Understanding dengue fever dynamics: a study of seasonality in vector-borne disease models

Rocha, Filipe; Mateus, Luís; Skwara, Urszula; Aguiar, Maíra; Stollenwerk, Nico

doi:10.1080/00207160.2015.1050961

Cited by 36 publications

(34 citation statements)

References 27 publications

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“…On the contrary, including vectorial transmission or a compartment for asymptomatic infections did not seem to improve the model fit despite the additional complexity. The non-utility of including vectorial components has been observed by several authors previously [29, 61, 62]. Mathematical analyses have suggested that because the time scale of the mosquito epidemiology is so fast compared to that in humans, it will be slaved by the slower human epidemiology.…”

Section: Discussionmentioning

confidence: 99%

“…Mathematical analyses have suggested that because the time scale of the mosquito epidemiology is so fast compared to that in humans, it will be slaved by the slower human epidemiology. Thus, for understanding human disease epidemiology, mainly the dynamics of the human time scale are essential and inclusion of mosquito dynamics results in an unnecessary increase in model complexity when vector data is not available [63, 61, 62]. The main effect of mosquito dynamics is captured in our model by the seasonal forcing.…”

Section: Discussionmentioning

confidence: 99%

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Dengue modeling in rural Cambodia: statistical performance versus epidemiological relevance

Champagne

Rácz

et al. 2017

Preprint

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17Dengue dynamics are shaped by the complex interplay between several factors, including 18 vector seasonality, interaction between four virus serotypes, and inapparent infections. 19However, paucity or quality of data do not allow for all of these to be taken into account 20 in mathematical models. In order to explore separately the importance of these factors in 21 models, we combined surveillance data with a local-scale cluster study in the rural province two-strain models with interacting effects and the lack of added value of incorporating 32 vector and explicit asymptomatic components.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Dengue modeling in rural Cambodia: statistical performance versus epidemiological relevance

Champagne

Rácz

et al. 2017

Preprint

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“…The disease‐induced death rate during and after treatment is not too high. When an individual is infected with one of the types of the fever and infected with another serotype, the individual conditions become complicated, which could result to death …”

Section: Introductionmentioning

confidence: 99%

On the co‐infection of dengue fever and Zika virus

Bonyah

Khan

Okosun

et al. 2019

Optim Control Appl Methods

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Summary In this paper, we present a co‐infection mathematical model for dengue‐Zika disease in order to carry out their synergistic relationship in the presence of prevention and treatment. Submodel analysis is investigated to establish the reproduction numbers for each disease and to determine the disease‐free local stability equilibrium status. The endemic disease equilibrium is investigated using bifurcation analysis and shows backward bifurcation. We use Pontryagin's maximum principle to explore and determine the best optimal strategies to control both diseases. Numerical optimal control analysis indicates that effective prevention and treatment of each disease will help in the effective control and eradication of the diseases. Finally, the control of co‐infection of dengue‐Zika requires that communities should combine both prevention and treatment associated with each disease at the same time.

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“…For several years, mathematical modeling is an important tool in epidemiology and dynamics. A series of different models for Dengue fever including stochastic and deterministic models, fractional differential equations, the effect of climate to the mosquito has been proposed; see, eg, previous studies and references therein. Of course, there are also many models and far too many to have a comprehensive list; for other arboviruses like Malaria and Chikungunya, which are comparable, see, eg, Abboubakar et al, Agusto, Cannon and Galiffa, and Cruz‐Pacheco et al…”

Section: Introductionmentioning

confidence: 99%

Optimal control and basic reproduction numbers for a compartmental spatial multipatch dengue model

Böck

Jayathunga

2018

Math Methods in App Sciences

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Dengue is a vector-borne viral disease increasing dramatically over the past years due to improvement in human mobility. In this work, a multipatch model for dengue transmission dynamics is studied, and by that, the control efforts to minimize the disease spread by host and vector control are investigated. For this model, the basic reproduction number is derived, giving a choice for parameters in the endemic case. The multipatch system models the host movement within the patches, which coupled via a residence-time budgeting matrix P. Numerical results confirm that the control mechanism embedded in incidence rates of the disease transmission effectively reduces the spread of the disease.

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Understanding dengue fever dynamics: a study of seasonality in vector-borne disease models

Cited by 36 publications

References 27 publications

Dengue modeling in rural Cambodia: statistical performance versus epidemiological relevance

Dengue modeling in rural Cambodia: statistical performance versus epidemiological relevance

On the co‐infection of dengue fever and Zika virus

Optimal control and basic reproduction numbers for a compartmental spatial multipatch dengue model

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