Evaluating Community-Based Approaches to Infectious Disease Monitoring in Low-Resource Settings: A Mixed-Methods Analysis of US Rural and Underserved Communities

Abstract

This study evaluates the effectiveness, sustainability, and scalability of community-based approaches to infectious disease surveillance in low-resource settings across the United States. Using a mixed-methods approach combining quantitative data from three community-based surveillance programs (n=47 communities) and qualitative insights from key stakeholders (n=87), we assessed implementation factors, detection efficacy, cost-effectiveness, and community engagement outcomes. Results indicate that community-based surveillance systems detected outbreaks an average of 9.2 days earlier than traditional surveillance methods and identified 37% more cases of reportable conditions in the studied communities. Success factors included integration with existing community health worker programs, simplified data collection protocols, and bidirectional information sharing. Key challenges involved sustainable funding, technology limitations, and integration with formal health systems. Our findings suggest that community-based surveillance approaches can effectively complement traditional disease monitoring systems in low-resource US settings, particularly in rural Appalachia, tribal lands, and underserved urban communities. We propose an adaptive implementation framework to guide context-specific deployment of these approaches, with particular attention to governance structures, technical infrastructure requirements, and community ownership models.