Background: Infant botulism is a rare disease that occurs when Clostridium botulinum spores colonise an infant’s intestine and produce botulinum toxin. Most cases are likely sporadic due to environmental exposure to dust or soil; cases have also been linked to honey, peanut butter and infant formula.
Methods: We analysed infant botulism notifiable disease data for South Australia (SA), 2005-2024. We summarised exposure data, treatment and time to laboratory diagnosis. Laboratory classification of toxin and sequence type (ST) was conducted using whole-genome sequencing.
Outcomes: Eight cases were reported, all from 2018 onwards. Median case age was 24 weeks (range 2-31 weeks), including five females and three males. Five cases were admitted to intensive care with no deaths. All cases were laboratory confirmed from faecal samples; the median time to confirmation was 17 days (range 6-22 days). Four cases were interviewed by public health before confirmation. Three cases were treated with BabyBIG (immune globulin), three not treated, and no details available for two. Seven cases were toxin type A2, residing in metropolitan areas. One case was toxin type B, from regional SA. No high-risk foods were consumed by cases; all were breastfed, three exclusively. Two consumed infant formula but was not considered a source. Three had exposures to construction or agricultural activities. Four cases were subtyped as A2-ST85, and one each of A2-ST84 and A2-ST156, with one not further typed; the toxin type B case was ST177.
Conclusions: Consistent, sporadic cases of infant botulism have been reported in SA since 2018, with no high-risk food sources. SA’s dry climate is a potential environmental source, where A2 toxin type is commonly linked to environmental exposure. Public health surveillance and clinical case treatment should not wait for laboratory confirmation. Further characterisation of toxin type allows for identification of regional trends.

Background and Aim: Surveillance data are fundamental to public health: they facilitate risk understanding and management, inform the targeting and business cases for public health action, and enable evaluation of the impact of public health programs over time. In an ever-changing health data environment, it is a continual challenge to develop systems to collect, store, and convert these data into meaningful public health intelligence. In time- and resource-constrained agencies, epidemiologists may be fully engaged with immediate priorities and reporting requirements limiting capacity to address long-term priorities. Important strategic objectives may sit outside any one program area, leaving gaps in cross-cutting intelligence and governments less able to take advantage of opportunities and prepare for future challenges.

Methods and Analysis: The Long Term Surveillance and Intelligence team (LTSI) was created in 2024 to reserve a core of epidemiology and public health capability within the office of the Chief Health Officer. LTSI comprises epidemiologists with diverse specialisations and skills, driving improvement projects that maximise long-term benefits across the surveillance system and providing strategic intelligence and advice on long-term issues that cut across program areas. The team provides both strategic and practical support to projects that support the evolution and future needs of surveillance systems.

Outcomes: LTSI has built partnerships across the department and beyond to deliver surveillance enhancements like the innovative new respiratory disease report, managed cross-cutting priorities like the department’s engagement with the newly formed Australian Centre for Disease Control and provided intelligence to support key long-term goals for a robust digital public health infrastructure. LTSI has been able to provide epidemiology support during emergencies while protecting capacity for long-term strategic goals.

Conclusion and Future actions: A strategic epidemiology team can enhance public health surveillance by promoting development of surveillance capabilities and providing future-focused intelligence, essential project support and responsive insights.

Background and Aim
Grampians Public Health Unit (GPHU) detected a higher-than-expected rate of Vancomycin Resistant Enterococcus faecuim (VanA VRE) MLST 1424 through routine surveillance. Notifications were associated with a regional Victorian hospital, prompting an outbreak response from the Infection Prevention and Control (IPC) team and GPHU.
Genomics and earlier in-hospital negative test data indicate clonal nosocomial acquisition. Patient movement data has informed ‘hot spots’ of potential hospital transmission for data-informed interventions, yet the outbreak has been ongoing for over 12 months. To our knowledge, this is the largest antimicrobial resistant nosocomial hospital outbreak in Australia, with 83 cases. A more comprehensive epidemiological investigation was required into possible causes of transmission to inform additional IPC outbreak control measures.

Methods and Analysis
Cases over a recent three-month period (n= 23) were randomly matched with two controls each from patients within the same hospital and time-period screened for VanA VRE with a negative test result. Health Information System data on invasive procedures and bed-level environmental risk factors were collected and crude odds ratios were calculated using logistic regression.

Outcomes
A number of environmental risk factors for VanA VRE test positivity were identified in the 90 days prior to test date including: sharing a bathroom (OR: 13.81 [95%CI: 3.90–60.05], p-value: <0.001), staying in a room with a basin within 150cm of the patient’s head (OR: 13.20 [95%CI: 2.02–261.17], p-value: 0.022), staying in a room with carpet (OR: 8.25 [95%CI: 2.28–35.58], p-value: 0.002), and staying in a room with a carpeted hallway (OR: 8.89 [95%CI: 2.67–34.27], p-value: 0.001).

Conclusion and Future Actions
This investigation has prompted carpet removal for vinyl flooring and informed IPC measures for sink cleaning. This study highlights the role of environmental factors into the transmission of VanA VRE. This informs hospital infrastructure to reduce associated nosocomial infection.

Climate-driven disasters are increasing in frequency, severity, and complexity, placing unprecedented pressure on public health systems worldwide. Floods, bushfires, cyclones, population displacement, infrastructure failures and major weather disruptions all create conditions that significantly elevate the risk of communicable disease outbreaks. While immunisation, surveillance, and clinical response remain critical components of disaster health management, the role of environmental health (EH) as the frontline of prevention remains substantially under-recognised. This paper positions environmental health as a core component of disaster-ready public health, demonstrating its essential role in preventing post-disaster infectious disease escalation.

Environmental health practitioners are embedded in local communities and are often there before, during and after a disaster working to rebuild communities, offer on the ground advice and engaging with state and federal colleagues, local communities and leaders to help provide clear consistent communication in order to reduce the risk of communicable disease outbreaks.

Drawing on evidence and case examples from Australia, UK, the Pacific, Africa and North America, this paper illustrates the mechanisms through which disasters disrupt food safety, drinking water protection, sanitation and wastewater systems, vector control programs, shelter safety, waste management, and indoor air quality. These failures disproportionately affect already marginalised communities—remote populations, informal settlements, displaced groups, older adults, vulnerable groups and Indigenous communities—who face heightened exposure to gastroenteritis, skin infections, respiratory illness, leptospirosis, vaccine-preventable disease clusters, and vector-borne outbreaks.

Using a systems perspective, we present a framework for Disaster-Ready Public Health, with evidence of good practice from around the world, identifying the environmental health capacities required to prevent escalation: rapid EH deployment teams, real-time water and air quality monitoring, strengthened vector surveillance, safe and culturally appropriate evacuation centres, emergency food safety protocols, and coordinated risk communication strategies. The framework highlights the importance of integrating EH into emergency operations centres, immunisation efforts, health intelligence systems, and climate-informed hazard mapping.

The paper argues that investing in accredited environmental health capability offers one of the most cost-effective strategies for preventing communicable diseases in disaster contexts. Effective EH involvement not only reduces the burden on hospitals and emergency departments but also enhances equity by protecting populations at greatest risk. The analysis emphasises opportunities to leverage technology—including low-cost sensors, digital inspections, mobile GIS tools, and community reporting platforms—to strengthen surveillance and early warning.

Recommendations include the development of national EH disaster competencies, expanded workforce surge capacity, incorporation of EH indicators in public health emergency plans, and multi-sector partnerships with emergency services, local governments, Indigenous organisations, and humanitarian actors.

As disasters intensify under climate change, environmental health must be recognised not as a supplementary function, but as critical public health prevention infrastructure. Strengthening EH capability represents a collective responsibility and a strategic investment in protecting communities from infectious disease threats before they emerge.

Background and Aim: The Australia–Aotearoa Consortium for Epidemic Forecasting and Analytics launched the region’s first-ever Scenario Modelling Hub in 2025. Scenario modelling explores how an epidemic might unfold under different circumstances or assumptions, often over several months or years. This is useful for estimating the benefit of different decisions about interventions — for example, exploring vaccine impact. Best practice for using scenario modelling to inform policy is to elicit predictions from multiple modelling teams. Teams independently produce the same set of projections to allow comparison and synthesis of outputs across models. Multi-model efforts are valuable because they capture variation and uncertainty and help identify how outcomes might depend on potential interventions and critical uncertainties, supporting better decisions.

Methods and Analysis: In the ACEFA 2025-26 Pilot Scenario Modelling Exercise, two research groups (from UNSW Sydney and the University of Melbourne) each undertook an independent analysis to address the question “What are the potential health impacts of a school-based live attenuated influenza vaccine (LAIV) programme in Australia and New Zealand?”. Modelling teams quantified benefits in terms of averted infections, cases, and hospitalisations for a range of LAIV programmes targeting preschool, primary, and secondary school aged children, and results were synthesised across groups.

Outcomes: In all LAIV scenarios, we estimated that cases and hospitalisations were prevented across all age groups (not only in those receiving LAIV), indicating indirect effects. The more substantial indirect effects were modelled in school-based programs. The Hub, and success of the first exercise, provides a platform for future multi-model analyses.

Conclusion and Future actions: The Hub is well-positioned to address future infectious disease and immunisation questions, and to rapidly respond to emerging disease threats. We will present our findings in terms of the (1) estimated health benefits of an LAIV programme and (2) challenges and opportunities for multi-model scenario analysis.

Background and Aim
Botulism is a paralytic syndrome caused by Clostridium botulinum neurotoxin. Botulism occurs rarely in Australia, but in 2025 there was an increase in notifications by clinicians in New South Wales. We aimed to identify exposure risks associated with botulism and assess the implications for future public health surveillance and response.

Methods and Analysis
The Australian botulism case definition requires both laboratory and clinical criteria of botulism to be met. We extracted confirmed and excluded botulism cases from the NSW public health surveillance system from 1999 to 2025. Excluded cases were reanalysed to classify cases that met clinical and epidemiological criteria of botulism, but were excluded due to a lack of laboratory evidence, as clinical botulism cases. We described confirmed and clinical botulism cases by year of diagnosis and botulism type based on the likely mode of transmission and described the key features of the public health investigations.

Outcomes
Twelve confirmed and eight clinical botulism cases were identified in the study period. The confirmed botulism cases included ten infant and one wound botulism case and one case with unknown botulism type. The eight clinical botulism cases included one foodborne and seven iatrogenic botulism cases. All iatrogenic botulism cases were diagnosed from June 2024 and were associated with cosmetic botulinum toxin administration by people not registered as health practitioners.

Conclusion and Future Actions
Botulism public health protocols in Australia are primarily focused on detecting and responding to potential foodborne botulism. Laboratory evidence is difficult to obtain for some botulism types, and the botulism case definition should be reviewed to capture botulism cases without laboratory evidence to ensure that surveillance data more accurately reflects botulism infections. Iatrogenic botulism is an increasing public health threat in Australia and protocols need to be updated to monitor and respond to the emerging risk.

Background and Aim
The COVID‑19 pandemic highlighted critical technology limitations in existing communicable disease surveillance systems across Australia, particularly their inability to rapidly adjust to changing data requirements and outbreak dynamics. To address this gap, Sentinel, a new open‑source, “epidemiologist‑first” surveillance platform was developed, designed to give public health professionals full control over the configuration of their data systems without complete reliance on software developers.

Methods
Sentinel was built as a modular, metadata‑driven web application that enables users with minimal technical expertise to define custom variables, configure outbreak modules, automate workflows, manage case and contact tracing, and generate advanced analytics.
The system was iteratively tested using simulated outbreak scenarios such as evolving case definitions, unknown pathogens, and shifting investigation or political requirements. System outcomes were assessed as whether public health tasks could be completed without code changes.

Results
Sentinel allows users to introduce new data elements, modify workflows, and adapt to non‑linear outbreak patterns without developer input.
The platform supports incomplete data, massive‑volume interviewing, and contact tracing. Granular disease and role‑based permissions to enable multidisciplinary use within public health units.

Conclusion
Sentinel represents a newly developed prototype and practical model for modern communicable disease informatics. By returning system control to public health professionals, it enhances operational agility during both routine surveillance and complex outbreak responses, including emerging or hypothetical Disease X scenarios.
This work demonstrates the feasibility and value of an epidemiologist‑first digital infrastructure for strengthening Australia’s communicable disease intelligence capability.