Emergency Department Presentations During Dry and Humid Heatwaves: A Case‐Crossover Study in the Northern Territory, Australia

In a rapidly warming climate, heatwaves pose an increasing threat to human health. However, there is limited knowledge of heatwave impacts on health outcomes, or the role of humidity in the tropical and arid climates of Australia's Northern Territory (NT). Using a space-time-stratified case-crossover design and conditional Poisson regression models, we analysed the association between heatwaves and emergency department (ED) presentations from 2001 to 2023, across all six NT public hospitals. Heatwaves were identified using the Excess Heat Factor (EHF) method, with both temperature-only (heatwaves_T) and temperature-plus-humidity, heat-index (heatwaves_TH) metrics. We undertook sub-group analyses by sociodemographic characteristics and principal diagnosis. All-cause ED presentations increased by 4.4% (RR = 1.044, 95%CI 1.018-1.071) for severe/extreme and 1.6% (RR = 1.016, 95%CI 1.002-1.030) for low-intensity heatwaves_T. For heatwaves_TH, presentations increased by 6.1% (RR = 1.061, 95%CI 1.025-1.098, severe/extreme) and 0.9% (RR = 1.009, 95%CI 0.995-1.024, low-intensity). Subpopulation increases for severe/extreme heatwaves_T occurred for ages 19-49 years (RR = 1.052; 95%CI 1.018-1.087), visitors (RR = 1.162, 95%CI 1.038-1.301) and skin conditions (RR = 1.116, 95%CI 1.048-1.189). Specific to severe/extreme heatwaves_TH, presentations increased for Aboriginal peoples (RR = 1.059, 95%CI 1.006-1.114), ages 50-64 years (RR = 1.141, 95%CI 1.059-1.230) and cardiovascular conditions (RR = 1.111, 95%CI 1.015-1.216). Comparing heatwave indexes, 57.1% of heatwave_T days were not captured by heatwave_TH, and conversely 49.6% of heatwaves_TH days were not captured by heatwave_T. These findings call for dual heatwave warning systems in the NT, incorporating both EHF temperature and heat-index, and further humidity-inclusive studies in varied climates. Preventative interventions should target high-risk populations, prioritizing resources for severe and extreme heatwaves.