ArticleHealthcare analytics (New York, N.Y.)2023
The stability analysis of a co-circulation model for COVID-19, dengue, and zika with nonlinear incidence rates and vaccination strategies.
Article in Healthcare analytics (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Exploring Zika's dynamics: A scoping review journey from epidemic to equations through mathematical modelling.Infectious Disease Modelling · 2025Review
- Dynamics of the optimality control of transmission of infectious disease: a sensitivity analysis.Scientific reports · 2024Article
- Cost-effectiveness analysis of COVID-19 intervention policies using a mathematical model: an optimal control approach.Scientific reports · 2024Article
- A fractional order Monkeypox model with protected travelers using the fixed point theorem and Newton polynomial interpolation.Healthcare analytics (New York, N.Y.) · 2023Article
- A non-linear mathematical model for analysing the impact of COVID-19 disease on higher education in developing countries.Healthcare analytics (New York, N.Y.) · 2023Article
- Analysis of a non-integer order mathematical model for double strains of dengue and COVID-19 co-circulation using an efficient finite-difference method.Scientific reports · 2023Article
- Modelling the transmission of dengue, zika and chikungunya: a scoping review protocol.BMJ open · 2023Article
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Abstract
This paper aims to study the impacts of COVID-19 and dengue vaccinations on the dynamics of zika transmission by developing a vaccination model with the incorporation of saturated incidence rates. Analyses are performed to assess the qualitative behavior of the model. Carrying out bifurcation analysis of the model, it was concluded that co-infection, super-infection and also re-infection with same or different disease could trigger backward bifurcation. Employing well-formulated Lyapunov functions, the model's equilibria are shown to be globally stable for a certain scenario. Moreover, global sensitivity analyses are performed out to assess the impact of dominant parameters that drive each disease's dynamics and its co-infection. Model fitting is performed on the actual data for the state of Amazonas in Brazil. The fittings reveal that our model behaves very well with the data. The significance of saturated incidence rates on the dynamics of three diseases is also highlighted. Based on the numerical investigation of the model, it was observed that increased vaccination efforts against COVID-19 and dengue could positively impact zika dynamics and the co-spread of triple infections.
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