Charles Sturt University, Media Release, 24 November 2021
Recent research by a team at Charles Sturt University aims to help develop a robust research framework for regional New South Wales (NSW) to help improve the control strategy for COVID-19 at the regional level in NSW. It can also assist other infectious disease epidemics.
Associate Professor in Mathematics and Statistics and the Leader of Data Mining Research Group Azizur Rahman (pictured, inset) in the Charles Sturt School of Computing, Mathematics and Engineering led his colleagues Dr Md Abdul Kuddus, Dr Ryan Ip, and Dr Michael Bewong in the research.
They recently published their findings, ‘A review of COVID-19 modelling strategies in three countries to develop a research framework for regional areas’, in the journal Viruses (October 2021, 13, 2185).
Professor Rahman said COVID-19 has had more attention from governments and media than any previous infectious disease, including influenza, and modelling studies can contribute to developing new control methods, improving computational tools, and public data sharing.
“In this review we discussed some important COVID-19 models and attempted to classify them by their structures, including some core assumptions,” he said.
“In addition, we summarise the model outcomes and distinctive features, including the impact of different intervention strategies and their cost, stability, and sensitivity analysis to identify the most impelling risk factors addressing model biases.
“In doing so, we have identified some open challenges and encouraging prospects for upcoming COVID-19 modelling-related research.”
Professor Rahman said when an outbreak of COVID-19 occurred in Wuhan city, China, at the end of December 2019, modelling played a crucial role in developing a strategy to prevent the disease outbreak from spreading around the globe.
His team’s research consisted of a literature review to summarise knowledge about COVID-19 disease modelling in three countries ─ China, the UK and Australia ─ to develop a robust research framework for the regional areas that are urban and rural health districts of the state of NSW in Australia.
“For example, modelling studies strongly advised border closures, and China first imposed an internal travel lockdown on Wuhan, which delayed the epidemic peak of COVID-19 within China, but had a more significant impact on other countries,” Professor Rahman said.
“Statistical modelling has also projected the shifting of outbreaks from one country to another, based on these locations’ connectedness.”
Professor Rahman said models have contributed to the ready insight into epidemiological variations between and within nations, and the planning of desired control strategies.
“We found that in different aspects of modelling, summarising disease and intervention strategies can help policymakers control the outbreak of COVID-19 and may motivate modelling disease-related research at a finer level of regional geospatial scales in the future.
“Therefore, future research in modelling will include models with a combination of control strategies, which we believe may help decision-makers improve the control strategy for COVID-19 epidemics at the regional level in NSW.”
This research was made possible by a Charles Sturt University COVID-19 Research Grant. Professor Rahman is also a member of the Charles Sturt Institute for Land, Water and Society (ILWS).