Adam KucharskiVerified account

@AdamJKucharski

Mathematician/epidemiologist at . fellow and . Author of The Rules of Contagion. Views own.

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Joined January 2012
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  1. Retweeted
    13 hours ago

    Congratulations - Rules of Contagion is a book of the year! "Essential reading to truly process the pandemic" 💪📊📈

    3 replies 8 retweets 41 likes
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  2. 13 hours ago

    More on how to evaluate forecasts, and discussion of challenges of forecasting infections like Ebola, where control measures also curbed transmission (). 9/9

    3 replies 2 retweets 40 likes
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  3. 13 hours ago

    For endemic childhood infections - like rotavirus - cycles of outbreaks driven by build up of immunity then new susceptibility among children have made it possible to predict long-term effects of introducing vaccination. 8/

    1 reply 3 retweets 36 likes
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  4. 13 hours ago

    It’s worth noting there are some infections where longer term forecasting does make more sense. E.g. flu dynamics depend on immunity and seasonality but not on reactive control, which makes forecasting theoretically (if not practically) easier: 7/

    2 replies 3 retweets 44 likes
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  5. 13 hours ago

    That being said, it can be possible to make short-term forecasts of things like COVID hospitalisations and deaths, because these are impacts of events (i.e. infections) that have already happened, and hence should be more predictable. 6/

    1 reply 6 retweets 53 likes
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  6. 13 hours ago

    That’s why COVID models generally use scenarios, to illustrate epidemiological consequence of available options (including doing nothing). In this sense, models are a tool to aid decision making, not one to make weather-style predictions. 5/

    1 reply 7 retweets 68 likes
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  7. 13 hours ago

    But of course, policy can change rapidly, informed by available evidence. Pointing out ‘a storm is coming’ won’t stop a storm, but pointing out a growing COVID outbreak could result in efforts to curb transmission. 4/

    2 replies 7 retweets 51 likes
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  8. 13 hours ago

    This means that long-term COVID forecasts don’t really make sense, because it’s equivalent of treating future policy & behaviour like something to be predicted from afar (more in this piece by & : ). 3/

    1 reply 5 retweets 45 likes
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  9. 13 hours ago

    Coverage of modelling is often framed as if epidemics were weather - you make a prediction and then it happens or it doesn’t. But COVID-19 isn’t a storm. Behaviour and policy can change its path... 2/

    1 reply 9 retweets 62 likes
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  10. 13 hours ago

    Why do COVID-19 modelling groups typically produce ‘scenarios’ rather than long-term forecasts when exploring possible epidemic dynamics? A short thread... 1/

    6 replies 88 retweets 264 likes
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  11. Retweeted
    Nov 11

    Tomorrow at 7pm I'll be talking about language, puzzles and pizza at the (virtual) Royal Institution. The talk is live streamed and FREE!

    What did the world take to during the first lockdown? Puzzles. They improve mental functions and trigger bonding if solved in a group. On 12 Nov, puzzle master will explore alphabets and languages through the medium of puzzles. Book here >
    1 reply 10 retweets 32 likes
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  12. Retweeted
    Nov 10

    After posting about sharply rising cases Friday, there were multiple replies to the effect of "but deaths aren't going up". As should be obvious to most at this point, (reported) deaths lag (reported) cases. This thread investigates. 1/8

    I know that everyone has been (justifiably) distracted by other things, but the epidemic in the US is looking pretty dire with 125,552 confirmed cases reported Friday by . 1/10
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    75 replies 680 retweets 1,843 likes
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  13. Nov 11

    This project is an example of one of my favourite aspects of science Twitter. A few months ago, we were grappling with positivity estimates, then posted a great pre-print – got talking and eventually collaborated to answer a Q everyone was interested in.

    We analysed data from London front-line healthcare workers who'd been regularly tested and reported whether they had symptoms at point of test ()... 2/
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    1 reply 17 retweets 56 likes
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  14. Retweeted
    Nov 11

    I want to flag this important work by , which is the best study on whether there are pre-existing antibodies to in uninfected people that affect risk of getting . (1/7).

    Our new paper showing that some humans possessed non-neutralizing antibodies against SARS-CoV-2 prior to the COVID-19 pandemic is now up at . Importantly, we find that these antibodies are not associated with SARS-CoV-2 protection. 1/7
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    3 replies 60 retweets 143 likes
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  15. Retweeted
    Nov 11

    Data from informs testing strategies. really happy to have contributed to this from with . Thanks .

    We analysed data from London front-line healthcare workers who'd been regularly tested and reported whether they had symptoms at point of test ()... 2/
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    1 reply 6 retweets 18 likes
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  16. Nov 11

    Footnote: As a couple of people have correctly noted, scenario was actually for England, although post above had plot labelled UK (so presumably this was what they were intending to compare). England deaths now over 270 for Nov 1st.

    2 replies 2 retweets 12 likes
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  17. Nov 11

    It's important to have independent scrutiny of modelling (e.g. ). This is why (& others) work to get code/analysis online asap (). But also important that those scrutinising do so in good faith and get basics right. 4/4

    1 reply 2 retweets 35 likes
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  18. Nov 11

    Why do data delays matter? Because it's difference between simplistic narrative of 'all model values were too high' and realisation that despite model variation, median of quoted worst-case estimates (376 deaths) concerningly close to Nov 1st average (which will rise further). 3/

    1 reply 6 retweets 26 likes
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  19. Nov 11

    Worth noting models above were preliminary scenarios, not forecasts. (Personally, I thought there were more than enough data/trends to be concerned about last month, regardless of results of one specific long-term modelling scenario from early Oct.) 2/

    Additional context on that early working analysis also now available (noting that unlike above, these were *scenarios* to illustrate a reasonable worst case without further interventions, not forecasts): 2/
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    4 replies 3 retweets 24 likes
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  20. Nov 11

    Data take time to appear on gov website, so deaths for 1st Nov now average over 320, not “just over 200” as claimed in this article. Either CEBM team aren't aware of delays in death reporting, or they are & for some reason chose to quote too low values. 1/

    15 replies 40 retweets 135 likes
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