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Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis
Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes. There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5456273/ https://www.ncbi.nlm.nih.gov/pubmed/28933396 http://dx.doi.org/10.3390/diseases4020016 |
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author | Parra-Amaya, Mayra Elizabeth Puerta-Yepes, María Eugenia Lizarralde-Bejarano, Diana Paola Arboleda-Sánchez, Sair |
author_facet | Parra-Amaya, Mayra Elizabeth Puerta-Yepes, María Eugenia Lizarralde-Bejarano, Diana Paola Arboleda-Sánchez, Sair |
author_sort | Parra-Amaya, Mayra Elizabeth |
collection | PubMed |
description | Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes. There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO) to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices) is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA) methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places. |
format | Online Article Text |
id | pubmed-5456273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54562732017-09-12 Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis Parra-Amaya, Mayra Elizabeth Puerta-Yepes, María Eugenia Lizarralde-Bejarano, Diana Paola Arboleda-Sánchez, Sair Diseases Article Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes. There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO) to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices) is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA) methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places. MDPI 2016-03-29 /pmc/articles/PMC5456273/ /pubmed/28933396 http://dx.doi.org/10.3390/diseases4020016 Text en © 2016 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Parra-Amaya, Mayra Elizabeth Puerta-Yepes, María Eugenia Lizarralde-Bejarano, Diana Paola Arboleda-Sánchez, Sair Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis |
title | Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis |
title_full | Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis |
title_fullStr | Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis |
title_full_unstemmed | Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis |
title_short | Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis |
title_sort | early detection for dengue using local indicator of spatial association (lisa) analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5456273/ https://www.ncbi.nlm.nih.gov/pubmed/28933396 http://dx.doi.org/10.3390/diseases4020016 |
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