Rather than clearly highlighting this bold assumption in the article, it's buried at the bottom as a footnote.
At what point do unrealistic model assumptions become misleading? Does the science support immunity lasting indefinitely? Or 80% of Americans getting fully vaccinated?
If the model used more realistic assumptions based on real-world data, they would probably conclude that we won't reach herd immunity. But that would likely break the premise of the model, so I can see why they chose not to explore this.
When can we return to normal? Forget about "herd immunity".
Below is my estimate for the number of susceptible individuals over time, as a proportion of the US population.
Looking at this graph, what is the best point to go back to normal? Christmas? Fall? Or Summer?
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By summer, everybody who wants a vaccine will be able to get one. The vulnerable population will long have been able to receive their shots. Hospitalizations & deaths will be at negligible levels.
Normality will happen... with or without herd immunity.
Our country currently has no concrete guidelines for when to expect a return to normal. We seem to be more concerned about a theoretical threshold than setting realistic goals about when restrictions can be dropped.
A @CDCgov report in Jan concluded that "university counties with in-person instruction experienced a 56% increase in incidence".
They only examined 21 days before/after classes start.
Since then, those counties saw a much lower incidence vs counties w/remote instruction.
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You can see above that counties with in-person instruction had a ~50% higher incidence in the weeks after classes start than remote counties, consistent with the CDC report.
But during the peak in Dec/Jan, counties w/in-person instruction actually had a ~50% *lower* incidence.
Contrary to what many believe, remote instruction did not decrease county-level incidence during the fall surge, when compared to in-person instruction.
Below is a breakdown based on total cases per capita.
I've seen many news articles cite that "the UK variant could be the dominant strain by March". This is emphasized by @CDCDirector.
While this will likely to be the case, this should not be an automatic cause for concern. Cases could still remain contained.
Here's how: 🧵
One of @CDCgov's own models has tracked the true decline in cases quite accurately thus far.
Their projection shows that the B.1.1.7 variant will become the dominant variant in March. But interestingly... there's no fourth wave. Cases simply level out:
This conclusion is based on the following new developments over the past month:
- Remained high levels of vaccine hesitancy
- New variants that may lower vaccine efficacy
- Rollout of the J&J vaccine (efficacy ~70%)
- Delayed arrival of the children vaccine
That said, herd immunity does not have a hard threshold, and being close to herd immunity may be sufficient to prevent large outbreaks.
Our goal should not be to reach "herd immunity", but to reduce COVID-19 deaths & hospitalizations so that life can return to normal.