National Taiwan Normal University Course Outline
Spring , 2024

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I.Course information
Serial No. 2591 Course Level Master / PhD
Course Code MAC8031 Chinese Course Name 流行病學的數理模型專題(一)
Course Name Topics of Mathematical Models in Epidemiology (I)
Department Department of Mathematics
Two/one semester 1 Req. / Sel. Sel.
Credits 3.0 Lecturing hours Lecture hours: 3
Prerequisite Course ◎1. This is a cross-level course and is available for junior and senior undergraduate students, master's students and PhD students. 2. If the listed course is a doctroal level course, it is only available for master's students and PhD students.
Comment
Course Description
Time / Location Wed. 2-4 Gongguan S201
Curriculum Goals Corresponding to the Departmental Core Goal
1. Our main course outcomes include the topic: How mathematical models of disease transmission and human policy interventions affect the spread of viruses in social groups. Master:
 1-2 Being able to reason and induct with mathematical logic
 1-3 Being able to think mathematically and critically
 1-5 Being able to use mathematics as tools to learn other subjects
 3-2 Possessing the abilities to think independently, criticize, and reflect
 3-4 Having insights, intuitions, and senses of mathematics
Doctor:
 1-2 Being able to reason and induct with mathematical logic
 1-3 Being able to think mathematically and critically
 1-5 Being able to use mathematics as tools to learn other subjects
 3-2 Possessing the abilities to think independently, criticize, and reflect
 3-4 Having insights, intuitions, and senses of mathematics
2. In this course, we will guide and learn the mathematical theory needed to model the spread of diseases. Master:
 1-2 Being able to reason and induct with mathematical logic
 1-3 Being able to think mathematically and critically
 1-5 Being able to use mathematics as tools to learn other subjects
Doctor:
 1-2 Being able to reason and induct with mathematical logic
 1-3 Being able to think mathematically and critically
 1-5 Being able to use mathematics as tools to learn other subjects
3. We will help the students to promote and develop the problem-solving skills with applied mathematics in the behaviors of spread of viruses. Master:
 2-1 Being able to communicate and express mathematically
 2-3 Being able to lead or collaboratively work with peers
 3-2 Possessing the abilities to think independently, criticize, and reflect
 3-3 Being willing to work collaboratively
 4-3 Possessing a variety of beliefs regarding mathematics values and mathematics learning
Doctor:
 2-1 Being able to communicate and express mathematically
 2-3 Being able to lead or collaboratively work with peers
 3-2 Possessing the abilities to think independently, criticize, and reflect
 3-3 Being willing to work collaboratively
 4-3 Possessing a variety of beliefs regarding mathematics values and mathematics learning

II. General Syllabus
Instructor(s) CHERN, Jann-Long/ 陳建隆
Schedule

This is one of EMI courses. In this topics course (I), we will study a comprehensive and further investigations study to the fundamental principles and techniques used in modeling the spread of infectious diseases within populations. The course begins by establishing the theoretical foundations of epidemiological modeling, including compartmental models such as the stochastic SIR (Susceptible-Infected-Recovered) model, etc. Students will learn to formulate, analyze, and interpret these models, as well as understand the significance of key epidemiological parameters. Additionally, the course explores practical applications through case studies and simulations. By the end of this course, students will have a solid grasp of the mathematical foundations underpinning epidemiological modeling.

There are also two main objectives for this topics course:

(1) Investigate the mathematics and methods required as studying the basic principles of differential equation/stochastic models in infectious disease epidemiology.

(2) Applying mathematical models to existing data as little projects/experiments (e.g., math. models vs. growth of HIV, Covid-19 infectious population respectively).  

Below is our teaching progress and topics:

Weeks 1-10:

Part I. Investigate the mathematics and methods required as studying the basic principles of differential equation(DE)/Stochastic models in infectious disease epidemiology

1. Study and Investigate the DE/Stochastic Mathematical Epidemiology

2. Compartmental Models for Disease Transmission; Endemic Disease Models; Epidemic Models

3. Models with Heterogeneous Mixing; Models for Diseases Transmitted by Vectors

4. Discussions of Exercises and Reports of Topics

Weeks 11-14 

Part II. Applying mathematical models to existing data as little projects/experiments (e.g., math. models vs. growth of HIV, Covid-19 infectious population respectively):

5. Models for Tuberculosis.

6. Models for HIV/AIDS

7. Discussions of Exercises and Reports of Topics.

Week 15-16: Project Studies (in Working Groups).

Instructional Approach
Methods Notes
Formal lecture In this course, we will study and investigate the basic principles and knowledge of related mathematical models and algorithms with examples.
Group discussion The key points of the related studying topics are discussed in groups by students.
Lab/Studio The students of the course will report in groups the related algorithms for each selected mathematical models.
Case studies The students of the course will report in groups the related algorithms and computer programs for each selected topics.
Grading assessment
Methods Percentage Notes
Assignments 30 % The students will need to do the home works of mathematical models and its applications to various mathematical models of infectious diseases.
Class discussion involvement 15 % We will ask the group discussions and seminar to test the students for the study of basic related mathematical models and knowledges.
Presentation 15 % We will ask the group reports to test the students for the study of basic related mathematical models and knowledges.
Shows/ Exhibitions 40 % For each group students will read and give a report of selected exercises and related topics of mathematical models of infectious diseases.
Required and Recommended Texts/Readings with References
  • Brauer, Fred; Castillo-Chavez, Carlos; Feng, Zhilan, Mathematical models in epidemiology. With a foreword by Simon Levin. Texts in Applied Mathematics, 69. Springer, New York, 2019. xvii+619 pp.
  • Hsu, Sze-Bi, Ordinary Differential Equations with Applications, Word Scientific Press, 2006 (First edition), 2013 (Second edition).
  • Meksianis Z. Ndii , Asep K. Supriatna, Stochastic Mathematical Models in Epidemiology.
  • Linda J. S. Allen, An Introduction to Stochastic Epidemic Models.

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