PuSH - Publication Server of Helmholtz Zentrum München

Sticha, C.* ; Picasso, F.* ; Kuttler, C.* ; Hoelscher, M. ; Wieser, A.* ; Castelletti, N.

A general deterministic model of ordinary differential equations for a broad variety of different diseases.

Chaos Solitons Fractals 188:115475 (2024)
Publ. Version/Full Text DOI
Open Access Hybrid
Creative Commons Lizenzvertrag
The COVID-19 pandemic underscored the pivotal role of mathematical models in comprehending pandemic dynamics and making accurate predictions under diverse interventions. Various mathematical models, particularly deterministic ones, have proven valuable for analyzing the impact of political, social, and medical measures during ongoing pandemics. In this study, we aim to formulate and characterize a comprehensive model applicable to different infectious diseases. Reviewing numerous disease-specific models reveals a common foundation in the Kermack–McKendrick model (SIR model). While there are more general versions incorporating population dynamics, vector populations, and vaccination, none encompass all attributes simultaneously. To address this gap, we propose a comprehensive general model capable of accommodating different transmission modes, pandemic control measures, and diverse pathogens. Unlike disease-specific models, having such a pre-established model with foundational mathematical properties analyzed eliminates the need to reevaluate these characteristics for each new disease-specific model. This article presents our comprehensive general model, supported by mathematical analysis and numerical simulations, offering a versatile tool for understanding the dynamics of emerging infectious diseases and guiding intervention strategies. The applicability of the model is demonstrated through simulations.
Impact Factor
Scopus SNIP
Altmetric
5.300
1.802
Tags
Annotations
Special Publikation
Hide on homepage

Edit extra information
Edit own tags
Private
Edit own annotation
Private
Hide on publication lists
on hompage
Mark as special
publikation
Publication type Article: Journal article
Document type Scientific Article
Keywords Compartmental Model ; Epidemic Control ; General Epidemic Model ; Numerical Simulation ; Ordinary Differential Equations ; Reproduction Rate; Dynamics
Language english
Publication Year 2024
HGF-reported in Year 2024
ISSN (print) / ISBN 0960-0779
e-ISSN 0960-0779
Quellenangaben Volume: 188, Issue: , Pages: , Article Number: 115475 Supplement: ,
Publisher Elsevier
Publishing Place The Boulevard, Langford Lane, Kidlington, Oxford Ox5 1gb, England
Reviewing status Peer reviewed
Institute(s) Institute of Radiation Medicine (IRM)
Research Unit Global Health (UGH)
POF-Topic(s) 30203 - Molecular Targets and Therapies
30205 - Bioengineering and Digital Health
Research field(s) Radiation Sciences
Enabling and Novel Technologies
PSP Element(s) G-501391-001
G-540001-003
Grants German Federal Ministry of Education and Research (BMBF)
Scopus ID 85203185501
Erfassungsdatum 2024-09-12