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Hospitalization Costs of Respiratory Diseases Attributable to Temperature in Australia and Projections for Future Costs in the 2030s and 2050s under Climate Change

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Listed:
  • Michael Tong

    (School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia)

  • Berhanu Wondmagegn

    (School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia)

  • Jianjun Xiang

    (School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia)

  • Alana Hansen

    (School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia)

  • Keith Dear

    (School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia)

  • Dino Pisaniello

    (School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia)

  • Blesson Varghese

    (School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia)

  • Jianguo Xiao

    (Department of Health, Government of Western Australia, Perth, WA 6004, Australia)

  • Le Jian

    (Department of Health, Government of Western Australia, Perth, WA 6004, Australia)

  • Benjamin Scalley

    (Department of Health, Government of Western Australia, Perth, WA 6004, Australia)

  • Monika Nitschke

    (Department of Health, Government of South Australia, Adelaide, SA 5000, Australia)

  • John Nairn

    (Australian Bureau of Meteorology, Adelaide, SA 5000, Australia)

  • Hilary Bambrick

    (School of Public Health and Social Work, Queensland University of Technology, Brisbane, QL 4000, Australia)

  • Jonathan Karnon

    (College of Medicine and Public Health, Flinders University, Bedford Park, SA 5001, Australia)

  • Peng Bi

    (School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia)

Abstract

This study aimed to estimate respiratory disease hospitalization costs attributable to ambient temperatures and to estimate the future hospitalization costs in Australia. The associations between daily hospitalization costs for respiratory diseases and temperatures in Sydney and Perth over the study period of 2010–2016 were analyzed using distributed non-linear lag models. Future hospitalization costs were estimated based on three predicted climate change scenarios-RCP2.6, RCP4.5 and RCP8.5. The estimated respiratory disease hospitalization costs attributable to ambient temperatures increased from 493.2 million Australian dollars (AUD) in the 2010s to more than AUD 700 million in 2050s in Sydney and from AUD 98.0 million to about AUD 150 million in Perth. The current cold attributable fraction in Sydney (23.7%) and Perth (11.2%) is estimated to decline by the middle of this century to (18.1–20.1%) and (5.1–6.6%), respectively, while the heat-attributable fraction for respiratory disease is expected to gradually increase from 2.6% up to 5.5% in Perth. Limitations of this study should be noted, such as lacking information on individual-level exposures, local air pollution levels, and other behavioral risks, which is common in such ecological studies. Nonetheless, this study found both cold and hot temperatures increased the overall hospitalization costs for respiratory diseases, although the attributable fractions varied. The largest contributor was cold temperatures. While respiratory disease hospitalization costs will increase in the future, climate change may result in a decrease in the cold attributable fraction and an increase in the heat attributable fraction, depending on the location.

Suggested Citation

  • Michael Tong & Berhanu Wondmagegn & Jianjun Xiang & Alana Hansen & Keith Dear & Dino Pisaniello & Blesson Varghese & Jianguo Xiao & Le Jian & Benjamin Scalley & Monika Nitschke & John Nairn & Hilary B, 2022. "Hospitalization Costs of Respiratory Diseases Attributable to Temperature in Australia and Projections for Future Costs in the 2030s and 2050s under Climate Change," IJERPH, MDPI, vol. 19(15), pages 1-16, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9706-:d:882060
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    References listed on IDEAS

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    2. Gasparrini, Antonio, 2011. "Distributed Lag Linear and Non-Linear Models in R: The Package dlnm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i08).
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