The most disadvantaged local government areas in greater Sydney have had almost twice as many Covid cases as the rest of the city during the current outbreak, according to a Guardian Australia analysis.
Experts say a multitude of cultural, environmental and economic factors could explain these differences. The impact of the pandemic is similar to health outcomes in general, with more disadvantaged areas suffering higher rates of mortality from all causes.
These areas not only contain large numbers of essential workers, an analysis of census data also shows a large number of workers in jobs that involve a lot of contact with other people, such as nursing, retail and childcare.
This outbreak’s hotspot LGAs – mainly in south-west Sydney – have also had the most cases throughout the entire pandemic.
The Australian Bureau of Statistics’ Index of Relative Socio-economic Advantage and Disadvantage (Irsad) was used to classify local government areas into four groups, or quartiles. Irsad summarises a range of information about the economic and social conditions including income, education, and employment.
Using these groupings allows us to see that while the initial outbreak occurred in more affluent areas, this was quickly brought under control. The outbreak then spread to less affluent LGAs – where more risky socioeconomic factors come into play, and transmission has continued.
A similar phenomenon was also present in Victoria’s second wave last year – the most disadvantaged areas saw both more cases and longer outbreaks.
Ben Harris-Roxas, a public health researcher at the University of NSW, says there are a variety of factors that might explain why less advantaged areas are being harder hit. What experts call the “social determinants of health” include work, but also lifestyle and environmental factors, such as how our cities are organised.
“A higher proportion of the population in south western Sydney works in care and healthcare, transport and manufacturing than other parts of Sydney. These generally aren’t casualised or insecure jobs, which is the common narrative. However they’re jobs that expose people to Covid.”
Analysis of census data shows many workers in affected areas are classified as essential workers – over 80,000 in Bankstown alone. So they would still have been allowed to move around under the more limited stay at home orders.
“People in western and south-western Sydney have to travel for work. A much lower share of Sydney’s jobs are within a 45 minute drive from the south-west than other parts of Sydney,” Harris-Roxas says.
“So this means that we have a mobile population that is actually travelling all over Sydney regularly, compared with the inner city, the eastern suburbs or the lower north shore.
The hardest hit areas in Sydney’s south-west on a per 100k basis are also regions where fewer people can work from home.
The socioeconomic trends in Covid cases mirror health outcomes in general. Data from New South Wales health shows that people in wealthier areas in the state live longer. People from poorer areas have greater all-cause mortality.
Just as there are complex socio-cultural factors underpinning the differences in outbreaks, Harris-Roxas says bringing the outbreak under control should take these complexities into account.
“My own experiences living in western Sydney for the past 20 years is that stigma and trust shape our perception of government and the media. Every story is about ethnic gangs or crime. Every government response is a crackdown. Covid has been no different.
“Policing and enforcement is not the way [to get the outbreak under control], particularly in western Sydney. You’re dealing with populations who have histories of trauma and poor treatment by governments, both in Australia and overseas. Now is the time to support existing community networks, and to keep building on the great work that NSW Health, and in particular south western Sydney and western Sydney local health districts, have been doing. We don’t need harsher lockdowns or a greater police presence.”
Notes and methods:
Data on case numbers and mortality sourced from NSW Health.
Socioeconomic indexes, employment figures, transport and estimated resident population data all sourced from the Australian Bureau of Statistics.
LGAs were grouped into quantiles based on their Irsad scores.
New cases were divided by the estimated resident population of LGAs and then multiplied by 100k before being aggregated by their Irsad quantile.