Brief Commentary: Using a Logic Model to Integrate Public Health Informatics Into Refinements of Public Health Surveillance System

Abstract

The COVID-19 pandemic has been a watershed moment in public health surveillance, highlighting the crucial role of data-driven insights in informing health actions and policies. Revisiting key concepts— public health, epidemiology in public health practice, public health surveillance, and public health informatics—lays the foundation for understanding how these elements converge to create a robust public health surveillance system framework. Especially during the COVID-19 pandemic, this integration was exemplified by the WHO efforts in data dissemination and the subsequent global response. The role of public health informatics emerged as instrumental in this context, enhancing data collection, management, analysis, interpretation, and dissemination processes. A logic model for public health surveillance systems encapsulates the integration of these concepts. It outlines the inputs and outcomes and emphasizes the crucial actions and resources for effective system operation, including the imperative of training and capacity development.