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44 results for “high transmission”
1-km high resolution model outputs using the WRF and WRF-Hydro model Raw data from the manuscipt "Process-based Atmosphere-Hydrology-Malaria Modeling: Performance for Spatio-temporal Malaria Transmission Dynamics in Sub-Saharan Africa "
<p>Here we provide the model outputs from the numerical climate model WRF (Weather Research and Forecasting) and its hydrological coupled model WRF-Hydro for the Health and Demographic Surveillance Systems (HDSS) site regions of Nouna in Burkina Faso. Model results are used for investigating the influence of surface hydrology representation, environmental and climate-sensitive driver factors on malaria incidence.<br>The experiments use the following model configuration: 1km horizontal resolution with 200*200 grid points, WSM6 microphysics, ACM2 PBL, and RRTM & Dudhia radiation scheme. WRF uses the Noah LSM, and WRF-Hydro uses the Noah LSM with enhanced lateral hydrological description (https://ral.ucar.edu/projects/wrf_hydro/overview). These simulations were conducted in the Karlsruhe Steinbuch Centre for Computing (SCC) Horeka.</p> <p>Model outputs are provided in daily step (originally derived from the hourly output). Filename with "wrf-hydro_pr_2000-2020_d02-1km.nc" provides Precipitation,<br>n mm/day"wrf-hydro_tas_2000-2020_d02-1km.nc" provides mean temperature in Celsius, "wrf-hydro_tasmax_2000-2020_d02-1km.nc" provides maximum temperature in Celsius, "wrf-hydro_tasmin_2000-2020_d02-1km.nc" provides minmum temperature in Celsius, "wrf-hydro_dtr_2000-2020_d02-1km.nc" provides diurnal temperature ranges in Celius, "wrf-hydro_rh_2000-2020_d02-1km.nc" provides relative humudity in % and "wrf-hydro_sw_2000-2020_d02-1km.nc" provides the surface hydrology.</p>
Supplementary Data: Full Results: Synergies of sector coupling and transmission extension in a cost-optimised, highly renewable European energy system
<p>Supplementary Data</p> <p><a href="https://arxiv.org/abs/1801.05290"><strong>Synergies of sector coupling and transmission extension in a cost-optimised, highly renewable European energy system</strong></a></p> <p>Authors: T. Brown, D. Schlachtberger, A. Kies, S. Schramm, M. Greiner</p> <p><a href="https://arxiv.org/abs/1801.05290">arXiv:1801.05290</a></p> <p>The files in this record contain the full output data from each of the scenarios considered in the above publication. They also include the post-processed input data, which might be useful if you want to rerun the scenarios with only small changes to the input data.</p> <p>The scripts to build the model, input data and result summaries can be found in a <a href="https://zenodo.org/record/1146665">companion Zenodo repository</a>. (The supplementary data was split because of the size of the full results.)</p> <p>For each scenario, there is a <a href="https://github.com/PyPSA/PyPSA">PyPSA</a> network file in <a href="https://en.wikipedia.org/wiki/Hierarchical_Data_Format">HDF5 format</a> and a CSV of shadow prices.</p> <p>To read in a network file do:</p> <pre><code class="language-python">import pypsa network = pypsa.Network("network_file_name.h5")</code></pre> <p>All data is released under the <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International Licence</a> (CC BY 4.0).</p>
High temperatures reduce growth, infection, and transmission of a naturally occurring fungal plant pathogen
<p>Climate change is rapidly altering the distribution of suitable habitats for many species as well as their pathogenic microbes. For many pathogens, including vector-borne diseases of humans and agricultural pathogens, climate change is expected to increase transmission and lead to pathogen range expansions. However, if pathogens have a lower heat tolerance than their host, increased warming could generate 'thermal refugia' for hosts. Predicting the outcomes of warming on disease transmission requires detailed knowledge of the thermal tolerances of both the host and the pathogen. Such thermal tolerance studies are generally lacking for fungal pathogens of wild plant populations, despite the fact that plants form the base of all terrestrial communities. Here, we quantified three aspects of the thermal tolerance (growth, infection, and propagule production) of the naturally occurring fungal pathogen <em>Microbotryum lychnidis-dioicae</em>, which causes a sterilizing anther-smut disease on the herbaceous plant <em>Silene latifolia</em>. We also quantified two aspects of host thermal tolerance: seedling survival and flowering rate. We found that temperatures >30 degreeC reduced the ability of anther-smut spores to germinate, grow, and conjugate in vitro. In addition, we found that high temperatures (30 degreeC) during, or shortly after the time of inoculation strongly reduced the likelihood of infection in seedlings. Finally, we found that high summer temperatures in the field temporarily cured infected plants, likely reducing transmission. Notably, high temperatures did not reduce survival or flowering of the host plants. Taken together, our results show that the fungus is considerably more sensitive to high temperatures than its host plant. A warming climate could therefore result in reduced disease spread or even local pathogen extirpation, leading to thermal refugia for the host.</p>
Data accompanying "Unipolar Quantum Optoelectronics for High Speed Direct Modulation and Transmission in 8-14 µm Atmospheric Window"
<p>This dataset contains measurement data for the results presented in "Unipolar Quantum Optoelectronics for High Speed Direct Modulation and Transmission in 8-14 µm Atmospheric Window".</p>
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
High temperatures reduce growth, infection, and transmission of a naturally occurring fungal plant pathogen
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Segmented high-resolution transmission electron microscopy images of nanoparticles
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Supplemental Material: High serological barriers may contribute to restricted Influenza-A-virus transmission between pigs and humans
<p>Human-to-swine (reverse zoonotic) transmission of seasonal and pandemic human influenza A viruses (IAV) to pigs primarily replenishes the vast reservoir of genetically and antigenically heterogeneous swine (sw) IAV maintained in domestic pigs worldwide. Sporadic but regularly observed cases of pig-to-human (zoonotic) infections with swIAV tend to be discovered by chance, with children being affected disproportionately often.</p> <p>Here, a total of 3070 porcine and 333 human nasal swab samples from 135 swine farms in Germany were investigated for IAV by real time RT-PCR and full genome sequencing. In addition, swIAV sequences generated in the frame of this study were analyzed to determine potential mutations for human MxA and BTN3A3 escape. </p> <div> <p><strong>01_Table S1: </strong>Summary of information of swine holdings and RT-qPCR results. 1 indicates applicable; 0 indicates not applicable; n.d. indicates not determined.</p> <p><strong>02_Table S2</strong>: Summary of information about human samples and. 1 indicates applicable; 0 indicates not applicable; n.d. indicates not determined.</p> <p><strong>03_Table S3: A.</strong> Comparison of relevant mutations in the genome of MWP/21, swine-MWP/21, and NRW/22 generated by Flusurver (http://flusurver.bii.a-star.edu.sg). 1 indicates the presence of mutation(s), 0 indicates the absence of those mutation(s).<strong> B.</strong> Visualization of the AA differences of affected segments of the zoonotic case MWP/21 and the corresponding sequence (sw-MWP/21) generated from pigs of the related herd. </p> <p><strong>04_Table S4: </strong>Accession number (EPI_ISL) of sequences analyzed in the frame of this study. All sequences are available on GISAID EpiFLU.</p> <p><strong>05_Table S5: </strong>Amino acids on positions in the nucleoprotein (NP) sequence associated with MxA resistance and BTN3A3 resistance of selected swIAV NP sequences. "av) indicates genome segments phylogenetically associated with the avian-derived H1 (1C), "pdm" indicates those of the human pandemic A/H1N1 2009 lineage (1A). </p> <p><strong>06_Figure S1: </strong>Phylogenic tree of swIAV H1 HA gene of the clades 1A, 1B and 1C annotated by global H1-lineage nomenclature by Anderson et al. (2016). Swine derived swIAV sequences generated in the frame of this study are colored in red, zoonotic cases MWP/21 and NRW/22 are colored in green. The reverse-zoonotic case is highlighted in violet with its closest related human sequence colored in green.<strong> </strong></p> <p><strong>07_Material and Methods:</strong> Description of material used and specification of applied methods in the frame of this study.</p> <p><strong>08_Questinonaire human participants:</strong> Questionaire used in the frame of this study.</p> <p><strong>09_Questinonaire swine farms:</strong> Questionaire used in the frame of this study.</p> </div> <p> </p>
Model-based analysis of tuberculosis genotype clusters in the United States reveals high degree of heterogeneity in transmission, and state-level differences across California, Florida, New York, and Texas.
<p>Data and codes for the publication</p>
Supplementary Data: Code, Input Data and Result Summaries: Synergies of sector coupling and transmission extension in a cost-optimised, highly renewable European energy system
<p>Supplementary Data</p> <p><a href="https://arxiv.org/abs/1801.05290"><strong>Synergies of sector coupling and transmission extension in a cost-optimised, highly renewable European energy system</strong></a></p> <p>Authors: T. Brown, D. Schlachtberger, A. Kies, S. Schramm, M. Greiner</p> <p><a href="https://arxiv.org/abs/1801.05290">arXiv:1801.05290</a></p> <p>The files in this record contain the scripts to build the model, input data and result summaries for the model PyPSA-Eur-Sec-30 described in the above publication.</p> <p>The full results files (which include the post-processed input data) can be found in a <a href="https://zenodo.org/record/1146649">companion Zenodo repository</a>. (The supplementary data was split because of the size of the full results.)</p> <p><strong>WARNING:</strong> A newer, improved version of this model, <a href="https://github.com/PyPSA/pypsa-eur-sec">PyPSA-Eur-Sec</a>, is under construction on GitHub.</p> <p><strong>Scripts</strong></p> <p>To use the scripts, you need the following free software Python libraries:</p> <ul> <li><a href="https://github.com/PyPSA/PyPSA">PyPSA</a> for the modelling framework</li> <li><a href="https://github.com/FRESNA/vresutils">vresutils</a> for various helper functions to build the model instance</li> <li><a href="https://github.com/FRESNA/atlite">atlite</a> to process weather data into power system data</li> <li><a href="https://snakemake.readthedocs.io/en/latest/">snakemake</a> to organise the execution of the software</li> </ul> <p>and other standard libraries from the <a href="https://pypi.python.org/pypi">Python Package Index</a> (PyPI), such as pandas, pyomo, countrycode, etc.</p> <p>snakemake requires that all code runs with Python version 3. The code setup is known to work with the following versions: PyPSA 0.12.0, pandas 0.21.1, numpy 0.14.0, scipy 0.19.1, pyomo 5.2. You may need to downgrade your libraries to these versions for the scripts to work. If you insist on using the latest versions, please be aware that you'll need to make at least the following changes:</p> <p>i) To accommodate changes in pandas versions 0.22 and higher, in scripts/prepare_network.py change "costs = costs.loc[idx[:,cost_year,:],"value"].unstack(level=2).groupby("technology").sum()" to "costs = costs.loc[idx[:,cost_year,:],"value"].unstack(level=2).groupby(level="technology").sum(min_count=1)".</p> <p>ii) In later versions of PyPSA the component groups like "pypsa.components.one_port_components" have become network-specific and are stored instead at "network.one_port_components".</p> <p>To solve the optimisation problem the scripts are coded to use the commercial solver <a href="http://www.gurobi.com/">Gurobi</a>. To solve the problems in a reasonable time, you will need <a href="http://www.gurobi.com/">Gurobi</a> or an equivalently fast solver such as <a href="https://www.ibm.com/analytics/data-science/prescriptive-analytics/cplex-optimizer">CPLEX</a>. <a href="http://www.gurobi.com/">Gurobi</a> and <a href="https://www.ibm.com/analytics/data-science/prescriptive-analytics/cplex-optimizer">CPLEX</a> both have cost-free licences for academic users.</p> <p>You will also need a computer with at least 64 GB of RAM, since pyomo and the solver are memory intensive.</p> <p>The Python scripts in this repository (in the directory scripts/) are released under the <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GNU General Public Licence Version 3.0</a> (GPL 3.0).</p> <p>The scripts build_*.py process all raw input data into a form where it can be used in the model.</p> <p>make_options.py prepares the options.yml file for each model run.</p> <p>prepare_network.py populates the PyPSA network for each model run with the input data.</p> <p>solve_network.py solves the optimisation problem with <a href="http://www.gurobi.com/">Gurobi</a> or the solver of your choice (this step takes several hours).</p> <p>make_summary.py aggregates the results into CSV files in the directory results/ (also provided in this repository).</p> <p>The scripts plot_*.py and paper_graphics*.py prepare graphical output.</p> <p>All scripts are managed with the <a href="http://snakemake.readthedocs.io/en/latest/">snakemake</a> workflow management tool.</p> <p>To run the scripts, adjust the parameters in config.yaml and cluster.yaml to your local configuration. Then simply execute</p> <pre><code>snakemake</code></pre> <p>for the rule you want to run.</p> <p>Since the jobs are computationally intensive you may want to run them on a cluster. To run the jobs on a cluster with <a href="https://slurm.schedmd.com/">Slurm</a>, then execute e.g.</p> <pre><code>./snakemake_cluster --jobs 6</code></pre> <p>The cluster is configured in cluster.yaml. You will need to create the directory for the logs, i.e. logs/cluster/, before running the script.</p> <p><strong>Data</strong></p> <p>All input data (in the directory scripts/) and results summaries (in the directory results/) are released under the <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International Licence</a> (CC BY 4.0), except those where explicit sources and licences are mentioned in the data folders.</p> <p>The input data include:</p> <ul> <li>Electricity sector data, which largely follows the <a href="https://doi.org/10.5281/zenodo.804337">Zenodo repository</a> for <strong><a href="https://doi.org/10.1016/j.energy.2017.06.004">The Benefits of Cooperation in a Highly Renewable European Electricity Network</a></strong>, except the current repository uses the <a href="https://data.open-power-system-data.org/time_series/2017-07-09/">Open Power System Data Time Series Data Package</a> for load data and <a href="http://renewables.ninja/">Renewables.ninja</a> for solar time series.</li> <li>Heating time series based on the degree-day approximation, constructed with the library <a href="https://github.com/FRESNA/atlite">atlite</a>.</li> <li>Hourly traffic statistics for a week from the German Federal Highway Research Institute (BASt).</li> <li>Yearly energy per country per sector from the <a href="http://www.indicators.odyssee-mure.eu/energy-efficiency-database.html">Odyssee database</a> and <a href="http://ec.europa.eu/eurostat/web/energy/data/energy-balances">Eurostat</a>.</li> <li>A cost database with literature sources.</li> </ul>
Fig. 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
Fig. 1 Map of Sri Lanka showing the location of Mawanella, the study area
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 from: Feeding sites promoting wildlife-related tourism might highly expose the endangered Yunnan snub-nosed monkey (Rhinopithecus bieti) to parasite transmission. DOI: 10.1038/s41598-021-95166-5
<p>An increasing number of studies have found that the implementation of feeding sites for wildlife-related tourism can affect animal health, behaviour and reproduction. Feeding sites can favour high densities, home range overlap, greater sedentary behaviour and increased interspecific contacts, all of which might promote parasite transmission. In the Yunnan snub-nosed monkey (Rhinopithecus bieti), human interventions via provisioning monkeys at specific feeding sites have led to the sub-structuring of a group into genetically differentiated sub-groups. The fed subgroup is located near human hamlets and interacts with domesticated animals. Using high-throughput sequencing, we investigated Entamoeba species diversity in a local host assemblage strongly influenced by provisioning for wildlife-related tourism. We identified 13 Entamoeba species or lineages in faeces of Yunnan snub-nosed monkeys, humans and domesticated animals (including pigs, cattle, and domestic chicken). In Yunnan snub-nosed monkeys, Entamoeba prevalence and OTU richness were higher in the fed than in the wild subgroup. Entamoeba polecki was found in monkeys, pigs and humans, suggesting that this parasite might circulates between the wild and domestic components of this local social–ecological system. The highest proportion of faeces positive for Entamoeba in monkeys geographically coincided with the presence of livestock and humans. These elements suggest that feeding sites might indirectly play a role on parasite transmission in the Yunnan snub-nosed monkey. The implementation of such sites should carefully consider the risk of creating hotspots of disease transmission, which should be prevented by maintaining a buffer zone between monkeys and livestock/humans. Regular screenings for pathogens in fed subgroup are necessary to monitor transmission risk in order to balance the economic development of human communities dependent on wildlife-related tourism, and the conservation of the endangered Yunnan snub-nosed monkey.</p>
Data from: Multiple transmission routes sustain high prevalence of a virulent parasite in a butterfly host
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Understanding the High Temperature Hydrogen Attack of Steels Utilizing Novel In situ Analytical Transmission Electron Microscopy Techniques
<p>A series of <em>in situ</em> transmission electron microscopy videos detailing the chemical reaction of Fe<sub>3</sub>C carbides in Eutectoid steel with high-temperature hydrogen, demonstrating nano-scale high-temperature hydrogen attack (HTHA). From the Thesis of Thomas Woodward.</p>
Data from: Imperfect vaccination can enhance the transmission of highly virulent pathogens
Could some vaccines drive the evolution of more virulent pathogens? Conventional wisdom is that natural selection will remove highly lethal pathogens if host death greatly reduces transmission. Vaccines that keep hosts alive but still allow transmission could thus allow very virulent strains to circulate in a population. Here we show experimentally that immunization of chickens against Marek's disease virus enhances the fitness of more virulent strains, making it possible for hyperpathogenic strains to transmit. Immunity elicited by direct vaccination or by maternal vaccination prolongs host survival but does not prevent infection, viral replication or transmission, thus extending the infectious periods of strains otherwise too lethal to persist. Our data show that anti-disease vaccines that do not prevent transmission can create conditions that promote the emergence of pathogen strains that cause more severe disease in unvaccinated hosts.
Data from: High Rates of Asymptomatic, Sub-microscopic Plasmodium vivax Infection and Disappearing Plasmodium falciparum Malaria in an Area of Low Transmission in Solomon Islands
Introduction: Solomon Islands is intensifying national efforts to achieve malaria elimination. A long history of indoor spraying with residual insecticides, combined recently with distribution of long lasting insecticidal nets and artemether-lumefantrine therapy, has been implemented in Solomon Islands. The impact of these interventions on local endemicity of Plasmodium spp. is unknown. Methods: In 2012, a cross-sectional survey of 3501 residents of all ages was conducted in Ngella, Central Islands Province, Solomon Islands. Prevalence of Plasmodium falciparum, P. vivax, P. ovale and P. malariae was assessed by quantitative PCR (qPCR) and light microscopy (LM). Presence of gametocytes was determined by reverse transcription quantitative PCR (RT-qPCR). Results: By qPCR, 468 Plasmodium spp. infections were detected (prevalence=13.4%; 463 P. vivax, five mixed P. falciparum/P. vivax, no P. ovale or P. malariae) versus 130 by LM (prevalence=3.7%; 126 P. vivax, three P. falciparum and one P. falciparum/P. vivax). The prevalence of P. vivax infection varied significantly among villages (range 3.0-38.5%, p<0.001) and across age groups (5.3-25.9%, p<0.001). Of 468 P. vivax infections, 72.9% were sub-microscopic, 84.5% afebrile and 60.0% were both sub-microscopic and afebrile. Local residency, low education level of the household head and living in a household with at least one other P. vivax infected individual increased the risk of P. vivax infection. Overall, 23.5% of P. vivax infections had concurrent gametocytaemia. Of all P. vivax positive samples, 29.2% were polyclonal by MS16 and msp1F3 genotyping. All five P. falciparum infections were detected in residents of the same village, carried the same msp2 allele and four were positive for P. falciparum gametocytes. Conclusion: P. vivax infection remains endemic in Ngella, with the majority of cases afebrile and below the detection limit of LM. P. falciparum has nearly disappeared, but the risk of re-introductions and outbreaks due to travel to nearby islands with higher malaria endemicity remains.
Data from: High-resolution contact networks of free-ranging domestic dogs Canis familiaris and implications for transmission of infection
Contact patterns strongly influence the dynamics of disease transmission in both human and non-human animal populations. Domestic dogs Canis familiaris are a social species and are a reservoir for several zoonotic infections, yet few studies have empirically determined contact patterns within dog populations. Using high-resolution proximity logging technology, we characterised the contact networks of free-ranging domestic dogs from two settlements (n = 108 dogs, covering >80% of the population in each settlement) in rural Chad. We used these data to simulate the transmission of an infection comparable to rabies and investigated the effects of including observed contact heterogeneities on epidemic outcomes. We found that dog contact networks displayed considerable heterogeneity, particularly in the duration of contacts and that the network had communities that were highly correlated with household membership. Simulations using observed contact networks had smaller epidemic sizes than those that assumed random mixing, demonstrating the unsuitability of homogenous mixing models in predicting epidemic outcomes. When contact heterogeneities were included in simulations, the network position of the individual initially infected had an important effect on epidemic outcomes. The risk of an epidemic occurring was best predicted by the initially infected individual's ranked degree, while epidemic size was best predicted by the individual's ranked eigenvector centrality. For dogs in one settlement, we found that ranked eigenvector centrality was correlated with range size. Our results demonstrate that observed heterogeneities in contacts are important for the prediction of epidemiological outcomes in free-ranging domestic dogs. We show that individuals presenting a higher risk for disease transmission can be identified by their network position and provide evidence that observable traits hold potential for informing targeted disease management strategies.
The impact of indoor residual spraying on Plasmodium falciparum microsatellite variation in an area of high seasonal malaria transmission in Ghana, West Africa
<p>Here, we report the first population genetic study to examine the impact of indoor residual spraying (IRS) on Plasmodium falciparum in humans. This study was conducted in an area of high seasonal malaria transmission in Bongo District, Ghana. IRS was implemented during the dry season (November-May) in three consecutive years between 2013 and 2015 to reduce transmission and attempt to bottleneck the parasite population in humans towards lower diversity with greater linkage disequilibrium. The study was done against a background of widespread use of long-lasting insecticidal nets, typical for contemporary malaria control in West Africa. Microsatellite genotyping with 10 loci was used to construct 392 P. falciparum multilocus infection haplotypes collected from two age-stratified cross-sectional surveys at the end of the wet seasons pre- and post-IRS. Three-rounds of IRS, under operational conditions, led to a >90% reduction in transmission intensity and a 35.7% reduction in the P. falciparum prevalence (p < .001). Despite these declines, population genetic analysis of the infection haplotypes revealed no dramatic changes with only a slight, but significant increase in genetic diversity (H<sub>e</sub> : pre-IRS = 0.79 vs. post-IRS = 0.81, p = .048). Reduced relatedness of the parasite population (p < .001) was observed post-IRS, probably due to decreased opportunities for outcrossing. Spatiotemporal genetic differentiation between the pre- and post-IRS surveys (D = 0.0329 [95% CI: 0.0209 - 0.0473], p = .034) was identified. These data provide a genetic explanation for the resilience of P. falciparum to short-term IRS programmes in high-transmission settings in sub-Saharan Africa.</p>
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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.