BELGIAN PANDEMIC INTELLIGENCE NETWORK
The project will lay the foundations for some key aspects essential for an effective pandemic intelligence network. The project will identify the current gaps in data and information preparedness, validation and interpretation facilitating the monitoring of an epidemic (WP1 Collaborative Surveillance). In direct support of policy makers, the project will establish an advanced analytical and modelling framework that generates the up-to-date epidemiological information they need for policy development, communication and justification (WP2 Advanced Analytics and Modelling). BE-PIN further contributes to a comprehensive theoretical framework for evidence-based pandemic management in the Belgian context and to the feasibility of quantifying carefully selected indicators indicating the impact on different sectors of the society (WP3 Evidence-based Policy Making).
Transversal to these three topics we dive into general capabilities indispensable for collaboration with and within the network. Communication practices for knowledge transfer during the COVID-19 crisis will be mapped and analysed to generate recommendations for effective knowledge brokering (WP4 Improving Communication Practices). Finally, the governance of such a network will be investigated, more importantly the organisation of it and the legal operation (WP5 Governance of the Pandemic Intelligence Network).
Throughout the project, stakeholder engagement, co-creation, international benchmarking and the anticipation of various pathogens and epidemic scenarios will be the main pathways to improved preparedness capacity.
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Project duration: December 2023 - February 2027
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Project Structure
WP6
Impact Plan
WP7
Project Management
WORK PACKAGE 1
COLLABORATIVE SURVEILLANCE
WP Leads: Brecht Ingelbeen (ITM), Toon Braeye (Sciensano)
According to the WHO, a core prerequisite to strengthen health emergency preparedness, response, and resilience, is the establishment of collaborative capacities to predict, identify, and assess infectious disease risks and monitor prevention or control response. Collaboration is needed
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across disease and threat surveillance systems for a more comprehensive understanding of the epidemiological situation across systems for monitoring hazards, threats, and vulnerabilities,
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across sectors, extending to One Health or other non-health sectors (eg, education, transport, security, and industry),
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across emergency cycles: routine monitoring and early warning of emerging events, but also intelligence throughout health emergency prevention and risk mitigation, preparedness, response, and recovery,
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across geographical levels.
BE-PIN’s main objective in this respect is to establish effective collaborative surveillance for (re-)emerging pathogens or antimicrobial resistance in the Belgian context.
Research objectives:​
identify information needs across stakeholders and related data gaps by priority epidemic and pandemic scenario
evaluate whether and how existing core and enhanced surveillance data can respond to these information needs
identify and validate risk surveillance data sources responding to epi/pandemic information gaps
develop and validate epi/pandemic scenario-specific epidemic intelligence reports defining threat/hazard/disease indicators to generate, data sources to generate indicators from and indicator thresholds generating signals
inform the set-up for essential prospective data collection during pandemics such as sero-surveys, case or household information
WORK PACKAGE 2
ADVANCED ANALYTICS AND MODELLING
WP Leads: Niel Hens (UHasselt), Simon Dellicour (ULB)
Another key aspect in responding to a pandemic is gaining insight in the (emerging) pathogen, its transmission route and the resulting epidemic scenario at hand, through advanced analytics and modelling. In such a context, studies are designed to understand the dispersal dynamics and inform on key epidemiological characteristics of an emerging pathogen X. Furthermore, the impact of certain response measures can be modelled such that policymakers can get timely insights into their degree of effectiveness and epidemiological relevance.
Research objectives:​
evaluate collaboratively the data analyses performed in the context of the COVID-19 epidemic in Belgium in regard to what has been performed internationally, including the identification of missed analytical opportunities
develop a comprehensive analytical framework designed in a time-line configuration prioritising the epidemiological analyses that can be carried out at different stages of a new outbreak (pathogen X)
implement an analytical procedure allowing the evaluation/validation of the predictive performance of epidemiological models used for short and mid-term projections
initiate a scientific community of modellers
WORK PACKAGE 3
ENABLING COMPREHENSIVE EVIDENCE-BASED POLICY MAKING
WP Leads: Philippe Beutels (UAntwerp), Mathias Dewatripont (ULB)
Going one step further, comprehensive evidence-based policy making requires the joint consideration of diverse population-level impacts on indicators of health, health care capacity and economic activity (i.e. “optimisation targets”), while safeguarding public trust. To this end, the team aims to specify a multicriteria theoretical framework for evidence-based pandemic management facilitating decisions on the prioritisation of options for pharmaceutical and non-pharmaceutical intervention. The team will assess the feasibility of such a framework and its constraints in the Belgian context for pathogen X.
Research objectives:​
identify, articulate and elicit preferences for optimisation targets, with attention to differences in preferences between the general population and stakeholders
analyse the impact of social contact modifications across various demographic groups on supply and demand patterns both directly from policy interventions and indirectly through production and consumption linkages across Belgian and international sector-regions
analyse existing and create updated templates for individual-level data coupling on infection and vaccination per NACEBEL sector, to propose sufficiently performant data formats to examine absenteeism patterns for pandemic management from occupational health service provider data
analyse the evolution of infection and absenteeism per economic sector in Belgium (including client-intensive vulnerable sectors like health care, education, and travel) and their relationships
review and assess the feasibility of jointly integrating in dynamic transmission models multiple outcomes relating to mortality, QALYs, health care usage and macroeconomic impact in Belgium in real time
formulate recommendations to balance impacts on the economy, society, health care and population health, in anticipation of and during a next pandemic
WORK PACKAGE 4
IMPROVING COMMUNICATION PRACTICES
WP Lead: David Domingo (ULB)
Transversal to the above-mentioned topics it’s paramount to have effective communication practices inside the pandemic intelligence network and with the different stakeholders it will engage with. Empirical studies on the management of the COVID-19 crisis in different countries indicate that the lack of adequate communication strategies was a key factor hindering the use of scientific evidence in policy-making. In order to address the analysis of the Belgian case and guide the co-creation of communication protocols for BE-PIN, the team will use the concept of knowledge brokering . While the analysis will especially focus on the communication between scientists and policy, it is not detached from the public sphere. A critical perspective on the infodemic surrounding COVID-19 will inform the teams’ approach, and the teams’ co-creation processes will be designed to be inclusive, inspired by the state of the art of participatory policy-making.
Research objectives:​
map the knowledge flows in Belgium during the COVID-19 crisis, what actors produced scientific knowledge, how it circulated and what were the gaps in available knowledge
analyse the relationship between policy, expertise and society through public debate. This will assess the visibility of scientific expertise during the COVID-19 crisis, as opposed to disinformation, at three levels (governmental advisory committees, professional journalistic media and social media platforms).
take stock of the communication processes that were set up for knowledge transfer fostering evidence-informed policy-making through international benchmarking, notably during the COVID-19 crisis
explore the expectations of citizens regarding the public communication of the pandemic intelligence network, in order to enhance institutional trust and civil responsibility
involve the diversity of stakeholders that will be part of the future pandemic intelligence network in the co-creation of the communication strategies for an effective multidisciplinary cooperation. The common goal is to foster evidence-informed policy-making and accountability.
identify the training needs of the different stakeholders of the network, and co-creating with them the appropriate modules for capacity building on effective internal and external communication and knowledge transfer
WORK PACKAGE 5
GOVERNANCE OF A PANDEMIC INTELLIGENCE NETWORK
WP Lead: Shona Cosgrove (Sciensano)
Finally, the team will focus on the governance of the Belgian Pandemic Intelligence Network. The team will identify the lessons learned from the COVID-19 pandemic to investigate how the network can be organised and set up in a structured way taking into account the legal framework. During the COVID-19 pandemic different expert groups were consulted. The procedures on how these expert groups were approached and who should be in the expert groups was not always clear. Therefore, some of the expert groups had competing interests and the flow of scientific information and evidence to be used by policy makers was not ideal . Here the team will dive into this issue to see how this can be improved from an organisational perspective considering earlier recommendations. The team will investigate conceptual and structural options based on national needs and international comparison.
Research objectives:​
assess the needs and potential gaps for the governance of a Belgian Pandemic Intelligence Network including the legal, organisational and collaboration aspects
investigate structural options of such a network based on international comparison and best practices
Identify structural international partnerships essential to a performant network