TRANSLATING INFECTIOUS DISEASE SURVEILLANCE DATA INTO TIMELY PUBLIC HEALTH ACTION: A TRANSLATIONAL RESEARCH APPROACH

Abstract

Infectious disease surveillance systems generate vast quantities of epidemiological data intended to inform early detection, response, and prevention strategies. However, persistent gaps remain between surveillance outputs and their timely translation into public health action. This study examines how infectious disease surveillance data can be effectively translated into decision-making processes and community-level interventions. Using a mixed-methods translational research design, the study integrates quantitative analysis of routine surveillance data with qualitative insights from public health practitioners involved in outbreak response. Findings indicate that while surveillance systems are technically robust, delays in interpretation, communication, and institutional coordination significantly limit their practical impact. The study demonstrates that translational mechanisms—such as structured data interpretation frameworks, cross-sector collaboration, and feedback loops—can enhance the responsiveness and effectiveness of public health action. The findings contribute to translational public health research by highlighting strategies for strengthening the link between surveillance evidence and population-level disease control.