The opioid syndemic is a public health crisis that consists of the overlapping epidemics of opioid use disorder, fatal and non-fatal overdose, HIV, and Hepatitis C. Accurate and local surveillance of community levels of opioid misuse is critical to inform public health policies but is extremely challenging because it is difficult, if not impossible, to measure directly. In this work, we leverage multiple sources of data to learn about complex spatio-temporal relationships within the syndemic and indirectly estimate the local burden of opioid misuse.

Healthy foods are essential for a healthy life, but accessing healthy food can be more challenging for some people than others. With this disparity in food access comes disparities in well-being, leading to disproportionate rates of diseases in communities that face more challenges in accessing healthy food (i.e., low-access communities). Identifying low-access, high-risk communities for targeted interventions is a public health priority, but current methods to quantify food access are either computationally simple or accurate, but not both. We propose a hybrid statistical approach to combine these methods, allowing researchers to harness the computational ease of one with the accuracy of the other.

Human exposures to the natural environment are changing as the climate is changing. As a result, people are dealing with health effects of heat, drought, food insecurity, and climate related natural disasters. In addition, the changing climate is shifting the distribution of other species that can carry or cause diseases that impact human health. Our current research focuses on two main areas. SESH members are involved in projects that forecast drought in the United States. We are also involved in research estimating the endemic regions of environmentally acquired airborne fungal investigations, like Valley Fever and histoplasmosis, which have shifted with the changing climate.