Fighting disease with data - the power of disease tracking and surveillance

The Black Death was probably the most devastating pandemic in history, killing well over 100 million people in the 1300’s, reducing half of Europe’s population. Back then, the disease traveled slowly from the plains of Asia along the Silk Road and on merchant ships, transmitted between humans and animals on the way.

As world travelers today, we all know that a pandemic like that could be just a plane ride away. But besides the speed at which disease spreads, the biggest difference between epidemics now and then is modern technology, our greatest weapon in the fight against contagion.

Partnering for surveillance and outbreak management

I was recently at the SAP IoTx and Big Data conference in Dubai to talk about how big data can help fight infectious diseases together with one of our key partners, Professor Dr. Gérard Krause, Head of Epidemiology at the Helmholtz Centre for Infection Research.

While I was there, we were following the alarming rise in the number of MERS cases spreading across Asia. Since the first few cases of MERS (Middle East Respiratory Syndrome) emerged in South Korea a few weeks ago, the local health ministry already has thousands of people under observation. These numbers are especially alarming as they follow hard on the heels of the Ebola epidemic which rattled the world with 24,288 reported cases of which 10,000 were fatal.

One of the most difficult aspects of containing viruses is identifying and tracking carriers. SORMAS, the Surveillance and Outbreak Response Management and Analysis System, is a tool that collects and monitors data and delivers real-time visualization of field events so that health officials can make more informed decisions about controlling diseases before they become pandemic. The tool was developed using design thinking and agile development methodology.

Here’s how SORMAS works

Surveillance officers collect notifications regarding potentially infected people from community hotlines and health facilities. The data is validated and passed on to case officers who begin the control process which includes decontamination and quarantine. And last but not least, the teams initiate community awareness programs because an informed public plays a critical role in halting the spread of the disease. One of the most widespread methods of contagion during the Ebola epidemic, for example, was through contact with the deceased. A massive campaign was required to educate people on how to handle contaminated bodies appropriately.

Advanced technology was put in place to overcome challenges such as mobile network connectivity issues. For example, it might have taken days for a native worker, in a remote area, to receive a hotspot on their mobile phone. This type of delay could interrupt transmission of key patient status information collected on their mobile device to be sent back to the officers at the command center.

In-memory technology built on a cloud platform that is mobile-aware, real-time and agile minimized such delays. SORMAS was designed to synchronize with one or more mobile devices the field worker used to capture key patient information. Regardless of whether the field worker had mobile connectivity or not, the application was able to maintain current status of the application session, picking things up again when network connectivity was restored.

In addition, predictive analytics plays a role in predicting which part of the population will be infected next. In the SORMAS solution, link analysis is leveraged to mine through the specific symptoms of a group of current patients exhibiting symptoms to identify which combination of symptoms are most likely to represent a possible infection based on the current strain of the virus.

In the SORMAS solution diagram below, those patients in red are most likely to be confirmed as infected based on the symptoms they exhibit. Those in green are likely not infected. Leveraging a real-time in-memory technology platform to quickly predict the likelihood of infection is critical in the world of infectious disease control management, and can often make the difference between life and death.

With SORMAS, incoming patient data is analyzed in real time, and predictive tools help project where the disease is likely to spread. One of the logical future expansions of this app is in utilizing business networksto quickly mobilize medical suppliers. as the SORMAS system identifies that the virus will likely spread into a new geographic area.

This image is a real-time visualization of in field events to allow more informed decisions to control infectious diseases before they become pandemic:

The road ahead

But we’re not there yet! SORMAS is currently in the pilot phase. It could become THE standard tool for disease surveillance and outbreak response in Africa and globally, once it’s proven to work in the field, can guarantee data confidentiality and adheres to very strict scientific requirements. As such, the SORMAS team is hard at work to prove this out.

Currently we are testing SORMAS in a field trial to look at multiple diseases including Influenza, Cholera and Measles. The initial results of the field trials have come in above projections, but we will need to wait until all trials are completed before a final evaluation is determined.

With the right tools, platforms and partnerships, I am confident we can fight disease with data!

The Hasso Plattner Institute, one of the co-innovators of SORMAS, shot a video about the development of SORMAS.

Image credit: SORMAS screen shots provided by SAP. Feature image is s screen shot from the Hasso Plattner Institute SORMAS video.