Seasonal changes in the diversity, host preferences and infectivity of mosquitoes in two arbovirus-endemic regions of Costa Rica

Mosquito Feeding Habits in Coastal French Guiana: Mammals in the Crosshairs?

Pathogens transmitted by mosquitoes (Diptera, Culicidae) in sylvatic or urban cycles involve wild or domestic animals and humans, driven by various mosquito species with distinct host preferences. Understanding mosquito-host associations is crucial for ecological insights and pathogen surveillance. In this study, we analyzed mosquito blood meals from coastal French Guiana by amplifying and sequencing host DNA from blood-fed females. Using the 12S ribosomal RNA gene and Sanger sequencing, we identified blood meals from 26 mosquito species across six genera, with 59% belonging to the Culex genus. Nanopore sequencing of selected samples showed 12 mosquito species with one to three mixed blood-meal sources. Mammals were the primary hosts (88%), followed by birds (7%), squamates (3%), and amphibians (2%), indicating a strong preference for mammalian hosts. A total of 46 vertebrate host species were identified, demonstrating high host diversity. This research provides insights into mosquito host usage and highlights the complexities of monitoring arboviruses of public health concern.

Spatial distribution of Japanese encephalitis cases and correlated geo-environmental factors in southern and northern counties of China

Japanese encephalitis (JE) is a mosquito-borne disease with a spatial distribution that is linked to geo-environmental factors. The spatial distribution of JE cases and correlated geo-environmental factors were investigated in two critical counties in southern and northern China. Based on maps, enhanced thematic mapper (ETM) remote sensing datasets from Landsat and spatial datasets of JE cases, spatial distribution and spatial cluster analyses of JE cases at the village scale were performed by using the standard deviational ellipse and Ripleys K-function. Global and regional spatial cluster analyses of JE cases were also performed by using Moran's index. Regression analysis was used to analyze the relationships between geo-environmental characteristics and the risk of JE cases. At the study sites, the JE cases were not spatially clustered at the village or district (global) level, whereas there was a spatial cluster at the district (local) level. Diversity-related features for JE patients at the district and village levels were detected at two sites. In the southern counties, the distance of a village from a road was related to the village-level JE risk (OR: 0.530, 95 CI: 0.297-0.947, P = 0.032), and the number of township-level JE cases was linked to the distance of the district center from the road (R =-0.467, P = 0.025) and road length (R = 0.516, P = 0.012) in the administrative area. In northern China, the modified normalized difference water index (MNDWI) in the 5 km buffer around the village was related to village-level JE risk (OR: 0.702, 95% CI: 0.524-0.940, P = 0.018), and the number of township-level JE cases was related to the MNDWI in the administrative region (R =-0.522, P = 0.038). This study elucidates the spatial distribution patterns of JE cases and risk, as well as correlated geo-environmental features, at various spatial scales. This study will significantly assist the JE control efforts of the local Centers for Disease Control and Prevention (CDC), which is the base-level CDC, particularly concerning the allocation of medicine and medical staff, the development of immunological plans, and the allocation of pesticides and other control measures for the mosquito vectors of JE.

Epidemiological, virological and clinical characterization of a Dengue/Zika outbreak in the Caribbean region of Costa Rica 2017-2018

The increase in incidence and geographical expansion of viruses transmitted by the Aedes mosquitoes, such as dengue (DENV) and zika (ZIKV) in the Americas, represents a burden for healthcare systems in tropical and subtropical regions. These and other under-detected arboviruses co-circulate in Costa Rica, adding additional complexity to their management due to their shared epidemiological behavior and similarity of symptoms in early stages. Since diagnostics of febrile illness is mostly based on clinical symptoms alone, we gathered acute-phase serum and urine from 399 samples of acute dengue-like cases from two healthcare facilities of Costa Rica, during an outbreak of arboviruses from July 2017 to May 2018, and tested them using molecular and serological methods. The analyses showed that of the clinically presumptive arbovirus cases that were reported, only 39.4% (n=153) of the samples were confirmed positive by RT-PCR to be DENV (DENV (10.3%), CHIKV (0.2%), ZIKV (27.3%), or mixed infections (1.5%). RT-PCR for other alphaviruses and flaviviruses, and PCR for Leptospira sp were negative. Furthermore, to assess flavivirus positivity in post-acute patients, the negative sera were tested against Dengue-IgM. 20% of sera were found positive, confounding even more the definitive number of cases, and emphasizing the need of several distinct diagnostic tools for accurate diagnostics. Molecular characterization of the prM and E genes from isolated viruses revealed that the American/Asian genotype of DENV-2 and the Asian lineage of ZIKV were circulating during this outbreak. Two different clades of DENV-2 American/Asian genotype were identified to co-circulate in the same region and a difference in the platelet and leukocyte count was noted between people infected with each clade, suggesting a putative distinct virulence. Our study sheds light on the necessity for healthcare strategies in managing arbovirus outbreaks, emphasizing the importance of comprehensive molecular and serological diagnostic approaches, as well as molecular characterization. This approach aids in enhancing our understanding of the clinical and epidemiological aspects of arboviral diseases during outbreaks. Our research highlights the need to strengthen training programs for health professionals and the need to increase research-based on laboratory evidence for diagnostic accuracy, guidance, development and implementation of public health interventions and epidemiological surveillance.

Local tree cover predicts mosquito species richness and disease vector presence in a tropical countryside landscape

Context

Land use change drives both biodiversity loss and zoonotic disease transmission in tropical countryside landscapes. Developing solutions for protecting countryside biodiversity, public health, and livelihoods requires understanding the scales at which habitat characteristics such as land cover shape biodiversity, especially for arthropods that transmit pathogens. Evidence increasingly shows that species richness for many taxa correlates with local tree cover.

Objectives

We investigated whether mosquito species richness, community composition, and presence of disease vector species responded to land use and tree cover - and if so, whether at spatial scales similar to other taxa.

Methods

We paired a field survey of mosquito communities in agricultural, residential, and forested lands in rural southern Costa Rica with remotely sensed tree cover data. We compared mosquito community responses to tree cover surrounding survey sites measured across scales, and analyzed community responses to land use and environmental gradients.

Results

Tree cover was positively correlated with mosquito species richness, and negatively correlated with the presence of the common invasive dengue vector Aedes albopictus, particularly at small spatial scales of 80 - 200m. Land use predicted community composition and Ae. albopictus presence. Environmental gradients of tree cover, temperature, and elevation explained 7% of species turnover among survey sites.

Conclusions

The results suggest that preservation and expansion of tree cover at local scales can protect biodiversity for a wide range of taxa, including arthropods, and also confer protection against disease vector occurrence. The identified spatial range of tree cover benefits can inform land management for conservation and public health protection.

Local tree cover predicts mosquito species richness and disease vector presence in a tropical countryside landscape

Context

Land use change drives both biodiversity loss and zoonotic disease transmission in tropical countryside landscapes. Developing solutions for protecting countryside biodiversity, public health, and livelihoods requires understanding the scales at which habitat characteristics such as land cover shape biodiversity, especially for arthropods that transmit pathogens. Evidence increasingly shows that species richness for many taxa correlates with local tree cover.

Objectives

We investigated whether mosquito species richness, community composition, and presence of disease vector species responded to land use and tree cover - and if so, whether at spatial scales similar to other taxa.

Methods

We paired a field survey of mosquito communities in agricultural, residential, and forested lands in rural southern Costa Rica with remotely sensed tree cover data. We compared mosquito community responses to tree cover surrounding survey sites measured across scales, and analyzed community responses to land use and environmental gradients.

Results

Tree cover was positively correlated with mosquito species richness, and negatively correlated with the presence of the common invasive dengue vector Aedes albopictus , particularly at small spatial scales of 80 - 200m. Land use predicted community composition and Ae. albopictus presence. Environmental gradients of tree cover, temperature, and elevation explained 7% of species turnover among survey sites.

Conclusions

The results suggest that preservation and expansion of tree cover at local scales can protect biodiversity for a wide range of taxa, including arthropods, and also confer protection against disease vector occurrence. The identified spatial range of tree cover benefits can inform land management for conservation and public health protection.

Longitudinal Study of Viral Diversity Associated with Mosquito Species Circulating in Cambodia

Arthropod-borne viruses (arboviruses) pose a significant global health threat and are primarily transmitted by mosquitoes. In Cambodia, there are currently 290 recorded mosquito species, with at least 17 of them considered potential vectors of arboviruses to humans. Effective surveillance of virome profiles in mosquitoes from Cambodia is vital, as it could help prevent and control arbovirus diseases in a country where epidemics occur frequently. The objective of this study was to identify and characterize the viral diversity in mosquitoes collected during a one-year longitudinal study conducted in various habitats across Cambodia. For this purpose, we used a metatranscriptomics approach and detected the presence of chikungunya virus in the collected mosquitoes. Additionally, we identified viruses categorized into 26 taxa, including those known to harbor arboviruses such as Flaviviridae and Orthomyxoviridae, along with a group of viruses not yet taxonomically identified and provisionally named "unclassified viruses". Interestingly, the taxa detected varied in abundance and composition depending on the mosquito genus, with no significant influence of the collection season. Furthermore, most of the identified viruses were either closely related to viruses found exclusively in insects or represented new viruses belonging to the Rhabdoviridae and Birnaviridae families. The transmission capabilities of these novel viruses to vertebrates remain unknown.

An Integrative Explainable Artificial Intelligence Approach to Analyze Fine-Scale Land-Cover and Land-Use Factors Associated with Spatial Distributions of Place of Residence of Reported Dengue Cases

Dengue fever is a prevalent mosquito-borne disease that burdens communities in subtropical and tropical regions. Dengue transmission is ecologically complex; several environmental conditions are critical for the spatial and temporal distribution of dengue. Interannual variability and spatial distribution of dengue transmission are well-studied; however, the effects of land cover and use are yet to be investigated. Therefore, we applied an explainable artificial intelligence (AI) approach to integrate the EXtreme Gradient Boosting and Shapley Additive Explanation (SHAP) methods to evaluate spatial patterns of the residences of reported dengue cases based on various fine-scale land-cover land-use types, Shannon's diversity index, and household density in Kaohsiung City, Taiwan, between 2014 and 2015. We found that the proportions of general roads and residential areas play essential roles in dengue case residences with nonlinear patterns. Agriculture-related features were negatively associated with dengue incidence. Additionally, Shannon's diversity index showed a U-shaped relationship with dengue infection, and SHAP dependence plots showed different relationships between various land-use types and dengue incidence. Finally, landscape-based prediction maps were generated from the best-fit model and highlighted high-risk zones within the metropolitan region. The explainable AI approach delineated precise associations between spatial patterns of the residences of dengue cases and diverse land-use characteristics. This information is beneficial for resource allocation and control strategy modification.