Maximizing Investigators' Research Award (R35)

PROJECT SUMMARY The "Tools for Transmission of Agents and Conditions (TRAC)" program will synergize statistical and mathematical modeling work in three areas of application: 1) Tuberculosis (TB) incidence and transmission; 2) monitoring substance use disorder (SUD) patterns; and 3) SARS CoV-2 transmission modeling. These three conditions are major public health problems, with TB being the leading cause of infectious disease death globally, SUD causing more deaths in the United States than HIV/AIDS in its peak, and SARS CoV-2 causing a pandemic with societal disruption and mortality exceeding anything we have experienced in the last century. We need improved analytical tools that leverage existing data to monitor these diseases, infer transmission hot spots, determine the efficacy of interventions, and understand the burden of these conditions. This program will bring together an expert group of quantitative researchers with skills that are readily applied to these problems. We also leverage our strong collaborations with clinician researchers and public health officials to ensure that the methods we develop are addressing important questions and consistent with our current understanding of these diseases. By creating a program to facilitate communication between these experts, we will enable greater innovation in modeling key aspects of these diseases and create exciting methodological synergies across diseases. Our team is well positioned to incorporate data from emerging technologies, including high throughput sequencing data to determine TB risk signatures and inform transmission links for TB and SARS CoV-2. Our expertise in machine learning, a broad range of statistical methodologies, and mathematical modeling will enable us to leverage the rich information in large databases that are emerging to better understand SUD patterns and identify risk signatures. We will also build infrastructure with our partners to make the analytical tools that we develop more accessible to public health practitioners and other researchers. The impact of this work is to develop a suite of analytical tools that leverage rapidly emerging rich data sets to improve our understanding of disease transmission patterns, monitor changing dynamics of these conditions, and understand intervention strategies that are most effective. This work will inform public health practice for these diseases and create reproducible tools that can be used in an ongoing way.