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

Exposure to non-endemic arboviruses (alphaviruses) in Costa Rica assessed from human samples collected in areas with contrasting levels of dengue endemicity

Arboviruses represent a global public health challenge. The lack of diagnostic protocols and the presence of asymptomatic infections complicate confirmatory diagnostics. Alphaviruses, such as the equine encephalitis viruses, can cause severe outbreaks and are usually misdiagnosed as dengue. Thus, evidence for their circulation was assessed here. Plaque reduction neutralization test (PRNT) was used to compare sera collected during 2022-2023 from an area with high dengue endemicity (Hone Creek) with another with low endemicity (Great Metropolitan Area, GMA) to elucidate the putative alphavirus circulation and determine whether there were differences between the two areas. The screening results of PRNT50% against the Venezuelan equine encephalitis virus (VEEV) and the Eastern equine encephalitis virus showed that 20.5% of sera collected from Hone Creek were positive for VEEV, with 15.4% (n = 40) showing real neutralizing titers. In the GMA, only 0.8% tested positive for VEEV during the screening, with only 0.3% (n = 1) showing a true neutralizing titer. No sample was positive for the Eastern equine encephalitis virus or Mayaro (MAYV) and one serum sample from Hone Creek was chikungunya positive. This study underscores the global health challenge posed by arboviruses with their similar clinical presentation and antibody cross-reactivity, particularly in tropical regions where flaviviruses and alphaviruses prevail and co-circulate. The comparison of PRNT results between high and low dengue-endemic areas in Costa Rica shed light on the potential circulation of the VEEV and the fact that there is no circulation of Eastern equine encephalitis virus or Mayaro yet. These findings indicate a higher prevalence of VEEV in the high-endemic area, emphasizing the importance of targeted surveillance, control measures, and better diagnostics.

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

CONTEXT

Land use change and deforestation drive both biodiversity loss and zoonotic disease transmission in tropical countrysides. For mosquito communities that can include disease vectors, forest loss has been linked to reduced biodiversity and increased vector presence. The spatial scales at which land use and tree cover shape mosquito communities present a knowledge gap relevant to both biodiversity and public health.

OBJECTIVES

We investigated the responses of mosquito species richness and Aedes albopictus disease vector presence to land use and to tree cover surrounding survey sites at different spatial scales. We also investigated species compositional turnover across land uses and along environmental gradients.

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 richness and vector presence responses to tree cover measured across scales from 30m to 1000m, and across land uses. We analyzed compositional turnover between land uses and along environmental gradients of tree cover, temperature, elevation, and geographic distance.

RESULTS

Tree cover was both positively correlated with mosquito species richness and negatively correlated with the presence of the common invasive dengue vector Ae. albopictus at small spatial scales of 90 - 250m. Land use predicted community composition and Ae. albopictus presence.

CONCLUSIONS

The results suggest that local tree cover preservation and expansion can support mosquito species richness and reduce disease vector presence. The identified spatial range at which tree cover shapes mosquito communities can inform the development of land management practices to protect both ecosystem and public health.

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.

An Analytical Approach for Temporal Infection Mapping and Composite Index Development

Significant and composite indices for infectious disease can have implications for developing interventions and public health. This paper presents an investment for developing access to further analysis of the incidence of individual and multiple diseases. This research mainly comprises two steps: first, an automatic and reproducible procedure based on functional data analysis techniques was proposed for analyzing the dynamic properties of each disease; second, orthogonal transformation was adopted for the development of composite indices. Between 2000 and 2019, nineteen class B notifiable diseases in China were collected for this study from the National Bureau of Statistics of China. The study facilitates the probing of underlying information about the dynamics from discrete incidence rates of each disease through the procedure, and it is also possible to obtain similarities and differences about diseases in detail by combining the derivative features. There has been great success in intervening in the majority of notifiable diseases in China, like bacterial or amebic dysentery and epidemic cerebrospinal meningitis, while more efforts are required for some diseases, like AIDS and virus hepatitis. The composite indices were able to reflect a more complex concept by combining individual incidences into a single value, providing a simultaneous reflection for multiple objects, and facilitating disease comparisons accordingly. For the notifiable diseases included in this study, there was superior management of gastro-intestinal infectious diseases and respiratory infectious diseases from the perspective of composite indices. This study developed a methodology for exploring the prevalent properties of infectious diseases. The development of effective and reliable analytical methods provides special insight into infectious diseases’ common dynamics and properties and has implications for the effective intervention of infectious diseases.

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.