Beate Jahn1, Gaby Sroczynski1, Martin Bicher2,3, Claire Rippinger2, Nikolai Mühlberger1, Júlia Santamaria1, Christoph Urach2, Michael Schomaker1,4, Igor Stojkov1, Daniela Schmid5, Günter Weiss6, Ursula Wiedermann7, Monika Redlberger-Fritz8, Christiane Druml9, Mirjam Kretzschmar10, Maria Paulke-Korinek11, Herwig Ostermann12, Caroline Czasch12, Gottfried Endel13, Wolfgang Bock14, Nikolas Popper2,3,15, Uwe Siebert1,16,17. 1. Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria. 2. dwh GmbH, dwh Simulation Services, Neustiftgasse 57-59, A-1070 Vienna, Austria. 3. Institute of Information Systems Engineering, TU Wien, Favoritenstraße 11, A-1050 Vienna, Austria. 4. Center for Infectious Disease Epidemiology and Research, University of Cape Town, Barnard Fuller Building, Anzio Rd, Observatory, Cape Town 7935, South Africa. 5. Division for Quantitative Methods in Public Health and Health Services Research, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria. 6. Department of Internal Medicine II, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria. 7. Center of Pathophysiology, Infectiology & Immunology (OEL), Institute of Specific Prophylaxis and Tropical Medicine, Medical University of Vienna, Kinderspitalgasse 15, 1090 Vienna, Austria. 8. Center of Virology, Medical University of Vienna, Kinderspitalgasse 15, 1090 Vienna, Austria. 9. UNESCO Chair on Bioethics, Medical University of Vienna, Waehringerstrasse 25, 1090 Vienna, Austria. 10. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX Utrecht, The Netherlands. 11. Ministry of Social Affairs, Health, Care and Consumer Protection, Stubenring 1, 1010 Vienna, Austria. 12. Austrian National Public Health Institute/Gesundheit Österreich GmbH, Stubenring 6, 1010 Vienna, Austria. 13. Austrian Federation of Social Insurances, Kundmanngasse 21, 1030 Vienna, Austria. 14. Department of Mathematics, TU Kaiserslautern, Gottlieb-Daimler-Straße 48, 67663 Kaiserslautern, Germany. 15. Association for Decision Support for Health Policy and Planning, DEXHELPP, Neustiftgasse 57-59, A-1070 Vienna, Austria. 16. Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 101 Merrimac St., Boston, MA 02114, USA. 17. Center for Health Decision Science, Departments of Epidemiology and Health Policy & Management, Harvard T.H. Chan School of Public Health, 718 Huntington Avenue, Boston, MA 02115, USA.
Abstract
(1) Background: The Austrian supply of COVID-19 vaccine is limited for now. We aim to provide evidence-based guidance to the authorities in order to minimize COVID-19-related hospitalizations and deaths in Austria. (2) Methods: We used a dynamic agent-based population model to compare different vaccination strategies targeted to the elderly (65 ≥ years), middle aged (45-64 years), younger (15-44 years), vulnerable (risk of severe disease due to comorbidities), and healthcare workers (HCW). First, outcomes were optimized for an initially available vaccine batch for 200,000 individuals. Second, stepwise optimization was performed deriving a prioritization sequence for 2.45 million individuals, maximizing the reduction in total hospitalizations and deaths compared to no vaccination. We considered sterilizing and non-sterilizing immunity, assuming a 70% effectiveness. (3) Results: Maximum reduction of hospitalizations and deaths was achieved by starting vaccination with the elderly and vulnerable followed by middle-aged, HCW, and younger individuals. Optimizations for vaccinating 2.45 million individuals yielded the same prioritization and avoided approximately one third of deaths and hospitalizations. Starting vaccination with HCW leads to slightly smaller reductions but maximizes occupational safety. (4) Conclusion: To minimize COVID-19-related hospitalizations and deaths, our study shows that elderly and vulnerable persons should be prioritized for vaccination until further vaccines are available.
(1) Background: The Austrian supply of COVID-19 vaccine is limited for now. We aim to provide evidence-based guidance to the authorities in order to minimize COVID-19-related hospitalizations and deaths in Austria. (2) Methods: We used a dynamic agent-based population model to compare different vaccination strategies targeted to the elderly (65 ≥ years), middle aged (45-64 years), younger (15-44 years), vulnerable (risk of severe disease due to comorbidities), and healthcare workers (HCW). First, outcomes were optimized for an initially available vaccine batch for 200,000 individuals. Second, stepwise optimization was performed deriving a prioritization sequence for 2.45 million individuals, maximizing the reduction in total hospitalizations and deaths compared to no vaccination. We considered sterilizing and non-sterilizing immunity, assuming a 70% effectiveness. (3) Results: Maximum reduction of hospitalizations and deaths was achieved by starting vaccination with the elderly and vulnerable followed by middle-aged, HCW, and younger individuals. Optimizations for vaccinating 2.45 million individuals yielded the same prioritization and avoided approximately one third of deaths and hospitalizations. Starting vaccination with HCW leads to slightly smaller reductions but maximizes occupational safety. (4) Conclusion: To minimize COVID-19-related hospitalizations and deaths, our study shows that elderly and vulnerable persons should be prioritized for vaccination until further vaccines are available.
Authors: Richard Pitman; David Fisman; Gregory S Zaric; Maarten Postma; Mirjam Kretzschmar; John Edmunds; Marc Brisson Journal: Med Decis Making Date: 2012 Sep-Oct Impact factor: 2.583
Authors: Jennifer M Dan; Jose Mateus; Yu Kato; Kathryn M Hastie; Esther Dawen Yu; Caterina E Faliti; Alba Grifoni; Sydney I Ramirez; Sonya Haupt; April Frazier; Catherine Nakao; Vamseedhar Rayaprolu; Stephen A Rawlings; Bjoern Peters; Florian Krammer; Viviana Simon; Erica Ollmann Saphire; Davey M Smith; Daniela Weiskopf; Alessandro Sette; Shane Crotty Journal: Science Date: 2021-01-06 Impact factor: 47.728