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maiamajumder's profile
Maia Majumder, PhD
Maia Majumder, PhD
Maia Majumder, PhD
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@maiamajumder

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Maia Majumder, PhDVerified account

@maiamajumder

Faculty at @harvardmed & @Bos_CHIP. Alum of @MIT (PhD), @HPDSLab (postdoc), @healthmap, & @icddr_b. Married to @imran_malek. I also make art, music, & stories.

Boston, MA, USA
maimunamajumder.com
Joined September 2012

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    Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

    New analysis from me & @mandl suggests that preprints might have driven global discourse about #nCoV2019 (#COVID19) transmissibility prior to the publication of relevant peer-reviewed studies. Find our preprint here [http://ssrn.com/abstract=3536663 …] as well as an explainer thread below!pic.twitter.com/8FvYC9XMet

    6:00 pm - 11 Feb 2020
    • 111 Retweets
    • 204 Likes
    • Megan Johnston Ghinwa El Hayek Mike Rogers, CPA Leisa Weld Taylor 😷 Jasnah Kholin PalmBeachCMA 👨🏻‍⚕️🙏🏽⛪️👩🏾‍⚕️ วันนี้ดีที่สุด Brian Mills
    17 replies . 111 retweets 204 likes
      1. New conversation
      2. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        Assuming representativeness, we first collected Google search trend interest & MediaCloud news volume data on #nCoV2019 (#COVID19) transmissibility. We then curated relevant studies from Google Scholar & four popular preprint servers. (Discovery specs are noted in our preprint.)

        1 reply . 3 retweets 17 likes
        Show this thread
      3. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        After plotting search interest & news media volume, we overlaid when each of the relevant studies were published. We found that both search interest & news media RE: the transmissibility potential of #nCoV2019 (#COVID19) peaked before publication of the first peer-reviewed study.

        2 replies . 4 retweets 26 likes
        Show this thread
      4. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        This alone was a really interesting finding, but we took it a step further by comparing the results of the relevant preprint studies against the relevant peer-reviewed studies. To do this, we first collected the basic reproduction number (R_0) estimates presented by each study.

        1 reply . 0 retweets 15 likes
        Show this thread
      5. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        Maia Majumder, PhD Retweeted Maia Majumder, PhD

        As y'all may recall, R_0 is a measure of transmissibility *potential*. It can be defined as the *average* number of individuals a new case may infect in a fully susceptible population. I posted a few explainers about this measure earlier, including this more technical one below.https://twitter.com/maiamajumder/status/1221896232001572866 …

        Maia Majumder, PhD added,

        Maia Majumder, PhDVerified account @maiamajumder
        I've seen a few tweets recently about how R_0 is the mean of a distribution (via @nntaleb) and how its dispersion is important to understand (via @DFisman & @C_Althaus). This is very true (for #nCoV2019 & otherwise), and it's why I posted this graphic last week. [THREAD] 1/x https://twitter.com/maiamajumder/status/1220802808976486406 …
        Show this thread
        1 reply . 2 retweets 24 likes
        Show this thread
      6. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        After collecting R_0 ranges from each study that estimated the transmissibility potential of #nCoV2019 (#COVID19), we plotted them by date of publication (see attached). Preprint estimates versus peer-reviewed estimates are clearly demarcated in the diagram to allow comparison.pic.twitter.com/ExseHbnXTw

        2 replies . 21 retweets 39 likes
        Show this thread
      7. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        We also collected methods & data specs for each relevant study, which can be found in our preprint. Notably, the presentation of R_0 ranges differed across studies (e.g. 95%CI, 95%CrI, etc.); moreover, different modeling approaches & data sources were used across studies too.

        1 reply . 1 retweet 14 likes
        Show this thread
      8. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        Nevertheless, we found that the range of R_0 estimates presented by preprints overlapped with those presented by peer-reviewed studies later down the line. Mean preprint estimates skewed higher on average than peer-reviewed estimates (R_0 = 3.61 & 2.54, respectively). However...

        1 reply . 2 retweets 16 likes
        Show this thread
      9. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        These differences were driven primarily by two mean estimates that fell outside of the 95%CI we calculated for the preprint group's collective mean estimates [95%CI = 2.77, 4.45]. When these two estimates were discarded, average R_0 = 3.02 – similar to the peer-reviewed average.

        1 reply . 5 retweets 21 likes
        Show this thread
      10. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        With this in mind (and given the impact preprints seem to be having on discourse around the ongoing #nCoV2019 [#COVID19] outbreak), we recommend that a consensus-based approach (like the one presented here) be used to assess the robustness of preprint findings whenever possible.

        2 replies . 2 retweets 28 likes
        Show this thread
      11. Maia Majumder, PhD‏Verified account @maiamajumder Feb 11

        I'm sure I'll have plenty more to say about this work later (all of which I'll add to this thread as appropriate), but I'm gonna leave it here for now... And as a reminder, our analysis has not yet been peer-reviewed & should thus be treated as *strictly provisional*. Thank you!

        5 replies . 3 retweets 42 likes
        Show this thread
      12. End of conversation

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