We offer support on the following areas:

Design and implementation of studies conducted at the population or field level to address applied research questions.

Statistical analysis and reporting of observational and experimental data using regression-based, hierarchical, longitudinal, survival, and causal inference methods, adapted to complex study designs, clustered data, and applied research questions.

Assessment of intervention outcomes in terms of clinical performance and associated costs, supporting comparison of effectiveness and economic implications across alternatives.

Development and application of predictive models to estimate risk, forecast outcomes, and support population-level planning and intervention strategies.