Global Health 777: Infectious Disease Epidemiology in Global Settings – Surveillance, Prevention and Control
GLHLTH 777 is the first online elective offered by Duke Global Health Institute. We provide an in-depth focus on the epidemiology of communicable diseases in global settings. The course content encompasses the individual-level of diagnosis and treatment of an infectious case as well as the population level of disease surveillance, prevention and control. The course also examines the relationships between infectious diseases and environmental health, including veterinary health, and ends with an introduction to relatively understudied global communicable diseases and new approaches to epidemiologic studies.
This course is organized into three complementary modules, each led by a different instructor. The instructors bring a wealth of experience in the study and control of infectious diseases in sub-Saharan Africa and South Asia, as well as active research programs in these settings
- Foundations in Infectious Disease Epidemiology, (Wendy O’Meara)
- Disease Surveillance & Prevention, (Gayani Tillekeratne)
- Frontiers in Infectious Disease Epidemiology (Steve Taylor)
The goal is for students to become global health scientists and practitioners with practical knowledge of how health programs small and large can confront communicable diseases across different contexts.
The course is part of the inter-institutional education initiatives of the Duke Global Health Institute and welcomes participants from other institutions via the GH777 Global Scholars Initiative. In addition to Durham-based students, we have welcomed students participating from China, Kenya, Peru, Sri Lanka and Tanzania. The online format allows for international participation and brings a truly global perspective to our discussions.
You can view the syllabus here: GH777 Spring2019 Syllabus.
GLOBAL HEALTH 778: GLOBAL HEALTH PROGRAMMING, POLICY AND RESPONSE – APPROACHES TO AND USE OF INFECTIOUS DISEASE MODELS
GLHLTH 778 is the first class offered jointly between Duke University and our long-standing Kenyan academic partner, Moi University. Students have a flipped classroom experience coupled with synchronous discussion sections that include students from both campuses. Guest lecturers from around the world, including the U.S., Nigeria, South Africa and Kenya offer unique insights into the interface between modelers and policy makers.
The recent global pandemic has brought popular attention to the use of models to understand and predict infectious disease spread. The public is generally aware that models are being used to forecast cases and deaths, predict the impact of interventions, and guide policy making. But the details of these models, how they are developed, why they give differing results, and how they are used remains mysterious to most.
Mathematical models can be a powerful tool to predict future scenarios or understand dynamic processes, particularly when collecting data is impractical or impossible. In this course, we will give an overview of how scientists build mathematical models to understand and predict the spread of pathogens, beginning with some of the first models developed by P.D. En’ko to describe measles transmission and Ronald Ross to understand vector-borne transmission of malaria. We will also explore how models are interpreted and used by policy makers and public health programs.
