COVID-19: An exploration of consecutive systemic barriers to pathogen-related data sharing during a pandemic

In 2020, the COVID-19 pandemic resulted in a rapid response from governments and researchers worldwide. As of March 2021, there have been over 122 million confirmed cases, with over 2.7 million people dying as a result of COVID-19. Despite this staggering toll, those who work with pandemic-relevant data often face significant systemic barriers to accessing, sharing or re-using this data. In this paper we report preliminary results for an in-progress qualitative study, where we interviewed data professionals working with COVID-19-relevant data types including social media, mobility, viral genome, testing, infection, hospital admission, and deaths. These data types are variously used for pandemic spread modelling, healthcare system strain awareness, and devising therapeutic treatments for COVID-19. Barriers to data sharing include cost of access to data (primarily certain healthcare sources and mobility data from mobile phone carriers), human throughput bottlenecks, unclear pathways to request access to data, unnecessarily strict access controls and data re-use policies, unclear data provenance, inability to link separate datasources that could collectively create a more complete picture, poor metadata standards, and a lack of computer-suitable data formats.