Program Overview

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Introduction to the Master in Global Epidemiology

The Master in Global Epidemiology: Advancing Health with AI and One-Health Perspectives (GIAHE) is a first-level university master's program designed to train highly qualified professionals to tackle complex global healthcare challenges through an innovative and multidisciplinary approach.

Program Description

This outstanding curriculum provides a practical and research-oriented approach, preparing professionals to react promptly and effectively to global healthcare emergencies and develop innovative strategies to prevent and monitor diseases, taking into account the interconnection between human, animal, and environmental health.

Learning Content

The program develops the right skills to analyze healthcare inequalities, plan innovative interventions, and react to global emergencies. Furthermore, it trains leaders capable of integrating human, animal, and environmental health in sustainable solutions for the future of public healthcare. The course is provided only online and on-demand, offering students the greatest flexibility. The course ends with a project work focused on one of the topics covered during the Master, discussed before a special committee that will grade the dissertation.

Recipients and Career Opportunities

The Master in Global Epidemiology trains highly qualified professionals capable of tackling global healthcare challenges through an innovative and multidisciplinary approach. At the end of the course, professionals will gain advanced knowledge in epidemiology, AI, and One-Health, and the ability to analyze the interactions between human, animal, and environmental health.

Program Structure

The Master provides in-depth knowledge on the following topics:

Module 1 Epidemiology Notions

Historical and theoretical fundamentals, descriptive and analytical epidemiology, disease dissemination, and risk factors. Main studies and investigations on epidemic outbreaks. Focus on epidemiology of chronic diseases and on epidemiologic surveillance methods.

Module 2 Quantitative and Biostatic Methods

Statistical epidemiology data analysis methods. Descriptive statistics, inference, and advanced models for epidemiologic analysis. Hands-on tutorials on statistical software, such as R and Python.

Module 3 Global Health

Main global healthcare issues, disease load, distribution, and global impact. Social and economic determinants of healthcare inequalities. Focus on environmental and planetary health, impact of ecological issues on human health. Healthcare emergency trends, including pandemics and reaction to global crises.

Module 4 One-Health Approach

Integration between human, animal, and environmental health. Analysis of zoonotic diseases, antimicrobial resistance, food safety, and sustainability. Analysis of One-Health healthcare policies and strategies to tackle any related health issues.

Module 5 Artificial Intelligence and Machine Learning in Epidemiology

Artificial Intelligence (AI) and Machine Learning (ML) to prevent, monitor, and foresee diseases and their diffusion, with identification of the risk factors. Insight on predictive models, bias, privacy, and ethical implications.

Module 6 Advanced Biostatistics

Advanced statistical analysis techniques applied to epidemiology. Analysis of hierarchical data and machine learning for predictive analysis. Hands-on tutorials with advanced software, such as R and Python.

Module 7 One-Health

Integration between human, animal, and environmental health, case studies on zoonosis, antimicrobial resistance, and food safety. One-Health framework principles and global political strategies. Virtual labs to simulate cross-cutting interventions and complex scenarios and develop sustainable and innovative solutions to global health challenges.

Module 8 Risk Analysis and Summary of Evidence

Techniques to identify, evaluate, and mitigate health risks. Use of meta-analysis, systemic revisions, and evidences for policy-making. Use of advanced data analysis and evidence summary software. Practical sessions and real case studies for a hands-on learning approach.

Objectives and Faculty

This Master, in its first edition, has been organized in partnership with the National Department of Public Health of the University of Antioquia (Colombia) to train specialists who can understand and analyze the dynamics of the interactions between human, animal, and environmental health.

General Information

• Thematic area: Health, environment, and territory
• End of classes: 30/10/2026
• Mandatory attendance: 70%
• Minimum available spots: 5
• Maximum available spots: 240
• First installment: 3,922.50
• Second installment: 2,600.00

Selection Process

Admission to the Master is based on degrees only. The methods are described on the Master's participation form.

Allowances

• Fee waiver for attendees with a disability
• PA110 and students who graduated with honors
• University staff
• Enrolment fee for auditors

Attendance Requirements

The Master's attendance is required, and the minimum threshold to obtain the title and the certificate of attendance is 70% of online lessons.

Internship

The Master does not provide for any internships, only a project work on one of the topics covered during the Master. The dissertation will be discussed online, before an assessing committee.

Program Details

• Classes start: 13/12/2025
• Duration: One year
• Venue: Padua
• Language: Italian
• ECTS: 60
• Teaching method: Distance learning
• Total enrollment fee: 6,522.50
• Pre-enrollment deadline: 24/11/2025