The effective use of analytics to interrogate data related to, for example, geography, population and mobile device use can help authorities discern underlying patterns and associations that will allow for relevant emergency services to quickly react to floods, fires and other pressing scenarios, says SAS senior business solutions manager Aneshan Ramloo.

The Data for Good movement, of which SAS is an active member, is a global initiative to use the capabilities of Big Data, advanced analytics and machine learning to tackle social and humanitarian issues, including poverty, poaching, drug trafficking, public health, education and disaster management.

“While there is nothing we can do to prevent natural disasters or severe weather events, we can use Big Data and advanced analytics to help us respond to disasters faster and more effectively,” he explains, adding that this also demonstrates how advanced analytics can assist in solving humanitarian issues.

Analysing a combination of historical data points and applying them to new data before, during and after a natural disaster occurs enables emergency services to plan highly targeted and more efficient relief efforts.

Emergency response agencies can model potential disasters and their effects, thereby enabling authorities to develop proactive plans to prevent or mitigate harmful consequences, Ramloo says.

This can be achieved using data from global populations with detailed demographics, family structures, travel patterns and activities. Construction of data models is done in such a way as to mirror real census, social, transit and telecoms data patterns, with authorities subsequently being able to effectively build virtual cities to test various disaster management strategies.

“Performing real-time advanced analytics on all this information will enable authorities to provide quicker, more effective responses to areas even as the disaster may be occurring,” Ramloo emphasises.

Analytics can help to save lives, as immediate access to all crisis data is available. Authorities can use analytics to determine where the safest and most optimal areas are to set up treatment centres, including taking into account traffic, road networks, nearby hospitals, closest supply centres and infected populations. It can also help to determine the medicines, food and medical equipment that will most likely be required in specific areas.

With Big Data, it is even possible to understand how residents may react to future catastrophes.