(1/4) Brief 🧵on Mumbai's all cause mortality and COVID-19 infection fatality rate (IFR). 2020 data shows a huge 24% rise in mortality over the previous 5 year average. That's about 22K extra deaths in 2020. Of these about 11K were recorded COVID deaths.
portal.mcgm.gov.in/irj/portal/ano…
(2/4) We don't know exactly how many 2020 excess deaths were COVID deaths. These could range from the official 11K up to more than 22K, since there's evidence some kinds of mortality fell in 2020. Let's say COVID deaths in 2020 were between 11K and 24K.
(3/4) We don't know exactly how many infections occurred in 2020, but based on seroprevalence data and modelling, somewhere between 6.5M to 9M infections occurred in the city. That's between 50% and 70% of the population (~12.9M), if we assume reinfections were rare.
(4/4) We get estimates of COVID-19 IFR ranging from
- 0.12% (11K deaths, 9M infections) to
- 0.37% (24K deaths, 6.5M infections).
Taking median values (17.5K deaths, 7.75M infections) gives IFR=0.23%.

The values are largely consistent with age-stratified international data.

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More from @muradbanaji

23 Feb
This thread is troubling. Yes, India's data is interesting - let's acknowledge the complexities and uncertainties, but based on evidence and without wild claims. #thread
First of all, the premise of the thread - comparing recorded cases and deaths across countries is meaningless without acknowledging differences in surveillance. There's enough seroprevalence data to go beyond "cases"...
From the latest Indian survey, about 3.5% of infections have been detected (science.thewire.in/health/third-n…).

In the US, it's over 20% (cidrap.umn.edu/news-perspecti…).

So an India-US comparison of cases per million is highly misleading.
Read 20 tweets
6 Feb
For this piece, I tried to gather together some thoughts about the serosurvey data coming out of India. There is a great deal of this data, and the messages are important but not always clear. Longish #thread. 1/n
scroll.in/article/986097…
First, to see the bogus narratives you can construct when you ignore serosurvey data, you just have to look at Chapter 1 of the recent "Economic Survey". (This thread took just one example, but there are many.)
Key message from the serosurveys? Extremely variable surveillance of infections *and probably deaths*. In some places, a decent proportion of infections are picked up; in others a tiny fraction. Some areas have seen a huge number of infections, but almost no recorded deaths.
Read 16 tweets
5 Feb
My piece in The Wire on the third national serosurvey. The headline (~21% prevalence) is probably not a major underestimate. Apparently the antibody test used was less vulnerable to missing old infections than the one used in the second serosurvey. 1/6
science.thewire.in/health/third-n…
The increase in prevalence from 2nd to 3rd survey is roughly consistent with the increase in cases over this period.

The breakdown of prevalence suggests that disease was moving towards rural areas even as daily cases peaked and declined nationally (September). 2/6
Weaker rural surveillance of infections and deaths could explain a moderate drop in detection, and a more noticeable drop in the naive infection fatality rate (recorded deaths over estimated infections) between 2nd and 3rd national serosurveys. 3/6
Read 6 tweets
1 Feb
Chapter 1 of the Economic Survey 2020-21 (indiabudget.gov.in/economicsurvey/): a glowing report on the govt's handling of the COVID crisis, and a case study in what happens when science is abandoned for propaganda. Page after page of spin and dishonesty, but here's just one example... 1/5
...These two pictures show "actual vs. expected" cases and deaths for different states. Bihar does well (green) and Chhattisgarh does badly (red). Why? Because Bihar has fewer recorded COVID cases and deaths than "expected", and Chhattisgarh more than "expected". But... 2/5
I'd earlier examined data from Bihar and Chhattisgarh quite carefully for a piece in The Wire Science - measured cases, recorded deaths and, crucially, serosurvey data. The basic conclusions of this analysis were simple. In the surveyed districts... 3/5
science.thewire.in/health/bihar-c…
Read 5 tweets
31 Dec 20
Mumbai #COVID19 update. Things have improved - daily recorded cases and deaths are at about a quarter of second wave peak values. But there is still a steady stream of new infections. Mumbai's data forces us to ask: could reinfection be more common than we think? 1/10 Image
The recent picture:
- the second wave receded steadily, apart from a small post-Diwali blip
- daily cases, daily deaths and test positivity have all been declining
- but the epidemic is still not dying away. Image
Each day there are about 600 new cases. If we (optimistically) assume 1 in 10 infections are detected, and each infection is "active" for 10 days, that's 600X10X10 = 60,000 active infections = about 0.5% of the city. Low compared to May or September, but still surprisingly high.
Read 10 tweets
19 Oct 20
How many have had #COVID19 in Delhi? What % of infections have been detected? What is the fatality rate?

A (longish) #thread on Delhi's epidemic, with some analysis of its three serosurveys + other data. Details in a technical document linked at the end. (1/11)
First, Delhi's current surge (which may be winding down) is real - not just about better detection. But the actual surge in infections has been considerably smaller than in June - detection has increased a lot, making it seem larger. (Similar story to Mumbai - more later.) 2/
Prevalence estimate: by mid-August between 37% and 49% of Delhi people had had COVID. By mid-September: between 43% and 60%. The wide range reflects many uncertainties. When the October serosurvey results are out, we'll know more. (bloombergquint.com/coronavirus-ou…) 3/
Read 11 tweets

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