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451 results for “outbreaks”
Fig. 3 in Traceback of the Psoroptes outbreak in British Columbian bighorn sheep (Ovis Canadensis)
Fig. 3. (a) Micrograph of a characteristic opisthosomal lobe of a USA bighorn mites (10× magnification captured on an Olympus C×33 compound light microscope with an Olympus EP50 camera using EP view software). The photographed mite was collected from a bighorn sheep in the Hells Canyon metapopulation. Note the more prominent outer opisthosomal lobe edge (circle) and broad base to the outer opisthosomal setae (arrow), (b) Micrograph of a characteristic opisthosomal lobe of BC bighorn origin mites (10× magnification captured on an Olympus C×33 compound light microscope with an Olympus EP50 camera using EP view software). This mite was collected from a bighorn in the Okanagan region of BC. Note the less distinct outer opisthosomal edge (circle) and the relatively less prominent base of the outer opisthosomal setae (arrow). (c) Micrograph of a characteristic opisthosomal lobe of rabbit origin mites (10× magnification captured on an Olympus C×33 compound light microscope with an Olympus EP50 camera using EP view software). This mite was collected from a rabbit in Maple Ridge, British Columbia. Note the less distinct outer opisthosomal edge (circle) and the relatively less prominent base of the outer opisthosomal setae (arrow).
Fig. 6 in Flea infestation of rodent and their community structure in frequent and non-frequent plague outbreak areas in Mbulu district, northern Tanzania
Fig. 6. Dendrogram of flea species showing two main groups (AB) of flea community based on farm and forest habitats.
Fig. 5 in Flea infestation of rodent and their community structure in frequent and non-frequent plague outbreak areas in Mbulu district, northern Tanzania
Fig. 5. Plot showing the predicted effect of locality and season on the probability of flea infestation, based on the final best-fitting generalized linear model with a binomial function. The analysis aimed to identify the factors that strongly influence flea infestation. The strongest predictors of flea infestation were plague persistent localities and short rain seasons. The probability of infestation on these predictors was found to be statistically significant (p <0.05), suggesting a higher likelihood of flea infestation in this locality and season. The bars are 95% confidence interval of the effects.
Fig. 4 in Flea infestation of rodent and their community structure in frequent and non-frequent plague outbreak areas in Mbulu district, northern Tanzania
Fig. 4. Plots showing predicted effect of rodent traits on flea abundance, based on final best fitting generalized linear mixed model with a negative-binomial function. The plots (a) indicates that rodent weight increased with flea abundance. The gray shade in the plots represents the strength and direction of the correlation, with the width of the shade indicating the 95% confidence interval (CI) around the estimated effect. Furthermore, plot (b) indicates that male rodents are more likely to have higher flea abundance compared to female rodents, but this association was not statistically significant. The bars are 95% confidence intervals of the effects.
Fig. 3 in Flea infestation of rodent and their community structure in frequent and non-frequent plague outbreak areas in Mbulu district, northern Tanzania
Fig. 3. Flea abundance for different flea species across habitat types in each locality and rodent species.
Fig. 2 in Flea infestation of rodent and their community structure in frequent and non-frequent plague outbreak areas in Mbulu district, northern Tanzania
Fig. 2. Flea abundance in the (a) localities, (b) habitats and (c) seasons. Error bars represent the standard error. There were no statistically significant differences that were observed.
Fig. 1. A in Flea infestation of rodent and their community structure in frequent and non-frequent plague outbreak areas in Mbulu district, northern Tanzania
Fig. 1. A map of Mbulu district indicating the two study localities, Endeshi-Arri (Persistent locality and Mongahay (non-persistent locality), along with the two study habitats (Farmland and forests) in each locality.
Fig. 4 in International Journal for Parasitology: Parasites and Wildlife Outbreak of parasite-induced limb malformations in a declining amphibian species in Colorado
Fig. 4. (A) Excysted metacercaria of Ribeiroia ondatrae from an infected frog; (B) Rams horn snails (Helisoma trivolvis) function as first intermediate hosts for multiple trematode species, including Ribeiroia ondatrae. Several of these snails have egg masses on their shells, which can be common in the spring.
Fig. 3 in International Journal for Parasitology: Parasites and Wildlife Outbreak of parasite-induced limb malformations in a declining amphibian species in Colorado
Fig. 3. Whole-body ventrodorsal Micro-CT scans of three leopard frogs from SBN illustrating malformations caused by the trematode Ribeiroia ondatrae. Panels A–C present 3D reconstructions of the skeletons (ventral view) of each of the living frogs in the corresponding lower panels (D–F). For each, obviously abnormal portions of the skeleton are colored in red while supernumerary limb elements are colored in teal. (A) Frog with a severely rotated ilium on the left axis, a thickened femur, thickened tibiofibula (calcaneum) with a bony triangle, an extra bone at the base of the ischium, a supernumerary left hindlimb (polymelia) with a bony triangle in the tibiofibular; the right leg is missing all metatarsals and phalanges. (B) Frog with polymelia of the left leg, with two supernumerary femurs and two unidentified supernumerary bones near the ischium; both primary hind limbs appear to have reductions of the metatarsals and phalanges. (C) Frog with an extremely thickened femur (possibly fusion of multiple femurs) in the left hind limb, a double bony triangle in the tibiofibula, and an extra bone caudal to the ilium.
Fig. 1 in International Journal for Parasitology: Parasites and Wildlife Outbreak of parasite-induced limb malformations in a declining amphibian species in Colorado
Fig. 1. (A) Spring Brook North (SBN) Pond is located in southern Boulder County near Eldorado Springs, Colorado, USA. (B) Image of the pond in spring. (C) Northern leopard frogs (Rana pipiens) use the pond as breeding habitat (image copyright David Herasimtschuk).
Fig. 2 in International Journal for Parasitology: Parasites and Wildlife Outbreak of parasite-induced limb malformations in a declining amphibian species in Colorado
Fig. 2. Limb malformations in leopard frogs from this study include (A–D) skin webbings, which can affect one (A–B) or both (C–D) hind limbs; (E–H) bony triangles, which entail a triangular folding in a longbone and an associated shortening of the limb; and (H–K) extra limbs, feet, and digits, which were typically ventral. Frog in (H) exhibits a double bony triangle and severe truncation in the limb with a duplicated foot. Many animals exhibited multiple malformations and severe structural limb deformities, such as (L).
Fig. 2 a in Circulating dengue virus serotypes and vertical transmission in AEdES larvae during outbreak and inter-outbreak seasons in a high dengue risk area of Sri Lanka
Fig. 2 a Distribution of dengue cases in the Kegalle District and Mawanella MOH area, Sri Lanka from December 2015 to March 2017. b Distribution of DENV serotypes in patients and distribution of Aedes mosquito larvae in and around the residences of dengue patients in Mawanella from December 2015 to March 2017. Abbreviations: DENV1, -2, -3, -4, DENV serotypes 1, 2, 3, 4
Shift in Circulating Human Adenovirus Species Leading to Nationwide Outbreak - China, January 2023-August 2024
<p><span>Detailed methodologies and data quality control standards are provided</span><span> in the supplementary materials</span></p>
Data of "Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics"
<p>The data reported in the paper: Sajjadi et al. (2021) Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics. PLoS ONE 16(7): e0253563. https://doi.org/10.1371/journal.pone.0253563<br> Each directory contains the data illustrated in one figure. The data structure and properties are described in .info files within each directory.</p> <p><br> All the simulations, analyses and illustrations have been conducted via the Epyc package (written in C++ and Python), developed by Sina Sajjadi. Epyc is available under GPLv3, at https://github.com/Sepante/Epyc.</p>
Variation in herbivore space use: comparing two savanna ecosystems with different anthrax outbreak patterns in southern Africa
<p><span>Background</span></p> <p><span>The distribution of resources can affect animal range sizes, which in turn may alter infectious disease dynamics in heterogenous environments. The risk of pathogen exposure or the spatial extent of outbreaks may vary with host range size. This study examined the range sizes of herbivorous anthrax host species in two ecosystems and relationships between spatial movement behavior and patterns of disease outbreaks for a multi-host environmentally transmitted pathogen. </span></p> <p><span>Methods</span></p> <p><span>We examined range sizes for seven host species and the spatial extent of anthrax outbreaks in Etosha National Park, Namibia and</span><span> Kruger National Park, South Africa, where the main host species and outbreak sizes differ</span><span>. We evaluated host range sizes using the local convex hull method at different temporal scales, within-individual temporal range overlap, and relationships between ranging behavior and species contributions to anthrax cases in each park. We estimated the spatial extent of annual anthrax mortalities and evaluated whether the extent was correlated with case numbers of a given host species. </span></p> <p><span>Results</span></p> <p><span>Range size differences among species were not linearly related to anthrax case numbers. In Kruger t</span><span>he main host species </span><span>had small range sizes and high range overlap, which may heighten exposure when outbreaks occur within their ranges. However, different patterns were observed in Etosha, where the main host species had large range sizes and relatively little overlap. The spatial extent of anthrax mortalities was similar between parks but less variable in Etosha than Kruger. In Kruger outbreaks varied from small local clusters to large areas and the spatial extent correlated with case numbers and species affected. </span><span>Secondary host species contributed relatively few cases to outbreaks; however, for these species with large range sizes, case numbers positively correlated with outbreak extent.</span></p> <p><span>Conclusions</span></p> <p><span>Our results provide new information on the spatiotemporal structuring of ranging movements of anthrax host species in two ecosystems. The results linking anthrax dynamics to host space use are correlative, yet suggest that, though partial and proximate, host range size and overlap may be contributing factors in outbreak characteristics for environmentally transmitted pathogens. </span></p>
Crowdsourced COVID-19 Cases and Outbreaks across Canadian Schools 2020-21: COVID Schools Canada
<p>This archive contains the final data freeze for COVID Schools Canada, and the software used to compile, clean, and plot the data. </p> <p>The <strong>Canada COVID-19 School Tracker</strong> was a 100% volunteer-led project tracking COVID-19 cases and outbreaks in schools across Canada from September 2020 to June 2021. The goal of this project was to highlight the impact of COVID-19 on schools and families; to advocate for safer schools; and to advocate for transparency in our educational system.<br> This project is an initiative of grassroots advocacy group <a href="https://masks4canada.org/">Masks4Canada</a>.</p> <p>To learn more about project and see the interactive map of COVID-19 cases and outbreaks across Canadian schools as compiled by this project, visit <a href="https://covidschoolscanada.org/">https://covidschoolscanada.org/ </a></p> <p>For questions about these data, please contact <a href="mailto:shraddha.pai@utoronto.ca?subject=COVID%20Schools%20Canada%20Zenodo%20archive">Shraddha Pai</a>.</p>
The MALaria Spatio-temporal Wind-Outbreak Trajectories Simulation (MALSWOTS)
<p>A mechanistic-stochastic algorithm to identify clusters of super-spreader houses and their related stable hotspots by accounting for mosquito flight capabilities and the spatial configuration of malaria infections at the house level.</p>
Genomic epidemiology unveils the dynamics and spatial corridor behind the Yellow Fever virus outbreak in Southern Brazil
<p>Despite the considerable morbidity and mortality of yellow fever virus (YFV) infections in Brazil our understanding of disease outbreaks is hampered by limited viral genomic data. Determining the timing and spatial corridors of YFV spread, as well as the geographic hotspots that link the endemic north of the country with epidemic extra-Amazonian regions, are central to predicting and preventing future outbreak and epidemics. Here, we tracked the recent spread of the virus by integrating genome sequences with both epidemiological and vector data. Through a combination of phylogenetic and epidemiological models we reconstructed the recent transmission history of YFV within different epidemic seasons in Brazil. A suitability index based on the highly domesticated <em>Aedes aegypti</em> was able to capture the seasonality of reported human infections. Spatial modelling revealed spatial hotspots with both past reporting and low vaccination coverage, which coincided with many of the largest urban centres in the Southeast. Phylodynamic analysis unravelled the circulation of three distinct YFV lineages, and provided proof of the directionality of a known spatial corridor of viral spread that connects the endemic North with the extra-Amazonian basin. This study illustrates that genomics linked with eco-epidemiology in a One Health framework can provide new insights into the landscape of YFV transmission, augmenting traditional approaches to infectious disease surveillance and control.</p>
Mysterious microsporidians: springtime outbreaks of disease in Daphnia communities in shallow pond ecosystems
<p>Parasites can play key roles in ecosystems, especially when they infect common hosts that play important ecological roles. <em>Daphnia</em> are critical grazers in many lentic freshwater ecosystems and typically reach peak densities in early spring. <em>Daphnia</em> have also become prominent model host organisms for the field of disease ecology, although most well-studied parasites infect them in summer or fall. Here, we report field patterns of virulent microsporidian parasites that consistently infect <em>Daphnia</em> in springtime, in a set of seven shallow ponds in Georgia, USA, sampled every 3–4 weeks for 18 months. We detected two distinct parasite taxa, closely matching sequences of <em>Pseudoberwaldia</em> <em>daphniae</em> and <em>Conglomerata</em> <em>obtusa</em>, both infecting all three resident species of <em>Daphnia</em>: <em>D. ambigua, D. laevis, </em>and<em> D. parvula</em>. To our knowledge, neither parasite has been previously reported in any of these host species or anywhere in North America. Infection prevalence peaked consistently in February-May, but the severity of these outbreaks differed substantially among ponds. Moreover, host species differed markedly in terms of their maximum infection prevalence (5% [<em>D. parvula</em>] to 72% [<em>D. laevis</em>]), mean reduction of fecundity when infected (70.6% [<em>D. ambigua</em>] to 99.8% [<em>D. laevis</em>]), mean spore yield (62,000 [<em>D. parvula</em>] to 377,000 [<em>D. laevis</em>] per host), and likelihood of being infected by each parasite. The timing and severity of the outbreaks suggest that these parasites could be impactful members of these shallow freshwater ecosystems and that the strength of their effects is likely to hinge on the composition of ponds' zooplankton communities.</p>
Data and code for: Disease outbreaks select for mate choice and coat color in wolves
<p><span>We know much about pathogen evolution and the emergence of new disease strains but less about host resistance and how it is signaled to other individuals and subsequently maintained. The cline in frequency of black-coated wolves across North America is hypothesized to result from a relationship with canine distemper virus (CDV) outbreaks. We test this hypothesis using cross-sectional data from wolf populations across North America that vary in the prevalence of CDV and the allele that makes coats black, longitudinal data from Yellowstone National Park, and modeling. The frequency of CDV outbreaks generates fluctuating selection that results in heterozygote advantage that in turn impacts the frequency of the black allele, the optimal mating behavior, and the black wolf cline across the continent.</span></p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.