I launched a new page that shows the path to US COVID-19 herd immunity: covid19-projections.com/path-to-herd-i…

It's built on the assumption that herd immunity will be achieved via vaccination and natural infection.

Tl;dr version: I estimate a "return to normal" by June/July 2021.
The underlying methodology is a simple model that simultaneously simulates daily vaccinations and new infections through 2022.

By May/June 2021, I estimate vaccinations to exceed 1 million people per day as they become available to the general public.
By mid-summer 2021, I estimate roughly 1/2 of the population have been vaccinated & 1/3 of the population have been infected.

After accounting for overlap/loss of immunity, this amounts to ~60% of the population possessing immunity to the virus, sufficient for herd immunity.
Currently, May-July 2021 is my best estimate for when new infections and deaths will become minimal, allowing society to return to normal.

It's been almost a year since the pandemic first began, and we can finally see the light at the end of the tunnel.
Many assumptions have to be made to generate these estimates. I detail all of them in the write-up linked above.

As usual, I must mention that if any of the assumptions do not hold, then the results may be drastically different (e.g. if vaccine rollout is faster than expected).
An obvious but important assumption is that a majority of Americans will choose to take the vaccine by year-end 2021.

Unfortunately, this is not a confident assumption, and hence we must all do our best to ensure that this assumption will hold true.
Despite the vaccine in the near horizon, I estimate ~40 million additional people will still be infected between now and next summer, resulting in ~200,000 additional reported deaths.

A ballpark estimate of the total US COVID-19 official death toll is 500,000 (+/- 100k).
With all of the technological advances & scientific breakthroughs we have achieved as a society over the past 100+ years, we are still at nature's mercy when it comes to a pandemic.

It's been a humbling realization, and I hope we can learn from these lessons for the future.

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More from @youyanggu

14 Dec
Many people are unaware that the COVID-19 vaccine has significantly more side effects than the flu vaccine. I hope to see more honest discussions regarding this.

Props to @Cat_Ho for her realistic, data-centric reporting of this issue. It's much needed.

sfchronicle.com/health/article… Image
Some notable numbers from the vaccine trial participants after the 2nd dose (age 16-55):

- 16% developed a fever vs 0% for the placebo
- 59%/52% had fatigue/headache vs 23/24% for placebo
- 45% took pain medication vs 13% for placebo

Those age 55+ have a slightly lower rate.
In comparison, roughly 1% of flu shot participants report a fever (16x lower), and ~20% report fatigue/headache (2x lower).

On top of that, COVID-19 vaccine participants have to go through this twice. Though the side effects are milder after dose #1.

Read 12 tweets
11 Dec
By many accounts, the US will have 100 million vaccine doses by February.

I estimated yesterday that we need ~100 million people to gain immunity via vaccination to reach herd immunity.

So *theoretically*, we can reach herd immunity by March if we vaccinate the right people.
This involves allocating the initial (limited) supply of vaccines based on two main criteria:

1) Each individual receives only one dose instead of two.
2) We prioritize individuals who have not had a prior infection.

This would be temporary, until supply catches up.
There is some evidence, though inconclusive, that even one dose of the vaccine can have reasonable efficacy (potentially >80%).

Read 15 tweets
9 Dec
The COVIDhub Ensemble model that combines all the models did not perform well over the past 2 months.

This is due to the fact that the majority of model submissions did not properly forecast this current wave.

Roughly half of all models failed to beat the baseline. ImageImage
This is a known issue with pandemic modeling. For most scenarios, it's beneficial for models to make forecasts close to the status quo (since that's usually true).

This means the they're accurate a majority of the time, but they will miss large spikes such as this current wave.
On the flip side, if a model predicts a large spike and is wrong, it will be heavily penalized by most evaluation metrics. This can happen even if the spike does happen but is a few weeks early/late.

That's the dilemma a lot of modelers face, including myself earlier this year.
Read 7 tweets
3 Dec
I posted the methodology for the new covid19-projections.com nowcasting model:

covid19-projections.com/estimating-tru…

I'm going to do a layman summary here, and hopefully receive some feedback from #epitwitter. Image
I've adjusted the methodology that I posted back in August based on new data and research:



Disclaimer: with that said, this is still a simple heuristic and hence is not perfect. There are more advanced methods (e.g. see covidestim.org).
The basic idea is this: for each day, we try to estimate the ratio of true infections to reported cases that day.

We call this the prevalence ratio, and we model this ratio as a function of the day and positivity rate: Image
Read 16 tweets
1 Dec
I deployed some new features to covid19-projections.com over the past week. Here's a brief summary:

1) Maps over time - you can now view how the pandemic progresses over time for the US, on both a state and county level: covid19-projections.com/maps-infection…
2) Plots of confirmed cases and deaths for every state and county in the US (in addition to estimates of true infections).

Example: covid19-projections.com/infections/us Image
3) Methodology writeup: covid19-projections.com/estimating-tru…. Will write a more detailed Tweet soon.

4) Daily county-level estimates: github.com/youyanggu/covi…. Due to storage constraints I moved it to a separate repository.
Read 5 tweets
24 Nov
Last week, Illinois reported 15,415 cases in a single day, more than Florida ever did in a single day. This is despite Illinois' population being 40% lower.

Many of you probably did not know the dire situation in Illinois. That's because no mainstream media chose to report it.
Here is how the media chose to report Illinois now (left) vs Florida in July (right).

Unfortunately, no national news outlet is covering the situation in Illinois.
No other state has ever averaged 12,000 cases a day for a whole week. Not even Florida (1.7x pop), California (3x pop), and Texas (2.3x pop).

For deaths per capita, Illinois also exceeded the peak deaths in Florida twice, once in May and once again now. So why is this not news?
Read 6 tweets

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