10 datasets found
  1. d

    SoE2017: Per capita waste generation

    • data.gov.au
    • data.qld.gov.au
    • +1more
    csv
    Updated Oct 7, 2019
    + more versions
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    Environment and Science (2019). SoE2017: Per capita waste generation [Dataset]. https://data.gov.au/dataset/ds-qld-087d020e-d390-4338-9bed-339963c68525?q=
    Explore at:
    csvAvailable download formats
    Dataset updated
    Oct 7, 2019
    Dataset provided by
    Environment and Science
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    Adjusting for population levels, Queensland households generated an average of 556kg of waste per capita in 2016 2017, ranging from 390kg in the Cairns region to 680kg in Remote Queensland. Adjusting for population levels, Queensland households generated an average of 556kg of waste per capita in 2016 2017, ranging from 390kg in the Cairns region to 680kg in Remote Queensland.

  2. Data from: Urban population structure and dispersal of an Australian...

    • data.niaid.nih.gov
    • search.dataone.org
    • +1more
    zip
    Updated Dec 6, 2022
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    Véronique Paris; Rahul Rane; Peter Mee; Stacey Lynch; Ary Hoffmann; Tom Schmidt (2022). Urban population structure and dispersal of an Australian mosquito (Aedes notoscriptus) involved in disease transmission [Dataset]. http://doi.org/10.5061/dryad.05qfttf60
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    zipAvailable download formats
    Dataset updated
    Dec 6, 2022
    Dataset provided by
    Commonwealth Scientific and Industrial Research Organisation
    The University of Melbourne
    Agriculture Victoria
    Authors
    Véronique Paris; Rahul Rane; Peter Mee; Stacey Lynch; Ary Hoffmann; Tom Schmidt
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Australia
    Description

    Dispersal is critical for successful pest control measures as it determines the rate of movement across target control areas and influences the risk of human exposure. We used a fine-scale spatial population genomic approach to investigate the dispersal ecology and population structure of Aedes notoscriptus, an important disease-transmitting mosquito at the Mornington Peninsula, Australia. We sampled and reared Ae. notoscriptus eggs at two time points from 170 traps up to 5 km apart and generated genomic data from 240 individuals. We also produced a draft genome assembly from a laboratory colony established from mosquitoes sampled near the study area. We found low genetic structure (Fst) and high coancestry throughout the study region. Using genetic data to identify close kin dyads, we found that mosquitoes had moved distances of >1 km within a generation, which is further than previously described. A spatial autocorrelation analysis of genetic distances indicated genetic similarity at >1 km separation, a tenfold higher distance than for a comparable population of Ae. aegypti, from Cairns, Australia. These findings point to high mobility of Ae. notoscriptus, highlighting challenges of localized intervention strategies. Further sampling within the same area 6 and 12 months after initial sampling showed that egg-counts were relatively consistent across time, and that spatial variation in egg-counts covaried with spatial variation in Wright’s neighbourhood size (NS). As NS increases linearly with population density, egg-counts may be useful for estimating relative density in Ae. notoscriptus. The results highlight the importance of acquiring species-specific data when planning control measures.

  3. O

    Births by Hospital

    • data.qld.gov.au
    • researchdata.edu.au
    • +1more
    csv
    Updated Feb 13, 2025
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    Justice (2025). Births by Hospital [Dataset]. https://www.data.qld.gov.au/dataset/births-by-hospital
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    csv(2 KiB), csv(1.5 KiB), csvAvailable download formats
    Dataset updated
    Feb 13, 2025
    Dataset authored and provided by
    Justice
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    Births that occurred by hospital name. Birth events of 5 or more per hospital location are displayed

  4. q

    Australian creative employment (Census extracts)

    • researchdatafinder.qut.edu.au
    Updated May 18, 2022
    + more versions
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    Dr Marion McCutcheon (2022). Australian creative employment (Census extracts) [Dataset]. https://researchdatafinder.qut.edu.au/display/n16132
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    Dataset updated
    May 18, 2022
    Dataset provided by
    Queensland University of Technology (QUT)
    Authors
    Dr Marion McCutcheon
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Area covered
    Australia
    Description

    Census employment and income data for persons working in creative industries and creative occupations.

    This dataset consists of 14 individual datasets that underpin the interactive dashboards on the project's Data Tables webpage.

    Project background:

    Australian cultural and creative activity: A population and hotspot analysis is an Australian Research Council Linkage project (LP160101724) being undertaken by QUT and the University of Newcastle, in partnership with Arts Queensland, Create NSW, Creative Victoria, Arts South Australia and the Western Australian Department of Local Government, Sport and Cultural Industries.

    This comprehensive project aims to grasp the contemporary dynamics of cultural and creative activity in Australia. It brings together population-level and comparative quantitative and qualitative analyses of local cultural and creative activity. The project will paint a complete national picture, while also exploring the factors that are producing local and regional creative hotspots.

    Creative hotspots for study were selected in consultation with state research partners:

    Queensland – Cairns, Sunshine Coast + Noosa, Gold Coast, Central West Queensland
    New South Wales – Coffs Harbour, Marrickville, Wollongong, Albury
    Victoria – Geelong + Surf Coast, Ballarat, Bendigo, Wodonga
    Western Australia – Geraldton, Fremantle, Busselton, Albany + Denmark
    South Australia – to be confirmed shortly
    

    Statistical summaries drawn from a diverse range of data sources including the Australian Census, the Australian Business Register, IP Australia registration data, infrastructure availability lists and creative grants and rights payments as well as our fieldwork, inform hotspot reports.

  5. Axiom canine microarray data from Australian dingoes and domestic dogs for...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated May 31, 2023
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    Kylie M. Cairns; Mathew S. Crowther; Heidi G. Parker; Elaine A. Ostrander; Mike Letnic (2023). Axiom canine microarray data from Australian dingoes and domestic dogs for admixture and population structure analysis [Dataset]. http://doi.org/10.5061/dryad.vq83bk3ww
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    zipAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    National Human Genome Research Institutehttps://www.genome.gov/
    UNSW Sydney
    The University of Sydney
    Authors
    Kylie M. Cairns; Mathew S. Crowther; Heidi G. Parker; Elaine A. Ostrander; Mike Letnic
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Australia
    Description

    Admixture between species is a cause for concern in wildlife management. Canids are particularly vulnerable to inter-specific hybridisation, and genetic admixture has shaped their evolutionary history. Microsatellite DNA testing, relying on a small number of genetic markers and geographically restricted reference populations, has identified extensive domestic dog admixture in Australian dingoes and driven conservation management policy. There has been concern that geographic variation in dingo genotypes could confound ancestry analyses that use a small number of genetic markers. Here we apply genome-wide single nucleotide polymorphism (SNP) genotyping to a set of 385 wild and captive dingoes from across Australia and then carry out comparisons to domestic dogs, and perform ancestry modelling and biogeographic analyses to characterize population structure in dingoes and investigate the extent of admixture between dingoes and dogs in different regions of the continent. We show that there are at least five distinct dingo populations across Australia. We observed limited evidence of dog admixture in wild dingoes, challenging previous reports regarding the occurrence and extent of dog admixture in dingoes, as our ancestry analyses show that previous assessments severely overestimate the degree of domestic dog admixture in dingo populations, particularly in southeastern Australia. These findings strongly support the use of genome-wide SNP genotyping as a refined method for wildlife managers and policy makers to assess and inform dingo management policy and legislation moving forwards. Methods This data was collected by microarray SNP genotyping using Axiom Canine Set A, Axiom Canine Set B and Axiom CanineHD arrays (Thermo Fischer Scientific Inc). Microarrays were processed at either the Ramaciotti Centre for Genomics (Sydney, Australia) or Thermo Scientific Microarray Research Services Laboratory (Santa Clara, CA, USA). Both the raw CEL files off the GeneTitan microarray scanner and Plink SNP datasets are provided.

  6. Adjusted dengue incidence rates per age class for the city of Cairns during...

    • plos.figshare.com
    xls
    Updated Jun 5, 2023
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    Gonzalo M. Vazquez-Prokopec; Uriel Kitron; Brian Montgomery; Peter Horne; Scott A. Ritchie (2023). Adjusted dengue incidence rates per age class for the city of Cairns during January–August 2003. [Dataset]. http://doi.org/10.1371/journal.pntd.0000920.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Gonzalo M. Vazquez-Prokopec; Uriel Kitron; Brian Montgomery; Peter Horne; Scott A. Ritchie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Cairns
    Description

    Adjusted dengue incidence rates per age class for the city of Cairns during January–August 2003.

  7. f

    Number of cases , age standardised (per 100 000) cancer incidence rates and...

    • plos.figshare.com
    xls
    Updated May 30, 2023
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    Shameq Sayeed; Isobel Barnes; Benjamin J. Cairns; Alexander Finlayson; Raghib Ali (2023). Number of cases , age standardised (per 100 000) cancer incidence rates and number of person-years of observation for White & Indian children in Leicester, and for children in Mumbai & Ahmedabad, India. (All rates are standardised to the age distribution of the Segi standard population). [Dataset]. http://doi.org/10.1371/journal.pone.0061881.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Shameq Sayeed; Isobel Barnes; Benjamin J. Cairns; Alexander Finlayson; Raghib Ali
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Leicester, Mumbai, Ahmedabad, India
    Description

    Number of cases , age standardised (per 100 000) cancer incidence rates and number of person-years of observation for White & Indian children in Leicester, and for children in Mumbai & Ahmedabad, India. (All rates are standardised to the age distribution of the Segi standard population).

  8. Description of each space-time cluster identified for the dengue epidemic...

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Gonzalo M. Vazquez-Prokopec; Uriel Kitron; Brian Montgomery; Peter Horne; Scott A. Ritchie (2023). Description of each space-time cluster identified for the dengue epidemic that affected the city of Cairns during January–August 2003. [Dataset]. http://doi.org/10.1371/journal.pntd.0000920.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Gonzalo M. Vazquez-Prokopec; Uriel Kitron; Brian Montgomery; Peter Horne; Scott A. Ritchie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Cairns
    Description

    Description of each space-time cluster identified for the dengue epidemic that affected the city of Cairns during January–August 2003.

  9. f

    Study population characteristics in discrete choice experiment eliciting...

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Christine Michaels-Igbokwe; Fern Terris-Prestholt; Mylene Lagarde; Effie Chipeta; John Cairns (2023). Study population characteristics in discrete choice experiment eliciting young people's preferences for FP service providers in Malawi, 2012. [Dataset]. http://doi.org/10.1371/journal.pone.0143287.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Christine Michaels-Igbokwe; Fern Terris-Prestholt; Mylene Lagarde; Effie Chipeta; John Cairns
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Malawi
    Description

    Study population characteristics in discrete choice experiment eliciting young people's preferences for FP service providers in Malawi, 2012.

  10. Demographic details of human brains.

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Jianjun Sun; Jinbin Xu; Nigel J. Cairns; Joel S. Perlmutter; Robert H. Mach (2023). Demographic details of human brains. [Dataset]. http://doi.org/10.1371/journal.pone.0049483.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Jianjun Sun; Jinbin Xu; Nigel J. Cairns; Joel S. Perlmutter; Robert H. Mach
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    PMI: Post-mortem interval; CDR: Clinical dementia rating.

  11. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Environment and Science (2019). SoE2017: Per capita waste generation [Dataset]. https://data.gov.au/dataset/ds-qld-087d020e-d390-4338-9bed-339963c68525?q=

SoE2017: Per capita waste generation

Explore at:
csvAvailable download formats
Dataset updated
Oct 7, 2019
Dataset provided by
Environment and Science
License

Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
License information was derived automatically

Description

Adjusting for population levels, Queensland households generated an average of 556kg of waste per capita in 2016 2017, ranging from 390kg in the Cairns region to 680kg in Remote Queensland. Adjusting for population levels, Queensland households generated an average of 556kg of waste per capita in 2016 2017, ranging from 390kg in the Cairns region to 680kg in Remote Queensland.

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