title: The burden of extreme heat and heatwave on emergency ambulance dispatches: A time-series study in Huainan, China.
abstract: BACKGROUND
  Although studies have well documented increased mortality risk during extreme heat and heatwaves, few have examined their impacts on emergency ambulance dispatches under different temperature metrics. Additionally, evidence on the attributable risk of emergency ambulance dispatches due to extreme heat and heatwaves is scarce around the world.
  
  
  METHODS
  A distributed lag nonlinear model (DLNM) was applied to quantify the impact of extreme heat and heatwaves on emergency ambulance dispatches in Huainan, China, during 2011-2013. Several local extreme heat and heatwave definitions were tested by using percentile of daily mean temperature (i.e., 95th, 97.5th and 99th) and duration (i.e.,≥2 consecutive days and ≥3 consecutive days). The fraction of emergency ambulance dispatches attributable to extreme heat and heatwaves was also quantitatively estimated.
  
  
  RESULTS
  Both extreme heat and heatwaves were significantly associated with increases in emergency ambulance dispatches, and their effects appeared to be acute. For extreme heat effects, the relative risks (RRs) of emergency ambulance dispatches at lag0 steadily increased from 95th percentile of daily mean temperature (1.03, 95% confidence interval (CI): 1.01-1.05) to 99th percentile (1.07, 95% CI: 1.05-1.10). For heatwave effects, we observed that RRs of emergency ambulance dispatches at lag0 fluctuated between 1.03 and 1.05 across different heatwave definitions. Notably, the fraction of emergency ambulance dispatches attributable to extreme heat decreased with higher percentile of daily mean temperature, dropping from 2.24% (95% CI: 1.41%-2.99%) at 95th percentile to 0.69% (95% CI: 0.45%-0.92%) at 99th percentile. Likewise, we found that heatwaves with higher intensity and (or) longer duration accounted for lower fraction of emergency ambulance dispatches, varying between 0.51%-1.52%.
  
  
  CONCLUSIONS
  Our findings may have important implications for the development of local heat warming systems and public health interventions to lessen the impact of extreme heat events on population health.
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Cheng
authors.affiliation: School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Brisbane, Qld, 4509, Australia.
authors.forename: Zhiwei
authors.initials: Z
authors.lastname: Xu
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.
authors.forename: Desheng
authors.initials: D
authors.lastname: Zhao
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.
authors.forename: Mingyu
authors.initials: M
authors.lastname: Xie
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.
authors.forename: Heng
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.
authors.forename: Shusi
authors.initials: S
authors.lastname: Wang
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China. Electronic address: suhong5151@sina.com.
authors.forename: Hong
authors.initials: H
authors.lastname: Su
mesh_terms: D000552:Ambulances / Q000706:statistics & numerical data*; D002681:China; D002947:Cities; D055874:Extreme Heat / Q000009:adverse effects*; D006801:Humans; D017711:Nonlinear Dynamics; D012307:Risk Factors
keywords: Ambulance dispatches; Heat; Heatwave; Time-series analysis