- Level Foundation
- المدة
- الطبع بواسطة The University of Hong Kong
- Total students 9,512 enrolled
-
Offered by
عن
With supplementary module on COVID-19
Including our study results, final size estimation for superspreading clusters, the Chinese experience for global preparedness, and more.
"If history is our guide, we can assume that the battle between the intellect and will of the human species and the extraordinary adaptability of microbes will be never-ending." (1)
Despite all the remarkable technological breakthroughs that we have made over the past few decades, the threat from infectious diseases has significantly accelerated. In this course, we will learn why this is the case by looking at the fundamental scientific principles underlying epidemics and the public health actions behind their prevention and control in the 21st century.
This is the second (spread of infectious diseases) of the four courses, covers these topics:
- Basic Concepts in Infectious Disease Epidemiology
- Epidemiologic Triangle: The Pathogen, The Host and The Environment
- Evidence Synthesis
- Infectious Disease Modelling
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(1) Fauci AS, Touchette NA, Folkers GK. Emerging Infectious Diseases: a 10-Year Perspective from the National Institute of Allergy and Infectious Diseases. Emerg Infect Dis 2005 Apr; 11(4):519-25.
What you will learn
- Epidemic Curve
- Timescale of Disease Transmission
- The Pathogen: Evolution (Case1: Myxoma Virus)
- The Pathogen: Evolution (Case 2: Human Immunodeficiency Virus)
- The Pathogen: Evolution (Case 3: Antimicrobial Resistance)
- The Host: How Age Affects Disease Transmission and Severity
- The Host: Sexual Mixing
- The Environment
- Uncertainty in Modeling (Dynamic Uncertainty, Parametric Uncertainty)
- Uncertainty in Modeling (Structural Uncertainty, Scenario Uncertainty)
- 流行病学曲线图
- 疾病传播的时幅
- 病原体:进化(病例1:粘液瘤病毒)
- 病原体:进化(病例2:人类免疫缺陷病毒)
- 病原体:进化(病例3:抗菌素耐药性)
- 宿主:年龄如何影响疾病的传播和严重性
- 宿主:性混合
- 环境
- 建模的不确定性(动态不确定性,参数不确定性)
- 建模的不确定性(结构不确定性,情境不确定性)
Skills you learn
Syllabus
Week 1: Spread (Infectious Disease Epidemiology)
- Basic Concepts in Infectious Disease Epidemiology
- Epidemic Curve
- What is Incubation Period and Use of Incubation Period
- Transmissibility of Communicable Diseases
- Timescale of Disease Transmission
- What is Severity of Infectious Disease
- Difficulties Associated with Severity Estimation
Week 2: Spread (Epidemiological Triangle)
- Epidemiologic Triangle
- The Pathogen: The Effects of Dose and Pathogen Genetics
- The Pathogen: Evolution (Case1: Myxoma Virus)
- The Pathogen: Evolution (Case 2: Human Immunodeficiency Virus)
- The Pathogen: Evolution (Case 3: Antimicrobial Resistance)
- The Host: Overview
- The Host: How Age Affects Disease Transmission and Severity
- The Host: Sexual Mixing
- The Environment
- Supplementary Module: Influenza Immunity and Transmission In Time, Age and Space
Week 3: Spread (Infectious Disease Modeling)
- Infectious Disease Modelling (Susceptible Infectious Removed Model)
- Evidence Synthesis
- Uncertainty in Modeling (Dynamic Uncertainty, Parametric Uncertainty)
- Uncertainty in Modeling (Structural Uncertainty, Scenario Uncertainty)
- Supplementary Module: Precision Public Health
Auto Summary
"Epidemics II" is a compelling course within the Science & Engineering domain, designed to delve into the science, prevention, and control of epidemics. This course offers a unique opportunity to learn from leading scientists at HKU and includes a special module on COVID-19, as well as panel discussions with world-renowned experts in the field of epidemics. Key topics covered include: - Basic Concepts in Infectious Disease Epidemiology - The Epidemiologic Triangle: The Pathogen, The Host, and The Environment - Evidence Synthesis - Infectious Disease Modelling Presented by edX, this foundational-level course is ideal for learners interested in understanding the spread of infectious diseases. The course is available through Professional and Starter subscription options, making it accessible to a wide range of students and professionals eager to enhance their knowledge in epidemic science.

Gabriel M. Leung

Joseph Wu

Guan Yi

Malik Peiris

Marc Lipsitch

Tommy Lam

Kwok-Yung Yuen

Mark Jit

Maria Huachen Zhu

Benjamin Cowling

Thomas Abraham