Mathematical Modelling of Infectious Diseases in Epidemiology with R

FineResults Research Services would like to invite you to take part in our upcoming workshops on  Research Courses at our FineResults Research Services training facilities in Nairobi, Kenya or online.

10/02/2025-21/02/2025 Mathematical Modelling of Infectious Diseases in Epidemiology Using R

12/05/2025-23/05/2025 Mathematical Modelling of Infectious Diseases in Epidemiology Using R

11/08/2025-22/08/2025 Mathematical Modelling of Infectious Diseases in Epidemiology Using R

10/11/2025-21/11/2025 Mathematical Modelling of Infectious Diseases in Epidemiology Using R

INTRODUCTION

Infectious diseases are disorders caused by organisms such as bacteria, viruses, fungi, protozoa, helminths, prions or parasites and they include SARS-CoV-2, Zika, Ebola, HIV/AIDS, swine flu, MERS CoV, ringworm, trichinosis, influenza, rabies, measles, rubella, tuberculosis and malaria among others. With the increased emergence and re-emergence of these diseases, there has been equally increased use of mathematical modelling to support relevant infectious diseases stakeholders (public health, pharmaceutical industry professionals, policy makers, infectious diseases researchers) in understanding the transmission and control of these diseases. This is possible when professionals are capable of interpreting and effectively evaluating both epidemiological data and the findings of mathematical modelling studies. This 10 days course will equip participants with knowledge on infectious diseases and hands on skills on use of R studio software in mathematical modelling of infectious diseases.

Duration

10 days

Who should attend?

Public health, medical, pharmaceutical industry professionals, policy makers, veterinary scientists, medical statisticians and infectious disease researchers and anybody who is looking forward to analysing and interpreting epidemiological data on infectious diseases and predicting the potential impact of infectious diseases control programmes.

What you will learn

By the end of the training participants will be able to:

· Understand fundamental statistical concepts

· Analyze data by applying appropriate statistical techniques

· Write a simple mathematical model that is appropriate for a specific infectious disease and related research question

· Learn R Programming

· Analyse the dynamics of the model

· Use the model to consider varying cost and intervention scenarios

· Construct valid mathematical models capturing the natural history of a given infectious disease.

· Use a calibrated model to create model projections for different intervention scenarios

· Implement a mathematical model in R, calibrating it against epidemiological data in order to estimate key model parameters

· Explain the strengths and limitations of a mathematical model in relation to given research and policy questions

 

Course outline

Module 1: R Programming

• Introduction to the R Statistical Software & R Studio
• Different Data Structures in R
• Reading in Data from Different Sources
• Indexing and Subletting of Data
• Data Cleaning: managing missing values, recoding to string variables to numeric variables
• Exploratory Data Analysis in R

 

Module 2: Understanding type of data and type of data analysis

• Descriptive Statistics
• Inferential statistics
• Test statistics- Test for normality

Module 3: Test statistics

• Test for independence for parametric data (one sample t test, independent sample t test, paired sample t-test, one way analysis of variance, repeated measure anova)
• Test for independence of non-parametric data (Wilcoxon signed rank, Wilcoxon signed rank, Man whitney, Friedman test and Kruskal Wallis test
• Test for independence of dichotomous data- MCNemar test, Chi-square test/ Fischers’ exact test, Cochran’s Q test

 

Module 4: Test of associations

• Tests of associations- Chis-square test of association, Pearson correlation, Speraman correlation
• Regression analysis
• Data reduction methods

Module 5: Developing infectious disease models

• Introduction to the major concepts used for studying the epidemiology of infectious diseases:
• Basic reproduction number
• Incubation periods
• Serial intervals, herd immunity
• Seasonal transmission

Module 6: Introduction to the main types of models that can be employed

• Application of model to determine optimal control strategies for outbreaks involving new pathogens as well as for endemic infection
• Learn methods for setting up deterministic models (difference and differential equations)

Module 7: Analysis of data and applications of modelling of seroprevalence data

• How to analyse and interpret seroprevalence data,
• different fitting methodologies.
• estimate (age-dependent) infection incidences (“forces of infection”) for high and low infection transmission settings
• Determine how seroprevalence data can be used to estimate mixing patterns of subgroups in given populations and how different contact patterns between individuals affect the impact of control.

Module 8: Additional methods and dynamics - stochastic and network modelling, health economics and sensitivity analyses

• Stochastic and network models,
• Health economics
• Sensitivity analyses

Module 9: Applications of modelling

• Applications of mathematical models
• The extent of transmission of diseases such as malaria

Module 10: Case study of data analysis and modelling of infectious disease of participants’ choice

• Interpretation of results and presentation of results using tables, charts and figures
• Discussion of findings from data analysis
• Review of articles (Past papers) that have used methods and critique them
• Exercise to plan and develop a model

 

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Training Customization

This training can also be customized for your institution upon request. You can also have it delivered your preferred location.

For further inquiries, please contact us through Mobile: (+254 759 285 295) or Email: [email protected] 

 

REQUIREMENTS

Participants should be reasonably proficient in English.  During the trainings, participants should come with their own laptops.

 

TRAINING FEE

Cost:

In-person USD 2000

Registration

February in-person

May in-person

August in-person

November in-person

Payment should be transferred to FineResults Research Services bank account one week prior to the training date and proof of payment sent to [email protected]

For any registration of 3 or more participants; we offer a discount of up to 10%.

This course fee covers the course tuition, training materials, two break refreshments, lunch, and study visits for in-person training.

Accommodation

Accommodation is arranged upon request. For reservations contact us through Mobile: (+254 759 285 295) or Email: [email protected] 

Payment

Payment should be transferred to FineResults Research Limited bank before commencement of training. Send proof of payment through the email: [email protected] 

Cancellation Policy

• All requests for cancellations must be received in writing.
• Changes will become effective on the date of written confirmation being received.