CR 16:133-143 (2001)  -  doi:10.3354/cr016133

An empirical mechanistic framework for heat-related illness

Nathan Y. Chan1, Mark T. Stacey2, Anne E. Smith3, Kristie L. Ebi4,*, Thomas F. Wilson4

1Talus Solutions Inc., 650 Castro Street, Suite 300, Mountain View, California 94041, USA
2Department of Civil and Environmental Engineering, 631 Davis Hall, University of California, Berkeley, California 94720, USA
3Charles River Associates Inc., 1201 F Street NW, Suite 700, Washington, DC 20004, USA
4EPRI, 3412 Hillview Ave., Palo Alto, California 94304-1395, USA
*Corresponding author. E-mail:

ABSTRACT: A physiologically based, mechanistic framework was developed to understand key risk factors associated with adverse health effects from heat waves. The framework consists of a number of integrated transdisciplinary modules. Environmental conditions and behavioral responses link to a physiological model, which predicts core temperature. Core temperature over time is then converted into a time-at-temperature metric. The output of the framework is a heat-related health effects index (HEI), reflecting the potential relative severity of the heat stress on health. The framework is flexible, allowing the individual models to be adapted to conditions at specific locations and to be updated as new information becomes available. Scenario analyses are easily accommodated, enabling the framework to evaluate issues such as intervention strategies and the possible effects of global climate change on heat-related illnesses. The framework and an initial set of component models were applied to conditions during the 1995 Chicago event and the results compared with published studies. For individuals, there was reasonably good agreement between HEI ratios and actual mortality risk ratios when comparing indoor versus outdoor environments. When aggregating across populations, predicted HEI ratios were significantly smaller than actual mortality ratios when comparing healthy versus compromised populations, supporting the notion that mortality may not be the best indicator of heat stress effects. Future work should include refinement of the initial models and application to other cities and heat events.


KEY WORDS: Heat stress · Chicago heat wave · Risk factors · Physiological model · Integrated modeling approach


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