R for Mathematical Modelling and Analysis of Infectious Disease
Predicting and Preventing Disease Outbreaks with R: A Hands-on Workshop
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MODE: Virtual (Google Meet)
TYPE: Mentor-Based Training
LEVEL: Moderate
DURATION: 3 Days (1.5 hours per day)
Start Date: March 24, 2025
Time: 10:00 AM IST
About the Workshop
Mathematical models play a critical role in analyzing and predicting infectious disease outbreaks. These models provide insights into how diseases spread, estimate the impact of an outbreak, and evaluate the effectiveness of intervention strategies. Infectious disease modeling assists public health authorities in decision-making, ensuring timely and effective control measures.
R programming is widely recognized for its powerful statistical and computational capabilities in modeling infectious diseases. It allows researchers to build complex models, simulate disease spread, and analyze intervention impacts with a user-friendly and flexible open-source environment. This workshop is designed to introduce mathematical modeling techniques using R, helping participants develop skills in disease modeling, data analysis, and visualization.
Workshop Objectives
- Forecast disease transmission trends and evaluate intervention strategies.
- Analyze epidemiological data to guide public health decisions.
- Implement mathematical models to study infectious disease dynamics.
- Understand vaccination strategies and measures to limit disease spread.
- Enhance proficiency in R programming for epidemiological modeling.
Workshop Structure
Day 1: Infectious Disease Modeling and Key Concepts
- Introduction to infectious disease modeling
- Deterministic models: Susceptible, Infected, Recovered (SIR)
- Basic reproduction number (R0) and force of infection
- Frequency-dependent and density-dependent transmission
Day 2: Introduction to R for Mathematical Modeling
- Setting up R and installing required packages
- Loading libraries and understanding R basics
- Compartment models and adding complexities
- Simulation of disease transmission using R
Day 3: SIR Model and Advanced Analysis
- Implementing the SIR model in R
- Plotting and visualizing disease progression
- Expanding models with population dynamics
- Evaluating intervention strategies and public health impact
Who Should Attend?
This workshop is ideal for:
- Undergraduate and postgraduate students in Epidemiology, Biostatistics, and Public Health
- Researchers and faculty working in disease modeling and public health analysis
- Data analysts and professionals in healthcare and epidemiology
- Individuals with basic R programming knowledge interested in infectious disease modeling
Important Dates
Registration Deadline: March 24, 2025 (09:00 AM IST)
Workshop Dates: March 24 – March 26, 2025
Session Timing: 10:00 AM IST Onwards
Workshop Outcomes
- Comprehensive understanding of infectious disease modeling concepts.
- Hands-on experience with deterministic models and epidemiological simulations.
- Ability to implement and analyze disease models in R.
- Knowledge of vaccination strategies and intervention planning.
- Proficiency in visualizing epidemiological data for decision-making.
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