Parasites & Vectors最新文献

Background: This study investigates the prevalence of leishmaniasis and American trypanosomiasis (Chagas disease) - two neglected vector-borne diseases - in humans and dogs in the Bolivian Chaco region, where high poverty levels increase population vulnerability. Leishmaniasis, which affects millions globally, is widespread in Bolivia, a country reporting some of the highest rates of cutaneous and mucocutaneous cases in Latin America. Chagas disease is endemic across the region, with an estimated 4.5 million individuals affected.

Methods: Blood and serum samples were collected from 189 dogs living in rural communities near the cities of Camiri and Villa Montes. Samples were tested using serological assays and quantitative PCR (qPCR) to detect Leishmania spp. and Trypanosoma cruzi. Additionally, serum samples from 151 school-aged children from both areas were screened for anti-Leishmania antibodies.

Results: The seroprevalence of Leishmania in dogs was significantly higher in Villa Montes (46%) compared with Camiri (26%). Moreover, Leishmania DNA was detected by qPCR in 9 out of 125 dogs tested (7.2%). Among children, 13.2% from Villa Montes tested positive for Leishmania antibodies, while no positive cases were found in Camiri. Serological evidence of previous T. cruzi infection was identified in 17.7% of dogs, although all qPCR results for T. cruzi were negative.

Conclusions: These findings highlight the relevance of a One Health approach, as dogs may serve as reservoirs for both parasites, potentially increasing the risk of human transmission. Integrated control measures - including vector management and ongoing surveillance - are essential to reduce transmission and protect public health. Future research should prioritise mapping infection patterns and exploring ecological factors influencing disease dynamics.

Oropouche virus (OROV) is mainly transmitted to humans by Culicoides paraensis, a biting midge widely distributed across the Americas. In this study, we modeled the potential distribution of C. paraensis in Brazil using environmental variables and found that temperature-related factors, particularly minimum temperature and annual temperature range, were the strongest predictors of its occurrence. Comparison of the predicted distribution with confirmed autochthonous OROV cases revealed several areas of mismatch, suggesting either underreporting of C. paraensis or the involvement of additional vector species in transmission. These findings highlight the need to integrate C. paraensis into Brazil's arbovirus surveillance systems and to strengthen entomological monitoring with the support of remote sensing, climate data, and ecological research to better anticipate and mitigate future transmission risks.

Background: The sterile insect technique (SIT) is a well-established, environmentally friendly method of insect population suppression that relies on the release of sterile males to reduce reproduction in wild populations. SIT has been successfully applied against several insect pests, including the tsetse fly (hereafter tsetse) in Africa and Aedes aegypti mosquitoes in Asia and the Americas, and is increasingly considered to be a complementary tool for vector control. For an SIT programme to succeed, the release process must ensure good coverage of the targeted area without compromising the performance of the released insects. The use of release systems paired with drones may play an important role. While interest in aerial releases is growing, the number of available aerial release systems remains limited.

Methods: The Birdview insect cassette, a lightweight, three-dimensional (3D)-printed device compatible with drones, was described and assessed for its suitability to release adult Aedes mosquitoes and tsetse under laboratory conditions. We determined the carrying capacity of the release system and the flight propensity, survival of and potential physical damage to Ae. aegypti and the tsetse Glossina palpalis gambiense, under laboratory conditions, using between 8000 and 30,000 insects.

Results: Overall, our findings highlight the potential of the insect cassette system, which can support loading densities up to 45,000 Ae. aegypti or 11,000 G. p. gambiensis, with release efficiencies ranging from 60% to 96% and a survival rate of > 70% after a 26-day monitoring period. Of the released insects, > 80% escaped from flight ability devices.

Conclusions: The Birdview insect cassette is valuable for aerial release programmes targeting Aedes mosquitoes and tsetse. Future research should focus on refining the system's design and functionality, as well as evaluating its performance in field settings to validate its effectiveness in vector control.

Background: Dirofilariosis is a vector-borne zoonotic disease primarily caused by the parasitic nematodes Dirofilaria immitis and D. repens. In Europe, the disease has expanded from traditionally endemic southern countries to central and northeastern regions, many of which are now also considered endemic. This study aimed to generate infection risk maps for dirofilariosis in Europe using ecoinformatic tools, at both annual and monthly scales, to serve as a prevention tool and contribute to more effective control of the disease, as well as helping to stop its spread.

Methods: A habitat suitability map was generated for the two most important and widely distributed culicid vectors in Europe (Culex pipiens and Aedes albopictus). This map was weighted with the number of D. immitis generations in the vectors, both annually and monthly. The resulting annual risk map was validated with georeferenced records of D. immitis- and D. repens-infected dogs and cats. In addition, a future habitat suitability projection for both vector species was performed for the year 2100 under the Representative Concentration Pathway (RCP) 8.5 climate change scenario.

Results: Dirofilariosis infection risk in Europe is highest in southern countries, where favorable climatic conditions and increased vector activity coincide. Central Europe showed medium- to high-risk values, while northern latitudes exhibited low or very low risk, correlating with lower average temperatures. Of the geolocated infected animals, 35.9%, 51% and 13% were located in high-, medium-, or low-risk areas, respectively. Infection risk appears to be very limited during winter, restricted mainly to Mediterranean coastal areas, the Canary Islands (Spain), and Madeira (Portugal); while in spring/summer it becomes high in these places and moderate across other parts of the range such us central and northeastern Europe. The 2100 projection predicts a 161.6% increase in habitat suitability for the vectors, particularly in northeastern regions, high-altitude areas, and northernmost countries.

Conclusions: The combined use of habitat suitability for Culex pipiens and Aedes albopictus and the number of Dirofilaria spp. generations allowed the development of a more comprehensive color-coded dirofilariosis infection risk map than previously available. Monthly infection risk maps across Europe could help guide targeted prevention and control measures, disrupt disease establishment in specific areas and seasons, and raise awareness about infection risks in both animals and humans.

Background: Leishmania infantum infection progression in dogs depends on the interaction between the parasite and the host's immune response. The adaptive immune response, primarily mediated by T-helper 1 lymphocytes, promotes an effective reaction by increasing cytokines such as interferon-gamma (IFN-γ). In addition, interleukin-17a (IL-17a) plays a role in controlling parasite growth through inducible nitric oxide synthase activation. However, limited data exist on IL-17a production in dogs at different disease stages. This study aimed to evaluate L. infantum-specific IL-17a production in blood samples from dogs with varying clinical stages of leishmaniosis and to assess its correlation with disease severity, humoral response, and IFN-γ  concentrations.

Methods: In total, 65 dogs were included; 10 healthy seronegative and 55 sick dogs, classified into three groups according to the LeishVet clinical stages, were studied. IFN-γ and IL-17a concentrations were measured using a sandwich enzyme-linked immunosorbent assay (ELISA) after performing a L. infantum-specific cytokine release whole-blood assay following stimulation with soluble L. infantum antigen.

Results: No significant differences in IL-17a concentration were observed between healthy and all sick dogs (P = 0.77). Dogs in stage I presented higher IL-17a concentrations than dogs in stages II and III. However, the difference was only statistically significant when compared with stage III (P = 0.044). Regarding IFN-γ, all sick dogs demonstrated higher concentrations than healthy dogs (P = 0.003). Stage I dogs also exhibited higher IFN-γ concentrations compared with healthy dogs (P = 0.0002) and with dogs in stage II (P = 0.016) and III (P = 0.016). Stage II dogs showed higher IFN- γ concentrations than healthy dogs (P = 0.03). All dogs studied presented a positive correlation between IFN-γ and IL-17a concentrations (Spearman's r: 0.54, P < 0.0001). Regarding all the sick dogs, a negative correlation was found between IFN-γ concentration and antibody levels (Spearman's r: -0.41, P = 0.002), and between IL-17a concentration and antibody levels (Spearman's r: -0.27, P = 0.044). There was a positive correlation between IFN-γ and IL-17a concentration (Spearman's r: 0.61, P < 0.0001).

Conclusions: This study demonstrates that IL-17a production is increased in mild disease when compared with more advanced clinical stages, acting as a possible "resistance" marker. However, IL-17a seems to be less reliable as a marker when compared with IFN-γ.

Background: Habitat suitability of Anopheles mosquitoes depends on appropriate climate and land-use conditions. Anopheles mosquitoes are the main vectors for malaria transmission in the Euro-Mediterranean region, and there are major concerns that these species will expand and/or shift their range due to the expected changes in climate and land-use. This study aims to identify the main climate and land-use drivers of changes in the habitat suitability for six different Anopheles species between 2000 and 2020 within the Euro-Mediterranean region.

Methods: Boosted regression trees were applied to establish the link between climate and land-use predictors and habitat suitability. An ensemble of 16 models, based on different methods of selecting background points and statistical predictors, was applied to each species. The ensemble was evaluated by means of model skill and transferability to identify the best model. Taking contribution, interactions and response range into account, the most important predictors and those responsible for changes were identified.

Results: The model ensembles agreed on the direction of change for four Anopheles species within the study area, with two of these showing an overall increase (An. atroparvus, An. sacharovi) of areas with suitable conditions and two showing a decrease (An. messeae, An. sergentii). Climate change was found to be the main driver of shifts in habitat suitability, with only a few models attributing changes mainly to land-use. The limited influence of land-use changes may be due to the spatial resolution being too coarse. For most species, temperature-related bioclimatic variables (BIO4, BIO5, BIO8) were the most important predictors of changes in habitat suitability. A superior method for either the specific background points or predictor selection did not emerge because the relative ranking of the corresponding models is dependent on the species analyzed.

Conclusions: Between 2000 and 2020, rising temperatures were the main driver of changes in the habitat suitability of Anopheles mosquitoes in the Euro-Mediterranean region, with land-use changes having a relatively minor impact. In particular, regions to the north of the respective distribution area were found to be characterized by an increasing habitat suitability, while regions to the south showed decreasing trends. These trends may also impact the risk of local malaria transmission in these regions.

Background: Ecological variables that vary across time and space shape mosquito populations, creating microenvironments that can become disease transmission hotspots. Rift Valley fever virus (RVFV), a priority zoonotic arbovirus, thrives in diverse conditions and has been detected in over 50 mosquito species. This diversity complicates efforts to identify the key vectors involved in transmission and highlights the need to understand how environmental conditions shape mosquito abundance in high-risk landscapes.

Methods: This study investigated spatio-temporal variation in mosquito abundance across the semi-pastoral landscape of Loitokitok sub-county, Kajiado County, Kenya. Over a full year, inclusive of the 2023-2024 El Niño rains, repeated mosquito trapping events were conducted at households enrolled in a human clinical cohort study, with weather station data linked to each trapping event.

Results: A total of 441 mosquitoes were captured across 39 trapping events, with an average of 11.3 mosquitoes per event. The highest rainfall occurred in November 2023, while mosquito abundance peaked in April 2024. Traps placed at households in cropland areas hosted significantly more mosquitoes overall and were associated with more Anopheles spp., predominantly Anopheles gambiae (Kruskal-Wallis χ² = 6.9, df = 2, P = 0.03), while those in shrubland areas had more Aedes aegypti (Kruskal-Wallis χ² = 11.9, df = 2, P = 0.002). Multivariable models showed that land use/land cover (LULC) consistently improved model fit, though temporal weather factors were stronger predictors. Weather conditions from the prior month better predicted mosquito abundance than weather conditions over shorter time frames, with temperature consistently included in top models and humidity outperforming rainfall as an additional covariate in the best-fit model that included LULC, temperature, and humidity.

Conclusions: These findings highlight the role of weather patterns and LULC in shaping mosquito dynamics, with irrigated cropland likely creating persistent breeding sites and shrubland providing niches for Ae. aegypti. This emphasizes the need for targeted, community-driven vector control strategies to mitigate RVFV transmission risk and highlights the importance of altered agricultural landscapes in driving vector dynamics.

Aedes albopictus, commonly known as the Asian tiger mosquito, is an invasive species of significant public health concern due to its ability to transmit dengue, chikungunya, and Zika viruses. Since arriving in Europe in the late 1970s, this mosquito species has progressively expanded its range, with Belgium marking an important step in its northward spread. The increasing frequency of its introduction raises the urgent question of whether Ae. albopictus could become permanently present in the country. This study investigates the potential for the establishment of Ae. albopictus populations in Belgium using a mechanistic model and assessing the likelihood of successful establishment based on simulated introduction events. Our results indicate that the probability of establishment is highest in Flanders, particularly under scenarios of early and multiple introductions during the summer months, even though the interannual climatic variability still plays a major role in establishment success. The establishment of Ae. albopictus in Belgium would introduce new epidemiological risks, as the species could facilitate the transmission of non-native viruses during particularly warm summers. While the transmission windows may remain limited compared to Mediterranean regions, continued introductions and climate change could expand these periods, increasing the likelihood of local outbreaks.

Background: Disease outbreaks, particularly cryptocaryoniasis caused by the ciliate Cryptocaryon irritans, pose significant barriers to sustainable marine fish aquaculture, undermining productivity, profitability, and biosecurity. Despite its impact, early warning tools for parasitic diseases leveraging advanced technologies remain underdeveloped.

Methods: We developed a machine learning (ML)-driven early warning system for cryptocaryoniasis, integrating seven years of outbreak surveillance data (n = 429 events from 2016 to 2023) with 17 high-resolution oceanographic predictors influencing parasite life cycles along China's coast. Five supervised ML models: logistic regression (LR), support vector machine (SVM), random forest (RF), XGBoost (XGB), and artificial neural network (ANN), were trained using cross-validation and benchmarked in commercial open-sea cages and recirculating aquaculture systems (RAS).

Results: The RF model achieved the highest sensitivity (98.6%), with RF and XGB excelling in F1 scores (0.93 and 0.938, respectively), identifying stocking density, water temperature, salinity, pH, and novel predictors such as silicate and nitrate as key risk factors. The predictive engine was deployed as an open-source web-based platform, delivering weekly, spatially resolved outbreak forecasts. Field validation across 12 open-sea cage events and weekly RAS monitoring confirmed high predictive accuracy (91.67% in sea cages; 87.5% in RAS), revealing seasonal and latitudinal disease trends.

Conclusions: This study establishes a robust, scalable framework for real-time disease forecasting in marine aquaculture, adaptable to other aquatic pathogen-host species to support parasite surveillance and precision health management across diverse global aquaculture systems. While further validation with larger datasets and integration of pathogen and host data will enhance future models, this system provides a flexible foundation for advancing disease control in aquatic environments.

Background: Cryptosporidium infection occurs in humans, domestic animals, and wildlife. To date, at least 49 species and 120 genotypes have been identified. Hitherto, molecular identification of Cryptosporidium species in wildlife has seldom been reported in China.

Methods: During 2014-2025, a total of 1855 small intestinal or fecal specimens were collected from 1500 mammals, 121 reptiles, and 234 birds in Xinjiang Uygur Autonomous Region (XUAR) and Inner Mongolia Autonomous Region (IMAR), northern China. The identification of each animal species was based on morphological characteristics and mitochondrial gene amplification. Detection of Cryptosporidium species was performed by amplifying part of the small subunit (SSU) ribosomal RNA (rRNA) gene. The 60 kDa glycoprotein (GP60) gene was used to confirm their species and subtypes.

Results: The samples were collected from 39 mammalian, 6 reptilian, and 30 avian species. In these samples, the average rate of infection with Cryptosporidium species was 8.09% (150/1855). In total, 18 known Cryptosporidium species and genotypes were identified, including Cryptosporidium hominis, Cryptosporidium ubiquitum, Cryptosporidium muris, Cryptosporidium canis, Cryptosporidium felis, Cryptosporidium equi, Cryptosporidium proventriculi, Cryptosporidium ryanae, Cryptosporidium rubeyi, chipmunk genotype V, vole genotype III, vole genotype V, muskrat genotype I, bat genotype IV, yak genotype, deer genotype, goose genotype I, and one unnamed Cryptosporidium sp. In addition, a novel genotype, here designated as Cryptosporidium Mongolian pika genotype, was identified in the Mongolian pika (Ochotona pallasi).

Conclusions: Investigation of Cryptosporidium infection was carried out by screening 75 animal species. Overall, 19 Cryptosporidium species and genotypes were detected, including a novel genotype in Mongolian pika and first-time diagnosis of this infection in several rodent species (e.g., red-cheeked ground squirrels, great gerbils, northern mole voles, and Libyan jirds).