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[OHDSI COVID-19] Harvard Data Science Review Call for COVID-19 papers


(David Madigan) #1

[From Xiao-Li Meng, HDSR Editor]

The world is craving for reliable information and analysis of the dynamics and impact of COVID-19. Case in point, Washington Post’s corona-simulator has received more hits (and still counting) than any of its other articles in history. HDSR clearly is in a position – and arguably also has the responsibility – to contribute in a timely manner to meet this need. With the help of several of you, the work has already began to publish a special issue on COVID-19 in April. Currently we have about 5 articles in the pipelines, and the plan is to start with them as soon as possible, and then rollout more articles as they become available, and we will go on as long as needed (though obviously we all hope the pandemic will end soon!).

I am therefore writing with three requests:

  1. Please help to solicit high quality relevant articles (ready to submit or in the making), including from yourself. Given the breadth of HDSR, we welcome any kind of thoughtful articles pertaining to data science for COVID-19, from historical lessons on pandemic, to public understanding of risks, and from epidemiological modeling to economic analysis that can improve/impact policies. (Just as examples: the papers in the pipeline range from helping the public to understand exponential growth to how FDA should modify its statistical criteria for drug approvals during outbreaks in order to save more lives.)

  2. The grand challenge for publishing this special issue is to ensure rigorous and speedy peer review. Time is essence, so is high quality – there is already too much misinformation and rushed decisions out there. With your help, we can achieve both. For those of you who have expertise and knowledge to help in particular areas (e.g., on SEIR model or on economic analysis for pandemic), please let me know ASAP, so when submissions come in, I will be able to get them to the right experts right way.

  3. When you receive a review request from me (either to serve as an Editor/AE or a reviewer yourself), please respond within 24 hours whether you will be able to handle it or not within the timeline as specified in my request. It is particularly critical that you let me know right away that if you cannot handle it, so I can find an alternative without delaying the process by one day. We are in a situation where every day counts, and hence your immediate response is absolutely essential and appreciated.

I’m sorry if such requests may add more stress to you, and I deeply appreciate your understanding and help. My hope is that by working together and helping each other, our individual stresses (and indeed fear) can be actually lessened. (Forgive me for preaching to the choir, I just wrote a piece to my fellow statisticians and probabilistists on this point, and I include it for your amusement.)

Thanks so much for your help and support. If you have any questions and suggestions, please let me know. This EIC account can reach Rebecca, Paige and me, and we all monitor it to ensure a speedy response on our side. If for whatever reason you want to write to me individually, please use xlmeng@g.harvard.edu, which I check frequently as well. (Please avoid using my stat account, which now I have to give a low priority.)

Please stay safe and well for all of us,

Xiao-Li Meng

Harvard Data Science Review

datasciencereview@harvard.edu

https://hdsr.mitpress.mit.edu


(David Madigan) #2

Please contact me if you have an idea for a paper


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