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": 2021-07-31 22:39
(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	+538 (+514)	+0 (+0)
CZ	Czechia	+140 (+207)	+0 (+0)
DE	Germany	+1 816 (+2 598)	+10 (+30)
HU	Hungary	+0 (+64)	+0 (+1)
PL	Poland	+153 (+153)	+2 (+2)
SK	Slovakia, [gov], [okr]	+66 (+44)	+4 (+0)

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

N.	Region	Population	Last 120 days	Last 30 days	Last 7 days
1	South America	437 834 662	3.22%	2.23%	1.45%
2	Europe	756 124 270	1.49%	1.65%	1.26%
3	North America	593 650 393	1.05%	1.18%	1.22%
4	Asia	4 670 998 850	0.70%	0.47%	0.44%
5	Australia/Oceania	43 338 238	0.10%	0.24%	0.23%
6	Africa	1 374 400 488	0.17%	0.31%	0.23%

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

N.	Region	Population	Mortality last 120 days	Mortality last 30 days	New positive cases last 30 days
1	South America	437 834 662	3.01%	3.87%	2.23%
2	Africa	1 374 400 488	2.39%	2.70%	0.31%
3	Asia	4 670 998 850	1.40%	2.18%	0.47%
4	North America	593 650 393	1.75%	1.36%	1.18%
5	Australia/Oceania	43 338 238	0.94%	1.14%	0.24%
6	Europe	756 124 270	1.69%	1.04%	1.65%

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	437 834 662	1 084 048	2.476‰
2	North America	593 650 393	915 143	1.542‰
3	Europe	756 124 270	1 131 121	1.496‰
4	Asia	4 670 998 850	880 746	0.189‰
5	Africa	1 374 400 488	167 611	0.122‰
6	Australia/Oceania	43 338 238	1 648	0.038‰

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	Africa	BW	Botswana	2 402 605	2.65%	5.34%	7.29%
2	North America	CU	Cuba	11 319 161	2.49%	5.90%	6.29%
3	Asia	GE	Georgia	3 980 909	3.30%	4.72%	5.74%
4	Asia	MY	Malaysia	32 811 983	2.18%	3.78%	4.25%
5	Asia	KZ	Kazakhstan	19 018 299	1.65%	2.77%	3.67%
6	Asia	MN	Mongolia	3 335 025	4.54%	5.39%	3.39%
7	Europe	ES	Spain	46 774 302	2.32%	4.90%	3.36%
8	Europe	GB	United Kingdom	68 270 129	2.09%	5.69%	3.36%
9	Africa	LY	Libya	6 971 764	1.19%	2.85%	3.35%
10	Asia	IR	Iran	85 149 163	2.21%	2.69%	2.67%
11	Africa	TN	Tunisia	11 951 687	2.74%	5.43%	2.65%
12	Asia	IL	Israel	9 326 000	0.42%	1.36%	2.61%
13	Europe	FR	France	65 429 176	2.18%	1.59%	2.33%
14	South America	AR	Argentina	45 642 150	5.53%	3.72%	2.26%
15	Europe	IE	Ireland	4 997 127	1.22%	1.97%	2.16%
16	Europe	GR	Greece	10 368 119	2.10%	2.41%	2.15%
17	Asia	IQ	Iraq	41 191 025	1.77%	2.34%	2.14%
18	Europe	PT	Portugal	10 164 639	1.35%	3.15%	2.11%
19	Europe	NL	Netherlands	17 175 733	3.35%	3.95%	2.07%
20	Asia	TH	Thailand	69 988 732	0.76%	1.70%	1.97%
21	Asia	OM	Oman	5 245 888	2.63%	2.51%	1.95%
22	Africa	NA	Namibia	2 590 333	2.83%	4.30%	1.84%
23	South America	BR	Brazil	214 186 368	3.27%	2.31%	1.80%
24	North America	CR	Costa Rica	5 144 185	3.60%	2.85%	1.78%
25	South America	CO	Colombia	51 466 439	4.55%	4.14%	1.77%
26	Asia	KW	Kuwait	4 338 465	3.73%	3.56%	1.77%
27	North America	PA	Panama	4 387 767	1.74%	2.62%	1.76%
28	Asia	TR	Turkey	85 315 528	2.70%	1.10%	1.72%
29	North America	US	USA	333 093 143	1.27%	1.32%	1.42%
30	Europe	RU	Russia	146 001 924	1.13%	1.87%	1.37%
31	Africa	ZA	South Africa	60 112 931	1.42%	2.86%	1.36%
32	Asia	AE	Arab Emirates	10 018 939	2.12%	1.73%	1.31%
33	North America	HN	Honduras	10 073 907	1.03%	1.23%	1.30%
34	Asia	KG	Kyrgyzstan	6 639 861	1.09%	2.08%	1.25%
35	Asia	ID	Indonesia	276 635 762	0.65%	1.62%	1.22%
36	Africa	MA	Morocco	37 381 174	0.27%	0.69%	1.21%
37	South America	PR	Puerto Rico	3 193 694	1.18%	0.55%	1.20%
38	Asia	LB	Lebanon	6 792 467	1.27%	0.78%	1.14%
39	North America	GT	Guatemala	18 271 521	0.90%	1.42%	1.04%
40	Europe	DK	Denmark	5 814 180	1.42%	1.37%	1.02%
41	Africa	ZW	Zimbabwe	15 095 525	0.44%	1.42%	0.89%
42	North America	MX	Mexico	130 390 343	0.41%	0.80%	0.84%
43	Europe	FI	Finland	5 549 998	0.49%	0.67%	0.83%
44	Europe	LT	Lithuania	2 681 250	2.39%	0.48%	0.80%
45	Asia	MM	Myanmar	54 802 585	0.27%	0.95%	0.76%
46	Europe	BY	Belarus	9 445 972	1.27%	1.09%	0.75%
47	Asia	JO	Jordan	10 312 137	1.45%	0.64%	0.74%
48	Asia	BD	Bangladesh	166 455 064	0.36%	0.72%	0.69%
49	Europe	IT	Italy	60 365 948	1.20%	0.47%	0.68%
50	Europe	BE	Belgium	11 643 962	1.92%	1.11%	0.67%
51	Asia	NP	Nepal	29 699 747	1.39%	0.67%	0.67%
52	Asia	VN	Vietnam	98 281 263	0.12%	0.42%	0.60%
53	South America	PY	Paraguay	7 226 775	3.26%	1.59%	0.58%
54	Asia	LK	Sri Lanka	21 509 978	0.97%	0.76%	0.57%
55	Asia	AM	Armenia	2 969 212	1.17%	0.59%	0.57%
56	South America	BO	Bolivia	11 844 236	1.67%	1.10%	0.56%
57	South America	CL	Chile	19 292 837	3.16%	1.17%	0.52%
58	Asia	PH	Philippines	111 149 482	0.73%	0.57%	0.52%
59	Europe	SE	Sweden	10 167 084	3.00%	0.34%	0.49%
60	Africa	MR	Mauritania	4 780 681	0.14%	0.33%	0.48%
61	Europe	CH	Switzerland	8 722 770	1.26%	0.58%	0.47%
62	Asia	QA	Qatar	2 807 805	1.60%	0.51%	0.45%
63	Africa	MZ	Mozambique	32 193 807	0.15%	0.49%	0.44%
64	Africa	RW	Rwanda	13 296 547	0.33%	0.85%	0.43%
65	North America	SV	El Salvador	6 521 459	0.33%	0.43%	0.43%
66	Asia	JP	Japan	126 058 811	0.33%	0.30%	0.43%
67	South America	UY	Uruguay	3 486 702	7.89%	1.44%	0.42%
68	Europe	NO	Norway	5 466 879	0.74%	0.38%	0.40%
69	Africa	LS	Lesotho	2 160 532	0.10%	0.31%	0.39%
70	Asia	KH	Cambodia	16 967 753	0.43%	0.58%	0.38%
71	North America	JM	Jamaica	2 975 091	0.43%	0.30%	0.38%
72	Africa	GM	Gambia	2 489 421	0.09%	0.26%	0.38%
73	Africa	SN	Senegal	17 216 952	0.12%	0.38%	0.37%
74	Asia	AZ	Azerbaijan	10 237 543	0.76%	0.23%	0.36%
75	Europe	AT	Austria	9 061 746	1.17%	0.31%	0.36%
76	Europe	HR	Croatia	4 077 945	2.13%	0.32%	0.32%
77	South America	PE	Peru	33 465 698	1.66%	0.64%	0.32%
78	Europe	SI	Slovenia	2 079 246	1.96%	0.31%	0.31%
79	South America	VE	Venezuela	28 349 033	0.50%	0.43%	0.30%
80	Asia	SA	Saudi Arabia	35 396 603	0.37%	0.39%	0.30%
81	South America	EC	Ecuador	17 931 028	0.86%	0.56%	0.30%
82	Africa	ZM	Zambia	18 935 680	0.56%	0.82%	0.28%
83	Asia	LA	Laos	7 389 060	0.07%	0.18%	0.28%
84	Africa	DZ	Algeria	44 701 619	0.11%	0.24%	0.27%
85	Africa	MW	Malawi	19 659 952	0.09%	0.29%	0.27%
86	Asia	KR	South Korea	51 316 749	0.18%	0.29%	0.25%
87	Europe	RS	Serbia	8 699 402	1.33%	0.20%	0.25%
88	North America	DO	Dominican R.	10 964 974	0.80%	0.57%	0.25%
89	Asia	IN	India	1 394 605 426	1.38%	0.32%	0.24%
90	Europe	BG	Bulgaria	6 891 984	1.13%	0.15%	0.21%
91	Europe	MD	Moldova	4 023 851	0.68%	0.22%	0.21%
92	Asia	UZ	Uzbekistan	33 990 675	0.13%	0.19%	0.20%
93	Asia	SG	Singapore	5 899 877	0.07%	0.14%	0.19%
94	Europe	DE	Germany	84 072 622	1.08%	0.16%	0.17%
95	Africa	GW	Guinea-Bissau	2 017 898	0.03%	0.10%	0.17%
96	Europe	MK	North Macedonia	2 083 282	1.19%	0.10%	0.15%
97	Africa	GH	Ghana	31 769 201	0.04%	0.09%	0.15%
98	Africa	KE	Kenya	55 042 384	0.12%	0.12%	0.13%
99	Europe	CZ	Czechia	10 730 394	1.18%	0.21%	0.13%
100	Asia	PK	Pakistan	225 498 161	0.15%	0.11%	0.13%
101	North America	CA	Canada	38 098 354	1.17%	0.14%	0.12%
102	Europe	UA	Ukraine	43 450 212	1.24%	0.14%	0.11%
103	Asia	AF	Afghanistan	39 869 084	0.22%	0.26%	0.09%
104	Africa	BI	Burundi	12 270 120	0.03%	0.05%	0.09%
105	Africa	TG	Togo	8 486 878	0.06%	0.07%	0.09%
106	Europe	AL	Albania	2 874 408	0.26%	0.06%	0.08%
107	Europe	SK	Slovakia	5 462 493	0.53%	0.07%	0.08%
108	Europe	BA	Bosnia and Herzegovina	3 258 795	1.05%	0.07%	0.08%
109	North America	NI	Nicaragua	6 709 335	0.03%	0.07%	0.07%
110	Europe	RO	Romania	19 099 182	0.65%	0.04%	0.06%
111	Australia/Oceania	AU	Australia	25 818 165	0.02%	0.04%	0.06%
112	Europe	HU	Hungary	9 633 893	1.44%	0.05%	0.06%
113	Africa	UG	Uganda	47 287 644	0.11%	0.11%	0.05%
114	Asia	PS	Palestine	5 228 642	0.00%	0.01%	0.04%
115	Africa	CM	Cameroon	27 254 503	0.13%	0.02%	0.04%
116	Africa	GN	Guinea	13 514 607	0.04%	0.04%	0.04%
117	Africa	GA	Gabon	2 282 073	0.25%	0.07%	0.04%
118	Australia/Oceania	PG	Papua New Guinea	9 129 039	0.12%	0.02%	0.03%
119	Africa	AO	Angola	33 961 015	0.06%	0.04%	0.03%
120	Africa	CG	Congo	5 663 755	0.06%	0.05%	0.03%
121	Africa	CD	DR Congo	92 477 515	0.02%	0.04%	0.03%
122	Europe	PL	Poland	37 801 912	1.31%	0.03%	0.03%
123	Africa	SS	South Sudan	11 334 900	0.01%	0.01%	0.02%
124	Africa	CI	Ivory Coast	27 078 801	0.02%	0.02%	0.02%
125	North America	HT	Haiti	11 552 042	0.06%	0.05%	0.02%
126	Africa	ET	Ethiopia	118 017 563	0.06%	0.01%	0.02%
127	Africa	ER	Eritrea	3 599 197	0.09%	0.06%	0.01%
128	Asia	TJ	Tajikistan	9 767 516	0.00%	0.00%	0.01%
129	Africa	NG	Nigeria	211 618 923	0.00%	0.01%	0.01%
130	Africa	SO	Somalia	16 368 393	0.03%	0.01%	0.01%
131	Africa	SL	Sierra Leone	8 151 140	0.03%	0.03%	0.01%
132	Africa	BJ	Benin	12 463 627	0.01%	0.00%	0.01%
133	Asia	TW	Taiwan	23 863 237	0.06%	0.01%	0.01%
134	Asia	SY	Syria	17 956 644	0.04%	0.01%	0.01%
135	Africa	LR	Liberia	5 185 207	0.06%	0.13%	0.00%
136	Africa	TZ	Tanzania	61 557 275	0.00%	0.00%	0.00%
137	Africa	EG	Egypt	104 407 309	0.08%	0.01%	0.00%
138	Africa	MG	Madagascar	28 454 297	0.07%	0.01%	0.00%
139	Asia	YE	Yemen	30 530 919	0.01%	0.00%	0.00%
140	Africa	BF	Burkina Faso	21 517 590	0.00%	0.00%	0.00%
141	Australia/Oceania	NZ	New Zealand	5 002 100	0.01%	0.01%	0.00%
142	Africa	NE	Niger	25 143 758	0.00%	0.00%	0.00%
143	Asia	HK	Hong Kong	7 562 460	0.01%	0.00%	0.00%
144	Africa	ML	Mali	20 875 763	0.02%	0.00%	0.00%
145	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
146	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
147	Africa	TD	Chad	16 930 869	0.00%	0.00%	0.00%
148	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
149	Africa	CF	Central African R.	4 919 984	0.04%	0.00%	0.00%
150	Africa	SD	Sudan	44 947 622	0.01%	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	South America	EC	Ecuador	17 931 028	9.00%	31.34%	0.56%
2	Asia	YE	Yemen	30 530 919	14.67%	(12.38)%	(0.00)%
3	Asia	TW	Taiwan	23 863 237	5.34%	(10.78)%	(0.01)%
4	Africa	UG	Uganda	47 287 644	4.48%	9.15%	0.11%
5	Europe	BA	Bosnia and Herzegovina	3 258 795	6.70%	(7.84)%	(0.07)%
6	Africa	MG	Madagascar	28 454 297	2.75%	(7.83)%	(0.01)%
7	Europe	PL	Poland	37 801 912	3.05%	(7.69)%	(0.03)%
8	Africa	SO	Somalia	16 368 393	5.82%	(7.42)%	(0.01)%
9	Europe	BG	Bulgaria	6 891 984	4.78%	6.48%	0.15%
10	Africa	EG	Egypt	104 407 309	5.19%	(6.42)%	(0.01)%
11	North America	JM	Jamaica	2 975 091	4.00%	5.66%	0.30%
12	South America	PE	Peru	33 465 698	8.64%	5.64%	0.64%
13	Asia	SY	Syria	17 956 644	8.14%	(5.57)%	(0.01)%
14	South America	PY	Paraguay	7 226 775	4.27%	5.19%	1.59%
15	North America	HT	Haiti	11 552 042	4.02%	(4.89)%	(0.05)%
16	Asia	AF	Afghanistan	39 869 084	4.70%	4.81%	0.26%
17	Asia	MM	Myanmar	54 802 585	4.42%	4.62%	0.95%
18	Africa	ML	Mali	20 875 763	2.97%	(4.26)%	(0.00)%
19	Australia/Oceania	PG	Papua New Guinea	9 129 039	1.05%	(4.23)%	(0.02)%
20	Europe	RO	Romania	19 099 182	4.28%	(3.71)%	(0.04)%
21	Africa	NA	Namibia	2 590 333	3.32%	3.70%	4.30%
22	South America	CL	Chile	19 292 837	1.83%	3.45%	1.17%
23	Africa	SD	Sudan	44 947 622	12.34%	(3.34)%	(0.00)%
24	Europe	SK	Slovakia	5 462 493	7.22%	(3.19)%	(0.07)%
25	North America	SV	El Salvador	6 521 459	2.84%	3.18%	0.43%
26	Europe	UA	Ukraine	43 450 212	3.04%	3.17%	0.14%
27	Africa	MW	Malawi	19 659 952	3.23%	3.05%	0.29%
28	Africa	ZW	Zimbabwe	15 095 525	3.10%	2.99%	1.42%
29	Europe	RU	Russia	146 001 924	3.58%	2.95%	1.87%
30	Asia	ID	Indonesia	276 635 762	3.01%	2.93%	1.62%
31	Africa	BJ	Benin	12 463 627	1.19%	(2.88)%	(0.00)%
32	Africa	GN	Guinea	13 514 607	1.43%	(2.85)%	(0.04)%
33	Asia	KH	Cambodia	16 967 753	1.92%	2.80%	0.58%
34	Africa	GM	Gambia	2 489 421	2.52%	2.78%	0.26%
35	North America	MX	Mexico	130 390 343	7.15%	2.75%	0.80%
36	Africa	AO	Angola	33 961 015	2.34%	(2.73)%	(0.04)%
37	Europe	HU	Hungary	9 633 893	4.51%	(2.70)%	(0.05)%
38	Africa	LS	Lesotho	2 160 532	2.58%	2.63%	0.31%
39	Africa	TN	Tunisia	11 951 687	3.28%	2.46%	5.43%
40	Europe	MD	Moldova	4 023 851	3.42%	2.45%	0.22%
41	Asia	LK	Sri Lanka	21 509 978	1.78%	2.42%	0.76%
42	South America	BR	Brazil	214 186 368	3.15%	2.41%	2.31%
43	South America	BO	Bolivia	11 844 236	2.73%	2.39%	1.10%
44	North America	HN	Honduras	10 073 907	3.07%	2.35%	1.23%
45	Europe	DE	Germany	84 072 622	1.45%	2.22%	0.16%
46	South America	AR	Argentina	45 642 150	1.92%	2.12%	3.72%
47	Africa	ZM	Zambia	18 935 680	2.05%	2.11%	0.82%
48	Asia	AM	Armenia	2 969 212	2.62%	2.10%	0.59%
49	Africa	ET	Ethiopia	118 017 563	1.78%	(2.05)%	(0.01)%
50	Africa	ZA	South Africa	60 112 931	2.19%	2.04%	2.86%
51	Asia	OM	Oman	5 245 888	1.55%	2.00%	2.51%
52	Asia	BD	Bangladesh	166 455 064	1.96%	1.99%	0.72%
53	Africa	MR	Mauritania	4 780 681	1.73%	1.96%	0.33%
54	South America	CO	Colombia	51 466 439	2.40%	1.95%	4.14%
55	Africa	GW	Guinea-Bissau	2 017 898	2.22%	1.94%	0.10%
56	North America	CA	Canada	38 098 354	0.75%	1.92%	0.14%
57	Africa	SS	South Sudan	11 334 900	0.81%	1.90%	0.01%
58	Africa	DZ	Algeria	44 701 619	2.43%	1.89%	0.24%
59	Europe	MK	North Macedonia	2 083 282	5.17%	1.88%	0.10%
60	Asia	IN	India	1 394 605 426	1.33%	1.85%	0.32%
61	South America	UY	Uruguay	3 486 702	1.70%	1.79%	1.44%
62	Asia	PK	Pakistan	225 498 161	2.40%	1.77%	0.11%
63	Europe	RS	Serbia	8 699 402	1.19%	1.73%	0.20%
64	Africa	TG	Togo	8 486 878	0.75%	1.72%	0.07%
65	Asia	PH	Philippines	111 149 482	1.68%	1.71%	0.57%
66	Africa	SL	Sierra Leone	8 151 140	1.78%	1.65%	0.03%
67	Africa	KE	Kenya	55 042 384	2.47%	1.64%	0.12%
68	Africa	NE	Niger	25 143 758	1.25%	1.64%	0.00%
69	Africa	CG	Congo	5 663 755	1.20%	1.60%	0.05%
70	Asia	JO	Jordan	10 312 137	1.59%	1.57%	0.64%
71	Africa	BF	Burkina Faso	21 517 590	2.18%	1.56%	0.00%
72	North America	GT	Guatemala	18 271 521	2.16%	1.55%	1.42%
73	Africa	BW	Botswana	2 402 605	1.80%	1.50%	5.34%
74	Europe	HR	Croatia	4 077 945	2.30%	1.45%	0.32%
75	Africa	MZ	Mozambique	32 193 807	1.46%	1.44%	0.49%
76	Asia	HK	Hong Kong	7 562 460	1.31%	1.43%	0.00%
77	Africa	GA	Gabon	2 282 073	0.67%	1.42%	0.07%
78	Asia	NP	Nepal	29 699 747	1.69%	1.35%	0.67%
79	Europe	LT	Lithuania	2 681 250	1.20%	1.33%	0.48%
80	Asia	KZ	Kazakhstan	19 018 299	1.12%	1.29%	2.77%
81	Africa	CD	DR Congo	92 477 515	1.49%	1.29%	0.04%
82	South America	VE	Venezuela	28 349 033	1.34%	1.27%	0.43%
83	Asia	MY	Malaysia	32 811 983	1.14%	1.26%	3.78%
84	Africa	ER	Eritrea	3 599 197	0.73%	1.24%	0.06%
85	Africa	RW	Rwanda	13 296 547	1.15%	1.22%	0.85%
86	Africa	LR	Liberia	5 185 207	1.88%	1.17%	0.13%
87	Africa	SN	Senegal	17 216 952	1.51%	1.16%	0.38%
88	Asia	GE	Georgia	3 980 909	1.63%	1.15%	4.72%
89	Asia	IR	Iran	85 149 163	1.49%	1.06%	2.69%
90	Africa	CI	Ivory Coast	27 078 801	1.09%	1.06%	0.02%
91	Europe	BY	Belarus	9 445 972	0.94%	1.06%	1.09%
92	Africa	CM	Cameroon	27 254 503	1.44%	1.02%	0.02%
93	Asia	SA	Saudi Arabia	35 396 603	1.18%	1.01%	0.39%
94	Asia	TH	Thailand	69 988 732	0.99%	1.00%	1.70%
95	South America	PR	Puerto Rico	3 193 694	1.22%	0.97%	0.55%
96	Asia	AZ	Azerbaijan	10 237 543	1.60%	0.95%	0.23%
97	Africa	MA	Morocco	37 381 174	1.13%	0.94%	0.69%
98	North America	CU	Cuba	11 319 161	0.86%	0.89%	5.90%
99	Europe	IT	Italy	60 365 948	2.15%	0.85%	0.47%
100	North America	CR	Costa Rica	5 144 185	1.11%	0.81%	2.85%
101	North America	US	USA	333 093 143	1.28%	0.77%	1.32%
102	North America	PA	Panama	4 387 767	0.89%	0.77%	2.62%
103	Asia	KG	Kyrgyzstan	6 639 861	1.17%	0.77%	2.08%
104	Asia	UZ	Uzbekistan	33 990 675	0.56%	0.76%	0.19%
105	Asia	TR	Turkey	85 315 528	0.79%	0.74%	1.10%
106	Asia	KW	Kuwait	4 338 465	0.59%	0.73%	3.56%
107	Africa	LY	Libya	6 971 764	1.05%	0.71%	2.85%
108	Africa	NG	Nigeria	211 618 923	0.99%	0.67%	0.01%
109	North America	DO	Dominican R.	10 964 974	0.70%	0.65%	0.57%
110	Europe	CZ	Czechia	10 730 394	1.89%	0.63%	0.21%
111	Europe	SI	Slovenia	2 079 246	0.77%	0.62%	0.31%
112	Asia	VN	Vietnam	98 281 263	0.58%	0.60%	0.42%
113	Africa	GH	Ghana	31 769 201	0.83%	0.58%	0.09%
114	Asia	IQ	Iraq	41 191 025	0.57%	0.56%	2.34%
115	Asia	JP	Japan	126 058 811	1.50%	0.52%	0.30%
116	Australia/Oceania	AU	Australia	25 818 165	0.36%	0.50%	0.04%
117	Asia	LB	Lebanon	6 792 467	1.59%	0.48%	0.78%
118	North America	NI	Nicaragua	6 709 335	0.87%	0.47%	0.07%
119	Asia	MN	Mongolia	3 335 025	0.53%	0.43%	5.39%
120	Europe	GR	Greece	10 368 119	2.13%	0.42%	2.41%
121	Europe	AT	Austria	9 061 746	0.96%	0.38%	0.31%
122	Europe	FR	France	65 429 176	0.97%	0.31%	1.59%
123	Europe	PT	Portugal	10 164 639	0.36%	0.29%	3.15%
124	Asia	QA	Qatar	2 807 805	0.62%	0.27%	0.51%
125	Asia	AE	Arab Emirates	10 018 939	0.20%	0.25%	1.73%
126	Asia	IL	Israel	9 326 000	0.83%	0.22%	1.36%
127	Asia	KR	South Korea	51 316 749	0.41%	0.20%	0.29%
128	Europe	BE	Belgium	11 643 962	0.85%	0.18%	1.11%
129	Europe	SE	Sweden	10 167 084	0.32%	0.15%	0.34%
130	Europe	IE	Ireland	4 997 127	0.53%	0.13%	1.97%
131	Asia	LA	Laos	7 389 060	0.14%	0.13%	0.18%
132	Europe	GB	United Kingdom	68 270 129	0.20%	0.13%	5.69%
133	Africa	BI	Burundi	12 270 120	0.08%	0.11%	0.05%
134	Europe	NO	Norway	5 466 879	0.28%	0.09%	0.38%
135	Europe	CH	Switzerland	8 722 770	0.38%	0.09%	0.58%
136	Europe	ES	Spain	46 774 302	0.42%	0.07%	4.90%
137	Europe	DK	Denmark	5 814 180	0.15%	0.07%	1.37%
138	Asia	SG	Singapore	5 899 877	0.19%	0.07%	0.14%
139	Europe	FI	Finland	5 549 998	0.47%	0.06%	0.67%
140	Europe	NL	Netherlands	17 175 733	0.21%	0.04%	3.95%
141	Europe	AL	Albania	2 874 408	2.14%	0.00%	0.06%
142	Australia/Oceania	NZ	New Zealand	5 002 100	0.00%	0.00%	0.01%
143	Africa	TD	Chad	16 930 869	1.99%	0.00%	0.00%
144	Africa	CF	Central African R.	4 919 984	1.50%	0.00%	0.00%
145	Asia	PS	Palestine	5 228 642	0.00%	0.00%	0.01%
146	Asia	TJ	Tajikistan	9 767 516	0.00%	0.00%	0.00%
147	Africa	TZ	Tanzania	61 557 275	0.00%	0.00%	0.00%
148	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
149	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
150	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%

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

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

N.	Region	CD	Country	Population	Deaths	*1000Deaths/Pop.**
1	South America	PE	Peru	33 465 698	196 050	5.858‰
2	Europe	HU	Hungary	9 633 893	30 026	3.117‰
3	Europe	BA	Bosnia and Herzegovina	3 258 795	9 687	2.973‰
4	Europe	CZ	Czechia	10 730 394	30 362	2.829‰
5	Europe	BG	Bulgaria	6 891 984	18 206	2.642‰
6	Europe	MK	North Macedonia	2 083 282	5 491	2.636‰
7	South America	BR	Brazil	214 186 368	551 388	2.574‰
8	South America	CO	Colombia	51 466 439	119 488	2.322‰
9	Europe	SK	Slovakia	5 462 493	12 538	2.295‰
10	South America	AR	Argentina	45 642 150	104 578	2.291‰
11	Europe	SI	Slovenia	2 079 246	4 762	2.290‰
12	Europe	BE	Belgium	11 643 962	25 236	2.167‰
13	Europe	IT	Italy	60 365 948	128 011	2.121‰
14	South America	PY	Paraguay	7 226 775	14 754	2.042‰
15	Europe	HR	Croatia	4 077 945	8 254	2.024‰
16	Europe	PL	Poland	37 801 912	75 254	1.991‰
17	Europe	GB	United Kingdom	68 270 129	129 374	1.895‰
18	North America	MX	Mexico	130 390 343	239 054	1.833‰
19	South America	CL	Chile	19 292 837	35 233	1.826‰
20	North America	US	USA	333 093 143	606 475	1.821‰
21	Europe	RO	Romania	19 099 182	34 277	1.795‰
22	South America	EC	Ecuador	17 931 028	31 468	1.755‰
23	Europe	ES	Spain	46 774 302	81 367	1.740‰
24	Europe	PT	Portugal	10 164 639	17 324	1.704‰
25	South America	UY	Uruguay	3 486 702	5 942	1.704‰
26	Europe	FR	France	65 429 176	110 725	1.692‰
27	Europe	LT	Lithuania	2 681 250	4 413	1.646‰
28	Africa	TN	Tunisia	11 951 687	19 210	1.607‰
29	Europe	MD	Moldova	4 023 851	6 247	1.552‰
30	Asia	AM	Armenia	2 969 212	4 603	1.550‰
31	North America	PA	Panama	4 387 767	6 778	1.545‰
32	South America	BO	Bolivia	11 844 236	17 702	1.495‰
33	Asia	GE	Georgia	3 980 909	5 778	1.451‰
34	Europe	SE	Sweden	10 167 084	14 655	1.441‰
35	Europe	GR	Greece	10 368 119	12 928	1.247‰
36	Europe	UA	Ukraine	43 450 212	52 906	1.218‰
37	Europe	CH	Switzerland	8 722 770	10 334	1.185‰
38	Africa	ZA	South Africa	60 112 931	70 722	1.177‰
39	Asia	LB	Lebanon	6 792 467	7 898	1.163‰
40	Europe	AT	Austria	9 061 746	10 531	1.162‰
41	Africa	NA	Namibia	2 590 333	2 916	1.126‰
42	Europe	DE	Germany	84 072 622	91 596	1.089‰
43	Europe	RU	Russia	146 001 924	156 970	1.075‰
44	Asia	IR	Iran	85 149 163	89 765	1.054‰
45	Europe	NL	Netherlands	17 175 733	17 810	1.037‰
46	Europe	IE	Ireland	4 997 127	5 026	1.006‰
47	North America	CR	Costa Rica	5 144 185	4 998	0.972‰
48	Asia	JO	Jordan	10 312 137	9 991	0.969‰
49	Europe	AL	Albania	2 874 408	2 456	0.854‰
50	Europe	RS	Serbia	8 699 402	7 110	0.817‰
51	South America	PR	Puerto Rico	3 193 694	2 569	0.804‰
52	North America	HN	Honduras	10 073 907	7 691	0.763‰
53	Asia	OM	Oman	5 245 888	3 788	0.722‰
54	North America	CA	Canada	38 098 354	26 559	0.697‰
55	Asia	IL	Israel	9 326 000	6 473	0.694‰
56	Africa	BW	Botswana	2 402 605	1 485	0.618‰
57	Asia	TR	Turkey	85 315 528	51 127	0.599‰
58	North America	GT	Guatemala	18 271 521	10 217	0.559‰
59	Asia	KW	Kuwait	4 338 465	2 304	0.531‰
60	Africa	LY	Libya	6 971 764	3 462	0.497‰
61	Asia	AZ	Azerbaijan	10 237 543	5 012	0.490‰
62	Asia	KZ	Kazakhstan	19 018 299	9 077	0.477‰
63	Asia	IQ	Iraq	41 191 025	18 480	0.449‰
64	Europe	DK	Denmark	5 814 180	2 547	0.438‰
65	North America	SV	El Salvador	6 521 459	2 593	0.398‰
66	North America	JM	Jamaica	2 975 091	1 182	0.397‰
67	Europe	BY	Belarus	9 445 972	3 422	0.362‰
68	North America	DO	Dominican R.	10 964 974	3 952	0.360‰
69	Asia	KG	Kyrgyzstan	6 639 861	2 302	0.347‰
70	Asia	NP	Nepal	29 699 747	9 814	0.330‰
71	Asia	ID	Indonesia	276 635 762	90 467	0.327‰
72	Asia	IN	India	1 394 605 426	422 564	0.303‰
73	Asia	MY	Malaysia	32 811 983	8 569	0.261‰
74	Africa	MA	Morocco	37 381 174	9 691	0.259‰
75	Asia	PH	Philippines	111 149 482	27 485	0.247‰
76	Asia	MN	Mongolia	3 335 025	795	0.238‰
77	Asia	SA	Saudi Arabia	35 396 603	8 200	0.232‰
78	North America	CU	Cuba	11 319 161	2 557	0.226‰
79	Africa	ZW	Zimbabwe	15 095 525	3 349	0.222‰
80	Asia	QA	Qatar	2 807 805	600	0.214‰
81	Asia	LK	Sri Lanka	21 509 978	4 194	0.195‰
82	Asia	AE	Arab Emirates	10 018 939	1 935	0.193‰
83	Europe	FI	Finland	5 549 998	978	0.176‰
84	Africa	ZM	Zambia	18 935 680	3 329	0.176‰
85	Africa	LS	Lesotho	2 160 532	363	0.168‰
86	Asia	AF	Afghanistan	39 869 084	6 605	0.166‰
87	Africa	EG	Egypt	104 407 309	16 502	0.158‰
88	Asia	MM	Myanmar	54 802 585	8 602	0.157‰
89	Europe	NO	Norway	5 466 879	799	0.146‰
90	South America	VE	Venezuela	28 349 033	3 527	0.124‰
91	Asia	BD	Bangladesh	166 455 064	20 234	0.122‰
92	Asia	JP	Japan	126 058 811	15 162	0.120‰
93	Africa	MR	Mauritania	4 780 681	547	0.114‰
94	Asia	SY	Syria	17 956 644	1 910	0.106‰
95	Asia	PK	Pakistan	225 498 161	23 152	0.103‰
96	Africa	DZ	Algeria	44 701 619	4 142	0.093‰
97	Africa	GM	Gambia	2 489 421	212	0.085‰
98	Africa	MW	Malawi	19 659 952	1 566	0.080‰
99	Asia	KH	Cambodia	16 967 753	1 346	0.079‰
100	Africa	SN	Senegal	17 216 952	1 320	0.077‰
101	Africa	GA	Gabon	2 282 073	164	0.072‰
102	Africa	KE	Kenya	55 042 384	3 887	0.071‰
103	Asia	TH	Thailand	69 988 732	4 575	0.065‰
104	Africa	SD	Sudan	44 947 622	2 776	0.062‰
105	Africa	RW	Rwanda	13 296 547	782	0.059‰
106	Africa	UG	Uganda	47 287 644	2 619	0.055‰
107	Africa	CM	Cameroon	27 254 503	1 334	0.049‰
108	Africa	SO	Somalia	16 368 393	798	0.049‰
109	North America	HT	Haiti	11 552 042	540	0.047‰
110	Asia	YE	Yemen	30 530 919	1 374	0.045‰
111	Africa	MZ	Mozambique	32 193 807	1 368	0.043‰
112	Asia	KR	South Korea	51 316 749	2 089	0.041‰
113	Africa	GW	Guinea-Bissau	2 017 898	75	0.037‰
114	Africa	ET	Ethiopia	118 017 563	4 376	0.037‰
115	Australia/Oceania	AU	Australia	25 818 165	921	0.036‰
116	Africa	MG	Madagascar	28 454 297	945	0.033‰
117	Asia	TW	Taiwan	23 863 237	787	0.033‰
118	Africa	CG	Congo	5 663 755	177	0.031‰
119	Africa	AO	Angola	33 961 015	999	0.029‰
120	North America	NI	Nicaragua	6 709 335	195	0.029‰
121	Africa	LR	Liberia	5 185 207	148	0.029‰
122	Asia	HK	Hong Kong	7 562 460	212	0.028‰
123	Africa	GH	Ghana	31 769 201	823	0.026‰
124	Africa	ML	Mali	20 875 763	531	0.025‰
125	Asia	UZ	Uzbekistan	33 990 675	861	0.025‰
126	Australia/Oceania	PG	Papua New Guinea	9 129 039	192	0.021‰
127	Africa	CF	Central African R.	4 919 984	98	0.020‰
128	Africa	TG	Togo	8 486 878	150	0.018‰
129	Africa	GN	Guinea	13 514 607	208	0.015‰
130	Africa	SL	Sierra Leone	8 151 140	119	0.015‰
131	Africa	CI	Ivory Coast	27 078 801	328	0.012‰
132	Africa	CD	DR Congo	92 477 515	1 038	0.011‰
133	Africa	SS	South Sudan	11 334 900	119	0.011‰
134	Africa	TD	Chad	16 930 869	174	0.010‰
135	Africa	NG	Nigeria	211 618 923	2 142	0.010‰
136	Africa	ER	Eritrea	3 599 197	34	0.009‰
137	Africa	BJ	Benin	12 463 627	107	0.009‰
138	Africa	BF	Burkina Faso	21 517 590	169	0.008‰
139	Africa	NE	Niger	25 143 758	195	0.008‰
140	Asia	SG	Singapore	5 899 877	37	0.006‰
141	Asia	VN	Vietnam	98 281 263	524	0.005‰
142	Australia/Oceania	NZ	New Zealand	5 002 100	26	0.005‰
143	Asia	LA	Laos	7 389 060	6	0.001‰
144	Africa	BI	Burundi	12 270 120	9	0.001‰
145	Asia	PS	Palestine	5 228 642	2	0.000‰
146	Africa	TZ	Tanzania	61 557 275	21	0.000‰
147	Asia	CN	China	1 439 323 776	0	0.000‰
148	Asia	KP	North Korea	25 660 000	0	0.000‰
149	Asia	TJ	Tajikistan	9 767 516	0	0.000‰
150	Europe	TM	Turkmenistan	6 118 000	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]
Latest SPR Covid Updates

Az Európa Tanács (ET) a 2361 (2021) állásfoglalásban úgy határozott, hogy betiltja a tagállamok oltási kötelezettségeinek előírását.
EU-tagállamok kötelesek:
7.3.1 annak biztosítása, hogy az állampolgárok tájékoztatást kapjanak arról, hogy az oltás NEM kötelező, és hogy senkit sem politikai, társadalmi vagy egyéb módon nem kényszerítenek oltásra, hacsak nem akarják
7.3.2 annak biztosítása, hogy senkit ne érjen hátrányos megkülönböztetés, mert esetleges egészségügyi kockázatok miatt nem oltották be, vagy nem oltották be
7.1.5 független kompenzációs programok létrehozása az oltásokkal szemben az aránytalan és az oltásokkal okozott károk megtérítése érdekében

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"