Spatial approaches for optimizing TB active case finding: an investigation of activity spaces, mobility patterns, and local burden of disease in Nairobi, Kenya

PROJECT SUMMARY/ABSTRACT Background: Tuberculosis (TB) remains one of the leading infectious causes of death globally, yet an estimated 3-4 million people who develop TB are not diagnosed each year. This case-detection gap critically impedes global efforts to end the TB epidemic. Identification of individuals with suspected TB through active case finding (ACF) and linking them to care can help to achieve earlier diagnosis and treatment and prevent onward transmission. ACF aims to diagnose TB by screening people in the community and among persons at risk as opposed to passive case finding which requires affected individuals with symptoms to seek care at health facilities and then be evaluated for TB. Project: In this study, we will use spatial approaches to optimize active case finding strategies, through three research aims: (1) employ multiple sources of human mobility and activity space data, collected via a combination of surveys, individual geo-tracking, and aggregated cell phone locations to pinpoint precise geographic locations within Nairobi, Kenya, with the highest potential yield for TB screening; (2) develop a geospatial statistical model to estimate neighborhood-level local TB burden in Nairobi utilizing serial TB prevalence survey data alongside case notifications and spatial covariates; and (3) produce an individual-based TB transmission model to simulate the impact of spatially-targeted ACF strategies in Nairobi. Candidate: I am an infectious diseases physician-scientist and epidemiologist with a background in global health policy, TB and HIV epidemiology, and geospatial analysis as well as experience conducting research in South Africa, Uganda, and Kenya. My long-term career goal is to become an independent investigator working to develop data-driven, targeted public health strategies for controlling the TB and HIV epidemics in high-burden settings. Career development plan: I am pursuing a K01 Career Development Award to establish my research niche at the intersection of geospatial analysis, human mobility, and infectious diseases epidemiology, with specific applications to TB and HIV. I seek advanced training and further research mentorship to develop additional skills in (i) geospatial modeling, (ii) agent-based modeling, (iii) human mobility data, and (iv) responsible conduct of research in international settings. Mentors and Environment: Dr. Jennifer Ross, an expert in infectious disease epidemiology and geospatial modeling, will oversee my overall career development and serve as my primary mentor. Co-mentors are Dr. David Horne, an expert on TB aerobiology and transmission; Dr. Videlis Nduba, senior scientist at the Kenya Medical Research Institute (KEMRI); and Dr. Abraham Flaxman, lead modeler at the Institute for Health Metrics and Evaluation (IHME). Scientific advisers consist of Dr. Thomas Hawn (TB immunology), Dr. Jane Ong’ang’o (population-based surveys in Kenya), and Dr. Adrian Dobra (data science & mobility data). This study will build upon an ongoing collaboration between the University of Washington and KEMRI Centre for Respiratory Diseases Research.