|
課程名稱 |
傳染病群突發資料分析實務
Practical Guide for Analysis of Infectious Diseases Outbreaks |
|
開課學期 |
112-2 |
|
授課對象 |
公共衛生學院 全球衛生博士學位學程 |
|
授課教師 |
吳亞克 |
|
課號 |
MGH7038 |
|
課程識別碼 |
853EM0380 |
|
班次 |
|
|
學分 |
1.0 |
|
全/半年 |
半年 |
|
必/選修 |
選修 |
|
上課時間 |
|
|
上課地點 |
|
|
備註 |
初選不開放。本課程以英語授課。寒假密集課程，需自備筆電。日期：2024/1/15-19。僅開放已修課完畢之學生於加選階段選課。
總人數上限：30人 |
|
|
|
|
課程簡介影片 |
|
|
核心能力關聯 |
核心能力與課程規劃關聯圖 |
|
課程大綱
|
|
為確保您我的權利,請尊重智慧財產權及不得非法影印
|
|
課程概述 |
We begin with understanding of the disease occurrence and continue on finding such important epidemiologic characteristics as a time-varied reproduction number. The course will mainly be based on explaining two methods for finding the reproduction number: Wallinga-Teunis method and Cori et al. method. Additionally, the use of some freely accessible R packages will be demonstrated. |
|
課程目標 |
The aim of the course is to give practical guide for students to perform first steps analysing the epidemiological data, especially to estimate the strength of spread of infectious diseases with particular focus on the spread of COVID-19. |
|
課程要求 |
Familiarity with random distributions. Basics in R programing language (you may go with other languages like Python or Julia if you prefer). Interest in infectious diseases modeling |
|
預期每週課後學習時數 |
|
|
Office Hours |
另約時間 備註： Arranged b/w the instructor and the student |
|
指定閱讀 |
|
|
參考書目 |
Shorter paper (optional reading):
1) Gostic KM, McGough L, Baskerville EB, Abbott S, Joshi K, et al. Practical considerations for measuring the effective reproductive number, Rt. PLOS Computational Biology 2020;16(12):e1008409. (http://dx.doi.org/doi:10.1371/journal.pcbi.1008409)
2) Thompson RN, Stockwin JE, van Gaalen RD, et al. Improved inference of time-varying reproduction numbers during infectious disease outbreaks. Epidemics. 2019;29:100356 (http://dx.doi.org/doi:10.1016/j.epidem.2019.100356)
3) Chatzilena A, van Leeuwen E, Ratmann O, Baguelin M, Demiris N. Contemporary statistical inference for infectious disease models using Stan. Epidemics. 2019;29:100367 (http://dx.doi.org/doi:10.1016/j.epidem.2019.100367)
4) Cobey S. Modeling infectious disease dynamics. Science. 2020;368(6492):713-4 (http://dx.doi.org/10.1126/science.abb5659)
5) Bjornstad ON, Shea K, Krzywinski M, Altman N. Modeling infectious epidemics. Nat. Methods, 2020;17(5):455-6 (https://dx.doi.org/10.1038/s41592-020-0822-z)
Longer books (possible future interest):
1) Handbook of Infectious Disease Data Analysis. Eds: Held L, Hens N, O'Neill P, Wallinga J. 1st ed. New York: Chapman and Hall/CRC. 2019
2) Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB. Bayesian data analysis. Third Edition. Chapman & Hall / CRC Press. 2013 (can be downloaded from http://www.stat.columbia.edu/~gelman/book/) |
|
評量方式
(僅供參考) |
|
|
針對學生困難提供學生調整方式 |
|
上課形式 |
|
|
作業繳交方式 |
|
|
考試形式 |
|
|
其他 |
由師生雙方議定 |
|
|
週次 |
日期 |
單元主題 |
|
Week 1-1 |
1/15 |
Introduction to modeling of infectious diseases. Definition of the effective reproduction number (Rt) - three ways to calculate it; estimating Rt using Cori et al. method |
|
Week 1-2 |
1/15 |
Practice in R: downloading the data for dengue fever outbreak |
|
Week 2-1 |
1/16 |
Estimating Rt using Wallinga-Teunis method |
|
Week 2-2 |
1/16 |
Practice in R: analyzing the spatial spread of the disease, plotting maps in R |
|
Week 3-1 |
1/17 |
Compartmental models; offspring distribution |
|
Week 3-2 |
1/17 |
Practice in R: estimating instantaneous and piecewise constant Rt for dengue outbreak in Tainan using piecewise estimators |
|
Week 4-1 |
1/18 |
Dengue fever - overview |
|
Week 4-2 |
1/18 |
Introduction to Stan (probabilistic programming language). Inference of Rt within Bayesian framework and using RStan, interface of Stan in R |
|
Week 5-1 |
1/19 |
Model selection. Practice in R: estimating piecewise constant and smoothed Rt for dengue outbreak in Tainan |
|
Week 5-2 |
1/19 |
Considering the role of local and imported cases for estimating the Rt. Preparing for the final project: explaining the main aims and analysis of dengue outbreak in Kaohsiung |
|