Background: Mosquitoes are vectors of various arboviruses belonging to the genera Alphavirus and Flavivirus, and Costa Rica is endemic to several of them. The aim of this study was to describe and analyze the community structure of such vectors in Costa Rica.
Methods: Sampling was performed in two different coastal locations of Costa Rica with evidence of arboviral activity during rainy and dry seasons. Encephalitis vector surveillance traps, CDC female gravid traps and ovitraps were used. Detection of several arboviruses by Pan-Alpha and Pan-Flavi PCR was attempted. Blood meals were also identified. The Normalized Difference Vegetation Index (NDVI) was estimated for each area during the rainy and dry seasons. The Chao2 values for abundance and Shannon index for species diversity were also estimated.
Results: A total of 1802 adult mosquitoes belonging to 55 species were captured, among which Culex quinquefasciatus was the most caught species. The differences in NDVI were higher between seasons and between regions, yielding lower Chao-Sørensen similarity index values. Venezuelan equine encephalitis virus, West Nile virus and Madariaga virus were not detected at all, and dengue virus and Zika virus were detected in two separate Cx. quinquefasciatus specimens. The primary blood-meal sources were chickens (60%) and humans (27.5%). Both sampled areas were found to have different seasonal dynamics and population turnover, as reflected in the Chao2 species richness estimation values and Shannon diversity index.
Conclusion: Seasonal patterns in mosquito community dynamics in coastal areas of Costa Rica have strong differences despite a geographical proximity. The NDVI influences mosquito diversity at the regional scale more than at the local scale. However, year-long continuous sampling is required to better understand local dynamics.
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http://dx.doi.org/10.1186/s13071-022-05579-y | DOI Listing |
Food Chem
December 2024
Centro para Investigaciones en Granos y Semillas, Universidad de Costa Rica, 11501 San Pedro, San José, Costa Rica. Electronic address:
Common beans (Phaseolus vulgaris L.) are widely consumed legumes in Latin America and Africa, valued for their nutritional compounds and antioxidants. Their high polyphenol content contributes to the antioxidant properties, with bioactive compounds showing antifungal and antimycotoxin effects.
View Article and Find Full Text PDFPLoS One
December 2024
Warnell School of Forestry, University of Georgia Athens, Athens, Georgia, United States of America.
Remotely-sensed risk assessments of emerging, invasive pathogens are key to targeted surveillance and outbreak responses. The recent emergence and spread of the fungal pathogen, Batrachochytrium salamandrivorans (Bsal), in Europe has negatively impacted multiple salamander species. Scholars and practitioners are increasingly concerned about the potential consequences of this lethal pathogen in the Americas, where salamander biodiversity is higher than anywhere else in the world.
View Article and Find Full Text PDFPediatr Pulmonol
December 2024
Department of Pediatrics & Kawasaki Disease Research Center, University of California San Diego (UCSD) & Rady Children's Hospital, San Diego, California, USA.
Importance: There is growing understanding that Social Determinants of Health (SDH) impact on the outcomes of different pediatric conditions. We aimed to determine whether SDH affect the severity of MIS-C.
Design: Retrospective cohort study, 2021-2023.
Front Microbiol
December 2024
Environmental Pollution Research Center, University of Costa Rica, San José, Costa Rica.
Front Artif Intell
December 2024
Universidad Latinoamérica de Ciencia y Tecnología (ULACIT), San José, Costa Rica.
The COVID-19 pandemic marked a before and after in the business world, causing a growing demand for applications that streamline operations, reduce delivery times and costs, and improve the quality of products. In this context, artificial intelligence (AI) has taken a relevant role in improving these processes, since it incorporates mathematical models that allow analyzing the logical structure of the systems to detect and reduce errors or failures in real-time. This study aimed to determine the most relevant aspects to be considered for detecting software defects using AI.
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