Useful discussion of COVID dynamics internationallly: https://www.ft.com/content/5b96ee2d-9ced-46ae-868f-43c9d8df1ecb …pic.twitter.com/QYsKUauuCo
Epidemiologist. Writer (Guardian, Observer etc). "Well known research trouble-maker". PhDing at @UoW Host of @senscipod Email gidmk.healthnerd@gmail.com he/him
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Useful discussion of COVID dynamics internationallly: https://www.ft.com/content/5b96ee2d-9ced-46ae-868f-43c9d8df1ecb …pic.twitter.com/QYsKUauuCo
These correlations look different in more local data. I.e., below is the local data within Lombardy, from the NYT. Case counts per capita this week (4th # column) are anti-correlated with total per capita case counts (2nd # column). (I haven't seen more local data for Spain.)pic.twitter.com/0EbdhifYIi
Yes, would make sense to see stronger pattern at finer scale – at the extreme (i.e. individual level), would obviously expect inverse correlation (because some people immune and others not). Question is at what resolution this ends up affecting overall dynamics.
Local Italian data v interesting. Here’s cumulative vs recent cases, all provinces, Lombardy highlighted. Suggests where case rates got *very* high in first wave, acquired immunity is dampening resurgence. Caveats on small sample + cases data + outliers, but worth considering.pic.twitter.com/5WRAeZ9SsO
Interesting! Would be great to see this mapped against the predicted reduction in cases using a classic herd immunity model, because at a glance it actually seems like there's less dampening there than we'd expect
What is the calculation you're doing in your head here? E.g. what ratio of infections to cases are you using?
TBH it's very hard to do, but there were reports that Bergamo had ~50% infected. Given that, you'd expect the spread of disease to be quite dramatically reduced, at least in the short term, especially using a more heterogenous assumption for HI
Wes Pegden Retweeted Wes Pegden
Those reports were mistaken.https://twitter.com/WesPegden/status/1270733017393364999?s=19 …
Wes Pegden added,
Fair enough. It's true that the probabilistically sampled national seroprevalence estimate for Lombardy was 7.5%, but I can't find the numbers broken down smaller than that unfortunately
Actually, I wonder if you could in theory estimate the proportion of people who have been infected in the smaller areas, using the demonstrable overall prevalence and the differences in infection numbers now?
If you trust that antibody study then yes I think this would be pretty reasonable. One other thing is that even significant numbers of cases in these places don't necessarily mean that R>1 there; it could also be explained by R<1 or R~1 but with constant introductions from...
... other places, leading to localized transmission which contributes meaningfully to case counts but would not be self-sustaining on its own. To me this seems like a hard thing to separate out.
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