Health Effects of Heat Vulnerability in Rio de Janeiro: A Validation Model for Policy Applications

Extreme heat events, already one of the deadliest natural hazards in the world, are likely to increase in frequency due to climate change. Unfortunately, while socio-economic and urban form factors are highly correlated to death and hospitalization during such extreme events, determining and interpreting such factors is not a trivial task. First, lack of data on risk behaviors and vulnerability conditions requires researchers to rely on proxy data designed for other purposes (i.e., census data or land use GIS data). Second, health consequences are not specifically captured by health surveillance systems, but are classified as other common conditions. For instance, causes of hospitalization or death could be classified as myocardial infarction, cardiovascular diseases, or dehydration even though the condition might have been triggered by a heatwave. Given this context, we consider a country which is expected to lead the world in extreme heat wave events: Brazil. Building on the climate related heat epidemiology and vulnerability literature, we construct and validate an index for the city of Rio de Janeiro. We use demographic and environmental data to construct a set of unobserved factors and respective weightings related to heat vulnerability using factor analysis. Then, we use distance to hospital and clinics as an instrumental variable to validate our factors. Since in Brazil health emergency calls and health care are both free and universal (and do not require enrollment), we can assume that patients experimenting any heat related symptom or condition would be taken to the nearest hospital or clinic for urgent care. Given this, we test the hypothesis that hospitals closer to high vulnerability neighborhoods would have more cardiovascular disease, myocardial infarction, and chronic pulmonary disease hospitalization and deaths during heatwaves. Finally, we perform a Monte Carlo simulation as a sensitivity analysis and also check the robustness of our results by examining diseases knowingly unrelated to weather heat exposure.