Sydney researchers develop NSW COVID-19 hotspot database
In collaboration with NSW Health, a multidisciplinary team of researchers at the University of Sydney has developed a searchable聽 that shows the location of COVID-19 cases in the state.
Led by Associate Professor Adam Kamradt-Scott from the School of Social and Political Sciences, together with Associate Professor Eleanor Bruce from the Faculty of Science 聽and Associate Professor Adam Dunn from the Faculty of Medicine and Health, the database is aimed at helping the government identify populations who might be at greater risk in the event of more widespread community transmission.
鈥淭his database is unique in that it combines NSW Health data with ABS data on, for example, the age and the socio-economic status of people within different postcodes鈥�, Associate Professor Kamradt-Scott, a former and current government adviser on pandemic strategy said. 鈥淲e hope it can inform state policy responses to COVID-19, including appropriate allocation of resources.鈥�
Understanding geographical differences in socio-economic disadvantage is important for supporting vulnerable communities
鈥淯nderstanding geographical differences in socio-economic disadvantage is important for supporting vulnerable communities,鈥� Associate Professor Bruce added.聽
The database, which is updated daily, also has the potential to assist authorities to create more detailed maps to support the allocation of resources in advance.
鈥淢y hope is that we will be able to look at how testing was deployed across the state to learn lessons about how we might next time use more targeted behaviour interventions to avoid much of the social, economic, and mental health harms caused by blanket policies that disproportionately burden vulnerable and marginalised communities,鈥� Dr Dunn said.
Potential to aid quarantine relaxation measures
The date of the last recorded case in each postcode will also be viewable. This can assist the government in making decisions around potentially relaxing social distancing and other COVID-19 containment measures in discrete, safe areas.
鈥淭here will be a minimum of 28 days of no or small transmission that will have to have elapsed before an area is possibly cleared for relaxation. The hope is that this process will enable the state to begin to get back to normal,鈥� Associate Professor Kamradt-Scott said.
Balancing data transparency with privacy
Dr Dunn explained why data transparency 鈥� a feature of the database 鈥� is critical in crisis communications: 鈥淢aking it easier for the public to see the number of cases in the places where they live and work will help to reduce anxiety in the community as we begin to return to normal and reopen businesses, schools, and borders.鈥�
鈥淗andling this data with care and respecting the privacy of people who have tested positive for COVID-19 is also our priority.鈥�