Can data help eradicate the Loneliness Epidemic?

TL;DR

• How one can use a data-driven approach to solve issues in identifying a target audience.
• Considering how the Age UK charity may use such an approach to best allocate their limited resources.
• Highlighting how the Kogenta Contextual Indices (KCIs) can be used to maximise the efficiency in which this task is completed and promoting the brilliant work charities do for our community across the UK.

Can data help eradicate the Loneliness Epidemic?

How data can be used to support charities and their deployment of resources

Kogenta’s wide range of demographic resources are usually used to obtain insights on audiences for advertising purposes. In this blog, we show how that same data can be applied to support charities in identifying their target audience, allowing them to better allocate their resources.

The COVID-19 global pandemic promoted isolation more than ever before, and since then statistically, people have become lonelier than ever before. Unfortunately, this is especially true for those later in life, with the UK charity Campaign to End Loneliness saying that it estimates over two million over-50s in the UK will be living with extreme loneliness by 2026. This ever-growing phenomenon has been termed – the ‘Loneliness Epidemic.’

ONS data indicates that those most likely to feel loneliness more often are people in poor health or who have conditions they describe as “limiting,” as well as those that are living alone due to the fact they are either single or widowed. The mapping above demonstrates hotspots in the spread of people over the age of 90 in the UK, statistically the people most likely to be lonely.

Patterns emerge in the data, where larger cities are more sparsely populated with elderly people, and generally areas where this populus over indexes are by the coast. The district of Eastbourne is a notable example of this, falling in the highest category of the subgroup of resident demographics, as shown below.

Adding the additional layer of Age UK data, we can see that they have successfully highlighted this risk of loneliness. Using the Age UK API, we can see that Eastbourne has multiple areas where the calculated net risk of loneliness is very high and very consistent.

The town is noticeably over indexed (in other words, hosts a higher proportion of this demographic compared to the national average) in its most central postcode areas. We can assume that the organisation has clearly taken a data-led approach to dispersion of their resources, striving to focus their philanthropic efforts into these over indexing areas.

Our research shows that Eastbourne OAPs, and indeed any in greater East Sussex, have access to a host of accessibility resources; telephone befriending, home support for those with cancer, house clearance and decluttering and assistance bringing pensioners home from the hospital. There are additionally two physical centres that residents of Eastbourne town can visit; a clothes vendor and a furniture warehouse and donation centre. This is a superb example of effectively matching the services to where the need exists most.

This can be taken one step further where we can use Kogenta Contextual Indices (KCIs) to help predict and plan the future allocation of charities’ resources; we can help identify areas where there may be high demand for support but an under-allocation of support resources.

We can see here that the village of Bucknall in Lincolnshire, situated just West of Horncastle, significantly over indexes for those households with members over the age of 90, alongside over indexing for those in fair to very bad health. We can then use the Age UK API again to identify their current activity in the same region.

Whilst the Age UK data acknowledged the need for elderly help profiled in Eastbourne, there is no recognition of the anomaly in Bucknall, despite it having tell-tale signs of an aging population – just one small primary school and a large nursing house. Age UK’s services within Lincolnshire seem to focus primarily on the city of Lincoln and the town of Boston – where their primary outposts are.

Here we have used the Kogenta Explorer platform to analyse geographic regions, cross referencing it with third party data resources, to create real-world solutions and spot important oversights.

Charities do fantastic work supporting our communities with much needed services. Having a data driven approach such as the one described here enables new and more efficient placement of these vital, life-changing services, resulting in best possible outcomes.