Using Bayesian statistics and mathematical models to assess the global response to COVID-19:
In the first six months of the COVID-19 pandemic a range of different responses were observed across the world. But comparing these strategies across diverse countries with the outcomes in terms of reported cases and deaths represents a real challenge. Not only are interventions diverse, the changes of behaviour in populations around the world has also varied.
To solve this problem, ACEMS researchers developed a mathematical model that describes the interaction of the virus with a population that changes their tendency to mix as the reports of cases increases. By including these mechanisms, the sensitivity and timing of the communities response could be estimated and compared against the size of the outbreaks across the globe.
This analysis of 158 countries confirms that a multi-pronged strategy coupled with a rapid response is essential for avoiding large outbreaks of COVID-19. Furthermore, communities should continue to be vigilant to avoid new hotspots and flare-ups until sufficient uptake of an effective vaccine is achieved.
- Link to publication: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-09972-z
Other researchers in the project include:
- Prof Wenbiao Hu, QUT
- Prof Antonietta Mira, University of Lugano
- Dr Anthony Ebert, University of Lugano