Modeling and validating dynamic accessibility to healthcare with system science approach

In public health sciences, people’s accessibility to healthcare determines how easily they can reach and utilize health services. For researchers and policy makers, modeling and measuring accessibility to healthcare is key to narrowing disparities and achieving health equality. Each year, a plethora of research efforts aim to model, estimate, and map geographic disparities in healthcare accessibility, informing targeted interventions in underserved areas. These studies have predominantly adopted either a travel cost-based approach or supply- demand approach to measure accessibility. Both approaches are population-based and temporally static, assuming uniformity among individuals and disregarding temporal factors. The derived accessibility measures fail to account for temporal variations, as well as heterogenous individuals and their interactions. To address these limitations, I will propose new conceptual frameworks to model and validate accessibility to healthcare using a system science approach. This two-year small project will study people’s access to healthcare in a dynamic and social system that involves complex interactions among individuals, as well as interactions between individuals and the environment (e.g., transportation network and health facilities). I will pioneer two models in system science, namely the system dynamics model and the agent-based model, to represent this system. I will implement these two types of models in the state of Florida in the context of recent ‘triplepidemic’ (flu, RSV and COVID) during 2022-23 season, and attempt to validate the model results. This study will contribute to the literature by adding a time dimension, individuals’ heterogeneity, and their social networks to the models of healthcare accessibility. Additionally, this study will investigate a novel method to validate healthcare accessibility models, addressing a persistent gap in existing research. Researchers and policy makers can use the newly developed tools to better monitor dynamics of healthcare accessibility and to mitigate health disparities more precisely with spatio-temporally dependent intervention. Project Number: 1R03AI185905-01A1 | Fiscal Year: 2025 | NIH Institute/Center: National Institute of Allergy and Infectious Diseases (NIAID) | Principal Investigator: Liang Mao | Institution: UNIVERSITY OF FLORIDA, GAINESVILLE, FL | Award Amount: $137,064 | Activity Code: R03 | Study Section: Organization and Delivery of Health Services Study Section[ODHS] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R03AI18590501A1