Responding to the coronavirus disease-2019 pandemic with innovative data use: The role of data challenges

Jamie Danemayer, Andrew Young, Siobhan Green, Lydia Ezenwa, Michael Klein
March 27, 2023
Academic Research Publications


Innovative, responsible data use is a critical need in the global response to the coronavirus disease-2019 (COVID-19) pandemic. Yet potentially impactful data are often unavailable to those who could utilize it, particularly in data-poor settings, posing a serious barrier to effective pandemic mitigation. Data challenges, a public call-to-action for innovative data use projects, can identify and address these specific barriers. To understand gaps and progress relevant to effective data use in this context, this study thematically analyses three sets of qualitative data focused on/based in low/middle-income countries: (a) a survey of innovators responding to a data challenge, (b) a survey of organizers of data challenges, and (c) a focus group discussion with professionals using COVID-19 data for evidence-based decision-making. Data quality and accessibility and human resources/institutional capacity were frequently reported limitations to effective data use among innovators. New fit-for-purpose tools and the expansion of partnerships were the most frequently noted areas of progress. Discussion participants identified building capacity for external/national actors to understand the needs of local communities can address a lack of partnerships while de-siloing information. A synthesis of themes demonstrated that gaps, progress, and needs commonly identified by these groups are relevant beyond COVID-19, highlighting the importance of a healthy data ecosystem to address emerging threats. This is supported by data holders prioritizing the availability and accessibility of their data without causing harm; funders and policymakers committed to integrating innovations with existing physical, data, and policy infrastructure; and innovators designing sustainable, multi-use solutions based on principles of good data governance.