Much of the existing guidance on sampling strategy required to detect novel and emerging viruses using genomic surveillance (GS) was developed during the SARS-CoV-2 pandemic; a time when unprecedented levels of diagnostic testing and sequencing were well-resourced, which is no longer the case. As viral pathogens continue to pose a global public health threat, GS objectives have broadened beyond SARS-CoV-2 variants to include early detection of emerging and novel viruses likely to appear initially at low numbers within a given population. The aim of this study was to estimate sample sizes for varying turnaround times (TATs) required to develop an agile, practical framework to enable contemporary early warning GS systems to detect emerging viral pathogens.

We estimated the number of genomes required to detect (with 80% or 95% probability) one case infected with a variant, amongst all cases within a population. We considered the effects of variant growth rate (doubling time) and TATs (the time between sample collection and sequence generation) upon the time to variant detection and its circulating prevalence at the time of detection, via a simple logistic growth model. We applied these estimates to two likely epidemiological scenarios, i) detection of novel virus or ii) emerging variant of an established virus, and therein defined the appropriate scales and speed for GS.

We found that the amount of sequencing required to detect a rare, low prevalence variant is affected by the doubling time of the variant. However, long TATs (>28 days) reduce the chance of early variant detection from a reasonable sample size irrespective of doubling time. Reducing TATs therefore reduces the overall amount of sequencing required for early detection. The findings of this study highlight both TATs and variant doubling times as critical elements that must be considered when designing and resourcing effective early warning GS systems.

Emerging infectious diseases caused by novel or neglected pathogens, such as flaviviruses, pose a significant global health risk, exemplified by the Japanese encephalitis virus (JEV) outbreak in southern temperate Australia in early 2022. Strengthening pandemic preparedness and prevention requires integrated healthcare and surveillance frameworks, emphasizing a One Health approach. This approach employs a multipronged strategy to monitor human, animal, and environmental health. We assessed the utility of wastewater for environmental surveillance for early warning of JEV as a proof-of-concept for human disease outbreaks, using mosquito surveillance and human cases as benchmark controls.

We developed real-time PCR-based assays to detect JEV and Murray Valley encephalitis virus (MVEV) in wastewater using retrospective passive sampler (PS) membranes collected from riverine Victorian catchments between January and February 2022. The analytical performance of detection assays for MVEV-G2 and all five JEV genotypes was assessed through wastewater spiking experiments, using varying quantities of viruses and evaluating their respective recoveries with PS membranes. Our results indicate that the assays’ lower limit of detection (copies/mL) ranged between 2,550 for MVEV-G2, 780 for JEV-GI, 2,760 for JEV-GII, 3,034 for JEV-GIII, 472 for JEV-GIV and 1,170 for JEV-GV, with viral recoveries around 5-40%. A total of 88 remnant stored PS membranes and cotton bud “Q-tips” were selected by location to known human cases, mosquito detections and flavivirus seroprevalence. Among these samples, JEV was detected in 23 (26.1%) PS, while MVEV was detected in 2 (2.3%) PS.

Furthermore, wastewater testing overlaid with complementary surveillance data from the same period revealed evidence of JEV in wastewater and mosquitoes up to 41 days before human cases. Conversely, timelines of MVEV did not align between sample types.
Our findings highlight wastewater testing has a complementary role in One Health surveillance with a potential to serve as an early warning system for broader flavivirus infections.

Background:

Japanese Encephalitis (JE) is a major human health concern in the World Health Organisation South-East Asia and Western Pacific Regions. There have been 45 human cases and seven deaths in Australia since January 2021. However, there are few Australian studies examining awareness and behaviour about mosquito-borne disease prevention. This is needed to inform policies and programs. This study explores what motivates people in NSW and QLD to adopt mosquito borne-disease preventive behaviours including JE vaccination.

Methods:

Semi-structured qualitative interviews of 25 purposively samples adults living/working in NSW and QLD Local Government Areas of concern for Japanese Encephalitis Virus and potential future risk areas. Data were thematically analysed using NVivo, and BeSD framework to explore the drivers for mosquito-borne disease prevention.

Results:

Participants reported a spectrum of behaviour combinations for JE prevention including mosquito and bite prevention, and vaccination. Common mosquito prevention methods included repellents, screens, and coils. Most participants from metro areas were unaware of JE and its vaccine, viewing it as a regional issue. Regional participants felt at risk due to exposure to water reservoirs and animals, despite knowing little about JE or its vaccine. Some saw mosquitoes as a part of Australian life that was of little concern. Participants expressed willingness to get vaccinated if recommended by their GP, however many viewed it as a travel vaccine. GP, media and school campaigns were common sources of information. Those living in border communities relied on information from both NSW and QLD. Confusion about eligibility criteria and questions about mandates were common and usually connected with COVID experience.

Conclusions:

The spectrum of risk perception and behaviours suggest the need for tailored campaigns and interventions that account for the impact of prior COVID experience. These should be implemented through multi-sectoral coordination.

Whole Genome Sequencing (WGS) has been used for routine surveillance of notifiable pathogens in NSW since 2016 with results discussed directly with operational teams for public health action. As WGS has grown in application there is a need for results to be accessible in statewide public health systems. Operationally, WGS data differs from conventional diagnostic notifications as they are dynamic, results, particularly relationships can change as more data is analysed. Data management systems such as Laboratory Information Management Systems and the NSW Notifiable Conditions Information Management System (NCIMS) were designed to process the traditional, static, diagnostic reports so careful consideration is needed to integrate WGS results in these systems.

To facilitate the integration of WGS, a working group was established between the genomics laboratory at the Institute of Clinical Pathology and Medical Research-NSW Health Pathology, and Health Protection NSW to enable the integration of routine WGS results into NCIMS. The objective was to establish a system where WGS results are integrated and readily reportable with epidemiological data. The group identified key WGS data required, development of methods for data importation and limitations for future system enhancements. To ensure operability, training sessions on how to access and interpret the results were provided to the network.

From August 2024 WGS has been routinely imported into NCIMS with successful integration of key data fields. Limitations that arose fell into three themes: data capture and management; ability to interpret aggregate WGS data; and tools for the interpretation and reporting of data. Key system requirements identified were: repeatable data fields; systems to aggregate data; and automation of reports for WGS interpretation. Future systems should be developed with WGS results in mind to ensure optimal use of genomics for public health action, facilitating readily accessible data and knowledge between epidemiologists, clinicians, laboratory scientists and decision makers.

Background:
The COVID-19 pandemic caused significant social and economic disruption, showing no country was well prepared for a new respiratory pandemic. We argue there is value in integrated epidemiological, social and economic scenario modelling of plausible respiratory pandemic viruses (i.e. Disease X) before their occurrence. This study illustrates such an approach by evaluating public health and social measure (PHSM) strategies for Disease X scenarios in Victoria, Australia.

Methods:
We used an agent-based model with 6.6 million agents to estimate infection-related morbidity, mortality, and costs over 3 years, considering Victorian demographic and movement patterns. We examined 27 Disease X typologies with low/medium/high: incubation period, infection fatality risk, and proportion asymptomatic. These parameters have plausible probability distributions from which their values were drawn. We also modelled 3 stringency levels of PHSM strategies (i.e. elimination, suppression and mitigation). These strategies were ranked based on cumulative deaths, days exceeding hospital capacity, days in lockdown, and cost-effectiveness from health system and partial societal perspectives.

Preliminary Results:
Initial results suggest more stringent PHSMs reduced hospitalisations and deaths by about 25% but led to an average of 50 more days in lockdown. From a health system perspective, stricter PHSMs were cost saving and resulted in greater health gain. Fuller results will be presented at the conference.

Avian influenza viruses represent a significant threat to global public health and have contributed to the emergence of human influenza pandemics in the past. In 2024, a large outbreak of avian influenza occurred in poultry farms in Victoria, Australia, commencing with the detection of high pathogenicity avian influenza (HPAI) H7N3 at a poultry farm in the Golden Plains Shire on 22 May 2024. Over the following four weeks, HPAI (H7N3 and H7N9) was detected in poultry at an additional seven properties in the Golden Plains and Corangamite Shires. The overall control agency for outbreak response was Agriculture Victoria, with the Victorian Department of Health leading the human health response. Human case and contact definitions were established, with management of contacts (e.g., poultry workers and visitors to affected premises) dependent on their risk classification. Public health actions included influenza vaccination, antiviral prophylaxis, and active surveillance of high-risk contacts. Medical assessment and testing of suspected cases was facilitated through local health services and clinics. A total of 212 human contacts were identified, including 165 high-risk and 47 low-risk contacts, distributed across 25 Victorian local government areas based on postcode of residence. Twenty suspected cases were identified, all of whom tested negative for influenza A. There were no probable or confirmed human avian influenza cases. The recent HPAI outbreak in Victoria showcases the effectiveness of a coordinated One Health approach to disease management, and demonstrates the need for governments, agricultural industries and healthcare professionals to strengthen preparedness and response strategies for the global threat of HPAI H5N1.

There are many approaches to communicable disease surveillance implemented in Australia, including (but not limited to) case-based reporting, hospital-based surveillance, syndromic surveillance, and surveys of infection markers. However, for most communicable diseases we do not currently have a national process for deciding which of these resources to prioritise and how to bring them together to support the public health goals underpinned by surveillance activities. A standardised process would provide a basis for determining how to make the best use of existing data systems, and what additional systems require resourcing, to achieve public health goals.

The Communicable Diseases Network of Australia (CDNA) has recently tasked a working group of researchers and public health practitioners to initiate, and then develop through iterative consultation with CDNA, such a standardised process. Here we describe the project goals and work plan, show preliminary outputs (including its application to test case scenarios), and invite feedback from conference attendees.

Our goal is to produce standardised and easy-to-follow checklists, accompanied by guidelines, that can be used to generate national surveillance plans tailored to the specific public health needs of individual diseases. The guidelines will support public health teams to identify and prioritise surveillance objectives, indicators, data sources, and analysis needs for each disease or group of diseases. With such a national process in place, we will be able to more rapidly and effectively develop surveillance plans for communicable diseases, supporting decision making and engagement with stakeholders, including the public.