COVID-19 has had a catastrophic impact on the world–inflicting enormous health, economic, political and cultural challenges.

Decision-makers around the world have undertaken varied approaches to minimise the spread of the virus and consequences of the pandemic. Many of these efforts were driven by data, including data from non-traditional sources – i.e. data that is 'digitally captured (e.g. mobile phone records and financial data), mediated (e.g. social media and online data) or observed (e.g. satellite imagery)', using new instrumentation mechanisms (e.g. mobile applications and websites).

COVID-19 is claimed to have been a 'watershed moment' in accessing and re-using non-traditional data. However, there has been little research into how non-traditional data initiatives were designed or what impacts they had on COVID-19 responses.

This review aimed to fill this gap by conducting an in-depth study about how different non-traditional data sources have been used during COVID-19. Among the questions researchers sought to answer: Why was non-traditional data used? What types and sources of non-traditional data stood out? Who was calling for non-traditional data? When and where did non-traditional data initiatives take place? How was non-traditional data accessed and used? By answering these questions, the GovLab identified important lessons from the pandemic that can prepare us for future crises.

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