How ownership rights over microorganisms affect infectious disease control and innovation: A root-cause analysis of barriers to data sharing as experienced by key stakeholders

Lassa fever research priorities: towards effective medical countermeasures by the end of the decade

In 2016, WHO designated Lassa fever a priority disease for epidemic preparedness as part of the WHO Blueprint for Action to Prevent Epidemics. One aspect of preparedness is to promote development of effective medical countermeasures (ie, diagnostics, therapeutics, and vaccines) against Lassa fever. Diagnostic testing for Lassa fever has important limitations and key advancements are needed to ensure rapid and accurate diagnosis. Additionally, the only treatment available for Lassa fever is ribavirin, but controversy exists regarding its effectiveness. Finally, no licensed vaccines are available for the prevention and control of Lassa fever. Ongoing epidemiological and behavioural studies are also crucial in providing actionable information for medical countermeasure development, use, and effectiveness in preventing and treating Lassa fever. This Personal View provides current research priorities for development of Lassa fever medical countermeasures based on literature published primarily in the last 5 years and consensus opinion of 20 subject matter experts with broad experience in public health or the development of diagnostics, therapeutics, and vaccines for Lassa fever. These priorities provide an important framework to ensure that Lassa fever medical countermeasures are developed and readily available for use in endemic and at-risk areas by the end of the decade.

eHealth implementation in Europe: a scoping review on legal, ethical, financial, and technological aspects

Background

The evolution of eHealth development has shifted from standalone tools to comprehensive digital health environments, fostering data exchange among diverse stakeholders and systems. Nevertheless, existing research and implementation frameworks have primarily emphasized technological and organizational aspects of eHealth implementation, overlooking the intricate legal, ethical, and financial considerations. It is essential to discover what legal, ethical, financial, and technological challenges should be considered to ensure successful and sustainable implementation of eHealth.

Objective

This review aims to provide insights into barriers and facilitators of legal, ethical, financial, and technological aspects for successful implementation of complex eHealth technologies, which impacts multiple levels and multiple stakeholders.

Methods

A scoping review was conducted by querying PubMed, Scopus, Web of Science, and ACM Digital Library (2018-2023) for studies describing the implementation process of eHealth technologies that facilitate data exchange. Studies solely reporting clinical outcomes or conducted outside Europe were excluded. Two independent reviewers selected the studies. A conceptual framework was constructed through axial and inductive coding, extracting data from literature on legal, ethical, financial, and technological aspects of eHealth implementation. This framework guided systematic extraction and interpretation.

Results

The search resulted in 7.308 studies that were screened for eligibility, of which 35 (0.48%) were included. Legal barriers revolve around data confidentiality and security, necessitating clear regulatory guidelines. Ethical barriers span consent, responsibility, liability, and validation complexities, necessitating robust frameworks. Financial barriers stem from inadequate funding, requiring (commercial) partnerships and business models. Technological issues include interoperability, integration, and malfunctioning, necessitating strategies for enhancing data reliability, improving accessibility, and aligning eHealth technology with existing systems for smoother integration.

Conclusions

This research highlights the multifaceted nature of eHealth implementation, encompassing legal, ethical, financial, and technological considerations. Collaborative stakeholder engagement is paramount for effective decision-making and aligns with the transition from standalone eHealth tools to integrated digital health environments. Identifying suitable stakeholders and recognizing their stakes and values enriches implementation strategies with expertise and guidance across all aspects. Future research should explore the timing of these considerations and practical solutions for regulatory compliance, funding, navigation of responsibility and liability, and business models for reimbursement strategies.

Six dilemmas for stakeholders inherently affecting data sharing during a zoonotic (re-)emerging infectious disease outbreak response

BACKGROUND

Timely access to outbreak related data, particularly in the early events of a spillover, is important to support evidence based control measures in response to outbreaks of zoonotic Emerging Infectious Diseases (EID). Yet, this is impeded by several barriers that need to be understood to promote timely sharing of data. Using the MERS epidemic as a model for a zoonotic EID outbreak, this study sought to provide an in-depth understanding of data sharing practices.

METHODS

Semi-structured interviews with 25 experts were conducted, along with Focus Group Discussions with 15 additional experts. A root-cause analysis was performed to examine the causal relationships between barriers. Enablers were mapped to the root-cause analysis to understand their influence on the barriers. Finally, root causes were placed in context of core dilemmas identified from the qualitative analysis.

FINDINGS

Eight barriers to data sharing were identified, related to collaboration, technical preparedness, regulations, and (conflict of) interests, and placed in the context of six dilemmas inherent to the multi-stakeholder collaboration required for a zoonotic outbreak response. Fourteen identified enablers showed the willingness of stakeholders to overcome or circumvent these barriers, but also indicated the inherent trial and error nature of implementing such enablers.

INTERPRETATION

Addressing the barriers requires solutions that must consider the complexity and interconnectedness of the root causes underlying them, and should consider the distinct scopes and interests of the different stakeholders. Insights provided by this study can be used to encourage data sharing practices for future outbreaks FUNDING: Wellcome Trust and UK Aid; EU-H2020 Societal Challenges (grant agreement no. 643476), Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VI.Veni.201S.044).

Developing One Health surveillance systems

The health of humans, domestic and wild animals, plants, and the environment are inter-dependent. Global anthropogenic change is a key driver of disease emergence and spread and leads to biodiversity loss and ecosystem function degradation, which are themselves drivers of disease emergence. Pathogen spill-over events and subsequent disease outbreaks, including pandemics, in humans, animals and plants may arise when factors driving disease emergence and spread converge. One Health is an integrated approach that aims to sustainably balance and optimize human, animal and ecosystem health. Conventional disease surveillance has been siloed by sectors, with separate systems addressing the health of humans, domestic animals, cultivated plants, wildlife and the environment. One Health surveillance should include integrated surveillance for known and unknown pathogens, but combined with this more traditional disease-based surveillance, it also must include surveillance of drivers of disease emergence to improve prevention and mitigation of spill-over events. Here, we outline such an approach, including the characteristics and components required to overcome barriers and to optimize an integrated One Health surveillance system.

An elephant in the glasshouse? Trade-offs between acceleration and transformation in COVID-19 vaccine innovation policies

Against the backdrop of a failing vaccine innovation system, innovation policy aimed at creating a COVID-19 vaccine was surprisingly fast and effective. This paper analyzes the influence of the COVID-19 landscape shock and corresponding innovation policy responses on the existing vaccine innovation system. We use document analysis and expert interviews, performed during vaccine development. We find that the sharing of responsibility between public and private actors on various geographical levels, and the focus on accelerating changes in the innovation system were instrumental in achieving fast results. Simultaneously, the acceleration exacerbated existing societal innovation barriers, such as vaccine hesitancy, health inequity, and contested privatization of earnings. Going forward, these innovation barriers may limit the legitimacy of the vaccine innovation system and reduce pandemic preparedness. Next to a focus on acceleration, transformative innovation policies for achieving sustainable pandemic preparedness are still urgently needed. Implications for mission-oriented innovation policy are discussed.

Ten simple rules for the sharing of bacterial genotype-Phenotype data on antimicrobial resistance

The increasing availability of high-throughput sequencing (frequently termed next-generation sequencing (NGS)) data has created opportunities to gain deeper insights into the mechanisms of a number of diseases and is already impacting many areas of medicine and public health. The area of infectious diseases stands somewhat apart from other human diseases insofar as the relevant genomic data comes from the microbes rather than their human hosts. A particular concern about the threat of antimicrobial resistance (AMR) has driven the collection and reporting of large-scale datasets containing information from microbial genomes together with antimicrobial susceptibility test (AST) results. Unfortunately, the lack of clear standards or guiding principles for the reporting of such data is hampering the field's advancement. We therefore present our recommendations for the publication and sharing of genotype and phenotype data on AMR, in the form of 10 simple rules. The adoption of these recommendations will enhance AMR data interoperability and help enable its large-scale analyses using computational biology tools, including mathematical modelling and machine learning. We hope that these rules can shed light on often overlooked but nonetheless very necessary aspects of AMR data sharing and enhance the field's ability to address the problems of understanding AMR mechanisms, tracking their emergence and spread in populations, and predicting microbial susceptibility to antimicrobials for diagnostic purposes.

Vaccine Innovation Meta-Model for Pandemic Contexts

Purpose

Over the past decade, successive outbreaks and epidemics of infectious diseases have challenged the emergency preparedness and response systems of global public health institutions, a context in which vaccines have become the centerpiece to strengthening global health security. Nevertheless, vaccine research and development (R&D) is a complex, lengthy, risky, uncertain, and expensive process. Alongside strict, time-consuming regulatory compliance, it takes multiple candidates and many years to register a new vaccine. This is certainly not welcome in a global health crisis such as the COVID-19 pandemic. Therefore, this study aims to understand the R&D paradigm shift in pandemic contexts and its impacts on the value chain of vaccine innovation.

Methods

To that end, this paper carried out a systematic literature review and meta-synthesis of 27 articles and reports (2011-2021) that addressed vaccine R&D in contexts of global health threats, disease outbreaks, epidemics, or pandemics.

Results

The research findings are synthesized in a meta-model, which describes a fast-track R&D for pandemic contexts, its driving forces, innovations, mechanisms, and impacts in the value chain of vaccine innovation.

Conclusions

The study demonstrates that, in pandemic contexts, a fast-track R&D process based on close collaboration among regulators, industry, and academia and leveraging enabling technologies can drastically reduce the time required to bring safe, stable, and effective vaccines to market by an average of 11 years compared to the traditional R&D process. Furthermore, pharmacovigilance and rigorous monitoring of real-world evidence became critical to ensuring that quality and safe products were authorized for use during a pandemic.

A new model for classification of medical CT images using CNN: a COVID-19 case study

SARS-CoV-2 is the causative agent of COVID-19 and leaves characteristic impressions on chest Computed Tomography (CT) images in infected patients and this analysis is performed by radiologists through visual reading of lung images, and failures may occur. In this article, we propose a classification model, called Wavelet Convolutional Neural Network (WCNN) that aims to improve the differentiation of images of patients with COVID-19 from images of patients with other lung infections. The WCNN model was based on a Convolutional Neural Network (CNN) and wavelet transform. The model proposes a new input layer added to the neural network, which was called Wave layer. The hyperparameters values were defined by ablation tests. WCNN was applied to chest CT images to images from two internal and one external repositories. For all repositories, the average results of Accuracy (ACC), Sensitivity (Sen) and Specificity (Sp) were calculated. Subsequently, the average results of the repositories were consolidated, and the final values were ACC = 0.9819, Sen = 0.9783 and Sp = 0.98. The WCNN model uses a new Wave input layer, which standardizes the network input, without using data augmentation, resizing and segmentation techniques, maintaining the integrity of the tomographic image analysis. Thus, applications developed based on WCNN have the potential to assist radiologists with a second opinion in the analysis.1.

Vaccine innovation model: A technology transfer perspective in pandemic contexts

This work identifies the innovations that made it possible for the Bio-Manguinhos/Fiocruz Immunobiological Technology Institute to engage in the entire production of the Oxford/AstraZeneca vaccine (ChAdOx1 nCov-19) in Brazil, just 1.8 years after the COVID-19 pandemic was declared. The results were summarized in a case-based innovation model composed of 11 workstreams, 32 stages, 22 gates, 11 innovations, and 38 events. In terms of research contributions, three were found: (i) the identification of firm and government-level innovations allowing the substantial reduction in the COVID-19 vaccine time-to-market in Brazil; (ii) the presentation of empirical evidence supporting the new Outbreak Paradigm for vaccine research, development, and production; and (iii) the proposition of a conceptual model for describing innovations through the vaccine value chain in pandemic contexts, particularly when technology transfer is involved.

Access and benefit-sharing by the European Virus Archive in response to COVID-19

Biobanking infrastructures, which are crucial for responding early to new viral outbreaks, share pathogen genetic resources in an affordable, safe, and impartial manner and can provide expertise to address access and benefit-sharing issues. The European Virus Archive has had a crucial role in the global response to the COVID-19 pandemic by distributing EU-subsidised (free of charge) viral resources to users worldwide, providing non-monetary benefit sharing, implementing access and benefit-sharing compliance, and raising access and benefit-sharing awareness among members and users. All currently available SARS-CoV-2 material in the European Virus Archive catalogue, including variants of concern, are not access and benefit-sharing cases per se, but multilateral benefit-sharing has nevertheless occurred. We propose and discuss how a multilateral system enabling access and benefit-sharing from pathogen genetic resources, based on the European Virus Archive operational model, could help bridge the discrepancies between the current bilateral legal framework for pathogen genetic resources and actual pandemic response practices.

Multilateral benefit-sharing from digital sequence information will support both science and biodiversity conservation

Open access to sequence data is a cornerstone of biology and biodiversity research, but has created tension under the United Nations Convention on Biological Diversity (CBD). Policy decisions could compromise research and development, unless a practical multilateral solution is implemented.

Ensuring international benefit-sharing from sequence data without jeopardising open sharing is a major obstacle for the Convention on Biological Diversity and other UN negotiations. Here, the authors propose a solution to address the concerns of both developing countries and life scientists.

Ethical Issues in Genetics and Infectious Diseases Research: An Interdisciplinary Expert Review

PURPOSE

Research in genetics and infectious diseases (ID) presents novel configurations of ethical, legal, and social issues (ELSIs) related to the intersection of genetics with public health regulations and the control of transmissible diseases. Such research includes work both in pathogen genetics and on the ways that human genetics affect responses to ID. This paper identifies and systematizes the unique issues at this intersection, based on an interdisciplinary expert review.

BASIC PROCEDURES

This paper presents results of a formal issue-spotting exercise among twenty experts in public health, law and genomics, biobanking, genetic epidemiology, ID medicine and public health, philosophy, ethics and ID, ethics and genomics, and law and ID. The focus of the exercise was on the collection, storage, and sharing of genetic information relating to ID.

MAIN FINDINGS

The issue-spotting exercise highlighted the following ELSIs: risks in reporting to government authorities, return of individual research results, and resource allocation - each taking on specific configurations based on the balance between public health and individual privacy/protection.

PRINCIPAL CONCLUSIONS

The public health implications of interactions between genomics and ID frame considerations for equity and justice. In the context of the COVID-19 pandemic, these issues are especially pressing.

Barriers Influencing Vaccine Development Timelines, Identification, Causal Analysis, and Prioritization of Key Barriers by KOLs in General and Covid-19 Vaccine R&D

A frequently mentioned factor holding back the introduction of new vaccines on the market are their prohibitively long development timelines. These hamper their potential societal benefit and impairs the ability to quickly respond to emerging new pathogens. This is especially worrisome since new pathogens are emerging at all-time high rates of over one per year, and many age-old pathogens are still not vaccine preventable.Through interviews with 20 key-opinion-leaders (KOLs), this study identified innovation barriers that increase vaccine development timelines. These innovation barriers were visualized, and their underlying causes revealed by means of qualitative root cause analysis. Based on a survey the innovation barriers were quantitatively ranked based on their relative impact on both regular, and Covid-19 vaccine development timelines. KOLs identified 20 key innovation barriers, and mapping these barriers onto the Vaccine Innovation Cycle model revealed that all phases of vaccine development were affected. Affected by most barriers is the area between the preclinical studies and the market entry. Difficult hand-off between academia and industry, lack of funding, and lack of knowledge of pathogen targets were often mentioned as causes. Quantitative survey responses from 93 KOLs showed that general vaccine development and Covid-19 vaccine development are impacted by distinct sets of innovation barriers. For the general vaccine development three barriers were perceived of the highest impact; limited ROI for vaccines addressing disease with limited market size, limited ROI for vaccines compared to non-vaccine projects, and academia not being able to progress beyond proof of principle. Of highest impact on Covid-19 vaccine development, are lack of knowledge concerning pathogen target, high risk of upscaling unlicensed vaccines, and proof of principle not meeting late-stage requirements. In conclusion, the current study demonstrates that barriers hampering timelines in vaccine development are present across the Vaccine Innovation Cycle. Prioritizing the impact of barriers in general, and in Covid-19 vaccine development, shows clear differences that can be used to inform policies to speed up development in both war and peace time.

Classification and specific primer design for accurate detection of SARS-CoV-2 using deep learning

In this paper, deep learning is coupled with explainable artificial intelligence techniques for the discovery of representative genomic sequences in SARS-CoV-2. A convolutional neural network classifier is first trained on 553 sequences from the National Genomics Data Center repository, separating the genome of different virus strains from the Coronavirus family with 98.73% accuracy. The network's behavior is then analyzed, to discover sequences used by the model to identify SARS-CoV-2, ultimately uncovering sequences exclusive to it. The discovered sequences are validated on samples from the National Center for Biotechnology Information and Global Initiative on Sharing All Influenza Data repositories, and are proven to be able to separate SARS-CoV-2 from different virus strains with near-perfect accuracy. Next, one of the sequences is selected to generate a primer set, and tested against other state-of-the-art primer sets, obtaining competitive results. Finally, the primer is synthesized and tested on patient samples (n = 6 previously tested positive), delivering a sensitivity similar to routine diagnostic methods, and 100% specificity. The proposed methodology has a substantial added value over existing methods, as it is able to both automatically identify promising primer sets for a virus from a limited amount of data, and deliver effective results in a minimal amount of time. Considering the possibility of future pandemics, these characteristics are invaluable to promptly create specific detection methods for diagnostics.

Perceived utility and feasibility of pathogen genomics for public health practice: a survey among public health professionals working in the field of infectious diseases, Belgium, 2019

BACKGROUND

Pathogen genomics is increasingly being translated from the research setting into the activities of public health professionals operating at different levels. This survey aims to appraise the literacy level and gather the opinions of public health experts and allied professionals working in the field of infectious diseases in Belgium concerning the implementation of next-generation sequencing (NGS) in public health practice.

METHODS

In May 2019, Belgian public health and healthcare professionals were invited to complete an online survey containing eight main topics including background questions, general attitude towards pathogen genomics for public health practice and main concerns, genomic literacy, current and planned NGS activities, place of NGS in diagnostic microbiology pathways, data sharing obstacles, end-user requirements, and key drivers for the implementation of NGS. Descriptive statistics were used to report on the frequency distribution of multiple choice responses whereas thematic analysis was used to analyze free text responses. A multivariable logistic regression model was constructed to identify important predictors for a positive attitude towards the implementation of pathogen genomics in public health practice.

RESULTS

146 out of the 753 invited public health professionals completed the survey. 63% of respondents indicated that public health agencies should be using genomics to understand and control infectious diseases. Having a high level of expertise in the field of pathogen genomics was the strongest predictor of a positive attitude (OR = 4.04, 95% CI = 1.11 - 17.23). A significantly higher proportion of data providers indicated to have followed training in the field of pathogen genomics compared to data end-users (p < 0.001). Overall, 79% of participants expressed interest in receiving further training. Main concerns were related to the cost of sequencing technologies, data sharing, data integration, interdisciplinary working, and bioinformatics expertise.

CONCLUSIONS

Belgian health professionals expressed favorable views about implementation of pathogen genomics in their work activities related to infectious disease surveillance and control. They expressed the need for suitable training initiatives to strengthen their competences in the field. Their perception of the utility and feasibility of pathogen genomics for public health purposes will be a key driver for its further implementation.

Ethical challenges in pathogen sequencing: a systematic scoping review

Background: Going forward, the routine implementation of genomic surveillance activities and outbreak investigation is to be expected. We sought to systematically identify the emerging ethical challenges; and to systematically assess the gaps in ethical frameworks or thinking and identify where further work is needed to solve practical challenges.

Methods: We systematically searched indexed academic literature from PubMed, Google Scholar, and Web of Science from 2000 to April 2019 for peer-reviewed articles that substantively engaged in discussion of ethical issues in the use of pathogen genome sequencing technologies for diagnostic, surveillance and outbreak investigation.

Results: 28 articles were identified; nine United States, five United Kingdom, five The Netherlands, three Canada, two Switzerland, one Australia, two South Africa, and one Italy. Eight articles were specifically about the use of sequencing in HIV. Eleven were not specific to a particular disease. Results were organized into four themes: tensions between public and private interests; difficulties with translation from research to clinical and public health practice; the importance of community trust and support; equity and global partnerships; and the importance of context.

Conclusion: While pathogen sequencing has the potential to be transformative for public health, there are a number of key ethical issues that must be addressed, particularly around the conditions of use for pathogen sequence data. Ethical standards should be informed by public values, and further empirical work investigating stakeholders’ views are required. Development in the field should also be under-pinned by a strong commitment to values of justice, in particular global health equity.

Whole genome sequencing and metagenomics for outbreak investigation, source attribution and risk assessment of food-borne microorganisms

This Opinion considers the application of whole genome sequencing (WGS) and metagenomics for outbreak investigation, source attribution and risk assessment of food‐borne pathogens. WGS offers the highest level of bacterial strain discrimination for food‐borne outbreak investigation and source‐attribution as well as potential for more precise hazard identification, thereby facilitating more targeted risk assessment and risk management. WGS improves linking of sporadic cases associated with different food products and geographical regions to a point source outbreak and can facilitate epidemiological investigations, allowing also the use of previously sequenced genomes. Source attribution may be favoured by improved identification of transmission pathways, through the integration of spatial‐temporal factors and the detection of multidirectional transmission and pathogen–host interactions. Metagenomics has potential, especially in relation to the detection and characterisation of non‐culturable, difficult‐to‐culture or slow‐growing microorganisms, for tracking of hazard‐related genetic determinants and the dynamic evaluation of the composition and functionality of complex microbial communities. A SWOT analysis is provided on the use of WGS and metagenomics for Salmonella and Shigatoxin‐producing Escherichia coli (STEC) serotyping and the identification of antimicrobial resistance determinants in bacteria. Close agreement between phenotypic and WGS‐based genotyping data has been observed. WGS provides additional information on the nature and localisation of antimicrobial resistance determinants and on their dissemination potential by horizontal gene transfer, as well as on genes relating to virulence and biological fitness. Interoperable data will play a major role in the future use of WGS and metagenomic data. Capacity building based on harmonised, quality controlled operational systems within European laboratories and worldwide is essential for the investigation of cross‐border outbreaks and for the development of international standardised risk assessments of food‐borne microorganisms.

Using Genomics to Track Global Antimicrobial Resistance

The recent advancements in rapid and affordable DNA sequencing technologies have revolutionized diagnostic microbiology and microbial surveillance. The availability of bioinformatics tools and online accessible databases has been a prerequisite for this. We conducted a scientific literature review and here we present a description of examples of available tools and databases for antimicrobial resistance (AMR) detection and provide future perspectives and recommendations. At least 47 freely accessible bioinformatics resources for detection of AMR determinants in DNA or amino acid sequence data have been developed to date. These include, among others but not limited to, ARG-ANNOT, CARD, SRST2, MEGARes, Genefinder, ARIBA, KmerResistance, AMRFinder, and ResFinder. Bioinformatics resources differ for several parameters including type of accepted input data, presence/absence of software for search within a database of AMR determinants that can be specific to a tool or cloned from other resources, and for the search approach employed, which can be based on mapping or on alignment. As a consequence, each tool has strengths and limitations in sensitivity and specificity of detection of AMR determinants and in application, which for some of the tools have been highlighted in benchmarking exercises and scientific articles. The identified tools are either available at public genome data centers, from GitHub or can be run locally. NCBI and European Nucleotide Archive (ENA) provide possibilities for online submission of both sequencing and accompanying phenotypic antimicrobial susceptibility data, allowing for other researchers to further analyze data, and develop and test new tools. The advancement in whole genome sequencing and the application of online tools for real-time detection of AMR determinants are essential to identify control and prevention strategies to combat the increasing threat of AMR. Accessible tools and DNA sequence data are expanding, which will allow establishing global pathogen surveillance and AMR tracking based on genomics. There is however, a need for standardization of pipelines and databases as well as phenotypic predictions based on the data.

Overcoming challenges for designing and implementing the One Health approach: A systematic review of the literature

Collaborative approaches in health, such as One Health (OH), are promising; nevertheless, several authors point at persistent challenges for designing and implementing OH initiatives. Among other challenges, OH practitioners struggle in their efforts to collaborate across disciplines and domains. This paper aims to provide insights into the existing challenges for designing and implementing OH initiatives, their causes and solutions, and points out strategic solutions with the potential to solve practical challenges. A systematic literature search was performed for emerging challenges and proposed solutions in the process of conducting OH initiatives. Next, a thematic and a causal analysis were performed to unravel challenges and their causes. Finally, solutions were discriminated on whether they were only recommended, or implemented as a proof-of-principle. The 56 included papers describe 21 challenges endured by OH initiatives that relate to different themes (policy and funding; education and training; surveillance; multi-actor, multi-domain, and multi-level collaborations; and evidence). These challenges occur in three different phases: the acquisition of sufficient conditions to start an initiative, its execution, and its monitoring and evaluation. The findings indicate that individual challenges share overlapping causes and crosscutting causal relations. Accordingly, solutions for the successful performance of OH initiatives should be implemented to tackle simultaneously different types of challenges occurring in different phases. Still, promoting collaboration between the wide diversity of stakeholders, as a fundamental aspect in the OH approach, is still by far the most challenging factor in performing OH initiatives. Causes for that are the difficulties in promoting meaningful and equal participation from diverse actors. Solutions proposed for this challenge focused on guiding stakeholders to think and collaborate beyond their professional and cultural silos to generate knowledge co-creation and innovative methodologies and frameworks. Finally, the biggest knowledge gap identified, in terms of proposed solutions, was for monitoring and evaluating OH initiatives. This highlights the need for future research on evaluation methods and tools specific for the OH approach, to provide credible evidence on its added value. When considering challenges endured by former OH initiatives and the proposed solutions for these challenges, practitioners should be able to plan and structure such initiatives in a more successful way, through the strategic pre-consideration of solutions or simply by avoiding known barriers.

The COMPARE Data Hubs

Data sharing enables research communities to exchange findings and build upon the knowledge that arises from their discoveries. Areas of public and animal health as well as food safety would benefit from rapid data sharing when it comes to emergencies. However, ethical, regulatory and institutional challenges, as well as lack of suitable platforms which provide an infrastructure for data sharing in structured formats, often lead to data not being shared or at most shared in form of supplementary materials in journal publications. Here, we describe an informatics platform that includes workflows for structured data storage, managing and pre-publication sharing of pathogen sequencing data and its analysis interpretations with relevant stakeholders.

Towards improved process efficiency in vaccine innovation: The Vaccine Innovation Cycle as a validated, conceptual stage-gate model

Continuing investments in vaccine innovation are insufficiently translated into market entries of novel vaccines. This innovation paradox is in part caused by stakeholders lacking complete understanding of the complex array of steps necessary for vaccine development and collaboration difficulties between the wide variety of stakeholders involved. Models providing cross-domain understanding can improve collaboration but currently lack both comprehensibility and granularity to enable a prioritized view of activities and criteria. Key opinion leaders (KOLs) were asked to contribute to the definition of a vaccine innovation cycle (VIC). In a first step, 18 KOLs were interviewed on the stages (activities and results) and gates (evaluation criteria and outcomes) of vaccine innovation. This first description of the VIC was subsequently validated and refined through a survey among 46 additional KOLs. The VIC identifies 29 distinct stages and 28 corresponding gates, distributed in ten different but integrated workstreams, and comprehensibly depicted in a circular innovation model. Some stage-gates occur at defined moments, whereas the occurrence and timing of other stage-gates is contingent on a variety of contextual factors. Yet other stage-gates continuously monitor internal and external developments. A gap-overlap analysis of stage-gate criteria demonstrated that 5 out of 11 criteria employed by vaccine developers correspond with criteria employed by competent (regulatory) authorities. The VIC provides a comprehensive overview of stage-gates throughout the value chain of vaccine innovation. Its cyclical nature highlights the importance of synchronizing with unmet needs and market changes, and conceptualizes the difference between incremental and radical vaccine innovation. Knowledge on the gap between internal and external criteria will enhance the viability of newcomers to the field. The VIC can be used by stakeholders to improve understanding and communication in forming collaborative alliances and consortia. Such a boundary-spanning function may contribute to the reduction of process inefficiencies, especially in public-private partnerships.