GeoAI for
Social Health
The GeoAI for Social Health project aims to investigate how wider aspects of the social environment, such as the places that people live, can affect their mental health and other valued outcomes like quality of life and ability to cope for people impacted by SMI.
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The project will explore social factors, including negative factors such as neighbourhood poverty and crime, or a lack of access to healthcare, and positive factors such as easy access to green spaces, recreational facilities and a cohesive community. As prior work has explored the influences of these factors separately, we are aiming to consider all these factors together to explore which may be more important than others, and also how they could all operate together to impact mental health and recovery
Research
Our study combines geographic data science and advanced statistical modelling to interrogate electronic health records and social information based on where people live.​
We will use detailed geographic data to produce a series of indicators thought to capture multiple social dimensions of neighbourhoods in England. The selection of the indicators is informed by evidence as well as feedback from people with lived experience of SMI. We will then link these indicators with anonymised electronic health records to understand how exposure to different aspects of the social environment impact the outcomes and journeys of people impacted by SMI.
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These findings will provide valuable evidence to inform non-medical treatments and care for people impacted by SMIs, in particular social interventions. Specifically, evidence will provide information on how improvements in housing, services and community resources could mitigate the impact of SMIs on functioning and outcomes such as quality of life. In the long term, we hope that these findings can result in policy change that contributes to reducing the burden of SMIs.
For more information contact the GeoAI for Social Health Project Manager,