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WillMaStat's profile
Will Ma
Will Ma
Will Ma
@WillMaStat

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Will Ma

@WillMaStat

PhD in statistics

New York, NY
Joined March 2020

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    1. Will Ma‏ @WillMaStat 9 Jun 2020

      A team led by @johnbrownstein of @harvardmed used satellite images and search engine data to suggest #coronavirus may have hit Wuhan in August. However, they seem to have used wrong Chinese words to search. Their findings in hospital traffic doesn’t have statistical significance.pic.twitter.com/LLy98psBRG

      16 replies 125 retweets 251 likes
      Show this thread
    2. Will Ma‏ @WillMaStat 9 Jun 2020

      It is unclear which Chinese words for “Diarrhea” @johnbrownstein ‘s team have used to analyze the search engine data. The most commonly used Chinese words for “Diarrhea” are “腹泻” and “拉肚子”, but neither of them has showed increase in Baidu’s search volume prior to Jan 2020.pic.twitter.com/fpYj29cqbO

      5 replies 18 retweets 71 likes
      Show this thread
    3. Will Ma‏ @WillMaStat 9 Jun 2020

      In @harvardmed study, the change in relative car volume varies dramatically from hospital to hospital. The estimated upward trend in hospital traffic from Aug to Jan doesn’t show statistical significance. In fact, removal of an outlier in Oct might just alter the conclusion.pic.twitter.com/I8S9WKmIOv

      4 replies 13 retweets 51 likes
      Show this thread
    4. Will Ma‏ @WillMaStat 10 Jun 2020

      pic.twitter.com/5o8SMdf3II

      1 reply 4 retweets 18 likes
      Show this thread
    5. Will Ma‏ @WillMaStat 10 Jun 2020

      I emailed @johnbrownstein at @harvardmed and it turned out “腹泻的症状” ("symptoms of diarrhea"), rather than “腹泻”("Diarrhea"), was used as the keyword in their search data analysis. In fact, the search volume of “腹泻” (correct term for “diarrhea”) is decreasing in August.pic.twitter.com/9gD4iOoBkh

      4 replies 8 retweets 38 likes
      Show this thread
    6. Will Ma‏ @WillMaStat 10 Jun 2020

      Moreover, increase in search volume of "腹泻的症状" ("symptoms of diarrhea") in 2H 2019 is not unique for Wuhan. It was observed nationwide in China for reasons unknown yet. Is this study suggesting that #COVID19 had swept over China in August?pic.twitter.com/uiP9dTS7zC

      3 replies 5 retweets 28 likes
      Show this thread
      Will Ma‏ @WillMaStat 10 Jun 2020

      @johnbrownstein needs to look at other symptoms of #COVID19 besides diarrhea, e.g., "short of breath”, “difficulty breathing" (“呼吸困难","气短"). The search volume of both terms are rather flat throughout 2019, which started to climb in late Jan 2020.pic.twitter.com/qM8gDvU1hs

      11:21 PM - 10 Jun 2020
      • 7 Retweets
      • 34 Likes
      • Hungarian Tankie Janet Kinneberg art kimmy Lucas Niewenhuis 秦皇汉武 Toby-凡 M roadsidetree
      4 replies 7 retweets 34 likes
        1. Zed Fang‏ @Fang__z 11 Jun 2020
          Replying to @WillMaStat @johnbrownstein

          The non-obviousness of the reported search term suggest P-hacking. i.e. the authors examined multiple different search terms and reported only the ones that show the pattern they looked for. This is a fraudulent academic practice.

          0 replies 0 retweets 3 likes
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        2. Sam Gilbert‏ @samgilb 11 Jun 2020
          Replying to @WillMaStat @johnbrownstein

          These are the most & least correlated & predictive Google symptom searches for Covid in Lampos et al's model: https://github.com/vlampos/covid-19-online-search/blob/master/covid-19-online-search.pdf …pic.twitter.com/22yOy9cm2m

          1 reply 0 retweets 0 likes
        3. Sam Gilbert‏ @samgilb 11 Jun 2020
          Replying to @samgilb @WillMaStat @johnbrownstein

          Google Trends data may also be worth digging into to triangulate Baidu. It does show a peak for the topic "Cough" in January 2020. (Obvious caveat is that in China this will only reflect searches by VPN users)pic.twitter.com/SsGsn3OfoR

          0 replies 0 retweets 0 likes
        4. End of conversation
        1. New conversation
        2. PB Politics‏ @BrackPolitics 11 Jun 2020
          Replying to @WillMaStat @johnbrownstein

          @threadreaderapp unroll

          1 reply 0 retweets 0 likes
        3. Thread Reader App‏ @threadreaderapp 11 Jun 2020
          Replying to @BrackPolitics

          Hola, please find the unroll here: @WillMaStat: A team led by @johnbrownstein of @harvardmed used satellite images and search engine data to suggest… https://threadreaderapp.com/thread/1270575010093182976.html … Have a good day. 🤖

          0 replies 0 retweets 0 likes
        4. End of conversation

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