Infectious Disease Dynamics, Analytics, and Modeling Certificate Program
This certificate program will provide students from diverse academic backgrounds with the skills to use mathematical and statistical modeling techniques to quantify and predict the spread of infectious diseases.
OVERVIEW
Students in the Certificate in Infectious Disease Dynamics, Analytics, and Modeling will take coursework covering i) the foundational epidemiological principles of infectious diseases, ii) advanced mathematical, statistical, and computational techniques relevant to analyzing infectious disease data, and iii) a specialized course on applied infectious disease modeling. They will be able to calculate metrics describing disease transmission, create mechanistic models of disease transmission, clinical progression, and control, use statistical methods to estimate model parameters and forecast disease dynamics, critically evaluate disease models in the scientific literature, and communicate model results to diverse stakeholders.
EDUCATIONAL OBJECTIVES
Upon completion of the program, students will be able to:
- Describe the observed epidemiological patterns for important infectious diseases around the world and their biological, sociological, and environmental drivers;
- Understand the predominant methods of infectious disease control and the pathogens to which they apply;
- Be familiar with the metrics used to quantify disease transmissibility and the methods used to estimate;
- Translate biological, epidemiological, and medical features of an infectious disease into mechanistic mathematical models;
- Develop and apply statistical methods to estimate model parameters and predict disease spread or outcomes;
- Understand the different types of infectious disease models (e.g. mathematical vs statistical, stochastic vs deterministic, well-mixed vs network) and the different uses of models (e.g. inference vs forecasting vs scenario projection);
- Understand the common challenges of real-world infectious disease data and methods to deal with data limitations;
- Critically evaluate infectious disease models in the scientific literature;
- Communicate the results of models - including their critical assumptions and uncertainty - to both technical and non-technical audiences.
SPONSORING DEPARTMENT
ADMISSIONS
Contact information and complete certificate program admissions information are available on the certificate program page on the Bloomberg School of Public Health website.
Requirements for Successful Completion
Students must take all required and elective courses for a letter grade and maintain an overall GPA of 2.75 or higher in all certificate coursework.
Students must successfully complete the core courses, demonstrated by full attendance and participation in all course activities and assignments. The student should review the section of the website that addresses completion before completing the certificate program requirements. The student's transcript will not indicate that the certificate was earned until the Notification of Completion has been submitted, verified by the certificate program and processed by the Registrar.
COURSE OF STUDY
Students are required to successfully complete 24 term credits, which are grouped into several categories of expertise. In addition, students must attend at least 4 research seminars in the “Infectious disease dynamics research seminar” series.
| Code | Title | Credits |
|---|---|---|
| PH.550.860 | Academic & Research Ethics at BSPH | |
| Basic Epidemiological Methods: Students must select 1 of the following courses | ||
| PH.340.601 | Principles of Epidemiology | 5 |
| PH.340.751 | Epidemiologic Methods 1 | 5 |
| PH.340.721 | Epidemiologic Inference in Public Health I | 5 |
| PH.340.761 | Epidemiologic Methods for EPI Doctoral Students I | 5 |
| Infectious Disease Epidemiology: Students must take 1 of the following courses | ||
| PH.340.627 | Epidemiology of Infectious Diseases | 4 |
| PH.340.668 | Topics in Infectious Disease Epidemiology | 3 |
| Infectious Disease Modeling: Students must take 1 of the following courses | ||
| PH.340.677 | Infectious Disease Dynamics: Theoretical and Computational Approaches | 4 |
| EN.580.673 | Dynamic Modeling of Infectious Diseases in Patients and Populations | 2 |
| Specialized Topics in Data Analytics and Modeling: Students must take at least 2 half semester courses (6 term credits) from this list | ||
| PH.340.609 | Concepts and Methods in Infectious Disease Epidemiology | 4 |
| PH.140.628 | Data Science for Public Health in Python | 4 |
| PH.140.629 | AI for Public Health in Python | 4 |
| EN.553.636 | Introduction to Data Science | 3 |
| EN.601.675 | Machine Learning | 3 |
| EN.601.682 | Machine Learning: Deep Learning | 4 |
| EN.601.788 | Machine Learning for Healthcare | 3 |
| EN.553.740 | Machine Learning I | 3 |
| EN.553.741 | Machine Learning II | 3 |
| EN.560.617 | Deep Learning for Physical Systems | 3 |
| PH.140.644 | Statistical Machine Learning: Methods, Theory, and Applications | 4 |
| AS.171.749 | Machine Learning for Physicists | 3 |
| PH.221.660 | Systems Science in Public Health: Basic Modeling and Simulation Methods | 3 |
| PH.380.603 | Demographic Methods for Public Health | 4 |
| PH.380.755 | Population Dynamics and Public Health | 2 |
| EN.560.653 | An Introduction to Network Modeling | 4 |
| EN.553.692 | Mathematical Biology | 3 |
| EN.580.680 | Precision Care Medicine | 4 |
| EN.580.640 | Systems Pharmacology and Personalized Medicine | 4 |
| EN.553.650 | Computational Molecular Medicine | 4 |
| EN.540.633 | Pharmacokinetics and Pharmacodynamics | 3 |
| AS.020.674 | Quantitative Biology and Biophysics | 4 |
| EN.553.691 | Dynamical Systems | 4 |
| EN.560.657 | System Dynamics | 3 |
| EN.520.621 | Introduction To Nonlinear Systems | 3 |
| EN.553.736 | System Identification and Likelihood Methods | 2 |
| EN.553.633 | Monte Carlo Methods | 4 |
| EN.553.626 | Introduction to Stochastic Processes | 4 |
| EN.553.632 | Bayesian Statistics | 3 |
| PH.140.762 | Bayesian Methods I | 3 |
| PH.140.773 | Foundations of Statistical Inference I | 4 |
| PH.140.777 | Statistical Programming Paradigms and Workflows | 3 |
| PH.140.779 | Advanced Statistical Computing | 4 |
| Specialized Topics in Infectious Disease Epidemiology: Students must take at least 2 half semester courses (or at least 6 term credits) from this list | ||
| PH.260.623 | Fundamental Virology | 4 |
| PH.340.654 | Epidemiology and Natural History of Human Viral Infections | 6 |
| PH.340.646 | Epidemiology and Public Health Impact of HIV and AIDS | 4 |
| PH.340.641 | Healthcare Epidemiology | 4 |
| PH.340.612 | Epidemiologic Basis for Tuberculosis Control | 2 |
| PH.182.640 | Food- and Water- Borne Diseases | 3 |
| PH.260.656 | Malariology | 4 |
| PH.223.682 | Clinical and Epidemiologic Aspects of Tropical Diseases | 4 |
| PH.340.651 | Emerging Infections | 2 |
| PH.380.761 | Sexually Transmitted Infections in Public Health Practice | 4 |
| PH.260.650 | Vector Biology and Vector-Borne Diseases | 3 |
| PH.260.631 | Immunology, Infection and Disease | 3 |
| PH.223.680 | Global Disease Control Programs and Policies | 4 |
| PH.223.662 | Vaccine Development and Application | 4 |
| PH.180.623 | Infectious Disease Threats to Global Health Security | 3 |
| PH.260.636 | Evolution of Infectious Disease | 3 |
| PH.223.663 | Infectious Diseases and Child Survival | 3 |
| PH.340.744 | Advanced Topics on Control and Prevention of HIV/AIDS | 4 |
| PH.260.655 | Pandemics of the 20Th Century | 1 |
| PH.260.635 | Biology of Parasitism | 5 |
| PH.223.688 | Clinical, Epidemiologic, and Climate Change factors of Enteric Infections in the Tropics | 4 |
| PH.340.653 | Epidemiologic Inference in Outbreak Investigations | 3 |
| PH.340.693 | Investigation of Outbreaks | 2 |
| ME.300.716 | Pathology for Graduate Students: Immunology/Infectious Disease | 1 |
| ME.250.633 | Organ Systems Foundations of Medicine - Infectious Disease and Microbiology | 2 |
| ME.250.714 | HIV Biology | 1 |