A Methodological Framework for Epidemiological Data Analysis: Dengue as a Model for Disease Surveillance and a One Health Perspective

Zoonotic and vector-borne diseases remain important public health problems, especially in regions where social, environmental, and epidemiological conditions favor their occurrence and spread. Transparent procedures for data organization, analysis, and interpretation are essential for translating epidemiological findings into public health information. In this context, dengue is an important model for epidemiological surveillance because its occurrence across diverse geographic settings involves seasonal patterns and demographic and environmental factors. Here, we propose a practical and structured framework for epidemiological data analysis in vector-borne diseases that can be applied to zoonotic diseases. We provide a step-by-step guide to organizing data, selecting descriptive and analytical methods, and interpreting results, using dengue as a model for disease surveillance and a One Health perspective. The framework is divided into five parts: (1) defining study scope and design, (2) conducting descriptive analysis, (3) examining association analyses of sociodemographic and clinical variables, (4) fitting multivariable analysis to integrate human and environmental data, and (5) performing statistical analysis through a step-by-step protocol. It combines dengue notification data with meteorological records to illustrate analyses at individual and population levels, while distinguishing observational associations from causal conclusions. The protocol demonstrates the analytical procedures using a freely available, user-friendly statistical software. The concepts and methodological approaches presented here can be adapted to other diseases according to their data sources, outcomes, and epidemiological context, supporting the development of epidemiological studies for disease surveillance, prevention, and control.