Periodic Reporting for period 1 - LEAPS (Integrating Multi-Disciplinary Expertise in a Learning and Adaptive European Pandemic Preparedness System)
Reporting period: 2023-10-01 to 2025-03-31
LEAPS aims to demonstrate the value and feasibility of a proactive policy-supporting strategy for genomic surveillance and for pandemic preparedness and response. It aims to deliver a system-wide stakeholder-validated proof of concept (PoC), of a proactive policy-supporting strategy for pandemic preparedness system against Pathogen X., LEAPS explores combining genomic One Health surveillance with modeling for detailed pathogen understanding, surveillance and precise public health intervention design through the establishment of an interconnected system.
LEAPS will respond to the identified needs for adequate speed, scale, effectiveness, and equity of response to reduce the time lost and reduce the severity of infections but it will also go beyond this by anticipating exacerbating factors for disease emergence or spread, and thereby creating more resilient health systems, all backed by validated system models.
LEAPS brings together a unique multi- and trans-disciplinary team with optimal complementary expertise and experience. LEAPS interacts regularly with medical and scientific communities, HERA, and health authorities. During non-emergency periods, LEAPS will validate a roadmap for large-scale implementation of LEAPS methodology.
LEAPS follows three cycles, each cycle represented by one pathogen: SARS-CoV-2, zoonotic influenza viruses, and West Nile virus. The aim of these cycles is to test new technologies, methodologies, and approaches against three different types of pathogens, with focus on learning from experiences related to each pathogen towards Pathogen X.
LEAPS will respond to the identified needs for adequate speed, scale, effectiveness, and equity of response to reduce the time lost and reduce the severity of infections but it will also go beyond this by anticipating exacerbating factors for disease emergence or spread, and thereby creating more resilient health systems, all backed by validated system models.
LEAPS brings together a unique multi- and trans-disciplinary team with optimal complementary expertise and experience. LEAPS interacts regularly with medical and scientific communities, HERA, and health authorities. During non-emergency periods, LEAPS will validate a roadmap for large-scale implementation of LEAPS methodology.
LEAPS follows three cycles, each cycle represented by one pathogen: SARS-CoV-2, zoonotic influenza viruses, and West Nile virus. The aim of these cycles is to test new technologies, methodologies, and approaches against three different types of pathogens, with focus on learning from experiences related to each pathogen towards Pathogen X.
During the first year, novel approaches were explored and evaluated.
WP1 developed and validated novel genomic surveillance methods by 1) applying non-targeted sequencing techniques in wastewater-based surveillance; 2) conducting a comparative study of targeted versus untargeted viral detection to inform recommendations for optimal surveillance; and 3) initiated a cross-national mapping exercise to understand the landscape for surveillance innovation.
First, WP2 set up a set up a pilot project to monitor seroprevalence in response to SARS-CoV-2 in the general population. They assessed the impact on the population of Ile-de-France (12 million inhabitants) of the visit to Paris during the Olympic Games by people from the southern hemisphere. The outcomes include sero-surveillance datasets and vaccination quantification. The collection set up offered new insights regarding the use of networks, logistics and ethical and regulatory procedures. These can be reactivated at local, regional or national level within a short timeframe of less than 2 weeks at local level, 3 weeks at regional level and 4 weeks at national level in the event of an epidemic which is useful in preparation of Pathogen X. Secondly, basing itself on samples from wastewater WP1, WP2 developed diagnostics for environmental samples as an exercise to study complementary approaches to strengthen public health preparedness and response efforts in a One Health approach. Antigenic assays have been also processed at IPP on wastewater or air samples using collecting filters or from sewers using soft matter smears on swab. Finally, they have also designed semi-automated and rapid assays to measure viral infectivity and neutralizing activity of sera and monoclonal antibodies.
WP3 developed a modelling paradigm that incorporates data from past epidemics to contrast forecasts that update as new data become available, following a real-time approach to forecasting. This is especially helpful when disease dynamics change rapidly. WP3 aims also to better understand the introduction and dispersal dynamics of the main variants –of concern (VOCs) of SARS-CoV-2 using a combination of phylogenetic and phylogeographic models in a Bayesian inference framework known as BEAST. This aims to study driving and limiting factors of viral spread during an epidemic / pandemic, as well as determining the factors that impact the geographical dispersal of a pathogen. Finally, WP3 investigates the accuracy of using phylogenetic inferences and contact tracing to determine local transmission clusters and its possible complimentary method.
WP4 has been capturing the indicators that determine a health emergency threat by creating a causal loop diagram (CLD). The method identifies feedback structures and includes the key characteristics of countermeasure surveillance systems, weighing the differences between a centralised and a decentralised approach. As the CLD emerges, gaps are identified, which particularly affect interoperability across the EU and Switzerland. The CLD is also used to inform where lessons learned from previous pandemics can be incorporated. From this CLD emerges a stock and flow diagram, which will be further expanded in the upcoming months.
WP5 first established a biobank infrastructure to develop a cell culturing system for SARS-CoV-2 in the BSL3 facility of the Diagnostic Department of HPI using Vero e6 cells. The isolated virus, together with clinical samples, may be used as reference material to assist with testing the assays developed by WP5 throughout the LEAPS program. As part of archiving data, WP5 also generated a timeline of events from key informing moments during the COVID-19 pandemic and also collected key demographic data from 250 patients from COVID-19 referral positive cases in 2020. WP5 will further test the feasibility of biobanking samples from WP1, wastewater samples, and WP2, plasma samples. Additionally, WP5 generated SARS-CoV-2 VLPs and pseudo viruses expressing S’s the Spike protein and accompanied these with the adapted procedures and visualization methods. Finally, HPI biochemists carried out in silico computational analysis of the key structural SARS-CoV-2 membrane protein and mapped all the structural and regulatory elements encountered in its amino acid sequence, using robust bioinformatics tools. They conducted a comparative analysis which revealed evolutionary changes between SAR-CoV-1 and SARS-CoV-2.
WP6 has been leveraging literature reviews, timeline of events, collaboration with other projects, and interviews to develop a conceptual model using CLDs and stock-and-flow diagrams (SFDs) to improve the understanding of mechanisms of responses to policies and measures implemented. To understand the different strategies for response, WP6 initiated learning meetings to uncover the state-of-the-art of current practices, technologies and methodologies as well as assess their underlying potential for innovation and impact. Mapping these feedback mechanisms offers insights on resulting health and socio-economic impacts and sustainable response strategies.
WP7 determined the key communication challenges experienced between healthcare professionals, policymakers and academia as a way to explore knowledge gaps, understand mechanisms driving misunderstandings and mis-disinformation. The main outcomes highlight the need for understanding the different role and responsibilities involved in pandemic response as well as the multiplicity of elements that must be weighed during the decision-making process which may go beyond epidemiology indicators. Regarding dis-misinformation, uncertainty and difficult access-to-data, leveraging real-time data infrastructure and research networks help mind the information gap, offering more space for dialogue and less space for speculation.
WP1 developed and validated novel genomic surveillance methods by 1) applying non-targeted sequencing techniques in wastewater-based surveillance; 2) conducting a comparative study of targeted versus untargeted viral detection to inform recommendations for optimal surveillance; and 3) initiated a cross-national mapping exercise to understand the landscape for surveillance innovation.
First, WP2 set up a set up a pilot project to monitor seroprevalence in response to SARS-CoV-2 in the general population. They assessed the impact on the population of Ile-de-France (12 million inhabitants) of the visit to Paris during the Olympic Games by people from the southern hemisphere. The outcomes include sero-surveillance datasets and vaccination quantification. The collection set up offered new insights regarding the use of networks, logistics and ethical and regulatory procedures. These can be reactivated at local, regional or national level within a short timeframe of less than 2 weeks at local level, 3 weeks at regional level and 4 weeks at national level in the event of an epidemic which is useful in preparation of Pathogen X. Secondly, basing itself on samples from wastewater WP1, WP2 developed diagnostics for environmental samples as an exercise to study complementary approaches to strengthen public health preparedness and response efforts in a One Health approach. Antigenic assays have been also processed at IPP on wastewater or air samples using collecting filters or from sewers using soft matter smears on swab. Finally, they have also designed semi-automated and rapid assays to measure viral infectivity and neutralizing activity of sera and monoclonal antibodies.
WP3 developed a modelling paradigm that incorporates data from past epidemics to contrast forecasts that update as new data become available, following a real-time approach to forecasting. This is especially helpful when disease dynamics change rapidly. WP3 aims also to better understand the introduction and dispersal dynamics of the main variants –of concern (VOCs) of SARS-CoV-2 using a combination of phylogenetic and phylogeographic models in a Bayesian inference framework known as BEAST. This aims to study driving and limiting factors of viral spread during an epidemic / pandemic, as well as determining the factors that impact the geographical dispersal of a pathogen. Finally, WP3 investigates the accuracy of using phylogenetic inferences and contact tracing to determine local transmission clusters and its possible complimentary method.
WP4 has been capturing the indicators that determine a health emergency threat by creating a causal loop diagram (CLD). The method identifies feedback structures and includes the key characteristics of countermeasure surveillance systems, weighing the differences between a centralised and a decentralised approach. As the CLD emerges, gaps are identified, which particularly affect interoperability across the EU and Switzerland. The CLD is also used to inform where lessons learned from previous pandemics can be incorporated. From this CLD emerges a stock and flow diagram, which will be further expanded in the upcoming months.
WP5 first established a biobank infrastructure to develop a cell culturing system for SARS-CoV-2 in the BSL3 facility of the Diagnostic Department of HPI using Vero e6 cells. The isolated virus, together with clinical samples, may be used as reference material to assist with testing the assays developed by WP5 throughout the LEAPS program. As part of archiving data, WP5 also generated a timeline of events from key informing moments during the COVID-19 pandemic and also collected key demographic data from 250 patients from COVID-19 referral positive cases in 2020. WP5 will further test the feasibility of biobanking samples from WP1, wastewater samples, and WP2, plasma samples. Additionally, WP5 generated SARS-CoV-2 VLPs and pseudo viruses expressing S’s the Spike protein and accompanied these with the adapted procedures and visualization methods. Finally, HPI biochemists carried out in silico computational analysis of the key structural SARS-CoV-2 membrane protein and mapped all the structural and regulatory elements encountered in its amino acid sequence, using robust bioinformatics tools. They conducted a comparative analysis which revealed evolutionary changes between SAR-CoV-1 and SARS-CoV-2.
WP6 has been leveraging literature reviews, timeline of events, collaboration with other projects, and interviews to develop a conceptual model using CLDs and stock-and-flow diagrams (SFDs) to improve the understanding of mechanisms of responses to policies and measures implemented. To understand the different strategies for response, WP6 initiated learning meetings to uncover the state-of-the-art of current practices, technologies and methodologies as well as assess their underlying potential for innovation and impact. Mapping these feedback mechanisms offers insights on resulting health and socio-economic impacts and sustainable response strategies.
WP7 determined the key communication challenges experienced between healthcare professionals, policymakers and academia as a way to explore knowledge gaps, understand mechanisms driving misunderstandings and mis-disinformation. The main outcomes highlight the need for understanding the different role and responsibilities involved in pandemic response as well as the multiplicity of elements that must be weighed during the decision-making process which may go beyond epidemiology indicators. Regarding dis-misinformation, uncertainty and difficult access-to-data, leveraging real-time data infrastructure and research networks help mind the information gap, offering more space for dialogue and less space for speculation.