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": 2021-05-08 10:01
(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 (+1 333)	+0 (+18)
CZ	Czechia	+1 631 (+1 572)	+15 (+36)
DE	Germany	+0 (+17 550)	+0 (+245)
HU	Hungary	+1 376 (+1 541)	+101 (+106)
PL	Poland	+0 (+6 047)	+0 (+453)
SK	Slovakia, [gov], [okr]	+0 (+362)	+0 (+26)

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

N.	Region	Population	Last 120 days	Last 30 days	Last 7 days
1	South America	437 019 460	2.76%	3.48%	3.19%
2	Europe	756 021 509	2.63%	2.32%	1.63%
3	North America	592 591 628	2.24%	1.52%	1.24%
4	Asia	4 663 155 475	0.46%	1.07%	1.13%
5	Africa	1 367 013 259	0.12%	0.09%	0.08%
6	Australia/Oceania	43 222 757	0.04%	0.05%	0.03%

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	437 019 460	2.78%	4.10%	3.48%
2	Africa	1 367 013 259	2.94%	(3.64)%	(0.09)%
3	Europe	756 021 509	2.17%	2.53%	2.32%
4	North America	592 591 628	2.22%	2.16%	1.52%
5	Australia/Oceania	43 222 757	1.04%	(1.42)%	(0.05)%
6	Asia	4 663 155 475	1.11%	1.20%	1.07%

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	437 019 460	697 137	1.595‰
2	North America	592 591 628	849 204	1.433‰
3	Europe	756 021 509	1 032 230	1.365‰
4	Asia	4 663 155 475	546 608	0.117‰
5	Africa	1 367 013 259	124 217	0.091‰
6	Australia/Oceania	43 222 757	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	3 483 946	5.44%	10.28%	8.28%
2	Europe	LT	Lithuania	2 689 901	3.57%	5.02%	5.24%
3	South America	AR	Argentina	45 547 060	3.11%	5.85%	5.24%
4	Europe	NL	Netherlands	17 167 057	4.06%	5.29%	4.98%
5	North America	CR	Costa Rica	5 133 520	1.71%	3.36%	4.86%
6	Europe	SE	Sweden	10 152 657	5.12%	6.32%	4.82%
7	Europe	HR	Croatia	4 083 725	3.08%	5.87%	4.33%
8	Asia	GE	Georgia	3 982 659	2.13%	3.46%	4.03%
9	Europe	SI	Slovenia	2 079 181	5.31%	4.45%	3.95%
10	Asia	MN	Mongolia	3 322 899	1.26%	3.74%	3.77%
11	South America	CO	Colombia	51 342 040	2.40%	3.77%	3.68%
12	Asia	TR	Turkey	85 107 359	3.17%	6.41%	3.58%
13	Asia	KW	Kuwait	4 323 963	3.01%	3.84%	3.56%
14	South America	PY	Paraguay	7 206 670	2.50%	3.71%	3.52%
15	South America	BR	Brazil	213 840 120	3.34%	3.57%	3.35%
16	South America	CL	Chile	19 255 219	3.15%	4.00%	3.34%
17	Europe	FR	France	65 396 123	4.55%	5.01%	3.33%
18	Asia	NP	Nepal	29 579 317	0.39%	1.34%	3.15%
19	Asia	IN	India	1 391 494 040	0.80%	2.46%	2.87%
20	Asia	QA	Qatar	2 807 805	2.31%	3.40%	2.70%
21	Asia	IR	Iran	84 902 433	1.60%	3.03%	2.59%
22	North America	CA	Canada	38 022 488	1.68%	2.57%	2.44%
23	Europe	BE	Belgium	11 632 413	3.00%	3.28%	2.31%
24	Europe	DE	Germany	84 011 297	1.96%	2.76%	2.23%
25	Europe	GR	Greece	10 379 746	2.07%	2.82%	2.16%
26	Asia	AE	Arab Emirates	9 991 520	3.11%	2.27%	2.14%
27	South America	PE	Peru	33 360 257	2.42%	2.79%	2.02%
28	Asia	OM	Oman	5 215 985	1.33%	2.60%	2.00%
29	Europe	IT	Italy	60 386 272	3.10%	2.60%	1.99%
30	Europe	AT	Austria	9 049 975	2.77%	2.74%	1.86%
31	Europe	CZ	Czechia	10 725 848	7.78%	2.85%	1.82%
32	Europe	DK	Denmark	5 809 511	1.37%	1.55%	1.79%
33	Europe	RS	Serbia	8 707 441	3.96%	3.18%	1.76%
34	South America	PR	Puerto Rico	3 193 694	1.70%	2.98%	1.70%
35	Europe	HU	Hungary	9 639 499	4.70%	3.82%	1.65%
36	Europe	CH	Switzerland	8 708 265	2.19%	2.50%	1.63%
37	Asia	IQ	Iraq	40 983 371	1.23%	2.03%	1.62%
38	North America	US	USA	332 648 503	3.33%	2.07%	1.61%
39	South America	BO	Bolivia	11 807 685	1.25%	1.26%	1.52%
40	Europe	ES	Spain	46 770 160	3.18%	1.97%	1.48%
41	Europe	PL	Poland	37 811 389	3.88%	3.73%	1.46%
42	South America	EC	Ecuador	17 869 505	1.00%	1.28%	1.44%
43	Asia	AM	Armenia	2 967 945	1.94%	2.56%	1.44%
44	Europe	UA	Ukraine	43 510 196	2.32%	2.85%	1.42%
45	Europe	BY	Belarus	9 446 682	1.69%	1.51%	1.37%
46	Asia	LB	Lebanon	6 799 448	4.81%	2.70%	1.33%
47	Africa	TN	Tunisia	11 923 323	1.39%	1.79%	1.31%
48	Europe	BG	Bulgaria	6 903 920	2.93%	2.61%	1.27%
49	Asia	MY	Malaysia	32 716 812	0.93%	0.95%	1.24%
50	Asia	JO	Jordan	10 288 909	4.03%	2.64%	1.21%
51	Europe	BA	Bosnia and Herzegovina	3 263 454	2.64%	2.63%	1.17%
52	North America	HN	Honduras	10 037 725	0.92%	1.01%	1.13%
53	Europe	MK	North Macedonia	2 083 301	3.27%	3.07%	1.09%
54	North America	CU	Cuba	11 320 742	0.89%	1.11%	1.09%
55	Africa	BW	Botswana	2 391 688	1.41%	1.12%	1.06%
56	Asia	AZ	Azerbaijan	10 216 590	1.01%	1.92%	1.06%
57	Asia	LK	Sri Lanka	21 489 420	0.35%	0.51%	1.05%
58	Europe	IE	Ireland	4 984 474	2.49%	1.01%	1.04%
59	Asia	KZ	Kazakhstan	18 966 765	0.94%	1.54%	0.89%
60	Europe	SK	Slovakia	5 461 888	3.46%	1.33%	0.88%
61	Europe	NO	Norway	5 457 163	1.14%	1.11%	0.87%
62	North America	PA	Panama	4 372 167	2.32%	0.87%	0.85%
63	Asia	PH	Philippines	110 814 711	0.55%	0.97%	0.78%
64	Europe	RO	Romania	19 128 475	2.12%	1.58%	0.78%
65	Europe	RU	Russia	145 987 611	1.05%	0.71%	0.68%
66	Europe	MD	Moldova	4 025 994	2.59%	1.46%	0.67%
67	Asia	KG	Kyrgyzstan	6 615 134	0.24%	0.51%	0.60%
68	Africa	NA	Namibia	2 579 758	0.89%	0.70%	0.60%
69	North America	GT	Guatemala	18 195 353	0.51%	0.78%	0.57%
70	Africa	CM	Cameroon	27 102 385	0.18%	0.31%	0.55%
71	Africa	LY	Libya	6 950 315	1.10%	0.83%	0.54%
72	North America	DO	Dominican R.	10 940 026	0.85%	0.55%	0.53%
73	North America	JM	Jamaica	2 972 132	1.11%	0.68%	0.49%
74	Europe	FI	Finland	5 548 028	0.91%	0.57%	0.47%
75	Asia	JP	Japan	126 147 280	0.29%	0.42%	0.46%
76	South America	VE	Venezuela	28 367 444	0.31%	0.49%	0.45%
77	Asia	KH	Cambodia	16 914 637	0.11%	0.36%	0.44%
78	Europe	PT	Portugal	10 171 433	3.76%	0.54%	0.40%
79	Europe	GB	United Kingdom	68 188 452	2.10%	0.41%	0.36%
80	Asia	TH	Thailand	69 948 647	0.10%	0.29%	0.35%
81	Asia	SA	Saudi Arabia	35 272 085	0.17%	0.33%	0.34%
82	Africa	ZA	South Africa	59 941 326	0.70%	0.26%	0.32%
83	Europe	AL	Albania	2 875 127	2.43%	0.61%	0.29%
84	North America	SV	El Salvador	6 513 963	0.34%	0.28%	0.24%
85	North America	MX	Mexico	130 079 641	0.68%	0.32%	0.24%
86	Asia	PK	Pakistan	224 512 144	0.16%	0.27%	0.22%
87	Asia	ID	Indonesia	275 972 350	0.33%	0.23%	0.22%
88	Asia	PS	Palestine	5 201 353	0.01%	0.04%	0.18%
89	Africa	GA	Gabon	2 269 987	0.60%	0.54%	0.18%
90	Africa	CG	Congo	5 632 490	0.07%	0.08%	0.14%
91	Asia	UZ	Uzbekistan	33 879 305	0.05%	0.11%	0.14%
92	Asia	KR	South Korea	51 306 656	0.12%	0.15%	0.14%
93	Africa	EG	Egypt	103 963 661	0.09%	0.11%	0.13%
94	Asia	BD	Bangladesh	166 078 786	0.15%	0.27%	0.12%
95	Africa	KE	Kenya	54 769 918	0.12%	0.16%	0.10%
96	Asia	LA	Laos	7 364 820	0.02%	0.06%	0.10%
97	Africa	MG	Madagascar	28 290 383	0.07%	0.18%	0.10%
98	Australia/Oceania	PG	Papua New Guinea	9 090 082	0.12%	0.18%	0.10%
99	Africa	MA	Morocco	37 280 793	0.17%	0.15%	0.09%
100	Africa	CF	Central African R.	4 900 689	0.03%	0.11%	0.09%
101	Africa	AO	Angola	33 725 272	0.03%	0.06%	0.08%
102	Asia	AF	Afghanistan	39 667 381	0.02%	0.05%	0.08%
103	Africa	MR	Mauritania	4 752 536	0.07%	0.06%	0.08%
104	Asia	IL	Israel	9 197 590	4.00%	0.16%	0.07%
105	Africa	DZ	Algeria	44 519 649	0.05%	0.05%	0.06%
106	Africa	ET	Ethiopia	117 362 028	0.11%	0.14%	0.06%
107	Africa	RW	Rwanda	13 222 636	0.12%	0.08%	0.05%
108	Asia	SY	Syria	17 858 790	0.06%	0.08%	0.05%
109	Africa	SO	Somalia	16 266 237	0.06%	0.06%	0.05%
110	Asia	SG	Singapore	5 889 331	0.04%	0.05%	0.05%
111	Africa	GN	Guinea	13 432 554	0.06%	0.06%	0.04%
112	Africa	ZM	Zambia	18 817 059	0.36%	0.06%	0.04%
113	Africa	ER	Eritrea	3 587 929	0.06%	0.04%	0.03%
114	Africa	TG	Togo	8 442 228	0.11%	0.08%	0.03%
115	Africa	SN	Senegal	17 115 337	0.12%	0.03%	0.03%
116	Africa	GM	Gambia	2 473 779	0.08%	0.06%	0.03%
117	Africa	LS	Lesotho	2 156 639	0.38%	0.01%	0.02%
118	North America	NI	Nicaragua	6 691 251	0.01%	0.01%	0.02%
119	Africa	SD	Sudan	44 712 026	0.02%	0.02%	0.02%
120	Africa	BI	Burundi	12 188 489	0.03%	0.04%	0.02%
121	Africa	ML	Mali	20 741 348	0.03%	0.06%	0.02%
122	Africa	CI	Ivory Coast	26 928 434	0.09%	0.02%	0.02%
123	Africa	ZW	Zimbabwe	15 045 847	0.13%	0.04%	0.02%
124	North America	HT	Haiti	11 520 146	0.03%	0.01%	0.02%
125	Africa	GH	Ghana	31 620 038	0.12%	0.02%	0.02%
126	Africa	UG	Uganda	46 954 508	0.01%	0.01%	0.01%
127	Africa	MZ	Mozambique	31 992 056	0.16%	0.02%	0.01%
128	Australia/Oceania	NZ	New Zealand	5 002 100	0.01%	0.01%	0.01%
129	Africa	SS	South Sudan	11 304 789	0.06%	0.01%	0.01%
130	Africa	BJ	Benin	12 390 502	0.04%	0.02%	0.01%
131	Asia	YE	Yemen	30 379 807	0.01%	0.02%	0.01%
132	Australia/Oceania	AU	Australia	25 750 285	0.01%	0.01%	0.01%
133	Africa	MW	Malawi	19 546 127	0.14%	0.01%	0.01%
134	Africa	CD	DR Congo	91 849 784	0.01%	0.01%	0.01%
135	Africa	LR	Liberia	5 157 851	0.01%	0.00%	0.01%
136	Africa	TD	Chad	16 822 255	0.01%	0.01%	0.01%
137	Africa	NE	Niger	24 941 425	0.01%	0.00%	0.01%
138	Africa	BF	Burkina Faso	21 385 551	0.03%	0.01%	0.00%
139	Asia	VN	Vietnam	98 080 462	0.00%	0.00%	0.00%
140	Africa	SL	Sierra Leone	8 113 840	0.02%	0.00%	0.00%
141	Asia	TW	Taiwan	23 853 373	0.00%	0.00%	0.00%
142	Asia	MM	Myanmar	54 719 008	0.03%	0.00%	0.00%
143	Africa	GW	Guinea-Bissau	2 007 194	0.06%	0.02%	0.00%
144	Africa	NG	Nigeria	210 442 777	0.03%	0.00%	0.00%
145	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
146	Africa	TZ	Tanzania	61 165 222	0.00%	0.00%	0.00%
147	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
148	Asia	TJ	Tajikistan	9 718 231	0.00%	0.00%	0.00%
149	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
150	Asia	HK	Hong Kong	7 548 518	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	Asia	YE	Yemen	30 379 807	15.62%	(14.44)%	(0.02)%
2	North America	MX	Mexico	130 079 641	9.55%	12.49%	0.32%
3	Africa	SD	Sudan	44 712 026	9.02%	(11.01)%	(0.02)%
4	Africa	LS	Lesotho	2 156 639	3.30%	(8.89)%	(0.01)%
5	Europe	SK	Slovakia	5 461 888	4.44%	8.10%	1.33%
6	Asia	SY	Syria	17 858 790	7.82%	(7.77)%	(0.08)%
7	Africa	SO	Somalia	16 266 237	6.68%	(6.14)%	(0.06)%
8	Africa	EG	Egypt	103 963 661	6.43%	5.86%	0.11%
9	Europe	BA	Bosnia and Herzegovina	3 263 454	5.21%	5.75%	2.63%
10	Africa	MW	Malawi	19 546 127	3.45%	(5.12)%	(0.01)%
11	Asia	AF	Afghanistan	39 667 381	5.74%	(4.88)%	(0.05)%
12	Europe	HU	Hungary	9 639 499	3.96%	4.87%	3.82%
13	Africa	ZA	South Africa	59 941 326	4.37%	4.77%	0.26%
14	Europe	BG	Bulgaria	6 903 920	4.39%	4.62%	2.61%
15	Europe	MK	North Macedonia	2 083 301	3.60%	4.45%	3.07%
16	Europe	RU	Russia	145 987 611	3.17%	4.28%	0.71%
17	Europe	RO	Romania	19 128 475	2.93%	4.14%	1.58%
18	South America	BR	Brazil	213 840 120	3.12%	4.12%	3.57%
19	Africa	DZ	Algeria	44 519 649	2.35%	(4.05)%	(0.05)%
20	North America	HT	Haiti	11 520 146	0.88%	(4.03)%	(0.01)%
21	Africa	TN	Tunisia	11 923 323	3.66%	3.97%	1.79%
22	South America	PE	Peru	33 360 257	3.24%	3.91%	2.79%
23	South America	EC	Ecuador	17 869 505	2.90%	3.77%	1.28%
24	North America	HN	Honduras	10 037 725	2.61%	3.71%	1.01%
25	South America	PY	Paraguay	7 206 670	2.68%	3.69%	3.71%
26	Africa	ZW	Zimbabwe	15 045 847	4.63%	(3.27)%	(0.04)%
27	Europe	MD	Moldova	4 025 994	2.66%	3.21%	1.46%
28	Africa	NA	Namibia	2 579 758	1.79%	2.97%	0.70%
29	Asia	ID	Indonesia	275 972 350	2.50%	2.94%	0.23%
30	Europe	PL	Poland	37 811 389	2.62%	2.92%	3.73%
31	Europe	GR	Greece	10 379 746	2.80%	2.83%	2.82%
32	Africa	SN	Senegal	17 115 337	3.20%	(2.81)%	(0.03)%
33	South America	CO	Colombia	51 342 040	2.61%	2.69%	3.77%
34	North America	JM	Jamaica	2 972 132	1.51%	2.68%	0.68%
35	Europe	UA	Ukraine	43 510 196	2.63%	2.65%	2.85%
36	Africa	ML	Mali	20 741 348	3.13%	(2.54)%	(0.06)%
37	South America	BO	Bolivia	11 807 685	2.66%	2.43%	1.26%
38	Asia	AM	Armenia	2 967 945	2.28%	2.41%	2.56%
39	Asia	PK	Pakistan	224 512 144	2.39%	2.38%	0.27%
40	Africa	KE	Kenya	54 769 918	1.85%	2.33%	0.16%
41	North America	NI	Nicaragua	6 691 251	2.54%	(2.33)%	(0.01)%
42	Europe	CZ	Czechia	10 725 848	1.87%	2.31%	2.85%
43	Europe	IT	Italy	60 386 272	2.36%	2.31%	2.60%
44	North America	GT	Guatemala	18 195 353	3.09%	2.31%	0.78%
45	North America	SV	El Salvador	6 513 963	3.25%	2.29%	0.28%
46	Asia	TW	Taiwan	23 853 373	1.52%	(2.08)%	(0.00)%
47	Europe	HR	Croatia	4 083 725	2.57%	2.05%	5.87%
48	Asia	IL	Israel	9 197 590	0.68%	2.03%	0.16%
49	Africa	CM	Cameroon	27 102 385	1.75%	1.99%	0.31%
50	Europe	AL	Albania	2 875 127	1.63%	1.97%	0.61%
51	Africa	NE	Niger	24 941 425	4.36%	1.93%	0.00%
52	Africa	GM	Gambia	2 473 779	2.39%	1.93%	0.06%
53	South America	UY	Uruguay	3 483 946	1.56%	1.92%	10.28%
54	Africa	BF	Burkina Faso	21 385 551	1.06%	1.87%	0.01%
55	Africa	AO	Angola	33 725 272	2.36%	1.87%	0.06%
56	Asia	KG	Kyrgyzstan	6 615 134	1.95%	1.84%	0.51%
57	Africa	MG	Madagascar	28 290 383	2.27%	1.84%	0.18%
58	Asia	IR	Iran	84 902 433	1.44%	1.72%	3.03%
59	Africa	BW	Botswana	2 391 688	2.10%	1.67%	1.12%
60	Asia	BD	Bangladesh	166 078 786	1.68%	1.61%	0.27%
61	Africa	CI	Ivory Coast	26 928 434	0.64%	1.61%	0.02%
62	Africa	CF	Central African R.	4 900 689	2.07%	1.60%	0.11%
63	Asia	LB	Lebanon	6 799 448	1.70%	1.59%	2.70%
64	South America	CL	Chile	19 255 219	1.71%	1.58%	4.00%
65	South America	AR	Argentina	45 547 060	1.68%	1.58%	5.85%
66	Asia	JO	Jordan	10 288 909	1.22%	1.58%	2.64%
67	Africa	CD	DR Congo	91 849 784	1.30%	1.58%	0.01%
68	Africa	LY	Libya	6 950 315	1.95%	1.57%	0.83%
69	Africa	GH	Ghana	31 620 038	1.18%	1.57%	0.02%
70	Africa	ET	Ethiopia	117 362 028	1.41%	1.54%	0.14%
71	Asia	AZ	Azerbaijan	10 216 590	1.81%	1.52%	1.92%
72	Africa	MZ	Mozambique	31 992 056	1.26%	1.50%	0.02%
73	South America	VE	Venezuela	28 367 444	1.44%	1.48%	0.49%
74	Europe	IE	Ireland	4 984 474	1.66%	1.45%	1.01%
75	Asia	GE	Georgia	3 982 659	1.85%	1.42%	3.46%
76	Africa	TD	Chad	16 822 255	2.40%	1.41%	0.01%
77	Asia	PH	Philippines	110 814 711	1.55%	1.39%	0.97%
78	Africa	MA	Morocco	37 280 793	1.96%	1.25%	0.15%
79	Europe	DE	Germany	84 011 297	2.77%	1.22%	2.76%
80	Asia	SA	Saudi Arabia	35 272 085	1.40%	1.19%	0.33%
81	Africa	GW	Guinea-Bissau	2 007 194	1.71%	1.19%	0.02%
82	Europe	LT	Lithuania	2 689 901	1.87%	1.19%	5.02%
83	Asia	NP	Nepal	29 579 317	2.68%	1.18%	1.34%
84	North America	US	USA	332 648 503	1.75%	1.16%	2.07%
85	Asia	JP	Japan	126 147 280	1.91%	1.14%	0.42%
86	North America	PA	Panama	4 372 167	1.62%	1.13%	0.87%
87	Asia	LK	Sri Lanka	21 489 420	0.84%	1.12%	0.51%
88	North America	CR	Costa Rica	5 133 520	1.35%	1.11%	3.36%
89	Africa	CG	Congo	5 632 490	1.07%	1.10%	0.08%
90	Europe	AT	Austria	9 049 975	1.40%	1.10%	2.74%
91	Africa	MR	Mauritania	4 752 536	1.64%	1.08%	0.06%
92	Europe	BE	Belgium	11 632 413	1.27%	1.07%	3.28%
93	North America	DO	Dominican R.	10 940 026	1.14%	1.07%	0.55%
94	Europe	RS	Serbia	8 707 441	0.86%	1.06%	3.18%
95	Australia/Oceania	PG	Papua New Guinea	9 090 082	1.08%	1.03%	0.18%
96	Asia	MM	Myanmar	54 719 008	2.23%	1.03%	0.00%
97	Africa	ZM	Zambia	18 817 059	1.18%	1.01%	0.06%
98	Asia	OM	Oman	5 215 985	0.90%	1.01%	2.60%
99	Africa	BJ	Benin	12 390 502	1.23%	0.97%	0.02%
100	Asia	IN	India	1 391 494 040	0.94%	0.97%	2.46%
101	Asia	KZ	Kazakhstan	18 966 765	0.97%	0.93%	1.54%
102	Europe	GB	United Kingdom	68 188 452	2.71%	0.90%	0.41%
103	South America	PR	Puerto Rico	3 193 694	1.42%	0.89%	2.98%
104	Africa	UG	Uganda	46 954 508	0.73%	0.87%	0.01%
105	North America	CU	Cuba	11 320 742	0.60%	0.86%	1.11%
106	Europe	FR	France	65 396 123	1.32%	0.86%	5.01%
107	Africa	GN	Guinea	13 432 554	0.80%	0.82%	0.06%
108	Europe	BY	Belarus	9 446 682	0.68%	0.81%	1.51%
109	Asia	KH	Cambodia	16 914 637	0.85%	0.80%	0.36%
110	Africa	SS	South Sudan	11 304 789	0.75%	0.78%	0.01%
111	Asia	TH	Thailand	69 948 647	0.52%	0.75%	0.29%
112	Europe	ES	Spain	46 770 160	1.51%	0.74%	1.97%
113	Africa	RW	Rwanda	13 222 636	1.35%	0.72%	0.08%
114	Asia	QA	Qatar	2 807 805	0.41%	0.69%	3.40%
115	Europe	PT	Portugal	10 171 433	2.25%	0.67%	0.54%
116	Europe	SI	Slovenia	2 079 181	1.17%	0.67%	4.45%
117	Europe	FI	Finland	5 548 028	0.67%	0.64%	0.57%
118	Asia	TR	Turkey	85 107 359	0.77%	0.63%	6.41%
119	Asia	KW	Kuwait	4 323 963	0.56%	0.59%	3.84%
120	North America	CA	Canada	38 022 488	1.27%	0.58%	2.57%
121	Asia	KR	South Korea	51 306 656	1.29%	0.56%	0.15%
122	Asia	IQ	Iraq	40 983 371	0.60%	0.53%	2.03%
123	Asia	MY	Malaysia	32 716 812	0.38%	0.52%	0.95%
124	Africa	ER	Eritrea	3 587 929	0.38%	0.52%	0.04%
125	Europe	NO	Norway	5 457 163	0.47%	0.48%	1.11%
126	Asia	MN	Mongolia	3 322 899	0.43%	0.48%	3.74%
127	Africa	GA	Gabon	2 269 987	0.56%	0.46%	0.54%
128	Africa	TG	Togo	8 442 228	0.58%	0.40%	0.08%
129	Europe	CH	Switzerland	8 708 265	1.02%	0.34%	2.50%
130	Asia	UZ	Uzbekistan	33 879 305	0.33%	0.34%	0.11%
131	Africa	NG	Nigeria	210 442 777	0.95%	0.32%	0.00%
132	Europe	DK	Denmark	5 809 511	1.17%	0.29%	1.55%
133	Europe	NL	Netherlands	17 167 057	0.75%	0.28%	5.29%
134	Europe	SE	Sweden	10 152 657	0.73%	0.27%	6.32%
135	Australia/Oceania	AU	Australia	25 750 285	0.07%	0.20%	0.01%
136	Asia	AE	Arab Emirates	9 991 520	0.29%	0.15%	2.27%
137	Asia	SG	Singapore	5 889 331	0.08%	0.13%	0.05%
138	Asia	LA	Laos	7 364 820	0.00%	0.00%	0.06%
139	Africa	BI	Burundi	12 188 489	0.13%	0.00%	0.04%
140	Australia/Oceania	NZ	New Zealand	5 002 100	0.22%	0.00%	0.01%
141	Africa	SL	Sierra Leone	8 113 840	0.20%	0.00%	0.00%
142	Africa	LR	Liberia	5 157 851	0.67%	0.00%	0.00%
143	Asia	VN	Vietnam	98 080 462	0.00%	0.00%	0.00%
144	Asia	PS	Palestine	5 201 353	0.00%	0.00%	0.04%
145	Africa	TZ	Tanzania	61 165 222	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	9 718 231	0.00%	0.00%	0.00%
149	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
150	Asia	HK	Hong Kong	7 548 518	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	9 639 499	28 504	2.957‰
2	Europe	CZ	Czechia	10 725 848	29 623	2.762‰
3	Europe	BA	Bosnia and Herzegovina	3 263 454	8 790	2.693‰
4	Europe	BG	Bulgaria	6 903 920	16 886	2.446‰
5	Europe	MK	North Macedonia	2 083 301	5 067	2.432‰
6	Europe	SI	Slovenia	2 079 181	4 593	2.209‰
7	Europe	SK	Slovakia	5 461 888	11 946	2.187‰
8	Europe	BE	Belgium	11 632 413	24 483	2.105‰
9	Europe	IT	Italy	60 386 272	122 470	2.028‰
10	South America	BR	Brazil	213 840 120	416 616	1.948‰
11	South America	PE	Peru	33 360 257	63 272	1.897‰
12	Europe	GB	United Kingdom	68 188 452	127 598	1.871‰
13	Europe	PL	Poland	37 811 389	69 445	1.837‰
14	Europe	HR	Croatia	4 083 725	7 388	1.809‰
15	North America	US	USA	332 648 503	574 499	1.727‰
16	Europe	ES	Spain	46 770 160	78 792	1.685‰
17	North America	MX	Mexico	130 079 641	218 491	1.680‰
18	Europe	PT	Portugal	10 171 433	16 989	1.670‰
19	Europe	FR	France	65 396 123	105 368	1.611‰
20	Europe	RO	Romania	19 128 475	28 799	1.506‰
21	Europe	LT	Lithuania	2 689 901	4 023	1.496‰
22	South America	CO	Colombia	51 342 040	76 468	1.489‰
23	Europe	MD	Moldova	4 025 994	5 929	1.473‰
24	South America	AR	Argentina	45 547 060	66 474	1.460‰
25	North America	PA	Panama	4 372 167	6 255	1.431‰
26	Asia	AM	Armenia	2 967 945	4 225	1.423‰
27	South America	CL	Chile	19 255 219	27 004	1.402‰
28	Europe	SE	Sweden	10 152 657	14 194	1.398‰
29	Europe	CH	Switzerland	8 708 265	10 060	1.155‰
30	Europe	AT	Austria	9 049 975	10 091	1.115‰
31	South America	BO	Bolivia	11 807 685	13 151	1.114‰
32	Asia	LB	Lebanon	6 799 448	7 436	1.094‰
33	Asia	GE	Georgia	3 982 659	4 263	1.070‰
34	South America	EC	Ecuador	17 869 505	19 061	1.067‰
35	Europe	UA	Ukraine	43 510 196	46 200	1.062‰
36	Europe	GR	Greece	10 379 746	10 910	1.051‰
37	Europe	DE	Germany	84 011 297	84 655	1.008‰
38	Europe	NL	Netherlands	17 167 057	17 291	1.007‰
39	Europe	IE	Ireland	4 984 474	4 921	0.987‰
40	South America	PY	Paraguay	7 206 670	6 889	0.956‰
41	Africa	TN	Tunisia	11 923 323	11 277	0.946‰
42	Africa	ZA	South Africa	59 941 326	54 687	0.912‰
43	Asia	JO	Jordan	10 288 909	9 047	0.879‰
44	Asia	IR	Iran	84 902 433	74 241	0.874‰
45	South America	UY	Uruguay	3 483 946	2 978	0.855‰
46	Europe	AL	Albania	2 875 127	2 408	0.838‰
47	Europe	RU	Russia	145 987 611	112 622	0.771‰
48	Europe	RS	Serbia	8 707 441	6 519	0.749‰
49	South America	PR	Puerto Rico	3 193 694	2 348	0.735‰
50	Asia	IL	Israel	9 197 590	6 375	0.693‰
51	North America	CR	Costa Rica	5 133 520	3 350	0.653‰
52	North America	CA	Canada	38 022 488	24 490	0.644‰
53	North America	HN	Honduras	10 037 725	5 522	0.550‰
54	Asia	TR	Turkey	85 107 359	42 465	0.499‰
55	Asia	AZ	Azerbaijan	10 216 590	4 650	0.455‰
56	Africa	LY	Libya	6 950 315	3 063	0.441‰
57	Europe	DK	Denmark	5 809 511	2 495	0.429‰
58	North America	GT	Guatemala	18 195 353	7 695	0.423‰
59	Asia	OM	Oman	5 215 985	2 083	0.399‰
60	Asia	IQ	Iraq	40 983 371	15 702	0.383‰
61	Asia	KW	Kuwait	4 323 963	1 628	0.377‰
62	North America	SV	El Salvador	6 513 963	2 146	0.329‰
63	North America	DO	Dominican R.	10 940 026	3 517	0.322‰
64	Africa	BW	Botswana	2 391 688	734	0.307‰
65	Europe	BY	Belarus	9 446 682	2 612	0.277‰
66	North America	JM	Jamaica	2 972 132	801	0.270‰
67	Africa	NA	Namibia	2 579 758	682	0.264‰
68	Asia	KG	Kyrgyzstan	6 615 134	1 649	0.249‰
69	Africa	MA	Morocco	37 280 793	9 057	0.243‰
70	Asia	KZ	Kazakhstan	18 966 765	4 542	0.239‰
71	Asia	SA	Saudi Arabia	35 272 085	7 045	0.200‰
72	Asia	QA	Qatar	2 807 805	496	0.177‰
73	Asia	ID	Indonesia	275 972 350	46 663	0.169‰
74	Asia	IN	India	1 391 494 040	234 088	0.168‰
75	Europe	FI	Finland	5 548 028	922	0.166‰
76	Asia	PH	Philippines	110 814 711	18 099	0.163‰
77	Asia	AE	Arab Emirates	9 991 520	1 607	0.161‰
78	Africa	LS	Lesotho	2 156 639	319	0.148‰
79	Europe	NO	Norway	5 457 163	767	0.141‰
80	Africa	EG	Egypt	103 963 661	13 779	0.133‰
81	Asia	NP	Nepal	29 579 317	3 579	0.121‰
82	Africa	ZW	Zimbabwe	15 045 847	1 576	0.105‰
83	Africa	MR	Mauritania	4 752 536	456	0.096‰
84	Asia	SY	Syria	17 858 790	1 639	0.092‰
85	Asia	JP	Japan	126 147 280	10 589	0.084‰
86	Asia	PK	Pakistan	224 512 144	18 657	0.083‰
87	South America	VE	Venezuela	28 367 444	2 245	0.079‰
88	Africa	DZ	Algeria	44 519 649	3 315	0.074‰
89	Asia	BD	Bangladesh	166 078 786	11 833	0.071‰
90	Africa	GM	Gambia	2 473 779	175	0.071‰
91	Asia	AF	Afghanistan	39 667 381	2 683	0.068‰
92	Africa	ZM	Zambia	18 817 059	1 256	0.067‰
93	Africa	SN	Senegal	17 115 337	1 116	0.065‰
94	North America	CU	Cuba	11 320 742	713	0.063‰
95	Africa	GA	Gabon	2 269 987	142	0.063‰
96	Africa	MW	Malawi	19 546 127	1 152	0.059‰
97	Asia	MM	Myanmar	54 719 008	3 210	0.059‰
98	Africa	SD	Sudan	44 712 026	2 365	0.053‰
99	Africa	KE	Kenya	54 769 918	2 865	0.052‰
100	Asia	MY	Malaysia	32 716 812	1 632	0.050‰
101	Africa	SO	Somalia	16 266 237	745	0.046‰
102	Asia	MN	Mongolia	3 322 899	149	0.045‰
103	Africa	CM	Cameroon	27 102 385	1 144	0.042‰
104	Asia	YE	Yemen	30 379 807	1 270	0.042‰
105	Asia	KR	South Korea	51 306 656	1 865	0.036‰
106	Asia	LK	Sri Lanka	21 489 420	764	0.036‰
107	Australia/Oceania	AU	Australia	25 750 285	910	0.035‰
108	Africa	GW	Guinea-Bissau	2 007 194	67	0.033‰
109	Africa	ET	Ethiopia	117 362 028	3 840	0.033‰
110	North America	NI	Nicaragua	6 691 251	183	0.027‰
111	Africa	CG	Congo	5 632 490	148	0.026‰
112	Africa	MZ	Mozambique	31 992 056	820	0.026‰
113	Africa	RW	Rwanda	13 222 636	338	0.026‰
114	Africa	GH	Ghana	31 620 038	783	0.025‰
115	Africa	MG	Madagascar	28 290 383	701	0.025‰
116	Africa	ML	Mali	20 741 348	497	0.024‰
117	North America	HT	Haiti	11 520 146	263	0.023‰
118	Asia	UZ	Uzbekistan	33 879 305	662	0.020‰
119	Africa	CF	Central African R.	4 900 689	93	0.019‰
120	Africa	AO	Angola	33 725 272	628	0.019‰
121	Africa	LR	Liberia	5 157 851	85	0.017‰
122	Africa	TG	Togo	8 442 228	124	0.015‰
123	Australia/Oceania	PG	Papua New Guinea	9 090 082	121	0.013‰
124	Africa	GN	Guinea	13 432 554	149	0.011‰
125	Africa	CI	Ivory Coast	26 928 434	291	0.011‰
126	Africa	SS	South Sudan	11 304 789	116	0.010‰
127	Africa	TD	Chad	16 822 255	170	0.010‰
128	Africa	NG	Nigeria	210 442 777	2 065	0.010‰
129	Africa	SL	Sierra Leone	8 113 840	79	0.010‰
130	Asia	TJ	Tajikistan	9 718 231	90	0.009‰
131	Africa	CD	DR Congo	91 849 784	772	0.008‰
132	Africa	BJ	Benin	12 390 502	100	0.008‰
133	Africa	NE	Niger	24 941 425	192	0.008‰
134	Africa	BF	Burkina Faso	21 385 551	161	0.007‰
135	Africa	UG	Uganda	46 954 508	346	0.007‰
136	Asia	KH	Cambodia	16 914 637	114	0.007‰
137	Asia	TH	Thailand	69 948 647	382	0.005‰
138	Asia	SG	Singapore	5 889 331	31	0.005‰
139	Australia/Oceania	NZ	New Zealand	5 002 100	26	0.005‰
140	Africa	ER	Eritrea	3 587 929	12	0.003‰
141	Asia	PS	Palestine	5 201 353	12	0.002‰
142	Africa	BI	Burundi	12 188 489	6	0.001‰
143	Asia	TW	Taiwan	23 853 373	12	0.001‰
144	Asia	VN	Vietnam	98 080 462	35	0.000‰
145	Africa	TZ	Tanzania	61 165 222	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	7 364 820	0	0.000‰
150	Asia	HK	Hong Kong	7 548 518	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"