Modeling and analysis of a novel two-strain dengue epidemics model considering secondary infections with increased mortality

Aytül Gökçe; Joseph Páez Chávez; Thomas Götz; Burcu Gürbüz; Aytül Gökçe; Joseph Páez Chávez; Thomas Götz; Burcu Gürbüz

doi:10.3934/era.2026364

Electronic Research Archive

2026, Volume 34, Issue 11: 8625-8649. doi: 10.3934/era.2026364

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Modeling and analysis of a novel two-strain dengue epidemics model considering secondary infections with increased mortality

1.
Faculty of Science and Letters, Department of Mathematics, Ordu University, 52200 Ordu, Türkiye
2.
Center for Applied Dynamical Systems and Computational Methods (CADSCOM), Faculty of Natural Sciences and Mathematics, Escuela Superior Politécnica del Litoral, P.O. Box 09-01-5863, Guayaquil, Ecuador
3.
Center for Dynamics, Department of Mathematics, TU Dresden, D-01062 Dresden, Germany
4.
Mathematical Institute, University of Koblenz, D-56070 Koblenz, Germany
5.
Institut für Mathematik, Johannes Gutenberg-Universität Mainz, Staudingerweg 9, 55099 Mainz, Germany
6.
Institute for Quantitative and Computational Biosciences (IQCB), Johannes Gutenberg University Mainz, 55128 Mainz, Germany

Received: 20 July 2026 Revised: 03 September 2026 Accepted: 14 September 2026 Published: 09 October 2026

In this study, we developed and analyzed a deterministic two-strain host–vector model for dengue transmission incorporating temporary cross-immunity, antibody-dependent enhancement (ADE), disease-induced mortality during secondary infections, and explicit DENV–DENV co-infection in mosquitoes. The model distinguishes primary and secondary human infections and allows co-infected mosquitoes to contribute to strain-specific transmission. We derived the basic reproduction number $ \mathcal{R}_0 $ and established the local stability of the disease-free equilibrium, while heterologous invasion of a one-strain endemic state was characterized through the corresponding invasion dynamics. Center-manifold analysis and numerical continuation revealed backward bifurcation, bistability between disease-free and endemic states, and Hopf-induced oscillations. Numerical simulations further illustrated transitions between disease-free, endemic, and periodic regimes. These results show how ADE, waning cross-immunity, and mosquito co-infection can jointly generate complex multi-strain dengue dynamics and provide a mechanistic framework for examining how the serotype composition of the vector population influences subsequent human infections.
- multi-strain modeling,
- stability,
- bifurcation analysis,
- vector co-infection,
- numerical continuation
Citation: Aytül Gökçe, Joseph Páez Chávez, Thomas Götz, Burcu Gürbüz. Modeling and analysis of a novel two-strain dengue epidemics model considering secondary infections with increased mortality[J]. Electronic Research Archive, 2026, 34(11): 8625-8649. doi: 10.3934/era.2026364

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Abstract

In this study, we developed and analyzed a deterministic two-strain host–vector model for dengue transmission incorporating temporary cross-immunity, antibody-dependent enhancement (ADE), disease-induced mortality during secondary infections, and explicit DENV–DENV co-infection in mosquitoes. The model distinguishes primary and secondary human infections and allows co-infected mosquitoes to contribute to strain-specific transmission. We derived the basic reproduction number $ \mathcal{R}_0 $ and established the local stability of the disease-free equilibrium, while heterologous invasion of a one-strain endemic state was characterized through the corresponding invasion dynamics. Center-manifold analysis and numerical continuation revealed backward bifurcation, bistability between disease-free and endemic states, and Hopf-induced oscillations. Numerical simulations further illustrated transitions between disease-free, endemic, and periodic regimes. These results show how ADE, waning cross-immunity, and mosquito co-infection can jointly generate complex multi-strain dengue dynamics and provide a mechanistic framework for examining how the serotype composition of the vector population influences subsequent human infections.

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