Making Sense of the Evidence to Inform Programmes, Policies, and Practice

About

In the rapid-evolving landscape of public health research, systematically synthesizing evidence is critical for informed and sound decision-making and advancing scientific understanding. This course offers a thorough introduction to the methods and tools required to evaluate, synthesize, and apply evidence in public health practice and research. Designed for researchers and public health practitioners at any level, this course provides foundational knowledge of systematic and scoping reviews, meta-analysis, and the integration of evidence into actionable recommendations.

Participants will engage with the principles of evidence reviews, including protocol development, question formulation, literature search strategies, data extraction, and quality appraisal. The course introduces various study designs essential for public health, enabling participants to conduct rigorous risk-of-bias assessments. A unique feature of the course is an introduction to the application of meta-analysis, a statistical toolkit to pool findings from multiple studies. Participants will learn how the basic concepts of meta-analyses (including Bayesian meta-analysis), assess heterogeneity, and interpret pooled results using real-world examples.

The course also incorporates modern tools and approaches, including AI-powered instruments to streamline various stages of the review process and enhance productivity.

Course leader

Prof. Gian Luca Di Tanna & Dr. Joseph Alvin Ramos Santos (SUPSI - The University of Applied Sciences and Arts of Southern Switzerland)

Target group

Practitioners, researchers, and graduate students

Course aim

By the end of the course the participant will:
- Understand the key steps in conducting systematic and scoping reviews, including literature mapping and quality appraisal;
- Gain knowledge of pivotal study designs, such as randomized controlled trials, and their strengths, limitations and susceptibility to bias;
- Master the foundational methods of meta-analysis, including heterogeneity assessment and publication bias detection;
- Develop proficiency in using AI tools to organize and synthesize evidence for public health applications.

Fee info

Discounts are available for PhD and Master’s students, participants from UMICs and LMICs, and members of LSS partner institutions (USI, SUPSI, Swiss TPH, and SSPH+). For details on fees and available discounts, contact us at info@ssph-lugano-summerschool.ch or visit our website.