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Active H2020 European Commission

Predicting the Impact of Monoclonal Antibodies & Vaccines on Antimicrobial Resistance

€9.25M EUR

Funder European Commission
Recipient Organization European Vaccine Initiative E.V
Country Germany
Start Date Nov 01, 2021
End Date Oct 31, 2026
Duration 1,825 days
Number of Grantees 17
Roles Participant; Coordinator
Data Source European Commission
Grant ID 101034420
Grant Description

Antibiotic resistance (AMR), a major threat to human health, is increasing in all bacteria through antibiotic-induced selection, cross-species transfer of genetic mobile elements harbouring resistance genes, global transport and environmental waste.

With an almost empty antibiotic pipeline, monoclonal antibodies (mAbs) and vaccines are increasingly recognized as important tools against AMR.

Yet, available resources cannot finance all potential interventions, and choices need to be made according to costs of mAbs and vaccines, impact on the burden of AMR and prevention of its economic consequences.

The PrIMAVeRa consortium will develop a web-based platform that combines advanced mathematical models with a comprehensive epidemiological repository.

Systematic reviews will generate data to inform the model structure and parametrisation and select the most appropriate models for determining the AMR burden by pathogen, infection and target population.

Deterministic continuous time models (ordinary differential equations [ODE]) and stochastic discrete time individual-based models with multiple modules will cover all relevant aspects of AMR, while Bayesian approaches will be used for cost-effectiveness analysis. The models will be calibrated in 8 EU countries based on the data coming from health information systems.

The PrIMAVeRa consortium comprises a prominent collection of European research groups with expertise in AMR, vaccines, mAbs, mathematical and economical modelling.

The proposal builds on established research collaborations and existing research infrastructures from EU- and IMI-funded research projects, such as EPI-Net (COMBACTE-MAGNET) and CLIN-Net and LAB-Net (COMBACTE-NET).

The major deliverable will be an open access web-based user interface that will allow the wider scientific community to freely access and apply the models.

This platform will also help healthcare authorities to make data-driven decisions on which vaccines and mAbs should be prioritised.

All Grantees

Pfizer Limited; Universita Degli Studi Di Verona; Universite de Geneve; Instituto de Salud Carlos Iii; Lietuvos Sveikatos Mokslu Universiteto Ligonine Kauno Klinikos; Glaxosmithkline Biologicals Sa; Department of Health; Universite Grenoble Alpes; Universitair Medisch Centrum Utrecht; Institut Pasteur; Danmarks Tekniske Universitet; Janssen Vaccines & Prevention Bv; European Vaccine Initiative E.V; The Chancellor, Masters and Scholars of the University of Oxford; Servicio Andaluz de la Salud; Eberhard Karls Universitaet Tuebingen; Life Science Network Ggmbh

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