Data

Odds ratios of climate, socio-economic and tidal variables associated with Barmah Forest virus disease outbreaks in the entire coastal region in Queensland

Queensland University of Technology
Adjunct Professor Shilu Tong (Aggregated by) Distinguished Professor Kerrie Mengersen (Aggregated by) Dr Sue Naish (Aggregated by) Professor Wenbiao Hu (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://goo.gl/zXYoHW&rft.title=Odds ratios of climate, socio-economic and tidal variables associated with Barmah Forest virus disease outbreaks in the entire coastal region in Queensland&rft.identifier=10378.3/8085/1018.15728&rft.publisher=Queensland University of Technology&rft.description=This dataset comes from a study which sought to forecast the future risk of Barmah Forest virus disease (BFV) under climate change scenarios. The study was conducted in Queensland, Australia, an area covering 1,727,200 km2 (22·5% of the country) with 7,400 km of continental coastline and 9,800 km including islands. The estimated population was 4,580,725 on 30 June, 2011 for Queensland, Australia. To complete the forecast several existing datasets were drawn upon: data on notified BFV cases covering the period 2000–2008 were obtained from Queensland Health. Gridded (5 km×5 km) climate data with complete records of annual average maximum and minimum temperature and rainfall were provided by Australian Bureau of Meteorology for the same period. Data on socio-economic indicator (i.e., SEIFA index) and tides were obtained from Australian Bureau of Statistics and Queensland Transport, respectively.This data was used to model the current geographical distribution of BFV disease transmission across Queensland coastal regions and to project the potential changes in the risk of geographical distribution of BFV disease transmission for the years 2025, 2050 and 2100 in Queensland, Australia, using the medium level A1B climate change scenario.This dataset presents the odds ratios of climate, socio-economic and tidal variables associated with Barmah Forest virus disease outbreaks in the entire coastal region in Queensland.&rft.creator=Adjunct Professor Shilu Tong&rft.creator=Distinguished Professor Kerrie Mengersen&rft.creator=Dr Sue Naish&rft.creator=Professor Wenbiao Hu&rft.date=2015&rft.coverage=153.552920,-9.929730 137.994575,-9.929730 137.994575,-29.178588 153.552920,-29.178588 153.552920,-9.929730&rft_rights=Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/3.0/au/&rft_subject=Population modeling &rft_subject=Infectious disease modeling &rft_subject=Ecology&rft_subject=Zoonoses &rft_subject=Socio-economic &rft_subject=Infectious disease control &rft_subject=Epidemiology&rft_subject=Population biology&rft_subject=Infectious diseases&rft_subject=Coastal regions &rft_subject=Public health &rft_subject=Variables&rft_subject=Barmah Forest virus &rft_subject=Geographic distribution &rft_subject=Tidal &rft_subject=Infectious disease epidemiology&rft_subject=Climate change&rft_subject=Computational biology &rft_subject=Disease surveillance &rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution 3.0
http://creativecommons.org/licenses/by/3.0/au/

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Contact Information

Postal Address:
Dr Sue Naish
Dr Sue Naish
Queensland University of Technology
Faculty of Health
2 George Street
Brisbane QLD 4000
Australia

s.naish@qut.edu.au

Full description

This dataset comes from a study which sought to forecast the future risk of Barmah Forest virus disease (BFV) under climate change scenarios.

The study was conducted in Queensland, Australia, an area covering 1,727,200 km2 (22·5% of the country) with 7,400 km of continental coastline and 9,800 km including islands. The estimated population was 4,580,725 on 30 June, 2011 for Queensland, Australia.

To complete the forecast several existing datasets were drawn upon: data on notified BFV cases covering the period 2000–2008 were obtained from Queensland Health. Gridded (5 km×5 km) climate data with complete records of annual average maximum and minimum temperature and rainfall were provided by Australian Bureau of Meteorology for the same period. Data on socio-economic indicator (i.e., SEIFA index) and tides were obtained from Australian Bureau of Statistics and Queensland Transport, respectively.

This data was used to model the current geographical distribution of BFV disease transmission across Queensland coastal regions and to project the potential changes in the risk of geographical distribution of BFV disease transmission for the years 2025, 2050 and 2100 in Queensland, Australia, using the medium level A1B climate change scenario.

This dataset presents the odds ratios of climate, socio-economic and tidal variables associated with Barmah Forest virus disease outbreaks in the entire coastal region in Queensland.

Data time period: 04 2008 to 2010

This dataset is part of a larger collection

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Related Websites

  • Associated with Naish, Suchithra, Mengersen, Kerrie, Hu, Wenbiao, & Tong, Shilu (2013) Forecasting the future risk of Barmah Forest Virus disease under climate change scenarios in Queensland, Australia. PLoS ONE, 8(5)
    eprints.qut.edu.au/67158/

153.55292,-9.92973 137.99458,-9.92973 137.99458,-29.17859 153.55292,-29.17859 153.55292,-9.92973

145.7737475,-19.554159

Subjects
Barmah Forest virus | Climate change | Coastal regions | Computational biology | Disease surveillance | Ecology | Epidemiology | Geographic distribution | Infectious disease control | Infectious disease epidemiology | Infectious disease modeling | Infectious diseases | Population biology | Population modeling | Public health | Socio-economic | Tidal | Variables | Zoonoses |

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Identifiers
  • Local : 10378.3/8085/1018.15728