Co-designing a public health data analytics platform

Pandemics such as COVID-19 reveal unique challenges to public health systems worldwide, particularly the need for real-time insights into the risk of infectious disease spread to guide public health prevention and containment efforts¹. During the COVID-19 pandemic, Australia reported the second lowest prevalence of SARS-CoV-2 infections per 100,000 people and the third lowest number of confirmed or suspected COVID-19 deaths per million population, relative to the 37 other countries of the Organisation for Economic Co-operation and Development². Although many factors contributed to this success, evidence-based decision-making and nationwide collaboration through the use of predictive modeling were key. This allowed policymakers to evaluate population risk and compare potential public health outcomes associated with various disease-control strategies³.

Other specific factors also had a part in ensuring Australia’s overall success. For example, the ability to maintain public confidence through timely sharing of information with the public was crucial in South Australia. To maintain this level of trust and degree of social license, relationships with local media were strengthened, and a substantial effort was made to ensure clarity of messaging. In addition, health officials built strong relationships with community groups, particularly with priority populations (such as culturally and linguistically diverse populations) through face-to-face meetings, where appropriate, and regular webinars.