Publication
Title
Who acquires infection from whom? A sensitivity analysis of transmission dynamics during the early phase of the COVID-19 pandemic in Belgium
Author
Abstract
Age -related heterogeneity in a host population, whether due to how individuals mix and contact each other, the nature of host-pathogen interactions defining epidemiological parameters, or demographics, is crucial in studying infectious disease dynamics. Compartmental models represent a popular approach to address the problem, dividing the population of interest into a discrete and finite number of states depending on, for example, individuals' age and stage of infection. We study the corresponding linearised system whose operator, in the context of a discrete -time model, equates to a square matrix known as the next generation matrix. Performing formal perturbation analysis of the entries of the aforementioned matrix, we derive indices to quantify the age -specific variation of its dominant eigenvalue (i.e., the reproduction number) and explore the relevant epidemiological information we can derive from the eigenstructure of the matrix. The resulting method enables the assessment of the impact of age -related population heterogeneity on virus transmission. In particular, starting from an age -structured SEIR model, we demonstrate the use of this approach for COVID-19 dynamics in Belgium. We analyse the early stages of the SARS-CoV-2 spread, with particular attention to the pre -pandemic framework and the lockdown lifting phase initiated as of May 2020. Our results, influenced by our assumption on age -specific susceptibility and infectiousness, support the hypothesis that transmission was only influenced to a small extent by children in the age group [0,18) and adults over 60 years of age during the early phases of the pandemic and up to the end of July 2020.
Language
English
Source (journal)
Journal of theoretical biology. - London
Publication
London : 2024
ISSN
0022-5193
DOI
10.1016/J.JTBI.2024.111721
Volume/pages
581 (2024) , p. 1-20
Article Reference
111721
ISI
001174216000001
Pubmed ID
38218529
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
Epidemic intelligence to minimize 2019-nCoV's public health, economic and social impact in Europe (EpiPose).
Efficient and rapidly SCAlable EU-wide evidence-driven Pandemic response plans through dynamic Epidemic data assimilation (ESCAPE).
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 29.03.2024
Last edited 05.04.2024
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