The LSE Data Science Institute hosted a research hackathon in December 2021 to find out why societies have had such different experiences of COVID. Ken Benoit (LSE) explains what happened.
How do you think political and social features of countries relate to cumulative COVID-19 deaths? Why does the impact of COVID vary so much, both across and within countries?
These questions and more were the focus of the recent CIVICA Research Hackathon, organised and hosted by the LSE Data Science Institute as part of the CIVICA Research consortium. The LSE team, which I led, met with representatives of partner institutions and members of the Data-Driven Technologies for Social Sciences Thematic Group to collaboratively define a suitable topic that would enable participants to share their expertise and skills to solve a specific but pressing issue of our time – the effects of the pandemic across and within different countries.
The hackathon, the first of four research collaboration hackathon events planned in the coming months, focused on the CIVICA-partner EUI team’s collaborative statistical modelling project, the COVID-19 Model Challenges. Haoyu Zhai (EUI) explained how the project is led by researchers at the EUI and the WZB-Berlin, allowing users to work with assembled data to build statistical models that predict future COVID mortality across the world and within countries.
The topic was chosen not only for its immediate timeliness and relevance, but also because it ties in directly with the purpose of the Data Driven Technologies for Social Sciences theme, “to find innovative digital methods for the benefit of social science research”. With the aim to bring together faculty, students, and other interested parties to tackle a joint challenge that crosses physical and disciplinary boundaries, the event was free and open to all. Participants included students, researchers, academics and other interested citizens and professionals within and beyond the CIVICA alliance.
Guest speakers and session guides were drawn from across the Data-Driven Technologies for Social Sciences Thematic Group including Rens Chazottes (European University Institute), Alberto Díaz-Cayeros (Stanford University), Miriam Golden, (European University Institute), Alex Scacco (WZB – Berlin Social Science Center), Tara Slough (New York University) and Haoyu Zhai, European University Institute.
Dr Miqdad Asaria (LSE Department of Health Policy) delivered a keynote talk titled ‘From Epidemiology to Politics’ that outlined the interdisciplinary nature of the hackathon through an exploration of why different societies have experienced COVID differently. Miqdad also explained how the ‘R’ number is calculated.
With these presentations as their foundation, participants were asked to consider how the political and social features of countries relate to cumulative COVID deaths. The presenters remained available throughout this time to answer questions and provide guidance and advice as participants got to grips with the data. As they began to develop their models, they were also provided with information on upcoming materials tied to the project that will help interested lecturers to use Model Challenges data for teaching purposes.
Following the event, the COVID-19 Model Challenges site reopened for model submissions by participants, particularly encouraging collaborative submissions in line with the mission of the broader framework of CIVICA – The European University of Social Sciences: to connect the pillars of education, research, and society with the aim of offering creative social science-based solutions to universal challenges.
Recordings of the event can be found on the LSE Data Science Institute YouTube channel.
CIVICA Research brings together researchers from eight leading European universities in the social sciences to contribute knowledge and solutions to the world’s most pressing challenges. The project aims to strengthen the research & innovation pillar of the European University alliance CIVICA. CIVICA Research is co-funded by the EU’s Horizon 2020 research and innovation programme.
This post represents the views of the author and not those of the COVID-19 blog, nor LSE.