Dengue Fever and the Zika Virus

Brauer, Fred; Castillo‐Chavez, Carlos; Feng, Zhilan

doi:10.1007/978-1-4939-9828-9_12

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…Dengue virus is an arthropod-borne virus transmitted mainly by the Aedes aegypti mosquito acting as a vector, with a higher incidence in urban areas. Symptoms include fever, headaches, joint and muscle pain, and nausea, disease varies from mild fever to severe conditions of dengue hemorrhagic fever and shock syndrome [1]- [3]. Over 50,000,000 infections are thought to occur annually globally, including 500,000 hospitalizations for dengue hemorrhagic fever [4].…”

Section: Introductionmentioning

confidence: 99%

Cluster-based LSTM models to improve Dengue cases forecast

Machuca

Díaz

Serra

2023

CLEIej

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Public health problems such as dengue fever need accurate forecasts so governments can take effective preventive measures. Deep learning (DL) and machine learning have become increasingly popular as the volume of data increases continuously. Nevertheless, performing accurate predictions in areas with fewer cases can be challenging. When we apply DL models using long short-term memory (LSTM) in different cities considering weekly dengue incidence and climate, some models may present heterogeneous behaviours and poor accuracy because of the need for more data. To mitigate this problem, clustering analysis across time series is performed based on scores to measure the clustering quality in 217 Paraguayan cities. First, we compare the raw and feature-based clustering techniques considering several metrics.Our results indicate that hierarchical clustering combined with Spearman correlation is the most appropriate approach. Finally, several LSTM models built using clustering results were compared. The main contribution of this work is a technique that can improve the performance of time series models that combine information from similar time series and weather data.

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Section: Introductionmentioning

confidence: 99%

Cluster-based LSTM models to improve Dengue cases forecast

Machuca

Díaz

Serra

2023

CLEIej

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“…Stability properties of the Zika infection model have been investigated in [30]. e authors in [31] have compared the Zika infection model with dengue to show effect of the virus on population.…”

Section: Introductionmentioning

confidence: 99%

A Fractional‐Order Model for Zika Virus Infection with Multiple Delays

2019

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Time delays and fractional order play a vital role in biological systems with memory. In this paper, we propose an epidemic model for Zika virus infection using delay differential equations with fractional order. Multiple time delays are incorporated in the model to consider the latency of the infection in a vector and the latency of the infection in the infected host. We investigate the necessary and sufficient conditions for stability of the steady states and Hopf bifurcation with respect to three time delays τ1, τ2, and τ3. The model undergoes a Hopf bifurcation at the threshold parameters τ1∗, τ2∗, and τ3∗. Some numerical simulations are given to show the effectiveness of obtained results. The numerical simulations confirm that combination of fractional order and time delays in the epidemic model effectively enriches the dynamics and strengthens the stability condition of the model.

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