Measuring health inequities due to housing characteristics

Existing heat vulnerability assessment methods do not typically consider housing characteristics due to limited data and understanding of their effects. This research shows how heat vulnerability assessment methods can be used to identify and address indoor health inequities at the urban scale. The ResStock dataset is used to investigate the impact of housing characteristics on the indoor heat index during extreme heat events and power outages. The heat index is a measure that combines temperature and relative humidity to estimate the perceived temperature. Higher indoor heat index values are a good predictor of increased vulnerability to extreme heat, uncovering indoor health inequities. A case study in Worcester, Massachusetts, US, uses urban-scale energy modeling simulations for extreme heat and power outages to understand how housing characteristics (e.g. access to cooling or air-conditioning, housing age, and housing type) increase or decrease the indoor heat index value, as well as the rate of surpassing the critical 80°F (26.7°C) indoor heat index threshold. Findings demonstrate that indoor health inequities are exacerbated in homes without air conditioning, mobile homes and older homes.