Mapping Health Equity: Equitable Intelligence For Emerging Infections (EI2)

Even though infectious diseases remain a major threat to human health everywhere, the world remains unprepared. When new infectious diseases like COVID-19 spread, not everyone is equally at risk of getting sick. Those on low incomes and people of colour usually have a greater risk of infection. Some will see a doctor if they become ill. However, many people can't go to hospitals, so we get an incomplete picture of who is getting ill and what happens to them. This might be because of where and how they live, not being able to afford the expense and time needed to seek care, or having existing health problems. When a new infectious disease spreads, we still don't know who is the most at risk of severe illness and where they are. This is a problem in the UK, but is worse in countries where healthcare is less accessible for everyone. I aim to address this issue by ensuring everyone, regardless of their financial status, background, or location, stays safe from infectious diseases. I will start by focusing on the UK and then expand to other countries. To do this, I will create the Equitable Intelligent Mapping platform (EI2), a AI program designed to predict who and where needs help the most. This platform will uniquely account for socio-environmental and individual vulnerabilities, which is currently missing from current surveillance platforms. By including health equity factors, we can better understand how risk is distributed, and look beyond just the number of cases reported by our healthcare system. First, I will develop a new system to understand how factors like wealth, living conditions, and the environment affect our chances of getting sick, then use mathematical simulations to confirm the capability of this system. Since many people are missing from hospital records, I will use health data gathered from new collection methods, such as phone apps and wastewater analysis, while ensuring personal privacy is protected. I will then use statistical models to run my system and predict who might get sick and identify how risk is distributed. Using AI, I will create a novel risk index to identify areas with the highest risks. Knowing which areas are most at risk helps our healthcare system direct help where it's needed the most. These tools will help form a mapping program called EI2, a dynamic interactive surveillance dashboard that shows who has the highest risk of illness and which neighbourhoods they live in. My project will improve preparedness for both new and existing infectious diseases. By working with leaders in government, healthcare, and business, we can make quicker and smarter decisions to control and prevent diseases. Better preparedness will reduce the pressure on hospitals during outbreaks, leading to improved healthcare for everyone. By closely monitoring health and prioritising those who might be overlooked, we can ensure everyone gets the care they need and help close the health gap.