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Our paper with @ChikinaLab on age-targeted migitations for COVID-19 has been published in @PLOSONE.

Quick summary thread. 1/8

journals.plos.org/plosone/articl…
One of the distinctive features of COVID-19 is its extremely age-differentiated mortality rate. E.g., a 65-year old has 50-100x the COVID mortality risk as a 25-year old.

For this reason, age-targeted restrictions have the potential to reduce COVID deaths significantly. 2/8
Our paper demonstrates that the benefits of age-targeting persist even if the epidemic will eventually be limited by immunity in the absence of age-targeting; that is, even if age-targeted restrictions eventually end. 3/8
This result depends on the the fact that normal age-mediated contact patterns are strongly anti-correlated with COVID mortality rates. In particular, for the control of the epidemic, immunity is most effective in younger people, who also have much lower fatality rates. 4/8
Note that our goal is not to make predictions about specific trajectories, numbers of deaths, etc., but instead to use a relatively simple model to demonstrate a robust qualitative phenomenon. For example, we don't model contact heterogeneity beyond what is mediated by age. 5/8
What does this mean for the real world?

Obviously, COVID deaths will be minimized in cases where COVID can be successfully suppressed. But it seems increasingly clear that in many cases, suppression of COVID will (or already has) failed, as transmission rates increase. 6/8
In these situations, where immunity ends up contributing to the control of an epidemic, age-targeted policies should be expected to have a significant impact on overall deaths.

7/8
Policy makers should consider ways in which they can reduce transmission involving older populations, *before* they have a second wave on their hands. 8/8

I gave a talk about an earlier version of this paper in the @ubcmath math-bio seminar. The recording is available below.

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