• A Charles Sturt University research project will assess the effectiveness of federal and state governments’ COVID-19 pandemic interventions in Australia on reducing the number of infected cases
• The research will develop a new statistical model that takes into account the spatial and temporal components within the data
• The findings will assist policy makers in making informed decisions to manage the risk to communities in the future

Since the start of the COVID-19 pandemic in Australia, how effective are the various federal and state government policy measures including lockdown, social distancing, and travel bans?

A Charles Sturt University research project, mentored by Associate Professor Azizur Rahman (pictured), leader of the Statistics and Data Mining Research Group and led by Dr Ryan Ip from the Charles Sturt School of Computing and Mathematics, aims to find out.

Professor Rahman said the research team will assess the impacts of the intervention measures by developing a novel statistical model that could accommodate complicated spatial and temporal components within the data.

Professor Rahman said, “Although the main targets of the policy measures are to reduce the number of infection cases, they do come with socio-economic consequences.

“It is therefore important to be aware of the effectiveness of these policy measures, so that informed decisions can be made to manage the risk to communities in the future.”

The project, ‘Developing an intervention model to assess effectiveness of policy measures on COVID-19 outbreak in Australia’ will extend Intervention Time Series Analysis (ITSA) models, which have proven useful in assessing the effectiveness of policies in various contexts.

Governments’ responses will be evaluated and compared at the state and local government levels, where possible, based on the resulting model.

Professor Rahman explained this project was underpinned by his recent research:

− Effect of preventive actions and health care factors in controlling the outbreaks of COVID-19 pandemic – which used different statistical methods to examine the links between the control measures and the country-wise infection and death indices across the world.

− Modelling the transmission dynamics of COVID-19 in six high burden countries − which aimed to predict the transmission rates in six high-burden countries; Australia, Spain, Canada, Italy, USA, and the UK.

The Charles Sturt School of Computing and Mathematics research project team comprises Dr Ryan Ip (Lecturer in statistics), Dr Dmitry Demskoy (Senior Lecturer in mathematics), Associate Professor Azizur Rahman (Associate Professor in Statistics and Data Science), and Associate Professor Lihong Zheng (Associate Professor in Computer Science).