Who were the very first to be vaccinated against COVID-19?

Recently, and gladly, vaccination campaigns against COVID-19 are popping up around the world. The first person to be vaccinated is mostly a political choice, a great opportunity to pass a message to the population. After seeing the first images of UK, Europe and Brazil, I got interested in looking for who received the first injection in every country. Until the day I gathered the data, the average first recipient is a 64-years-old retired woman. Next, I present in details my small research.

The methodology is quite simple: from the Our World In Data database, I got the countries that were already vaccinating (55 at the time). This list was enough to direct my research on the web for news and official statements indicating the first person to be vaccinated on every country. In the case of ambiguity or simultaneous vaccination, like for Costa Rica (Elizabeth Castillo Cervantes, 91 years old, and Jorge De Fort Almetlla, 72) or Luxembourg (Catarina Fernandes, 40, and Kevin Nazzaro, 28), I simply selected the first name or photo that appeared in most of the articles. I cataloged the vaccination date, the vaccine that was used (Pfizer/BioNTech, Sinovac, etc), name, age, occupation and sex of the first vaccine recipient. I’ll focus on the latter characteristics, complete list is available on the end of this post so whoever is interested can also analyze and expand the database.

Of course this does not really represent the first person to be ever vaccinated against COVID-19 in any given country, as it ignores the testing phases and only open, publicized ceremonies are taken into account, however, it represents a part of the image each country populations’ will associate to the vaccine. By looking at the age and occupation of the recipients, we get a pretty prospect of what is happening.

Graph presenting the age and occupation of first recipients of COVID-19 vaccine by country

The diversity of first COVID-19 vaccine recipients

Two main groups were clearly vaccinated first (for this analysis, database is reduced to only countries which age of the recipient was found): people at higher risk (15 in 36, 41.7 %), mostly living in care facilities, and nurses (10, 27.8 %). Front-line workers in general were 14, 38.9 % of the database. Government officials were 19.4 % of the first to be inoculated, including Israel’s Prime Minister Benjamin Netanyahu and Seychelles’ President Wavel Ramkalawan, in an effort to give an example to the population. Younger recipient was Jelena Rozinko, a 24-years-old medical resident from Estonia; oldest recipient was german citizen Edith Kwoizalla, at 101 years old. In terms of geography, Europe is ahead, with 38 of the 55 countries that had already started vaccination at the time of my research.

As I was expecting, there is an important skewness in the age of the recipients, with 52.8 % of them being older than 60 years old. Such distribution of recipients is far from being a reflect of world’s population.

Histogram chart presenting the age distribution of first recipients of COVID-19 vaccine by country

Comparison of world’s age structure and age distribution of first vaccine recipients

Although the reference values, from the United Nations’ World Population Prospects, do not really represent the age structure of the countries that started vaccinating until the time I did my research (mostly European nations), the recipients are way more concentrated at the right of the graph. The elderly are more affected by the disease and also more prone to occupy I.C.U.s beds (compared to 18-29 years old, there is 5 times more risk to hospitalization and 90 times more risk of death when one is 65 years old or older), thus, it is in everybody’s interest that they get the first vaccine doses. Many countries are following this logic in their vaccination campaigns as well.

Another interesting aspect of the dataset is the occurrence of way more females than males. There is an easy explanation to why women were more present at the ceremonies that launched the vaccination campaigns. Most represented societal groups are nurses and older adults. In both of these groups women are more numerous than men. Considering the average of several countries’ female to male ratios, data from the World Health Organization, women are almost 80 % of global nursing personnel.

Bar chart presenting the sex ratio of first recipients of COVID-19 vaccine

The preponderance of females among the first recipients of COVID-19 vaccines

Vaccines are a stunning example of our scientific capacities and of human endeavor. I am by far not instructed to discuss diseases or vaccination policies, this is just a first look at a reduced and not so meaningful database. I hope it got you interested and that everybody get their doses as fast as possible. If you find any mistake or have any suggestion or comments, please contact me!

Database

Table with the information of the first vaccine recipients is presented next. I was not able to find any info for some of the countries (Bahrain, China, Russia, Saudi Arabia and United Arab Emirates), and for a significant part of them the age and name of the recipient was apparently not disclosed. Links were accessed between January 19 and 21.

country date name sex age occupation source
Argentina 29/12/20 Juliana Torquati female nurse link
Austria 27/12/20 female 84 retired link
Bahrain
Belgium 28/12/20 Jos Hermans male 96 retired link
Brazil 17/01/20 Monica Calazans female 54 nurse link
Bulgaria 27/12/20 Kostadin Angelov male 43 health minister link
Canada 14/12/20 Gisele Levesque female 89 retired link
Chile 24/12/20 Zulema Riquelme female 46 nurse link
China
Costa Rica 24/12/20 Elizabeth Castillo Cervantes female 91 retired link
Croatia 27/12/20 Branka Aničić female 81 retired link
Cyprus 27/12/20 Anastasios Tsiftsis male medical doctor link
Czechia 27/12/20 Andrej Babis male 66 prime minister link
Denmark 27/12/20 Leif Heiselberg male 79 retired link
England 08/12/20 Margaret Keenan female 90 retired link
Estonia 27/12/20 Jelena Rozinko female 24 medical doctor link
Finland 27/12/20 Andrea Nummi female nurse link
France 27/12/20 Mauricette female 78 retired link
Germany 27/12/20 Edith Kwoizalla female 101 retired link
Gibraltar 10/01/20 Dr Krishna Rawal male medical doctor
Greece 27/12/20 Efstathia Kambissiouli female nurse link
Hungary 27/12/20 Adrienne Kertesz female medical doctor link
Iceland
India 16/01/20 Manish Kumar male 34 sanitation worker link
Ireland 29/12/20 Annie Lynch female 79 retired link
Israel 19/12/20 Benjamin Netanyahu male 71 prime minister link
Italy 27/12/20 Claudia Alivernini female 29 nurse link
Kuwait 24/12/20 Sheikh Sabah Al-Khalid Al-Sabah male 67 prime minister link
Latvia 28/12/20
Lithuania 27/12/20 Nijole Ramonaite female nurse link
Luxembourg 28/12/20 Catarina Fernandes female 40 nurse link
Malta 01/01/21 Mary Pizzuto female 94 retired link
Mexico 24/12/20 María Irene Ramírez female 59 nurse link
Netherlands 06/01/20 Sanna Elkadiri female 39 nurse link
Northern Ireland 08/12/20 Joanna Sloan female nurse link
Norway 27/12/20 Svein Andersen male 67 retired
Oman 27/12/20 Ahmed bin Mohammed Al Saidi male health minister link
Poland 27/12/20 Alicja Jakubowska female nurse link
Portugal 27/12/20 António Sarmento male 65 medical doctor link
Romania 27/12/20 Mihaela Anghel female 26 nurse link
Russia
Saudi Arabia
Scotland 08/12/20 Melissa Sheppard female nurse link
Serbia 24/12/20 Ana Brnabic female 45 prime minister link
Seychelles 10/01/21 Wavel Ramkalawan male 59 president link
Singapore 30/12/20 Sarah Lim female 46 nurse link
Slovakia 26/12/20 Vladimir Krcmery male 60 medical doctor link
Slovenia
Spain 27/12/20 Araceli Hidalgo female 96 retired link
Sweden 27/12/20 Gun-Britt Johansson female 91 retired link
Switzerland 23/12/20 female 90 retired link
Turkey 13/01/21 Fahrettin Koca male 56 health minister link
United Arab Emirates
United States 14/12/20 Sandra Lindsay female 26 nurse link
Wales 08/12/20 Craig Atkins male 48 nurse link

Data was treated in Python using pandas library, plots were generated using matplotlib and seaborn(for the swarm plot only). Code for generating the plots and CSV files of the 3 databases used in this analysis are available for download here and in my GitHub. World population database is made available by the United Nations under license CC BY 3.0 IGO; gender distribution of health workers comes from the Worlds Health Organization under CC BY-NC-SA 3.0 IGO license. In what concerns my data, field source indicates one of the reference pages used to confirm the identity of the first receiver; date of access is given just before, in the accessed column.