Integrated Surveillance of <em>Shigella</em> in Australia, 2017–2024: Epidemiological and Antimicrobial Resistance Trends — The Association Specialists
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Integrated Surveillance of Shigella in Australia, 2017–2024: Epidemiological and Antimicrobial Resistance Trends (23845)

Eliza Schioldann 1 2 3 , Aruna Phabmixay 2 , Christina Bareja 2 , Courtney Lane 3 , Davoud Pourmarzi 1
  1. NCEPH (National Center for Epidemiology and Population Health), Australian National University, Canberra, ACT, Australia
  2. Public Health Division, Australian Centre for Disease Control, Canberra, ACT, Australia
  3. WHO Collaborating Centre for Antimicrobial Resistance, University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia

Background

Antimicrobial resistance (AMR) poses a major challenge for the control of shigellosis in Australia, but fragmented surveillance data across multiple systems limit a comprehensive understanding of national trends. We aimed to provide a more complete picture of shigellosis epidemiology and AMR in Australia from 2017 to 2024.

Methods

We explored temporal, demographic, geographic, and AMR trends using data from the National Notifiable Diseases Surveillance System (NNDSS); susceptibility results from voluntarily contributing pathology services in Australian Passive AMR Surveillance (APAS); and multidrug-resistant Shigella reported to the National Alert System for Critical Antimicrobial Resistances (CARAlert). Analyses were conducted using R version 4.5.1.

Results

Between 2017 and 2024, 16,761 shigellosis notifications were reported to the NNDSS; 2,189 Shigella isolates to APAS, and 1,754 isolates to CARAlert.

NNDSS crude notification rates peaked at 12.4 cases per 100,000 in 2019, declined to a low of 1.8 per 100,000 during the COVID-19 pandemic, and increased again thereafter. The greatest burden across all three datasets was observed among males aged 30–39 years. Notification rates (NNDSS) and isolate counts (APAS) were highest in IRSAD decile 1 (relatively greatest socio-economic disadvantage) areas.

APAS data indicate non-susceptibility was highest in penicillins (75.7%, [1,652/2,183]) and lowest in third-generation cephalosporins (13.6%, [294/2,168]); no non-susceptibility was observed for meropenem. The odds of non-susceptibility in third-generation cephalosporins increased significantly each year (OR 1.45, 95% CI 1.37–1.53).

Among isolates with a reported ceftriaxone result in CARAlert, 62.9% (999/1,589) were resistant; 96.3% of these carried extended-spectrum β-lactamase (ESBL) genes, 3.6% AmpC β-lactamases, and one isolate carried neither.

Conclusion

Distinct demographic and socio-economic patterns of shigellosis burden in Australia were observed, along with increasing resistance to key antimicrobials and predominance of ESBL genes among ceftriaxone-resistant isolates. This highlights the need for integrated shigellosis surveillance including AMR data to inform clinical management and antimicrobial stewardship.