Geographic information and geospatial technologies play an important role in understanding changes in planetary health and the defining the drivers contributing to different health outcomes both locally and globally. Patterns influencing health outcomes and disease in the environment are complex and require an understanding of the ecology of the disease and how these interact in space and time. Knowing where and when diseases are prevalent, who is affected and what may be driving these outcomes are important for determining how to respond. In reality, we all would like to be healthy and live in healthy places.

In this book, epidemiology and public health are integrated with spatial data science to examine health issues in dynamically changing environments.  This is too broad a field to be completely covered in one book and so it has been necessary to be selective with the topics, methods and examples used to avoid overwhelming introductory readers, while at the same time providing sufficient depth for geospatial experts interested in health, and for health professionals interested in integrating geospatial elements for health analysis.  A variety of geographic information (some novel, some volunteered, some authoritative, some big and messy) are used with a mix of methods consisting of spatial analysis, data science, machine learning and spatial statistics to better understand health risks and disease outcomes.

Key Features:

• Makes spatial data science accessible to health professionals and makes health accessible to spatial data scientists.
• Integrates epidemiology and ecology with spatial data science.
• Integrates theoretical geographic information science concepts and domain knowledge thinking with digital data.
• Provides practical and applied approaches for examining and exploring health and disease outcomes.
• Provides spatial data science skill development ranging from map making to spatial modelling.