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37 results for “Chagas disease vector”
Figure 2. Box-plot head centroid size. A. Rhodnius prolixus instars. B in Head geometric morphometrics of two Chagas disease vectors from Venezuela
Figure 2. Box-plot head centroid size. A. Rhodnius prolixus instars. B. Triatoma maculata instars. Abbreviation: I—First instar; II— Second instar; III—Third instar; IV—Fourth instar; V—Fifth instar; F—Adult female; M—Adult male.
Figure 4. Canonical Variates Analysis head conformation diagram for 136 in Head geometric morphometrics of two Chagas disease vectors from Venezuela
Figure 4. Canonical Variates Analysis head conformation diagram for 136 Triatoma maculata specimens and thin-plate deformation grids. A. V instar–Adults. B. I instar–Adults. C. II instar–III instar.
Figure 3. Canonical Variates Analysis head conformation diagram for 140 in Head geometric morphometrics of two Chagas disease vectors from Venezuela
Figure 3. Canonical Variates Analysis head conformation diagram for 140 Rhodnius prolixus specimens and thin-plate deformation grids. A. V instar–Adults. B. I instar–Adults. C. II instar–III instar.
Figure 1. Landmarks head selection. A. Rhodnius prolixus. B in Head geometric morphometrics of two Chagas disease vectors from Venezuela
Figure 1. Landmarks head selection. A. Rhodnius prolixus. B. Triatoma maculata. Scale bar = 1 mm.
Vector species richness predicts local mortality rates by Chagas disease
<p>Vector species richness may drive the prevalence of vector-borne diseases by influencing pathogen transmission rates. The dilution effect hypothesis predicts that higher biodiversity reduces disease prevalence, but with inconclusive evidence. In contrast, the amplification effect hypothesis suggests that higher vector diversity may result in greater disease transmission by increasing and diversifying the transmission pathways. The relationship between vector diversity and pathogen transmission remains unclear and requires further study. Chagas disease is a vector-borne disease most prevalent in Brazil and transmitted by multiple species of Triatominae insect vectors, yet the drivers of spatial variation in its impact on human populations remain unresolved. We tested whether triatomine species richness, latitude, bioclimatic variables, human host population density, and socioeconomic variables predict Chagas disease mortality rates across over 5000 spatial grid cells covering all of Brazil. Results show that species richness of triatomine vectors is a good predictor of mortality rates caused by Chagas disease, which supports the amplification effect hypothesis. Vector richness and the impact of Chagas disease may also be driven by latitudinal components of climate and human socioeconomic factors. We provide evidence that vector diversity is a strong predictor of disease prevalence and give support to the amplification effect hypothesis.</p>
Data from: Population structure of the Chagas disease vector Triatoma infestans in an urban environment
Chagas disease is a vector-borne disease endemic in Latin America. Triatoma infestans, a common vector of this disease, has recently expanded its range into rapidly developing cities of Latin America. We aim to identify the environmental features that affect the colonization and dispersal of T. infestans in an urban environment. We amplified 13 commonly used microsatellites from 180 T. infestans samples collected from a sampled transect in the city of Arequipa, Peru, in 2007 and 2011. We assessed the clustering of subpopulations and the effect of distance, sampling year, and city block location on genetic distance among pairs of insects. Despite evidence of genetic similarity, the majority of city blocks are characterized by one dominant insect genotype, suggesting the existence of barriers to dispersal. Our analyses show that streets represent an important barrier to the colonization and dispersion of T. infestans in Arequipa. The genetic data describe a T. infestans infestation history characterized by persistent local dispersal and occasional long-distance migration events that partially parallels the history of urban development.
Data from: 2b-RAD genotyping for population genomic studies of Chagas disease vectors: Rhodnius ecuadoriensis in Ecuador
Background: Rhodnius ecuadoriensis is the main triatomine vector of Chagas disease, American trypanosomiasis, in Southern Ecuador and Northern Peru. Genomic approaches and next generation sequencing technologies have become powerful tools for investigating population diversity and structure which is a key consideration for vector control. Here we assess the effectiveness of three different 2b restriction site-associated DNA (2b-RAD) genotyping strategies in R. ecuadoriensis to provide sufficient genomic resolution to tease apart microevolutionary processes and undertake some pilot population genomic analyses. Methodology/Principal findings: The 2b-RAD protocol was carried out in-house at a non-specialized laboratory using 20 R. ecuadoriensis adults collected from the central coast and southern Andean region of Ecuador, from June 2006 to July 2013. 2b-RAD sequencing data was performed on an Illumina MiSeq instrument and analyzed with the STACKS de novo pipeline for loci assembly and Single Nucleotide Polymorphism (SNP) discovery. Preliminary population genomic analyses (global AMOVA and Bayesian clustering) were implemented. Our results showed that the 2b-RAD genotyping protocol is effective for R. ecuadoriensis and likely for other triatomine species. However, only BcgI and CspCI restriction enzymes provided a number of markers suitable for population genomic analysis at the read depth we generated. Our preliminary genomic analyses detected a signal of genetic structuring across the study area. Conclusions/Significance: Our findings suggest that 2b-RAD genotyping is both a cost effective and methodologically simple approach for generating high resolution genomic data for Chagas disease vectors with the power to distinguish between different vector populations at epidemiologically relevant scales. As such, 2b-RAD represents a powerful tool in the hands of medical entomologists with limited access to specialized molecular biological equipment.
Data from: Seasonality and temperature-dependent flight dispersal of Triatoma infestans (Hemiptera: Reduviidae) and other vectors of Chagas disease in western Argentina
Flight dispersal of Triatominae is affected by climatic conditions and determines the spatiotemporal patterns of house invasion and transmission of Trypanosoma cruzi Chagas (Kinetoplastida: Trypanosomatidae). We investigated the detailed time structure and temperature dependencies of flight occurrence of Triatoma infestans Klug (Hemiptera: Reduviidae) and other triatomine species in a rural village of western Argentina by taking advantage of the attraction of adult triatomines to artificial light sources. Most of the village's streetlight posts were systematically inspected for triatomines twice between sunset and midnight over 425 nights in the spring–summer seasons of 1999–2002, an unprecedented light-trap sampling effort for any triatomine species. In total, 288 adults were captured, including 122 Triatoma guasayana Wygodzinsky and Abalos, 89 T. infestans, 72 Triatoma eratyrusiformis Del Ponte, and 5 Triatoma garciabesi Carcavallo et al. Adult sex ratios were balanced in T. infestans and strongly male-biased in other species. Nearly all flight-dispersing triatomines were caught when temperatures at sunset were >20 °C (range, 16.6–31.7 °C), suggesting a putative threshold around 17–18 °C. Triatomine catches were rare on rainy days. Logistic regression analysis revealed that the proportion of nights in which at least an adult T. infestans was caught increased highly significantly with increasing temperature at sunset and was modified by collection month, with greater catches in early spring and no sex differential. This study confirms that spring represents a previously overlooked, important dispersal period of T. infestans, and shows large variations among and within Triatominae in their temporal patterns of flight occurrence, abundance, and sex ratio.
Data from: Population structure of the Chagas disease vector, Triatoma infestans, at the urban-rural interface
The increasing rate of biological invasions resulting from human transport or human-mediated changes to the environment have had devastating ecologic and public health consequences. The kissing bug, Triatoma infestans, has dispersed through the Peruvian city of Arequipa. The biological invasion of this insect has resulted in a public health crisis, putting thousands of residents of this city at risk of infection by Trypanosoma cruzi and subsequent development of Chagas disease. Here we show that populations of Tria. infestans in geographically distinct districts within and around this urban center share a common recent evolutionary history although current gene flow is restricted even between proximal sites. The population structure among the Tria. infestans in different districts is not correlated with the geographic distance between districts. These data suggest that migration among the districts is mediated by factors beyond the short-range migratory capabilities of Tria. Infestans and that human movement has played a significant role in the structuring of the Tria. infestans population in the region. Rapid urbanization across southern South America will continue to create suitable environments for Tria. infestans and knowledge of its urban dispersal patterns may play a fundamental role in mitigating human disease risk.
Data from: Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab
Identification of arthropods important in disease transmission is a crucial, yet difficult, task that can demand considerable training and experience. An important case in point is that of the 150+ species of Triatominae, vectors of Trypanosoma cruzi, causative agent of Chagas disease across the Americas. We present a fully automated system that is able to identify triatomine bugs from Mexico and Brazil with an accuracy consistently above 80%, and with considerable potential for further improvement. The system processes digital photographs from a photo apparatus into landmarks, and uses ratios of measurements among those landmarks, as well as (in a preliminary exploration) two measurements that approximate aspects of coloration, as the basis for classification. This project has thus produced a working prototype that achieves reasonably robust correct identification rates, although many more developments can and will be added, and—more broadly—the project illustrates the value of multidisciplinary collaborations in resolving difficult and complex challenges.
FIGURE 9 in The Triatoma phyllosoma species group (Hemiptera: Reduviidae: Triatominae), vectors of Chagas disease: Diagnoses and a key to the species
FIGURE 9. Pygophore of Triatoma spp., lateral view A, T. bassolsae; B, T. longipennis; C, T. mazzottii; D, T. pallidipennis; E, T. phyllosoma; F, T. picturata.
FIGURE 8 in The Triatoma phyllosoma species group (Hemiptera: Reduviidae: Triatominae), vectors of Chagas disease: Diagnoses and a key to the species
FIGURE 8. Pygophore of Triatoma spp., ventral view (A, T. bassolsae; B, T. longipennis; C, T. mazzottii; D, T. pallidipennis; E, T. phyllosoma; F, T. picturata.
FIGURE 7 in The Triatoma phyllosoma species group (Hemiptera: Reduviidae: Triatominae), vectors of Chagas disease: Diagnoses and a key to the species
FIGURE 7. Pygophore of Triatoma spp., ventral view. A, T. dimidiata; B, T. huehuetenanguensis; C, T. mopan. Credits of B, Lima-Cordón et al. 2019; C, Dorn et al. 2018.
FIGURE 5. Triatoma spp. A, T in The Triatoma phyllosoma species group (Hemiptera: Reduviidae: Triatominae), vectors of Chagas disease: Diagnoses and a key to the species
FIGURE 5. Triatoma spp. A, T. longipennis; B, T. mazzottii; C, D, E. T. mexicana. F, T. pallidipennis.
FIGURE 4. Triatoma spp. A, B, T in The Triatoma phyllosoma species group (Hemiptera: Reduviidae: Triatominae), vectors of Chagas disease: Diagnoses and a key to the species
FIGURE 4. Triatoma spp. A, B, T. gerstaeckeri; C, T. gomeznunezi; D, T. hegneri; E, F, T. indictiva (4C and D courtesy of C. Dale, 4E, F courtesy of E. Barrera-Vargas).
FIGURE 3. Triatoma spp. A, B, T in The Triatoma phyllosoma species group (Hemiptera: Reduviidae: Triatominae), vectors of Chagas disease: Diagnoses and a key to the species
FIGURE 3. Triatoma spp. A, B, T. bassolsae; C, T. brailovskyi; D, E, F T. dimidiata (3B courtesy of E. Barrera-Vargas and 3C courtesy of C. Dale).
FIGURE 2 in The Triatoma phyllosoma species group (Hemiptera: Reduviidae: Triatominae), vectors of Chagas disease: Diagnoses and a key to the species
FIGURE 2. Morphology of Triatoma. A, male of T. dimidiata, ventral view; B, corium of T. longipennis, dorsal view; C, corium of T. mazzottii, dorsal view; D, pronotum of T. mazzottii, lateral view; E, spongy fossulae of T. dimidiata.
FIGURE 6. Triatoma spp. A, T in The Triatoma phyllosoma species group (Hemiptera: Reduviidae: Triatominae), vectors of Chagas disease: Diagnoses and a key to the species
FIGURE 6. Triatoma spp. A, T. phyllosoma; B, T. picturata; C, T. recurva; D, T. sanguisuga (6D courtesy of C. Dale).
FIGURE 1 in The Triatoma phyllosoma species group (Hemiptera: Reduviidae: Triatominae), vectors of Chagas disease: Diagnoses and a key to the species
FIGURE 1. Morphology of Triatoma. A, Head of T. mopan, dorsal view (based on Dorn et al., 2018); B, head of T. huehuetenanguensis, ventral view (based on Lima-Cordón et al., 2019); C, pronotum and scutellum of Triatoma, dorsal view; D, abdomen of Triatoma, dorsal view; E, abdomen of T. mopan, ventral view.
Data from: 2b-RAD genotyping for population genomic studies of Chagas disease vectors: Rhodnius ecuadoriensis in Ecuador
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