Mathematical Modelling of Vaccine Preventable Diseases with R Training Course

Mathematical Modelling of Vaccine Preventable Diseases with R Training Course

Overview of the Course

This training course is designed to equip participants with the essential skills to develop and apply mathematical models for vaccine-preventable diseases using R. Participants will learn how to construct, analyze, and interpret models to inform vaccination strategies and public health policies.

The course covers topics such as disease transmission dynamics, model building, parameter estimation, sensitivity analysis, and scenario analysis using R. Participants will gain hands-on experience through practical sessions integrated into each module.

Who Should Attend the Training

  • Public health professionals

  • Epidemiologists

  • Researchers

  • Data analysts

  • Healthcare professionals

Objectives of the Training

  • Understand the fundamentals of mathematical modeling for vaccine-preventable diseases

  • Learn how to use R for model development and analysis

  • Develop skills in parameter estimation and sensitivity analysis

  • Apply models to inform vaccination strategies
    Interpret and communicate model results effectively

Personal Benefits

  • Enhance your modeling and data analysis skills

  • Gain practical experience with R for modeling

  • Improve your ability to make data-driven decisions

  • Expand your career opportunities

  • Network with professionals in the field

Organizational Benefits

  • Improved modeling capabilities within the organization

  • Better-informed decision-making for vaccination strategies

  • Enhanced reporting and communication of model insights

  • Increased efficiency in managing and interpreting disease data

  • Strengthened public health response

Training Methodology

  • Interactive lectures

  • Hands-on practical sessions

  • Case studies and real-world examples

  • Group discussions and collaborative learning

  • Continuous assessment and feedback

Course Duration

5 days

Training Fee

  • KES 167,960

  • USD 1,300

Course Outline

Module 1: Introduction to Mathematical Modelling

  • Overview of mathematical modeling in epidemiology
  • Importance of modeling vaccine-preventable diseases
  • Basic principles of model construction
  • Introduction to R for modeling
  • Practical session: Setting up R for modeling

Module 2: Disease Transmission Dynamics

  • Concepts of disease transmission
  • Reproductive number (R0) and its significance
  • Compartmental models (SIR, SEIR)
  • Model assumptions and limitations
  • Practical session: Constructing SIR models in R

Module 3: Parameter Estimation and Calibration

  • Methods of parameter estimation
  • Data sources for parameter estimation
  • Calibration techniques for model fitting
  • Sensitivity analysis
  • Practical session: Parameter estimation and calibration in R

Module 4: Scenario Analysis and Simulation

  • Designing and running simulations
  • Exploring different vaccination strategies
  • Analyzing model outcomes
  • Communicating simulation results
  • Practical session: Conducting scenario analysis in R

Module 5: Advanced Modeling Techniques

  • Incorporating age-structured models
  • Stochastic modeling approaches
  • Modeling herd immunity
  • Evaluating model performance
  • Practical session: Advanced modeling techniques in R

Module 6: Case Studies in Vaccine Preventable Diseases

  • Reviewing real-world case studies
  • Applying modeling techniques to case studies
  • Group discussions and collaborative analysis
  • Presenting findings and recommendations
  • Practical session: Case study analysis

Module 7: Model Validation and Uncertainty Analysis

  • Validating model predictions
  • Assessing model robustness
  • Uncertainty analysis techniques
  • Communicating uncertainty to stakeholders
  • Practical session: Model validation and uncertainty analysis

Module 8: Data Visualization and Reporting

  • Principles of effective data visualization
  • Creating visualizations for model results
  • Customizing plots and visualizations in R
  • Reporting and communicating model insights
  • Practical session: Visualizing model results in R

Module 9: Policy Implications of Modeling

  • Linking models to public health policy
  • Evaluating the impact of vaccination programs
  • Communicating model results to policymakers
  • Ethical considerations in modeling
  • Practical session: Policy analysis and recommendations

Module 10: Future Directions in Disease Modeling

  • Emerging trends in mathematical modeling
  • Advances in computational modeling
  • Integrating new data sources
  • Future challenges and opportunities
  • Practical session: Exploring future directions in R

Trainer Experience

Our trainers are seasoned professionals with extensive experience in epidemiology, mathematical modeling, and the use of R. They bring a wealth of practical knowledge and real-world insights to the training.

Quality Statement

We are committed to providing high-quality training that meets the needs of our participants. Our courses are designed to be interactive, engaging, and relevant to real-world challenges.

Tailor-Made Courses

We offer tailor-made courses to suit the specific needs of organizations. Please contact us to discuss your requirements and we will design a course that meets your needs.

Payment Information

Payment is required a week before the training starts.

Accommodation and Airport Pick-Up

We provide accommodation and airport pick-up services for participants. Please contact us for more details.

Instructor-led Training Schedule

Course Dates Venue Fees Enroll

Self-Paced Online Course

Platform Price Access Duration Enroll
Online LMS $1,300 30 Days
Armstrong Global Institute

Armstrong Global Institute
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