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With the onset of Covid-19 Durham County Council needed to identify vulnerable individuals in the area and target them with specific assistance services. Shielded population lists received from central government had to be summarised for senior managers for them to plan their workload. The shielded list was used as a starting point. The data team knew that there were vulnerable residents who were not on this list but were nevertheless also in need of services. The team decided to join up internal council data sets to identify more people to support with services.
The Solution
During the first lockdown shielded population lists were provided daily by central government, this then became weekly since November 2020. At the time, these lists did not contain Unique Property Reference Numbers (UPRNs). The Council went through a process of looking through these lists record by record and linking up the UPRN to the list. Doing this allowed the council to join the lists to other internal geographies to produce internal summary reports.
During the Covid-19 pandemic the county was divided into two areas which were called Hubs. The UPRN was applied to every record in the shielded list. Once the UPRN was applied to the lists, it was divided into groups based on these hubs. These lists were then used to contact individuals and make them aware of the support available to them.
The council also looked at internal datasets such as adult and children social care services and assisted bin collection and used the data to identify those known to the council to be potentially vulnerable. The UPRN was then added to these data sets. The datasets were then joined together to find people who had multiple vulnerabilities in addition to being on shielded population list. A lot of manual work was involved in this process as every addressdata base in the council is different and there is currently no standardisation.
The UPRN allowed the council to summarise data and see where hotspots might be by geography. This could then join to other data sets such as Index of Deprivation so potential correlations between the shielded population list and multiple vulnerability lists could be identifi ed. The council found that there was a strong correlation between the lists.
Challenges
One of the greatest challenges involved attaching UPRNs to different data sets, particularly those coming in from central government. In addition, although the shielded population list could be attributed with the right details, subsequent updates meant a continuous manual process of verifi cation was necessary.
The data team also found that colleagues usually wanted a summary instead of a full data set – because it was diffi cult to understand that information’s granular detail. However, the addition of the UPRN delivered standardisation and that made it easier for people without a technical background to interpret results.
Future Plans
Durham County Council has plans to apply learnings from its use of COVID-19 response data. In the school census, for example, it has used student-level data to derive location-based insights that enable the council to report on and identify possible problems. By using the UPRN, the council doesn’t need to use students’ personal details. It can run analysis and create summaries with non-disclosive data that still identifies target areas for action. The council is also looking at ways to extend this approach into a wider range of services; building a data warehouse, using UPRNs as the key to future insights.
