Tracking the spread of Covid-19 across countries and towns, identifying the patient zero, antibody testing, modelling predicted infection and death rates – communities globally are desperately scrabbling to get a firm handle on the vast array data which lies at our fingertips in order to gain control of the pandemic.
The data is right there for the taking by scientists, to be found in a myriad of forms and sources. But it will only be of value if the right type of data is collected and analysed in a cohesive, global approach.
Let’s be clear, it might be a global public health crisis, but the collection and analysis of health data alone will not be enough to provide a clear understanding of the spread, magnitude and effective response to the pandemic.
Past examples clearly illustrate the true extent to which we need to rethink the global approach to data analysis and collection.
A town in Italy experienced a sudden, unexplained spike in respiratory-issue linked deaths. Heads were scratched as to the cause behind this, something which only became clear when officials looked at the local shipping records.
The start of these issues coincided with a large shipment of peanuts entering the town – revealing a link between peanut dust and the respiratory issues.
Data which may seem inconsequential at first, if analysed effectively and placed in the right context, can shed light on key trends.
When it comes to Covid-19, no stone should be left unturned in careful consideration of the sources of data which can provide valuable insight once placed in the same, bigger picture. Just this week, a stark link was drawn between higher levels of air pollution, and significantly higher death rates in people with Covid-19.
In light of this, scientists should be looking to the NHS, insurance claims, supply-chain logistics, satellite imagery for road traffic levels, the Met Office, infection rates in the context of every conceivable demographic.
There must be clear alignment and co-operation globally on the approach to data collection. A global data picture is the only perspective which is all-encompassing enough when tackling a pandemic of the scale we’re currently facing.
For example, the two studies connecting air pollution to Covid-19 death rates were conducted on opposite sides of the world, in US and Italy. The corroboration between the two strengthens their conviction.
Also, scientists have suggested these findings could be applied across communities, informing which areas with high levels of air pollution may need additional resources deployed to.
It’s precisely why this week at WANdisco we made our cloud software available to science teams across the globe fighting the pandemic. This requires a united, global approach – and we should all get behind this effort.
Understandably, privacy remains a key fear in the data collection conversation, with copies of 1984 still gracing many living room bookshelves. However, when such an inconceivable amount of lives are at risk, this is not about corporations profiting off the vast amounts of data handed over everyday by consumers.
This is about data with real-life implications, and the potential to save lives globally. Healthcare data can be anonymised in its sets, with personal information not at risk – with the return being immeasurably higher.
The data around us in relation to Covid-19 is developing constantly and a rapid rate. That is why we need real-time data collection and analysis, and clear communication on a global level.
Only then will we build a full worldwide picture of the problem, which will in turn give healthcare the best possible chance at saving and protecting lives.