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Extreme heat events are responsible for more annual deaths in the United States than other natural disasters combined, and global and regional climate models have indicated that more severe and longer lasting heat events are likely to occur in the upper Midwest over the next several decades. Epidemiological studies have contributed to the identification of populations vulnerable to extreme heat. However, local decision-makers still lack tools that would help them evaluate policy and management options to reduce heat risk for these vulnerable populations, and to prevent deaths and illness once a heat event arrives. We developed a system dynamics modeling tool, called the Mid-Michigan Heat Model (MMHM), to depict the dynamics of hospitalizations and deaths over the course of a heat event in Detroit. Modelers incorporated input from decision-makers at each stage of the model-building process, and the project culminated with a workshop in which potential model-users offered feedback on MMHM. The process of building a model in a participatory manner was useful for facilitating conversations and data-exchange around an important topic, and for developing a tool with the greatest potential utility. MMHM could be made more powerful and useful by adapting its framework to local circumstances for decision-making at the municipality scale, and by combining its dynamics with spatial modeling.
In the video below. Dr. Laura Schmidt-Olabisi decsribes this work during the 2011 GLISA Symposium.
Informing decision-maker response to extreme heat events in Michigan under climate change