| Attribute | Detail |
|---|---|
| Format | Online (e-LMS) |
| Level | Advanced |
| Duration | 3 Weeks |
| Certification | e-Certification + e-Marksheet |
| Fee | ₹5499 / $59 |
| Tools | Disease Transmission Modeling Epidemiology Modeling in R Infectious Disease Control Strategies Mathematical Epidemiology Training Online Infectious Disease Workshop SIR Model Epidemic Forecasting Health Data Visualization Public Health Analytics |
About the R for Mathematical Modelling and Analysis of Infectious Disease Course
The R for Mathematical Modelling and Analysis of Infectious Disease course is an intermediate-level program designed to provide learners with a structured understanding of how mathematical models are used to study, analyze, and manage infectious disease spread. The course focuses on the use of R-based epidemiology modeling to understand disease transmission patterns, outbreak dynamics, intervention planning, and public health decision-making.
This program introduces learners to the foundations of infectious disease modeling, including transmission parameters, population compartments, epidemic curves, reproduction numbers, forecasting concepts, and scenario-based analysis. Learners will explore how mathematical epidemiology supports disease surveillance, outbreak response, vaccination strategy planning, and evaluation of control measures.
Special emphasis is placed on Disease Transmission Modeling, Epidemiology Modeling in R, Infectious Disease Control Strategies, Mathematical Epidemiology Training, and Online Infectious Disease Workshop, helping learners build practical understanding of infectious disease analysis and response planning.
Program Highlights
• Mentorship by industry experts and NSTC faculty
• Structured learning in mathematical epidemiology and infectious disease modeling
• Hands-on conceptual exposure to epidemiology modeling in R
• Case studies on outbreak analysis, disease spread, and public health interventions
• Practical understanding of disease transmission modeling and control strategy evaluation
• Focus on modeling assumptions, interpretation, forecasting, and decision support
• e-Certification + e-Marksheet upon successful completion
Course Curriculum
Module 1: Introduction to Infectious Disease Modeling
- Overview of Infectious Disease Modeling and Its Importance
- Role of Mathematical Models in Public Health Decision-Making
- Understanding Epidemics, Outbreaks, and Disease Spread
- Applications of Modeling in Surveillance, Forecasting, and Control Planning
Module 2: Foundations of Mathematical Epidemiology Training
- Core Concepts in Mathematical Epidemiology Training
- Host, Pathogen, Transmission, Susceptibility, and Recovery Concepts
- Understanding Population-Level Disease Dynamics
- Key Assumptions and Limitations in Epidemiological Models
Module 3: Disease Transmission Modeling
- Principles of Disease Transmission Modeling
- Transmission Routes, Contact Patterns, and Infection Risk
- Understanding Incidence, Prevalence, and Epidemic Curves
- Interpreting Transmission Dynamics in Different Population Settings
Module 4: Epidemiology Modeling in R
- Introduction to Epidemiology Modeling in R
- Structuring Infectious Disease Data for Analysis
- Building Basic Model Workflows and Interpreting Outputs
- Using R-Based Approaches for Visualization and Scenario Analysis
Module 5: Compartmental Models for Infectious Diseases
- Introduction to Compartmental Modeling Concepts
- Susceptible, Infected, Recovered, and Exposed Population Groups
- Modeling Disease Progression Across Population Compartments
- Applications of Compartmental Models in Outbreak Analysis
Module 6: Reproduction Numbers and Epidemic Forecasting
- Understanding Basic and Effective Reproduction Numbers
- Estimating Disease Spread Potential and Outbreak Growth
- Forecasting Trends Under Different Transmission Conditions
- Using Model Outputs to Support Public Health Planning
Module 7: Infectious Disease Control Strategies
- Introduction to Infectious Disease Control Strategies
- Modeling Vaccination, Isolation, Quarantine, Screening, and Treatment Effects
- Evaluating Intervention Timing, Coverage, and Effectiveness
- Comparing Control Scenarios for Better Decision-Making
Module 8: Online Infectious Disease Workshop and Case Applications
- Online Infectious Disease Workshop for Applied Learning
- Case Studies in Respiratory, Vector-Borne, and Emerging Infectious Diseases
- Interpreting Model Results for Reports and Policy Communication
- Final Applied Exercise on Infectious Disease Modeling and Control Planning
Tools, Techniques, or Platforms Covered
Disease Transmission Modeling Epidemiology Modeling in R Infectious Disease Control Strategies Mathematical Epidemiology Training Online Infectious Disease Workshop SIR Model Epidemic Forecasting Health Data Visualization Public Health Analytics
Real-World Applications
- Modeling infectious disease spread during outbreaks and epidemics
- Using epidemiology modeling in R to analyze disease trends and transmission patterns
- Evaluating infectious disease control strategies such as vaccination, isolation, and treatment planning
- Supporting public health decision-making through mathematical epidemiology training
- Forecasting outbreak scenarios under different transmission and intervention assumptions
- Communicating model findings for research reports, health programs, and policy planning
- Applying disease transmission modeling to respiratory, vector-borne, and emerging infections
Who Should Attend & Prerequisites
- Designed for students, researchers, public health learners, epidemiology professionals, healthcare researchers, data analysis learners, and industry participants interested in infectious disease modeling, epidemiology, and public health analytics.
- Suitable for learners from public health, epidemiology, biotechnology, biomedical science, statistics, data science, life sciences, healthcare, medical research, and related fields.
Certification
