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...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2016-03-01
|
| Series: | Diseases |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2079-9721/4/2/16 |
| _version_ | 1828749462619553792 |
|---|---|
| author | Mayra Elizabeth Parra-Amaya María Eugenia Puerta-Yepes Diana Paola Lizarralde-Bejarano Sair Arboleda-Sánchez |
| author_facet | Mayra Elizabeth Parra-Amaya María Eugenia Puerta-Yepes Diana Paola Lizarralde-Bejarano Sair Arboleda-Sánchez |
| author_sort | Mayra Elizabeth Parra-Amaya |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-10T20:22:16Z |
| format | Article |
| id | doaj.art-86c9779ecdc94cf896a3008ced8dd604 |
| institution | Directory Open Access Journal |
| issn | 2079-9721 |
| language | English |
| last_indexed | 2024-12-10T20:22:16Z |
| publishDate | 2016-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diseases |
| spelling | doaj.art-86c9779ecdc94cf896a3008ced8dd6042022-12-22T01:34:59ZengMDPI AGDiseases2079-97212016-03-01421610.3390/diseases4020016diseases4020016Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) AnalysisMayra Elizabeth Parra-Amaya0María Eugenia Puerta-Yepes1Diana Paola Lizarralde-Bejarano2Sair Arboleda-Sánchez3Grupo de Análisis Funcional y Aplicaciones, Universidad EAFIT, Carrera 49 No. 7 Sur-50, Medellín 050022, ColombiaGrupo de Análisis Funcional y Aplicaciones, Universidad EAFIT, Carrera 49 No. 7 Sur-50, Medellín 050022, ColombiaGrupo de Análisis Funcional y Aplicaciones, Universidad EAFIT, Carrera 49 No. 7 Sur-50, Medellín 050022, ColombiaGrupo Biología y Control de Enfermedades Infecciosas—BCEI, Universidad de Antioquia, Calle 70 No. 52-21, Medellin 050010, ColombiaDengue 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.http://www.mdpi.com/2079-9721/4/2/16dengue risk classificationearly warningspatial analysistemporal indices |
| spellingShingle | Mayra Elizabeth Parra-Amaya María Eugenia Puerta-Yepes Diana Paola Lizarralde-Bejarano Sair Arboleda-Sánchez Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis Diseases dengue risk classification early warning spatial analysis temporal indices |
| 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 | dengue risk classification early warning spatial analysis temporal indices |
| url | http://www.mdpi.com/2079-9721/4/2/16 |
| work_keys_str_mv | AT mayraelizabethparraamaya earlydetectionfordengueusinglocalindicatorofspatialassociationlisaanalysis AT mariaeugeniapuertayepes earlydetectionfordengueusinglocalindicatorofspatialassociationlisaanalysis AT dianapaolalizarraldebejarano earlydetectionfordengueusinglocalindicatorofspatialassociationlisaanalysis AT sairarboledasanchez earlydetectionfordengueusinglocalindicatorofspatialassociationlisaanalysis |