Big Data Health Science Fellow Program in Infectious Disease Research

The multiple, massive, and rich Big Data streams in healthcare (e.g., electronic health records [EHR], mobile technologies, wearable devices, genomic data) and the emergence of advanced information and computational technologies (e.g., machine learning and artificial intelligence [AI]) offer an invaluable opportunity for applying innovative data science research in NIAID focus areas of infectious diseases such as HIV and COVID-19. Data science has the potential to identify high-risk individuals and communities and prioritize them for early biomedical or public health interventions, predict long-term clinical outcomes and disease progression, and evaluate public health policy impact. Key to addressing these complexities is a critical mass of health researchers with adequate knowledge, competencies, and skills to unlock important answers from Big Data to better understand, treat, and ultimately prevent these diseases and related comorbidities. However, there is a nationwide shortage of talent with such knowledge, competencies, and skills, especially in traditional academic settings. While junior faculty, as part of the generations of digital learners, have the greatest potential to develop their Big Data health science (BDHS) research, many face multiple structural barriers to conduct Big Data research. Such barriers include a lack of protected time to initiate new Big Data research, lack of opportunity to participate in funded Big Data research, and a lack of adequate mentoring. To address these gaps, we propose developing a "Big Data Heath Science Fellow" program for junior faculty (i.e., assistant professors) at the University of South Carolina (USC). Specifically, we plan to recruit 4 USC junior faculty per year and provide them with protected time (25%) to participate in comprehensive training, including: 1) courses for competency and skill development; 2) hands-on research and grant proposal development; and 3) interdisciplinary mentoring in Big Data research and professional development. The proposed training program will be implemented with the support of the existing infrastructure of the USC Big Data Health Science Center (BDHSC). With a mission to promote and support BDHS research at USC and across SC through capacity development, academic training, professional development, community engagement, and methodological advancement, BDHSC contains 5 content cores (EHR, geospatial, genomic, social media, and AI for sensing and diagnosis) and 2 supporting hubs (technology and business/entrepreneurship) with the involvement of 50 faculty from 10 USC college/schools. The proposed training will be an integral component of the BDHSC professional development mission. Upon the accomplishment of the proposed training, each trainee will be expected to: 1) obtain hands-on mentored research experience on an NIAID-funded project; 2) develop at least one Big Data-related manuscript on HIV or COVID-19; and 3) submit one grant application to NIAID or other appropriate funding source. The training program will foster a research environment to encourage individuals from all backgrounds to pursue further BDHS research in HIV, COVID-19, and other NIAID focus areas.