It included the first instance of a day of >10 million vaccinations, in a week where the worst weekday was 5.6 million. This new chart reports daily number for the past 3 months broken into buckets:
2/
This new chart was necessitated by the fact that every day is now over 5m. 4 weeks of August are:
19 days >5m
5 days of 4-5m
4 Sundays
The data above 5m is so frequent and varied that it does not work as a single bucket anymore.
3/
This was also the best month ever. Currently at 162 million with three more days to go. There’s a Sunday and Krishna Janmashtami, so the government appears to have worked hard to get nearly 20 million doses done just on Fri+Sat.
4/
India only started general vaccinations on March 1. Until then, like several countries including Japan, India only vaccinated the healthcare and frontline workers. Since the start of general vaccinations, here are the numbers to date:
5/
The data is even more revealing looking at performance since beginning of June - India significantly outperforms the European Union and United States combined, and is close to EU + North America combined.
6/
With 630 million doses done, over 50% of adult population - 485 million - have a single dose. Nearly 150 million are fully vaccinated, a number that will rise significantly in the next few weeks as a large number of June first doses become eligible.
7/
September should see the fully vaccinated count increase by 100 million, even as total vaccinations for that month remain on track to exceed the 200 million mark based on early production estimates, with SII alone indicating 200m output.
8/
August should end with 640-650 million cumulative, with September estimated to add another 200m+ . Given successive months of over-delivering on promises (131m vs 120m in July, 162m+ vs 150m in Aug), one can make their own guesses for September performance.
9/
September has significant upside surprise potential due to potential availability of new vaccines like Corbevax, which could result in a monthly total near quarter billion, i.e. vaccinating an entire Japan every 2 weeks.
And of course, all of these are Made in India.
10/10
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The IPL is also far more lucrative in revenue per game, despite the fact that with a mere 74 games, it’s in the bottom 5 of sports leagues by number of games played per season.
Each of those games is a money spinner. Let’s look at how much.
2/
In terms of total revenue, the IPL ranks a reasonable 13th position among global leagues, despite having so few games in a single season.
There are only three countries on the planet with $1 trillion+ exports - China, USA and Germany. Even Japan is around $850-900B in FY 2021.
India jumped ~10 ranking places to provisionally #8 this year. Positions 4-7 are Japan, UK, France and Netherlands - all $700-900B.
India began 1949 the 9th biggest exporter.
It left the top 10 by end of that year.
It left the top 20 in 1957.
It reentered the top 20 in 2010, but didn't rise further until 2017-18 when it was 18th ranked. 2021-22 saw a big jump to 8th position.
Today was a day of symmetry as the vaccination total hit 175 crore (1.75 billion), exactly on day 400 since start of vaccination. This corresponds to an average of almost 4.4 million vaccinations a day, over four hundred days.
The monthly total to date is now almost 88 million. February should easily cross 100 million and will likely finish at around 125 million. This is expected as it is predominantly second dose + boosters. March will be much higher as the 12+ group becomes eligible.
2/
With even the second dose numbers not very high now, the daily average over the past week was just 4 million - multiple days towards the end of week being around 3.98 million, and thus still in the 3.x bucket.
So how do you fix sampling error ? You get a small number of people to agree - keeping pop standard deviation down because sample size is tiny.
Disagreement is a problem - if you get half of them to disagree, your sampling error is 20-45% depending on sample size. Oops.
2/
So let us pretend these experts indeed know what they’re doing. Let us look at the data. This author has the entire VDem dataset, analyzed in detail together with @jai_menon :