Background: Trash piles and abandoned tires that are exposed to the elements collect water and create productive breeding grounds for Aedes aegypti mosquitoes, the primary vector for multiple arboviruses. Unmanned aerial vehicle (UAV) imaging provides a novel approach to efficiently and accurately mapping trash, which could facilitate improved prediction of Ae. aegypti habitat and consequent arbovirus transmission. This study evaluates the efficacy of trash identification by UAV imaging analysis compared with the standard practice of walking through a community to count and classify trash piles.
Methods: We conducted UAV flights and four types of walkthrough trash surveys in the city of Kisumu and town of Ukunda in western and coastal Kenya, respectively. Trash was classified on the basis of a scheme previously developed to identify high and low risk Aedes aegypti breeding sites. We then compared trash detection between the UAV images and walkthrough surveys.
Results: Across all walkthrough methods, UAV image analysis captured 1.8-fold to 4.4-fold more trash than the walkthrough method alone. Ground truth validation of UAV-identified trash showed that 94% of the labeled trash sites were correctly identified with regards to both location and trash classification. In addition, 98% of the visible trash mimics documented during walkthroughs were correctly avoided during UAV image analysis. We identified advantages and limitations to using UAV imaging to identify trash piles. While UAV imaging did miss trash underneath vegetation or buildings and did not show the exact composition of trash piles, this method was efficient, enabled detailed quantitative trash data, and granted access to areas that were not easily accessible by walking.
Conclusions: UAVs provide a promising method of trash mapping and classification, which can improve research evaluating trash as a risk factor for infectious diseases or aiming to decrease community trash exposure.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11883972 | PMC |
http://dx.doi.org/10.1186/s13071-025-06706-1 | DOI Listing |
Worldwide, indulgence in high-risk behaviors such as substance abuse is on the rise in street children. Though substance abuse among street children has been investigated and reported in Pakistan, few studies have explored the relationship between narcotic use and its associated factors. This study was conducted to determine factors associated with narcotic use among street children in Islamabad Capital Territory.
View Article and Find Full Text PDFSci Rep
March 2025
Shaanxi Transportation Holding Group Co., Ltd, Xi'an, 710075, China.
The research examines the challenges city street sweepers face, which struggles to adapt cleaning settings based on varying road garbage volume, resulting in inefficient cleaning and high energy consumption. The study proposes a fuzzy control algorithm for adjusting the cleaning parameters of street sweepers based on road garbage volume grading. It starts by utilizing the YOLO (You Only Look Once) v5 deep learning model for target detection and garbage classification on road surfaces.
View Article and Find Full Text PDFIntegr Pharm Res Pract
March 2025
Department of Clinical Pharmacy and Pharmacy Practices, University of Rwanda, Kigali, Rwanda.
Background: University students typically use prescribed or non-prescribed medications, often resulting in the accumulation of leftover medications. Hence, understanding their disposal practices is crucial, as improper disposal contribute to significant public health and environmental risks.
Objective: This study intended to assess the disposal practices of leftover medications among undergraduate students at the University of Rwanda, as well as the factors influencing these practices.
Brain Stimul
March 2025
Department of Psychiatry & Behavioral Sciences, Department of Biomedical Engineering, Department of Electrical & Computer Engineering, Department of Neurosurgery, Duke University, Durham, NC, USA. Electronic address:
Sci Rep
March 2025
School of Chemical Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea.
Waste management handles all kinds of waste, including household, industrial, municipal, organic, biomedical, biological, and radioactive wastes. People still face challenges in proper disposal methods for different types of waste, including landfill-bound items, recyclable materials, and biodegradable waste. Inadequate waste management poses a significant and multifaceted global challenge.
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