Youyang Gu Profile picture
Oct 1, 2020 9 tweets 3 min read Read on X
If you're under 50, your odds of dying if you contract COVID-19 is ~0.013% or 1 in 8000. This is similar to the odds of dying in a car accident in a year.

BUT many infected people will go on to infect others. In this thread I'll explain why we cannot treat the two risks equally.
The current Rt for the SARS-CoV-2 virus in the US is ~1. This means that an infected person will infect, on average, 1 other person. That person will infect another, and so on.

After 3 months, ~20 people will have been infected that can be indirectly attributed to the 1st case.
If Rt increases to 1.2, then 130 people will have been infected after 3 months. All stemming from 1 infection.

The chance that at least 1 person among the 130 will die is non-trivial (~50%).

That's why we need to view COVID-19 as a *community risk*, not an *individual risk*.
If you are young and healthy, then yes, you will most likely not die if you contract COVID-19. If you transmit it to someone else, chances are they will survive too.

But what about the next person? Or the one after that? They may not be as young as you.

So I hope we can all agree that we can do a better job of protecting ourselves and others.

If simple actions such as wearing a mask can reduce even a single infection, that can stop a whole chain of transmission. There is widespread scientific consensus:

cdc.gov/coronavirus/20…
While I used average Rt for this simple example, in reality, a minority of infected individuals are responsible for the majority of transmissions.

This is a phenomenon called overdispersion, as @zeynep explains this in her recent Atlantic piece: theatlantic.com/health/archive…
Due to this superspreading nature of the virus, effective contact tracing is key to mitigating the spread by tracking down superspreader events and notifying the exposed contacts in a timely manner.

Targeted testing and fast turnarounds are crucial.

So to conclude, we should not be thinking about Covid risks from an individual perspective, but rather from a community perspective. Our actions directly and indirectly affect those around us.

If I was able to change just one person's view with this thread, then it was worth it.
UPDATE: I find it interesting that my most controversial Tweet was "we can all do better to protect ourselves and others, such as wearing masks."

A common response? "But lockdown kills."

The two are not remotely related and it has shown how polarized our beliefs have become.

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More from @youyanggu

Aug 5, 2021
People were worried cases would spike further when the UK lifted almost all remaining restrictions in July. The opposite happened.

We must acknowledge that restrictions aren't all that effective in Western countries.

(Except Australia, who just entered their 6th lockdown)
It's interesting that some experts would rather question the accuracy of the data than acknowledge this reality.
Many bad papers looked at these curves in 2020 & concluded that more restrictions is followed by a decline in cases, when the decline would've happened regardless.

If we apply the same flawed logic here, one can say that the lifting of restrictions is followed by fewer cases.
Read 6 tweets
Jul 22, 2021
Thanks @ScottGottliebMD! On data, research & messaging, there’s lots of room for improvement at the CDC.

For modeling, they were right in enlisting @reichlab to run Forecast Hub: cdc.gov/coronavirus/20…

They’ve crowdsourced 30+ teams for weekly updates.

Of course, the modeling isn’t perfect & never will be. But this ensemble of forecasts coming from 250+ researchers has helped add clarity for many over the past year.

The CDC deserves credit for taking a conscious, hands-off approach on this.

technologyreview.com/2021/05/28/102…
That said, I do think there's too much focus on modeling cases/deaths. For ex, I've haven't seen many efforts on vaccination forecasts or infections/immunity estimates.

There may be some reluctance in the general scientific community to do this, so it's hard to blame one entity.
Read 4 tweets
Jul 1, 2021
On its last model update on March 5, 2021, covid19-projections.com projected that 180 million people in the US will be vaccinated by July 1 (1+ dose).

Today, July 1, @CDCgov reported that the US surpassed 180M people vaccinated.

Not all models are bad.

covid19-projections.com/path-to-herd-i… Image
Since I began making vaccination projections in Dec 2020, I have consistently predicted a return to normal by Summer 2021.

Some said it was too optimistic, others too pessimistic.

It appears that as of this week, all states (minus HI) are fully reopen.

ImageImage
Of course, this is a new normal - we will never return to pre-pandemic normal.

The Delta variant will be around. People will still be infected, even among the vaccinated.

But that's expected. Efforts must continue to focus on vaccinating the vulnerable population.
Read 4 tweets
Jun 30, 2021
South Dakota has a vaccination rate of 50% (1+ dose). Maine is at 66%. So is Maine better protected?

Not quite. If you factor in immunity from natural infection, SD has a total population immunity of ~70%, while ME is at ~62%.

I created a calculator: docs.google.com/spreadsheets/d…
Many existing immunity estimates only look at a single metric: vaccination rate. But there are two main issues:

1) Not all vaccinated individuals are fully immune
2) They do not take into account acquired natural immunity

This calculator attempts to correct for this.
Looking at the US:
- 54% of the population have been vaccinated
- Natural infection rate is ~30-40% (covid19-projections.com/path-to-herd-i…).

If you assume the vaccination rate of previously infected individuals is slightly lower (say 45%), that gives a total population immunity of ~65%.
Read 5 tweets
Jun 22, 2021
I believe income inequality is the single best predictor of total Covid deaths in the US.

Not income, but income *inequality*. The R^2 is surprisingly high: 0.35.

Thanks to @joe_sill, I was able to look at over 40 different variables, and expands on my analysis from last month.
It's honestly shocking how correlated the Gini coefficient, a measure of inequality in wealth distribution in a state, is with total Covid deaths.

No other predictor I've seen comes close.

Props to @joe_sill for the finding and an excellent dataset:

Income is not correlated at all with total Covid deaths, but income *inequality* is.

While intuitively this makes sense, this clear dichotomy was extremely surprising for me.

(By the way, there is almost no correlation between income and income inequality)
Read 13 tweets
May 25, 2021
Is containing COVID-19 a requirement for preserving the economy? My analysis suggests: probably not.

In the US, there is no correlation between Covid deaths & changes in unemployment rates.

However, blue states are much more likely to have higher increases in unemployment.

🧵 Image
We can dive deeper by looking at levels of restrictions in each state, using the Oxford Covid-19 Government Response Tracker (OxCGRT).

More restrictions in a state is NOT correlated with fewer COVID-19 deaths.

However, more restrictions IS correlated with higher unemployment. ImageImage
The most interesting data point is South Dakota.

As the only state to never order closures of restaurants, bars & retail, SD actually saw a 0.5% DECREASE in unemployment since the pandemic started. It also never ordered a mask mandate.

Its deaths per capita is the 10th highest.
Read 18 tweets

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