How Big Data is helping the fight to end malaria by 2020
A new initiative is using the power of the cloud to help eliminate malaria in Zambia by 2020 after research suggested a drug-resistant form of the disease is emerging out of Africa.
Analytic database provider EXASOL is partnering with PATH, an international non-profit organisation and leader in global health innovation, intend to tackle the issue head-on.
Together, as part of the project Visualize No Malaria, the organisations want to support the Zambian government’s ambitious campaign, and the first part of that is predicting where outbreaks will occur using Big Data.
Mapping wetness in Zambia - red=dry, blue=wet
By mapping geospatial data, using data such as elevation and slope, combined with hydrological features such as topographic wetness and stream power, scientists can create a very precise, accurate map of water courses.
Combining this with meteorological models of precipitation and temperature allows health officials to proactively focus on probable outbreaks.
This is the first time that cloud technology has combined with the know-how to take on malaria in this innovative way.
Aaron Auld, CEO of EXASOL, said: “Data analytics is often discussed as a way for business to derive value from the data they hold, whether that is to increase profitability or serve customers better.
“But data can also unlock important information that can help organizations such as PATH improve the way they address Malaria.
“This ultimately shows the value of data in saving lives.”
Nearly half the world’s population is at risk of malaria, and organisations worldwide are continuously looking for new ways to combat this global health issue.
According to the World Health Organisation, there were roughly 212 million malaria cases in 2015, with young children and pregnant women particularly vulnerable to the disease.
In Africa, it takes the life of a child every two minutes.
Allan Walker, a volunteer with expertise in data analytics and visualization, is helping PATH’s #visualizenomalaria team create analyses that estimate where malaria cases will be more likely to occur.
He said: “EXASOL simply puts the ‘snap’ and ‘zing’ back into Tableau projects, regardless of scale, effortlessly returning queries of billions of rows of data.
“It has back-end database power and speed that Tableau developers require and users in the field will appreciate.”
The analyses aim to find the relationship between the mosquito vector and human carriers.
The team’s current project involves loading complex geospatial data into the EXASOL database to model geological features in Zambia’s Southern Province such as elevation and slope and hydrological features such as topographic wetness and stream power.
This shows whether the land is dry or wet, and if water is still or moving.
Jeff Bernson, senior director of PATH's Results Management, Measurement and Learning Department, said: “If you’re trying to inspire data use among counterparts and decision-makers, watching a spinning wheel and waiting for dashboards to render can often be a deal breaker.
“Partnering with EXASOL and Tableau is helping us tackle challenges with data access and speed.
“It truly aligns with our focus to develop and apply transformative innovation in low-resource settings.”
Auld added: “It has been a great pleasure to support PATH in this fantastic initiative.
“Furthermore, we have an enormous amount of respect for Allan and his team for their dedication and hard work around the program.
“We are grateful to Jeff and the PATH organization for their decision to engage with us, and we look forward to continuing to make a contribution towards supporting PATH and the Zambian government in their efforts.”
Malaria, a mosquito-borne illness, has seen remarkable reductions worldwide, with mortality rates declining 60 percent since the year 2000.
But this preventable disease is still killing too many people in sub-Saharan Africa, where malaria takes the life of a child every two minutes. In Zambia alone, it’s estimated nearly 3,000 people die from malaria each year.