Background: More than seventy per cent of salmonellosis in Australia is thought to be due to contaminated food. Rates of salmonellosis vary across the Australian states and territories, with the highest rates in the Northern Territory. In 2020, to control coronavirus disease 2019 (COVID-19), Australia implemented public health measures including border closures, physical distancing and hygiene advice. This study analyses salmonellosis notification rates in 2020 and considers possible impacts of COVID-19 measures. Methods: Monthly and annual salmonellosis notifications per 100,000 population, for each of Australia's eight states and territories for the years 2015 to 2020, were extracted from Australia's publicly accessible National Notifiable Diseases Surveillance System. For each jurisdiction, the salmonellosis rate each month in 2020 was compared with the previous 5-year median rate for that calendar month. The possible impacts of COVID-19 public health measures on salmonellosis notifications in the respective states and territories were examined. Results: The annual Australian salmonellosis notification rate was 27% lower in 2020 than the previous 5-year median. The reduction in salmonellosis rate varied throughout Australia. States and territories with more stringent, more frequent or longer COVID-19 public health measures had generally greater salmonellosis rate reductions. However, Tasmania had a 50% deeper reduction in salmonellosis rate than did the Northern Territory, despite similar restriction levels. Conclusions: Salmonellosis notifications decreased in Australia during the global COVID-19 pandemic. The reduction in notifications corresponded with the implementation of public health measures. Persistence of high rates in the Northern Territory could indicate the overarching importance of demographic and environmental factors.
CITATION STYLE
Davis, B. P., Amin, J., Franklin, N., & Beggs, P. J. (2022). Salmonellosis in Australia in 2020: possible impacts of COVID-19 related public health measures. Communicable Diseases Intelligence (2018), 46. https://doi.org/10.33321/cdi.2022.46.2
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