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Epidemiology Special Lecture

Latest update on: 2 October 2024

1. Overview

To learn epidemiology, an excellent textbook is used (shown below). Technical terms are explained in both English and Japanese, since knowing Japanese terms is needed to read epidemiological research papers in Japanese and reports from MHLW.

Doctoral course students have to do presentation to explain the contents of the text chapter once and the same role with master course students in other time. Master course students have to ask at least one question each time. All participants also should read the chapter in advance.

I strongly recommend for all participants to solve questions in the end of each chapter by oneself.

2. Plan

The lecture is done in the second semester on Thursday, 13:10-14:40 (3rd time block of the Graduate School of Health Sciences) at GSICS 202 with Zoom if you cannot come to the room.

Zoom access information will be given in BEEFPLUS [3K444]. Question and answer will be done via the "forum" of BEEFPLUS.

( 1) Orientation and Assignment for Doctoral Students (with introducing preface and contents), Chap. 1. Introduction to Epidemiologic Thinking: Oct. 3 (Preface and Chapter 1, Notes on technical terms in Japanese for Chapters 1 and 2)
( 2) Chap. 2. Pioneers in Epidemiology and Public Health: Oct. 10 (presentation)
( 3) Chap. 3. What Is Causation?: Oct. 17 (presentation, Notes on technical terms in Japanese for Chapters 3)
( 4) Chap. 4. Measuring Disease Occurrence and Causal Effects (pp.38-56): Oct. 24 (presentation, Notes on technical terms in Japanese for Chapters 4)
( 5) Chap. 4. Measuring Disease Occurrence and Causal Effects (pp.57-68): Oct. 31 (presentation)
( 6) Chap. 5. Types of Epidemiologic Studies (pp.69-87): Nov. 7 (handout)
( 7) Chap. 5. Types of Epidemiologic Studies (pp.87-109): Nov. 14 (handout w/o image)
( 8) Chap. 6. Infectious Disease Epidemiology (by Rimsha-san): Nov. 21 (handout, libuseTokyoRt.R, Reed-Frost projection code in R, Reed-Frost projection result)
( 9) Chap. 7. Dealing with Biases (by Asai-san): Nov. 28 (handout)
(10) Chap. 8. Random Error and the Role of Statistics: Dec. 5 (handout, R code for Chapter 8 tables and figures)
(11) Chap. 9. Analyzing Simple Epidemiologic Data: Dec. 12 (handout, R code for Chapter 9)
(12) Chap. 10. Controlling Confounding by Stratifying Data: Dec. 19 (handout, R code for Chapter 10)
(13) Chap. 11. Measuring Interactions: Jan. 9 (handout, R code for Chapter 11)
(14) Chap. 12. Using Regression Models in Epidemiologic Analysis (handout, R code for chapter 12): Jan. 16
(15) Chap. 13. Epidemiology in Clinical Settings (handout): Jan. 23

3. Evaluation

Based on several mini-reports at BEEFPLUS and discussion.

4. Textbook

Kenneth J. Rothman (2012) Epidemiology: An Introduction, 2nd Ed., Oxford University Press, Oxford. (Companion site: Possible answers to chapter questions are submitted by the readers)

4-1. Further Readings

Bonita R, Beaglehole R, Kjellström T & WHO (2006). "Basic epidemiology, 2nd ed." (The full text is freely available in English, Japanese, and several other languages)

Rothman KJ, Greenland S, Lash TL (2012) Modern Epidemiology, 3rd Ed., LWW.

Lash TL, VanderWeele TJ, Haneuse S, Rothman KJ (2020) Modern Epidemiology, 4th Ed., LWW. ISBN/ISSN: 9781451193282

Westreich D (2019) Epidemiology by Design: A Causal Approaches to Health Sciences. Oxford Univ. Press

Horney JA [Ed.] (2017) Disaster Epidemiology: Methods and Applications. Academic Press

Krickeberg K, Van Trong P, Thi My Hanh P (2019) Epidemiology: Key to Public Health (Statistics for Biology and Health). Springer

5. Office hour

For the students of the Graduate School of Health Sciences, Tuesday, 18:00-18:30, at Myodani campus E707. For the students of GSICS, Thusday afternoon at Frontier Building Room 717. In 2020 and 2021, basically via Zoom. Taking appointment is recommended.

6. Message to the students

Done in English.

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