Learn practical uses of mathematical modeling for infectious diseases and public health decision-making
Learn practical uses of mathematical modeling for infectious diseases and public health decision-making
Master the practical applications of mathematical modeling in infectious disease epidemiology. This course covers the basic principles of infectious disease models, their adaptation to specific diseases, and key assumptions. Learn to evaluate control strategies, quantify transmission rates, and forecast disease burden. Explore data-model interactions, uncertainty in results, and comparative analysis of modeling approaches. Ideal for those with a background in epidemiology and university-level mathematics.
Instructors:
English
What you'll learn
Understand the basic principles and practical applications of infectious disease modeling
Evaluate potential control strategies using mathematical models
Quantify and compare transmission rates of infectious diseases
Apply models to forecast future disease burden
Interpret model results and handle uncertainty in predictions
Compare different modeling and analytic approaches for infectious diseases
Skills you'll gain
This course includes:
3 Hours PreRecorded video
11 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 modules in this course
This comprehensive course provides an in-depth overview of the practical applications of mathematical modeling in infectious disease epidemiology and public health decision-making. The curriculum covers the fundamental principles of infectious disease models, their adaptation to specific diseases and scenarios, and important assumptions underlying different modeling approaches. Students will learn how data informs models, how models can be used to interpret data, and how to handle uncertainty in model results. The course focuses on three key use cases for models: evaluating potential control strategies, quantifying and comparing transmission rates of infections, and forecasting future disease burden. Through a combination of video lectures, readings, and assignments, learners will gain practical skills in applying mathematical models to real-world infectious disease challenges.
The Basics of Building Infectious Disease Transmission Models
Module 1 · 1 Hours to complete
Inferring Infectious Disease Transmission Rates from Outbreak Data
Module 2 · 1 Hours to complete
Prediction of Infectious Disease: Forecasting and Scenario Projection
Module 3 · 1 Hours to complete
Fee Structure
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Instructors
Expert in Computational Epidemiology and Infectious Disease Transmission
Dr. Amy Wesolowski is an Assistant Professor in Epidemiology at the Johns Hopkins Bloomberg School of Public Health. Her research leverages computational methods to explore transmission patterns of infectious diseases, with a particular focus on vaccine-preventable and vector-borne diseases. Before joining Johns Hopkins, she completed postdoctoral fellowships at Princeton University and the Harvard T.H. Chan School of Public Health. Dr. Wesolowski earned her Ph.D. in Engineering and Public Policy from Carnegie Mellon University.
Professor of the Practice
Dr. Gurley has been involved in public health research in Bangladesh since 2003, spending 12 years at the icddr,b (International Center for Diarrheal Diseases Research, Bangladesh), where she led the Surveillance and Outbreak Investigation Unit and served as Director of the Program on Emerging Infections. She collaborated with the US CDC and the Government of Bangladesh to establish national surveillance systems for diseases like meningo-encephalitis, respiratory infections, acute gastroenteritis, acute hepatitis, and hospital-acquired infections, with an emphasis on developing junior scientists. Dr. Gurley leads multi-disciplinary studies on the transmission, burden, and epidemiology of emerging and vaccine-preventable diseases, considering the ecological context in which these diseases occur. Her work focuses on enhancing collaboration between field epidemiologists and infectious disease modelers, as well as developing novel surveillance and outbreak detection strategies. Since 2004, she has been studying the ecology and epidemiology of Nipah virus, including transmission pathways and drivers of person-to-person spread, and designing interventions to prevent human infection. She serves on the WHO's Nipah Virus Taskforce, advising on the research and development of medical countermeasures. Dr. Gurley's research adopts a One Health approach to understanding and preventing infectious diseases. She is also the Co-Director for the Child Health and Mortality Prevention Surveillance (CHAMPS) site in Bangladesh, which focuses on determining the causes of and preventing child deaths, and works closely with the US CDC's Global Disease Detection program.
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