CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.

The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded ß-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systematic curation of resistance-modifying agents. This expanded curation includes 180 new AMR gene families, 15 new drug classes, 1 new resistance mechanism, and two new ontological relationships: evolutionary_variant_of and is_small_molecule_inhibitor. In silico prediction of resistomes and prevalence statistics of ARGs has been expanded to 377 pathogens, 21,079 chromosomes, 2,662 genomic islands, 41,828 plasmids and 155,606 whole-genome shotgun assemblies, resulting in collation of 322,710 unique ARG allele sequences. New features include the CARD:Live collection of community submitted isolate resistome data and the introduction of standardized 15 character CARD Short Names for ARGs to support machine learning efforts.

First isolation and whole-genome sequencing of Trueperella abortisuis from a goat in Canada.

Objective: The present study reports the first isolation and whole-genome sequencing of a Trueperella abortisuis bacterium from a goat. Animals and sample: The T. abortisuis was isolated from the uterus of a goat following an abortion. Procedure: The T. abortisuis was identified by pure culture phenotype and MALDI-TOF analysis and further characterized by whole-genome sequencing. Results: This isolate was reliably identified as T. abortisuis and showed similar properties to type strain T. abortisuis DSM 19515T, which was recovered from a sow following an abortion. The assembled genome of this isolate was 2 564 866 bp long with a GC content of 63.9%. A total of 30 virulence-related genes were determined, suggesting the pathogenic potential of this organism. Conclusion and clinical relevance: This study details the first isolation of T. abortisuis from goats. The genotypic findings of this isolate will serve as a baseline description for any similar future studies.

Premier isolement et séquençage du génome entier de Trueperella abortisuis provenant d'une chèvre au Canada. Objectif: La présente étude rapporte le premier isolement et séquençage du génome entier d'un isolat de Trueperella abortisuis provenant d'une chèvre. Animaux et échantillon: Le T. abortisuis a été isolé de l'utérus d'une chèvre à la suite d'un avortement. Procédure: Le T. abortisuis a été identifié par un phénotype de culture pure et analyse par MALDI-TOF, puis caractérisé par séquençage du génome entier. Résultats: Cet isolat a été identifié de manière fiable comme étant T. abortisuis et a montré des propriétés similaires à la souche type T. abortisuis DSM 19515T, qui a été récupérée chez une truie après un avortement. Le génome assemblé de cet isolat mesurait 2 564 866 pb avec une teneur en GC de 63,9 %. Au total, 30 gènes liés à la virulence ont été déterminés, suggérant le potentiel pathogène de cet organisme. Conclusion et pertinence clinique: Cette étude détaille le premier isolement de T. abortisuis chez la chèvre. Les résultats génotypiques de cet isolat serviront de description de base pour toute étude future similaire.(Traduit par Dr Serge Messier).

ProbeTools: designing hybridization probes for targeted genomic sequencing of diverse and hypervariable viral taxa.

BACKGROUND: Sequencing viruses in many specimens is hindered by excessive background material from hosts, microbiota, and environmental organisms. Consequently, enrichment of target genomic material is necessary for practical high-throughput viral genome sequencing. Hybridization probes are widely used for enrichment in many fields, but their application to viral sequencing faces a major obstacle: it is difficult to design panels of probe oligo sequences that broadly target many viral taxa due to their rapid evolution, extensive diversity, and genetic hypervariability. To address this challenge, we created ProbeTools, a package of bioinformatic tools for generating effective viral capture panels, and for assessing coverage of target sequences by probe panel designs in silico. In this study, we validated ProbeTools by designing a panel of 3600 probes for subtyping the hypervariable haemagglutinin (HA) and neuraminidase (NA) genome segments of avian-origin influenza A viruses (AIVs). Using in silico assessment of AIV reference sequences and in vitro capture on egg-cultured viral isolates, we demonstrated effective performance by our custom AIV panel and ProbeTools' suitability for challenging viral probe design applications. RESULTS: Based on ProbeTool's in silico analysis, our panel provided broadly inclusive coverage of 14,772 HA and 11,967 NA reference sequences. For each reference sequence, we calculated the percentage of nucleotide positions covered by our panel in silico; 90% of HA and NA references sequences had at least 90.8 and 95.1% of their nucleotide positions covered respectively. We also observed effective in vitro capture on a representative collection of 23 egg-cultured AIVs that included isolates from wild birds, poultry, and humans and representatives from all HA and NA subtypes. Forty-two of forty-six HA and NA segments had over 98.3% of their nucleotide positions significantly enriched by our custom panel. These in vitro results were further used to validate ProbeTools' in silico coverage assessment algorithm; 89.2% of in silico predictions were concordant with in vitro results. CONCLUSIONS: ProbeTools generated an effective panel for subtyping AIVs that can be deployed for genomic surveillance, outbreak prevention, and pandemic preparedness. Effective probe design against hypervariable AIV targets also validated ProbeTools' design and coverage assessment algorithms, demonstrating their suitability for other challenging viral capture applications.

CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database.

The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD's Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.

Sequence database versioning for command line and Galaxy bioinformatics servers.

MOTIVATION: There are various reasons for rerunning bioinformatics tools and pipelines on sequencing data, including reproducing a past result, validation of a new tool or workflow using a known dataset, or tracking the impact of database changes. For identical results to be achieved, regularly updated reference sequence databases must be versioned and archived. Database administrators have tried to fill the requirements by supplying users with one-off versions of databases, but these are time consuming to set up and are inconsistent across resources. Disk storage and data backup performance has also discouraged maintaining multiple versions of databases since databases such as NCBI nr can consume 50 Gb or more disk space per version, with growth rates that parallel Moore's law. RESULTS: Our end-to-end solution combines our own Kipper software package-a simple key-value large file versioning system-with BioMAJ (software for downloading sequence databases), and Galaxy (a web-based bioinformatics data processing platform). Available versions of databases can be recalled and used by command-line and Galaxy users. The Kipper data store format makes publishing curated FASTA databases convenient since in most cases it can store a range of versions into a file marginally larger than the size of the latest version. AVAILABILITY AND IMPLEMENTATION: Kipper v1.0.0 and the Galaxy Versioned Data tool are written in Python and released as free and open source software available at https://github.com/Public-Health-Bioinformatics/kipper and https://github.com/Public-Health-Bioinformatics/versioned_data, respectively; detailed setup instructions can be found at https://github.com/Public-Health-Bioinformatics/versioned_data/blob/master/doc/setup.md CONTACT: : Damion.Dooley@Bccdc.Ca or William.Hsiao@Bccdc.CaSupplementary information: Supplementary data are available at Bioinformatics online.

Uncovering effects of antibiotics on the host and microbiota using transkingdom gene networks.

OBJECTIVE: Despite widespread use of antibiotics for the treatment of life-threatening infections and for research on the role of commensal microbiota, our understanding of their effects on the host is still very limited. DESIGN: Using a popular mouse model of microbiota depletion by a cocktail of antibiotics, we analysed the effects of antibiotics by combining intestinal transcriptome together with metagenomic analysis of the gut microbiota. In order to identify specific microbes and microbial genes that influence the host phenotype in antibiotic-treated mice, we developed and applied analysis of the transkingdom network. RESULTS: We found that most antibiotic-induced alterations in the gut can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues and the effects of remaining antibiotic-resistant microbes. Normal microbiota depletion mostly led to downregulation of different aspects of immunity. The two other factors (antibiotic direct effects on host tissues and antibiotic-resistant microbes) primarily inhibited mitochondrial gene expression and amounts of active mitochondria, increasing epithelial cell death. By reconstructing and analysing the transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria, a finding further validated using in vitro experiments. CONCLUSIONS: In addition to revealing mechanisms of antibiotic-induced alterations, this study also describes a new bioinformatics approach that predicts microbial components that regulate host functions and establishes a comprehensive resource on what, why and how antibiotics affect the gut in a widely used mouse model of microbiota depletion by antibiotics.

Harnessing the privatisation of China's fragmented health-care delivery.

Although China's 2009 health-care reform has made impressive progress in expansion of insurance coverage, much work remains to improve its wasteful health-care delivery. Particularly, the Chinese health-care system faces substantial challenges in its transformation from a profit-driven public hospital-centred system to an integrated primary care-based delivery system that is cost effective and of better quality to respond to the changing population needs. An additional challenge is the government's latest strategy to promote private investment for hospitals. In this Review, we discuss how China's health-care system would perform if hospital privatisation combined with hospital-centred fragmented delivery were to prevail--population health outcomes would suffer; health-care expenditures would escalate, with patients bearing increasing costs; and a two-tiered system would emerge in which access and quality of care are decided by ability to pay. We then propose an alternative pathway that includes the reform of public hospitals to pursue the public interest and be more accountable, with public hospitals as the benchmarks against which private hospitals would have to compete, with performance-based purchasing, and with population-based capitation payment to catalyse coordinated care. Any decision to further expand the for-profit private hospital market should not be made without objective assessment of its effect on China's health-policy goals.

Giardia spp. Are Commonly Found in Mixed Assemblages in Surface Water, as Revealed by Molecular and Whole-Genome Characterization.

Giardia is the most common parasitic cause of gastrointestinal infections worldwide, with transmission through surface water playing an important role in various parts of the world. Giardia duodenalis (synonyms: G. intestinalis and G. lamblia), a multispecies complex, has two zoonotic subtypes, assemblages A and B. When British Columbia (BC), a western Canadian province, experienced several waterborne giardiasis outbreaks due to unfiltered surface drinking water in the late 1980s, collection of isolates from surface water, as well as from humans and beavers (Castor canadensis), throughout the province was carried out. To better understand Giardia in surface water, 71 isolates, including 29 from raw surface water samples, 29 from human giardiasis cases, and 13 from beavers in watersheds from this historical library were characterized by PCR. Study isolates also included isolates from waterborne giardiasis outbreaks. Both assemblages A and B were identified in surface water, human, and beavers samples, including a mixture of both assemblages A and B in waterborne outbreaks. PCR results were confirmed by whole-genome sequencing (WGS) for one waterborne outbreak and supported the clustering of human, water, and beaver isolates within both assemblages. We concluded that contamination of surface water by Giardia is complex, that the majority of our surface water isolates were assemblage B, and that both assemblages A and B may cause waterborne outbreaks. The higher-resolution data provided by WGS warrants further study to better understand the spread of Giardia.

EBARDenovo: highly accurate de novo assembly of RNA-Seq with efficient chimera-detection.

MOTIVATION: High-accuracy de novo assembly of the short sequencing reads from RNA-Seq technology is very challenging. We introduce a de novo assembly algorithm, EBARDenovo, which stands for Extension, Bridging And Repeat-sensing Denovo. This algorithm uses an efficient chimera-detection function to abrogate the effect of aberrant chimeric reads in RNA-Seq data. RESULTS: EBARDenovo resolves the complications of RNA-Seq assembly arising from sequencing errors, repetitive sequences and aberrant chimeric amplicons. In a series of assembly experiments, our algorithm is the most accurate among the examined programs, including de Bruijn graph assemblers, Trinity and Oases. AVAILABILITY AND IMPLEMENTATION: EBARDenovo is available at http://ebardenovo.sourceforge.net/. This software package (with patent pending) is free of charge for academic use only. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Financing and provision of healthcare for two billion people in low-income nations: Is the cooperative healthcare model a solution?

The international consensus in support of universal health coverage (UHC), though commendable, thus far lacks a clear mechanism to finance and deliver accessible and effective basic healthcare to the two billion rural residents and informal workers of low- and lower-middle-income countries (LLMICs). Importantly, the two preferred financing modes for UHC, general tax revenue and social health insurance, are often infeasible for LLMICs. We identify from historical examples a community-based model that we argue shows promise as a solution to this problem. This model, which we call Cooperative Healthcare (CH), is characterized by community-based risk-pooling and governance and prioritizes primary care. CH leverages communities' existing social capital, such that even those for whom the private benefit of enrolling in a CH scheme is outweighed by the cost may choose to enroll (given sufficient social capital). For CH to be scalable, it needs to demonstrate that it can organize delivery of accessible and reasonable-quality primary healthcare that people value, with management accountable to the communities themselves through structures that people trust, combined with government legitimacy. Once LLMICs with CH programs have industrialized sufficiently to make universal social health insurance feasible, CH schemes can be rolled into such universal programs. We defend cooperative healthcare's suitability for this bridging role and urge LLMIC governments to launch experiments testing it out, with careful adaptation to local conditions.

Whole-genome sequencing of Western Canadian Borrelia spp. collected from diverse tick and animal hosts reveals short-lived local genotypes interspersed with longer-lived continental genotypes.

Changing climates are allowing the geographic expansion of ticks and their animal hosts, increasing the risk of Borrelia-caused zoonoses in Canada. However, little is known about the genomic diversity of Borrelia from the west of the Canadian Rockies and from the tick vectors Ixodes pacificus, Ixodes auritulus and Ixodes angustus. Here, we report the whole-genome shotgun sequences of 51 Borrelia isolates from multiple tick species collected on a range of animal hosts between 1993 and 2016, located primarily in coastal British Columbia. The bacterial isolates represented three different species from the Lyme disease-causing Borrelia burgdorferi sensu lato genospecies complex [Borrelia burgdorferi sensu stricto (n=47), Borrelia americana (n=3) and Borrelia bissettiae (n=1)]. The traditional eight-gene multi-locus sequence typing (MLST) strategy was applied to facilitate comparisons across studies. This identified 13 known Borrelia sequence types (STs), established 6 new STs, and assigned 5 novel types to the nearest sequence types. B. burgdorferi s. s. isolates were further differentiated into ten ospC types, plus one novel ospC with less than 92 % nucleotide identity to all previously defined ospC types. The MLST types resampled over extended time periods belonged to previously described STs that are distributed across North America. The most geographically widespread ST, ST.12, was isolated from all three tick species. Conversely, new B. burgdorferi s. s. STs from Vancouver Island and the Vancouver region were only detected for short periods, revealing a surprising transience in space, time and host tick species, possibly due to displacement by longer-lived genotypes that expanded across North America.This article contains data hosted by Microreact.

The diversity of clinical Mycobacterium abscessus isolates in morphology, glycopeptidolipids and infection rates in a macrophage model.

Introduction. Mycobacterium abscessus (MABS) is a pathogenic bacterium that can cause severe lung infections, particularly in individuals with cystic fibrosis. MABS colonies can exhibit either a smooth (S) or rough (R) morphotype, influenced by the presence or absence of glycopeptidolipids (GPLs) on their surface, respectively. Despite the clinical significance of these morphotypes, the relationship between GPL levels, morphotype and the pathogenesis of MABS infections remains poorly understood.Gap statement. The mechanisms and implications of GPL production and morphotypes in clinical MABS infections are unclear. There is a gap in understanding their correlation with infectivity and pathogenicity, particularly in patients with underlying lung disease.Aim. This study aimed to investigate the correlation between MABS morphology, GPL and infectivity by analysing strains from cystic fibrosis patients' sputum samples.Methodology. MABS was isolated from patient sputum samples and categorized by morphotype, GPL profile and replication rate in macrophages. A high-content ex vivo infection model using THP-1 cells assessed the infectivity of both clinical and laboratory strains.Results. Our findings revealed that around 50 % of isolates displayed mixed morphologies. GPL analysis confirmed a consistent relationship between GPL content and morphotype that was only found in smooth isolates. Across morphotype groups, no differences were observed in vitro, yet clinical R strains were observed to replicate at higher levels in the THP-1 infection model. Moreover, the proportion of infected macrophages was notably higher among clinical R strains compared to their S counterparts at 72 h post-infection. Clinical variants also infected THP-1 cells at significantly higher rates compared to laboratory strains, highlighting the limited translatability of lab strain infection data to clinical contexts.Conclusion. Our study confirmed the general correlation between morphotype and GPL levels in smooth strains yet unveiled more variability within morphotype groups than previously recognized, particularly during intracellular infection. As the R morphotype is the highest clinical concern, these findings contribute to the expanding knowledge base surrounding MABS infections, offering insights that can steer diagnostic methodologies and treatment approaches.

Mediterranean diet and associations with the gut microbiota and pediatric-onset multiple sclerosis using trivariate analysis.

BACKGROUND: The interplay between diet and the gut microbiota in multiple sclerosis (MS) is poorly understood. We aimed to assess the interrelationship between diet, the gut microbiota, and MS. METHODS: We conducted a case-control study including 95 participants (44 pediatric-onset MS cases, 51 unaffected controls) enrolled from the Canadian Pediatric Demyelinating Disease Network study. All had completed a food frequency questionnaire ≤21-years of age, and 59 also provided a stool sample. RESULTS: Here we show that a 1-point increase in a Mediterranean diet score is associated with 37% reduced MS odds (95%CI: 10%-53%). Higher fiber and iron intakes are also associated with reduced MS odds. Diet, not MS, explains inter-individual gut microbiota variation. Several gut microbes abundances are associated with both the Mediterranean diet score and having MS, and these microbes are potential mediators of the protective associations of a healthier diet. CONCLUSIONS: Our findings suggest that the potential interaction between diet and the gut microbiota is relevant in MS.

Multiple sclerosis (MS) is a disease where the immune system attacks the protective covering of nerve cells in the brain. There may be a relationship between diet and bacteria within the gut and MS, however this is not well understood. We investigated how diet and gut bacteria are linked to MS in young people. We examined the diet and types of bacteria in stool samples from those with and without MS. We found that a diet richer in fiber and Mediterranean foods were less common in those with MS. This dietary pattern was linked to certain differences in the gut bacteria. These findings raise the possibility, but cannot prove, that what we eat may help prevent MS by influencing our gut bacteria. This research opens the door to further studies on how diet can impact MS through our gut bacteria.

PHA4GE quality control contextual data tags: standardized annotations for sharing public health sequence datasets with known quality issues to facilitate testing and training.

As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower quality datasets be made available for analysis and comparison alongside those of higher quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays. Sharing of useful, but sub-optimal datasets requires careful annotation and documentation of known issues to enable appropriate interpretation, avoid being mistaken for better quality information, and for these data (and their derivatives) to be easily identifiable in repositories. Unfortunately, there are currently no standardized attributes or mechanisms for tagging poor-quality datasets, or datasets generated for a specific purpose, to maximize their utility, searchability, accessibility and reuse. The Public Health Alliance for Genomic Epidemiology (PHA4GE) is an international community of scientists from public health, industry and academia focused on improving the reproducibility, interoperability, portability, and openness of public health bioinformatic software, skills, tools and data. To address the challenges of sharing lower quality datasets, PHA4GE has developed a set of standardized contextual data tags, namely fields and terms, that can be included in public repository submissions as a means of flagging pathogen sequence data with known quality issues, increasing their discoverability. The contextual data tags were developed through consultations with the community including input from the International Nucleotide Sequence Data Collaboration (INSDC), and have been standardized using ontologies - community-based resources for defining the tag properties and the relationships between them. The standardized tags are agnostic to the organism and the sequencing technique used and thus can be applied to data generated from any pathogen using an array of sequencing techniques. The tags can also be applied to synthetic (lab created) data. The list of standardized tags is maintained by PHA4GE and can be found at https://github.com/pha4ge/contextual_data_QC_tags. Definitions, ontology IDs, examples of use, as well as a JSON representation, are provided. The PHA4GE QC tags were tested, and are now implemented, by the FDA's GenomeTrakr laboratory network as part of its routine submission process for SARS-CoV-2 wastewater surveillance. We hope that these simple, standardized tags will help improve communication regarding quality control in public repositories, in addition to making datasets of variable quality more easily identifiable. Suggestions for additional tags can be submitted to PHA4GE via the New Term Request Form in the GitHub repository. By providing a mechanism for feedback and suggestions, we also expect that the tags will evolve with the needs of the community.

Early appraisal of China's huge and complex health-care reforms.

China's 3 year, CN¥850 billion (US$125 billion) reform plan, launched in 2009, marked the first phase towards achieving comprehensive universal health coverage by 2020. The government's undertaking of systemic reform and its affirmation of its role in financing health care together with priorities for prevention, primary care, and redistribution of finance and human resources to poor regions are positive developments. Accomplishing nearly universal insurance coverage in such a short time is commendable. However, transformation of money and insurance coverage into cost-effective services is difficult when delivery of health care is hindered by waste, inefficiencies, poor quality of services, and scarcity and maldistribution of the qualified workforce. China must reform its incentive structures for providers, improve governance of public hospitals, and institute a stronger regulatory system, but these changes have been slowed by opposition from stakeholders and lack of implementation capacity. The pace of reform should be moderated to allow service providers to develop absorptive capacity. Independent, outcome-based monitoring and evaluation by a third-party are essential for mid-course correction of the plans and to make officials and providers accountable.

MicrobeDB: a locally maintainable database of microbial genomic sequences.

UNLABELLED: Analysis of microbial genomes often requires the general organization and comparison of tens to thousands of genomes both from public repositories and unpublished sources. MicrobeDB provides a foundation for such projects by the automation of downloading published, completed bacterial and archaeal genomes from key sources, parsing annotations of all genomes (both public and private) into a local database, and allowing interaction with the database through an easy to use programming interface. MicrobeDB creates a simple to use, easy to maintain, centralized local resource for various large-scale comparative genomic analyses and a back-end for future microbial application design. AVAILABILITY: MicrobeDB is freely available under the GNU-GPL at: http://github.com/mlangill/microbedb/

OntoTrek: 3D visualization of application ontology class hierarchies.

An application ontology often reuses terms from other related, compatible ontologies. The extent of this interconnectedness is not readily apparent when browsing through larger textual presentations of term class hierarchies, be it Manchester text format OWL files or within an ontology editor like Protege. Users must either note ontology sources in term identifiers, or look at ontology import file term origins. Diagrammatically, this same information may be easier to perceive in 2 dimensional network or hierarchical graphs that visually code ontology term origins. However, humans, having stereoscopic vision and navigational acuity around colored and textured shapes, should benefit even more from a coherent 3-dimensional interactive visualization of ontology that takes advantage of perspective to offer both foreground focus on content and a stable background context. We present OntoTrek, a 3D ontology visualizer that enables ontology stakeholders-students, software developers, curation teams, and funders-to recognize the presence of imported terms and their domains, ultimately illustrating how projects can capture knowledge through a vocabulary of interwoven community-supported ontology resources.

Canadians' opinions towards COVID-19 data-sharing: a national cross-sectional survey.

OBJECTIVES: COVID-19 research has significantly contributed to pandemic response and the enhancement of public health capacity. COVID-19 data collected by provincial/territorial health authorities in Canada are valuable for research advancement yet not readily available to the public, including researchers. To inform developments in public health data-sharing in Canada, we explored Canadians' opinions of public health authorities sharing deidentified individual-level COVID-19 data publicly. DESIGN/SETTING/INTERVENTIONS/OUTCOMES: A national cross-sectional survey was administered in Canada in March 2022, assessing Canadians' opinions on publicly sharing COVID-19 datatypes. Market research firm Léger was employed for recruitment and data collection. PARTICIPANTS: Anyone greater than or equal to 18 years and currently living in Canada. RESULTS: 4981 participants completed the survey with a 92.3% response rate. 79.7% were supportive of provincial/territorial authorities publicly sharing deidentified COVID-19 data, while 20.3% were hesitant/averse/unsure. Datatypes most supported for being shared publicly were symptoms (83.0% in support), geographical region (82.6%) and COVID-19 vaccination status (81.7%). Datatypes with the most aversion were employment sector (27.4% averse), postal area (26.7%) and international travel history (19.7%). Generally supportive Canadians were characterised as being ≥50 years, with higher education, and being vaccinated against COVID-19 at least once. Vaccination status was the most influential predictor of data-sharing opinion, with respondents who were ever vaccinated being 4.20 times more likely (95% CI 3.21 to 5.48, p=0.000) to be generally supportive of data-sharing than those unvaccinated. CONCLUSIONS: These findings suggest that the Canadian public is generally favourable to deidentified data-sharing. Identifying factors that are likely to improve attitudes towards data-sharing are useful to stakeholders involved in data-sharing initiatives, such as public health agencies, in informing the development of public health communication and data-sharing policies. As Canada progresses through the COVID-19 pandemic, and with limited testing and reporting of COVID-19 data, it is essential to improve deidentified data-sharing given the public's general support for these efforts.

The DataHarmonizer: a tool for faster data harmonization, validation, aggregation and analysis of pathogen genomics contextual information.

Pathogen genomics is a critical tool for public health surveillance, infection control, outbreak investigations as well as research. In order to make use of pathogen genomics data, they must be interpreted using contextual data (metadata). Contextual data include sample metadata, laboratory methods, patient demographics, clinical outcomes and epidemiological information. However, the variability in how contextual information is captured by different authorities and how it is encoded in different databases poses challenges for data interpretation, integration and their use/re-use. The DataHarmonizer is a template-driven spreadsheet application for harmonizing, validating and transforming genomics contextual data into submission-ready formats for public or private repositories. The tool's web browser-based JavaScript environment enables validation and its offline functionality and local installation increases data security. The DataHarmonizer was developed to address the data sharing needs that arose during the COVID-19 pandemic, and was used by members of the Canadian COVID Genomics Network (CanCOGeN) to harmonize SARS-CoV-2 contextual data for national surveillance and for public repository submission. In order to support coordination of international surveillance efforts, we have partnered with the Public Health Alliance for Genomic Epidemiology to also provide a template conforming to its SARS-CoV-2 contextual data specification for use worldwide. Templates are also being developed for One Health and foodborne pathogens. Overall, the DataHarmonizer tool improves the effectiveness and fidelity of contextual data capture as well as its subsequent usability. Harmonization of contextual information across authorities, platforms and systems globally improves interoperability and reusability of data for concerted public health and research initiatives to fight the current pandemic and future public health emergencies. While initially developed for the COVID-19 pandemic, its expansion to other data management applications and pathogens is already underway.