Mathematical Modelling and Analysis of Infectious Disease using R
Predicting and Preventing Disease Outbreaks with R: A Hands-on Workshop
Skills you will gain:
About Program:
A model serves as a simplified depiction of a more intricate system or process. Infectious disease models can aid in outbreak responses by offering insights into the spread of diseases within populations, estimating the magnitude of outbreaks, and assessing the potential effects of interventions. Mathematical models can forecast the progression of infectious diseases to illustrate the probable outcomes of an epidemic and assist in shaping public health measures and interventions. In recent years, mathematical modelling has emerged as a crucial Instrument in analysing the dynamics of infectious diseases and supporting the creation of control strategies.
R is a robust tool for modelling infectious diseases mathematically due to its flexible and opensource programming environment. It offers a broad array of statistical and numerical analysis functionalities, enabling researchers to construct intricate models, simulate disease behaviours, and evaluate the effects of various interventions, all within an intuitive interface.
Aim: The aim is to explore mathematical modelling and assessment of infectious diseases utilizing R.
Program Objectives:
- To forecast the transmission of illness, determine interventions, and guide public health.
- To aid in making choices regarding the limitation of disease transmission and the implementation of vaccination strategies.
What you will learn?
Day 1: Infectious disease model and terminology
- Basics of Infectious disease model, Deterministic infectious disease model
- Susceptible, Infected, Recovered, Force of infection, Basic Reproductive Ratio, Frequency dependent transmission, Density dependent transmission
Day 2: R studio and packages, Framework for mathematical model
- R and packages installation, Loading Library
- Basic Compartment Model, Understanding the model, Model complexities, Addition of interventions, Visualization of the model
Day 3: SusceptibleInfected-Recovered (SIR) Model
- SIR Model, Plotting and SIR Model
- SIR model with population Demographics, Variations on the SIR model
Mentor Profile
Fee Plan
Get an e-Certificate of Participation!
Intended For :
- Undergraduate/Postgraduate students in Epidemiology, Biostatistics, Public Health, or related fields.
- Researchers and faculty in disease modelling and public health.
- Data analysts and professionals in healthcare and epidemiology.
- Individuals with a background in R programming and an interest in infectious disease modelling.
Career Supporting Skills
Program Outcomes
- Understanding of infectious disease modelling concepts
- Ability to implement and analyze epidemiological models in R
- Hands-on experience with deterministic models and simulations
- Knowledge of disease intervention strategies and public health impact
- Proficiency in data visualization and interpretation for decision-making