{"title":"Algorithm and rapid intervention to attenuate Zika virus outbreak in large cities","authors":"H. Nieto-Chaupis, H. Matta-Solis","doi":"10.1109/ETCM.2016.7750814","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":6480,"journal":{"name":"2016 IEEE Ecuador Technical Chapters Meeting (ETCM)","volume":"28 1","pages":"1-3"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Ecuador Technical Chapters Meeting (ETCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETCM.2016.7750814","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.