The struggle in West Africa and worldwide to contain Ebola has led to numerous calls from doctors to aid organisations for better use of technology to curb the spread of the virus – whether it is the development of new ways to test for the disease, early-warning systems or methods of communication for frontline healthcare workers. We’ve become so used to technology providing an answer in all aspects of life, that it only makes sense to turn to it when faced with a crisis.
Indeed, developments in emerging technologies do have a big part to play in the fight against pandemics and disease. A recent example is how satellite data is being used by researchers to track wind storms and their connection with valley fever and meningitis, two airborne diseases that are transmitted more easily in dusty environments. As in this instance, while most technologies will not provide an out and out cure, they can go a long way to enhancing early detection or indeed, preventing the spread of the disease.
Let’s take big data analytics to start with. While both the healthcare industry and the private sector have been advocates of this technology for some time, it’s potential to benefit aid organisations on the ground has remained largely unexplored. Fortunately, things are beginning to change; since the latest outbreak of Ebola in March, many experts have come to the realisation that big data can provide crucial insights which can be used to help fight infectious diseases.
Hundreds of relevant data sources exist – there’s social media data, data on people’s movements in and out of sea and air terminals and information about the disease itself. The biggest hurdle is pulling multiple and unstructured data streams from different sources into a format that can be easily analysed, and, importantly, one that allows us to understand how the disease has spread.
When disasters or pandemics hit, having the ability to make informed and data-driven decisions, such as where to deploy rapid response teams or community programmes, is critical. When visualised in the right way, data has the potential to isolate previously unexpected trends, pinpoint vital information gaps and, ultimately, become an indispensable tool in a health worker’s armoury.
In the case of Ebola, what has been achieved so far with big data? At Qlik, we’ve created an application that aggregates publically available data on infection levels and mortality rates. This has given us the ability to visualise the patterns around the number of mortalities in each region compared to the number of people infected, and also the trend of the spread. By adding in data on medical intervention we would also be able to track the effectiveness of different preventive measures and the extent to which each approach has curbed contagion levels.
Another valuable data set is generated by the use of technology itself – mobile phone data or call-data records (CDR), which contain information about when calls are made and received, and roughly where the device is located. While this information doesn’t tell you exactly who is infected, it does show patterns of conversation and tracks movement. Most notably, CDR data has been used by researchers to monitor the spread of malaria in Kenya and to ascertain which areas were most likely to be hit next by the disease.
This type of data, in particular, can help aid and health organisations determine where and how best to respond. After all, one of the greatest challenges in the event of any epidemic – whether it is Ebola or winter flu – is distributing the right medical resource and intervention where needed to contain the spread. What this data should be able to do, is ensure that resources are allocated quickly, in right place and at the right time to administer the correct care, rather than a stab in the dark approach. Not only would it save lives, but it would also mean that health experts and aid volunteers are being used as effectively as possible.
Tracking the outbreak isn’t the only way we can use technology to curb a spread. Other technologies that we’ve deployed in a business environment can also help. Take technologies that enable flexible working for example.
If you can set staff up with the ability to securely access company information and do their jobs remotely then they can still work as effectively away from the office as they can onsite. That means that, if a member of staff contracts a virus, rather than having to go in and potentially spread it to a co-worker, they can continue to work from home. Or in a more extreme situation, if the office becomes a contagion-zone, then staff can avoid the area completely, but still do their jobs wherever they are.
When harnessed in the right way, technology such as big data analytics can help governments and health organisations intervene effectively when a viral outbreak hits. If we work together, share data sets and continue to use these innovations to tackle our approach to wider societal issues, then we put ourselves in good stead to contain and maybe one day even stop the spread of diseases in their entirety.
Sean Farrington has been MD UK & Ireland and Regional Vice President for Northern Europe for Qlik since July 2009. Prior to Qlik, he was Regional Vice President and General Manager, UK, Ireland and South Africa for SAP Business Objects. During his tenure, he doubled the company’s revenue to approximately €30M per annum. Sean has over 19 years’ experience in the business software industry, 15 of those are within Business intelligence.
(Image credit: Ebola virus, via NIAID)
