How Simulation Modelling Research can support global and local communities to tackle the pandemic

The onset of the COVID-19 pandemic has had a huge impact on our lives and society globally. The pandemic has generated many problems and questions, of a personal, local, national and international nature. Simulation research can play a crucial role in helping governments, businesses and communities to understand the impact of the pandemic and to plan for the months and years to come.
This time last year, we could not have predicted the impact that an infectious disease, such as COVID-19 could have had on our lives and society. COVID-19 looks set to be the worst infectious disease pandemic of a generation in terms of numbers infected and mortalities worldwide. To date (20 May 2020) according to WHO data more than 4.8m people globally have tested positive for the disease, out of which around 36% have recovered, while 7% have died. We have seen governments introduce extreme measures to manage the spread of the disease, such as social distancing and lockdown of the population.
The economic consequences from organisational shutdowns and other measures taken, such as school closures, have become real, with countries, including the UK, facing a severe recession. Furthermore, the pandemic has brought high health and wellbeing risks, for health care professionals and the wider population, due to the loss of informal support networks as a result of social distancing. Almost 0.5 million people in the UK are believed to have suffered from anxiety and other mental health issues during the pandemic. The question is, how can communities spring back out from the dire outlook ahead of us?
While we cannot predict with 100% certainty what the future holds and if there will be a future pandemic, simulation modelling expertise can help governments, communities and organisations to understand the impact of the pandemic and plan to reduce its impact.
Simulation is generally considered a niche area of modelling expertise, which is often taught in top business schools, including here at Loughborough. Its impact and potential have now become evident. Here in the UK alone, each one of us has heard at least once the word “computer simulation model” mentioned in the media. Computer simulations provide a virtual representation of real-world systems as they progress over time. These models are used to test the outcome of different scenarios instead of experimenting with the real population. This is a key benefit of using simulation. Developing the models helps us to gain a better understanding of the system as a whole and to make better decisions.
For example, governments appear to have relied heavily on epidemiological computer simulations to determine the spread of COVID-19 and to decide on social distancing measures. The key aim has been to flatten the growth curve of the disease and to reduce the pressure on the healthcare systems. However, the pandemic raises many more economic and societal challenges that computer simulations could be equally useful in addressing.
A recent paper published in the Journal of Simulation (Currie et al 2020) identifies a set of problems raised by the COVID-19 pandemic, particularly suited to simulation modelling. These problems require crucial decisions that need to be made as the epidemic progresses and diminishes. The paper splits these into three types:
- Decisions affecting disease transmission and interventions.
- Decisions regarding the management of organisational resources.
- Decisions about population care.
For each key decision, we describe the problem, how it might be modelled and any specific data requirements. The aim of this being to provide modellers and decision makers with some initial ideas where simulation modelling can be useful in addressing problems that have arisen during this pandemic and likely to arise in any future pandemic. For example, a computer simulation model can answer questions about how health care services can resume, how health and mental health services, in hospital and the community can be configured, how much medical staff and PPE are needed in a specific region given its demographics.
Aside from identifying problems the article also proposes a research agenda for the simulation modelling community. For example, as many services move to remote working, the article proposes that the simulation community should extend collaborative modelling practices in the virtual environment and build facilitation skills of future modellers to engage effectively with policy makers. Our research in the Simulation Practice Research Interest group here at Loughborough has focused on building simulations collaboratively with stakeholders to elicit information and to gain a better understanding of the possible options available. For example, collaborative simulations were developed to evaluate the design and development of Lightbulb, a community-based housing support service in the Leicestershire area, by involving the staff and patients (service users) in stakeholder workshops. This has led to developing a more effective service, benefiting not only the health and social care services and the frail and elderly people in Leicestershire as well as more widely the local economy.
With simulation models often applied to organisational problems in a variety of industries, collaborative simulation can offer a fertile environment for engagement with local and global businesses in the COVID-19 environment. Therefore, the role of simulation research could be crucial in developing the global modelling and simulation capacity needed to support mitigation efforts as well as to address the vast number of challenges during the response and recovery phases of a pandemic.
This blog post was written by Dr Antuela Anthi Tako, Reader in Operational Research and leader of the Simulation Practice Research Interest Group (SP-RIG). She can be contacted on A.Takou@lboro.ac.uk or via Twitter: @AntuelaTako
Read the full article: Christine S.M. Currie, John W. Fowler, Kathy Kotiadis, Thomas Monks, Bhakti Stephan Onggo, Duncan A. Robertson & Antuela A. Tako (2020) How simulation modelling can help reduce the impact of COVID-19, Journal of Simulation, DOI: 10.1080/17477778.2020.1751570