Hourly level analysis of the effects of temperature extremes on emergency ambulance calls

We obtained hourly data on EACs, weather conditions, and air pollutants from Nanjing, a megacity in eastern China, during 2018-21. We first extracted data from the cold and warm seasons to quantify the hourly impact of extreme cold and heat on EACs and potential modifying factors using a distributed lag nonlinear model. Then, we used a random-effects meta-analysis model to pool the estimates of extreme temperatures on EACs from this Nanjing study and from studies identified in the published literature.

The results showed that hourly exposure to extreme cold and heat increased the risk of EACs for all non-accidental causes, with relative risks (RRs) of 1.175 (95% confidence interval (CI) = 1.135, 1.216) at lag seven to 22 hours and 1.096 (95% CI = 1.048, 1.146) at lag zero to 10 hours, respectively. Stronger extreme heat-EAC associations were found between 16:00-24:00. The meta-analysis, which additionally included four prior studies, confirmed a significant association between hourly exposure to temperature extremes and EAC risk (RR = 1.155 for extreme cold and RR = 1.172 for extreme heat).

Our findings indicate that transient exposure to temperature extremes can increase the demand for EACs within a few hours, which may have implications for improving ambulance service efficiency and developing an ambulance early warning system under extreme weather conditions.