Algorithm and Rapid Intervention to Attenuate Zika Virus Outbreak in Large Cities

Descripción del Articulo

A rapid-decision algorithm aimed to tackle the increase of cases by infection due to the possible presence of Zika virus in Peri-urban areas of large cities, was developed and tested computationally. This approach targets to provide rapid assistance to possible cases caused by the Aedes mosquitoes m...

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Detalles Bibliográficos
Autores: Nieto Chaupis, Huber, Matta Solis, Hernán
Formato: objeto de conferencia
Fecha de Publicación:2016
Institución:Universidad de Ciencias y Humanidades
Repositorio:UCH-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.uch.edu.pe:uch/369
Enlace del recurso:http://repositorio.uch.edu.pe/handle/uch/369
https://ieeexplore.ieee.org/abstract/document/7750814
http://dx.doi.org/10.1109/ETCM.2016.7750814
Nivel de acceso:acceso embargado
Materia:Decision algorithms
Large cities
Peri-urban areas
Phone calls
Pregnant woman
Viruses
Descripción
Sumario:A rapid-decision algorithm aimed to tackle the increase of cases by infection due to the possible presence of Zika virus in Peri-urban areas of large cities, was developed and tested computationally. This approach targets to provide rapid assistance to possible cases caused by the Aedes mosquitoes minimizing the time of the processes of identification, evaluation and intervention. Basically, the algorithm focuses on the rapid decision for a better localization of pregnant women away from infected areas where there is one suspected case already manifesting Zika symptoms. The algorithm assumes that at least there is one suspected case of Zika virus. Assuming the case that this person performs a phone call to health specialists, then an optimized route for a rapid attention is drawn. By assuming the scenario that the suspected is already a confirmed case, the knowledge of its Geographic localization might be also crucial to focus efforts to identify the vulnerable human groups living around it. The simulations have shown that given an initial sample of suspected cases, the application systematic of the algorithm might avoid complications in a 90% of identified pregnant women population.
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