Summary and Setup

On this page, you will find the instructions and code for the R exercises of the Introduction to Infectious Disease Modelling for Public Health Course.

The Introduction to Infectious Disease Modelling for Public Health course was developed by Pontificia Universidad Javeriana for African audiences, as part of the EpiTKit training strategy under the Epiverse Initiative. The course aims to strengthen knowledge and skills in infectious disease modelling and data analysis within the public health context.

BACKGROUND

Enhancing Tools for Response, Analytics and Control of Epidemics in Latin America and the Caribbean (TRACE-LAC) is a project funded by the International Development Research Centre (IDRC) with the objective of building a high-quality, open-source, and interoperable data toolkit for epidemic analytics — and fostering an engaged user community — to support decision-makers in responding to epidemics in Latin America.

The Pontificia Universidad Javeriana (Javeriana) has been supported by IDRC to develop various activities and research products within the TRACE-LAC project. As part of this effort, Javeriana created the Epi Training Kit (EpiTKit), an open-access online training strategy.

The EpiTKit consists of a series of modules and units for virtual training in public health data science and infectious disease modeling, aligned with the Epiverse initiative led by data.org. To date, 10 units have been developed in Spanish, tailored for audiences in Latin America and the Caribbean.

This new phase, developed through a partnership between Pontificia Universidad Javeriana and data.org, with the collaboration of the Medical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, expands the reach of the EpiTKit to Africa through a South-South collaboration. It emphasizes multilingualism and localism in the translation and cultural adaptation of training materials. The initiative aims to strengthen local capacities in data science for public health, while promoting knowledge exchange between regions facing similar gaps and epidemiological challenges.

GENERAL OBJECTIVE

To translate and culturally adapt the materials of the Epi Training Kit (EpiTKit) for the target audience in  Côte d'Ivoire, The Gambia, Ghana, Kenya, Nigeria, Rwanda, Senegal, Sierra Leone, Tanzania, and Togo, ensuring linguistic clarity, technical accuracy, and cultural relevance. This initiative embraces a multilingual and localism approach to create context-sensitive learning experiences that reflect local public health realities and strengthen regional capacities in data science for epidemic response.

This objective includes:

  • Translating and adapting the training materials from an initial set of five units developed by Epiverse TRACE-LAC into English and French, while integrating local contexts and region-specific examples.

  • Reviewing technical terminology to ensure consistency, accuracy, and relevance to local epidemiological landscapes.

  • Adapting and producing multilingual multimedia resources that are culturally appropriate and reflective of the diverse realities across African regions.

The five units to be translated and adapted are:

  1. Introduction to Epidemic Theory

  2. General Epidemiology

  3. Introduction to Statistics and Probability

  4. Parameters

  5. Building a Deterministic Model

INSTITUTIONS

Pontificia Universidad Javeriana data.org The Medical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine

For more information about the project, visit our page: Project page on GitHub

Course Rules

Learn about our TRACE-LAC Code of Conduct.

Software Configuration

Follow these two steps:

1. Install or Update R and RStudio

R and RStudio are two separate pieces of software:

  • R is a programming language and software used to execute code written in R.
  • RStudio is an integrated development environment (IDE) that makes working with R easier. We recommend using RStudio to interact with R.

To install R and RStudio, follow these instructions https://posit.co/download/rstudio-desktop/.

Already Installed?

Wait! This is a great time to ensure your R installation is up to date. This tutorial requires R versión 4.0.0 or later.

To check if your R version is up to date:

  • In RStudio, your R version will be displayed in the la ventana de la consola. Or you can run sessionInfo().

  • - To update R, download and install the latest version from the R proiect website for your operating system.

    • After installing a new version, you’ll need to reinstall all packages.

    • For Windows, the installr package can update R and migrate your package library.

  • To update RStudio, open RStudio and click Help > Check for Updates. If a new version is available, follow the on-screen instructions.

Check for Updates Regularly

While this might sound intimidating, it’s far more common to encounter issues due to outdated versions of R or R packages. Keeping up with the latest versions of R, RStudio, and any frequently used packages is a best practice.

Dataset

Remember to store them in the data folder within your project location