A minimal model coupling communicable and non-communicable diseases
Identifiers
Permanent link (URI): http://hdl.handle.net/10017/60115DOI: 10.1051/mmnp/2023026
ISSN: 0973-5348
Publisher
EDP Sciences
Date
2023-09-15Funders
Agencia Estatal de Investigación
Ministerio de Economía y Competitividad
Universidad de Alcalá
Bibliographic citation
Mavá Ruiz, M., Venturino, E. & Vera García, M.C. 2023, "A minimal model coupling communicable and non-communicable diseases", Mathematical Modelling of Natural Phenomena, vol. 18, art. no. 23, pp. 1-17.
Keywords
Non-communicable disease
Communicable disease
Basic reproduction number
Subcritical bifurcation
Heterogeneous populations
Syndemics
Project
info:eu-repo/grantAgreement/MINECO//MTM2014-56022-C2-1-P/ES/ANALISIS Y REDUCCION DE MODELOS DE DINAMICA DE POBLACIONES ESTRUCTURADAS Y APLICACIONES/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096884-B-C32/ES/DATA-DRIVEN MODELS OF FOREST DROUGHT VULNERABILITY AND RESILIENCE ACROSS SPATIAL AND TEMPORAL SCALES: APPLICATION TO THE SPANISH CLIMATE CHANGE ADAPTATION STRATEGY
info:eu-repo/grantAgreement/UAH//PIUAH22%2FCC-041
Document type
info:eu-repo/semantics/article
Version
info:eu-repo/semantics/publishedVersion
Publisher's version
https://doi.org/10.1051/mmnp/2023026Rights
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
© 2023 The authors
Access rights
info:eu-repo/semantics/openAccess
Abstract
This work presents a model combining the simplest communicable and non-communicable disease models. The latter is, by far, the leading cause of sickness and death in the World, and introduces basal heterogeneity in populations where communicable diseases evolve. The model can be interpreted as a risk-structured model, another way of accounting for population heterogeneity. Our results show that considering the non-communicable disease (in the end, a dynamic heterogeneous population) allows the communicable disease to become endemic even if the basic reproduction number is less than 1. This feature is known as subcritical bifurcation. Furthermore, ignoring the non-communicable disease dynamics results in overestimating the basic reproduction number and, thus, giving wrong information about the actual number of infected individuals. We calculate sensitivity indices and derive interesting epidemic-control information.
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