Disclaimer: This article was originally posted on Dataconomy.com in 2014 covering the spread of the Ebola

With the Ebola threat still looming large, widespread efforts are being made to identify, quarantine and treat possible carriers. BigMosaic, a big data analytics program developed by the Centers for Disease Control in collaboration with Healthmap will aid CDC in monitoring new cases and work with the West African expat community.

Marty Cetron, director of CDC’s Division of Global Migration and Quarantine, explained at a public discussion on Tuesday – “We have the near real-time availability of the global air transportation network, and we’re able to identify, and in a sense target, the risk populations, the diaspora populations from Liberia, Sierra Leone and Guinea, where they’re distributed down from the county-and-below levels, so we have a mosaic map of the U.S., and in some cases with other countries’ data.”

CDC, HealthMap, Boston Children’s Hospital, and Toronto-based BlueDot (formerly, BioDiaspora), worked together to see this app to completion. Utilizing census, demographic and migration health data of expat populations in the U.S. from 105 countries of birth, it can track the spread of infectious diseases globally, while also breaking down the population by education level, household income, and English speaking ability, reports MedCity News.

BioDiaspora had developed, an online tool charting spread of infectious diseases through international travellers. BioMosaic, using BioDiaspora, maps census data, migration patterns and health status identifies countries where international travel may give rise to emerging disease.

“CDC layers many data sets atop one another to create this mosaic map of the diaspora population both on the move and statically in terms of the resident population,” Cetron points out. “There are a number of big data sets that we access and aggregate, the common feature is that all of them are geo-coded,” Cetron said.

“So we bring in weather data, climate data, we bring in global distribution of poultry, we bring in distribution of swine populations, vector disease incidents from [the World Health Organization] and other sets, and pull all these things together and then put them in a way that they can be easily visualized or queried.”

Health kits with thermometers and mobile phones were distributed by CDC at airports that also debriefed on marking symptoms and instructions for the use of the kit. An estimated 100 mobile phones would allow CDC to exchange information with the users for a month.

Asked about the calls the CDC has handled for the program, Cetron said people queried about a fever but it turned out to be unrelated to Ebola. It has also helped direct people to local health facilities.

He further added in an Q&A with Peter Beinart of The Atlantic- “Epidemics of disease are frequently followed by epidemics of fear … and stigma. The epidemic of fear is understandable given the nature of this disease. But we need to make sure we get the balance right when we speak to the media…The disease needs to be controlled at the source.”

Read more here.

Follow @DataconomyMedia

(Image credit: DFID)

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.

Follow @DataconomyMedia

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)

The International Rescue Committee (IRC) has revealed the intentions of deploying an Electronic Medical Records (EMR) system to counter the spread of Ebola.

The announcement which came earlier last week, reports that IRC teams in West Africa have been “preparing and testing the technology”, for betterment of Ebola patients, clinicians’ decision-making, staff safety, and learning for possible future outbreaks. EMRs also will enable the IRC to systematically document the quality of care if provides to patients.

David Miliband, President and CEO of the IRC explained, “The information provided by electronic medical records significantly increases the power and potential we have to fight Ebola and improve care for its victims. EMRs are a potential game-changer, providing us with critical information for the response and important data that can be used during future health emergencies. The fight against Ebola is far from won, and now is the time to redouble our efforts.”

Owing to the risk of infection most previous outbreak records have been destroyed. In order to better handle situations and remove shortcomings of the system, the IRC has employed teams with expertise in IT, data, business development and medical to structure an approach that betters the quality and efficiency of care.

What they came up with is a system called  “Jedi” (Joint Electronic Health Decision Support Interface) with the potential to dramatically alter the Ebola response in West Africa and which can pave the way for use of electronic health systems in sub-Saharan Africa generally, according to IRC.

IRC explains that JEDI essentially it does three things :

1. Keeping Ebola health care workers safe

The time spent inside high-risk areas of Ebola treatment centers must be carefully monitored. Health care workers wear cumbersome and hot protective gear that limits their time treating patients to about an hour. Jedi can track the location of health care workers to help them maximize their caregiving without jeopardizing their own health.

2. Tracking Ebola patients

Jedi can track Ebola patients’ history from the time they arrive at a treatment center to the time they leave. Health care workers will know instantly how many patients are seen a day, the condition of patients when they arrive, what percentage of the patients test positive for the virus, what essential treatments were given to discharged patients, and the survival rate of patients.

3. Decision-making

Jedi will help health care workers simplify and speed up orders for essential medicines and dosing. If a patient has severe pain, the staff using Jedi can access and order the proper dose of morphine; if someone is vomiting, the health care worker presses the option for anti-emetic to prescribe Zofran.

It will debut later this month at the IRC’s Ebola treatment unit in Monrovia, Liberia.

Read more here.

Follow @DataconomyMedia

(Image credit: JD Hancock)

The world has turned its attention to ebola as the deadly disease continues to spread, mostly in west Africa. Already, the virus has killed nearly 5,000 people in this latest outbreak, but the situation may be even more dire than that. The Centers for Disease Control and Prevention (CDC) is even predicting that as many as 1.4 million people will be infected by January 2015. With a shockingly high mortality rate, this year’s ebola outbreak may be the most devastating one ever recorded. Health workers from around the globe are looking for help in any way to fight the disease, and one technology has stepped up. Big data, while most often used in businesses, is now being utilized by doctors and researchers as they race to contain the disease and save lives.

The very nature of big data can be effective in helping healthcare workers reach their goals. Big data essentially consists of collecting large amounts of data from a large variety of sources. Once the data is collected and organized, big data analytics takes over, mining that data and finding previously unseen patterns and trends that would take humans years to discover, if they could do it at all. Big data analytics also removes any data that is deemed unimportant or irrelevant, further helping in organizing the data that matters.

The only way big data can be effective in fighting ebola is by collecting the necessary data from as many sources as possible, or what’s known as multi-center ingest. This technique and the technology to accomplish it were simply not possible even a few years ago. Now, researchers and data experts can collect information from social media, mobile phones, hospital records, flight records, and even media reports. From there, they can more accurately predict where the disease may spread, which is a vital step in stopping an ongoing outbreak.

Mobile records in particular are offering researchers a deeper level of insight in predicting the spread of ebola. Even some of the least wealthy African countries have high ownership of mobile phones, which can be valuable tools when fighting the disease. Using mobile mapping, researchers are taking data from more than 150,000 mobile phones and charting where regional populations are moving. This not only helps medical workers better predict where the disease might spread, it also lets them know where would be the best areas to send resources so those who have contracted the disease can receive help as quickly as possible. Mobile mapping has run into some limitations for now. The main problem is that tracking regional movements is done based on historic data, not done in real-time, which would be much more effective.

Big data is also playing an important role in helping medical workers research a cure. For now, the ebola virus has no known cure–one of the many reasons it’s so deadly. Big data, however, may help researchers with a breakthrough. Recently, Microsoft announced that it would be offering special cloud tools that would allow experts from all over the world to share information about their ebola research. By collaborating using these cloud computing tools, researchers will be able to pool all their big data and hopefully discover a vaccine that will save lives. This can only be done by using all the available data to help scientists understand more about the disease and how best to treat it.

While big data is a highly useful tool, it’s not without its weaknesses. Skeptics point to Google’s recent inability to accurately predict flu outbreaks based on social media data and other information found on the web. Critics are also quick to note how big data wasn’t able to predict early warning signs of this year’s ebola outbreak, instead pointing out is was through traditional means like governmental reports and media outlets that word of the disease’s spread grew. Proponents of big data counter by saying big data analytics played a key role in the relief operations involved in a 2010 cholera outbreak in Haiti and the spread of malaria in Kenya. In any case, it’s important to recognize that big data is only a tool, and human minds and expertise are still needed to interpret the results and make important decisions regarding strategy in fighting any disease.

However it’s used, big data is one more ingredient researchers need in order to control and stop the spread of ebola. With more experts weighing in with their own data, a cure may even be found. Given enough time, big data may help in consigning ebola to a relic of the past, in turn promoting better health in some of the most impoverished areas of the world.

Rick Delgado- I’ve been blessed to have a successful career and have recently taken a step back to pursue my passion of freelance writing. I love to write about new technologies and keeping ourselves secure in a changing digital landscape. I occasionally write articles for several companies, including Dell.
 

Follow @DataconomyMedia

(Image credit: NIAID)

This week has been a week of conferences in the realm of big data. Our news roster has been dominated this week by a whole host of announcements from the Strata + Hadoop world conference. Highlights include a raft of new integrations on Microsoft’s Azure platform, Waterline announcing the release of their Waterline Data Inventory, and GraphLab making their signature product available to the public.

Here in Europe, the team behind disease monitoring app Infected Flight scooped the Grand Hackathon Prize at TechCrunch Disrupt London. This week also saw the Gartner BI Conference get underway in Munich; our correspondent on the ground Furhaad Shah has been enthusiastically tweeting all of the major announcements over on our Twitter channel. We also hosted the second installment of Big Data, Berlin event series this week. For readers who couldn’t make it this week, we have further events coming up in Munich, London and will be announcing a raft of other locations early next year- stay tuned!

TOP DATACONOMY ARTICLES

6 Stumbling Blocks for Marketing With Data

Touted as a silver marketing bullet, data and scientific thinking will guide creativity in an evolving social and mobile universe. This is the rationale underlying the launch of OgilvyAmp, essentially an aggregation and rebranding of the data wonk’s buried among Ogilvy’s global offices.

Exasol: Building the Fastest Database in The World

Exasol was founded 14 years ago with a mission in mind: to build an ultra-fast, highly scalable database for analytics. We recently caught up with Graham Mossman, Exasol’s Senior Solutions Architect to discuss Exasol’s development and his upcoming talk at Data Enthusiasts London.

TOP DATACONOMY NEWS

ThoughtSpot Combine Enterprise-Class Features With Consumer-Class Usability on 1 BI Platform

As every industry becomes more data-driven, it becomes increasingly crucial that everyone in an organisation- from the Heads of IT to the least tech-savvy business person- has access to the key information. But of course, the requirements of these personel differ wildly, and there is yet to emerge a single technology which combines the enterprise-class infrastructure needed for big data analytics, with usability features that open the data to every person on the payroll. This is where ThoughtSpot come in.

84% of Businesses Think Big Data Analytics Will Change Their Competitive Landscapes

The Industrial Internet (A combination of Big Data analytics and the Internet of Things) holds great potential if executives in healthcare and industrial sectors are to be believed, reveals a research published by GE and Accenture. To put things in perspective with regards to the economic potential of Industrial Internet, an estimate of worldwide spending is predicted to be $500 billion by 2020, pointing to a mammoth global GDP of $15 trillion by 2030, according to Wikibon and GE.

The Fight Against Ebola May Have An Ally in Data Science, Believe Experts

Jai Vijayan while writing for Information Week explains its the unlikely channels are opening up to fight the spread. WHO’s predictions for this week, of 70% fatality rates and 1,000 new infections per week, comes from data about people who have died from or symptomatic, from facilities across Sierra Leone, Liberia, Guinea, and Nigeria, collated with data gathered from medical diagnostic facilities and burial grounds in the affected region.

Augmented Reality Development Gets Fuel as Google Leads Investment of Record $542M in Secretive Magic Leap

An augmented reality startup, Magic Leap, (whom everyone seems to find mysterious) has positively gained some more mystique quotient with the Google (and not Google Ventures) led $542 million Series B financing that it announced on Tuesday. There was participation from Qualcomm Ventures, Legendary Entertainment, including a personal investment from CEO Thomas Tull, KKR, Vulcan Capital, Kleiner Perkins Caufield & Byers, Andreessen Horowitz, Obvious Ventures, and other investors.

Upcoming Events

27-28 October, 2014- Chief Data Officer European Leadership Forum, London

In recent years, there has been a significant rise in the appointments of Chief Data Officers (CDOs), in both the public and private sector. This is a result of data becoming an increasingly important strategic asset to businesses and public authorities.

Data Science Day Wants to Hear from You!
The 7th Data Science Day is hitting Berlin on the 30th October, hosted by Zalando and The Unbelievable Machine Company. The event is entitled “What´s next in Data Science? – or: just a bunch of really hot stuff!!!” If that amount of exclamation marks isn’t enough to get you excited, I don’t what is.

Follow @DataconomyMedia

Big Data may play a key role in impeding the recent outbreak of the Ebola virus according to experts in Data Science.

Jai Vijayan while writing for Information Week explains its the unlikely channels are opening up to fight the spread. WHO’s predictions for this week, of 70% fatality rates and 1,000 new infections per week, comes from data about people who have died from or symptomatic, from facilities across Sierra Leone, Liberia, Guinea, and Nigeria, collated with data gathered from medical diagnostic facilities and burial grounds in the affected region.

However, disease-monitoring website HealthMap, provides “early detection and real-time surveillance” through information sources, like social media streams, online news stories, official reports, travel sites, and official sources, such as WHO.

Senegal based Orange Telecom is providing Flowminder, a Swedish non-profit organisation, with anonymised data from 150,000 mobile phones to to map out basic population movements in affected areas aiding authorities to draw out strategies for setting up high exposure treatment sites.

Compared to WHO, the other channels provide information from ground zero, which many believe to be more accurate. In-spite of that, the information through these channels is historical, while effective thwarting requires something more real time.

“We’ve never had this large-scale, anonymised mobile phone data before as a species,” says Nuria Oliver, a scientific director at mobile phone company Telefonica. “The most positive impact we can have is to help emergency relief organisations and governments anticipate how a disease is likely to spread. Until now they had to rely on anecdotal information, on-the-ground surveys, police and hospital reports,” Oliver said.

In this regard, US Centers for Disease Control and Prevention (CDC) has started collecting mobile phone data from operators to track calls to helplines to in order to establish locations. Mapping innovator, Esri has been helping CDC to “visualise this data and overlay other existing sources of data from censuses to build up a richer picture.”

Questions over the effectiveness of Data Science here, remain unanswered. To get a fuller picture, we need more sources of data and the ability to analyse them quickly, experts say, reports BBC News.

“Big data analytics is about bringing together many different data sources and mining them to find patterns,” notes Frances Dare, managing director of Accenture Health. While reports on the social media may not be completely accurate, they might contain early ‘warning signals’, says Michael Hendrix, director of emerging research and issues at the US Chamber of Commerce Foundation.

To help alert and avert outbreaks like the current Ebola, this information can work well when combined with official data sources.

Read more here.

Follow @DataconomyMedia

(Image credit: NIAID)