Please use this identifier to cite or link to this item: doi:10.22028/D291-40457
Title: Heterogeneity matters: Contact structure and individual variation shape epidemic dynamics
Author(s): Großmann, Gerrit
Backenköhler, Michael
Wolf, Verena
Language: English
Title: PloS One
Volume: 16
Issue: 7
Publisher/Platform: Plos
Year of Publication: 2021
DDC notations: 004 Computer science, internet
Publikation type: Journal Article
Abstract: In the recent COVID-19 pandemic, mathematical modeling constitutes an important tool to evaluate the prospective effectiveness of non-pharmaceutical interventions (NPIs) and to guide policy-making. Most research is, however, centered around characterizing the epidemic based on point estimates like the average infectiousness or the average number of contacts. In this work, we use stochastic simulations to investigate the consequences of a population’s heterogeneity regarding connectivity and individual viral load levels. Therefore, we translate a COVID-19 ODE model to a stochastic multi-agent system. We use contact networks to model complex interaction structures and a probabilistic infection rate to model individual viral load variation. We observe a large dependency of the dispersion and dynamical evolution on the population’s heterogeneity that is not adequately captured by point estimates, for instance, used in ODE models. In particular, models that assume the same clinical and transmission parameters may lead to different conclusions, depending on different types of heterogeneity in the population. For instance, the existence of hubs in the contact network leads to an initial increase of dispersion and the effective reproduction number, but to a lower herd immunity threshold (HIT) compared to homogeneous populations or a population where the heterogeneity stems solely from individual infectivity variations.
DOI of the first publication: 10.1371/journal.pone.0250050
URL of the first publication: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0250050
Link to this record: urn:nbn:de:bsz:291--ds-404579
hdl:20.500.11880/36352
http://dx.doi.org/10.22028/D291-40457
ISSN: 1932-6203
Date of registration: 1-Sep-2023
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Verena Wolf
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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