Organisation of the course and brief introduction to Mathematical Epidemiology

Organisation of the course and brief introduction to Mathematical Epidemiology

by Julien Arino

Formal & Physical Sciences Mathematics PBWApplied mathematicsPBWHMathematical modelling
🎙 Julien Arino 👥 618 📅 October 9, 2022 ⏱ 25 min 👁 206 📄 lecture 🧭 2026-08-17
Available in: English (current) Français

Keywords

mathematical epidemiologyepidemiology terminologyhistory of epidemiologycompartmental modelsinfectious disease modeling

Summary

This lecture is the first in a course on One Health modeling for emerging infectious diseases. The instructor, Julien Arino, begins by outlining the course structure, which includes an introductory part and three thematic blocks on coronaviruses, influenza, and environmental transmission. He then provides a brief introduction to mathematical epidemiology, starting with key terminology such as incidence versus prevalence, and the distinction between ’exposed’ in mathematical models versus real-world exposure. He discusses epidemic curves and defines epidemic, pandemic, and endemic. The lecture covers the historical development of mathematical epidemiology, mentioning Daniel Bernoulli’s 1760 smallpox model, Ronald Ross’s work on malaria, and the seminal Kermack-McKendrick model. He highlights important books and papers, including those by Macdonald, Hethcote, Anderson and May, and Diekmann et al. The lecture concludes with a discussion of modern trends, including the use of computational models, network models, and the increasing availability of data.

146 words

Critical Evaluation

Value of the Information & Strength of the Argument

The lecture provides a valuable overview of mathematical epidemiology, clarifying important terminology and historical context. The argumentation is clear and well-structured, though it remains introductory and does not delve into technical details. The instructor’s expertise is evident, and he effectively communicates the relevance of mathematical modeling in epidemiology.

Scientific Rigor, Source Quality, Title Accuracy

The lecture demonstrates scientific rigor through its accurate historical references and clear explanations. However, sources are mentioned but not formally cited, and the title accurately reflects the content. The instructor’s academic background adds credibility, but the lack of formal citations limits the ability to verify specific claims.

110 words

Title / Content Match

The title accurately reflects the content, which covers course organization and a brief introduction to mathematical epidemiology.

Quality & Reliability

7/10

The lecture is given by a university professor in mathematics, providing a structured overview of mathematical epidemiology. It includes historical references and clarifies terminology, but lacks detailed citations and in-depth technical derivations.

Chapters

Cited Sources

  • Course slides — Slides for this lecture, containing links to referenced works.

Concurring Sources

  • Kermack-McKendrick model — The model is mentioned as a landmark in mathematical epidemiology.
  • Basic reproduction number — The concept is discussed in the context of computing R0.

Contribution & Novelties

This lecture provides a concise introduction to mathematical epidemiology, emphasizing terminology and historical context. It serves as a foundation for the course, clarifying common misconceptions and highlighting key references.

Pour aller plus loin :

72 words

Radar Profile

The radar profile shows balanced scores across information quantity, quality, technical level, and reliability, with a slight emphasis on quality and reliability. This indicates a well-structured introductory lecture with solid content, though not highly technical.

Reliability 7/10