# SatHealth: A Multimodal Public Health Dataset with Satellite-based Environmental Factors

## TL;DR

SatHealth is a new dataset combining satellite and health data to improve AI models for public health by incorporating environmental factors.

## Contribution

SatHealth introduces a novel multimodal dataset integrating environmental, satellite, and health data for public health AI research.

## Key findings

- Environmental data significantly improves AI model performance in public health tasks.
- SatHealth enables better temporal-spatial generalizability in disease risk prediction.
- A web application and code pipeline support easy access and use of the dataset.

## Abstract

Living environments play a vital role in the prevalence and progression of diseases, and understanding their impact on patient’s health status becomes increasingly crucial for developing AI models. However, due to the lack of long-term and fine-grained spatial and temporal data in public and population health studies, most existing studies fail to incorporate environmental data, limiting the models’ performance and real-world application. To address this shortage, we developed SatHealth, a novel dataset combining multimodal spatiotemporal data, including environmental data, satellite images, all-disease prevalences estimated from medical claims, and social determinants of health (SDoH) indicators. We conducted experiments under two use cases with SatHealth: regional public health modeling and personal disease risk prediction. Experimental results show that living environmental information can significantly improve AI models’ performance and temporal-spatial generalizability on various tasks. Finally, we deploy a web-based application1 to provide an exploration tool for SatHealth and one-click access to both our data and regional environmental embedding to facilitate plug-and-play utilization. SatHealth is now published with data in Ohio, and we will keep updating SatHealth to cover the other parts of the US. With the web application and published code pipeline2, our work provides valuable angles and resources to include environmental data in healthcare research and establishes a foundational framework for future research in environmental health informatics.