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Keywords: COVID-19, Vaccine Development, Clinical Trials, Demography, Ethnicity, Data Science, Data Visualization, Tableau
The COVID-19 Prevention Network(CoVPN) was established by the National Institute of Allergy and Infectious Diseases as the functional unit of Operation Warp Speed. To conduct efficacy trials for COVID-19 vaccines and monoclonal antibodies, the target for CoVPN was to rapidly enroll volunteers globally. As the pandemic progressed, racial and ethnic minority groups were disproportionately affected, which underscored the critical need to measure and monitor enrollment, focusing on recruiting marginalized populations in CoVPN sites and ramping up community engagement and recruitment response. In absence of an existing mechanism, a suite of Tableau dashboards was designed to monitor enrollment in these trials, namely Moderna (n=5940), Oxford-AstraZeneca (n=9307), Johnson & Johnson (n=13213), Novavax (n=3940) which included 144 CoVPN sites located across US, Argentina, Brazil, Mexico, Peru, and South Africa. For creating the visual analytics, a data pool was created from categorical and unstructured data through extract, transform, load (ETL) process considering variable data types and data structures from different sources. Key performance indicators (KPIs) were created based on the enrollment targets defined by CoVPN Leadership for participants by age, sex, race, and ethnicity. Additionally, a detailed report was created to inform fiscal site-related operations. The primary challenge was to create an easily understandable, efficient report across studies while maintaining the data quality. The visualization product was refreshed weekly and helped CoVPN Leadership and community engagement team to monitor enrollment by showing study cumulative as well as site-level detailed distribution of demography, race, and ethnicity of study participants. Tracking KPIs allowed better understanding of key population recruitment and timely intervention at sites along with detailed fiscal reporting to keep financials aligned.