Use of Unmanned Aerial Vehicles for Building a House Risk Index of Mosquito-Borne Viral Diseases
The Vector Control Program in Mexico has developed operational research strategies to identify entomological and sociodemographic parameters associated with dengue transmission in order to direct targeted actions and reduce transmission. However, these strategies have limitations in establishing the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Machines |
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| Online Access: | https://www.mdpi.com/2075-1702/10/12/1161 |
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| author | Víctor Muñiz-Sánchez Kenia Mayela Valdez-Delgado Francisco J. Hernandez-Lopez David A. Moo-Llanes Graciela González-Farías Rogelio Danis-Lozano |
| author_facet | Víctor Muñiz-Sánchez Kenia Mayela Valdez-Delgado Francisco J. Hernandez-Lopez David A. Moo-Llanes Graciela González-Farías Rogelio Danis-Lozano |
| author_sort | Víctor Muñiz-Sánchez |
| collection | DOAJ |
| description | The Vector Control Program in Mexico has developed operational research strategies to identify entomological and sociodemographic parameters associated with dengue transmission in order to direct targeted actions and reduce transmission. However, these strategies have limitations in establishing their relationship with landscape analysis and dengue transmission. This study provides a proof of concept of the use of unmanned aerial vehicle technology as a possible way to collect spatial information of the landscape in real time through multispectral images for the generation of a multivariate predictive model that allows for the establishment of a risk index relating sociodemographic variables with the presence of the vector in its different larval, pupal, and adult stages. With flight times of less than 30 min, RGB orthomosaics were built, where houses, roads, highways, rivers, and trails are observed in detail, as well as in areas with a strong influence of vegetation, detailing the location of the roofs or the infrastructure of the house, grass, bushes, and trees of different dimensions, with a pixel resolution level of 5 centimeters. For the risk index, we developed a methodology based on partial least squares (PLS), which takes into account the different type of variables are involved and the geographic distribution of the houses as well. Results show the spatial pattern of downtown low-risk housing, which increases as we approach the outskirts of the town. The predictive model of dengue transmission risk developed through orthomosaics can help decision makers to plan control and public health activities. |
| first_indexed | 2024-03-09T16:09:49Z |
| format | Article |
| id | doaj.art-360f7ff30e9843a297a6af474f1172a9 |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-09T16:09:49Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-360f7ff30e9843a297a6af474f1172a92023-11-24T16:16:39ZengMDPI AGMachines2075-17022022-12-011012116110.3390/machines10121161Use of Unmanned Aerial Vehicles for Building a House Risk Index of Mosquito-Borne Viral DiseasesVíctor Muñiz-Sánchez0Kenia Mayela Valdez-Delgado1Francisco J. Hernandez-Lopez2David A. Moo-Llanes3Graciela González-Farías4Rogelio Danis-Lozano5Monterrey Campus, Centro de Investigación en Matemáticas, A.C., Km. 10 Autopista al Aeropuerto, Parque de Investigación e Innovación Tecnológica (PIIT), Av. Alianza Centro 502, Apodaca 66628, MexicoCentro Regional de Investigación en Salud Pública (CRISP), Instituto Nacional de Salud Pública (INSP), 4a Av. Norte esquina 19 Calle Poniente s/n, Tapachula 30700, MexicoCONACYT—Centro de Investigación en Matemáticas, A.C., CIMAT Unidad Mérida, Parque Científico y Tecnológico de Yucatán (PCTY), Sierra Papacal, Mérida 97302, MexicoCentro Regional de Investigación en Salud Pública (CRISP), Instituto Nacional de Salud Pública (INSP), 4a Av. Norte esquina 19 Calle Poniente s/n, Tapachula 30700, MexicoMonterrey Campus, Centro de Investigación en Matemáticas, A.C., Km. 10 Autopista al Aeropuerto, Parque de Investigación e Innovación Tecnológica (PIIT), Av. Alianza Centro 502, Apodaca 66628, MexicoCentro Regional de Investigación en Salud Pública (CRISP), Instituto Nacional de Salud Pública (INSP), 4a Av. Norte esquina 19 Calle Poniente s/n, Tapachula 30700, MexicoThe Vector Control Program in Mexico has developed operational research strategies to identify entomological and sociodemographic parameters associated with dengue transmission in order to direct targeted actions and reduce transmission. However, these strategies have limitations in establishing their relationship with landscape analysis and dengue transmission. This study provides a proof of concept of the use of unmanned aerial vehicle technology as a possible way to collect spatial information of the landscape in real time through multispectral images for the generation of a multivariate predictive model that allows for the establishment of a risk index relating sociodemographic variables with the presence of the vector in its different larval, pupal, and adult stages. With flight times of less than 30 min, RGB orthomosaics were built, where houses, roads, highways, rivers, and trails are observed in detail, as well as in areas with a strong influence of vegetation, detailing the location of the roofs or the infrastructure of the house, grass, bushes, and trees of different dimensions, with a pixel resolution level of 5 centimeters. For the risk index, we developed a methodology based on partial least squares (PLS), which takes into account the different type of variables are involved and the geographic distribution of the houses as well. Results show the spatial pattern of downtown low-risk housing, which increases as we approach the outskirts of the town. The predictive model of dengue transmission risk developed through orthomosaics can help decision makers to plan control and public health activities.https://www.mdpi.com/2075-1702/10/12/1161<i>Aedes aegypti</i>UAVrisk modelFAMDPLS |
| spellingShingle | Víctor Muñiz-Sánchez Kenia Mayela Valdez-Delgado Francisco J. Hernandez-Lopez David A. Moo-Llanes Graciela González-Farías Rogelio Danis-Lozano Use of Unmanned Aerial Vehicles for Building a House Risk Index of Mosquito-Borne Viral Diseases Machines <i>Aedes aegypti</i> UAV risk model FAMD PLS |
| title | Use of Unmanned Aerial Vehicles for Building a House Risk Index of Mosquito-Borne Viral Diseases |
| title_full | Use of Unmanned Aerial Vehicles for Building a House Risk Index of Mosquito-Borne Viral Diseases |
| title_fullStr | Use of Unmanned Aerial Vehicles for Building a House Risk Index of Mosquito-Borne Viral Diseases |
| title_full_unstemmed | Use of Unmanned Aerial Vehicles for Building a House Risk Index of Mosquito-Borne Viral Diseases |
| title_short | Use of Unmanned Aerial Vehicles for Building a House Risk Index of Mosquito-Borne Viral Diseases |
| title_sort | use of unmanned aerial vehicles for building a house risk index of mosquito borne viral diseases |
| topic | <i>Aedes aegypti</i> UAV risk model FAMD PLS |
| url | https://www.mdpi.com/2075-1702/10/12/1161 |
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