The so-called Covid “supermodel” commissioned by the Govt of India is fundamentally flawed.

Not surprising, since it was built by people who had no clue about epidemiology or public health (the Govt ignored the advice of *actual* public health experts).

See for yourself. Thread On 09/03/21 they explicitly predicted there would be no “second wave”.

OK, models can get their predictions wrong. Presumably, once it became clear there was a raging second wave, the model builders would admit their model was flawed, right?

Wrong.

What’s behind India’s second wave? A simple model can help us understand what’s going on.

There’s lots of variation between cities, so it’s best to look at a single city like Bangalore. Why did cases in Bangalore start to dip in Oct 2020? Why did they start to rise in Mar 2021? “R0” is the average number of new infections that would be caused by one infected individual, assuming nobody is immune. This depends both on behaviour and viral biology.

Let’s define the “level of caution” as the inverse of R0. Less cautious people cause more infections.

"The term community transmission means that the source of infection for the spread of an illness is unknown or a link in terms of contacts between patients and other people is missing." [Wikipedia]

The authorities seem confused about the definition: aninews.in/news/national/…

1/5 The novel coronavirus originated in Wuhan. So *every* case in India must have arisen, via a chain of contacts, from Wuhan. Therefore, *every* case in India involves an international traveller as part of the chain of infection. This is a matter of logic, not epidemiology.

2/5

In coming days, it's important for the public to know that experts looking at the same data can legitimately disagree.

E.g. Consider the debate about whether community transmission has begun. Due to Bayes' Theorem, the answer depends on what you already believe.

Thread.

1/9 Assume the ideal case: don't consider asymptomatic carriers, let test results be instant.

We test 1,000 symptomatic cases and all are negative. This means there's no community transmission right?

Wrong. To interpret the result, we need to make a bunch of assumptions.

2/9

Covid-19-positive cases in India (source:covidindia.org).

One active case on Mar 2nd. Then:

9 days to 50
5 days to 100
3 days to 150
1 day to 200

We are well into exponential growth, which strongly implies community transmission. This suggests a doubling every 2.5 days (i.e. exactly the 33% per day increase seen in other countries). Nothing special about India.

If this continues unabated, in 3 weeks the total number of positive cases will be 100,000, exceeding the total number of kits ICMR currently has.

I was shocked to see such shoddy journalism from @the_hindu. They spun a 3-month-old *open-access* paper into a "secret" conspiracy theory, without even requesting a statement from the authors! The report, even the headline, contained many false statements. A science journalist would have read the paper and spoken to the authors, rather indulging in speculation in the midst of a public health crisis. As @NCBS_Bangalore was not given a chance to respond, we have issued a clarification, covered by @1amnerd.
thewire.in/the-sciences/c…

In dogs, three genes *independently* determine if the coat is short or long, soft or wiry, and straight or curly! science.sciencemag.org/content/326/59…

This kind of "gene-for-X" story is actually very rare, despite what the news headlines often claim. So why is it true in this case? Knowing how cells work, it's not surprising most traits are "complex": they depend on 1000s of genes:
quantamagazine.org/omnigenic-mode…. Conversely, mutations in most genes are "pleiotropic": they affect 1000s of traits.

So when would we expect a single gene to control a single trait?

Indian science funding is stalling.

India has historically made large public investments in science. But now govt support is flat (in $) and decreasing per scientist (with PhD numbers as proxy). When government steps back, private entities will be able to set the agenda.

Thread There are many reasons the nominal cost of research goes up:

1. More scientists.
2. Inflation raises costs of supplies, salaries.
3. Cost of new technologies.

We can't just track inflation rate for bunsen burners: we need cryo-EMs and DNA sequencers too. New tech is expensive.

I've been searching for a good metaphor to explain what genes are. Hear me out. (No doubt, someone has thought of this before.) Think of an orchestra.

There are players -- these are the laws of physics and chemistry.

There's a symphony -- this is the organism.

Finally there are the instruments -- these are the genes.

Breaking news reports of the first genome-edited babies. If true, these are the first humans to be born with a deliberately edited germline (the inherited genome). They will be able to pass on these edited genes to their children. This is practice is outlawed in many countries.

https://twitter.com/EricTopol/status/1066887338964398081

Lots of focus on CRISPR "off-target effects" (when the target gene is edited, some other DNA might also be accidentally modified). This suggests that once this tech works without errors, we should go full steam ahead. Let me explain: bad tech is not why this is controversial. 2/n