About this Course: Infectious Disease Epidemiology

This intermediate-level course explores the fundamental scientific principles underlying epidemics and the essential public health strategies for their prevention and control. With a specific focus on infectious diseases, it uses a supplementary module on COVID-19 as a current case study to elaborate on concepts like superspreading and global disease containment strategies.

What Students Will Learn

• Understanding the timeline of disease transmission through Epidemiologic curves.
• Evolutionary aspects of pathogens like Myxoma Virus, HIV, and Antimicrobial Resistance.
• Impact of age, social behavior (sexual mixing patterns) on disease spread and severity.
• Complexities of disease modeling including dynamic and structural uncertainties.

Course Prerequisites

No prerequisites are required. This course is designed to be accessible to students with a general understanding of scientific concepts.

Course Coverage

• Basic concepts in Infectious Disease Epidemiology.
• The Epidemiologic Triangle: Pathogen, Host, and Environment.
• Techniques for evidence synthesis and infectious disease modelling.
• Detailed study of disease transmission dynamics and control measures.

Who Should Take this Course?

This course is intended for students, public health professionals, and anyone interested in understanding the complexities and control strategies of infectious diseases. It is especially relevant given the current global concerns around pandemics and healthcare preparedness.

Application of Skills in the Real World

Skills acquired from this course can be applied in various public health roles, including epidemic investigation, disease modeling, and implementation of control strategies during outbreaks. These capabilities are crucial for contributing to global health security and responding effectively to infectious disease threats.

Syllabus

• Key principles and terms.
• Understanding the epidemic curve and incubation period.
• Estimating disease transmissibility and severity.

• Detailed analysis of the pathogen, host, and environmental factors.
• Case studies on pathogen evolution.
• Supplementary material on influenza immunity.

• Models and frameworks for predicting disease spread.
• Addressing the uncertainties in disease modeling.
• Supplementary module on precision public health.