Big Data Health Science Fellow Program in Infectious Disease Research

Abstract The multiple, massive, and rich Big Data streams in healthcare (e.g., electronic health records, mobile technologies, wearable devices, genomic data) and the emergence of advanced information and computational technologies (e.g., machine learning and artificial intelligence) offer an invaluable opportunity for applying

innovative Big Data science research in NIAID focus areas of infectious diseases such as HIV/AIDS and COVID-19. Big 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 research agenda, many face multiple structural barriers to conduct Big

Data science research. Such barriers include a lack of protected time to initiate new interdisciplinary 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 early career junior

faculty (i.e., assistant professors) at health science schools (e.g., medicine, public health, nursing, pharmacy, social work) at the University of South Carolina (USC). Specifically, we plan to recruit 4 USC health science junior faculty per year and provide them with protected time (25%) to participate in the comprehensive training

program, including: 1) courses for competency and skill development in Big Data research and professional development; 2) participation in hands-on research and grant proposal development; and 3) rich mentoring experience 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), one of USC’s Excellence Initiatives. BDHSC’s mission is to promote and support Big Data health science research at USC and across SC through capacity development, academic training, professional

development, community engagement, and methodological advancement. BDHSC contains 5 content cores (electronic health records, geospatial, genomic, social media, and bio-nanomaterial data) and 2 supporting hubs (business/entrepreneurship and technology) with the involvement of 43 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 diverse backgrounds, including those from underrepresented groups, to pursue further Big Data health science research in HIV, COVID-19, and other NIAID focus areas.