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45 results for “Disease Ecology”
FIG. 2 in Amphibian Disease Ecology: Are We Just Scratching the Surface?
FIG. 2.—Percentage distribution of investigated pathogens (A) and host life stage (B) in the amphibian disease literature between 2009 and 2019.
FIG. 3 in Amphibian Disease Ecology: Are We Just Scratching the Surface?
FIG. 3.—Percentage distribution of investigated pathogens and associated host life stage in chytridomycota (A, B), ranaviruses (C, D), and helminths (E,
FIG. 1 in Amphibian Disease Ecology: Are We Just Scratching the Surface?
FIG. 1.—Flow diagram of basic relationships between amphibian host–pathogen systems and environmental factors. Adapted from Gray et al. 2009.
Effects of Ecological Rythmic-acoustic Stimulation (E-RAS) on Motor Skills in Individuals With Parkinson's Disease
ClinicalTrials.gov study NCT03228888. IPD Sharing: NO. Countries: 1. Publications: 1.
Ecological Momentary Assessment and Physical Activity in Patients With Inflammatory Rheumatic Diseases
ClinicalTrials.gov study NCT07167784. IPD Sharing: YES. Countries: 1. Publications: 0.
Data from: Natural enemy ecology: comparing the effects of predation risk, infection risk and disease on host behavior
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Evolution of Castanea in North America: RADseq and ecological modeling reveal a history of radiation, range shifts, and disease
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Data from: Anthropogenic and ecological drivers of amphibian disease (Ranavirosis)
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List of papers reviewed to uncover trends in the use of model systems in infectious disease ecology & evolutionary biology
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Data from: Invasion of two tick-borne diseases across New England: harnessing human surveillance data to capture underlying ecological invasion processes
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Building an ecologically-founded disease risk prioritization framework for migratory species based on contact with livestock
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Data from: Host and pathogen ecology drive the seasonal dynamics of a fungal disease, white-nose syndrome
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Data from: Missing the people for the trees: identifying coupled natural-human system feedbacks driving the ecology of Lyme disease
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Data from: Cross-scale dynamics in community and disease ecology: relative timescales shape the community ecology of pathogens
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Data from: Ecological and evolutionary effects of fragmentation on infectious disease
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Data from: The ecology of wildlife disease surveillance: demographic and prevalence fluctuations undermine surveillance
Wildlife disease surveillance is the first line of defence against infectious disease. Fluctuations in host populations and disease prevalence are a known feature of wildlife disease systems. However, the impact of such heterogeneities on the performance of surveillance is currently poorly understood. We present the first systematic exploration of the effects of fluctuations' prevalence and host population size on the efficacy of wildlife disease surveillance systems. In this study, efficacy is measured in terms of ability to estimate long-term prevalence and detect disease risk. Our results suggest that for many wildlife disease systems, fluctuations in population size and disease lead to bias in surveillance-based estimates of prevalence and overconfidence in assessments of both the precision of prevalence estimates and the power to detect disease. Neglecting such ecological effects may lead to poorly designed surveillance and ultimately to incorrect assessments of the risks posed by disease in wildlife. This will be most problematic in systems where prevalence fluctuations are large and disease fade-outs occur. Such fluctuations are determined by the interaction of demography and disease dynamics. Although particularly likely in highly fluctuating populations typical of fecund short-lived hosts, such fluctuations cannot be ruled out in more stable populations of longer-lived hosts. Synthesis and applications. Fluctuations in population size and disease prevalence should be considered in the design and implementation of wildlife disease surveillance, and the framework presented here provides a template for conducting suitable power calculations. Ultimately, understanding the impact of fluctuations in demographic and epidemiological processes will enable improvements to wildlife disease surveillance systems leading to better characterization of, and protection against endemic, emerging and re-emerging disease threats.
Data from: Discovery and exploitation of a natural ecological trap for a mosquito disease vector
Ecological traps occur due to a mismatch between a habitat's attractiveness and quality, wherein organisms show preference for low-quality habitats over other available high-quality habitats. Our previous research identified leaf litter from common blackberry (Rubus allegheniensis) as a natural ecological trap for an important vector for West Nile virus (Culex pipiens), attracting mosquitoes to oviposit in habitats deleterious to the survival of their larvae. Here we demonstrate that manipulation of leaf litter in stormwater catch basins, an important source of disease vector mosquitoes in urban environments, can increase Cx. pipiens oviposition but reduce survival. In a series of experiments designed to elucidate the mechanisms that explain the attractive and lethal properties of this native plant, behavioral bioassays suggest that oviposition site selection by Cx. pipiens is mediated primarily by chemical cues as leaves decompose. However, we also show that juvenile mosquito survival mainly is related to the suitability of the bacterial community in the aquatic habitat for mosquito nutritional needs, which does not appear to create a cue that influences oviposition choice. This mismatch between oviposition cues and drivers of larval habitat quality may account for the ecological trap phenomenon detected in this study. Our findings provide new insights into potential mechanistic pathways by which ecological traps may occur in nature and proof-of-concept for a new 'attract-and-kill' tool for mosquito control.
Demography, education, and research trends in the interdisciplinary field of disease ecology
<p><strong><em>Description of Supporting Files </em></strong></p> <p><strong>Demography, education, and research trends in the interdisciplinary field of disease ecology </strong></p> <p>Ellen E. Brandell, Daniel J. Becker, Laura Sampson, Kristian M. Forbes </p> <p> </p> <p><strong>TopArticles_Inclusion.xlsx</strong></p> <p>This Excel provides a list of influential articles written in by survey participants at least two times. </p> <p>Sheet “table”: just tabular information</p> <p>Sheet “withNotes”: includes notes about data, number of citations from survey participants, and percent inclusion calculations.</p> <p>Columns are:</p> <ul> <li>‘INCLUDED’: if the article appeared in the corpus (1) or not (0)</li> <li>‘COUNT’: the number of times survey participants wrote in the article</li> <li>‘ARTICLE’: article citation Percent of articles included in the corpus are calculated for 4 or more write-ins, 3-write-ins, 2 write-ins, and across all articles written in twice. </li> </ul> <p> </p> <p><strong>IRB_Correspondence_STUDY00010582.pdf</strong></p> <p>Institutional Review Board correspondence and approval from Pennsylvania State University. Survey response data may be available upon request from the corresponding author. To protect participants, any potentially identifying information will be removed prior to filling a request. See the online Supporting Information for this article for extensive reporting of survey results prior to a request. </p> <p> </p> <p><strong>FullSurvey.pdf</strong></p> <p>A PDF of the full survey form. </p> <p> </p> <p><strong>CorpusFrequencyAnalysis.ipynb</strong></p> <p>This is the Python script used for corpus organization and the topic detection analysis. It includes some plot generation.</p>
Evaluation of a Socio-ecological Cardiovascular Disease Prevention Intervention for Ultra-Orthodox Jewish Hasidic Women
ClinicalTrials.gov study NCT03201523. IPD Sharing: NO. Countries: 0. Publications: 6.
Data from: Predicting the thermal and allometric dependencies of disease transmission via the metabolic theory of ecology
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ScienceDex guides
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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.