Optimal control for infectious disease epidemics.
This repository contains implementations of optimal control problems for infectious disease epidemics, showcasing multiple epidemiological models and optimisation frameworks. It provides a comparison of different approaches to solving epidemiological optimisation problems.
Related preprint is now available:
“Exploring epidemic control policies using nonlinear programming and mathematical models”
Read it on arXiv
The following examples demonstrate the application of JuMP (Julia), in combination with the IPOPT solver, to assess control intervention strategies within a Susceptible-Infected-Recovered (SIR) model. These examples assess various strategic objectives, such as minimising total infections during an epidemic through lockdown measures, "flattening the curve", or vaccination efforts.
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SIR model with optimal lockdown timing and intensity This example is used to demostrate implementations across multiple optimisation frameworks:
We welcome contributions to this repository. Each example should be placed in its own directory, as a Quarto (.qmd) file. The header of the notebook should contain a list of output formats, for example:
---
title: Lockdown optimisation on an SIR model using JuMP.jl
date: 2025-03-10
author: Simon Frost (@sdwfrost) and Sandra Montes (@slmontes)
format:
html: default
docx: default
gfm: default
pdf: default
---To render Quarto files, install Quarto and run the following command in the example directory (where {FILENAME_OF_QMD} is the name of the Quarto file):
quarto render {FILENAME_OF_QMD}This project is licensed under the MIT License - see the LICENSE file for details.