Intelligent Delivery Solutions: Why poor quality data is hampering Covid-19 efforts
It's fair to say that COVID-19 has upended virtually every aspect of our life. Working from home, leaving the house for the essentials and tuning in at 5pm for the daily Government update is the new normal. We see the numbers of cases and deaths and hope that the current approach is going to allow us to get back to normal and beat this Coronavirus outbreak sooner rather than later.
COVID-19 has highlighted many things but the current approach to this Coronavirus outbreak has highlighted how important good data, thorough data collection of available data and strong data management is.
The speed with which the Coronavirus outbreak has travelled through every nation on earth has meant finding and sorting data about this infectious disease into accessible ways has been difficult for public health experts. Thoughts about good data collection, format, access, storage and overall quality have been thin on the ground.
Unfortunately, the way you beat the Covid-19 Pandemic is by ensuring you have good quality data. It's vital that your available data is showing you things like the spread of the disease, population mobility, insight into preventative actions and the resilience of systems & institutions to cope with the virus. All this global analysis and good data quality help health departments public health officials make informed decisions.
What is 'Data Quality'?
At IDS, we define Data Quality as whether or not the data you have to hand is fit for purpose. Getting to the point where you can effectively use your data and transform it is one thing, but it all goes to waste and will drastically affect decision making if the available data is poor.
Some common data quality challenges have been highlighted in this current Coronavirus pandemic. The main takeaway, however, is that lack of good quality, accessible data is one of the reasons this became a global crisis so quickly. You have lots of separate data groups, national statistical systems and official statistics owned by any number of governments, EU member states, health care providers and health departments. All these health metrics and forecast models have not been joined up due to confinement, separation and frankly, a reluctance by some governments to even take the novel coronavirus seriously. This has led to poor data sharing which doesn't give the relevant authorities an accurate picture of the current public health situation.
The Affect Poor Quality Data Has Had On Care Homes
A good example of how poor data quality can have a large effect on model predictions and the total daily average is the way that care home deaths have been counted in the UK. Because there hasn't been effective tracking and tracing in care homes, vital statistics like total confirmed cases and overall deaths is likely to be much, much higher. The London School of Economics researchers believe that there could be more 22,000 "excess deaths" during this crisis.
The Care Quality Commission had changed the data collection methods for recording deaths in care homes on April 10th, the original method of describing each death in a free hand box was found to not match evidence from providers. Here, we can see how poor data capture in the initial period of lockdown completely spoiled the quality of the overall data. Manual methods like this can't be accurately relied on for such a serious issue.
How Some Countries Are Using Big Data to Inform their Crisis Response
In Belgium, one of the organisations working alongside the government there have been collecting telecom data from the three main telecom companies in the country. They use this data on how people are moving and operating during lockdown measures to find ways of reducing infection increase in specific regions. Having this data from an existing network allows the Belgium government to determine the impacts of direct measures, response efforts and find places where there is a risk of virus outbreaks.
In South Korea, an app has been set up to 'watch' citizens who are self-isolating. This non-mandatory, opt-out app can be used to communicate with the local government. Case officers and all parties are notified if the infected person has left the quarantine zone.
Developing countries like Nigeria and Kenya are using data to map areas where the ability for people to respond to the virus is severely compromised. Satellite images and primary data collection are used to help create epidemiological models to inform decision making.
How IDS' iData Tool Can Help Improve Your Data Quality
You've seen in this blog how important data quality is for huge global events like a pandemic. That doesn't mean however that the importance of your data quality is diminished. Here at IDS, our iData tool can help you undertake rapid, real-time quality control checks on data that is meaningful to you and your organisations. Discover the level of data integrity you have in any number of repeatable, automated testing scenarios so you can speed up your development process.
If you're in an institution, organisation or business in the UK and want to make better, more informed decisions based on high-quality data sets then get in touch with the team at IDS today.