Project description DEENESFRITPL New policy design to reduce antibiotic resistance Antibiotics represent a huge step in human disease treatment, but their increased use promotes the development of resistant bacteria. According to the World Health Organization, resistance to antibiotics is a major global threat associated with 700 000 deaths per year due to untreatable infections. The design of new policies for the supply and demand of existing and new drugs is needed. The EU-funded ABRSEIST project intends to identify and assess feasible and efficient demand-side policy interventions that address physicians and patients. The project will use a broad econometric set of software tools to detect mechanisms connecting antibiotic resistance and consumption. Using machine learning methods and econometric analyses, ABRSEIST will provide strong evidence on effective intervention designs improving our understanding of prescribing, resistance and antibiotic use. Show the project objective Hide the project objective Objective Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing. Fields of science social scienceseconomics and businesseconomicseconometricsmedical and health scienceshealth sciencespublic healthmedical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugsantibioticsnatural sciencescomputer and information sciencesartificial intelligencemachine learningmedical and health sciencesbasic medicinepharmacology and pharmacydrug resistanceantibiotic resistance Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-2018-STG - ERC Starting Grant Call for proposal ERC-2018-STG See other projects for this call Funding Scheme ERC-STG - Starting Grant Host institution DEUTSCHES INSTITUT FUR WIRTSCHAFTSFORSCHUNG DIW (INSTITUT FUR KONJUNKTURFORSCHUNG) EV Net EU contribution € 903 996,25 Address MOHRENSTRASSE 58 10117 Berlin Germany See on map Region Berlin Berlin Berlin Activity type Research Organisations Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 903 996,25 Beneficiaries (2) Sort alphabetically Sort by Net EU contribution Expand all Collapse all DEUTSCHES INSTITUT FUR WIRTSCHAFTSFORSCHUNG DIW (INSTITUT FUR KONJUNKTURFORSCHUNG) EV Germany Net EU contribution € 903 996,25 Address MOHRENSTRASSE 58 10117 Berlin See on map Region Berlin Berlin Berlin Activity type Research Organisations Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 903 996,25 KOBENHAVNS UNIVERSITET Denmark Net EU contribution € 594 923,75 Address NORREGADE 10 1165 Kobenhavn See on map Region Danmark Hovedstaden Byen København Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 594 923,75
