Philippine Relief Efforts Aided by Visual Analytics


In giving advice on how to build a compelling analytics resume, hiring managers and recruiters we've talked to at All Analytics typically include volunteer work among their suggestions. Plenty of non-profit organizations are lacking resources needed to make sense of, and get value from, their data.

Today, I've learned that SAS, this site's sponsor, is leading by example with noteworthy analytics volunteerism of its own.

Typhoon Haiyan showing
annual characteristics on
Nov. 7, 2013 (source: NASA).
Typhoon Haiyan showing
annual characteristics on
Nov. 7, 2013 (source: NASA).

In November 2013, as you no doubt recall, Typhoon Haiyan unleashed its fury on the Philippines. The devastation was horrific, with USAID reporting 6,201 dead, 4.1 million displaced, and 1.1 million homes damaged or destroyed.

The situation remains dicey, at best, as the International Organization for Migration (IOM) noted in an evidence-based May report on the continued impact. As noted on the Philippine Response Blog:

Now, more than six months on, more than two million people are still without adequate shelter or durable housing, with over 26,000 living in temporary sites (evacuation centres, tent cities, spontaneous settlements and bunkhouses). Many face prolonged uncertainty about whether they will be allowed to settle back in their former homes -- most of which lie in designated "no-safe" zones -- and what plans there are for their permanent relocation, with a lack of transparent information a key concern.

In spite of the wealth of information generated, it has been difficult to form a coherent understanding of the evolving and complex displacement situation [following Typhoon Haiyan]...," says Alfredo Zamudio, director of the Internal Displacement Monitoring Centre, the reportís co-authors.

And that's where SAS, via a pro-bono pilot project, fits in.

In crises such as the one wrought by Typhoon Haiyan, IOM, an inter-governmental organization, works on behalf of the displaced -- managing shelters and coordinating operational efforts at evacuation centers, camps, and schools. Central to those efforts is a tracking and monitoring system called Displacement Tracking Matrix, or DTM.

As part of the Philippine relief effort, IOM shared DTM data with government and humanitarian partners, as well as with SAS for use in a pro-bono project using SAS Visual Analytics. Another Philippine Response Blog post described the project, which started with Excel data, as such:

The Philippines office of SAS Visual Analytics organized and analysed the data to identify shelters which faced the most critical health risks. Within minutes of the first data being uploaded, a map emerged showing shelters experiencing a dangerous mix of overcrowding, unsafe drinking water and solid waste disposal problems. This allowed IOM to pinpoint sites where high number of families still lived in makeshift shelters or dramatic growth of certain vulnerable populations in a short amount of time.

A SAS Visual Analytics display of demographic data on people displaced by Typhoon Haiyan.
A SAS Visual Analytics display of demographic data on people displaced by Typhoon Haiyan.

Further, as SAS described in a press release, text analysis showed upper respiratory and cold symptoms to be the most common health complaints. "But more alarming were higher concentrations of diarrhea, fever, and skin disease among older people living in evacuation centers in Leyte. The DTM-generated data was shared with local health authorities to address these health needs."

The use of Visual Analytics fit into IOM's overall goal to modernize disaster response. In a prepared statement, Ambassador William Swing, IOM director general, said:

We have been working to enhance preparedness by developing practical tools for government officials, humanitarian organizations and affected communities. The SAS collaboration provided the right tool at the right time. We, our beneficiaries and partners are all grateful for the partnership and technology.

Text analysis also came into play for assessing reports coming in via social media conversations from areas like Guiuan, where phone lines had been knocked out of service. For example, an analysis of more than 10,000 tweets "indicated total structural devastation in Guiuan," SAS said. However, the same analysis confirmed Red Cross efforts to distribute food and the presence of an Australian emergency medical team. "It further shed light on what the local hospital needed most -- essential medicines such as antibiotics and fuel for generators, so that critical hospital services could continue to meet increased health care demands."

It seems to me this is an example of volunteerism at its best -- bringing together the data-savvy with sophisticated tools enabling real-time analysis and insight into critical recovery services. Do you have your own examples of analytical-minded volunteerism? We'd love to hear your story, so share below.

— Beth Schultz, Circle me on Google+ Follow me on TwitterVisit my LinkedIn pageFriend me on Facebook, Editor in Chief, AllAnalytics.com

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Beth Schultz, Editor in Chief

Beth Schultz has more than two decades of experience as an IT writer and editor.  Most recently, she brought her expertise to bear writing thought-provoking editorial and marketing materials on a variety of technology topics for leading IT publications and industry players.  Previously, she oversaw multimedia content development, writing and editing for special feature packages at Network World. In particular, she focused on advanced IT technology and its impact on business users and in so doing became a thought leader on the revolutionary changes remaking the corporate datacenter and enterprise IT architecture. Beth has a keen ability to identify business and technology trends, developing expertise through in-depth analysis and early adopter case studies. Over the years, she has earned more than a dozen national and regional editorial excellence awards for special issues from American Business Media, American Society of Business Press Editors, Folio.net, and others.

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Coordination
  • 6/10/2014 9:55:27 PM
NO RATINGS

The 2004 tsunami relief efforts were really difficult to coordinate. If big data analytics were available at the time it would have helped a lot. I know this first hand since I volunteered to coordinate relief efforts in Sri Lanka. Some of the projects are still on going. You can imagine the scale of devastation and the effort it takes to bring things back to normal or as normal as it can ever be. Internet and email helped a lot to organise everything. But it was a daunting task with so many people in need.

Re: Coordination
  • 6/11/2014 12:38:56 PM
NO RATINGS

@Phoenix -- first off, kudos to you for volunteering your services to help in the relief effort. Did you do so from a technical skills perspective or more generally?

Second, did you see any evidence that relief organizations were collecting and analyzing data at all? 2004 predates much of the advanced analytics of today, but I'm wondering what might have been done with the tools available at the time?

I would imagine there are lots of lessons to be learned from today's recovery efforts, and from what I've learned in reading about this project, the United Nation is really pushing for more data to be made available to the public -- which in turn will lead, hopefully, to more analytical insight. That's a great direction to be moving in.

 

Disaster Relief analytics
  • 6/12/2014 7:39:42 AM
NO RATINGS

With that many people still displaced I can see the usefulness of data collection to keep relief efforts on track.  I'm wondering though how many of those who were displaced want to resume the life they had before the tsunami hit?  The scattering seems like a natural consequence and that some people would rebuild elsewhere.  On the note of the illness that the data is showing this is a great tool to have.  The symptoms seem to indicate a few simple to fix problems in the shelter areas.  Now they have to decide how to go about addressing the problem and they have data points to look at to see if they are making a difference.  With that many people to look after I'm sure medical personnel don't see much change day to day because they are deep in the trenches but the numbers could show trends over time.

Re: Disaster Relief analytics
  • 6/12/2014 12:08:00 PM
NO RATINGS

@SaneIT, you make a good point about the scatter effect from displacement. These numbers would be valuable, though, when focused in on the temporary shelters set up for relief purposes or when used in combination with other data sources on factors like crime, overcrowding, unemployment, etc -- how has the effect of the displacement affected conditions overall? 

Re: Disaster Relief analytics
  • 6/13/2014 7:49:44 AM
NO RATINGS

Yes the numbers would be very good for keeping up with people who are still living in shelters and keeping them as safe as possible.  I do wonder if they are tracking how many people have left and where they settled as well.  When you've lost everything in a matter of minutes and have no real reason to go back I'm sure that changes how people view their future.  If they see no good reason to leave the new area then the new area needs to build up services to support their growing population.

Re: Coordination
  • 6/13/2014 12:00:51 PM
NO RATINGS

Not having personally been involved in a disaster since Hurricane Andrew in Miami, I wonder how difficult it is to get the data distributed when phone lines and most other direct communication is spotty in disaster areas. It would seem internet access should be pretty hard to get at least immediately after a disaster and for several weeks?

Re: Coordination
  • 6/15/2014 3:21:37 PM
NO RATINGS

@Beth I helped with the coordination of donations. Wherever possible aid was given out directly to the victims for their specific needs. For instance if it was a small tea shop owner we'd buy everything they needed to start a new tea shop. This way they can get back on their feet much sooner. The larger efforts were more general. And catered to the needs of the majority. I had a data base with everyone's needs listed out and individual donors were matched so that it was a more personal effort. I did the coordination from my home with my home computer using only excel and access databases. A donor would know who they helped and some people visited Sri Lanka to meet the victims they helped later on. After the initial couple of years I went back to work but this time for a management consultancy firm catering to NGOs. So I came across a lot of data that they had gathered. But the systems used for analyzing were not as good as what you get today. Excel and access databases were used by smaller organisations while large NGOs had their own systems.

Re: Coordination
  • 6/15/2014 3:33:23 PM
NO RATINGS

@kq4ym At least in Sri Lanka things moved very fast. The mobile phone networks were working after the initial jam. Only some of the coastal areas were effected so the communication networks inland were still available. Sri Lanka is also a very small country so it was much easier to reach disaster areas.

Re: Coordination
  • 6/16/2014 8:22:02 AM
NO RATINGS

@Phoenix, being able to contribute to the recovery in that way must have been very gratifying -- especially being able to link donors to recipients. Thanks for sharing your story.

Re: Coordination
  • 6/16/2014 12:38:30 PM
NO RATINGS

@ Beth It was an amazing experience. I'm also very grateful to the people who made the relief and rebuilding efforts such a success through their contributions. Most of the fisherman who lost their boats and others who lost livelihoods have managed to start their lives again. Some who depended on family members who were lost in the tsunami had to find new ways to support themselves. We live in a very generous society. In addition to the foreign aid it was the villagers who took care of their neighbours. Before emergency help arrived people living around the affected areas had already helped save many lives. Even the poorest of the poor had shared what they had. It was wonderful to see the human spirit survive and the outpouring of kindness and support for fellow human beings. It was truly remarkable.

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