COVID-19 Recovery: Modelling Transmission

Ulster University are collaborating on a project to develop mathematical models that better understand the transmission dynamics of Covid-19.

The School of Engineering, Computing and a range of other research groups from across the University are collaborating on a project to develop mathematical models that better understand the transmission dynamics of Covid-19.

The team are working closely with Dr Rob Brisk, ECME-Ulster based researcher and cardiologist at the Southern Health and Social Care Trust. Dr Brisk is also part of the Governments Specialist Modelling Response Expert Group in Northern Ireland.

The main purpose of the project is to validate and inform the Modelling Response Team’s work as well as help governing bodies in Northern Ireland to better plan for intervention measures and ultimately flatten the curve.

Our modelling activities can be broken into three key areas

  1. Model the initial trajectories of COVID-19 in Northern Ireland and establish the initial basic reproduction number of COVID-19 (the R number). By establishing this number, we can indicate how rapidly the virus is spreading within our society.
  2. Integrate the various intervention measures into our models and understand the effect of such control action on the ‘R number’ with a goal of reducing this and bringing the virus under better control.
  3. Model the various options for exit and recovery strategies, to help the relevant governing bodies in planning when to initiate or lift control interventions.

You can find out more about Sensitivity analysis of the infection transmissibility in the UK during the COVID-19 pandemic and the Development of a robust mathematical model and simulation package.

This work will help in fighting the virus here in Northern Ireland and protect our vital health services.

Understanding the effects of time-dependent restrictions and control to flatten the curve

Dr Mark Ng also leads a team of researchers from Ulster University and Queen’s University Belfast to assist scientists around the globe in modelling activities.

Examples of such collaborative activities are as follows:

  • Working together with researchers from the School of Engineering and Digital Sciences, Nazarbayev University, Kazakhstan, to model the transmission dynamics of COVID-19 when little coverage or analysis existed. The study focused on the analysis of the control action taken by the authorities in Kazakhstan. View the study results.
  • Working with Dr Tudor Codreanu, the Incident Controller for the State Health Incident Control Centre and Deputy Chief Health Officer of the Department of Health in Western Australia, to model the outbreak of COVID-19 on commercial cargo vessels.

Related staff

Dr Raymond Bond

Reader in Data Analytics

School of Computing

Areas of expertise Digital health, biomedical and healthcare informatics, human-computer interaction, data modelling.


Professor James McLaughlin

Head of School of Engineering

School of Engineering

Areas of expertise Nanotechnology, point of care diagnostics, integrated algorithm based solutions, sensor & IOT technology, Digital Healthcare Technology, Innovation.


Dr Min Jing

Research Fellow in Artificial Intelligence, ECME

School of Engineering


Professor Dewar Finlay

Associate Dean (Research & Impact)

Dean's Office (Comp, Eng & Be)



Dr Mark Ng

Lecturer in Mechatronics Engineering and Control

School of Engineering