The public health crisis caused by COVID-19 has had an enormous impact across society, posing severe challenges for both the private and public sector. The digital infrastructure has helped in understanding and adapting to a world in which health care and social distancing have changed everything across travelling, shopping, teaching to business models. Information is vital to develop strategies which take the complexity of such issues into account. Data-driven solutions turn vast amounts of information into quick and actionable insight. Yet, a common problem organisations face is that data insight remains merely accessible for the technically trained staff which has made it difficult for decision-makers to develop strategies across organisations to cater towards their communities in a crisis like this.
What we are doing to help
Drawing on our work with Local Authorities such as London Borough of Barking and Dagenham and Oxfordshire County Council, we know what it takes to get the right information to the right person at the right time to help them care for their communities. With the disruptions due to COVID-19, we wanted to assist in broadening the resource of information. We collated a range of relevant open data sets to help understand the socio-economic impact by visualising these through an instance of our Location Insights Explorer.
We have opened up this free instance of LINE to all local authorities in the UK so that anyone with a valid @gov.uk email address can sign up to utilise all the valuable tools that local authorities like London Borough of Barking and Dagenham and Oxfordshire County Council are already benefiting from. We are doing this to give people across government organisations an accessible, comprehensive, and valuable tool to identify which parts of their communities are key action zones for early intervention and support.
Please follow this link to sign up to our free instance of LINE.
What data have we visualised, and how will this assist you?
We have sourced and collated open data sets on a series of important factors relating to consequences from the pandemic, everything from precarious jobs to strain on citizen’s mental health. With this data, we have created seven maps for you to explore socio-economic vulnerabilities:
- Economic Vulnerability
- Employment Vulnerability
- Health Vulnerability
- Business Vulnerability
- Changes in Vulnerability over time
- Pavement Widths to aid Social Distancing measures
- In-depth map on all socio-economic vulnerabilities
In addition to these seven maps, we have included layer sets showing the positions of important buildings, from supermarkets to hospitals, to help further explore the areas of vulnerability and the services provided to the community in those areas. This layer can be accessed and overlaid on all the various maps, allowing the user to interrogate health vulnerabilities while taking into account the locations of hospitals and pharmacies, or looking into business vulnerabilities while knowing the locations of supermarkets and transport facilities connected to the businesses in question.
This is what LINE does really well; it enables its users to easily engage with multiple data sets by layering them on top of one another, such as various vulnerability factors to show correlation and intricacies which would previously be hard to identify from data sheets alone.
3 things users have discovered in the data by using LINE over the past few months:
- Health implications
COVID-19 has exposed pre-existing health disparities and has made it even more important to understand where vulnerable groups are located and how to ensure access to health care. The data sets on health vulnerability permit users to grasp health coverage in certain areas and determine if additional resources and services are required to care for their communities.
As social distancing has been adopted as an effective strategy, we sourced and added datasets on the width of pavements to allow local authorities to assess long-term strategy to let their residents move more safely around their communities.
As shown below, this map shows the location of GPs and hospitals in Exeter and pavement width whilst considering the population over 70 years (highlighted as the red area). This helps to better understand accessibility to key infrastructure that elderly people need as well as identify roads that may hinder adequate social distancing on their way to the these facilities.
2. Predicting Changes in Vulnerability
The fifth map, titled Vulnerability Changes, allows the user to explore and predict future changes in debt vulnerability by looking at two metrics. The first metric identifies Layer Super Output Areas (LSOA) of economic vulnerability through aggregated data of income support, job seekers allowance, career benefits, household income, etc. The second metric considers data such as young age, self-employment and vulnerable areas of work, to get an idea of which people may be economically vulnerable in the future because of the economic crisis caused by COVID-19. This map allows the user to explore the relationship between all these metrics to get a better idea of which areas may suffer from most changes in economic vulnerability.
The two maps below explore areas, which may be vulnerable to debt. Two metrics have been calculated – one which identifies economic vulnerability and one which focuses on people who may be economically vulnerable in a post COVID-19 world. The first filter layer showcases vulnerability pre-COVID-19. The second filter showcases the shift post-COVID-19.
3. Business Vulnerability
The hospitality and retail businesses are significantly affected by the impact of COVID-19 due to closure and lack of spending ability. Understanding business vulnerability in correlation with other data sets such as economic vulnerability on the consumer side permits councils to understand where revenue may be lost, and support and funding is necessary. Such an instance may be a towns’ income stream which is heavily dependent on students or commuters spending may lose out on crucial consumers due to the need to study or work from home now.
Below you can see an example of Oxford. Part of Oxford’s economy is heavily reliant on the influx of students and tourism. The map showcases where a large proportion (grey colour scheme from low to dark) of students resides and offers an insight how the population structure has changed due to students returning home. This lack of customers enables to see how businesses such as local high street and hospitality are severely affected by it (visualised by the orange dots).
This illustration has made use of the filter option and only showcases areas with >50% students.
This illustration has applied the filter option and showcases areas with >80% students.
Determining the business vulnerability in an area permits local councils to trace better how the closure and precautions of businesses due to COVID-19 affects the wider community and the certainty of income streams for local authorities. With this insight it enables decision-makers to develop schemes that are adjusted to the local needs whilst boosting the business flux.
Why should you visualise your data in LINE?
LINE is designed to include people across a local authority. LINE visualises location data in accessible, easy to understand maps which make data insight also comprehensive beyond the technical staff. Not only does the intuitive user design allow you to work with geospatial insight in no time, it also enables you to share and present location insight as visual evidence to everyone in your team, from the GIS person to operations manager and CEO inviting people across the organisation to engage with locations insights and draw strategies and decisions from it.
If you have any questions, please do not hesitate to contact our Business Development Executive Martine Skaret via email@example.com.