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451 results for “outbreaks”
Environmental drivers of biseasonal anthrax outbreak dynamics in two multi-host savanna systems
<p>Environmental factors are common forces driving infectious disease dynamics. We compared inter-annual and seasonal patterns of anthrax infections in two multi-host systems in southern Africa: Etosha National Park, Namibia, and Kruger National Park, South Africa. Using several decades of mortality data from each system, we assessed possible transmission mechanisms behind anthrax dynamics, examining 1) within- and between-species case correlations, and 2) associations between anthrax mortalities and environmental factors, specifically rainfall and the Normalized Difference Vegetation Index (NDVI). Anthrax cases in Kruger had wide inter-annual variation in case numbers, and large outbreaks seemed to follow roughly a decadal cycle. In contrast, outbreaks in Etosha were smaller in magnitude and occurred annually. In Etosha, the host species commonly affected remained consistent over several decades, although plains zebra (<em>Equus quagga</em>) became relatively more dominant. In Kruger, turnover of the main host species occurred after the 1990s, where the previously dominant host species, greater kudu (<em>Tragelaphus strepsiceros</em>), was replaced by impala (<em>Aepyceros melampus</em>). In both parks, anthrax infections showed two seasonal peaks, with each species having only one peak in a year. Zebra, springbok (<em>Antidorcas marsupialis</em>), wildebeest (<em>Connochaetes taurinus</em>) and impala cases peaked in wet seasons, while elephant (<em>Loxodonta africana</em>), kudu and buffalo (<em>Syncerus caffer</em>) cases peaked in dry seasons. For common host species shared between the two parks, anthrax mortalities peaked in the same season in both systems. Among host species with cases peaking in the same season, anthrax mortalities were mostly synchronized, which may imply similar transmission mechanisms or shared sources of exposure. Between seasons, outbreaks in one species may contribute to more cases in another species in the following season. Higher vegetation greenness was associated with more zebra and springbok anthrax mortalities in Etosha, but fewer elephant cases in Kruger. These results suggest that host behavioral responses to changing environmental conditions may affect anthrax transmission risk, with differences in transmission mechanisms leading to multi-host biseasonal outbreaks. This study reveals the dynamics and potential environmental drivers of anthrax in two savanna systems, providing a better understanding of factors driving biseasonal dynamics and outbreak variation among locations.</p>
Supplementary Material: Climate-sensitive disease outbreaks in the aftermath of extreme climatic events: a scoping review
<p><strong>Supplemental experimental procedures</strong></p> <p><em>General Information</em></p> <p>Here we provide the data extraction of the studies retrieved for the scoping review "Climate-sensitive disease outbreaks in the aftermath of extreme climatic events" following PRISMA-ScR guidelines. Data were extracted for the following variables: title, first author, year of publication, country/region studied, extreme climate event, extreme climate event name (tropical cyclones are often named e.g. Typhoon Haiyan), Index used to measure climate anomaly, extreme climate event definition, text description of extreme climate event, disease, outbreak definition, time period of the study, data source, baseline/reference period, study design, statistics, outcome, outcome quantification, outbreak risk, qualitative description of extreme climate event and outbreak risk, time lag. Outcome was defined as either disease cases or incidence. </p>
Data: Guiding the design of SARS-CoV-2 genomic surveillance by estimating the resolution of outbreak detection
<p>Contains data necessary to reproduce the quantitative results related to a SARS-CoV-2 outbreak in NSW, Australia in the associated paper.</p> <p><strong>icpmr_delta_gisaid.csv</strong><br> Tabular data containing the GISAID accession numbers, dates of collection and submission for all sequences used in the NSW outbreak analysis. The epi set is available on GISAID as EPI_SET_220919ef. The <code>wgs_cluster</code> column contains identifiers of genomic clusters defined at ICPMR, NSW Health Pathology. A value of "Other" means that the sequence either did not belong to a cluster or was part of a cluster that contained fewer than 30 sequences in the study period, and sequences with this value should not be considered to form a single cluster.</p> <p><strong>icpmr_delta_gisaid.dists.tsv.gz</strong><br> Compressed pairwise SNP distance matrix in the format output by snp-dists. The script that creates this file from sequence data is available in the linked code archive.</p>
Georgetown Outbreak Activity Library (GOAL) dataset
<p>The Georgetown Outbreak Activity Library (GOAL) dataset is a research effort led by Dr. Rebecca Katz at the Georgetown University Center for Global Health Science and Security. The data is designed to support responders in understanding what needs to get done, by whom, and when in the context of an event, providing information on existing guidance and authorities and to define response requirements for new and emerging events. GOAL can also be used for preparedness and planning efforts to ensure that this work is comprehensive and based in the practical realities of outbreak response.</p> <p>The GOAL dataset is available as an Excel file (.xlsx) which includes data coded about response activities needed throughout all phases of an outbreak, with case studies available to exemplify these activities during preparedness, response, and recovery efforts. The GOAL dataset contains a comprehensive set of fields describing what needs to be done for each response activity, when, by whom, and under what circumstances. A Data Dictionary and Glossary are included in the Excel file download.</p> <p>In addition to the coded data, the GOAL Case Study PDF Files (.zip) folder contains the original case studies written by Georgetown researchers which exemplify many of the activities described in the GOAL dataset. </p> <p>To learn more about the project and interact with the data, visit <a href="https://outbreaklibrary.org/">https://outbreaklibrary.org/.</a> The complex data contained within the GOAL dataset have also been translated for a public audience into <em>The Outbreak Atlas, </em>a book by Rebecca Katz and Mackenzie S. Moore. </p>
Data for Seropositivity to Dengue virus DENV in three neighborhoods in the periphery of a city with a recent history of outbreaks in Argentina: what can we learn from unreported cases?
<p>This release include the datasets, R scripts and interactive maps generated for the manuscript: Seropositivity to Dengue virus DENV in three neighborhoods in the periphery of a city with a recent history of outbreaks in Argentina: what can we learn from unreported cases? Authors: DA Mendicino, T Ricardo, MA Cristaldi, M Maglianesi, G Guzmán S Claussen, RG Chiaraviglio, CA Ávalos, MA Previtali. (2024).</p>
Defoliator outbreaks track with warming across the Pacific coastal temperate rainforest of North America
<p>The biogeography of irruptive insect herbivores is determined by host availability and climate conditions. As such, outbreak distributions are sensitive to climatic change, especially across large latitudinal gradients. Here, we investigate the outbreak distributions of two understudied defoliators, hemlock sawfly (Hymenoptera; <em>Neodiprion tsugae</em>) and western blackheaded budworm (Lepidoptera; <em>Acleris gloverana</em>), that have both recently impacted the greatest land area recorded across the Pacific coastal temperate rainforest since the establishment of aerial survey programs. We compiled polygon-based estimates of insect damage collected by aerial observers, forest inventory, and downscaled climatic data to develop gridded estimates of bioclimatic conditions across the extent of the Pacific coastal temperate rainforest, including the continental United States, British Columbia, and Alaska. We leveraged these data to develop ensemble machine learning models with the goal of predicting the outbreak distribution of each insect. In this manuscript we: (1) describe the historical patterns of defoliator outbreaks, (2) identify and describe climatic conditions associated with outbreaks in both species, and (3) assess whether historic outbreaks have tracked geographic shifts in climate conditions across the region. We demonstrate that outbreaks of hemlock sawfly and western blackheaded budworm have been observed across the Pacific coastal temperature rainforests of North America in each decade since the establishment of the Canadian and United States aerial survey programs. The distribution of outbreaks by both insects were best explained by host availability, a limited range of spring, summer, and winter temperatures, and minimum precipitation. Finally, we demonstrate that outbreaks have tracked the poleward shift in suitable climate over the last century. This study establishes a baseline understanding of the climatic constraints and biogeographic patterns of historic sawfly and budworm outbreaks across the Pacific coastal temperate rainforest and emphasizes the overarching importance of climate in driving the irruptive dynamics of these defoliator species.</p>
Figure 7 in Diet and reproductive outputs of common barn-owl (Tyto alba) during the common vole (Microtus arvalis) outbreak and crash
Figure 7. GLMM diagrams illustrating the effect of the main and alternative prey taxa and the two derived indices on the number of fledglings (A: Common vole, B: Apodemus genus, C: Microtinae/Murinae ratio, D: Trophic level index).
Figure 5 in Diet and reproductive outputs of common barn-owl (Tyto alba) during the common vole (Microtus arvalis) outbreak and crash
Figure 5. GLMM diagrams illustrating the effect of the main and alternative prey taxa and the two derived indices on clutch size (A: Common vole, B–C: Apodemus genus, D–E: Microtinae/Murinae ratio, F: Trophic level index).
Figure 4 in Diet and reproductive outputs of common barn-owl (Tyto alba) during the common vole (Microtus arvalis) outbreak and crash
Figure 4. Box plots of the relative frequency of the main and alternative prey taxa. The bottom and top limits of each box are the lower and upper quartiles; error bars equal ±1.5 times the interquartile range; the horizontal black band within each box is the median; and the red triangle is the mean.
Figure 6 in Diet and reproductive outputs of common barn-owl (Tyto alba) during the common vole (Microtus arvalis) outbreak and crash
Figure 6. GLMM diagrams illustrating the effect of the main and alternative prey taxa and the two derived indices on the number of hatchlings (A: Common vole, B: Apodemus genus, C: Microtinae/Murinae ratio, D: Trophic level index).
Figure 3 in Diet and reproductive outputs of common barn-owl (Tyto alba) during the common vole (Microtus arvalis) outbreak and crash
Figure 3. Rank abundance curves of the prey composition of the common barn-owl in different outbreak and crash years, and cumulative results of these two periods.
Figure 2 in Diet and reproductive outputs of common barn-owl (Tyto alba) during the common vole (Microtus arvalis) outbreak and crash
Figure 2. Box plots of barn owls' breeding parameters (A: clutch size; B: number of hatchlings; C: number of fledglings). The bottom and top limits of each box are the lower and upper quartiles; error bars equal ±1.5 times the interquartile range; the horizontal black band within each box is the median; and the red triangle is the mean.
Figure 1 in Diet and reproductive outputs of common barn-owl (Tyto alba) during the common vole (Microtus arvalis) outbreak and crash
Figure 1. Study area in Baranya County (Hungary), showing the location of sampled nesting pairs (settlements).
Figure 1 in The Solar Activity Cycles and the Outbreaks of the Gypsy Moth - Lymantria dispar L. (Lepidoptera: Lymantriidae) in Serbia
Figure 1. Gypsy moth outbreaks and the solar flux at 2.8 GHz in the period 1948–2016 (the solar flux at 2.8 GHz data source: http://www.esrl.noaa.gov/psd/data/correlation/solar.data)
Figs. 1 and 2 in Sudden appearance and population outbreak of Eunica monima (Lepidoptera: Nymphalidae) on Desecheo Island, Puerto Rico
Figs. 1 and 2. Eunica monima outbreak on Bursera simaruba trees on Desecheo Island, Puerto Rico, Apr 2016, following island-wide invasive rat removal. Note that the level of damage from herbivory by larvae has lef the majority of the tree canopy branches leafless (both photos). Photos by Aaron B. Shiels, 8–10 Apr 2016. Figs. 3–6. Eunica monima adults collected during their outbreak (Apr 2016) in a Bursera simaruba dominated forest on Desecheo Island, Puerto Rico, following island-wide invasive rat removal. 3. Adult and abundant empty chrysalises on the trunk of B. simaruba. 4. Adult feeding on juices from fruit of Sideroxylon obova- tum Lamarck (Sapotaceae) (photos by Juan G. García-Cancel, 14–16 Apr 2016). 5 and 6. Voucher specimen (dorsal and ventral aspects) collected from Desecheo and genetically analyzed to confirm species identification (specimen was unfortunately rubbed and tattered when received). Collection data: USA, Puerto Rico, Desecheo Island, 18.385437°N, 67.480044°W, 8 Apr 2016; collector: A. B. Shiels (photos by William P. Haines).
Fig. 1 in Disappearance and Return of an Outbreak of the Coral-killing Cyanobacteriosponge in Southern Japan.
Fig. 1. (A) Location of Okinaerabu-jima Island, Kagoshima, Japan in the northwestern Pacific and, (B) map of Yakomo coast on Okinoerabu-jima Island. Red dotted box shows the Terpios hoshinota survey area, white dotted lines show the approximate area of T. hoshinota along the coast, and red solid lines approximate locations of permanent transects. Images from Google Earth.
Fig. 3 in Contrasting patterns of insecticide resistance and knockdown resistance (kdr) in Aedes aegypti populations from Jacarezinho (Brazil) after a Dengue Outbreak
Fig. 3. Allelic frequencies of 1016Val and 1016Ile in the Nav of A.aegypti populations from Jacarezinho in 2011 and 2012. Besides, the allelic frequencies of the Val1016Ile mutation by regions (Region I–IV) for 2012 are presented.
Fig. 2 in Contrasting patterns of insecticide resistance and knockdown resistance (kdr) in Aedes aegypti populations from Jacarezinho (Brazil) after a Dengue Outbreak
Fig. 2. Jacarezinho map shows the collection sites by regions in the urban area used for the analysis of the Val1016Ile mutation in 2012. Additionally, the main roads that cross Jacarezinho are presented.
Fig. 1 in Traceback of the Psoroptes outbreak in British Columbian bighorn sheep (Ovis Canadensis)
Fig. 1. Characteristic long segmented peduncle (circle) that differentiates the genus of Psoroptes spp. from other psoroptidae that have relatively short unsegmented peduncles. (40× magnification captured on a Zeiss Universal compound light microscope outfitted with a TRke SPOT camera using SPOT image capture software).
Fig. 4 in Traceback of the Psoroptes outbreak in British Columbian bighorn sheep (Ovis Canadensis)
Fig. 4. Distribution of outer opisthosomal setae (OOS) lengths of Psoroptes collected from rabbits (labelled Rabbit), USA bighorn sheep (labelled BHS_USA), and Canada-outbreak associated bighorn sheep (labelled BHS_CAN). Each is marked with the province or state of host origin. Horizontal lines represent median OOS of each host grouping.
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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.