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451 results for “outbreaks”
Data from: Is salvage logging effectively dampening bark beetle outbreaks and preserving forest carbon stocks?
<p>The published dataset contains the result of the paper titled <em><strong>Is salvage logging effectively dampening bark beetle outbreaks and preserving forest carbon stocks? </strong></em></p> <p>The first sheet contains time averages for the 104years simulation period for several variables driven by different climate conditions and salvaging intensities. Other sheets shows data for the Appendices: time series for reference climate and one climate model scenario, time averages of salvaged and removed C and finally the time series of number of frost days.</p> <p>See more details about target area, and iLand model:</p> <p>https://www.sciencedirect.com/science/article/pii/S0168192318302946</p> <p>http://iland.boku.ac.at/startpage</p> <p> </p> <p>contact: Laura Dobor; dobor.laura@gmail.com</p>
Fig. 2 in Traceback of the Psoroptes outbreak in British Columbian bighorn sheep (Ovis Canadensis)
Fig. 2. Map of the sample origin locations and associated host groups of Psoroptes samples used.
Shift in Circulating Human Adenovirus Species Leading to Nationwide Outbreak - China, January 2023-August 2024
<p><span>The list of pathogens detected by the tNGS used in this study</span></p>
Data and metadata associated with ice-nucleating particles during the 2022 Arctic Cold Air Outbreak Campaign
<p>Data and metadata associated with analysis of ice-nucleating particle concentrations and aerosol-size distributions measured during the March 2022 Arctic Cold Air Outbreak campaign.</p> <p>Contains INP concentrations and aerosol-size normalisations of these, parametrisations of these, SEM data and metadata and backtrajectory modelling inputs and results.</p>
Table 2 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
<p><b>Table 2</b> Distribution of DENV serotypes in patients with suspected dengue and in <i>Aedes</i> mosquito larvae</p><table><tbody><tr><th>Patient no.</th><th><i>Ae. aegypti</i></th><th><i>Ae. albopictus</i></th><th>DENV serotype identified in mosquito pools</th><th>DENV serotype identified in patients</th></tr></tbody><tbody><tr><th>1</th><td>Detected</td><td>ND</td><td>DENV-3</td><td>DENV-3</td></tr><tr><th>2</th><td>ND</td><td>Detected</td><td>DENV-1</td><td>DENV-1</td></tr><tr><th>3</th><td>ND</td><td>Detected</td><td>DENV-3</td><td>DENV-3</td></tr><tr><th>4</th><td>ND</td><td>Detected</td><td>DENV-4</td><td>ND</td></tr><tr><th>5</th><td>ND</td><td>Detected</td><td>DENV-3</td><td>ND</td></tr><tr><th>6</th><td>ND</td><td>Detected</td><td>DENV-1</td><td>ND</td></tr><tr><th>7</th><td>Detected</td><td>ND</td><td>DENV-2</td><td>ND</td></tr><tr><th>8</th><td>Detected</td><td>ND</td><td>DENV-1</td><td>ND</td></tr><tr><th>9</th><td>Detected</td><td>ND</td><td>DENV-1</td><td>ND</td></tr><tr><th>10</th><td>ND</td><td>Detected</td><td>DENV-3</td><td>ND</td></tr><tr><th>11</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>ND</td></tr><tr><th>12</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>DENV-1</td></tr><tr><th>13</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>ND</td></tr><tr><th>14</th><td>ND</td><td>Detected</td><td>DENV-4</td><td>ND</td></tr><tr><th>15</th><td>ND</td><td>Detected</td><td>DENV-1</td><td>ND</td></tr><tr><th>16</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>DENV-2</td></tr></tbody></table><p><i>ND</i> Not detected</p>
Table 1 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
<p><b>Table 1</b> Distribution of <i>Aedes</i> mosquito larvae in and around residences of patients with suspected dengue in Mawanella from December 2015 to March 2017</p><table><tbody><tr><th>Period</th><th>Month and year of sample collection</th><th>Total no. of vector pools collected in entomological survey</th><th>No. of <i>Aedes</i> mosquito pools identified</th></tr><tr><th><i>Ae. aegypti</i></th><th><i>Ae. albopictus</i></th></tr></tbody><tbody><tr><th>Epidemic</th><td>12/2015</td><td>18</td><td>3</td><td>15</td></tr><tr><th></th><td>1/2016</td><td>22</td><td>8</td><td>14</td></tr><tr><th>Inter-epidemic</th><td>2/2016</td><td>5</td><td>0</td><td>5</td></tr><tr><th></th><td>3/2016</td><td>3</td><td>1</td><td>2</td></tr><tr><th></th><td>4/2016</td><td>4</td><td>1</td><td>3</td></tr><tr><th></th><td>5/2016</td><td>12</td><td>1</td><td>11</td></tr><tr><th></th><td>6/2016</td><td>15</td><td>9</td><td>6</td></tr><tr><th>Epidemic</th><td>7/2016</td><td>7</td><td>1</td><td>6</td></tr><tr><th></th><td>8/2016</td><td>5</td><td>2</td><td>3</td></tr><tr><th></th><td>9/2016</td><td>5</td><td>2</td><td>3</td></tr><tr><th>Inter-epidemic</th><td>10/2016</td><td>6</td><td>1</td><td>5</td></tr><tr><th></th><td>11/2016</td><td>6</td><td>1</td><td>5</td></tr><tr><th>Epidemic</th><td>12/2016</td><td>14</td><td>3</td><td>11</td></tr><tr><th></th><td>1/2017</td><td>23</td><td>8</td><td>15</td></tr><tr><th>Inter-epidemic</th><td>2/2017</td><td>1</td><td>0</td><td>1</td></tr><tr><th></th><td>3/2017</td><td>25</td><td>8</td><td>17</td></tr><tr><th>Total</th><td></td><td>171</td><td>49</td><td>122</td></tr></tbody></table>
Data and codes for "The impact, costs, and cost-effectiveness of tuberculosis outbreak investigations in the United States: a model-based analysis"
<p>Data and codes for the manuscript entitled:</p> <p>"<strong>The impact, costs, and cost-effectiveness of tuberculosis outbreak investigations in the United States: a model-based analysis"</strong></p> <p> </p> <p><strong>Please see Readme.txt for details</strong></p>
COV-BHP - Psychological Impact of the COVID-19 Outbreak on Health Professionals
<p>The COVID-19 pandemic had a massive impact on health care systems,<br> increasing the risks of psychological distress in health professionals. This database includes data from a study which assessed the prevalence of burnout and psychopathological conditions in health professionals working in a health institution in the Northern Italy, and identified socio-demographic, work-related and psychological predictors of burnout. Health professionals working in the hospitals of the Istituto Auxologico Italiano were asked to participate to an online anonymous survey investigating socio-demographic data, COVID-19 emergency-related work and psychological factors, state anxiety, psychological distress, post-traumatic symptoms and burnout.</p>
Dataset from: A curated DNA barcode reference library for parasitoids of northern European cyclically outbreaking geometrid moths
<p><span>Large areas of forests are annually damaged or destroyed by outbreaking insect pests. Understanding the factors that trigger and terminate such population eruptions has become crucially important, as plants, plant-feeding insects, and their natural enemies may respond differentially to the ongoing changes in the global climate. In northernmost Europe, climate-driven range expansions of the geometrid moths <em>Epirrita autumnata</em> and <em>Operophtera brumata</em> have resulted in overlapping and increasingly severe outbreaks. Delayed density-dependent responses of parasitoids are a plausible explanation for the ten-year population cycles of these moth species, but the impact of parasitoids on geometrid outbreak dynamics is unclear due to a lack of knowledge on the host ranges and prevalences of parasitoids attacking the moths in nature. To overcome these problems, we reviewed the literature on parasitism in the focal geometrid species in their outbreak range, and then constructed a DNA barcode reference library for all relevant parasitoid species based on reared specimens and sequences obtained from public databases. The combined parasitoid community of<em> E. autumnata</em> and <em>O. brumata</em> consists of 32 hymenopteran species, all of which can be reliably identified based on their barcode sequences. The curated barcode library presented here opens up new opportunities for estimating the abundance and community composition of parasitoids across populations and ecosystems based on mass barcoding and metabarcoding approaches. Such information can be used for elucidating the role of parasitoids in moth population control, possibly also for devising methods for reducing the extent, intensity, and duration of outbreaks.</span></p>
Data and Code: British Columbia beetle outbreaks and wildfires
<p>No description provided.</p>
On the Role of Sub-Grid Variability and Microphysics in Km-Scale Simulations of Mixed-Phase Clouds during Cold Air Outbreaks
<p>Model output data used in manuscript "On the Role of Sub-Grid Variability and Microphysics in Km-Scale Simulations of Mixed-Phase Clouds during Cold Air Outbreaks" currently under review in Journal of Geophysical Research - Atmosphere.</p>
Food and waterborne outbreaks data complementing the European Union One Health 2021 Zoonoses Report
<p>Food and waterborne outbreaks data reported under the framework of Directive 2003/99/EC and in accordance with the update of the technical specifications for harmonised reporting of FBOs through the EU reporting system in accordance with Directive 2003/99/EC. This dataset includes the number of outbreaks, as well as the number of human cases, hospitalisations and deaths, per causative agent. In addition, other information can include data on causative agents, food vehicles, and the factors in food preparation and handling that contributed to the food-borne outbreaks. Reporting countries can also provide information on the nature of the evidence supporting the suspicion of the food vehicle. This evidence can be epidemiological, microbiological, descriptive environmental, or based on product tracing investigations. </p>
Dataset incr1 - NGS-based S. aureus typing and outbreak analysis in clinical microbiology laboratories: lessons learned from a Swiss-wide proficiency test
<p>Supplemental material of article "NGS-based S. aureus typing and outbreak analysis in clinical microbiology laboratories: lessons learned from a Swiss-wide proficiency test" by D. Dylus et al. Please refer to Methods therein.</p> <p>FASTQ datasets for increment 1. </p>
Macroeconomic Impact of Ebola outbreaks in SSA and potential mitigation of GDP loss with prophylactic vaccination programs
<p>Introduction: Decisions about prevention of and response to Ebola outbreaks require an understanding of the macroeconomic implications of these interventions. Prophylactic vaccines hold promise to mitigate the negative economic impacts of infectious disease outbreaks. The objective of this study was to evaluate the relationship between outbreak size and economic impact among countries with recorded Ebola outbreaks and to quantify the hypothetical benefits of prophylactic Ebola vaccination interventions in these outbreaks.</p> <p>Methods: The synthetic control method was used to estimate the causal impacts of Ebola outbreaks on per capita gross domestic product (GDP) of five countries in sub-Saharan Africa that have previously experienced Ebola outbreaks between 2000 and 2016, where no vaccines were deployed. Using illustrative assumptions about vaccine coverage, efficacy, and protective immunity, the potential economic benefits of prophylactic Ebola vaccination were estimated using the number of cases in an outbreak as a key indicator.</p> <p>Results: The impact of Ebola outbreaks on the macroeconomy of the selected countries led to a decline in GDP of up to 36%, which was greatest in the third year after the onset of each outbreak and increased exponentially with the size of outbreak (i.e., number of reported cases). Over three years, the aggregate loss estimated for Sierra Leone from its 2014-2016 outbreak is estimated at 16.1 billion International$. Prophylactic vaccination could have prevented up to 89% of an outbreak’s negative impact on GDP, reducing the outbreak’s impact to as little as 1.6% of GDP lost. </p> <p>Conclusion: This study supports the case that macroeconomic returns are associated with prophylactic Ebola vaccination. Our findings support recommendations for prophylactic Ebola vaccination as a core component of prevention and response measures for global health security. </p>
Mechanical transmission of Dengue Virus by Aedes aegypti may influence disease transmission dynamics during outbreaks data
<strong><span>Summary</span></strong> <p class="MsoNormal"><em><span>Background</span></em><span>: Dengue virus outbreaks are increasing in number and severity worldwide. Viral transmission is assumed to require a minimum time period of viral replication within the mosquito midgut. It is unknown if alternative transmission periods not requiring replication are possible.</span></p> <p class="MsoNormal"><em><span>Methods</span></em><span>: We used a mouse model of dengue virus transmission to investigate the potential of mechanical transmission of dengue virus. We investigated minimal viral titres necessary for development of symptoms in bitten mice and used resulting parameters to inform a new model of dengue virus transmission within a susceptible population.</span></p> <p class="MsoNormal"><em><span>Findings</span></em><span>: Naïve mice bitten by mosquitoes immediately after they took partial blood meals from dengue infected mice showed symptoms of dengue virus, followed by mortality. Incorporation of mechanical transmission into mathematical models of dengue virus transmission suggests that this supplemental transmission route could result in larger outbreaks which peak sooner.</span></p> <p class="MsoNormal"><em><span>Interpretation</span></em><span>: The potential of dengue transmission routes independent of midgut viral replication has implications for vector control strategies that target mosquito lifespan and suggest the possibility of similar mechanical transmission routes in other disease-carrying mosquitoes.</span></p>
Ecogeographic drivers of the spatial spread of highly pathogenic avian influenza outbreaks in Europe and North America, 2016–2022
<p>H5Nx highly pathogenic avian influenza (HPAI) viruses of clade 2.3.4.4 have caused outbreaks in Europe among wild and domestic birds since 2016 and were introduced to North America via wild migratory birds in December 2021. We examined the spatiotemporal extent of HPAI viruses across continents and characterize ecological and environmental predictors of virus spread between geographic regions through constructing a Bayesian phylodynamic generalized linear model (phylodynamic-GLM). Findings demonstrate localized epidemics of H5Nx throughout Europe in the first several years of the epizootic, followed by a singular branching point where H5N1 viruses were introduced to North America, likely via stopover locations throughout the North Atlantic. Once in the US, H5Nx viruses spread at a greater rate between US-based regions and no evidence demonstrated spread back to any European region. We establish that geographic proximity is a predictor of virus spread between regions, which implies that inter-continental transport across the Atlantic Ocean is relatively rare. Increase in mean ambient temperature over time was predictive of reduced H5Nx virus spread, which may reflect the effect of climate change on declines in host species abundance, decreased persistence of the virus in the environment, or changes in migratory patterns due to ecological alterations. Our data provide new knowledge about the spread and directionality of H5Nx virus dispersal in Europe and North America during an actively evolving inter-continental outbreak, including predictors of virus movement between regions, which will contribute to surveillance and mitigation strategies as the outbreak unfolds, and in future instances of uncontained avian spread of HPAI viruses.</p>
Limited outbreak of highly pathogenic influenza A(H5N1) virus in a Herring Gull colony, Canada, 2022
<p class="MsoNormal">In summer 2022, highly pathogenic influenza A(H5N1) virus reached the Herring Gull (<em>Larus argentatus</em>) breeding colony on Kent Island, New Brunswick, Canada. Real-time monitoring revealed a self-limiting outbreak with low mortality. Proactive seabird surveillance is crucial for monitoring such limited outbreaks, protecting vulnerable seabirds, and tracing potential zoonotic transmission routes.</p>
Early detection and environmental drivers of sewage fungus outbreaks in rivers
<p>Sewage effluent is a major ongoing threat to water quality and biodiversity in freshwater environments. It can cause outbreaks of sewage fungus (filamentous bacteria which form macroscopic masses) but, until now, these were only qualitatively recorded from visual inspection, ignoring microscopic forms. Here, we used an innovative method which combines machine learning, microscopy and flow cytometry, to rapidly and efficiently quantify the presence and abundance of sewage fungus in rivers. Our study involved 11 rivers with (n=6) and without (n=5) sewage input in the south-west of England over four sampling occasions. We were able to detect and enumerate the filaments before masses became visible to the naked eye and, as expected, we found a higher number of filaments downstream of sites where treated sewage was offloaded into the river. Therefore, our detection method could be used as a 'canary in the coal mine' for future outbreaks allowing early intervention. Combining our quantitative data on filaments with data on the physical and chemical parameters of the rivers, we found that high conductivity, sulphate, nitrates and TDS were associated with the presence and proliferation of sewage fungus. This information can be extremely useful for regulatory bodies and water companies to develop mitigating strategies and action to prevent future outbreaks.</p>
Data for modelling of bark beetle damage and outbreaks in Austria
<p>The data shows salvage logging amounts caused by the European spruce bark beetle (Ips typographus) in Austrian political district resolution combined with climatic and forest structure parameters for the same year and district.</p> <p>The data set comprises of 6 files:</p> <ul> <li><strong>Data_Geography.csv</strong> <strong>:</strong> Collected data of the considered political districts of Austria, naming convention for the rest of the files, total area, population and population density of 2023, number of municipalities and the reference latitude, longitude and elevation for the "district center" chosen in this analysis.<br> </li> <li><strong>Data_Climate_AUTDistrictCenters.csv</strong> <strong>:</strong> Data extracted or calculated from Copernicus E-OBS Dataset and mapped to reference district centers given in the <em>Data_Geography.csv</em> file. Climate parameters include temperatures (minimum, maximum, average), precipitation, humidity, radiation, windspeed plus bark beetle-relevant calculated parameters like degreedays, estimated start and end date of brooding season, and frostdays during winter that indicate overwintering success of bark beetles.<br> </li> <li><strong>Data_BMLRT_AnnualLoggingReports.xlsx</strong> <strong>:</strong> Collected data from Austrian logging reports in political district-resolution, stating salvage logging from bark beetle and storm damage to deciduous trees yearly from 2003-2022. Units are Efm (harvest cubic meters), Vfm (stcok cubic meters) and ha (hectar). Around 95% of bark beetle damages to deciduous trees were identified to be caused by <em>Ips typugraphus</em> to <em>Picea abies</em>.<br> </li> <li><strong>Data_BWF_DocumentationOfForestdamagefactors.xlsx</strong> <strong>:</strong> Collected data from Austrian documentation of forest damaging agents mostly in federal state-level resolution, stating bark beetle and storm damage to forests from 1989-2022.<br> </li> <li><strong>Data_BWF_ForestInventory.csv</strong> <strong>:</strong> Collected data from Austrian forest inventories in political district-resolution yearly from 1996-2021, including total district area , total forest area, total coniferous forest area, total spruce area and associated shares and stocks, as well as some scarce data on dead wood.<br> </li> <li><strong>Data_Merged_NaNcleared.csv</strong> <strong> :</strong> Table that contains all overlapping and imputed data from above, cleared of NaN values. Ready for further calculations or analysis.</li> </ul> <p> </p> <p>The python scripts for calculating the present (and more) bark beetle-relevant parameters can be found on GitHub: <em>https://github.com/nadinefreistetter/barkbeetle_outbreak_scripts</em> in .ipynb format.</p> <p> </p> <blockquote> <p>These data were prepared for the International Institute of Applied Systems Analysis Young Scientists Summer Program 2023. The report will be available online in 2024. The work of Freistetter has been carried out with funding from the Academy of Finland (decision number 341311).</p> </blockquote>
The Psychological Impact of COVID-19 Outbreak on COVID-19 Survivors and Their Families
ClinicalTrials.gov study NCT04365348. IPD Sharing: NO. Countries: 1. Publications: 2.
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.