Ateneo - UPO

The module introduces the fundamentals of epidemic spreading models (SI, SIR, etc.) and the basic epidemiological concepts such as the basic reproduction number (R0), infection period, and epidemic thresholds.
Students will gain hands-on experience with dedicated simulation tools (e.g., GleamViz and Epydemix) to generate epidemic curves and analyze alternative spreading scenarios, in order to understand how models can provide useful insights for the evaluation of interventions in epidemic situations. Skills will be developed through video-lectures, lectures and practical sessions, focused on: 1. Understanding mathematical models of epidemic spreading (SI, SIR, etc.). 2. Calculating and interpreting key epidemiological parameters (R0, infection period, recovery rate). 3. Using simulation software to produce epidemic curves. 4. Analyzing different scenarios (e.g., contact reduction, lockdown, vaccination strategies) and assessing their impact on epidemic dynamics.

All materials needed are provided by the teacher.

1. Understand mathematical models of epidemic spreading (SI, SIR, SEIR, etc.) and their underlying assumptions. 2. Calculate and interpret key epidemiological parameters (R0, infection period, recovery rate, epidemic threshold). 3. Use dedicated software (GleamViz, Epydemix) to simulate epidemic spreading and generate epidemic curves. 4. Analyze alternative scenarios (contact reduction, non-pharmaceutical interventions, vaccination strategies) and assess their impact on epidemic dynamics. 5. Develop critical skills in interpreting simulations, recognizing the strengths and limitations of models as decision-support tools in health emergencies.

No background knowledge required

The module adopts a blended format, combining online lectures and in-class activities. * Asynchronous video lectures: introduce the fundamental concepts of epidemic models (SI, SIR, etc.) and key parameters (R0, infection period, recovery rate), supported by examples and theoretical explanations. * In-class activities: include frontal teaching to further explore models and their interpretation, followed by active learning sessions using simulation software (GleamViz, Epydemix). Students will be guided in setting up epidemic scenarios, generating curves, and analyzing the effects of different containment strategies.

Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://uniupo.it/en/services/services-students-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.

The exam is written and in-person, and consists of a quiz with multiple-choice questions. The final grade is expressed in thirtieths, and to pass the exam, a student must achieve at least 18/30. To pass the exam, students must demonstrate knowledge and understanding of at least the fundamental concepts of the subject. To achieve a passing grade, students must be familiar with the context of basic epidemic models (SI, SIR, etc.) and be able to demonstrate acquisition of the relevant basic notions, including key epidemiological parameters (R0, infection period, recovery rate) and the use of simulation software GleamViz and Epydemix to generate epidemic curves and analyze scenarios. To achieve a high grade, students must demonstrate complete mastery of the topics covered and the ability to correctly interpret simulation results.

- Introduction to epidemic models: basic concepts in mathematical epidemiology, SI, SIR models and their extensions. - Key parameters: basic reproduction number (R0), infection period, recovery rate, epidemic threshold. - Simulation software: introduction to GleamViz and Epydemix, overview of main features. - Epidemic scenario simulations: generating epidemic curves based on key parameters. - Policy interventions analysis: exploring scenarios with contact reduction, lockdowns, vaccination campaigns. - Discussion of results: critical interpretation of simulations, strengths and limitations of epidemiological models as decision-support tools.

Knowledge and understanding: acquire the fundamentals of epidemic spreading models (SI, SIR, etc.); understand key epidemiological parameters (R0, infection period, recovery rate, epidemic threshold); gain knowledge of the main features of GleamViz and Epydemix software for simulating epidemic scenarios. Applying knowledge and understanding: ability to set up epidemic simulations with realistic parameters; skills in analyzing generated epidemic curves and evaluating the impact of different containment policies (contact reduction, lockdowns, vaccination strategies). Communication skills: describe and discuss simulation results; interpret models and communicate their strengths and limitations clearly; understand how models can provide useful insights for evaluating interventions in epidemic situations. Learning skills: develop adequate proficiency in 1) basic epidemiological modeling, 2) the use of simulation software, 3) critical analysis of epidemic scenarios.