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": 2021-06-12 21:11
(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	+200 (+216)	+0 (+2)
CZ	Czechia	+180 (+189)	+1 (+5)
DE	Germany	+679 (+2 194)	+31 (+115)
HU	Hungary	+0 (+199)	+0 (+8)
PL	Poland	+239 (+338)	+47 (+68)
SK	Slovakia, [gov], [okr]	+91 (+84)	+3 (+0)

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

N.	Region	Population	Last 120 days	Last 30 days	Last 7 days
1	South America	437 359 128	3.08%	3.62%	2.98%
2	Europe	756 064 321	2.01%	0.84%	0.53%
3	North America	593 032 781	1.29%	0.68%	0.41%
4	Asia	4 666 498 454	0.62%	0.67%	0.35%
5	Africa	1 370 091 267	0.09%	0.10%	0.11%
6	Australia/Oceania	43 270 874	0.05%	0.05%	0.04%

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	North America	593 032 781	2.29%	3.49%	0.68%
2	Africa	1 370 091 267	2.84%	(3.48)%	(0.10)%
3	South America	437 359 128	3.23%	3.38%	3.62%
4	Europe	756 064 321	2.01%	2.92%	0.84%
5	Asia	4 666 498 454	1.21%	2.07%	0.67%
6	Australia/Oceania	43 270 874	0.94%	(0.89)%	(0.05)%

COVID-19, Total Mortality from population of Regions

N.	Region	Population	Deaths	*1000Deaths/Pop.**
1	South America	437 359 128	931 035	2.129‰
2	North America	593 032 781	884 083	1.491‰
3	Europe	756 064 321	1 083 973	1.434‰
4	Asia	4 666 498 454	722 534	0.155‰
5	Africa	1 370 091 267	134 137	0.098‰
6	Australia/Oceania	43 270 874	1 392	0.032‰

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	3 485 094	8.02%	11.54%	10.83%
2	South America	AR	Argentina	45 586 681	4.46%	7.41%	5.69%
3	South America	CO	Colombia	51 393 873	2.86%	4.74%	5.11%
4	Asia	MN	Mongolia	3 327 951	2.06%	2.93%	4.24%
5	South America	PY	Paraguay	7 215 047	3.34%	4.42%	4.07%
6	South America	CL	Chile	19 270 893	3.58%	4.00%	3.74%
7	Asia	KW	Kuwait	4 330 005	3.42%	3.24%	3.46%
8	North America	CR	Costa Rica	5 137 964	2.67%	4.82%	3.30%
9	Asia	OM	Oman	5 228 445	1.77%	2.02%	2.97%
10	Africa	NA	Namibia	2 584 165	1.02%	1.74%	2.78%
11	South America	BR	Brazil	213 984 390	3.49%	3.44%	2.56%
12	South America	BO	Bolivia	11 822 915	1.38%	2.49%	2.29%
13	Africa	BW	Botswana	2 396 237	1.51%	1.94%	2.24%
14	Asia	AE	Arab Emirates	10 002 945	2.52%	2.04%	2.15%
15	Asia	MY	Malaysia	32 756 466	1.17%	2.28%	1.91%
16	Asia	GE	Georgia	3 981 930	2.21%	2.64%	1.79%
17	North America	PA	Panama	4 378 667	1.26%	1.49%	1.74%
18	Africa	TN	Tunisia	11 935 141	1.19%	1.29%	1.46%
19	Asia	LK	Sri Lanka	21 497 986	0.66%	1.55%	1.31%
20	Asia	NP	Nepal	29 629 496	1.11%	2.41%	1.14%
21	South America	PE	Peru	33 404 191	2.36%	1.59%	1.13%
22	North America	DO	Dominican R.	10 950 421	0.72%	1.17%	1.12%
23	North America	CU	Cuba	11 320 084	1.04%	1.22%	1.07%
24	Europe	DK	Denmark	5 811 456	1.49%	1.82%	1.07%
25	Europe	SE	Sweden	10 158 668	4.78%	2.48%	1.03%
26	Africa	ZA	South Africa	60 012 828	0.39%	0.79%	1.00%
27	Asia	IQ	Iraq	41 069 893	1.47%	1.11%	0.97%
28	Europe	NL	Netherlands	17 170 672	3.80%	2.13%	0.96%
29	Europe	GB	United Kingdom	68 222 484	0.78%	0.60%	0.94%
30	Asia	IR	Iran	85 005 237	1.77%	1.37%	0.88%
31	Europe	SI	Slovenia	2 079 208	3.80%	1.65%	0.87%
32	Europe	GR	Greece	10 374 902	2.35%	1.68%	0.87%
33	Europe	BY	Belarus	9 446 386	1.47%	1.33%	0.85%
34	Europe	RU	Russia	145 993 575	0.78%	0.73%	0.75%
35	Asia	TR	Turkey	85 194 096	3.23%	1.13%	0.73%
36	Europe	LT	Lithuania	2 686 296	3.21%	2.24%	0.71%
37	Africa	ZM	Zambia	18 866 484	0.21%	0.29%	0.70%
38	Asia	KG	Kyrgyzstan	6 625 437	0.36%	0.58%	0.69%
39	Europe	FR	France	65 409 895	3.52%	1.47%	0.68%
40	Asia	IN	India	1 392 790 451	1.32%	1.59%	0.68%
41	Europe	ES	Spain	46 771 885	1.50%	1.04%	0.67%
42	Europe	PT	Portugal	10 168 602	0.76%	0.58%	0.65%
43	North America	HN	Honduras	10 052 801	0.86%	0.88%	0.65%
44	Asia	QA	Qatar	2 807 805	2.26%	1.02%	0.62%
45	Asia	KZ	Kazakhstan	18 988 238	1.09%	1.10%	0.61%
46	Asia	PH	Philippines	110 954 199	0.68%	0.63%	0.60%
47	Europe	BE	Belgium	11 637 225	2.90%	1.59%	0.54%
48	North America	GT	Guatemala	18 227 090	0.55%	0.61%	0.54%
49	Europe	IE	Ireland	4 989 746	1.17%	0.90%	0.53%
50	South America	VE	Venezuela	28 359 773	0.40%	0.51%	0.50%
51	Asia	JO	Jordan	10 298 587	3.88%	0.76%	0.50%
52	South America	EC	Ecuador	17 895 139	0.96%	0.68%	0.40%
53	Europe	NO	Norway	5 461 212	1.13%	0.73%	0.40%
54	Asia	AF	Afghanistan	39 751 424	0.08%	0.24%	0.39%
55	Asia	TH	Thailand	69 965 349	0.24%	0.55%	0.39%
56	North America	US	USA	332 833 770	1.78%	0.74%	0.39%
57	North America	CA	Canada	38 054 099	1.53%	1.01%	0.39%
58	Africa	LY	Libya	6 959 252	0.89%	0.44%	0.39%
59	Asia	KH	Cambodia	16 936 769	0.21%	0.37%	0.39%
60	Europe	CH	Switzerland	8 714 309	1.81%	0.94%	0.34%
61	Europe	IT	Italy	60 377 804	2.58%	0.72%	0.33%
62	Asia	SA	Saudi Arabia	35 323 967	0.26%	0.37%	0.33%
63	Europe	AT	Austria	9 054 880	2.41%	0.62%	0.33%
64	Europe	HR	Croatia	4 081 316	2.97%	0.98%	0.33%
65	Europe	UA	Ukraine	43 485 203	2.20%	0.78%	0.30%
66	Asia	ID	Indonesia	276 248 772	0.25%	0.23%	0.25%
67	Europe	DE	Germany	84 036 849	1.65%	0.69%	0.24%
68	Europe	CZ	Czechia	10 727 742	5.51%	0.55%	0.23%
69	Asia	AM	Armenia	2 968 473	1.84%	0.45%	0.23%
70	Asia	LB	Lebanon	6 796 539	3.10%	0.46%	0.23%
71	Africa	UG	Uganda	47 093 315	0.04%	0.13%	0.23%
72	North America	SV	El Salvador	6 517 087	0.28%	0.28%	0.22%
73	South America	PR	Puerto Rico	3 193 694	1.34%	0.45%	0.20%
74	Europe	BG	Bulgaria	6 898 946	2.78%	0.42%	0.19%
75	North America	MX	Mexico	130 209 100	0.37%	0.22%	0.19%
76	Europe	RS	Serbia	8 704 091	3.43%	0.50%	0.19%
77	North America	JM	Jamaica	2 973 365	1.04%	0.30%	0.19%
78	Europe	FI	Finland	5 548 849	0.80%	0.31%	0.18%
79	Europe	SK	Slovakia	5 462 140	2.19%	0.30%	0.18%
80	Africa	ER	Eritrea	3 592 624	0.07%	0.11%	0.16%
81	Asia	JP	Japan	126 110 418	0.28%	0.35%	0.16%
82	Asia	TW	Taiwan	23 857 483	0.05%	0.19%	0.13%
83	Europe	HU	Hungary	9 637 163	4.39%	0.47%	0.13%
84	Europe	BA	Bosnia and Herzegovina	3 261 513	2.44%	0.34%	0.13%
85	Asia	BD	Bangladesh	166 235 568	0.17%	0.10%	0.12%
86	Africa	GA	Gabon	2 275 023	0.55%	0.18%	0.11%
87	Asia	KR	South Korea	51 310 862	0.12%	0.13%	0.11%
88	North America	HT	Haiti	11 533 436	0.04%	0.10%	0.10%
89	Europe	MD	Moldova	4 025 101	2.19%	0.25%	0.10%
90	Africa	MA	Morocco	37 322 618	0.12%	0.09%	0.10%
91	Europe	PL	Poland	37 807 440	3.44%	0.33%	0.09%
92	Europe	MK	North Macedonia	2 083 293	2.85%	0.21%	0.09%
93	Africa	DZ	Algeria	44 595 470	0.05%	0.07%	0.08%
94	Africa	MR	Mauritania	4 764 263	0.07%	0.10%	0.08%
95	Africa	LR	Liberia	5 169 249	0.01%	0.03%	0.08%
96	Africa	EG	Egypt	104 148 514	0.10%	0.12%	0.08%
97	Europe	RO	Romania	19 116 269	1.70%	0.22%	0.08%
98	Asia	UZ	Uzbekistan	33 925 709	0.07%	0.08%	0.08%
99	Asia	AZ	Azerbaijan	10 225 321	1.01%	0.27%	0.07%
100	Australia/Oceania	PG	Papua New Guinea	9 106 314	0.17%	0.16%	0.07%
101	Africa	CM	Cameroon	27 165 767	0.18%	0.05%	0.07%
102	Asia	PK	Pakistan	224 922 985	0.17%	0.12%	0.07%
103	Africa	KE	Kenya	54 883 446	0.13%	0.07%	0.07%
104	Africa	RW	Rwanda	13 253 433	0.08%	0.05%	0.06%
105	Africa	ZW	Zimbabwe	15 066 546	0.03%	0.03%	0.05%
106	Africa	AO	Angola	33 823 498	0.05%	0.08%	0.05%
107	North America	NI	Nicaragua	6 698 786	0.02%	0.03%	0.03%
108	Europe	AL	Albania	2 874 828	1.48%	0.08%	0.03%
109	Africa	CD	DR Congo	92 111 338	0.01%	0.02%	0.03%
110	Asia	VN	Vietnam	98 164 129	0.01%	0.03%	0.03%
111	Africa	SN	Senegal	17 157 677	0.07%	0.03%	0.03%
112	Asia	SG	Singapore	5 893 725	0.04%	0.06%	0.02%
113	Africa	SL	Sierra Leone	8 129 382	0.01%	0.01%	0.02%
114	Africa	CG	Congo	5 645 517	0.06%	0.04%	0.02%
115	Asia	MM	Myanmar	54 753 832	0.01%	0.01%	0.02%
116	Asia	IL	Israel	9 326 000	1.34%	0.03%	0.02%
117	Africa	MG	Madagascar	28 358 680	0.08%	0.03%	0.02%
118	Africa	MZ	Mozambique	32 076 119	0.07%	0.01%	0.02%
119	Africa	ET	Ethiopia	117 635 168	0.11%	0.03%	0.01%
120	Africa	BI	Burundi	12 222 502	0.03%	0.02%	0.01%
121	Africa	GH	Ghana	31 682 190	0.07%	0.02%	0.01%
122	Africa	TG	Togo	8 460 832	0.09%	0.02%	0.01%
123	Asia	SY	Syria	17 899 562	0.06%	0.03%	0.01%
124	Africa	GN	Guinea	13 466 742	0.06%	0.02%	0.01%
125	Africa	SD	Sudan	44 810 191	0.01%	0.01%	0.01%
126	Africa	SO	Somalia	16 308 802	0.06%	0.01%	0.01%
127	Africa	CI	Ivory Coast	26 991 087	0.06%	0.02%	0.01%
128	Africa	GM	Gambia	2 480 296	0.07%	0.01%	0.01%
129	Australia/Oceania	NZ	New Zealand	5 002 100	0.01%	0.00%	0.01%
130	Africa	MW	Malawi	19 593 554	0.03%	0.01%	0.01%
131	Africa	GW	Guinea-Bissau	2 011 654	0.05%	0.01%	0.01%
132	Asia	LA	Laos	7 374 920	0.03%	0.03%	0.01%
133	Australia/Oceania	AU	Australia	25 778 568	0.01%	0.00%	0.01%
134	Asia	HK	Hong Kong	7 554 327	0.02%	0.00%	0.01%
135	Asia	YE	Yemen	30 442 770	0.02%	0.00%	0.00%
136	Africa	LS	Lesotho	2 158 261	0.05%	0.01%	0.00%
137	Africa	NG	Nigeria	210 932 837	0.01%	0.00%	0.00%
138	Africa	CF	Central African R.	4 908 729	0.04%	0.03%	0.00%
139	Africa	ML	Mali	20 797 354	0.03%	0.00%	0.00%
140	Africa	BJ	Benin	12 420 971	0.03%	0.00%	0.00%
141	Africa	BF	Burkina Faso	21 440 567	0.01%	0.00%	0.00%
142	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
143	Africa	TZ	Tanzania	61 328 577	0.00%	0.00%	0.00%
144	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
145	Asia	TJ	Tajikistan	9 738 767	0.00%	0.00%	0.00%
146	Africa	TD	Chad	16 867 510	0.01%	0.00%	0.00%
147	Africa	NE	Niger	25 025 730	0.00%	0.00%	0.00%
148	Africa	SS	South Sudan	11 317 335	0.05%	0.00%	0.00%
149	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
150	Asia	PS	Palestine	5 212 723	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	SD	Sudan	44 810 191	13.73%	(20.16)%	(0.01)%
2	Asia	YE	Yemen	30 442 770	15.60%	(18.03)%	(0.00)%
3	Europe	MK	North Macedonia	2 083 293	4.07%	14.14%	0.21%
4	North America	MX	Mexico	130 209 100	11.02%	13.57%	0.22%
5	Europe	RO	Romania	19 116 269	3.58%	12.20%	0.22%
6	Europe	BA	Bosnia and Herzegovina	3 261 513	5.67%	11.99%	0.34%
7	South America	PE	Peru	33 404 191	9.53%	8.58%	1.59%
8	Asia	SY	Syria	17 899 562	8.07%	(8.48)%	(0.03)%
9	Africa	LS	Lesotho	2 158 261	6.10%	(6.82)%	(0.01)%
10	North America	JM	Jamaica	2 973 365	1.94%	6.62%	0.30%
11	Europe	BG	Bulgaria	6 898 946	4.22%	6.32%	0.42%
12	Europe	PL	Poland	37 807 440	2.55%	6.15%	0.33%
13	Africa	ZW	Zimbabwe	15 066 546	4.89%	(5.84)%	(0.03)%
14	Africa	LR	Liberia	5 169 249	2.94%	(5.80)%	(0.03)%
15	Africa	ML	Mali	20 797 354	2.97%	(5.54)%	(0.00)%
16	Africa	GM	Gambia	2 480 296	2.42%	(5.32)%	(0.01)%
17	Europe	SK	Slovakia	5 462 140	5.10%	5.30%	0.30%
18	Europe	MD	Moldova	4 025 101	2.74%	4.66%	0.25%
19	Europe	HU	Hungary	9 637 163	3.76%	4.63%	0.47%
20	Africa	BF	Burkina Faso	21 440 567	1.30%	(4.50)%	(0.00)%
21	Africa	TN	Tunisia	11 935 141	4.24%	4.50%	1.29%
22	Asia	IL	Israel	9 326 000	0.70%	(4.40)%	(0.03)%
23	South America	EC	Ecuador	17 895 139	3.26%	4.25%	0.68%
24	Africa	EG	Egypt	104 148 514	5.75%	4.24%	0.12%
25	Europe	RU	Russia	145 993 575	3.93%	4.18%	0.73%
26	Africa	GW	Guinea-Bissau	2 011 654	2.10%	(4.08)%	(0.01)%
27	Asia	TW	Taiwan	23 857 483	4.01%	4.08%	0.19%
28	Asia	AF	Afghanistan	39 751 424	4.32%	4.07%	0.24%
29	Africa	MG	Madagascar	28 358 680	2.63%	(4.06)%	(0.03)%
30	Africa	KE	Kenya	54 883 446	2.22%	(3.92)%	(0.07)%
31	Asia	AM	Armenia	2 968 473	2.42%	3.88%	0.45%
32	South America	PY	Paraguay	7 215 047	3.23%	3.86%	4.42%
33	Europe	UA	Ukraine	43 485 203	2.81%	3.64%	0.78%
34	Africa	NG	Nigeria	210 932 837	1.33%	(3.50)%	(0.00)%
35	Africa	SO	Somalia	16 308 802	6.46%	(3.48)%	(0.01)%
36	North America	HT	Haiti	11 533 436	2.64%	(3.39)%	(0.10)%
37	North America	HN	Honduras	10 052 801	3.09%	3.16%	0.88%
38	Asia	ID	Indonesia	276 248 772	2.77%	3.10%	0.23%
39	Africa	NA	Namibia	2 584 165	2.48%	3.07%	1.74%
40	Europe	AL	Albania	2 874 828	1.86%	(3.04)%	(0.08)%
41	Africa	SL	Sierra Leone	8 129 382	0.68%	(3.00)%	(0.01)%
42	Europe	HR	Croatia	4 081 316	2.31%	2.99%	0.98%
43	Africa	DZ	Algeria	44 595 470	2.83%	(2.85)%	(0.07)%
44	South America	BO	Bolivia	11 822 915	2.71%	2.81%	2.49%
45	Africa	TD	Chad	16 867 510	3.20%	(2.80)%	(0.00)%
46	Africa	SN	Senegal	17 157 677	3.08%	(2.80)%	(0.03)%
47	North America	SV	El Salvador	6 517 087	3.08%	2.78%	0.28%
48	South America	BR	Brazil	213 984 390	3.27%	2.75%	3.44%
49	Asia	PK	Pakistan	224 922 985	2.47%	2.65%	0.12%
50	South America	PR	Puerto Rico	3 193 694	1.43%	2.62%	0.45%
51	South America	CO	Colombia	51 393 873	2.70%	2.59%	4.74%
52	Africa	ZA	South Africa	60 012 828	4.61%	2.58%	0.79%
53	Africa	ET	Ethiopia	117 635 168	1.55%	(2.34)%	(0.03)%
54	Asia	BD	Bangladesh	166 235 568	1.75%	2.33%	0.10%
55	Africa	MW	Malawi	19 593 554	2.88%	(2.19)%	(0.01)%
56	Africa	AO	Angola	33 823 498	2.14%	(2.19)%	(0.08)%
57	Asia	LB	Lebanon	6 796 539	1.71%	2.14%	0.46%
58	Asia	AZ	Azerbaijan	10 225 321	1.72%	2.09%	0.27%
59	Europe	IT	Italy	60 377 804	2.09%	2.08%	0.72%
60	Europe	GR	Greece	10 374 902	2.56%	2.07%	1.68%
61	Asia	GE	Georgia	3 981 930	1.92%	2.07%	2.64%
62	Asia	KG	Kyrgyzstan	6 625 437	2.00%	2.06%	0.58%
63	Africa	CD	DR Congo	92 111 338	1.49%	(2.03)%	(0.02)%
64	Africa	CM	Cameroon	27 165 767	1.72%	(2.01)%	(0.05)%
65	Asia	PH	Philippines	110 954 199	1.50%	1.99%	0.63%
66	North America	US	USA	332 833 770	1.77%	1.95%	0.74%
67	Asia	JP	Japan	126 110 418	1.99%	1.94%	0.35%
68	Europe	RS	Serbia	8 704 091	0.89%	1.90%	0.50%
69	North America	GT	Guatemala	18 227 090	2.38%	1.90%	0.61%
70	Asia	MM	Myanmar	54 753 832	1.67%	1.85%	0.01%
71	South America	AR	Argentina	45 586 681	1.74%	1.80%	7.41%
72	Asia	NP	Nepal	29 629 496	2.00%	1.80%	2.41%
73	Africa	GN	Guinea	13 466 742	0.94%	1.78%	0.02%
74	Europe	DE	Germany	84 036 849	1.77%	1.76%	0.69%
75	Asia	JO	Jordan	10 298 587	1.26%	1.75%	0.76%
76	Europe	CZ	Czechia	10 727 742	1.92%	1.74%	0.55%
77	South America	UY	Uruguay	3 485 094	1.64%	1.63%	11.54%
78	Asia	IR	Iran	85 005 237	1.52%	1.57%	1.37%
79	South America	CL	Chile	19 270 893	1.64%	1.52%	4.00%
80	Africa	RW	Rwanda	13 253 433	1.21%	1.49%	0.05%
81	Asia	TR	Turkey	85 194 096	0.77%	1.46%	1.13%
82	Africa	MZ	Mozambique	32 076 119	1.19%	1.45%	0.01%
83	Africa	BW	Botswana	2 396 237	1.95%	1.39%	1.94%
84	Asia	OM	Oman	5 228 445	1.07%	1.37%	2.02%
85	Asia	IN	India	1 392 790 451	1.14%	1.34%	1.59%
86	Africa	MA	Morocco	37 322 618	1.60%	1.32%	0.09%
87	Asia	LK	Sri Lanka	21 497 986	1.16%	1.27%	1.55%
88	Africa	ZM	Zambia	18 866 484	1.08%	1.26%	0.29%
89	Asia	SA	Saudi Arabia	35 323 967	1.28%	1.23%	0.37%
90	South America	VE	Venezuela	28 359 773	1.38%	1.23%	0.51%
91	North America	CR	Costa Rica	5 137 964	1.21%	1.21%	4.82%
92	Europe	LT	Lithuania	2 686 296	1.45%	1.17%	2.24%
93	Africa	CI	Ivory Coast	26 991 087	0.74%	1.16%	0.02%
94	Africa	MR	Mauritania	4 764 263	1.49%	1.16%	0.10%
95	North America	NI	Nicaragua	6 698 786	1.84%	1.11%	0.03%
96	Europe	AT	Austria	9 054 880	1.04%	1.09%	0.62%
97	Asia	MY	Malaysia	32 756 466	0.74%	1.08%	2.28%
98	Europe	FR	France	65 409 895	1.21%	1.02%	1.47%
99	Asia	KH	Cambodia	16 936 769	0.91%	1.01%	0.37%
100	Africa	GA	Gabon	2 275 023	0.63%	0.94%	0.18%
101	North America	PA	Panama	4 378 667	1.52%	0.92%	1.49%
102	Africa	LY	Libya	6 959 252	1.76%	0.91%	0.44%
103	Asia	TH	Thailand	69 965 349	0.87%	0.90%	0.55%
104	Africa	CF	Central African R.	4 908 729	1.67%	0.88%	0.03%
105	Africa	CG	Congo	5 645 517	0.83%	0.84%	0.04%
106	Europe	BY	Belarus	9 446 386	0.78%	0.84%	1.33%
107	North America	CU	Cuba	11 320 084	0.69%	0.82%	1.22%
108	Africa	UG	Uganda	47 093 315	0.79%	0.80%	0.13%
109	North America	CA	Canada	38 054 099	0.80%	0.80%	1.01%
110	Asia	KZ	Kazakhstan	18 988 238	2.06%	0.79%	1.10%
111	Asia	MN	Mongolia	3 327 951	0.55%	0.71%	2.93%
112	Australia/Oceania	PG	Papua New Guinea	9 106 314	1.01%	0.69%	0.16%
113	Europe	BE	Belgium	11 637 225	0.96%	0.69%	1.59%
114	Europe	FI	Finland	5 548 849	0.55%	0.67%	0.31%
115	Asia	IQ	Iraq	41 069 893	0.59%	0.62%	1.11%
116	Asia	QA	Qatar	2 807 805	0.49%	0.60%	1.02%
117	Europe	SI	Slovenia	2 079 208	0.84%	0.59%	1.65%
118	Europe	ES	Spain	46 771 885	1.33%	0.54%	1.04%
119	Africa	BJ	Benin	12 420 971	1.16%	0.51%	0.00%
120	Asia	KR	South Korea	51 310 862	0.75%	0.49%	0.13%
121	North America	DO	Dominican R.	10 950 421	0.99%	0.46%	1.17%
122	Africa	GH	Ghana	31 682 190	1.15%	0.44%	0.02%
123	Asia	UZ	Uzbekistan	33 925 709	0.36%	0.44%	0.08%
124	Asia	KW	Kuwait	4 330 005	0.56%	0.41%	3.24%
125	Asia	VN	Vietnam	98 164 129	0.33%	0.39%	0.03%
126	Europe	CH	Switzerland	8 714 309	0.54%	0.35%	0.94%
127	Asia	SG	Singapore	5 893 725	0.20%	0.34%	0.06%
128	Europe	PT	Portugal	10 168 602	2.10%	0.30%	0.58%
129	Europe	GB	United Kingdom	68 222 484	2.08%	0.29%	0.60%
130	Africa	ER	Eritrea	3 592 624	0.33%	0.28%	0.11%
131	Europe	SE	Sweden	10 158 668	0.40%	0.26%	2.48%
132	Africa	BI	Burundi	12 222 502	0.16%	0.25%	0.02%
133	Europe	NL	Netherlands	17 170 672	0.46%	0.24%	2.13%
134	Asia	LA	Laos	7 374 920	0.16%	0.23%	0.03%
135	Africa	TG	Togo	8 460 832	0.56%	0.22%	0.02%
136	Asia	AE	Arab Emirates	10 002 945	0.28%	0.19%	2.04%
137	Europe	NO	Norway	5 461 212	0.32%	0.13%	0.73%
138	Europe	DK	Denmark	5 811 456	0.29%	0.08%	1.82%
139	Europe	IE	Ireland	4 989 746	1.74%	0.03%	0.90%
140	Australia/Oceania	NZ	New Zealand	5 002 100	0.27%	0.00%	0.00%
141	Australia/Oceania	AU	Australia	25 778 568	0.08%	0.00%	0.00%
142	Asia	HK	Hong Kong	7 554 327	1.46%	0.00%	0.00%
143	Africa	NE	Niger	25 025 730	2.91%	0.00%	0.00%
144	Africa	SS	South Sudan	11 317 335	0.75%	0.00%	0.00%
145	Asia	KP	North Korea	25 660 000	0.00%	0.00%	0.00%
146	Africa	TZ	Tanzania	61 328 577	0.00%	0.00%	0.00%
147	Europe	TM	Turkmenistan	6 118 000	0.00%	0.00%	0.00%
148	Asia	TJ	Tajikistan	9 738 767	0.00%	0.00%	0.00%
149	Asia	CN	China	1 439 323 776	0.00%	0.00%	0.00%
150	Asia	PS	Palestine	5 212 723	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	33 404 191	187 410	5.610‰
2	Europe	HU	Hungary	9 637 163	29 813	3.094‰
3	Europe	BA	Bosnia and Herzegovina	3 261 513	9 473	2.905‰
4	Europe	CZ	Czechia	10 727 742	30 212	2.816‰
5	Europe	MK	North Macedonia	2 083 293	5 468	2.625‰
6	Europe	BG	Bulgaria	6 898 946	17 878	2.591‰
7	Europe	SK	Slovakia	5 462 140	12 436	2.277‰
8	Europe	SI	Slovenia	2 079 208	4 712	2.266‰
9	South America	BR	Brazil	213 984 390	479 007	2.239‰
10	Europe	BE	Belgium	11 637 225	25 068	2.154‰
11	Europe	IT	Italy	60 377 804	126 819	2.100‰
12	Europe	HR	Croatia	4 081 316	8 112	1.988‰
13	Europe	PL	Poland	37 807 440	74 494	1.970‰
14	Europe	GB	United Kingdom	68 222 484	127 872	1.874‰
15	South America	AR	Argentina	45 586 681	83 354	1.829‰
16	South America	CO	Colombia	51 393 873	93 492	1.819‰
17	North America	US	USA	332 833 770	592 972	1.782‰
18	North America	MX	Mexico	130 209 100	229 343	1.761‰
19	Europe	ES	Spain	46 771 885	80 368	1.718‰
20	Europe	PT	Portugal	10 168 602	17 038	1.675‰
21	Europe	FR	France	65 409 895	109 336	1.672‰
22	Europe	RO	Romania	19 116 269	31 388	1.642‰
23	Europe	LT	Lithuania	2 686 296	4 330	1.612‰
24	South America	CL	Chile	19 270 893	30 248	1.570‰
25	Europe	MD	Moldova	4 025 101	6 148	1.527‰
26	Asia	AM	Armenia	2 968 473	4 478	1.508‰
27	North America	PA	Panama	4 378 667	6 416	1.465‰
28	Europe	SE	Sweden	10 158 668	14 562	1.434‰
29	South America	PY	Paraguay	7 215 047	10 294	1.427‰
30	South America	UY	Uruguay	3 485 094	4 793	1.375‰
31	South America	BO	Bolivia	11 822 915	15 273	1.292‰
32	Asia	GE	Georgia	3 981 930	5 018	1.260‰
33	Europe	GR	Greece	10 374 902	12 367	1.192‰
34	Europe	UA	Ukraine	43 485 203	51 576	1.186‰
35	Europe	CH	Switzerland	8 714 309	10 244	1.175‰
36	South America	EC	Ecuador	17 895 139	20 951	1.171‰
37	Europe	AT	Austria	9 054 880	10 388	1.147‰
38	Asia	LB	Lebanon	6 796 539	7 785	1.145‰
39	Africa	TN	Tunisia	11 935 141	13 289	1.113‰
40	Europe	DE	Germany	84 036 849	89 616	1.066‰
41	Europe	NL	Netherlands	17 170 672	17 701	1.031‰
42	Europe	IE	Ireland	4 989 746	4 941	0.990‰
43	Asia	IR	Iran	85 005 237	81 634	0.960‰
44	Africa	ZA	South Africa	60 012 828	57 492	0.958‰
45	Asia	JO	Jordan	10 298 587	9 566	0.929‰
46	Europe	RU	Russia	145 993 575	125 677	0.861‰
47	Europe	AL	Albania	2 874 828	2 452	0.853‰
48	North America	CR	Costa Rica	5 137 964	4 275	0.832‰
49	Europe	RS	Serbia	8 704 091	6 945	0.798‰
50	South America	PR	Puerto Rico	3 193 694	2 524	0.790‰
51	Asia	IL	Israel	9 326 000	6 428	0.689‰
52	North America	CA	Canada	38 054 099	25 809	0.678‰
53	North America	HN	Honduras	10 052 801	6 564	0.653‰
54	Asia	TR	Turkey	85 194 096	48 503	0.569‰
55	Asia	AZ	Azerbaijan	10 225 321	4 950	0.484‰
56	Asia	OM	Oman	5 228 445	2 448	0.468‰
57	North America	GT	Guatemala	18 227 090	8 359	0.459‰
58	Africa	LY	Libya	6 959 252	3 155	0.453‰
59	Europe	DK	Denmark	5 811 456	2 522	0.434‰
60	Asia	KW	Kuwait	4 330 005	1 809	0.418‰
61	Asia	IQ	Iraq	41 069 893	16 636	0.405‰
62	Asia	KZ	Kazakhstan	18 988 238	7 465	0.393‰
63	Africa	NA	Namibia	2 584 165	955	0.370‰
64	Africa	BW	Botswana	2 396 237	885	0.369‰
65	North America	SV	El Salvador	6 517 087	2 283	0.350‰
66	North America	DO	Dominican R.	10 950 421	3 691	0.337‰
67	North America	JM	Jamaica	2 973 365	994	0.334‰
68	Europe	BY	Belarus	9 446 386	2 950	0.312‰
69	Asia	KG	Kyrgyzstan	6 625 437	1 874	0.283‰
70	Asia	NP	Nepal	29 629 496	8 240	0.278‰
71	Asia	IN	India	1 392 790 451	360 156	0.259‰
72	Africa	MA	Morocco	37 322 618	9 195	0.246‰
73	Asia	SA	Saudi Arabia	35 323 967	7 519	0.213‰
74	Asia	QA	Qatar	2 807 805	575	0.205‰
75	Asia	PH	Philippines	110 954 199	22 335	0.201‰
76	Asia	ID	Indonesia	276 248 772	52 326	0.189‰
77	Europe	FI	Finland	5 548 849	964	0.174‰
78	Asia	AE	Arab Emirates	10 002 945	1 714	0.171‰
79	Africa	LS	Lesotho	2 158 261	326	0.151‰
80	Africa	EG	Egypt	104 148 514	15 508	0.149‰
81	Europe	NO	Norway	5 461 212	789	0.144‰
82	Asia	MY	Malaysia	32 756 466	3 687	0.113‰
83	Asia	JP	Japan	126 110 418	13 911	0.110‰
84	Africa	ZW	Zimbabwe	15 066 546	1 625	0.108‰
85	Asia	SY	Syria	17 899 562	1 803	0.101‰
86	Asia	MN	Mongolia	3 327 951	333	0.100‰
87	Africa	MR	Mauritania	4 764 263	471	0.099‰
88	South America	VE	Venezuela	28 359 773	2 766	0.098‰
89	Asia	PK	Pakistan	224 922 985	21 510	0.096‰
90	North America	CU	Cuba	11 320 084	1 055	0.093‰
91	Asia	LK	Sri Lanka	21 497 986	1 910	0.089‰
92	Asia	AF	Afghanistan	39 751 424	3 404	0.086‰
93	Africa	DZ	Algeria	44 595 470	3 552	0.080‰
94	Asia	BD	Bangladesh	166 235 568	12 988	0.078‰
95	Africa	GM	Gambia	2 480 296	180	0.073‰
96	Africa	ZM	Zambia	18 866 484	1 341	0.071‰
97	Africa	GA	Gabon	2 275 023	156	0.069‰
98	Africa	SN	Senegal	17 157 677	1 150	0.067‰
99	Africa	KE	Kenya	54 883 446	3 363	0.061‰
100	Africa	SD	Sudan	44 810 191	2 719	0.061‰
101	Asia	MM	Myanmar	54 753 832	3 235	0.059‰
102	Africa	MW	Malawi	19 593 554	1 158	0.059‰
103	Africa	CM	Cameroon	27 165 767	1 310	0.048‰
104	Africa	SO	Somalia	16 308 802	774	0.048‰
105	Asia	YE	Yemen	30 442 770	1 342	0.044‰
106	Asia	KR	South Korea	51 310 862	1 980	0.039‰
107	Africa	ET	Ethiopia	117 635 168	4 230	0.036‰
108	Australia/Oceania	AU	Australia	25 778 568	910	0.035‰
109	Africa	GW	Guinea-Bissau	2 011 654	69	0.034‰
110	Africa	MG	Madagascar	28 358 680	877	0.031‰
111	North America	HT	Haiti	11 533 436	345	0.030‰
112	North America	NI	Nicaragua	6 698 786	188	0.028‰
113	Asia	HK	Hong Kong	7 554 327	210	0.028‰
114	Africa	RW	Rwanda	13 253 433	366	0.028‰
115	Africa	CG	Congo	5 645 517	155	0.028‰
116	Africa	MZ	Mozambique	32 076 119	840	0.026‰
117	Africa	ML	Mali	20 797 354	523	0.025‰
118	Africa	GH	Ghana	31 682 190	789	0.025‰
119	Africa	AO	Angola	33 823 498	815	0.024‰
120	Asia	UZ	Uzbekistan	33 925 709	703	0.021‰
121	Asia	TH	Thailand	69 965 349	1 404	0.020‰
122	Africa	CF	Central African R.	4 908 729	98	0.020‰
123	Africa	LR	Liberia	5 169 249	93	0.018‰
124	Australia/Oceania	PG	Papua New Guinea	9 106 314	164	0.018‰
125	Asia	KH	Cambodia	16 936 769	298	0.018‰
126	Asia	TW	Taiwan	23 857 483	411	0.017‰
127	Africa	TG	Togo	8 460 832	126	0.015‰
128	Africa	GN	Guinea	13 466 742	165	0.012‰
129	Africa	CI	Ivory Coast	26 991 087	306	0.011‰
130	Africa	TD	Chad	16 867 510	174	0.010‰
131	Africa	SS	South Sudan	11 317 335	115	0.010‰
132	Africa	SL	Sierra Leone	8 129 382	82	0.010‰
133	Africa	NG	Nigeria	210 932 837	2 117	0.010‰
134	Asia	TJ	Tajikistan	9 738 767	90	0.009‰
135	Africa	UG	Uganda	47 093 315	417	0.009‰
136	Africa	CD	DR Congo	92 111 338	824	0.009‰
137	Africa	BJ	Benin	12 420 971	102	0.008‰
138	Africa	BF	Burkina Faso	21 440 567	167	0.008‰
139	Africa	NE	Niger	25 025 730	192	0.008‰
140	Asia	SG	Singapore	5 893 725	34	0.006‰
141	Australia/Oceania	NZ	New Zealand	5 002 100	26	0.005‰
142	Africa	ER	Eritrea	3 592 624	14	0.004‰
143	Africa	BI	Burundi	12 222 502	8	0.001‰
144	Asia	VN	Vietnam	98 164 129	56	0.001‰
145	Asia	PS	Palestine	5 212 723	2	0.000‰
146	Asia	LA	Laos	7 374 920	3	0.000‰
147	Africa	TZ	Tanzania	61 328 577	21	0.000‰
148	Asia	CN	China	1 439 323 776	0	0.000‰
149	Asia	KP	North Korea	25 660 000	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"