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

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.

Keywords: climate change; hospitalization cost; respiratory diseases; temperature.

Figure 1

Time-series plots for daily mean temperatures and daily hospitalization costs of respiratory diseases in Sydney and Perth, 2010–2016. Costs are significantly correlated with the temperatures (Spearman rho = −0.49, p < 0.001) in Sydney and (Spearman rho = −0.43, p < 0.001) in Perth. Dark points are daily mean temperatures; Grey points are daily hospitalization costs; Black line is the best fit line generated based on daily hospitalization costs.

Figure 2

Overall cumulative exposure–response relationships between daily mean temperatures and daily hospitalization costs for 14 lag days in Sydney and Perth, 2010–2016. RR is the relative risk for hospitalization costs. The optimum temperatures are 27.7 °C and 20.6 °C for respiratory disease hospitalization costs in Sydney and Perth, respectively. The red lines represent the cumulative relative risk, and the grey shaded areas represent the 95% confidence interval.

Figure 3

Lag-specific exposure–response curves for daily mean temperatures and respiratory disease hospitalization costs in Sydney, 2010–2016. RR is relative risk for respiratory disease hospitalization costs. The red lines represent the lag-specific relative risk, and the grey shaded areas represent the 95% confidence interval.

Figure 4

Lag-specific exposure–response curves for daily mean temperatures and respiratory disease hospitalization costs in Perth, 2010–2016. RR is relative risk for respiratory disease hospitalization costs. The red lines represent the lag-specific relative risk, and the grey shaded areas represent the 95% confidence interval.