As far as unique metropolitan areas seems that the New York City metro area leads the world in Covid19.
Let's take a look at some actual data.
What you'll see below, unless otherwise noted, is derived from https://www.worldometers.info/coronavirus/#countries.
So let's start with a "sequence of events" table - on the very far right is the first reported Covid19 case date (this table data is also available as .CSV data at the bottom of the post). This is just the linked table sorted by first.
The columns we care about are the last three (all are in order from the link above so you can figure out the rest). totper1mPop is the total Covid19 cases per one million population. This is important because it normalizes the way the cases are reported. (If you don't understand why stop reading this blog immediately and flush your head in the toilet.) deathper1mPop is the total Covid19 cases per one million that have died. Again normalized so we are comparing apples to apples. Finally first is the first "officially" reported case which we will accept as truth for now...
Everything starts in China. And after it appears (officially on the linked site above) in China on 01/10/2020 it reaches the USA ten (10) days later on 01/20/20.
The first odd thing you will notice is Italy, about half way down Part 1. One hundred sixty six (166) deaths per million - at least an order of magnitude greater than anything else until you get to Spain with one hundred forty (140). Note too that Covid19 arrived in Italy only nine days (9) after the US on 01/29/20. It arrives in Spain one day later. Things are really out of control by the time you reach San Marino (a small micro-state on the west side of the Italian peninsula) with 648 deaths and Covid19 arriving on 02/26/20.
These are outliers. They are not like the rest. There a many, many tens of millions more people in China, the US, and so on.
You have to ask what's so different about these few countries?
Late start, huge explosion of cases very quickly.
Yet they are always singled out in the press as the harbinger of death.
Compare them to Taiwan with .08 deaths per million. Right next door to China and much like Japan, South Korea, and other Asian countries near the epicenter in China.
Yet the squealing of "horror, horror" continues to focus on Italy.
Sure, Italy has "a lot of deaths", but why is Italy chosen by the press as a representative sample of this data?
Now let's look at the death rate or how many people, per one million of population, die of Covid19.
This is the same table sorted by deathper1mPop.
The world Covid19 death rate today stands at .0000041 (4.1 per million).
The USA is nearly double that at seven (7); not quite double the world rate.
Belgium and up are roughly ten times (10x) the world rate.
The US automobile death rate (from here) per one million is about 120 or .00012 or thirty times more than Covid19. The distribution (from here) looks like this:
This is expected: young people are reckless and old people who shouldn't be driving cause accidents.
From here we see how the deaths in Italy are distributed:
Basically the older you are the more likely you are to die from Covid19. Here in the US (from here, blue is 2017, 1999 is grey):
Converting to "per million" we see about between 1,000 and 3,700 deaths per million in the elderly population.
This translates to a fatality rate of around .1% to .37% for the elderly.
So Covid19 is quite a bit more dangerous than flu in general (perhaps on the order of 50x given what we've seen so far).
But there's a problem here.
We don't actually know who has Covid19 or how many cases there actually are.
Flu is well understood by the CDC and they have been tracking it for decades.
Covid19 seems, at best, to have a checkered past as far as testing goes. Checkered in two primary ways: The tests are unreliable and many people have it and either don't get sick or don't get sick enough for anyone to notice or care in the statistics industry creating these charts.
And this is critical.
What we do know is that for South Korea and Germany, for example, the more testing that's done there is a higher the number of mild cases yielding a lower mortality rate.
Testing per million as of 03/20/20 is here:
So if you believe in mathematics you have to believe the full story is far from being told.
Covid19 is dangerous, particularly if you are older or have underlying health conditions, but it still can affect everybody and anybody.
So common sense is about the best you can do given no scientifically blessed "cure." Alternates such as those described here like chloroquine and hydroxychloroquine are available as long as you don't live in a state controlled by a Democratic governor.
The direction of the numbers, to me, tells the tail.
A lot of people are likely infected but sense the testing is virtually non-existent in the USA we are flying blind.
Covid19 is dangerous so use common sense.
Which brings us to New York City.
Several previous posts here have shown the utter irresponsibility of the government of NYC.
Now statistically I see NYC metro area (say about twenty million) as slightly larger than the Netherlands (about seventeen million) in terms of population. The Covid19 death rate per million is about the same (see stats here).
It would seem that the rate of new cases has leveled off according to the chart below from the stats link in the previous paragraph:
According to this link New York, New Jersey and California account for seventy five percent (75%) of all US cases:
(It is perhaps unfair to include California because of its very large area and distributed urban centers.)
None the less NYC has somehow managed to become the leader as it would be either just above or below the Netherlands in the deathper1mPop chart above, and it's a single metro area.
To me this simply points out that the irresponsible behavior of de Blasio, Oxiris Barbot and others has directly lead to avoidable deaths.
Statistics here are very clear.
Political correctness and ignorance is killing people in the NYC metro area (see https://lwgat.blogspot.com/2020/03/coronavirus-politicians-kill.html).
Little wonder the populous is fleeing NYC (Italy is on lockdown, shouldn't NYC be?)
Let's hope they get things under control.
The captain of the titanic went down with his ship.
The magnitude of the problem becomes clear when you compare the top US Covid19 areas with the rest of the world.
Without them the US would like like the China at the bottom of the deathper1mPop chart.
What does that say?
Perhaps these politicians should reflect on the actions...
Data:
Country totalcases newcases totaldeaths newdeaths recovered activecases seriouscritical totper1mPop deathper1mPop first
World 683,694 +20,615 32,156 +1,299 146,397 505,141 25,426 87.7 4.1 01/10
USA 123,828 +250 2,231 +10 3,238 118,359 2,666 374 7 01/20
Italy 92,472 10,023 12,384 70,065 3,856 1,529 166 01/29
China 81,439 +45 3,300 +5 75,448 2,691 742 57 2 01/10
Spain 78,797 +5,562 6,528 +546 14,709 57,560 4,165 1,685 140 01/30
Germany 58,247 +552 455 +22 8,481 49,311 1,581 695 5 01/26
Iran 38,309 +2,901 2,640 +123 12,391 23,278 3,206 456 31 Feb 18
France 37,575 2,314 5,700 29,561 4,273 576 35 01/23
UK 19,522 +2,433 1,235 +216 135 18,152 163 288 18 01/30
Switzerland 14,593 +517 290 +26 1,595 12,708 301 1,686 34 02/24
Netherlands 10,866 +1,104 771 +132 3 10,092 914 634 45 02/26
Belgium 10,836 +1,702 431 +78 1,359 9,046 867 935 37 02/03
S. Korea 9,583 +105 152 +8 5,033 4,398 59 187 3 01/19
Austria 8,536 +265 86 +18 479 7,971 187 948 10 02/24
Turkey 7,402 108 70 7,224 445 88 1 03/09
Portugal 5,962 +792 119 +19 43 5,800 89 585 12 03/01
Canada 5,655 61 +1 508 5,086 120 150 2 01/24
Norway 4,235 +220 25 +2 7 4,203 91 781 5 02/25
Australia 3,969 +334 16 +2 226 3,727 23 156 0.6 01/24
Brazil 3,904 117 +3 6 3,781 296 18 0.6 02/24
Israel 3,865 +246 14 +2 89 3,762 66 447 2 02/20
Sweden 3,700 +253 110 +5 16 3,574 255 366 11 01/30
Czechia 2,697 +66 13 +2 11 2,673 45 252 1 02/29
Malaysia 2,470 +150 34 +7 388 2,048 73 76 1 01/24
Ireland 2,415 36 5 2,374 59 489 7 02/28
Denmark 2,395 +194 72 +7 1 2,322 113 413 12 02/26
Chile 1,909 6 61 1,842 7 100 0.3 03/02
Luxembourg 1,831 18 40 1,773 25 2,925 29 02/28
Ecuador 1,823 48 3 1,772 58 103 3 02/28
Poland 1,771 +133 20 +2 7 1,744 3 47 0.5 03/03
Romania 1,760 +308 40 +3 169 1,551 34 91 2 02/25
Japan 1,693 52 424 1,217 56 13 0.4 01/14
Russia 1,534 +270 8 +4 64 1,462 8 11 0.05 01/30
Pakistan 1,526 +31 14 +2 29 1,483 11 7 0.06 02/25
Philippines 1,418 +343 71 +3 42 1,305 1 13 0.6 01/29
Thailand 1,388 +143 7 +1 97 1,284 11 20 0.1 01/12
Saudi Arabia 1,299 +96 8 +4 66 1,225 12 37 0.2 03/01
Indonesia 1,285 +130 114 +12 64 1,107 5 0.4 03/01
Finland 1,239 +72 11 +2 10 1,218 32 224 2 01/28
South Africa 1,187 1 31 1,155 7 20 0.02 03/04
Greece 1,061 37 +5 52 972 66 102 4 02/25
Iceland 1,020 +57 2 114 904 19 2,989 6 02/27
India 987 25 +1 87 875 0.7 0.02 01/29
Panama 901 17 4 880 32 209 4 03/09
Mexico 848 +131 16 +4 4 828 1 7 0.1 02/27
Singapore 844 +42 3 +1 212 629 19 144 0.5 01/22
Argentina 745 19 72 654 16 0.4 03/02
Serbia 741 +82 13 +3 42 686 25 85 1 03/05
Slovenia 730 +46 11 +2 10 709 23 351 5 03/03
Dominican Republic 719 28 3 688 66 3 02/29
Croatia 713 +56 6 +1 52 655 26 174 1 02/24
Diamond Princess 712 10 597 105 15 02/04
Estonia 679 +34 3 +2 20 656 10 512 2 02/26
Peru 671 16 16 639 33 20 0.5 03/05
Hong Kong 641 +81 4 118 519 5 86 0.5 01/22
Colombia 608 6 10 592 12 0.1 03/05
Qatar 590 1 45 544 6 205 0.3 02/28
Egypt 576 36 121 419 6 0.4 02/13
Iraq 547 +41 42 143 362 14 1 02/21
New Zealand 514 1 56 457 1 107 0.2 02/27
Bahrain 499 +23 4 272 223 1 293 2 02/23
UAE 468 2 55 411 2 47 0.2 01/28
Algeria 454 29 31 394 10 0.7 02/24
Morocco 450 +48 26 +1 13 411 1 12 0.7 03/01
Lebanon 438 +26 10 +2 30 398 4 64 1 02/20
Lithuania 437 +43 7 1 429 2 161 3 02/27
Armenia 424 +17 3 +2 30 391 6 143 1 02/29
Ukraine 418 +62 9 5 404 10 0.2 03/02
Hungary 408 +65 13 +2 34 361 6 42 1 03/03
Latvia 347 +42 1 346 3 184 03/01
Bulgaria 338 +7 8 +1 11 319 8 49 1 03/06
Andorra 334 +26 6 +3 1 327 10 4,323 78 03/01
Bosnia and Herzegovina 323 +45 6 8 309 1 98 2 03/04
Slovakia 314 +22 2 312 1 58 03/05
Uruguay 304 1 303 9 88 0.3 03/12
Taiwan 298 +15 2 39 257 13 0.08 01/20
Costa Rica 295 2 3 290 6 58 0.4 03/04
Tunisia 278 8 2 268 10 24 0.7 03/01
North Macedonia 259 +18 6 +2 3 250 1 124 3 02/25
Kuwait 255 +20 67 188 12 60 02/23
Kazakhstan 251 +23 1 18 232 13 0.05 03/12
Jordan 246 1 18 227 3 24 0.10 03/01
Moldova 231 2 2 227 33 57 0.5 03/06
San Marino 224 22 6 196 16 6,602 648 02/26
Albania 212 +15 10 33 169 3 74 3 03/07
Azerbaijan 209 +27 4 15 190 23 21 0.4 02/27
Burkina Faso 207 11 21 175 10 0.5 03/08
Vietnam 188 +14 21 167 3 2 01/22
Réunion 183 1 182 204 03/10
Cyprus 179 5 15 159 3 148 4 03/08
Oman 167 +15 23 144 33 02/23
Faeroe Islands 159 +4 70 89 1 3,254 03/03
Ghana 152 +11 5 2 145 1 5 0.2 03/11
Malta 151 +2 2 149 4 342 03/06
Senegal 142 +12 27 115 8 03/01
Ivory Coast 140 +39 3 137 5 03/10
Uzbekistan 133 +29 2 7 124 8 4 0.06 03/14
Brunei 126 +6 1 34 91 1 288 2 03/08
Afghanistan 120 +10 4 2 114 3 0.1 02/23
Cuba 119 3 4 112 2 11 0.3 03/10
Venezuela 119 2 39 78 2 4 0.07 03/12
Sri Lanka 115 +2 1 11 103 5 5 0.05 01/26
Honduras 110 +15 1 3 106 4 11 0.1 03/10
Palestine 106 +2 1 18 87 21 0.2 03/04
Cambodia 103 +4 21 82 1 6 01/26
Guadeloupe 102 2 17 83 4 255 5 03/12
Mauritius 102 2 100 1 80 2 03/17
Channel Islands 100 +3 1 99 575 6 03/08
Nigeria 97 1 3 93 0.5 0.00 02/27
Belarus 94 32 62 2 10 02/27
Martinique 93 1 92 12 248 3 03/04
Cameroon 91 2 2 87 3 0.08 03/05
Georgia 90 18 72 1 23 02/25
Montenegro 85 +1 1 84 1 135 2 03/16
Kyrgyzstan 84 +26 84 13 03/17
Bolivia 81 +7 81 3 7 03/09
Trinidad and Tobago 76 3 1 72 54 2 03/11
DRC 65 6 2 57 0.7 0.07 03/09
Mayotte 63 63 231 03/13
Rwanda 60 60 5 03/13
Paraguay 56 3 1 52 1 8 0.4 03/06
Gibraltar 56 14 42 1,662 03/02
Liechtenstein 56 56 1,469 03/02
Bangladesh 48 5 15 28 1 0.3 0.03 03/07
Aruba 46 1 45 431 03/12
Monaco 43 1 1 41 1,096 25 02/27
Madagascar 39 +13 39 1 03/19
Kenya 38 1 1 36 2 0.7 0.02 03/12
Macao 37 +3 10 27 57 01/21
Isle of Man 37 +5 37 435 03/18
Guatemala 34 1 10 23 1 2 0.06 03/12
Jamaica 32 +2 1 2 29 11 0.3 03/09
French Polynesia 30 30 107 03/10
Uganda 30 30 0.7 03/20
French Guiana 28 6 22 94 03/06
Zambia 28 28 2 03/17
Barbados 26 26 90 03/16
Togo 25 1 1 23 3 0.1 03/05
El Salvador 24 +5 24 4 03/18
Bermuda 22 +5 2 20 353 03/17
Congo 19 +15 19 3 03/14
Ethiopia 19 +3 1 18 0.2 03/12
Mali 18 1 17 0.9 0.05 03/24
Niger 18 +8 1 17 0.7 0.04 03/18
Maldives 17 +1 11 6 31 03/06
Guinea 16 +8 16 1 03/12
Haiti 15 +7 1 14 1 03/19
New Caledonia 15 15 53 03/17
Djibouti 14 14 14 03/17
Tanzania 14 1 13 0.2 03/15
Equatorial Guinea 12 12 9 03/13
Mongolia 12 12 4 03/09
Dominica 11 11 153 03/21
Namibia 11 +3 2 9 4 03/13
Saint Martin 11 11 284 02/29
Bahamas 10 1 9 25 03/14
Greenland 10 2 8 176 03/15
Grenada 9 +2 9 80 03/21
Eswatini 9 9 8 03/13
Cayman Islands 8 1 7 122 15 03/12
Curaçao 8 1 2 5 49 6 03/12
Guyana 8 1 7 10 1 03/11
Laos 8 8 1 03/23
Mozambique 8 8 0.3 03/21
Myanmar 8 8 0.1 03/22
Seychelles 8 8 81 03/13
Suriname 8 8 14 03/12
Gabon 7 1 6 3 0.4 03/12
Zimbabwe 7 1 6 0.5 0.07 03/19
Antigua and Barbuda 7 7 71 03/12
Cabo Verde 6 1 5 11 2 03/19
Benin 6 6 0.5 03/15
Eritrea 6 6 2 03/20
Vatican City 6 6 7,491 03/05
Sudan 5 1 4 0.1 0.02 03/12
Nepal 5 1 4 0.2 01/23
Angola 5 5 0.2 03/19
Fiji 5 5 6 03/18
Mauritania 5 5 1 03/12
Montserrat 5 5 1,002 03/17
St. Barth 5 5 506 02/29
Syria 5 5 0.3 03/21
Nicaragua 4 1 3 0.6 0.2 03/18
Bhutan 4 +1 4 5 03/05
Saint Lucia 4 +1 1 3 22 03/12
Turks and Caicos 4 4 103 03/22
Gambia 3 1 2 1 0.4 03/16
CAR 3 3 0.6 03/14
Chad 3 3 0.2
03/18
Liberia 3 3 0.6 03/15
Libya 3 3 0.4 03/23
Sint Maarten 3 3 70 03/17
Somalia 3 3 0.2 03/15
MS Zaandam 2 2 03/26
Anguilla 2 2 133 03/25
Belize 2 2 5 03/22
British Virgin Islands 2 2 66 03/24
Guinea-Bissau 2 2 1 03/24
Saint Kitts and Nevis 2 2 38 03/24
Papua New Guinea 1 1 0.1 03/19
St. Vincent Grenadines 1 1 0 9 03/10
Timor-Leste 1 1 0.8 03/2
Let's take a look at some actual data.
What you'll see below, unless otherwise noted, is derived from https://www.worldometers.info/coronavirus/#countries.
So let's start with a "sequence of events" table - on the very far right is the first reported Covid19 case date (this table data is also available as .CSV data at the bottom of the post). This is just the linked table sorted by first.
The columns we care about are the last three (all are in order from the link above so you can figure out the rest). totper1mPop is the total Covid19 cases per one million population. This is important because it normalizes the way the cases are reported. (If you don't understand why stop reading this blog immediately and flush your head in the toilet.) deathper1mPop is the total Covid19 cases per one million that have died. Again normalized so we are comparing apples to apples. Finally first is the first "officially" reported case which we will accept as truth for now...
 |
| Covid19 by First Reported Date (Part 1) |
 |
| Covid19 by First Reported Date (Part 2) |
Everything starts in China. And after it appears (officially on the linked site above) in China on 01/10/2020 it reaches the USA ten (10) days later on 01/20/20.
The first odd thing you will notice is Italy, about half way down Part 1. One hundred sixty six (166) deaths per million - at least an order of magnitude greater than anything else until you get to Spain with one hundred forty (140). Note too that Covid19 arrived in Italy only nine days (9) after the US on 01/29/20. It arrives in Spain one day later. Things are really out of control by the time you reach San Marino (a small micro-state on the west side of the Italian peninsula) with 648 deaths and Covid19 arriving on 02/26/20.
These are outliers. They are not like the rest. There a many, many tens of millions more people in China, the US, and so on.
You have to ask what's so different about these few countries?
Late start, huge explosion of cases very quickly.
Yet they are always singled out in the press as the harbinger of death.
Compare them to Taiwan with .08 deaths per million. Right next door to China and much like Japan, South Korea, and other Asian countries near the epicenter in China.
Yet the squealing of "horror, horror" continues to focus on Italy.
Sure, Italy has "a lot of deaths", but why is Italy chosen by the press as a representative sample of this data?
Now let's look at the death rate or how many people, per one million of population, die of Covid19.
This is the same table sorted by deathper1mPop.
 |
| Sorted by deathper1mPop |
The USA is nearly double that at seven (7); not quite double the world rate.
Belgium and up are roughly ten times (10x) the world rate.
The US automobile death rate (from here) per one million is about 120 or .00012 or thirty times more than Covid19. The distribution (from here) looks like this:
This is expected: young people are reckless and old people who shouldn't be driving cause accidents.
From here we see how the deaths in Italy are distributed:
Basically the older you are the more likely you are to die from Covid19. Here in the US (from here, blue is 2017, 1999 is grey):
Converting to "per million" we see about between 1,000 and 3,700 deaths per million in the elderly population.
This translates to a fatality rate of around .1% to .37% for the elderly.
So Covid19 is quite a bit more dangerous than flu in general (perhaps on the order of 50x given what we've seen so far).
But there's a problem here.
We don't actually know who has Covid19 or how many cases there actually are.
Flu is well understood by the CDC and they have been tracking it for decades.
Covid19 seems, at best, to have a checkered past as far as testing goes. Checkered in two primary ways: The tests are unreliable and many people have it and either don't get sick or don't get sick enough for anyone to notice or care in the statistics industry creating these charts.
And this is critical.
What we do know is that for South Korea and Germany, for example, the more testing that's done there is a higher the number of mild cases yielding a lower mortality rate.
Testing per million as of 03/20/20 is here:
So if you believe in mathematics you have to believe the full story is far from being told.
Covid19 is dangerous, particularly if you are older or have underlying health conditions, but it still can affect everybody and anybody.
So common sense is about the best you can do given no scientifically blessed "cure." Alternates such as those described here like chloroquine and hydroxychloroquine are available as long as you don't live in a state controlled by a Democratic governor.
The direction of the numbers, to me, tells the tail.
A lot of people are likely infected but sense the testing is virtually non-existent in the USA we are flying blind.
Covid19 is dangerous so use common sense.
Which brings us to New York City.
Several previous posts here have shown the utter irresponsibility of the government of NYC.
Now statistically I see NYC metro area (say about twenty million) as slightly larger than the Netherlands (about seventeen million) in terms of population. The Covid19 death rate per million is about the same (see stats here).
It would seem that the rate of new cases has leveled off according to the chart below from the stats link in the previous paragraph:
(It is perhaps unfair to include California because of its very large area and distributed urban centers.)
None the less NYC has somehow managed to become the leader as it would be either just above or below the Netherlands in the deathper1mPop chart above, and it's a single metro area.
To me this simply points out that the irresponsible behavior of de Blasio, Oxiris Barbot and others has directly lead to avoidable deaths.
Statistics here are very clear.
Political correctness and ignorance is killing people in the NYC metro area (see https://lwgat.blogspot.com/2020/03/coronavirus-politicians-kill.html).
Little wonder the populous is fleeing NYC (Italy is on lockdown, shouldn't NYC be?)
Let's hope they get things under control.
The captain of the titanic went down with his ship.
The magnitude of the problem becomes clear when you compare the top US Covid19 areas with the rest of the world.
Without them the US would like like the China at the bottom of the deathper1mPop chart.
What does that say?
Perhaps these politicians should reflect on the actions...
Country totalcases newcases totaldeaths newdeaths recovered activecases seriouscritical totper1mPop deathper1mPop first
World 683,694 +20,615 32,156 +1,299 146,397 505,141 25,426 87.7 4.1 01/10
USA 123,828 +250 2,231 +10 3,238 118,359 2,666 374 7 01/20
Italy 92,472 10,023 12,384 70,065 3,856 1,529 166 01/29
China 81,439 +45 3,300 +5 75,448 2,691 742 57 2 01/10
Spain 78,797 +5,562 6,528 +546 14,709 57,560 4,165 1,685 140 01/30
Germany 58,247 +552 455 +22 8,481 49,311 1,581 695 5 01/26
Iran 38,309 +2,901 2,640 +123 12,391 23,278 3,206 456 31 Feb 18
France 37,575 2,314 5,700 29,561 4,273 576 35 01/23
UK 19,522 +2,433 1,235 +216 135 18,152 163 288 18 01/30
Switzerland 14,593 +517 290 +26 1,595 12,708 301 1,686 34 02/24
Netherlands 10,866 +1,104 771 +132 3 10,092 914 634 45 02/26
Belgium 10,836 +1,702 431 +78 1,359 9,046 867 935 37 02/03
S. Korea 9,583 +105 152 +8 5,033 4,398 59 187 3 01/19
Austria 8,536 +265 86 +18 479 7,971 187 948 10 02/24
Turkey 7,402 108 70 7,224 445 88 1 03/09
Portugal 5,962 +792 119 +19 43 5,800 89 585 12 03/01
Canada 5,655 61 +1 508 5,086 120 150 2 01/24
Norway 4,235 +220 25 +2 7 4,203 91 781 5 02/25
Australia 3,969 +334 16 +2 226 3,727 23 156 0.6 01/24
Brazil 3,904 117 +3 6 3,781 296 18 0.6 02/24
Israel 3,865 +246 14 +2 89 3,762 66 447 2 02/20
Sweden 3,700 +253 110 +5 16 3,574 255 366 11 01/30
Czechia 2,697 +66 13 +2 11 2,673 45 252 1 02/29
Malaysia 2,470 +150 34 +7 388 2,048 73 76 1 01/24
Ireland 2,415 36 5 2,374 59 489 7 02/28
Denmark 2,395 +194 72 +7 1 2,322 113 413 12 02/26
Chile 1,909 6 61 1,842 7 100 0.3 03/02
Luxembourg 1,831 18 40 1,773 25 2,925 29 02/28
Ecuador 1,823 48 3 1,772 58 103 3 02/28
Poland 1,771 +133 20 +2 7 1,744 3 47 0.5 03/03
Romania 1,760 +308 40 +3 169 1,551 34 91 2 02/25
Japan 1,693 52 424 1,217 56 13 0.4 01/14
Russia 1,534 +270 8 +4 64 1,462 8 11 0.05 01/30
Pakistan 1,526 +31 14 +2 29 1,483 11 7 0.06 02/25
Philippines 1,418 +343 71 +3 42 1,305 1 13 0.6 01/29
Thailand 1,388 +143 7 +1 97 1,284 11 20 0.1 01/12
Saudi Arabia 1,299 +96 8 +4 66 1,225 12 37 0.2 03/01
Indonesia 1,285 +130 114 +12 64 1,107 5 0.4 03/01
Finland 1,239 +72 11 +2 10 1,218 32 224 2 01/28
South Africa 1,187 1 31 1,155 7 20 0.02 03/04
Greece 1,061 37 +5 52 972 66 102 4 02/25
Iceland 1,020 +57 2 114 904 19 2,989 6 02/27
India 987 25 +1 87 875 0.7 0.02 01/29
Panama 901 17 4 880 32 209 4 03/09
Mexico 848 +131 16 +4 4 828 1 7 0.1 02/27
Singapore 844 +42 3 +1 212 629 19 144 0.5 01/22
Argentina 745 19 72 654 16 0.4 03/02
Serbia 741 +82 13 +3 42 686 25 85 1 03/05
Slovenia 730 +46 11 +2 10 709 23 351 5 03/03
Dominican Republic 719 28 3 688 66 3 02/29
Croatia 713 +56 6 +1 52 655 26 174 1 02/24
Diamond Princess 712 10 597 105 15 02/04
Estonia 679 +34 3 +2 20 656 10 512 2 02/26
Peru 671 16 16 639 33 20 0.5 03/05
Hong Kong 641 +81 4 118 519 5 86 0.5 01/22
Colombia 608 6 10 592 12 0.1 03/05
Qatar 590 1 45 544 6 205 0.3 02/28
Egypt 576 36 121 419 6 0.4 02/13
Iraq 547 +41 42 143 362 14 1 02/21
New Zealand 514 1 56 457 1 107 0.2 02/27
Bahrain 499 +23 4 272 223 1 293 2 02/23
UAE 468 2 55 411 2 47 0.2 01/28
Algeria 454 29 31 394 10 0.7 02/24
Morocco 450 +48 26 +1 13 411 1 12 0.7 03/01
Lebanon 438 +26 10 +2 30 398 4 64 1 02/20
Lithuania 437 +43 7 1 429 2 161 3 02/27
Armenia 424 +17 3 +2 30 391 6 143 1 02/29
Ukraine 418 +62 9 5 404 10 0.2 03/02
Hungary 408 +65 13 +2 34 361 6 42 1 03/03
Latvia 347 +42 1 346 3 184 03/01
Bulgaria 338 +7 8 +1 11 319 8 49 1 03/06
Andorra 334 +26 6 +3 1 327 10 4,323 78 03/01
Bosnia and Herzegovina 323 +45 6 8 309 1 98 2 03/04
Slovakia 314 +22 2 312 1 58 03/05
Uruguay 304 1 303 9 88 0.3 03/12
Taiwan 298 +15 2 39 257 13 0.08 01/20
Costa Rica 295 2 3 290 6 58 0.4 03/04
Tunisia 278 8 2 268 10 24 0.7 03/01
North Macedonia 259 +18 6 +2 3 250 1 124 3 02/25
Kuwait 255 +20 67 188 12 60 02/23
Kazakhstan 251 +23 1 18 232 13 0.05 03/12
Jordan 246 1 18 227 3 24 0.10 03/01
Moldova 231 2 2 227 33 57 0.5 03/06
San Marino 224 22 6 196 16 6,602 648 02/26
Albania 212 +15 10 33 169 3 74 3 03/07
Azerbaijan 209 +27 4 15 190 23 21 0.4 02/27
Burkina Faso 207 11 21 175 10 0.5 03/08
Vietnam 188 +14 21 167 3 2 01/22
Réunion 183 1 182 204 03/10
Cyprus 179 5 15 159 3 148 4 03/08
Oman 167 +15 23 144 33 02/23
Faeroe Islands 159 +4 70 89 1 3,254 03/03
Ghana 152 +11 5 2 145 1 5 0.2 03/11
Malta 151 +2 2 149 4 342 03/06
Senegal 142 +12 27 115 8 03/01
Ivory Coast 140 +39 3 137 5 03/10
Uzbekistan 133 +29 2 7 124 8 4 0.06 03/14
Brunei 126 +6 1 34 91 1 288 2 03/08
Afghanistan 120 +10 4 2 114 3 0.1 02/23
Cuba 119 3 4 112 2 11 0.3 03/10
Venezuela 119 2 39 78 2 4 0.07 03/12
Sri Lanka 115 +2 1 11 103 5 5 0.05 01/26
Honduras 110 +15 1 3 106 4 11 0.1 03/10
Palestine 106 +2 1 18 87 21 0.2 03/04
Cambodia 103 +4 21 82 1 6 01/26
Guadeloupe 102 2 17 83 4 255 5 03/12
Mauritius 102 2 100 1 80 2 03/17
Channel Islands 100 +3 1 99 575 6 03/08
Nigeria 97 1 3 93 0.5 0.00 02/27
Belarus 94 32 62 2 10 02/27
Martinique 93 1 92 12 248 3 03/04
Cameroon 91 2 2 87 3 0.08 03/05
Georgia 90 18 72 1 23 02/25
Montenegro 85 +1 1 84 1 135 2 03/16
Kyrgyzstan 84 +26 84 13 03/17
Bolivia 81 +7 81 3 7 03/09
Trinidad and Tobago 76 3 1 72 54 2 03/11
DRC 65 6 2 57 0.7 0.07 03/09
Mayotte 63 63 231 03/13
Rwanda 60 60 5 03/13
Paraguay 56 3 1 52 1 8 0.4 03/06
Gibraltar 56 14 42 1,662 03/02
Liechtenstein 56 56 1,469 03/02
Bangladesh 48 5 15 28 1 0.3 0.03 03/07
Aruba 46 1 45 431 03/12
Monaco 43 1 1 41 1,096 25 02/27
Madagascar 39 +13 39 1 03/19
Kenya 38 1 1 36 2 0.7 0.02 03/12
Macao 37 +3 10 27 57 01/21
Isle of Man 37 +5 37 435 03/18
Guatemala 34 1 10 23 1 2 0.06 03/12
Jamaica 32 +2 1 2 29 11 0.3 03/09
French Polynesia 30 30 107 03/10
Uganda 30 30 0.7 03/20
French Guiana 28 6 22 94 03/06
Zambia 28 28 2 03/17
Barbados 26 26 90 03/16
Togo 25 1 1 23 3 0.1 03/05
El Salvador 24 +5 24 4 03/18
Bermuda 22 +5 2 20 353 03/17
Congo 19 +15 19 3 03/14
Ethiopia 19 +3 1 18 0.2 03/12
Mali 18 1 17 0.9 0.05 03/24
Niger 18 +8 1 17 0.7 0.04 03/18
Maldives 17 +1 11 6 31 03/06
Guinea 16 +8 16 1 03/12
Haiti 15 +7 1 14 1 03/19
New Caledonia 15 15 53 03/17
Djibouti 14 14 14 03/17
Tanzania 14 1 13 0.2 03/15
Equatorial Guinea 12 12 9 03/13
Mongolia 12 12 4 03/09
Dominica 11 11 153 03/21
Namibia 11 +3 2 9 4 03/13
Saint Martin 11 11 284 02/29
Bahamas 10 1 9 25 03/14
Greenland 10 2 8 176 03/15
Grenada 9 +2 9 80 03/21
Eswatini 9 9 8 03/13
Cayman Islands 8 1 7 122 15 03/12
Curaçao 8 1 2 5 49 6 03/12
Guyana 8 1 7 10 1 03/11
Laos 8 8 1 03/23
Mozambique 8 8 0.3 03/21
Myanmar 8 8 0.1 03/22
Seychelles 8 8 81 03/13
Suriname 8 8 14 03/12
Gabon 7 1 6 3 0.4 03/12
Zimbabwe 7 1 6 0.5 0.07 03/19
Antigua and Barbuda 7 7 71 03/12
Cabo Verde 6 1 5 11 2 03/19
Benin 6 6 0.5 03/15
Eritrea 6 6 2 03/20
Vatican City 6 6 7,491 03/05
Sudan 5 1 4 0.1 0.02 03/12
Nepal 5 1 4 0.2 01/23
Angola 5 5 0.2 03/19
Fiji 5 5 6 03/18
Mauritania 5 5 1 03/12
Montserrat 5 5 1,002 03/17
St. Barth 5 5 506 02/29
Syria 5 5 0.3 03/21
Nicaragua 4 1 3 0.6 0.2 03/18
Bhutan 4 +1 4 5 03/05
Saint Lucia 4 +1 1 3 22 03/12
Turks and Caicos 4 4 103 03/22
Gambia 3 1 2 1 0.4 03/16
CAR 3 3 0.6 03/14
Chad 3 3 0.2
03/18
Liberia 3 3 0.6 03/15
Libya 3 3 0.4 03/23
Sint Maarten 3 3 70 03/17
Somalia 3 3 0.2 03/15
MS Zaandam 2 2 03/26
Anguilla 2 2 133 03/25
Belize 2 2 5 03/22
British Virgin Islands 2 2 66 03/24
Guinea-Bissau 2 2 1 03/24
Saint Kitts and Nevis 2 2 38 03/24
Papua New Guinea 1 1 0.1 03/19
St. Vincent Grenadines 1 1 0 9 03/10
Timor-Leste 1 1 0.8 03/2
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