COVID-19 modelling and risk analysis

Research program: 
Currently recruiting: 
The challenge: 

Risk analysis and predictive modelling can assist with policy and practice in epidemic control of COVID-19. UNSW Biodefense is a collaboration between the Kirby Institute’s Biosecurity Program, and School of Public Health and Community Medicine (SPHCM), both at UNSW Sydney. We have developed a transmission model for COVID-19 that can be used to answer a range of urgent policy questions.

The project: 

The first study examined the impact of the travel ban Australia implemented on China. We looked at scenarios of partial and complete lifting of the ban, related to the incidence of disease in China and the travel patterns. We have since done work on regional disease control, school closures, and social distancing strategies with colleagues at Arizona State University within the PLuS Alliance, and on universal face mask use.

The method: 

A SEIR (Susceptible - Exposed - Infectious - Recovered) model for COVID-19 transmission was developed by the Kirby Institute’s Biosecurity Program to undertake the modelling and risk analyses mentioned above.

The results: 

Our published study on travel bans showed the travel ban was highly effective for containing the COVID-19 epidemic in Australia during the epidemic peak in China and averted a much larger epidemic while COVID-19 was largely localised to China. This research demonstrates the effectiveness of travel bans applied to countries with high disease incidence and can inform decisions on placing or lifting travel bans during the COVID-19 epidemic. A study done with Arizona State University shows that physical distancing and mask use are effective in controlling COVID-19.

Other studies are currently underway.

The impact: 

We will be able to provide rapid decision support for key policy questions around control of COVID-19.

Project contact: 
Head, Biosecurity Program, and Professor of Global Biosecurity, Kirby Institute and NHMRC Principal Research Fellow
Project collaborators: 
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