048	0.171‰
75	Europe	FI	Finland	5 548 075	922	0.166‰
76	Asia	PH	Philippines	110 822 682	18 359	0.166‰
77	Asia	AE	Arab Emirates	9 992 172	1 612	0.161‰
78	Africa	LS	Lesotho	2 156 732	319	0.148‰
79	Europe	NO	Norway	5 457 395	767	0.141‰
80	Africa	EG	Egypt	103 974 224	13 904	0.134‰
81	Asia	NP	Nepal	29 582 184	3 771	0.128‰
82	Africa	ZW	Zimbabwe	15 047 030	1 576	0.105‰
83	Africa	MR	Mauritania	4 753 206	456	0.096‰
84	Asia	SY	Syria	17 861 120	1 657	0.093‰
85	Asia	JP	Japan	126 145 174	10 876	0.086‰
86	Asia	PK	Pakistan	224 535 621	18 875	0.084‰
87	South America	VE	Venezuela	28 367 006	2 274	0.080‰
88	Africa	DZ	Algeria	44 523 981	3 328	0.075‰
89	Asia	BD	Bangladesh	166 087 745	11 916	0.072‰
90	Africa	GM	Gambia	2 474 151	175	0.071‰
91	Asia	AF	Afghanistan	39 672 184	2 698	0.068‰
92	Africa	ZM	Zambia	18 819 883	1 257	0.067‰
93	Africa	SN	Senegal	17 117 756	1 118	0.065‰
94	North America	CU	Cuba	11 320 705	732	0.065‰
95	Africa	GA	Gabon	2 270 275	143	0.063‰
96	Africa	MW	Malawi	19 548 837	1 153	0.059‰
97	Asia	MM	Myanmar	54 720 998	3 210	0.059‰
98	Africa	KE	Kenya	54 776 405	2 895	0.053‰
99	Africa	SD	Sudan	44 717 636	2 365	0.053‰
100	Asia	MY	Malaysia	32 719 078	1 674	0.051‰
101	Asia	MN	Mongolia	3 323 187	168	0.051‰
102	Africa	SO	Somalia	16 268 669	747	0.046‰
103	Africa	CM	Cameroon	27 106 006	1 144	0.042‰
104	Asia	YE	Yemen	30 383 405	1 272	0.042‰
105	Asia	LK	Sri Lanka	21 489 910	801	0.037‰
106	Asia	KR	South Korea	51 306 896	1 875	0.036‰
107	Australia/Oceania	AU	Australia	25 751 901	910	0.035‰
108	Africa	GW	Guinea-Bissau	2 007 449	67	0.033‰
109	Africa	ET	Ethiopia	117 377 636	3 888	0.033‰
110	North America	NI	Nicaragua	6 691 682	183	0.027‰
111	Africa	CG	Congo	5 633 234	148	0.026‰
112	Africa	MZ	Mozambique	31 996 859	823	0.026‰
113	Africa	MG	Madagascar	28 294 285	723	0.026‰
114	Africa	RW	Rwanda	13 224 396	338	0.026‰
115	Africa	GH	Ghana	31 623 590	783	0.025‰
116	Africa	ML	Mali	20 744 549	500	0.024‰
117	North America	HT	Haiti	11 520 906	263	0.023‰
118	Asia	UZ	Uzbekistan	33 881 957	662	0.020‰
119	Africa	CF	Central African R.	4 901 149	93	0.019‰
120	Africa	AO	Angola	33 730 885	633	0.019‰
121	Africa	LR	Liberia	5 158 502	85	0.017‰
122	Africa	TG	Togo	8 443 291	124	0.015‰
123	Australia/Oceania	PG	Papua New Guinea	9 091 010	121	0.013‰
124	Africa	GN	Guinea	13 434 507	150	0.011‰
125	Africa	CI	Ivory Coast	26 932 014	291	0.011‰
126	Africa	SS	South Sudan	11 305 506	116	0.010‰
127	Africa	TD	Chad	16 824 841	171	0.010‰
128	Africa	NG	Nigeria	210 470 780	2 065	0.010‰
129	Africa	SL	Sierra Leone	8 114 728	79	0.010‰
130	Asia	TJ	Tajikistan	9 719 405	90	0.009‰
131	Africa	CD	DR Congo	91 864 730	772	0.008‰
132	Africa	BJ	Benin	12 392 243	100	0.008‰
133	Africa	NE	Niger	24 946 242	192	0.008‰
134	Africa	BF	Burkina Faso	21 388 695	162	0.008‰
135	Asia	KH	Cambodia	16 915 901	126	0.007‰
136	Africa	UG	Uganda	46 962 440	346	0.007‰
137	Asia	TH	Thailand	69 949 602	421	0.006‰
138	Asia	SG	Singapore	5 889 582	31	0.005‰
139	Australia/Oceania	NZ	New Zealand	5 002 100	26	0.005‰
140	Africa	ER	Eritrea	3 588 197	12	0.003‰
141	Asia	PS	Palestine	5 202 003	7	0.001‰
142	Africa	BI	Burundi	12 190 433	6	0.001‰
143	Asia	TW	Taiwan	23 853 608	12	0.001‰
144	Asia	VN	Vietnam	98 085 243	35	0.000‰
145	Africa	TZ	Tanzania	61 174 557	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	7 365 397	0	0.000‰
150	Asia	HK	Hong Kong	7 548 850	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) 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]

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"