Now more than ever, the interpretation of data is key to decision making. On a scale we never imagined would occur in our lifetime…

However if you open any news article at the moment, there’s a good chance that you’ll be flooded with misleading charts that are often designed to shock, rather than communicate what’s really going on.

Everyone has an interest in ‘the numbers’, whether that is the number of Covid-19 cases being confirmed, the number of deaths recorded, the number of deaths not recorded, the risk of going outside in our communities, or projections of when our lives might get back to ‘normal’.

What’s really interesting to observe, is that it didn’t take long for people to tire of hearing the same headlines over and over again, and quickly start asking questions of context. How many times have you heard someone compare volumes of Coronavirus to a normal flu season? Or quote the ‘thousands of people who die each year anyway’? Decision making at both a strategic and operational level needs context and it needs enough data to compare and draw rational inferences.

That’s why I was really keen to get my hands on some different data sets that could be analysed to show contextual trends rather than stand-alone numbers. Weekly death registration data has been released by the Office for National Statistics (ONS) for a number of years, but never has it told such a compelling story as it does today. Yes the figures have now been broadened to include more detailed data relating to Covid-19 related deaths specifically, but what is most interesting is simply looking at the patterns over time and how these vary geographically. Using this standard weekly death data over the last 10 years, we can observe how many deaths we would ‘expect’ to see in any average week and compare these patterns with the volumes we are recording today.

You can interact with this report to filter the time periods visible on the charts and pick out any specific years (for example where we may have seen unseasonable cold/heat; often the biggest contributor to ‘excess’ deaths in a given period). However the real impact is simply tracking our orange lines – the 2020 data – against the muddle of historical, and largely similar, trends in death volumes.

What is your eye drawn to? The clear number of deaths recorded in London over the last 4 weeks? The perhaps surprisingly more consistent levels recorded in Wales? The relatively low numbers recorded in the North East compared with other regions?

Of course there’s much more we could add to this to start normalising by population, deprivation, gender etc. but those initial observations are worthy in their own right, and certainly start to tell us more about what’s happening in our communities than a single number published each day…

It’s certainly not a light-hearted topic to analyse and I’ve looked at all data that has been published over the last couple of months, but the insight drawn from this data genuinely made me take a pause and really look at what was going on.  Change like this even over a few months is going to have a significant impact on the make-up of our population and patterns in life-expectancy and health/social care needs over the short, medium and long-term.

The report on this page will continue to update each week as the registered deaths data is released by ONS. To support our colleagues in the Public Sector and provide valuable local context, we will also update these analytics with further (and more local) analysis over the next few months, so bookmark this page for future reference. And feel free to drop me a line if you’d like to discuss our analytics support in more detail.

Susie Bentley

Susie Bentley

Susie is itelligent-i's Analytics Director, responsible for development of our analytics offer, capability and training. Specialising in applied analytics in the Public Sector, she started her career as a crime analyst for the police and has had several data and research roles across Local Government.