Calling all social scientists:



Why does Covid-19 impact vary so much, both across and within countries? What are the political and social determinants of such differences? If you have a good model for these questions, then our Covid-19 Model Challenges is for you. We are looking for the best statistical models to explain cross-national and subnational patterns of Covid-19 mortalities, and advance our understanding of how well social scientists can predict truly important outcomes that are in part affected by social processes and political institutions.



Join us at our Hackathon this Thursday 10 December (9:00 PST, 12:00 ET, and 18:00 CET) to learn more about our project, share your ideas, and propose your models on our platform. Our Steering Committee members will be present to explain the model challenges, demonstrate the process, and provide assistance for writing custom functions. This will also be a great opportunity to form teams for the main challenge, if you would like to be part of one.



To register for the Hackathon, follow the Zoom link here: https://ucr.zoom.us/meeting/register/tJYlfuurrjwtHNXYwL5Vl_DT5lKpMrfNXz9x. For more information, see below and check out our website: https://eos.wzb.eu/ipi/shiny-covid-crowdsourcing/.





  *   Who we are: we are a team of social scientists across leading institutions, with a shared desire to contribute to understanding patterns of mortality caused by the raging global pandemic. We came together to design a platform to help us learn from and share knowledge across social science disciplines. Our hope is that by providing a better understanding of the political economy of disease outcomes, we may contribute to better policy responses and politically viable strategies in future pandemics. We organise ourselves through a Steering Committee led by Miriam A. Golden (EUI) and Alexandra Scacco (WZB), together with Alberto Diaz-Cayeros (Stanford), Kim Yi Dionne (UC Riverside), Macartan Humphreys (Columbia, WZB), Sampada KC (WZB), Eugenia Nazrullaeva (Glasgow), and Eva Vivalt (Toronto).





  *   What we do: we are trying to 'crowdsource' models for understanding COVID-19 variation across and within states. We want each team to build a statistical model using political and social variables to predict future COVID-19 mortality numbers, as of 31 August 2021. Our online platform allows you to see how the variables you think matter perform on the current data. We have data for four challenges: global, India, Mexico, and the USA, and you can enter a model for each challenge. You can also include your own data, if we are missing variables you think that matter. Models will be judged using 8/31/21 data.





  *   Why to participate: your participation helps to build up our collective social scientific capacity — each legible model will advance our understanding of how well social scientists can predict truly important outcomes by social and political factors. In addition, contributors of the 10 best models in each challenge will be asked for inclusion as co-authors in our write-ups. All those who submit a legible model will also with permission be publicly acknowledged. Finally, the model challenges are fun in themselves!



If you would like to participate in the model challenges but cannot join us on 10 December  (or if the event is over-subscribed, as it likely will — so register soon!), please contact us by email ([log in to unmask]<mailto:[log in to unmask]>) to inform us. We will work to create a second Hackathon if there is sufficient demand.



Please do not hesitate to contact us for any issues or inquiry. We look forward to seeing many of you this Thursday, and throughout December!



Best regards,

The Covid-19 Model Challenges Team







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