High acceptability of a national platform for public health genomic data sharing and surveillance in Australia: a mixed methods evaluation study

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However, formal evaluation of pathogen genomic surveillance systems has been a major gap. Where evaluation has been undertaken, this has largely focused on economics, rather than assessing system attributes that contribute to the usefulness and acceptability of pathogen genomic surveillance systems. In Australia, the AusTrakka platform was established and deployed nationally to address barriers to genomic data sharing across jurisdictions, enhance interoperability and usability, and improve governance of public health genomic data. Here we present our evaluation of AusTrakka and examine how its utilisation and impact shifted throughout the COVID-19 pandemic. Methods We utilised the United States’ Centers for Disease Control (CDC) Updated Guidelines for Evaluating Public Health Surveillance Systems to guide assessment of the AusTrakka platform. The evaluation used a mixed-methods approach consisting of a quantitative analysis of AusTrakka utilisation data throughout the COVID-19 pandemic and a qualitative component comprised of key informant interviews and analysis of investigation reports produced by the AusTrakka National Analysis Team. Semi-structured individual and group interviews were held with key informants (n=63) representing all jurisdictions across Australia and New Zealand. These included individuals representing public health laboratories and health departments, infectious disease physicians, genomic epidemiologists and bioinformaticians. Results End users reported that AusTrakka had a very high degree of usefulness as a centralised platform to enable sharing sequence data across jurisdictions, facilitate multijurisdictional outbreak investigations and clarifying transmission chains. Acceptability was a key system that contributed to the usefulness of the platform, enhanced through collective design of data governance frameworks. Integration of epidemiological data with the pathogen genomic data was an ongoing challenge in data completeness. Conclusions Robust evaluation of pathogen genomics surveillance systems is critical to identify contextual and system elements that impact the capacity of these systems to accomplish their objectives. Our findings demonstrate the importance of strong stakeholder engagement in developing data governance mechanisms for pathogen genomics in ultimately ensuring the capacity of surveillance systems to detect outbreaks and support public health utility, and reinforce the value of a nationally developed, purpose-built approach in Australia. Pathogen genomics surveillance public health evaluation COVID-19 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Pathogen genomics is increasingly being integrated into public health surveillance and outbreak investigations around the world in the detection, prevention and control of infectious diseases (1). The US Food and Drug Administration established GenomeTrakr in 2012 as the first laboratory network to utilise whole genome sequencing (WGS) in tracing bacterial foodborne contamination and pathogen identification (2). Soon after, in 2014, Public Health England began using pathogen genomics in Salmonella surveillance (3) and by 2016, 26 European countries reported routine use of WGS in public health practice (4). In 2020, the COVID-19 pandemic brought into focus the necessity of national and international surveillance systems that are adequately equipped to understand and respond to emerging and previously unknown pathogens. Australia was also an early adopter of pathogen genomics for public health surveillance and response activities with national genomic surveillance of Listeriosis as an example (5). The Australian government released its first National Microbial Genomics Framework in 2019 (6), which highlighted the value of genomics in infectious diseases surveillance and promoted national consistency and mechanisms for data sharing. Systematic evaluation of pathogen genomic surveillance systems Rigorous and systematic evaluation of surveillance systems that integrate pathogen genomics is important for making explicit the expected contribution of pathogen genomics; understanding how well such surveillance systems are meeting their objectives; and clarifying the processes by which they do so, or areas requiring further strengthening. Evaluation contributes to the body of evidence available for the development of genomics-informed public health practice and supports identification of needed investment, infrastructure and training (7). Despite substantial investment into the integration of pathogen genomics in public health surveillance, evaluation of genomics-informed surveillance systems has been limited. Where evaluation has taken place, the focus has been on economic evaluation (8-10), rather than the surveillance system’s usefulness, or the attributes that contribute to the system attaining its objectives. This may be because there are limited systems globally that have been fully implemented. The US Centers for Disease Control (CDC) published the Updated Guidelines for Evaluating Public Health Surveillance Systems in 2001 to support integration of surveillance and health information and address changes in public health surveillance to respond to emerging health threats including new diseases (11). The updated guidelines aim to help organise the evaluation of a public health surveillance system for assessment of how well the system meets its purpose and objectives. These guidelines also underpin the elements of surveillance quality in WHO’s 2006 Communicable disease surveillance and response systems: Guide to monitoring and evaluating (12). In considering the usefulness of a public health surveillance system, the guidelines indicate that a useful system contributes to prevention and control of adverse health-related events, and an improved understanding of such events. The guidelines state that due to variability between surveillance systems, relevant attributes may differ between systems. The surveillance system and therefore the evaluation should place emphasis on those attributes that are most important to the objectives of the system (12). At the time of this evaluation, despite the strong and increasing investment in public health pathogen genomics and the integration of pathogen genomics into surveillance systems, a systematic evaluation of attributes contributing to the usefulness of such systems was not available. We therefore applied the CDC Updated Guidelines for Evaluating Public Health Surveillance Systems to evaluate the usefulness of the Australian national platform for public health pathogen genomics, AusTrakka (13). This represents an early opportunity to evaluate one of the first national platforms for data integration in pathogen genomics globally and identify strengths and opportunities for enhancements of such systems. COVID-19 in Australia and deployment of AusTrakka At the start of the COVID-19 pandemic in Australia, there were no established mechanisms for rapid and consistent sharing, analysis and reporting of SARS-CoV-2 genomic data. In the context of the pandemic, rapid and informed decision-making was key to successful precision public health responses (2, 3). In Australia, this involved the integration of pathogen genomic data with traditional epidemiological data to provide evidence to inform public health decisions and generate unique public health information (5). Underpinning this public health utility of genomics findings has been the open, integrated, rapid and secure sharing of data between organisations, jurisdictions, and nations (7). Implementing pathogen genomics on a national level requires harmonising data from multiple sources into a central database for analysis, visualisation and reporting. AusTrakka was established as the Australian national platform for interjurisdictional sharing of SARS-CoV-2 genomic data and is operationalised under the Communicable Disease Genomics Network (CDGN) by the AusTrakka Advisory Group and a National Analysis Team (NAT). While the AusTrakka platform commenced development in 2017, the pandemic accelerated its development and deployment, with the platform becoming active in May 2020. Since the establishment of AusTrakka, there has been a strong focus on ongoing monitoring and evaluation of the platform utility and impact to ensure that there is continuous improvement and that the system is fit for purpose. AusTrakka functionality and governance AusTrakka was established to address barriers to genomic data sharing across jurisdictions in Australia and New Zealand, enhance the interoperability and usability of genomic data, and coordinate governance of genomic data. The governance of AusTrakka describes that public health laboratories (PHLs) that upload sequence and meta data to AusTrakka retain custodianship of their data. PHLs can upload sequences to AusTrakka directly through uploading a FASTA file, as well as uploading epidemiological and sample metadata. During the COVID-19 pandemic, PHLs submitted data as it became available and new phylogenetic trees were generated daily, or occasionally more frequently if needed to support public health decision making during the pandemic. A number of analyses can be undertaken through AusTrakka, including routine phylogenetic analysis. Requests for multi-jurisdictional analyses, where sequence data may need to be shared between jurisdictions, or requests for interjurisdictional data are governed through established approval processes. The AusTrakka NAT, comprised of bioinformaticians and genomic epidemiologists located at PHLs across Australia, can access all data to conduct regular genomic analyses (Figure 1). Here we report on our evaluation of AusTrakka and examine how its utilisation and impact shifted throughout the pandemic to demonstrate the public health utility of pathogen genomics and the merit of integrated national platforms to supports its implementation. Methods Our evaluation utilised a mixed-methods approach consisting of a quantitative analysis of AusTrakka utilisation data throughout the pandemic and a qualitative component comprised of key informant interviews and analysis of Variants of Concern (VoC) and AusTrakka Outbreak Investigation (ATOI) reports produced by the AusTrakka NAT. Quantitative data from AusTrakka was analysed to examine changes in utilisation of AusTrakka over time. Upload and user data are available from the launch of AusTrakka and all utilisation data are available from April 2021. This includes: Total number and role of users Uploads of sequences to AusTrakka from each PHL Number of user sessions to view phylogenetic trees VoC summary table views Semi-structured interviews and focus group sessions were held with key informants (n=63) representing all jurisdictions across Australia and New Zealand. These included individuals representing PHLs and health departments, infectious disease physicians, genomic epidemiologists and bioinformaticians. Themes covered in interviews with PHL personnel include: Processes of receiving samples from clinical laboratories, including decisions regarding which samples are prioritised for sequencing and coordination of sample transfer. ‘Future-proofing’ practices to ensure the future useability of isolates and sequence data, including adequate documentation of sample selection and how particular isolates are isolated, cultured, and maintained Issues regarding changes to and levels of satisfaction with workflow processes including managing staff fatigue, training of staff in new processes and ensuring redundancy in laboratory systems; Agreements in place regarding data sharing and rights to access and satisfaction with such agreements; Mechanisms in place to facilitate data archiving, tracking, tracing, and sharing and satisfaction with these mechanisms; Perceived level of articulation between genomic and epidemiological investigations and the approaches by which this is achieved; Perceptions of genomic epidemiologists and bioinformaticians regarding their own understanding of the needs of end users; Sustainability of increases in capacity developed through the COVID-19 pandemic; and Lessons learned and applicability for future pandemic preparedness. Interviews held with AusTrakka stakeholders included bioinformaticians from PHLs responsible for uploading and/or accessing AusTrakka data, members of the National Analysis Team and AusTrakka developers. These interviews explored the following themes: Perspectives of various participants with respect to the expected outcomes from AusTrakka and reasons for participation (or reluctance to participate); Relevant ELSI and how they are managed; Issues of data ownership; Decision-making processes in relation to governance structures and data-sharing agreements; Decisions and criteria regarding selection of genomic and metadata for upload; Technical issues in providing or accessing AusTrakka data; Changes in how AusTrakka has been used throughout the pandemic; Sustainability of AusTrakka and further development; and Utilisation of AusTrakka for pathogens other than SARS-CoV-2. Key informant interviews with genomic data end users were held to assess the perspectives of stakeholders regarding the acceptability, usefulness and sustainability of pathogen genomics in the COVID-19 response. These interviews explored: Reporting agreements and processes in place to communicate SARS-CoV-2 genomic data to end users and satisfaction with these; Perceptions of end users’ own understanding of the uses and limitations of microbial genomics; Perceptions of bioinformaticians’ and genomic epidemiologists’ understanding of end user information needs in relation to SARS-CoV-2 genomic data; Perceived appropriateness of reporting and communication processes; Perceived utility and risks of pathogen genomics in the COVID-19 response; The use of pathogen genomics in public health decision-making, including perceived confidence in making decisions based on the information provided; Which samples are likely to be identified as a high priority for sequencing and why; Implications of selective sequencing strategies for utility in public health decision-making; Technical issues in accessing AusTrakka data; Impetus and anticipated benefit from utilising AusTrakka data; Application of AusTrakka data and utility in public health decision-making; and Lessons learned through the pandemic and applicability for other pathogens. Qualitative one-on-one interviews were conducted virtually by two research team members (ASF, DE). In 2020, 24 interviews were conducted with Victorian key informants given the impact of the pandemic primarily in Victoria at the time. In 2021, 24 individual interviews and 3 group interviews (with 31 participants in total) were held across seven Australian jurisdictions and New Zealand. In 2022, 5 interviews and 5 group interviews (with 18 participants in total) were held. Some 2021 and 2022 interviews included follow-up discussions from previous years. Interviews lasted between 45 minutes and 1 hour 15 minutes. Interviews were audio recorded and notes taken during the interviews. Participants were given the opportunity to review their transcripts to ensure completeness and accurately, and were able to provide corrections or additional information. Key informants were approached due to their positions held and their involvement in the COVID-19 response. Participants were also asked to identify any additional relevant key informants. Initial contact was via email. While the majority of key informants agreed to participate in the research, there were some that were not available due to the intensity of competing demands on their time during the research period. Recruitment continued until key informants in relevant positions were identified across all jurisdictions. Key informants included: Representatives from the CDGN PHL staff (bioinformaticians, genomic scientists, genomic epidemiologists) AusTrakka team members (NAT, Development Team) AusTrakka stakeholders (user groups, end users (government, public health units (PHUs), clinicians)) Two authors (ASF and DE) conducted the interviews. ASF (PhD, female) is the lead researcher and holds an Academic Specialist position. DE (MPH, female) conducted interviews in the role of Research Assistant. Both interviewers have had training and extensive experience in conducting interviews and qualitative research. Interviewers did not have knowledge or relationships prior to study commencement. In 2020 and 2021, upon request, the AusTrakka NAT provided ongoing monthly national reports and weekly SARS-CoV-2 VoC reports to support multijurisdictional outbreak investigations. These reports were examined with regards to intended audience, application and information included. Analysis was underpinned by the relevant attributes outlined in the US CDC’s Updated Guidelines for Evaluating Public Health Surveillance Systems (the Guidelines). Given the evaluation’s focus on the contribution of AusTrakka to public health surveillance and response to COVID-19, technical attributes of the system were not assessed. The elements of Simplicity (the simplicity of the surveillance system’s structure and ease of operations) and Stability (a system’s ability to collect, manage, and provide data properly without failure and ability to be operational when needed) were therefore not included. Predictive Positive Value (the proportion of reported cases that actually have the health-related event under surveillance) is not relevant to pathogen genomics and has also been excluded. Qualitative coding was undertaken by ASF using NVivo13. Codes were developed a priori based on the structure of the relevant attributes from the Guidelines. Ethical approval to conduct this study was obtained from the University of Melbourne Biomedical Sciences Human Ethics Advisory Group (ID: 2056426.1). Results Usefulness The Guidelines consider a public health surveillance system to be useful if it ‘contributes to the prevention and control of adverse health-related events, including an improved understanding of the public health implications of such events’. Since it became operational in May 2020, AusTrakka provided a centralised platform to enable interjurisdictional data sharing. Sharing sequence and metadata across jurisdictions was used to facilitate investigation of multi-jurisdictional outbreaks and clarify transmission chains during the period when preventing interjurisdictional transmission was a key public health focus. AusTrakka began to be used with increasing functionality in July to August 2020. Until this point, comparison of genomic data between jurisdictions was mainly undertaken using publicly available data or by sharing data via e-mail or file sharing. The additional analytical capability provided by AusTrakka was seen to be particularly important for those jurisdictions that had limited local capacity. In 2021, AusTrakka end users from PHLs indicated that they used AusTrakka regularly to situate their own local sequences within the national context and highlighted the utility of centralising jurisdictional data. …it's important to have the national sort of samples because initially at the time when the first COVID happened we only have… 200 cases and they're all from all sorts of different places, or different areas. So in order to trace particular cases or clusters is a bit tricky … So it's always important to consolidate everything that we have into a single repository, and that’s where AusTrakka comes in… When end users were asked about the reason for their AusTrakka use over 2020 and 2021, the most common response across a number of settings was for confirming or rejecting a hypothesis regarding transmission that had been developed from the epidemiological data or providing additional clarity about transmission where there was limited epidemiological information available. In 2022, the utilisation of AusTrakka focused on VoC surveillance in response to the public health demand at the time. While to date, the direct public health impacts of VoC surveillance are uncertain, this was particularly important for communication and understanding the distribution of variants in the population, as well as monitoring the possibility of emerging strains that may exhibit increase public health risks. The first fear was, you know, a new variant of concern… suddenly another variant starts to take over there’s this worry, is this going to be worse? … Will it be resistant to drugs? Will it … be a more severe disease? A key use of AusTrakka in the COVID-19 pandemic was in providing access to data and reports which increased confidence in public health approaches. The interviewee below speaks on demonstrating that lockdowns were effective in preventing transmission, which led to increased confidence in continuing to use this strategy to control outbreaks. By the time we get to that point we don’t need that link – it’s not going to change anything we do, it just provides a bit of reassurance… In addition, the genomic findings had value in being able to provide accurate advice regarding VoCs to national bodies and provide context for data interpretation with regards to jurisdictional sequencing strategies. So it’s been a very invaluable process to be able to see what is going on, particularly because we have to provide a lot of advice higher up…and it’s helped the confidence of the advice in that we do actually understand what is going on nationally. In addition to individual users within jurisdictions using AusTrakka to identify interjurisdictional transmission, the AusTrakka NAT regularly produced national-level reports, including monthly Communicable Diseases Intelligence reports for COVID-19 and monthly AusTrakka SARS-CoV-2 national genomics surveillance reports. AusTrakka reports were helpful in providing up-to-date data used in briefings and public-facing sessions, facilitating appropriate public communication both internally and externally, nationally and internationally. Acceptability Acceptability is characterised as the ‘willingness of persons and organizations to participate in the surveillance system’ ( 11 ). The anticipated need for efficient sequence data sharing to inform the pandemic response prompted further development and operationalisation of AusTrakka in the early stages of the COVID-19 pandemic. As the interviewee below outlines, AusTrakka is comprised of three key components: 1) the open-data sharing philosophy underpinning its development 2) the established data governance between stakeholders 3) the accessibility useability of the platform itself. Developing these three elements were shown to be central to the acceptability of AusTrakka. I think it’s fair to say AusTrakka is kind of three different things, it's… the data sharing philosophy… there's the web platform…itself which enables the interaction sharing of the data, and then there's sort of the governance and all the agreements behind it. And although the platform only exists now, the philosophy was there, and then quite a few years were spent getting this data sharing agreement up over many years…the philosophy was always there, the data sharing took years of groundwork… Open Science principles around data sharing were central to the design and implementation of AusTrakka. Underpinning this philosophy of open data sharing was the presence of established governance between all stakeholders and a governance framework to ensure responsible data-sharing practices. ... I think that if we had had a team that wasn’t as conscious of their legal responsibilities, if data breaches had occurred, or if there had been any leakage, it would’ve posed a problem. So I think the information security side has been good, that’s provided a sense of trust. Willingness to participate is indicated by an increase in the number of users and contributing jurisdictions over time. As of October 2022, there were 76 active users across 12 individual organisations with access to the AusTrakka platform. Within two months of the launch of AusTrakka, there were active users from each of Australia’s jurisdictions and New Zealand, showing that the platform was adopted quickly. Over the initial three months, the numbers of users grew at an average of 10 new users per month and by the end of 2020 most jurisdictions had at least four end users (Fig. 2 ). The next section describes in more detail the willingness of users to contribute sequence data to the system. Representativeness and sensitivity The Representativeness of a system is the extent to which it ‘accurately describes the occurrence of a health-related event over time and its distribution in the population by place and person.’ Sensitivity refers to the proportion of cases of a disease detected by the surveillance system and the ability of the system to detect outbreaks and monitor changes in the number of cases over time. The representativeness and sensitivity of AusTrakka relies on the consistent generation and contribution of sequences from across jurisdictions. As of October 2022, a total of 166 083 SARS-CoV-2 sequences from Australia and New Zealand were available through AusTrakka. In this time, 1735 phylogenetic trees were made available to end users. The total number of sequences uploaded mirrored growing case totals in Australia and New Zealand throughout the second wave in Victoria in July 2020, the Delta outbreak in New South Wales (NSW) and Victoria from July/August 2021 and the start of the Omicron outbreak in December 2021. Following this we see the number of uploaded sequences remaining high throughout 2022 with peaks in April and July where over 2500 sequences were uploaded in a single week. Each of these peaks was primarily driven by large number of uploads from an individual organisation and jurisdiction (Fig. 3 ). A Spearman's correlation test was run to determine the relationship between reported weekly COVID-19 cases and weekly sequence uploads to AusTrakka. The test showed a strong, positive monotonic correlation and association between COVID-19 case numbers and sequence uploads (R = 0.697, 95% CI (0.604–0.772), p < 0.001). By the end of 2021, a total of 53,285 SARS-CoV-2 sequences were uploaded to AusTrakka by PHLs, at an average rate of 500 sequences uploaded per week. Additionally, 535 phylogenetic trees were made available to users—174 between June 2020 and June 2021 and 361 between July and December 2021. In the first 10 months alone of 2022 112,798 sequences were uploaded to AusTrakka at an average rate of 2,700 sequences uploaded per week. During this time, 1,200 phylogenetic trees were made available at an average rate of 30 tree accesses per week (Fig. 4 ). Figure 5 below shows clear peak of tree image loads in June and July 2021 of 60–87 weekly loads respectively, which correlates with rising cases at this time. In total there are 1,204 tree data loads recorded in 2021 with an average of approximately 38 loads per week in this time. Utilisation begins to increase again towards the end of 2021 as case totals related to the Omicron variant surge. Throughout 2022 the number of tree data loads declines despite rising case numbers as contact tracing efforts and social restrictions begin to be rolled back in multiple jurisdictions. Similarly to the tree uploads there is a peak of use in June 2021 of 22 VoC weekly loads. From May 2021 until December 2021 there are 230 VoC summary table views which is approximately eight views per week throughout the year. However, unlike the number of tree loads, which declines over 2022, VoC table views remain high, indicating continued use (Fig. 6 ). From early 2022, with opening of the international borders and the increasing use of Rapid Antigen Testing (RAT), there was a shift in how AusTrakka was utilised in the public health response to SARS-CoV-2. With the sheer number of COVID cases now, AusTrakka is less representative through no fault of its own just the sheer number of cases and the prevalence of … RATs which you can't sequence from and a shift in the … sequencing priorities from the jurisdictions …and so the focus of AusTrakka has shifted to more of a variant surveillance platform. This shift in priorities throughout the pandemic led to lowered rates of direct user engagement with AusTrakka alongside a continued high level of interest in and utilisation of AusTrakka reports, particularly in relation to VoC identification. At the moment we are providing particularly focussed on there’s a really great graphic in the VOC report that actually goes up to the health minister weekly so that’s on the variants … and then of course the information does filter through to the weekly surveillance reports that get developed at the national level. Timeliness Timeliness according to the Guidelines ‘reflects the speed between steps in a public health surveillance system’. While interviewees generally agreed that having access to genomic data through AusTrakka was useful in confirming or discarding these hypotheses, the majority also indicated that genomic data was typically not available quickly enough to inform the day-to-day response to COVID-19. …on a day-to-day basis it doesn’t actually make a huge impact, we’re responding very rapidly as you would understand and need to respond rapidly within 24 hours of identifying a case in terms of managing the case, and identifying their close contacts, so obviously in relation to those close contacts it has no impact, but and also in relation to outbreaks when our outbreak management is very much based on epidemiological data … Data quality The Guidelines state that ‘ Data quality reflects the completeness and validity of the data recorded in the public health surveillance system’. The importance of the relationships between PHLs and PHUs in relation to ensuring pathogen genomic data quality and the articulation between epidemiological and genomic data was a recurring theme in the interviews. There was an understanding that the power of genomic data lies in its use alongside epidemiological data, and interviewees were consistent in expressing a need for routine articulation to derive the most benefit from genomic data. But I think the other really important thing that I have learnt is that you do have to line it up with the epidemiology and what you get from basic interviewing, you know like with the ICU people had we not known that they were married we would’ve said they were separate, completely separate subtypes. So yeah I think correlating it with your epi is really important. While some interviewees indicated that this was normally done well, others expressed concern that there were times that incorrect conclusions were drawn due to insufficient contextualisation from epidemiological data. The collaborative nature of the work also brought with it significant challenges in managing data across organisations, which was repeatedly mentioned throughout the research. While the following quote comes from the earlier days of the pandemic, subsequent interviews indicated that there have been minimal improvements to data management. And I think one of the hardest things has actually been data management… we’re getting information from at least six different sources… a lot of privacy issues means it’s hard to match things up…trying to coordinate that has been a bit of a nightmare. Some interviewees indicated that the COVID-19 epidemic presented a unique opportunity to create viable structures to enable stronger integration. …the main thing I would like to see coming out of this is an extension to the way genomic and epidemiological data are integrated and speed and efficiency with which intelligence can be gathered by their integration. That’s what I’d really love to come out of this. And we’ve got that opportunity now . Flexibility The Flexibility of a public health surveillance system is based on its ability to ‘adapt to changing information needs or operating conditions with little additional time, personnel, or allocated funds’. While AusTrakka was rapidly developed during the COVID-19 pandemic and focused on SARS-CoV-2, interviewees indicated that the genomics infrastructure developed in response to COVID-19 was largely applicable to other pathogens. A key development to facilitate and simplify data-sharing moving forward has been a shift towards ‘pathogen agnostic’ governance frameworks which support the broader application of pathogen genomics. What has changed is…we had pathogen-specific data governance but now because we were working with COVID mainly and we had started branching out to some other pathogens but now that we are starting to take a lot more pathogens and... we have now shifted to a pathogen agnostic framework which has the same principles it’s just that it covers all of the pathogens. While there has been a move towards data-sharing agreements that cover all pathogens, participants also indicated that elements such as minimum metadata requirements would need to be established on a per-pathogen basis. In line with this approach, ‘AusTrakka 2’ has been developed to be pathogen agnostic. AusTrakka 1 really was set up in a hurry for COVID ….AusTrakka 2 is set up in a much more generic way, so we can put in different proformas for different fields are expected and they're validated and we have to supply that metadata if you are putting it in through that system, all the metadata can be kind of checked against one another in a consistent way and the permissions can be set up and done properly. There are several possible and developing applications where capacity could be strengthened to increase the benefit of pathogen genomics in the control of COVID-19 and future preparedness. While still in the early stages, there is scope for AusTrakka to potentially be used more broadly to enable access to genomic data across a variety of organisations in human health. I think well there will be two main potential clients – one would be hospitals and the other ones would be labs more generally. So in the hospital a lot of it will come through the micro lab, but I think we’re kind of viewing this as a pilot for how AusTrakka or a similar platform can be used to communicate genomic data to hospitals and health systems and labs…. Interviewees referred to other communicable diseases and the potential benefits of the AusTrakka platform evolving as a One Health tool. We also now see that outside of the context of COVID-19, the AusTrakka model is going to be useful for so many other communicable diseases. So currently Monkeypox, but also Japanese Encephalitis, and the really important thing about Japanese Encephalitis is that we have an opportunity for AusTrakka to bridge the boundaries of human health and to evolve into a One Health tool. Table 1 AusTrakka performance against elements of public health surveillance system quality Elements of surveillance quality AusTrakka performance Impact of element Usefulness: contributes to the prevention and control of adverse health-related events, including an improved understanding of the public health implications of such events • Provided a centralised platform to enable interjurisdictional data sharing • Shift over the course of the pandemic from identifying transmission networks towards VoC surveillance • Provided centralised access to jurisdictional and national-level data and reports • Provided advice to national bodies and context for data interpretation • End users used centralised data to situate their own local sequences within the national context • Provided up-to-date data used in briefings and public-facing sessions • Shared sequence and metadata were used to facilitate investigation of outbreaks and clarify transmission chains to inform prevention of interjurisdictional transmission • Availability of data and reports increased confidence in public health approaches, including large-scale lockdowns to prevent transmission • Improved communication and understanding distribution of variants in the population and contributed to monitoring emerging strains that may increase public health risks • Facilitated appropriate public communication both internally and externally, nationally and internationally Flexibility: able to adapt to changing information needs or operating conditions • AusTrakka was limited to SARS-CoV-2 data, but infrastructure is largely applicable to other pathogens • AusTrakka 2 has been developed to be pathogen agnostic • The establishment of AusTrakka facilitated a shift towards ‘pathogen agnostic’ governance frameworks which support the broader application of pathogen genomics. • Scope for AusTrakka to enable access to genomic data across a variety of health organisations • Potential of AusTrakka evolving as a One Health tool Data quality: completeness and validity of the data recorded in the public health surveillance system • Relationships between PHLs and PHUs crucial to ensuring pathogen genomic data quality and articulation between epidemiological and genomic data • Challenges in managing data across organisations • Concern regarding incorrect conclusions due to insufficient contextualisation from epidemiological data Acceptability: willingness of persons and organisations to participate in the surveillance system • AusTrakka is underpinned by established governance between all stakeholders and a framework to ensure responsible data-sharing practices • Established data governance by stakeholders was shown to be central to the acceptability of AusTrakka • Quick uptake across jurisdictions at the beginning of the pandemic • Steady increase in number of users and organisations contributing to AusTrakka from mid-2020 to 2022 Sensitivity: at the level of case reporting, the proportion of cases of a disease detected by the surveillance system; also, the ability to detect outbreaks and monitor changes in the number of cases over time Representativeness: ability to accurately describe the occurrence of a condition over time and its distribution in the population • Strong positive correlation and association between COVID-19 case numbers and sequence uploads • Shift in priorities throughout the pandemic led to lower rates of direct user engagement with AusTrakka alongside a continued high level of interest in and utilisation of AusTrakka reports, particularly in relation to VoC identification • Tree image views correlates with rising cases Timeliness: the speed between steps in a surveillance system • Genomic data generally not available within a timeframe to inform day-to-day decision-making or case management • AusTrakka supported access to data that was used to confirm or discard hypotheses regarding transmission • Genomic data was used to support broader outbreak management and clarify transmission chains • Availability of data and reports increased confidence in public health approaches, including large-scale lockdowns to prevent transmission • Facilitated appropriate public communication both internally and externally, nationally and internationally Discussion Whole genome sequencing has proven to be a revolutionary technology, and one that has been increasingly embedded into public health responses to current communicable disease threats and planning for future epidemic and pandemic preparedness. With sequencing capacity continuing to increase, there is a need for ongoing evaluation of pathogen genomics surveillance systems both to ensure functionality and to understand and incorporate elements of pathogen genomics-informed surveillance systems that contribute to public health outcomes. The development and implementation of AusTrakka in the early stages of the COVID-19 pandemic in Australia allowed for centralised and efficient inter-jurisdictional sharing of sequences, as well as epidemiological and sequence metadata, which previously did not exist. This facilitated jurisdictional and national understanding of transmission events and outbreaks, and informed population-level public health responses. Over the period 2020 to 2022, the COVID-19 pandemic changed enormously and throughout this time, the use of AusTrakka in the public health response also shifted. The high Acceptability (willingness of persons and organisations to participate) of AusTrakka was predicated on the governance mechanisms which were collectively established by stakeholders across Australian jurisdictions. Having national-level coordination and governance of AusTrakka was an important factor both in facilitating the development of the platform and in ensuring continued trust and buy-in. The central role played by end users in the design led to rapid adoption across jurisdictions, which then supported robust sequence uploads and increased Representativeness (ability to accurately describe the occurrence of a health-related event over time) and Sensitivity (proportion of cases detected by a surveillance system and the ability to detect outbreaks). Integration between epidemiological and genomic data was identified as an ongoing challenge to the Data quality system attribute. The importance of a platform capable of harmonising data from multiple source and linking genomic data with epidemiological data was clearly demonstrated. The integration of epidemiological and genomic data was shown to have two key elements, first, the integration of data systems to facilitate increased data sharing or access to data and second, working relationships and human capacity to understand and utilise genomic and epidemiological data appropriately. While having access to genomic and epidemiological data is one part of an effective system, data needs to be coupled with analysis through effective communication among those who are contributing to the decision-making process. This supports the need for integrated national pathogen genomics surveillance platforms such as AusTrakka alongside ongoing training, capacity building and strong communication to enhance its public health utility. Implications for development of pathogen genomics-informed surveillance systems Explicit consideration of surveillance system quality criteria and ongoing evaluation The evaluation of AusTrakka makes clear how supporting criteria of surveillance quality facilitates system use and impact. Ongoing monitoring and evaluation is essential to ensure that the fundamental changes to surveillance systems enacted by the introduction of pathogen genomics (e.g. changes in data generation, governance and sharing; reporting and communication; and use of genomic data in public health implementation) are undertaken in ways that provide increased utility to users and contribute to public health outcomes ( 14 , 15 ). Consideration of these factors and how to ensure they are represented in the system should be undertaken in the early stages of planning, establishment and integration of public health pathogen genomics. Frameworks to support evaluation of pathogen genomics-informed surveillance systems have been adapted from established guidelines to evaluate surveillance systems ( 7 ); use of these frameworks to guide development and implementation will support in-depth understanding of how well the system is functioning, identification of expected and unexpected impacts and early and ongoing identification of appropriate targets for system strengthening. This will be particularly relevant as use of pathogen genomics continues to expand and be used in novel approaches, such as in the development of One Health surveillance systems and integration of metagenomics. Strong governance and engagement The experience of AusTrakka during the COVID-19 pandemic illustrates the centrality of the Acceptability criterion in responding to the Usefulness , Representativeness and Sensitivity criteria; that is, buy-in, engagement and trust was essential to the functionality of AusTrakka. This is reinforced by the emphasis placed on national leadership, ownership and commitment by the WHO guidance for developing national genomic surveillance ( 15 ). However, this engagement must be multi-level, rather than resting solely at the national level, and include representation from sub-national and organisational levels that generate and use pathogen genomic data. This includes PHLs, policymakers, PHUs, donors and implementing partners. Coordination across these stakeholders from the early stages facilitates a shared understanding of the purpose and benefits from the integration of pathogen genomics in surveillance systems, as well as the contribution and roles of each. Given the ongoing evolution in application of pathogen genomics, this ongoing coordination and engagement is also necessary to support adaptability and sustainability of the system. Data quality and harmonisation Sequence data must be appropriately contextualised in order to be useful for public health purposes. This necessitates the harmonisation of data from different sources; however, this is a recognised challenge as laboratories, public repositories, international agencies, hospitals and other data sources may use different standards, formats and methods for collection and organisation of data. Approaches such as the Public Health Alliance for Genomic Epidemiology (PHA4GE) contextual data standard aim to address these challenges ( 16 ); development of the AusTrakka COVID-19 pro forma was based on the PHA4GE data standards for international consistency. Within Australia, programs such as AusPathoGen (a translational research program funded by the Medical Research Future Fund) are now providing evidence towards a best-practice national approach and strengthening capacity to coordinating the genomics experts across Australia to harmonise the implementation of pathogen genomics within Australia’s health system ( 17 ). Data standardisation, particularly through bioinformatics analysis proved to be a key driver in generating consistency across jurisdictions in the reporting and communication of genomics surveillance outputs. Data harmonisation may also be facilitated through the development of a centralised approach to data management and sharing ( 15 ) and establishment of a centralised platform for data sharing such as AusTrakka can facilitate and be an impetus for coordinated data harmonisation at multiple levels. In developing the future iterations of AusTrakka, a focus on consistency and alignment with both national and international data standards will be required to ensure ease of use of the platform. Furthermore, interoperability or harmonisation of the platform to existing surveillance systems at both a subnational and national level will assist with potential issues in resourcing or capacity that may arise in a post-pandemic environment where investment in pathogen genomics will not be at the same scale. AusTrakka provides a semi-open environment that adopts the FAIR (Findability, Accessibility, Interoperability, and Reuse of digital assets) data principles that states that data should be ‘as open as possible, and as closed as necessary’ ( 18 ). In the public health environment, whilst the generation of pathogen genomic data is being implemented widely across the world, the analysis, interpretation and implementation into data for action is still an emerging field in many countries. Particularly during the COVID-19 pandemic, which experienced a rise in misinformation and disinformation, AusTrakka provided a secure environment that allowed for the rapid data sharing between PHLs that provided public health decision makers with a centralised capacity for a coordinated and consistent approach to understanding the genomics landscape during this critical time. Conclusions Whole genome sequencing is a transformative technology that has been increasingly integrated into public health responses to communicable diseases. The development and implementation of AusTrakka in the early stages of the COVID-19 pandemic in Australia allowed for centralised and efficient inter-jurisdictional sharing of sequences, as well as epidemiological and sequence metadata. The experience of AusTrakka highlights the importance of robust governance on the willingness of persons and organisations to contribute and participate. This engagement and adoption is fundamental to the effectiveness, representativeness and sensitivity of the system. With public health sequencing capacity continuing to increase, there is a need for ongoing evaluation of pathogen genomics surveillance systems both to ensure functionality and to understand and incorporate elements of pathogen genomics-informed surveillance systems that contribute to public health outcomes. Declarations Ethics approval and consent to participate Ethical approval to conduct this study was obtained from the University of Melbourne Biomedical Sciences Human Ethics Advisory Group (HEAG) (Application ID: 2056426.1). Consent for publication Consent for publication was obtained from all participants in line with ethical approval from the University of Melbourne HEAG. Availability of data and materials The data generated and analysed during the current study are not publicly available due to reasons of confidentiality and privacy but are available from the corresponding author on reasonable request. Competing interests The authors are employed at the organisation that has received funding for development of the AusTrakka platform. The authors are not directly involved in this work. Funding This work was funded by the National Health and Medical Research Council (NHMRC) through the Medical Research Future Fund (MRFF) – Coronavirus Research Response: 2020 Tracking COVID-19 in Australia using Genomics Grant Opportunity (MRF9200006). AusTrakka is supported by the Australian Government Department of Health, Disability and Ageing (the Department). The opinions expressed in this publication are those of the authors, and do not necessarily represent the views of the Department. Authors' contributions ASF conceptualised the research. ASF and CME drafted the initial manuscript. All authors have had the opportunity to review and approve the manuscript before submission. Acknowledgements Not applicable References Black A, MacCannell DR, Sibley TR, Bedford T. Ten recommendations for supporting open pathogen genomic analysis in public health. Nature Medicine. 2020;26(6):832-41. Allard MW, Strain E, Melka D, Bunning K, Musser SM, Brown EW, et al. Practical Value of Food Pathogen Traceability through Building a Whole-Genome Sequencing Network and Database. J Clin Microbiol. 2016;54(8):1975-83. Chattaway MA, Dallman TJ, Larkin L, Nair S, McCormick J, Mikhail A, et al. The Transformation of Reference Microbiology Methods and Surveillance for Salmonella With the Use of Whole Genome Sequencing in England and Wales. Frontiers in Public Health. 2019;7. Revez J, Espinosa L, Albiger B, Leitmeyer KC, Struelens MJ. Survey on the Use of Whole-Genome Sequencing for Infectious Diseases Surveillance: Rapid Expansion of European National Capacities, 2015-2016. Front Public Health. 2017;5:347. Kwong JC, Mercoulia K, Tomita T, Easton M, Li HY, Bulach DM, et al. Prospective Whole-Genome Sequencing Enhances National Surveillance of Listeria monocytogenes. J Clin Microbiol. 2016;54(2):333-42. Australian Government Department of Health and Aged Care. National Microbial Genomics Framework. Canberra; 2019. Ferdinand AS, Kelaher M, Lane CR, da Silva AG, Sherry NL, Ballard SA, et al. An implementation science approach to evaluating pathogen whole genome sequencing in public health. Genome Med. 2021;13(1):121. Alleweldt F, Kara Ş, Best K, Aarestrup FM, Beer M, Bestebroer TM, et al. Economic evaluation of whole genome sequencing for pathogen identification and surveillance - results of case studies in Europe and the Americas 2016 to 2019. Euro Surveill. 2021;26(9). Tran M, Smurthwaite KS, Nghiem S, Cribb DM, Zahedi A, Ferdinand AD, et al. Economic evaluations of whole-genome sequencing for pathogen identification in public health surveillance and health-care-associated infections: a systematic review. Lancet Microbe. 2023;4(11):e953-e62. Scharff RL, Besser J, Sharp DJ, Jones TF, Peter GS, Hedberg CW. An Economic Evaluation of PulseNet: A Network for Foodborne Disease Surveillance. Am J Prev Med. 2016;50(5 Suppl 1):S66-s73. Guidelines Working Group. Updated Guidelines for Evaluating Public Health Surveillance Systems: United States Centers for Diseases Control; 2001 [Available from: https://www.cdc.gov/mmwr/preview/mmwrhtml/rr5013a1.htm. World Health Organization. Communicable disease surveillance and response systems: Guide to monitoring and evaluating. World Health Organization; 2006. Hoang T, da Silva AG, Jennison AV, Williamson DA, Howden BP, Seemann T. AusTrakka: Fast-tracking nationalized genomics surveillance in response to the COVID-19 pandemic. Nature Communications. 2022;13(1):865. World Health Organization. Global genomic surveillance strategy for pathogens with pandemic and epidemic potential, 2022–2032. Geneva; 2022. World Health Organization. Considerations for developing a national genomic surveillance strategy or action plan for pathogens with pandemic and epidemic potential. Geneva; 2023. Griffiths EJ, Timme RE, Mendes CI, Page AJ, Alikhan NF, Fornika D, et al. Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package. Gigascience. 2022;11. Webb JR, Andersson P, Sim E, Zahedi A, Donald A, Hoang T, et al. Implementing a national programme of pathogen genomics for public health: the Australian Pathogen Genomics Program (AusPathoGen). The Lancet Microbe. 2025;6(3). GO FAIR. FAIR Principles [Available from: https://www.go-fair.org/fair-principles/. Additional Declarations Competing interest reported. The authors are employed at the organisation that has received funding for development of the AusTrakka platform. The authors are not directly involved in this work. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Aug, 2025 Reviews received at journal 08 Aug, 2025 Reviews received at journal 31 Jul, 2025 Reviewers agreed at journal 29 Jul, 2025 Reviewers agreed at journal 08 Jul, 2025 Reviews received at journal 15 Jun, 2025 Reviewers agreed at journal 15 Jun, 2025 Reviewers agreed at journal 29 May, 2025 Reviewers invited by journal 29 May, 2025 Editor assigned by journal 28 May, 2025 Submission checks completed at journal 28 May, 2025 First submitted to journal 27 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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2","display":"","copyAsset":false,"role":"figure","size":34675,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative AusTrakka users\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6758871/v1/c210782aa31738ca38b8c1f4.png"},{"id":83746925,"identity":"dd2d08c6-c5fe-4430-954a-a0ef483426ac","added_by":"auto","created_at":"2025-06-02 05:01:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":75036,"visible":true,"origin":"","legend":"\u003cp\u003eWeekly COVID-19 cases versus sequence uploads\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6758871/v1/233cd1e608a435891c924a7f.png"},{"id":83746930,"identity":"81997e50-83df-459c-a45b-19819d68e9de","added_by":"auto","created_at":"2025-06-02 05:01:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":57818,"visible":true,"origin":"","legend":"\u003cp\u003eWeekly counts of phylogenetic trees generated\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6758871/v1/8c2705ded1b75dc2edcc34aa.png"},{"id":83746928,"identity":"0fa18dcf-72f5-4612-9564-c68fe01fe98c","added_by":"auto","created_at":"2025-06-02 05:01:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":58013,"visible":true,"origin":"","legend":"\u003cp\u003eWeekly counts of phylogenetic trees loaded\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6758871/v1/7458d870d8eee80ac5e5c896.png"},{"id":83746927,"identity":"63d1a568-655c-429f-b7ed-a15796c91559","added_by":"auto","created_at":"2025-06-02 05:01:11","extension":"png","order_by":6,"title":"Figure 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The authors are employed at the organisation that has received funding for development of the AusTrakka platform. The authors are not directly involved in this work.","formattedTitle":"High acceptability of a national platform for public health genomic data sharing and surveillance in Australia: a mixed methods evaluation study","fulltext":[{"header":"Background","content":"\u003cp\u003ePathogen genomics is increasingly being integrated into public health surveillance and outbreak investigations around the world in the detection, prevention and control of infectious diseases (1). The US Food and Drug Administration established GenomeTrakr in 2012 as the first laboratory network to utilise whole genome sequencing (WGS) in tracing bacterial foodborne contamination and pathogen identification (2). Soon after, in 2014, Public Health England began using pathogen genomics in \u003cem\u003eSalmonella\u003c/em\u003e surveillance (3) and by 2016, 26 European countries reported routine use of WGS in public health practice (4). In 2020, the COVID-19 pandemic brought into focus the necessity of national and international surveillance systems that are adequately equipped to understand and respond to emerging and previously unknown pathogens.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAustralia was also an early adopter of pathogen genomics for public health surveillance and response activities with national genomic surveillance of Listeriosis as an example (5). The Australian government released its first National Microbial Genomics Framework in 2019 (6),\u0026nbsp;which highlighted the value of genomics in infectious diseases surveillance and promoted national consistency and mechanisms for data sharing.\u003c/p\u003e\n\u003cp\u003eSystematic evaluation of pathogen genomic surveillance systems\u003c/p\u003e\n\u003cp\u003eRigorous and systematic evaluation of surveillance systems that integrate pathogen genomics is important for making explicit the expected contribution of pathogen genomics; understanding how well such surveillance systems are meeting their objectives; and clarifying the processes by which they do so, or areas requiring further strengthening. Evaluation contributes to the body of evidence available for the development of genomics-informed public health practice and supports identification of needed investment, infrastructure and training (7).\u003c/p\u003e\n\u003cp\u003eDespite substantial investment into the integration of pathogen genomics in public health surveillance, evaluation of genomics-informed surveillance systems has been limited. \u0026nbsp; Where evaluation has taken place, the focus has been on economic evaluation (8-10), rather than the surveillance system\u0026rsquo;s usefulness, or the attributes that contribute to the system attaining its objectives. This may be because there are limited systems globally that have been fully implemented. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe US Centers for Disease Control (CDC) published the \u003cem\u003eUpdated Guidelines for Evaluating Public Health Surveillance Systems\u003c/em\u003e in 2001 to support integration of surveillance and health information and address changes in public health surveillance to respond to emerging health threats including new diseases (11). The updated guidelines aim to help organise the evaluation of a public health surveillance system for assessment of how well the system meets its purpose and objectives. These guidelines also underpin the elements of surveillance quality in WHO\u0026rsquo;s 2006 \u003cem\u003eCommunicable disease surveillance and response systems: Guide to monitoring and evaluating\u003c/em\u003e (12).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn considering the usefulness of a public health surveillance system, the guidelines indicate that a useful system contributes to prevention and control of adverse health-related events, and an improved understanding of such events. The guidelines state that due to variability between surveillance systems, relevant attributes may differ between systems. The surveillance system and therefore the evaluation should place emphasis on those attributes that are most important to the objectives of the system (12).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt the time of this evaluation, despite the strong and increasing investment in public health pathogen genomics and the integration of pathogen genomics into surveillance systems, a systematic evaluation of attributes contributing to the usefulness of such systems was not available. We therefore applied the CDC Updated Guidelines for Evaluating Public Health Surveillance Systems to evaluate the usefulness of the Australian national platform for public health pathogen genomics, AusTrakka (13). This represents an early opportunity to evaluate one of the first national platforms for data integration in pathogen genomics globally and identify strengths and opportunities for enhancements of such systems.\u003c/p\u003e\n\u003cp\u003eCOVID-19 in Australia and deployment of AusTrakka\u003c/p\u003e\n\u003cp\u003eAt the start of the COVID-19 pandemic in Australia, there were no established mechanisms for rapid and consistent sharing, analysis and reporting of SARS-CoV-2 genomic data. In the context of the pandemic, rapid and informed decision-making was key to successful precision public health responses (2, 3). In Australia, this involved the integration of pathogen genomic data with traditional epidemiological data to provide evidence to inform public health decisions and generate unique public health information (5). Underpinning this public health utility of genomics findings has been the open, integrated, rapid and secure sharing of data between organisations, jurisdictions, and nations (7).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eImplementing pathogen genomics on a national level requires harmonising data from multiple sources into a central database for analysis, visualisation and reporting. AusTrakka was established as the Australian national platform for interjurisdictional sharing of SARS-CoV-2 genomic data and is operationalised under the Communicable Disease Genomics Network (CDGN) by the AusTrakka Advisory Group and a National Analysis Team (NAT). While the AusTrakka platform commenced development in 2017, the pandemic accelerated its development and deployment, with the platform becoming active in May 2020. Since the establishment of AusTrakka, there has been a strong focus on ongoing monitoring and evaluation of the platform utility and impact to ensure that there is continuous improvement and that the system is fit for purpose.\u003c/p\u003e\n\u003cp\u003eAusTrakka functionality and governance\u003c/p\u003e\n\u003cp\u003eAusTrakka was established to address barriers to genomic data sharing across jurisdictions\u0026nbsp;in Australia and New Zealand, enhance the interoperability and usability of genomic data, and coordinate governance of genomic data. The governance of AusTrakka describes that public health laboratories (PHLs) that upload sequence and meta data to AusTrakka retain custodianship of their data. PHLs can upload sequences to AusTrakka directly through uploading a FASTA file, as well as uploading epidemiological and sample metadata. \u0026nbsp;During the COVID-19 pandemic, PHLs submitted data as it became available and new phylogenetic trees were generated daily, or occasionally more frequently if needed\u0026nbsp;to support public health decision making during the pandemic.\u003c/p\u003e\n\u003cp\u003eA number of analyses can be undertaken through AusTrakka, including routine phylogenetic analysis. \u0026nbsp;Requests for multi-jurisdictional analyses, where sequence data may need to be shared between jurisdictions, or requests for interjurisdictional data are governed through established approval processes. The AusTrakka NAT, comprised of bioinformaticians and genomic epidemiologists located at PHLs across Australia, can access all data to conduct regular genomic analyses (Figure 1).\u003c/p\u003e\n\u003cp\u003eHere we report on our evaluation of AusTrakka and examine how its utilisation and impact shifted throughout the pandemic to demonstrate the public health utility of pathogen genomics and the merit of integrated national platforms to supports its implementation.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eOur evaluation utilised a mixed-methods approach consisting of a quantitative analysis of AusTrakka utilisation data throughout the pandemic and a qualitative component comprised of key informant interviews and analysis of Variants of Concern (VoC) and AusTrakka Outbreak Investigation (ATOI) reports produced by the AusTrakka NAT.\u003c/p\u003e\n\u003cp\u003eQuantitative data from AusTrakka was analysed to examine changes in utilisation of AusTrakka over time. Upload and user data are available from the launch of AusTrakka and all utilisation data are available from April 2021. This includes:\u0026nbsp;\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eTotal number and role of users\u003c/li\u003e\n \u003cli\u003eUploads of sequences to AusTrakka from each PHL\u003c/li\u003e\n \u003cli\u003eNumber of user sessions to view phylogenetic trees\u003c/li\u003e\n \u003cli\u003eVoC summary table views\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eSemi-structured interviews and focus group sessions were held with key informants (n=63) representing all jurisdictions across Australia and New Zealand. These included individuals representing PHLs and health departments, infectious disease physicians, genomic epidemiologists and bioinformaticians.\u0026nbsp;Themes covered in interviews with PHL personnel include:\u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eProcesses of receiving samples from clinical laboratories, including decisions regarding which samples are prioritised for sequencing and coordination of sample transfer.\u003c/li\u003e\n \u003cli\u003e‘Future-proofing’ practices to ensure the future useability of isolates and sequence data, including adequate documentation of sample selection and how particular isolates are isolated, cultured, and maintained\u003c/li\u003e\n \u003cli\u003eIssues regarding changes to and levels of satisfaction with workflow processes including managing staff fatigue, training of staff in new processes and ensuring redundancy in laboratory systems;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAgreements in place regarding data sharing and rights to access and satisfaction with such agreements;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMechanisms in place to facilitate data archiving, tracking, tracing, and sharing and satisfaction with these mechanisms;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePerceived level of articulation between genomic and epidemiological investigations and the approaches by which this is achieved;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePerceptions of genomic epidemiologists and bioinformaticians regarding their own understanding of the needs of end users;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSustainability of increases in capacity developed through the COVID-19 pandemic; and\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLessons learned and applicability for future pandemic preparedness.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eInterviews held with AusTrakka stakeholders included bioinformaticians from PHLs responsible for uploading and/or accessing AusTrakka data, members of the National Analysis Team and AusTrakka developers. \u0026nbsp;These interviews explored the following themes:\u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003ePerspectives of various participants with respect to the expected outcomes from AusTrakka and reasons for participation (or reluctance to participate);\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRelevant ELSI and how they are managed;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eIssues of data ownership;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDecision-making processes in relation to governance structures and data-sharing agreements;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDecisions and criteria regarding selection of genomic and metadata for upload;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTechnical issues in providing or accessing AusTrakka data;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eChanges in how AusTrakka has been used throughout the pandemic;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSustainability of AusTrakka and further development; and\u003c/li\u003e\n \u003cli\u003eUtilisation of AusTrakka for pathogens other than SARS-CoV-2.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eKey informant interviews with genomic data end users were held to assess the perspectives of stakeholders regarding the acceptability, usefulness and sustainability of pathogen genomics in the COVID-19 response. \u0026nbsp; These interviews explored:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eReporting agreements and processes in place to communicate SARS-CoV-2 genomic data to end users and satisfaction with these;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePerceptions of end users’ own understanding of the uses and limitations of microbial genomics;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePerceptions of bioinformaticians’ and genomic epidemiologists’ understanding of end user information needs in relation to SARS-CoV-2 genomic data;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePerceived appropriateness of reporting and communication processes;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePerceived utility and risks of pathogen genomics in the COVID-19 response;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe use of pathogen genomics in public health decision-making, including perceived confidence in making decisions based on the information provided;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWhich samples are likely to be identified as a high priority for sequencing and why;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eImplications of selective sequencing strategies for utility in public health decision-making;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTechnical issues in accessing AusTrakka data;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eImpetus and anticipated benefit from utilising AusTrakka data;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eApplication of AusTrakka data and utility in public health decision-making; and\u003c/li\u003e\n \u003cli\u003eLessons learned through the pandemic and applicability for other pathogens.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eQualitative one-on-one interviews were conducted virtually by two research team members (ASF, DE). In 2020, 24 interviews were conducted with Victorian key informants given the impact of the pandemic primarily in Victoria at the time. In 2021, 24 individual interviews and 3 group interviews (with 31 participants in total) were held across seven Australian jurisdictions and New Zealand. In 2022, 5 interviews and 5 group interviews (with 18 participants in total) were held. \u0026nbsp;Some 2021 and 2022 interviews included follow-up discussions from previous years. \u0026nbsp; Interviews lasted between 45 minutes and 1 hour 15 minutes. Interviews were audio recorded and notes taken during the interviews. \u0026nbsp;Participants were given the opportunity to review their transcripts to ensure completeness and accurately, and were able to provide corrections or additional information.\u003c/p\u003e\n\u003cp\u003eKey informants were approached due to their positions held and their involvement in the COVID-19 response. \u0026nbsp;Participants were also asked to identify any additional relevant key informants. \u0026nbsp;Initial contact was via email. \u0026nbsp;While the majority of key informants agreed to participate in the research, there were some that were not available due to the intensity of competing demands on their time during the research period. \u0026nbsp;Recruitment continued until key informants in relevant positions were identified across all jurisdictions.\u003c/p\u003e\n\u003cp\u003eKey informants included:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eRepresentatives from the CDGN\u003c/li\u003e\n \u003cli\u003ePHL staff (bioinformaticians, genomic scientists, genomic epidemiologists)\u003c/li\u003e\n \u003cli\u003eAusTrakka team members (NAT, Development Team)\u003c/li\u003e\n \u003cli\u003eAusTrakka stakeholders (user groups,\u0026nbsp;end users (government, public health units (PHUs), clinicians))\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eTwo authors (ASF and DE) conducted the interviews. \u0026nbsp;ASF (PhD, female) is the lead researcher and holds an Academic Specialist position. \u0026nbsp;DE (MPH, female) conducted interviews in the role of Research Assistant. \u0026nbsp;Both interviewers have had training and extensive experience in conducting interviews and qualitative research. \u0026nbsp;Interviewers did not have knowledge or relationships prior to study commencement.\u003c/p\u003e\n\u003cp\u003eIn 2020 and 2021, upon request, the AusTrakka NAT provided ongoing monthly national reports and weekly SARS-CoV-2 VoC reports to support multijurisdictional outbreak investigations. \u0026nbsp;These reports were examined with regards to intended audience, application and information included.\u003c/p\u003e\n\u003cp\u003eAnalysis was underpinned by the relevant attributes outlined in the US CDC’s \u003cem\u003eUpdated Guidelines for Evaluating Public Health Surveillance Systems\u0026nbsp;\u003c/em\u003e(the Guidelines). \u0026nbsp;Given the evaluation’s focus on the contribution of AusTrakka to public health surveillance and response to COVID-19, technical attributes of the system were not assessed. \u0026nbsp;The elements of \u003cem\u003eSimplicity\u003c/em\u003e (the simplicity of the surveillance system’s structure and ease of operations) and \u003cem\u003eStability\u003c/em\u003e (a system’s ability to collect, manage, and provide data properly without failure and ability to be operational when needed) were therefore not included. \u0026nbsp;\u003cem\u003ePredictive Positive Value\u003c/em\u003e (the proportion of reported cases that actually have the health-related event under surveillance) is not relevant to pathogen genomics and has also been excluded.\u003c/p\u003e\n\u003cp\u003eQualitative coding was undertaken by ASF using NVivo13. \u0026nbsp; Codes were developed a priori based on the structure of the relevant attributes from the Guidelines.\u003c/p\u003e\n\u003cp\u003eEthical approval to conduct this study was obtained from the University of Melbourne Biomedical Sciences Human Ethics Advisory Group (ID: 2056426.1).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eUsefulness\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eGuidelines\u003c/em\u003e consider a public health surveillance system to be useful if it \u0026lsquo;contributes to the prevention and control of adverse health-related events, including an improved understanding of the public health implications of such events\u0026rsquo;. Since it became operational in May 2020, AusTrakka provided a centralised platform to enable interjurisdictional data sharing. Sharing sequence and metadata across jurisdictions was used to facilitate investigation of multi-jurisdictional outbreaks and clarify transmission chains during the period when preventing interjurisdictional transmission was a key public health focus.\u003c/p\u003e \u003cp\u003eAusTrakka began to be used with increasing functionality in July to August 2020. Until this point, comparison of genomic data between jurisdictions was mainly undertaken using publicly available data or by sharing data via e-mail or file sharing. The additional analytical capability provided by AusTrakka was seen to be particularly important for those jurisdictions that had limited local capacity.\u003c/p\u003e \u003cp\u003eIn 2021, AusTrakka end users from PHLs indicated that they used AusTrakka regularly to situate their own local sequences within the national context and highlighted the utility of centralising jurisdictional data.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003e\u0026hellip;it's important to have the national sort of samples because initially at the time when the first COVID happened we only have\u0026hellip; 200 cases and they're all from all sorts of different places, or different areas. So in order to trace particular cases or clusters is a bit tricky \u0026hellip; So it's always important to consolidate everything that we have into a single repository, and that\u0026rsquo;s where AusTrakka comes in\u0026hellip;\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhen end users were asked about the reason for their AusTrakka use over 2020 and 2021, the most common response across a number of settings was for confirming or rejecting a hypothesis regarding transmission that had been developed from the epidemiological data or providing additional clarity about transmission where there was limited epidemiological information available.\u003c/p\u003e \u003cp\u003eIn 2022, the utilisation of AusTrakka focused on VoC surveillance in response to the public health demand at the time. While to date, the direct public health impacts of VoC surveillance are uncertain, this was particularly important for communication and understanding the distribution of variants in the population, as well as monitoring the possibility of emerging strains that may exhibit increase public health risks.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eThe first fear was, you know, a new variant of concern\u0026hellip; suddenly another variant starts to take over there\u0026rsquo;s this worry, is this going to be worse? \u0026hellip; Will it be resistant to drugs? Will it \u0026hellip; be a more severe disease?\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eA key use of AusTrakka in the COVID-19 pandemic was in providing access to data and reports which increased confidence in public health approaches. The interviewee below speaks on demonstrating that lockdowns were effective in preventing transmission, which led to increased confidence in continuing to use this strategy to control outbreaks.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eBy the time we get to that point we don\u0026rsquo;t need that link \u0026ndash; it\u0026rsquo;s not going to change anything we do, it just provides a bit of reassurance\u0026hellip;\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn addition, the genomic findings had value in being able to provide accurate advice regarding VoCs to national bodies and provide context for data interpretation with regards to jurisdictional sequencing strategies.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eSo it\u0026rsquo;s been a very invaluable process to be able to see what is going on, particularly because we have to provide a lot of advice higher up\u0026hellip;and it\u0026rsquo;s helped the confidence of the advice in that we do actually understand what is going on nationally.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn addition to individual users within jurisdictions using AusTrakka to identify interjurisdictional transmission, the AusTrakka NAT regularly produced national-level reports, including monthly Communicable Diseases Intelligence reports for COVID-19 and monthly AusTrakka SARS-CoV-2 national genomics surveillance reports. AusTrakka reports were helpful in providing up-to-date data used in briefings and public-facing sessions, facilitating appropriate public communication both internally and externally, nationally and internationally.\u003c/p\u003e \u003cp\u003eAcceptability\u003c/p\u003e \u003cp\u003e \u003cem\u003eAcceptability\u003c/em\u003e is characterised as the \u0026lsquo;willingness of persons and organizations to participate in the surveillance system\u0026rsquo; (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The anticipated need for efficient sequence data sharing to inform the pandemic response prompted further development and operationalisation of AusTrakka in the early stages of the COVID-19 pandemic. As the interviewee below outlines, AusTrakka is comprised of three key components: 1) the open-data sharing philosophy underpinning its development 2) the established data governance between stakeholders 3) the accessibility useability of the platform itself. Developing these three elements were shown to be central to the acceptability of AusTrakka.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eI think it\u0026rsquo;s fair to say AusTrakka is kind of three different things, it's\u0026hellip; the data sharing philosophy\u0026hellip; there's the web platform\u0026hellip;itself which enables the interaction sharing of the data, and then there's sort of the governance and all the agreements behind it. And although the platform only exists now, the philosophy was there, and then quite a few years were spent getting this data sharing agreement up over many years\u0026hellip;the philosophy was always there, the data sharing took years of groundwork\u0026hellip;\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eOpen Science principles around data sharing were central to the design and implementation of AusTrakka. Underpinning this philosophy of open data sharing was the presence of established governance between all stakeholders and a governance framework to ensure responsible data-sharing practices.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e...\u003cem\u003eI think that if we had had a team that wasn\u0026rsquo;t as conscious of their legal responsibilities, if data breaches had occurred, or if there had been any leakage, it would\u0026rsquo;ve posed a problem. So I think the information security side has been good, that\u0026rsquo;s provided a sense of trust.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWillingness to participate is indicated by an increase in the number of users and contributing jurisdictions over time. As of October 2022, there were 76 active users across 12 individual organisations with access to the AusTrakka platform. Within two months of the launch of AusTrakka, there were active users from each of Australia\u0026rsquo;s jurisdictions and New Zealand, showing that the platform was adopted quickly. Over the initial three months, the numbers of users grew at an average of 10 new users per month and by the end of 2020 most jurisdictions had at least four end users (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe next section describes in more detail the willingness of users to contribute sequence data to the system.\u003c/p\u003e \u003cp\u003eRepresentativeness and sensitivity\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eRepresentativeness\u003c/em\u003e of a system is the extent to which it \u0026lsquo;accurately describes the occurrence of a health-related event over time and its distribution in the population by place and person.\u0026rsquo; \u003cem\u003eSensitivity\u003c/em\u003e refers to the proportion of cases of a disease detected by the surveillance system and the ability of the system to detect outbreaks and monitor changes in the number of cases over time. The representativeness and sensitivity of AusTrakka relies on the consistent generation and contribution of sequences from across jurisdictions.\u003c/p\u003e \u003cp\u003eAs of October 2022, a total of 166 083 SARS-CoV-2 sequences from Australia and New Zealand were available through AusTrakka. In this time, 1735 phylogenetic trees were made available to end users. The total number of sequences uploaded mirrored growing case totals in Australia and New Zealand throughout the second wave in Victoria in July 2020, the Delta outbreak in New South Wales (NSW) and Victoria from July/August 2021 and the start of the Omicron outbreak in December 2021. Following this we see the number of uploaded sequences remaining high throughout 2022 with peaks in April and July where over 2500 sequences were uploaded in a single week. Each of these peaks was primarily driven by large number of uploads from an individual organisation and jurisdiction (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A Spearman's correlation test was run to determine the relationship between reported weekly COVID-19 cases and weekly sequence uploads to AusTrakka. The test showed a strong, positive monotonic correlation and association between COVID-19 case numbers and sequence uploads (R\u0026thinsp;=\u0026thinsp;0.697, 95% CI (0.604\u0026ndash;0.772), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBy the end of 2021, a total of 53,285 SARS-CoV-2 sequences were uploaded to AusTrakka by PHLs, at an average rate of 500 sequences uploaded per week. Additionally, 535 phylogenetic trees were made available to users\u0026mdash;174 between June 2020 and June 2021 and 361 between July and December 2021. In the first 10 months alone of 2022 112,798 sequences were uploaded to AusTrakka at an average rate of 2,700 sequences uploaded per week. During this time, 1,200 phylogenetic trees were made available at an average rate of 30 tree accesses per week (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e below shows clear peak of tree image loads in June and July 2021 of 60\u0026ndash;87 weekly loads respectively, which correlates with rising cases at this time. In total there are 1,204 tree data loads recorded in 2021 with an average of approximately 38 loads per week in this time. Utilisation begins to increase again towards the end of 2021 as case totals related to the Omicron variant surge. Throughout 2022 the number of tree data loads declines despite rising case numbers as contact tracing efforts and social restrictions begin to be rolled back in multiple jurisdictions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSimilarly to the tree uploads there is a peak of use in June 2021 of 22 VoC weekly loads. From May 2021 until December 2021 there are 230 VoC summary table views which is approximately eight views per week throughout the year. However, unlike the number of tree loads, which declines over 2022, VoC table views remain high, indicating continued use (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFrom early 2022, with opening of the international borders and the increasing use of Rapid Antigen Testing (RAT), there was a shift in how AusTrakka was utilised in the public health response to SARS-CoV-2.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eWith the sheer number of COVID cases now, AusTrakka is less representative through no fault of its own just the sheer number of cases and the prevalence of \u0026hellip; RATs which you can't sequence from and a shift in the \u0026hellip; sequencing priorities from the jurisdictions \u0026hellip;and so the focus of AusTrakka has shifted to more of a variant surveillance platform.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThis shift in priorities throughout the pandemic led to lowered rates of direct user engagement with AusTrakka alongside a continued high level of interest in and utilisation of AusTrakka reports, particularly in relation to VoC identification.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eAt the moment we are providing particularly focussed on there\u0026rsquo;s a really great graphic in the VOC report that actually goes up to the health minister weekly so that\u0026rsquo;s on the variants \u0026hellip; and then of course the information does filter through to the weekly surveillance reports that get developed at the national level.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eTimeliness\u003c/p\u003e \u003cp\u003e\u003cem\u003eTimeliness\u003c/em\u003e according to the \u003cem\u003eGuidelines\u003c/em\u003e \u0026lsquo;reflects the speed between steps in a public health surveillance system\u0026rsquo;. While interviewees generally agreed that having access to genomic data through AusTrakka was useful in confirming or discarding these hypotheses, the majority also indicated that genomic data was typically not available quickly enough to inform the day-to-day response to COVID-19.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cem\u003e\u0026hellip;on a day-to-day basis it doesn\u0026rsquo;t actually make a huge impact, we\u0026rsquo;re responding very rapidly as you would understand and need to respond rapidly within 24 hours of identifying a case in terms of managing the case, and identifying their close contacts, so obviously in relation to those close contacts it has no impact, but and also in relation to outbreaks when our outbreak management is very much based on epidemiological data\u003c/em\u003e\u0026hellip;\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eData quality\u003c/p\u003e \u003cp\u003eThe Guidelines state that \u0026lsquo;\u003cem\u003eData quality\u003c/em\u003e reflects the completeness and validity of the data recorded in the public health surveillance system\u0026rsquo;. The importance of the relationships between PHLs and PHUs in relation to ensuring pathogen genomic data quality and the articulation between epidemiological and genomic data was a recurring theme in the interviews. There was an understanding that the power of genomic data lies in its use alongside epidemiological data, and interviewees were consistent in expressing a need for routine articulation to derive the most benefit from genomic data.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cem\u003eBut I think the other really important thing that I have learnt is that you do have to line it up with the epidemiology and what you get from basic interviewing, you know like with the ICU people had we not known that they were married we would\u0026rsquo;ve said they were separate, completely separate subtypes. So yeah I think correlating it with your epi is really important.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhile some interviewees indicated that this was normally done well, others expressed concern that there were times that incorrect conclusions were drawn due to insufficient contextualisation from epidemiological data.\u003c/p\u003e \u003cp\u003eThe collaborative nature of the work also brought with it significant challenges in managing data across organisations, which was repeatedly mentioned throughout the research. While the following quote comes from the earlier days of the pandemic, subsequent interviews indicated that there have been minimal improvements to data management.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eAnd I think one of the hardest things has actually been data management\u0026hellip; we\u0026rsquo;re getting information from at least six different sources\u0026hellip; a lot of privacy issues means it\u0026rsquo;s hard to match things up\u0026hellip;trying to coordinate that has been a bit of a nightmare.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eSome interviewees indicated that the COVID-19 epidemic presented a unique opportunity to create viable structures to enable stronger integration.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003e\u0026hellip;the main thing I would like to see coming out of this is an extension to the way genomic and epidemiological data are integrated and speed and efficiency with which intelligence can be gathered by their integration. That\u0026rsquo;s what I\u0026rsquo;d really love to come out of this. And we\u0026rsquo;ve got that opportunity now\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eFlexibility\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eFlexibility\u003c/em\u003e of a public health surveillance system is based on its ability to \u0026lsquo;adapt to changing information needs or operating conditions with little additional time, personnel, or allocated funds\u0026rsquo;. While AusTrakka was rapidly developed during the COVID-19 pandemic and focused on SARS-CoV-2, interviewees indicated that the genomics infrastructure developed in response to COVID-19 was largely applicable to other pathogens. A key development to facilitate and simplify data-sharing moving forward has been a shift towards \u0026lsquo;pathogen agnostic\u0026rsquo; governance frameworks which support the broader application of pathogen genomics.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eWhat has changed is\u0026hellip;we had pathogen-specific data governance but now because we were working with COVID mainly and we had started branching out to some other pathogens but now that we are starting to take a lot more pathogens and... we have now shifted to a pathogen agnostic framework which has the same principles it\u0026rsquo;s just that it covers all of the pathogens.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhile there has been a move towards data-sharing agreements that cover all pathogens, participants also indicated that elements such as minimum metadata requirements would need to be established on a per-pathogen basis. In line with this approach, \u0026lsquo;AusTrakka 2\u0026rsquo; has been developed to be pathogen agnostic.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eAusTrakka 1 really was set up in a hurry for COVID \u0026hellip;.AusTrakka 2 is set up in a much more generic way, so we can put in different proformas for different fields are expected and they're validated and we have to supply that metadata if you are putting it in through that system, all the metadata can be kind of checked against one another in a consistent way and the permissions can be set up and done properly.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThere are several possible and developing applications where capacity could be strengthened to increase the benefit of pathogen genomics in the control of COVID-19 and future preparedness. While still in the early stages, there is scope for AusTrakka to potentially be used more broadly to enable access to genomic data across a variety of organisations in human health.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eI think well there will be two main potential clients \u0026ndash; one would be hospitals and the other ones would be labs more generally. So in the hospital a lot of it will come through the micro lab, but I think we\u0026rsquo;re kind of viewing this as a pilot for how AusTrakka or a similar platform can be used to communicate genomic data to hospitals and health systems and labs\u0026hellip;.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eInterviewees referred to other communicable diseases and the potential benefits of the AusTrakka platform evolving as a One Health tool.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eWe also now see that outside of the context of COVID-19, the AusTrakka model is going to be useful for so many other communicable diseases. So currently Monkeypox, but also Japanese Encephalitis, and the really important thing about Japanese Encephalitis is that we have an opportunity for AusTrakka to bridge the boundaries of human health and to evolve into a One Health tool.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAusTrakka performance against elements of public health surveillance system quality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElements of surveillance quality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAusTrakka performance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImpact of element\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUsefulness: contributes to the prevention and control of adverse health-related events, including an improved understanding of the public health implications of such events\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Provided a centralised platform to enable interjurisdictional data sharing\u003c/p\u003e \u003cp\u003e\u0026bull; Shift over the course of the pandemic from identifying transmission networks towards VoC surveillance\u003c/p\u003e \u003cp\u003e\u0026bull; Provided centralised access to jurisdictional and national-level data and reports\u003c/p\u003e \u003cp\u003e\u0026bull; Provided advice to national bodies and context for data interpretation\u003c/p\u003e \u003cp\u003e\u0026bull; End users used centralised data to situate their own local sequences within the national context\u003c/p\u003e \u003cp\u003e\u0026bull; Provided up-to-date data used in briefings and public-facing sessions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026bull; Shared sequence and metadata were used to facilitate investigation of outbreaks and clarify transmission chains to inform prevention of interjurisdictional transmission\u003c/p\u003e \u003cp\u003e\u0026bull; Availability of data and reports increased confidence in public health approaches, including large-scale lockdowns to prevent transmission\u003c/p\u003e \u003cp\u003e\u0026bull; Improved communication and understanding distribution of variants in the population and contributed to monitoring emerging strains that may increase public health risks\u003c/p\u003e \u003cp\u003e\u0026bull; Facilitated appropriate public communication both internally and externally, nationally and internationally\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlexibility: able to adapt to changing information needs or operating conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; AusTrakka was limited to SARS-CoV-2 data, but infrastructure is largely applicable to other pathogens\u003c/p\u003e \u003cp\u003e\u0026bull; AusTrakka 2 has been developed to be pathogen agnostic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026bull; The establishment of AusTrakka facilitated a shift towards \u0026lsquo;pathogen agnostic\u0026rsquo; governance frameworks which support the broader application of pathogen genomics.\u003c/p\u003e \u003cp\u003e\u0026bull; Scope for AusTrakka to enable access to genomic data across a variety of health organisations\u003c/p\u003e \u003cp\u003e\u0026bull; Potential of AusTrakka evolving as a One Health tool\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData quality: completeness and validity of the data recorded in the public health surveillance system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Relationships between PHLs and PHUs crucial to ensuring pathogen genomic data quality and articulation between epidemiological and genomic data\u003c/p\u003e \u003cp\u003e\u0026bull; Challenges in managing data across organisations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026bull; Concern regarding incorrect conclusions due to insufficient contextualisation from epidemiological data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcceptability: willingness of persons and organisations to participate in the surveillance system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; AusTrakka is underpinned by established governance between all stakeholders and a framework to ensure responsible data-sharing practices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026bull; Established data governance by stakeholders was shown to be central to the acceptability of AusTrakka\u003c/p\u003e \u003cp\u003e\u0026bull; Quick uptake across jurisdictions at the beginning of the pandemic\u003c/p\u003e \u003cp\u003e\u0026bull; Steady increase in number of users and organisations contributing to AusTrakka from mid-2020 to 2022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensitivity: at the level of case reporting, the proportion of cases of a disease detected by the surveillance system; also, the ability to detect outbreaks and monitor changes in the number of cases over time\u003c/p\u003e \u003cp\u003eRepresentativeness: ability to accurately describe the occurrence of a condition over time and its distribution in the population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Strong positive correlation and association between COVID-19 case numbers and sequence uploads\u003c/p\u003e \u003cp\u003e\u0026bull; Shift in priorities throughout the pandemic led to lower rates of direct user engagement with AusTrakka alongside a continued high level of interest in and utilisation of AusTrakka reports, particularly in relation to VoC identification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026bull; Tree image views correlates with rising cases\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTimeliness: the speed between steps in a surveillance system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Genomic data generally not available within a timeframe to inform day-to-day decision-making or case management\u003c/p\u003e \u003cp\u003e\u0026bull; AusTrakka supported access to data that was used to confirm or discard hypotheses regarding transmission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026bull; Genomic data was used to support broader outbreak management and clarify transmission chains\u003c/p\u003e \u003cp\u003e\u0026bull; Availability of data and reports increased confidence in public health approaches, including large-scale lockdowns to prevent transmission\u003c/p\u003e \u003cp\u003e\u0026bull; Facilitated appropriate public communication both internally and externally, nationally and internationally\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWhole genome sequencing has proven to be a revolutionary technology, and one that has been increasingly embedded into public health responses to current communicable disease threats and planning for future epidemic and pandemic preparedness. With sequencing capacity continuing to increase, there is a need for ongoing evaluation of pathogen genomics surveillance systems both to ensure functionality and to understand and incorporate elements of pathogen genomics-informed surveillance systems that contribute to public health outcomes.\u003c/p\u003e \u003cp\u003eThe development and implementation of AusTrakka in the early stages of the COVID-19 pandemic in Australia allowed for centralised and efficient inter-jurisdictional sharing of sequences, as well as epidemiological and sequence metadata, which previously did not exist. This facilitated jurisdictional and national understanding of transmission events and outbreaks, and informed population-level public health responses. Over the period 2020 to 2022, the COVID-19 pandemic changed enormously and throughout this time, the use of AusTrakka in the public health response also shifted.\u003c/p\u003e \u003cp\u003eThe high \u003cem\u003eAcceptability\u003c/em\u003e (willingness of persons and organisations to participate) of AusTrakka was predicated on the governance mechanisms which were collectively established by stakeholders across Australian jurisdictions. Having national-level coordination and governance of AusTrakka was an important factor both in facilitating the development of the platform and in ensuring continued trust and buy-in. The central role played by end users in the design led to rapid adoption across jurisdictions, which then supported robust sequence uploads and increased \u003cem\u003eRepresentativeness\u003c/em\u003e (ability to accurately describe the occurrence of a health-related event over time) and \u003cem\u003eSensitivity\u003c/em\u003e (proportion of cases detected by a surveillance system and the ability to detect outbreaks).\u003c/p\u003e \u003cp\u003eIntegration between epidemiological and genomic data was identified as an ongoing challenge to the \u003cem\u003eData quality\u003c/em\u003e system attribute. The importance of a platform capable of harmonising data from multiple source and linking genomic data with epidemiological data was clearly demonstrated. The integration of epidemiological and genomic data was shown to have two key elements, first, the integration of data systems to facilitate increased data sharing or access to data and second, working relationships and human capacity to understand and utilise genomic and epidemiological data appropriately. While having access to genomic and epidemiological data is one part of an effective system, data needs to be coupled with analysis through effective communication among those who are contributing to the decision-making process. This supports the need for integrated national pathogen genomics surveillance platforms such as AusTrakka alongside ongoing training, capacity building and strong communication to enhance its public health utility.\u003c/p\u003e \u003cp\u003eImplications for development of pathogen genomics-informed surveillance systems\u003c/p\u003e\n\u003ch3\u003eExplicit consideration of surveillance system quality criteria and ongoing evaluation\u003c/h3\u003e\n\u003cp\u003eThe evaluation of AusTrakka makes clear how supporting criteria of surveillance quality facilitates system use and impact. Ongoing monitoring and evaluation is essential to ensure that the fundamental changes to surveillance systems enacted by the introduction of pathogen genomics (e.g. changes in data generation, governance and sharing; reporting and communication; and use of genomic data in public health implementation) are undertaken in ways that provide increased utility to users and contribute to public health outcomes (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Consideration of these factors and how to ensure they are represented in the system should be undertaken in the early stages of planning, establishment and integration of public health pathogen genomics. Frameworks to support evaluation of pathogen genomics-informed surveillance systems have been adapted from established guidelines to evaluate surveillance systems (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e); use of these frameworks to guide development and implementation will support in-depth understanding of how well the system is functioning, identification of expected and unexpected impacts and early and ongoing identification of appropriate targets for system strengthening. This will be particularly relevant as use of pathogen genomics continues to expand and be used in novel approaches, such as in the development of One Health surveillance systems and integration of metagenomics.\u003c/p\u003e\n\u003ch3\u003eStrong governance and engagement\u003c/h3\u003e\n\u003cp\u003eThe experience of AusTrakka during the COVID-19 pandemic illustrates the centrality of the \u003cem\u003eAcceptability\u003c/em\u003e criterion in responding to the \u003cem\u003eUsefulness\u003c/em\u003e, \u003cem\u003eRepresentativeness\u003c/em\u003e and \u003cem\u003eSensitivity\u003c/em\u003e criteria; that is, buy-in, engagement and trust was essential to the functionality of AusTrakka. This is reinforced by the emphasis placed on national leadership, ownership and commitment by the \u003cem\u003eWHO guidance for developing national genomic surveillance\u003c/em\u003e (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, this engagement must be multi-level, rather than resting solely at the national level, and include representation from sub-national and organisational levels that generate and use pathogen genomic data. This includes PHLs, policymakers, PHUs, donors and implementing partners. Coordination across these stakeholders from the early stages facilitates a shared understanding of the purpose and benefits from the integration of pathogen genomics in surveillance systems, as well as the contribution and roles of each. Given the ongoing evolution in application of pathogen genomics, this ongoing coordination and engagement is also necessary to support adaptability and sustainability of the system.\u003c/p\u003e\n\u003ch3\u003eData quality and harmonisation\u003c/h3\u003e\n\u003cp\u003eSequence data must be appropriately contextualised in order to be useful for public health purposes. This necessitates the harmonisation of data from different sources; however, this is a recognised challenge as laboratories, public repositories, international agencies, hospitals and other data sources may use different standards, formats and methods for collection and organisation of data. Approaches such as the Public Health Alliance for Genomic Epidemiology (PHA4GE) contextual data standard aim to address these challenges (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e); development of the AusTrakka COVID-19 pro forma was based on the PHA4GE data standards for international consistency. Within Australia, programs such as AusPathoGen (a translational research program funded by the Medical Research Future Fund) are now providing evidence towards a best-practice national approach and strengthening capacity to coordinating the genomics experts across Australia to harmonise the implementation of pathogen genomics within Australia\u0026rsquo;s health system (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Data standardisation, particularly through bioinformatics analysis proved to be a key driver in generating consistency across jurisdictions in the reporting and communication of genomics surveillance outputs.\u003c/p\u003e \u003cp\u003eData harmonisation may also be facilitated through the development of a centralised approach to data management and sharing (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) and establishment of a centralised platform for data sharing such as AusTrakka can facilitate and be an impetus for coordinated data harmonisation at multiple levels. In developing the future iterations of AusTrakka, a focus on consistency and alignment with both national and international data standards will be required to ensure ease of use of the platform. Furthermore, interoperability or harmonisation of the platform to existing surveillance systems at both a subnational and national level will assist with potential issues in resourcing or capacity that may arise in a post-pandemic environment where investment in pathogen genomics will not be at the same scale.\u003c/p\u003e \u003cp\u003eAusTrakka provides a semi-open environment that adopts the FAIR (Findability, Accessibility, Interoperability, and Reuse of digital assets) data principles that states that data should be \u0026lsquo;as open as possible, and as closed as necessary\u0026rsquo; (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In the public health environment, whilst the generation of pathogen genomic data is being implemented widely across the world, the analysis, interpretation and implementation into data for action is still an emerging field in many countries. Particularly during the COVID-19 pandemic, which experienced a rise in misinformation and disinformation, AusTrakka provided a secure environment that allowed for the rapid data sharing between PHLs that provided public health decision makers with a centralised capacity for a coordinated and consistent approach to understanding the genomics landscape during this critical time.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWhole genome sequencing is a transformative technology that has been increasingly integrated into public health responses to communicable diseases. The development and implementation of AusTrakka in the early stages of the COVID-19 pandemic in Australia allowed for centralised and efficient inter-jurisdictional sharing of sequences, as well as epidemiological and sequence metadata. The experience of AusTrakka highlights the importance of robust governance on the willingness of persons and organisations to contribute and participate. This engagement and adoption is fundamental to the effectiveness, representativeness and sensitivity of the system. With public health sequencing capacity continuing to increase, there is a need for ongoing evaluation of pathogen genomics surveillance systems both to ensure functionality and to understand and incorporate elements of pathogen genomics-informed surveillance systems that contribute to public health outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval to conduct this study was obtained from the University of Melbourne Biomedical Sciences Human Ethics Advisory Group (HEAG) (Application ID: 2056426.1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsent for publication was obtained from all participants in line with ethical approval from the University of Melbourne HEAG.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data generated and analysed during the current study are not publicly available due to reasons of confidentiality and privacy but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are employed at the organisation that has received funding for development of the AusTrakka platform. The authors are not directly involved in this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the National Health and Medical Research Council (NHMRC) through the Medical Research Future Fund (MRFF) – Coronavirus Research Response: 2020 Tracking COVID-19 in Australia using Genomics Grant Opportunity (MRF9200006).\u003c/p\u003e\n\u003cp\u003eAusTrakka is supported by the Australian Government Department of Health, Disability and Ageing (the Department). The opinions expressed in this publication are those of the authors, and do not necessarily represent the views of the Department.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eASF conceptualised the research. \u0026nbsp;ASF and CME drafted the initial manuscript. \u0026nbsp;All authors have had the opportunity to review and approve the manuscript before submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBlack A, MacCannell DR, Sibley TR, Bedford T. Ten recommendations for supporting open pathogen genomic analysis in public health. Nature Medicine. 2020;26(6):832-41.\u003c/li\u003e\n \u003cli\u003eAllard MW, Strain E, Melka D, Bunning K, Musser SM, Brown EW, et al. Practical Value of Food Pathogen Traceability through Building a Whole-Genome Sequencing Network and Database. J Clin Microbiol. 2016;54(8):1975-83.\u003c/li\u003e\n \u003cli\u003eChattaway MA, Dallman TJ, Larkin L, Nair S, McCormick J, Mikhail A, et al. The Transformation of Reference Microbiology Methods and Surveillance for Salmonella With the Use of Whole Genome Sequencing in England and Wales. Frontiers in Public Health. 2019;7.\u003c/li\u003e\n \u003cli\u003eRevez J, Espinosa L, Albiger B, Leitmeyer KC, Struelens MJ. Survey on the Use of Whole-Genome Sequencing for Infectious Diseases Surveillance: Rapid Expansion of European National Capacities, 2015-2016. Front Public Health. 2017;5:347.\u003c/li\u003e\n \u003cli\u003eKwong JC, Mercoulia K, Tomita T, Easton M, Li HY, Bulach DM, et al. Prospective Whole-Genome Sequencing Enhances National Surveillance of Listeria monocytogenes. J Clin Microbiol. 2016;54(2):333-42.\u003c/li\u003e\n \u003cli\u003eAustralian Government Department of Health and Aged Care. National Microbial Genomics Framework. Canberra; 2019.\u003c/li\u003e\n \u003cli\u003eFerdinand AS, Kelaher M, Lane CR, da Silva AG, Sherry NL, Ballard SA, et al. An implementation science approach to evaluating pathogen whole genome sequencing in public health. Genome Med. 2021;13(1):121.\u003c/li\u003e\n \u003cli\u003eAlleweldt F, Kara Ş, Best K, Aarestrup FM, Beer M, Bestebroer TM, et al. Economic evaluation of whole genome sequencing for pathogen identification and surveillance - results of case studies in Europe and the Americas 2016 to 2019. Euro Surveill. 2021;26(9).\u003c/li\u003e\n \u003cli\u003eTran M, Smurthwaite KS, Nghiem S, Cribb DM, Zahedi A, Ferdinand AD, et al. Economic evaluations of whole-genome sequencing for pathogen identification in public health surveillance and health-care-associated infections: a systematic review. Lancet Microbe. 2023;4(11):e953-e62.\u003c/li\u003e\n \u003cli\u003eScharff RL, Besser J, Sharp DJ, Jones TF, Peter GS, Hedberg CW. An Economic Evaluation of PulseNet: A Network for Foodborne Disease Surveillance. Am J Prev Med. 2016;50(5 Suppl 1):S66-s73.\u003c/li\u003e\n \u003cli\u003eGuidelines Working Group. Updated Guidelines for Evaluating Public Health Surveillance Systems: United States Centers for Diseases Control; 2001 [Available from: https://www.cdc.gov/mmwr/preview/mmwrhtml/rr5013a1.htm.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. Communicable disease surveillance and response systems: Guide to monitoring and evaluating. World Health Organization; 2006.\u003c/li\u003e\n \u003cli\u003eHoang T, da Silva AG, Jennison AV, Williamson DA, Howden BP, Seemann T. AusTrakka: Fast-tracking nationalized genomics surveillance in response to the COVID-19 pandemic. Nature Communications. 2022;13(1):865.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. Global genomic surveillance strategy for pathogens with pandemic and epidemic potential, 2022\u0026ndash;2032. Geneva; 2022.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. Considerations for developing a national genomic surveillance strategy or action plan for pathogens with pandemic and epidemic potential. Geneva; 2023.\u003c/li\u003e\n \u003cli\u003eGriffiths EJ, Timme RE, Mendes CI, Page AJ, Alikhan NF, Fornika D, et al. Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package. Gigascience. 2022;11.\u003c/li\u003e\n \u003cli\u003eWebb JR, Andersson P, Sim E, Zahedi A, Donald A, Hoang T, et al. Implementing a national programme of pathogen genomics for public health: the Australian Pathogen Genomics Program (AusPathoGen). The Lancet Microbe. 2025;6(3).\u003c/li\u003e\n \u003cli\u003eGO FAIR. FAIR Principles [Available from: https://www.go-fair.org/fair-principles/.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-global-and-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Global and Public Health](https://bmcglobalpublichealth.biomedcentral.com/)","snPcode":"44263","submissionUrl":"https://submission.springernature.com/new-submission/44263/3","title":"BMC Global and Public Health","twitterHandle":"@BMC_GPH","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pathogen genomics, surveillance, public health, evaluation, COVID-19","lastPublishedDoi":"10.21203/rs.3.rs-6758871/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6758871/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePathogen genomics has increasingly been integrated into infectious disease surveillance, outbreak detection, and response globally. However, formal evaluation of pathogen genomic surveillance systems has been a major gap. Where evaluation has been undertaken, this has largely focused on economics, rather than assessing system attributes that contribute to the usefulness and acceptability of pathogen genomic surveillance systems.\u003c/p\u003e\n\u003cp\u003eIn Australia, the AusTrakka platform was established and deployed nationally to address barriers to genomic data sharing across jurisdictions, enhance interoperability and usability, and improve governance of public health genomic data. Here we present our evaluation of AusTrakka and examine how its utilisation and impact shifted throughout the COVID-19 pandemic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe utilised the United States’ Centers for Disease Control (CDC) Updated Guidelines for Evaluating Public Health Surveillance Systems to guide assessment of the AusTrakka platform. The evaluation used a mixed-methods approach consisting of a quantitative analysis of AusTrakka utilisation data throughout the COVID-19 pandemic and a qualitative component comprised of key informant interviews and analysis of investigation reports produced by the AusTrakka National Analysis Team.\u003c/p\u003e\n\u003cp\u003eSemi-structured individual and group interviews were held with key informants (n=63) representing all jurisdictions across Australia and New Zealand. These included individuals representing public health laboratories and health departments, infectious disease physicians, genomic epidemiologists and bioinformaticians.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEnd users reported that AusTrakka had a very high degree of usefulness as a centralised platform to enable sharing sequence data across jurisdictions, facilitate multijurisdictional outbreak investigations and clarifying transmission chains. \u003cem\u003eAcceptability\u003c/em\u003e was a key system that contributed to the usefulness of the platform, enhanced through collective design of data governance frameworks. Integration of epidemiological data with the pathogen genomic data was an ongoing challenge in data completeness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRobust evaluation of pathogen genomics surveillance systems is critical to identify contextual and system elements that impact the capacity of these systems to accomplish their objectives. Our findings demonstrate the importance of strong stakeholder engagement in developing data governance mechanisms for pathogen genomics in ultimately ensuring the capacity of surveillance systems to detect outbreaks and support public health utility, and reinforce the value of a nationally developed, purpose-built approach in Australia.\u003c/p\u003e","manuscriptTitle":"High acceptability of a national platform for public health genomic data sharing and surveillance in Australia: a mixed methods evaluation study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-02 05:01:06","doi":"10.21203/rs.3.rs-6758871/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-11T18:48:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-08T09:05:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-31T06:08:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"194841987531781390539931095115375894807","date":"2025-07-29T06:29:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"158038592065832206699055219694770732846","date":"2025-07-08T05:22:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-15T22:36:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201974254752510624386285444024348331478","date":"2025-06-15T17:08:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"119765065891693069942557504050296926380","date":"2025-05-29T16:14:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-29T15:58:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-28T06:26:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-28T06:19:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Global and Public Health","date":"2025-05-27T11:10:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-global-and-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Global and Public Health](https://bmcglobalpublichealth.biomedcentral.com/)","snPcode":"44263","submissionUrl":"https://submission.springernature.com/new-submission/44263/3","title":"BMC Global and Public Health","twitterHandle":"@BMC_GPH","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0122b606-bf53-47f8-8eca-efaa76becc49","owner":[],"postedDate":"June 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-26T20:10:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-02 05:01:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6758871","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6758871","identity":"rs-6758871","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}