Optimality in COVID-19 vaccination strategies determined by heterogeneity in human-human interaction networks


Interactions between humans cause transmission of SARS-CoV-2. We demonstrate that heterogeneity in human-human interactions give rise to non-linear infection networks that gain complexity with time. Consequently, targeted vaccination strategies are challenged as such effects are not accurately captured by epidemiological models assuming homogeneous mixing. With vaccines being prepared for global deployment determining optimality for swiftly reaching population level immunity in heterogeneous local communities world-wide is critical. We introduce a model that predicts the effect of vaccination into an ongoing COVID-19 outbreak using precision simulation of human-human interaction and infection networks. We show that simulations incorporating non-linear network complexity and local heterogeneity can enable governance with performance-quantified vaccination strategies. Vaccinating highly interactive people diminishes the risk for an infection wave, while vaccinating the elderly reduces fatalities at low population level immunity. Interestingly, a combined strategy is not better due to non-linear effects. While risk groups should be vaccinated first to minimize fatalities, significant optimality branching is observed with increasing population level immunity. Importantly, we demonstrate that regardless of immunization strategy non-pharmaceutical interventions are required to prevent ICU overload and breakdown of healthcare systems. The approach, adaptable in real-time and applicable to other viruses, provides a highly valuable platform for the current and future pandemics.

SEEK ID: https://seek.lisym.org/publications/290

Projects: LiSyM Pillar I: Early Metabolic Injury (LiSyM-EMI)

Publication type: Unpublished

Journal: Nature Biotechnology


Date Published: No date defined


Registered Mode: manually

Authors: Bjoern Goldenbogen, Stephan O. Adler, Oliver Bodeit, Judith AH Wodke, Ximena Escalera-Fanjul, Aviv Korman, Maria Krantz, Lasse Bonn, Rafael U Morán-Torres, Johanna E L Haffner, Maxim Karnetzki, Ivo Maintz, Lisa Mallis, Patrick S Segelitz, Martin Seeger, Rune Linding, Edda Klipp

help Creator
Not specified

Views: 24

Created: 7th Jan 2021 at 19:22

help Attributions


Related items

Powered by
Copyright © 2008 - 2020 The University of Manchester and HITS gGmbH