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Otimização multiobjetivo no controle da dengue

Authors: Bannwart, Bettina Fiorini;

Otimização multiobjetivo no controle da dengue

Abstract

A dengue é uma doença infecciosa febril aguda causada por um vírus da família Flaviridae e é transmitida através de mosquito, comumente do gênero Aedes Aegypti. Esta doença tem sido atualmente um problema mundial de saúde pública, pois em 45 dias de vida um único mosquito pode contaminar até 300 pessoas e existe uma estimativa da Organização Mundial da Saúde (OMS) que anualmente de 50 a 100 milhões de pessoas se infectam em mais de 100 países em quase todos os continentes, cerca de 550 mil doentes necessitam de hospitalização e 20 mil morrem em consequência da dengue. Desta forma, atualmente a dengue é um assunto de intensa pesquisa, seja na busca de vacinas e tratamentos para a doença ou nas formas eficientes e econômicas de controle do mosquito. Assim, este trabalho apresenta um estudo dos processos biológicos para formulação de modelos matemáticos que descrevem a dinâmica populacional do mosquito transmissor da dengue, visando a investigação de controles otimizados destes mosquitos. É proposta a utilização de controles químico com uso inseticida e genético com liberação de machos estéreis no ambiente natural. Tal problema de controle ótimo visa a minimização dos investimentos com o inseticida e com a produção de machos estéreis, minimizando também a quantidade de fêmeas fertilizadas e o efeito do inseticida sobre os machos estéreis inseridos na população. É proposto um algoritmo genético para resolução do modelo de controle ótimo aplicado a problemas de combate ao mosquito da dengue e são discutidos os resultados computacionais obtidos

Dengue is an febrile infectious disease caused by a virus of the Flavi- ridae family and is transmitted throught mosquito, the Aedes Aegypti genus is the most common. This disease has been currently a worldwide problem of public health, because about 45 days of life a single mosquito can infect up to 300 people and is an estimate of the World Health Organization (WHO) annually from 50 to 100 million people are infected in over 100 countries from all continents, about 550 thousand patients require hospitalization and 20 thousand die as a result of dengue. Thus, dengue is currently a subject of intense research, whether in the search for vaccines and treatments for the disease or the efficient and economical forms of mosquito control. Thus, this paper presents a study of biological processes for formulation of mathematical models that describe the population dynamics of the mosquito that transmits dengue, aimed at investigating optimized controls these mosquitoes. It is proposed to use controls with chemical insecticide use and genetic-releasing sterile males into the natural environment.Such optimal control problem aims at minimizing the investments of the insecticide and the production of male-sterile, while also minimizing the amount of fertilized females and the effect of the insecticide on the inserted male-sterile population. We propose a genetic algorithm to solve the model applied to optimal control problems to combat dengue mosquito and discusses the computational results

Pós-graduação em Biometria - IBB

Country
Brazil
Keywords

Biometria, Aedes aegypti, Dengue - Tratamento, Saude publica - Administração

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green