Herd immunity. It's surprising people are still being simplistic about this concept, even when the COVID-19 situation worldwide is so messy. In what way messy? Well:
- vaccines
- highly uneven spread (and vaccine coverage),
- movements of people, and
- variants.
So what?...
We've also got much more real world data and experience. We've seen arguments using complicated models go wrong: e.g., "the HIT in practice should be much lower than the theoretical value". Contradicted by high prevalence in many places, even before the arrival of variants.
We've also seen wrong arguments based on simple models: e.g. "there should be no major new outbreaks once the theoretical HIT is reached". Definitely not true when you have uneven spread. Easily shown with a two compartment model. Possibly being seen in practice in some places.
So what about variants? If a more transmissible variant comes to dominate, it raises R0 (and the HIT) and can push a locality previously above the HIT back below again - even if it isn't an "immune escape" variant able to bypass immunity developed against previous variants.
And if an immune escape variant becomes widespread? There are then more susceptible people again - and this too can push a locality below the HIT. It's not all or nothing - prior infection by other variants likely reduces overall transmission of the new variant - but how much?
And what about vaccines? We know they reduce severe disease and very likely reduce transmission. But does 70% vaccine coverage = 70% immunity? Generally no, but we don't know how much it does mean. The answer likely depends on which vaccine + which variants are circulating.
So, right now there are lots of questions to which "don't know" is the correct answer. No doubt people will write down models which take some of the complexities into account. But in the meantime let's just accept that we're seeing something very complex play out.
Finally, a replug of this explainer. There are a few things I would add - especially about variants - if I wrote it now (I might do an update). But I think it's still useful.
science.thewire.in/health/india-c…

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More from @muradbanaji

7 Apr
I keep doing threads on Mumbai's shocking COVID situation. Another longish one - sorry!
1) Active infection is at eye-watering levels.
2) Everything has happened fast, and things are not yet improving.
3) Modelling can't explain the current surge without new assumptions.
🧵
Before any details, a general point about modellers and models. They've got many things wrong during this pandemic. Some embarrassingly wrong. Models keep having to be rewritten. BUT models build and challenge intuition in a way data crunching alone can't - at least for me...
The models didn't find Mumbai's second wave (Sept-Oct 2020) surprising. They said weakening restrictions & uneven spread could cause such a surge. It hit nonslums harder than the first, and slums much less than the first (as expected). It added fewer infections than the first.
Read 20 tweets
5 Apr
When commenting for this piece by @soutikBBC, here are some things I noticed.
(1/4) Almost all regions are showing rapid exponential growth in cases at the same time.
(2/4) Places badly hit earlier (sometimes more than once) are being badly hit again.
(3/4) At the moment, there is no reason to believe that deaths are rising more slowly than expected from the rise in cases- when you take delays into account. Optimism is good, but not misplaced optimism.
(4/4) In districtwise data from @covid19indiaorg you often see the great majority of districts in a state surging together. This is clearest in log plots of recent data: Andhra Pradesh, Maharashtra, Gujarat and Punjab shown. (4 more districts in the next tweet.)
Read 4 tweets
2 Apr
It's hard to discuss COVID-19 in Mumbai without sounding alarmist. Because the situation is alarming. Calculations suggest:
- more people are being infected daily in housing societies than ever before
- transmission in slums could be close to the huge speeds of April-May 2020.
🧵
In the last week Mumbai has recorded 43K cases. But this figure is useless if we don't know how many infections are missed. I estimate:

43K cases = more than 7 lakh infections. That's >5% of the city. In one week.

Let's see how. [Notes on the numbers at the end.]
In the last week ~15% of tests returned +ve. (About half were rapid - if all had been more sensitive RT-PCR tests, positivity would be closer to 20%.) We know that as test positivity (TPR) rises, detection drops - the fraction of missed infections rises. Let's track back...
Read 10 tweets
28 Mar
Mumbai #COVID19 update. There has been a sharp rise in testing in Mumbai over the last 4 days. This has stabilised test positivity (weekly averages), but not yet brought it down. About half of the tests are now rapid tests, up from ~30% earlier. (1/6)
Cases and deaths. Cases are doubling roughly every week at the moment (partly, perhaps, about the rise in testing). In the last two weeks deaths have also been rising - doubling roughly every two weeks (the relatively low numbers mean there's a lot of uncertainty). (2/6)
In the past week, the slum epidemic seems to be growing faster - estimated case doubling times have been lower in the slums. This is a worrying trend - we've seen before how a nonslum surge sparks a faster slum surge. (These are estimates based on examining ward-wise data.) (3/6)
Read 6 tweets
26 Mar
#COVID19 in Punjab. Are we seeing effects of widespread circulation of the more lethal "U.K. variant" (B.1.1.7) in Punjab? (thehindu.com/news/national/…).

Yes, I think so. Apparently this variant could be ~64% more deadly (medicalnewstoday.com/articles/covid…).

#thread (1/6)
Fatalities in Punjab seem to lag cases by about 17 days - that's something of an educated guess since there's a lot of noise in the data. Here's the 17-day delayed CFR in Punjab since the start of the year. It is an astonishing picture. What does it show? (2/6) Image
Through January the delayed CFR hovered between 2 and 3. Since late April it's hovered around 5. A *very clear* change. This could be the effect of increased circulation of the more lethal variant. An alternative explanation also needs to be looked at... (3/6)
Read 6 tweets
22 Mar
Data from Mumbai's latest COVID-19 wave is suggesting that reinfections are important and/or a more transmissible variant is circulating. Here's why. (A slightly technical thread, assumptions and possible objections at the end.) (1/n)
First, the argument in brief: current spread is just too fast. The speed is at odds with levels of prior infection in the city and what we know about R0 - the basic reproduction number in the city - based on the earliest availale data.
The current doubling time for daily cases (weekly average) is ~8 days. With TPR also rising sharply, the true doubling time for infections may be shorter. With standard assumptions, we get R = ~1.57. Estimated cases from slums and nonslums give roughly the same R value in both.
Read 16 tweets

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