Programme Parameters
Graduate / Intermediate
4 Weeks (40 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This 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. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
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.
📋 Course Objectives
1. Put bioinformatics techniques to work on real datasets and case studies.
2. Produce a reproducible, portfolio-ready project you can cite in a thesis, paper, or job application.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in bioinformatics
• R&D engineers and working professionals applying bioinformatics in industry
• Academics and educators building research or teaching capacity in bioinformatics
🚀 Key Learning Outcomes
• A portfolio-grade bioinformatics deliverable you can defend and extend.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
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
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
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
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
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
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
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
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
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Disease Transmission Modeling |
| Covered Tool / Platform | Epidemiology Modeling in R |
| Covered Tool / Platform | Infectious Disease Control Strategies |
| Covered Tool / Platform | Mathematical Epidemiology Training |
| Covered Tool / Platform | Online Infectious Disease Workshop |
| Covered Tool / Platform | SIR Model |
| Covered Tool / Platform | Epidemic Forecasting |
| Covered Tool / Platform | Health Data Visualization |
| Covered Tool / Platform | Public Health Analytics |
Frequently Asked Questions
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