Estimation of heat-related morbidity from weather data: A computational study in three prefectures of Japan over 2013–2018

In recent years, the rates of heat-related morbidity and mortality have begun to increase with the increase in global warming; in this context, it is noteworthy that the number of patients transported by ambulance in heat-related cases in Japan reached 95,137 in 2018. The estimation of heat-related morbidity forms a key factor in proposing and implementing suitable intervention strategies and ambulance availability and arrangements. Heat-related morbidity is known to be fairly correlated to metrics related to ambient conditions, thus necessitating the exploration of new metrics to more accurately estimate morbidity. In this study, we use an integrated computational technique relating to thermodynamics and thermoregulation to estimate daily peak core temperature elevation and daily water loss, which are linked to heat-related illnesses, from weather data of three different prefectures in Japan (Tokyo, Osaka, and Aichi). The correlations of the computed core temperature elevation and water loss as well as conventional ambient conditions are investigated in terms of number of patients suffering from heat-related illnesses transported by ambulance from 2013 to 2018. The estimated water loss per the proposed computation yields better correlation with the number of patients transported by ambulance. In particular, the weight-sum daily water loss for two to three successive days is found to be an important metric for predicting the number of patients transported by ambulance. For the same ambient conditions, morbidity is found to decrease to 0.4 owing to heat adaption at the end of summer (60 days) as compared with that at the end of the rainy season. Thus, the weighted sum of water loss and daily average ambient temperature for successive days can be used as better metrics than conventional weather data for the application of intervention strategies and planning of ambulance arrangements for heat-related morbidity.