Using the "Our Word in Data" website we have extracted the latest snapshot for each country of total vaccinations per hundred people and total 'covid deaths' per million. The full data by country - in order of vaccinations - is listed at the bottom of this page (all numbers rounded to 0 decimal places).
We use inverted commas for 'covid deaths' because (as readers of this blog will know) this is a very vague metric and we have no confidence that it is accurate or consistently collected for any country in the world. If the data were accurate, and if the vaccines worked as claimed, then what we should see when we plot the vaccinations against deaths is something like this:
i.e. the more vaccinations in a country the fewer deaths.
Obviously there are multiple confounding factors (other than inconsistent reporting) that can impact on the relationship (timing when covid first hit, average population age, population density, geographial location, access to healthcare, etc) not to mention all the missing factors previously discussed**. Ideally the deaths should also be restricted to post-vaccination roll out (difficult to do that using the Our World in Data spreadsheet). But it is still surprising that the following is the actual plot:
All pretty random*** but note the high number of low vaccination, low covid death countries (mainly in Africa) as shown in this map:
But what it really shows more than anything is how poor all the 'official' covid data are (look at the laughable China data) and, because of the universally poor data, how little evidence there is of either the severity of Covid or the effectiveness of any covid interventions.
**As we have been saying since March 2020 all of the 'official' Covid data are essentially useless because they do not provide us with the necessary information to take account of all of the causal explanations for what is observed:
Country | total vaccinations per hundred | total deaths per million |
Gibraltar | 322 | 2968 |
Cuba | 268 | 735 |
Chile | 230 | 2035 |
United Arab Emirates | 224 | 216 |
Iceland | 209 | 108 |
Denmark | 209 | 560 |
Isle of Man | 208 | 784 |
Malta | 208 | 922 |
South Korea | 202 | 111 |
Uruguay | 200 | 1771 |
China | 197 | 3 |
Cayman Islands | 196 | 165 |
Faeroe Islands | 196 | 285 |
United Kingdom | 195 | 2181 |
Ireland | 194 | 1186 |
Portugal | 191 | 1864 |
Belgium | 186 | 2434 |
Seychelles | 185 | 1324 |
Bahrain | 185 | 797 |
Spain | 184 | 1909 |
Italy | 184 | 2278 |
France | 183 | 1830 |
Austria | 182 | 1520 |
Bermuda | 182 | 1707 |
Canada | 181 | 798 |
Israel | 180 | 887 |
Cambodia | 180 | 178 |
Brunei | 179 | 222 |
Germany | 178 | 1336 |
Norway | 178 | 239 |
Qatar | 178 | 211 |
Malaysia | 176 | 961 |
Singapore | 175 | 149 |
Finland | 175 | 282 |
Sweden | 173 | 1507 |
Cyprus | 172 | 698 |
Argentina | 168 | 2569 |
Greece | 167 | 2005 |
Australia | 165 | 88 |
Luxembourg | 165 | 1429 |
Liechtenstein | 165 | 1804 |
Mongolia | 161 | 619 |
Kuwait | 160 | 570 |
Mauritius | 160 | 188 |
New Zealand | 160 | 10 |
San Marino | 159 | 2793 |
Japan | 158 | 146 |
Switzerland | 158 | 1397 |
Sri Lanka | 158 | 698 |
Hungary | 156 | 3934 |
Netherlands | 155 | 1193 |
Brazil | 155 | 2894 |
Turkey | 155 | 968 |
Lithuania | 154 | 2752 |
United States | 153 | 2476 |
Aruba | 153 | 1689 |
Ecuador | 153 | 1881 |
Vietnam | 151 | 322 |
Costa Rica | 151 | 1429 |
Andorra | 150 | 1719 |
Bhutan | 148 | 4 |
Peru | 148 | 6071 |
Thailand | 147 | 309 |
El Salvador | 147 | 585 |
Taiwan | 146 | 36 |
Maldives | 145 | 482 |
Saudi Arabia | 144 | 251 |
Czechia | 144 | 3374 |
Turks and Caicos Islands | 144 | 586 |
Fiji | 140 | 772 |
Slovenia | 140 | 2693 |
Greenland | 138 | 18 |
Iran | 137 | 1545 |
Latvia | 137 | 2443 |
Morocco | 135 | 397 |
Panama | 135 | 1696 |
Anguilla | 134 | 264 |
Curacao | 132 | 1147 |
Hong Kong | 132 | 28 |
Dominican Republic | 129 | 388 |
Monaco | 126 | 835 |
Colombia | 126 | 2533 |
Poland | 124 | 2581 |
New Caledonia | 123 | 971 |
Antigua and Barbuda | 123 | 1195 |
Serbia | 120 | 1840 |
British Virgin Islands | 118 | 1282 |
French Polynesia | 116 | 2251 |
Nicaragua | 116 | 32 |
Croatia | 116 | 3072 |
Oman | 116 | 787 |
Uzbekistan | 115 | 44 |
Estonia | 115 | 1458 |
Mexico | 114 | 2299 |
Slovakia | 112 | 3046 |
Azerbaijan | 111 | 818 |
Wallis and Futuna | 108 | 631 |
Belize | 105 | 1462 |
Venezuela | 105 | 183 |
India | 104 | 346 |
Barbados | 104 | 904 |
Saint Kitts and Nevis | 102 | 523 |
Cape Verde | 102 | 625 |
Tunisia | 102 | 2141 |
Indonesia | 101 | 521 |
Montenegro | 101 | 3844 |
Russia | 101 | 2080 |
Trinidad and Tobago | 100 | 2054 |
Rwanda | 99 | 102 |
Philippines | 98 | 463 |
Guyana | 97 | 1318 |
Honduras | 95 | 1037 |
Paraguay | 95 | 2301 |
Kosovo | 94 | 1678 |
Kazakhstan | 92 | 959 |
Botswana | 92 | 1020 |
Timor | 89 | 91 |
North Macedonia | 84 | 3752 |
Romania | 83 | 3072 |
Suriname | 83 | 2009 |
Bolivia | 82 | 1661 |
Belarus | 82 | 570 |
Albania | 81 | 1116 |
Jordan | 80 | 1205 |
Bangladesh | 80 | 169 |
Laos | 79 | 19 |
Bahamas | 76 | 1796 |
Nepal | 74 | 390 |
Pakistan | 70 | 128 |
Grenada | 69 | 1770 |
Ukraine | 65 | 2354 |
Lebanon | 65 | 1350 |
Tajikistan | 64 | 13 |
Palestine | 63 | 932 |
Georgia | 63 | 3457 |
Guatemala | 62 | 883 |
Sao Tome and Principe | 62 | 255 |
Montserrat | 61 | 201 |
Comoros | 59 | 170 |
Myanmar | 58 | 350 |
Saint Lucia | 57 | 1600 |
Saint Vincent and the Grenadines | 55 | 728 |
Armenia | 55 | 2676 |
Bulgaria | 54 | 4492 |
Egypt | 51 | 207 |
Vanuatu | 49 | 3 |
Zimbabwe | 48 | 332 |
Bosnia and Herzegovina | 48 | 3590 |
South Africa | 46 | 1515 |
Mozambique | 46 | 62 |
Moldova | 44 | 2556 |
Jamaica | 41 | 833 |
Libya | 39 | 819 |
Iraq | 34 | 586 |
Angola | 34 | 52 |
Eswatini | 34 | 1102 |
Kyrgyzstan | 34 | 423 |
Lesotho | 32 | 308 |
Equatorial Guinea | 31 | 121 |
Namibia | 29 | 1398 |
Algeria | 28 | 139 |
Togo | 28 | 29 |
Gabon | 25 | 125 |
Ghana | 24 | 40 |
Congo | 23 | 63 |
Guinea | 21 | 29 |
Uganda | 21 | 69 |
Guinea-Bissau | 21 | 74 |
Djibouti | 20 | 189 |
Kenya | 18 | 98 |
Cote d'Ivoire | 18 | 26 |
Liberia | 17 | 55 |
Central African Republic | 16 | 21 |
Benin | 14 | 13 |
Senegal | 13 | 110 |
Afghanistan | 13 | 183 |
Sudan | 12 | 72 |
Sierra Leone | 11 | 15 |
Gambia | 11 | 138 |
Syria | 10 | 156 |
Ethiopia | 9 | 59 |
Somalia | 9 | 81 |
Zambia | 9 | 197 |
Malawi | 9 | 120 |
Nigeria | 7 | 14 |
Papua New Guinea | 6 | 65 |
Mali | 5 | 32 |
Burkina Faso | 5 | 15 |
Tanzania | 4 | 12 |
Niger | 4 | 10 |
Cameroon | 4 | 67 |
Madagascar | 3 | 34 |
Yemen | 3 | 64 |
South Sudan | 2 | 12 |
Chad | 2 | 11 |
Haiti | 2 | 66 |
Burundi | 0 | 3 |
Mozambique | 0 | 22 |
***For those who place value in correlation coefficients for such relationships (we don't) there is a significant positive correlation of 0.31 between number of vaccines and number of deaths
Correlation coefficient may not give one too much information, but I would LOVE to see the strength of a correlation between total vaccination to date and total excess mortality.....
ReplyDelete£50 to your favourite charity that the correlation will be stronger.
A very good idea. I hope Dr. Fenton obliges.
DeleteBolgger Orwell2024 did have a look at excess deaths and vaccination, Eva Smagacz - Michael Levitt praised this work:
ReplyDeletehttps://orwell2024.substack.com/p/age-adjusted-all-cause-mortality?r=zp558&utm_campaign=post&utm_medium=web
Excellent analysis as usual
ReplyDeleteAs you have repeatedly stated in several of your analyses published on this blog, the only objective metric that can and should be used to determine the efficacy, or lack thereof, of a particular vaccine is all-cause mortality. It is for this very reason, data regarding all-cause mortality, not just in relation to the covid vaccines, but to many other vaccines in the past, are typically suppressed or obfuscated (e.g. released in a form susceptible to confounding by other factors). However, truth has a tendency to emerge, even inadvertently, in some form or another. The analyses published on this blog is hitting extremely close to that truth despite the intentional suppression and obfuscation of crucial data, the proper disclosure and transparency of which would've obviated the need for such excellent analyses.
ReplyDeleteTake, for example, the DTP (diphtheria, tetanus, pertussis) vaccine, which is amongst the most widely and frequently administrated vaccine in the past century. In 2017, a team of doctors and scientists found a unique opportunity to carry out a natural experiment in Africa in order to determine the effectiveness of the DTP vaccine purely in terms of all-cause mortality.
The study was well-designed and thorough, and free from biases that had plagued (often intentionally so) previous studies of this nature, such as the "healthy user bias" (i.e. people who were too frail and ill to take a vaccine would automatically fall into the unvaccinated group and thus affect the results in favour of the vaccinated).
The results were shocking, to say the least.
Although, the DTP vaccine was successful in reducing incidences of Diptheria, Tetanus and Pertussis in the vaccinated group, which is traditionally the only metric used to determine vaccine efficacy, the vaccine was also "successful" in increasing all-cause mortality by a factor of 10!
Combined administration of DTP with the oral polio vaccine, while again "successful" in reducing incidences of the target diseases, was also "successful" in increasing all-cause mortality by a factor of 5.
Dr Peter Aaby, one of the authors of this study and amongst the leading vaccine experts in the world, was constrained to admit candidly:
“All currently available evidence suggests that DTP vaccine may kill more children from other causes than it saves from diphtheria, tetanus or pertussis.”
Please refer to Mogensen et al, 2017,
"The Introduction of Diphtheria-Tetanus-Pertussis and Oral Polio Vaccine Among Young Infants in an Urban African Community: A Natural Experiment."
The parallels with these Covid vaccines are clear, although it may even be debatable whether or not they successfully reduce incidences of the target disease, Covid. Nevertheless, all-cause mortality should ALWAYS (though, in practice, it is never) be the only metric to determine the true efficacy of a particular vaccine.
It's more than a few childhood vaccines that have been associated with increased all-cause mortality. And multiple studies of DTP done different ways have all found increased mortality. There is even a second "natural experiment" published like the one you mention. You are right that these are really the best types of studies. A sad situation. Perhaps in another 30 years there will be some semblance of justice for all this.
DeleteAt last someone tells it like it really is. I'm a scientist myself and am baffled by how many simply ignore the real data. Congratulations, now if the Gove just listens to you.
Delete"Perhaps in another 30 years there will be some semblance of justice for all this."
DeleteI hope you're right, but so long as the entire industry, from top to bottom, continues to be rigged with conflicts of interest, as it is currently, any semblance of justice for the millions, possibly billions, of collateral casualties of this brutally ruthless industry will remain a pipedream.
At first glance, this (Aabey et al) is a troubling study, but it also raises some questions. Why is the mortality rate of boys so much higher than that of girls? Why do the reported mortality rates not correspond to the official ones? Why are sick children not counted among the non-vaccinated, even though it is not at all clear that they were not vaccinated in principle? Is it at all meaningful under these conditions (extremely high infant mortality, very small number of subjects.ie. few deaths)?
DeleteHi Anonymous:
Delete1) Boy mortality is higher because it kills more boys than girls. Sex-differences with vaccines is not a new thing. For example, myocarditis may be more common after covid vaccines with men than women. If you read measles studies, what you will find is measles appears to cut boy mortality more than girls. Just the opposite. I think this is in part because the kids visibly harmed by earlier DTP are not given measles vaccines months later because their parents no longer trust vaccines. Then some of those kids die from earlier DTP harms, are counted in a control group, and make measles vaccine look like it has huge all-cause mortality benefit, but especially in boys.
2) Not sure I understand the question.
3)That study is a natural experiment that only includes vaccinated children. There are no unvaccinated children. Children's "unvaccinated time" is being compared to "vaccinated time". In a sense, vaccinated children are being compared to themselves at different times. This is the beauty of such a design because it eliminates the classical selection biases that happen if you have an unvaccinated control group.
4) Extremely high infant mortality is precisely were DTP would be dangerous. It makes you more likely to die of other infections, so the increased mortality shows up where other deadly infections are going around. Yes, small numbers and deaths are an issue. But a second natural experiment confirmed similar results. Plus all the least biased earlier cohort and case-control studies found the same thing. Different methods, all same signal. It means it's almost certainly true.
Would it be possible to do a "Total Covid deaths per million" VS "Total excess deaths per million" graph. And also a "Total excess deaths per million" VS "Total deaths per million". I understand that all data is poor, but as soon as I read your article it came to my mind what would look like if we had also the excess deaths. Thanks. Regards
ReplyDeleteI wonder if such a graph could tell us about which countries are the worst offenders in terms of misclassifying non-covid deaths as covid deaths?
DeleteThe central African nations are less affected by Covid because the IFR of Covid is exponential with age, about a factor of 10 increased mortality per 20 years of age, and the median age in that region is about 20 years, while in Europe it is 40 years. That means I'd expect the mortality impact of Covid on Africa is ten times less than in Europe. And obviously the central African nations have a lot of more severe medical and health problems than Covid (poverty, hunger, water, etc...).
ReplyDeleteIf one adds time into consideration, as one should, pondering Covid-19 deaths 14 days later and how the relationship vaccines vs. future deaths evolves, the picture is actually one where it seems that more Covid-19 vaccination actually leads to more Covid-19 deaths.
ReplyDeleteJust plot time (days), daily vaccination rates, and deaths 14 days later. Then do a surface fit (Linear, for simplicity, or something like a Spline to better "hug" the data points). One finds that deaths decrease with time and actually INCREASE with vaccination.
I posted a graph in response to your tweet.
Recently I thought I'll have another look at Alfred Russel Wallace's brilliant (19th century) exposé of the smallpox vaccination racket, entitled, " Vaccination a Delusion: It’s Penal Enforcement a Crime."
ReplyDeleteI recall that the very same ploys employed by the vaccine industry which the author so expertly uncovered more than a century ago were still at play with many modern vaccines. The covid versions today have simply taken this fraud to new levels.
I found an online version of the book on the Gutenberg website. When I clicked the link to the book, I was immediately struck by the author’s preface. Notice how much of it bears an uncanny resemblance and relevance to our predicament today:
Vaccination a Delusion
Its Penal Enforcement a Crime:
PROVED BY THE OFFICIAL EVIDENCE IN THE REPORTS
OF THE ROYAL COMMISSION
BY
ALFRED RUSSEL WALLACE
PREFACE
This Essay has been written for the purpose of influencing Parliament, and securing the speedy abolition of the unjust, cruel, and pernicious Vaccination laws. For this purpose it has been necessary to speak plainly of the ignorance and incompetence displayed by the Royal Commission, proofs of which I give from their “Final Report” and the evidence they have collected and printed.
I most solemnly urge upon our Legislators that this is a question not only of the liberties of Englishmen, but one affecting the lives of their children, and the health of the whole community; and that they will be individually responsible if they do not inquire into this matter for themselves,—not accept the statements or opinions of others.
In order that they may do this with a minimum expenditure of time and labour, I have put before them the essential facts, in almost every case taken from the Reports of the Royal Commission or of the Registrar-General, and with references to page, question, or paragraph, so that they can themselves verify every statement I make.
I thus abundantly prove, first, that in all previous legislation they have been misled by facts and figures that are untrue and by promises that have been all unfulfilled; and that similar misstatements have characterised the whole official advocacy of Vaccination from the time of Jenner down to this day. I claim, therefore, that all official statements as to Vaccination are untrustworthy.
I then show that all the statistics of small-pox mortality, whether of London; of England, Scotland, and Ireland; of the best vaccinated Continental States; of unvaccinated Leicester; or of the revaccinated Army and Navy, without any exception, prove the absolute inutility of Vaccination; and I feel confident that every unprejudiced person who will carefully read these few pages, and will verify such of my statements as seem to them most incredible, will be compelled to come to the same conclusion.
I appeal from the medical and official apologists of Vaccination to the intelligence and common sense of my fellow-countrymen, and I urge them to insist upon the immediate abolition of all legislation enforcing or supporting this useless and dangerous operation.
Fascinating !
ReplyDeleteThanks for posting this informative blog! I am an online class help expert and have been looking for this topic as I needed proper graphs and figures. This blog is really well written and helped me out.
ReplyDelete