There has been significant modelling of infection and transmission rates of COVID-19 in Australia. What about the potential for the pandemic to impact unevenly across the Australian population?
Using our Defin’d model of the Australian population, comprising profiles of households and individuals which when aggregated replicate the actual known multi-dimensional characteristics of individuals in each local community, the Finity analytics team in collaboration with the School of Risk and Actuarial Studies at UNSW have developed the COVID-19 Susceptibility Index.
The index provides a risk score for local communities, ranking the risk of severe illness if individuals in these communities were to contract the virus, based on the profile of significant co-morbidities (age, cancer, diabetes, cardiovascular disease, obesity and lung disease). This information can assist ongoing attempts to model the pandemic’s development as well as inform decisions regarding preventative measures.
Read more about how the index was developed and the interesting insights we found in our article published in Actuaries Digital.
How can this help?
This research could be used by policymakers to target specific geographic areas and demographic segments for highest impact. For example, when a vaccine becomes available, the index could be used to identify which population segments should be prioritised. Another use case could be informing decisions around testing for COVID-19 in populations who are more likely to go on to develop severe reactions to the disease should they become infected.
Conversely, identifying segments of the population who face lower risk if infected would be useful in making decisions about selectively lifting lockdown or social distancing measures. This could allow for a more tailored approach in balancing efforts to reinvigorate the economy while keeping the population safe.
Read the article in full via the Actuaries Institute.