Over 11000 people died during the 2014-2016 Ebola outbreak in West Africa.The virus hopped between Guinea, Leone, Nigeria and Liberia, before making its way to the UK and US. But what would have happened if analysis and machine learning stepped in to help solve the problem, asks ANESHAN RAMALOO of SAS.
But what if we could have predicted the outbreak months before it happened, buying us time to take proactive measures to contain it and curb its spread?
With access to overwhelming volumes of data, the computational power needed to store and analyse this data in real time, and sophisticated algorithms that can find patterns in the data and alert authorities to health problems before they become, well, problems, pandemics don’t have to be as devastating as they have been in the past.
In fact, with advanced data analytics, we can better manage any disease – long-term, short-term or pandemic – resulting in better patient treatment, more efficient use of resources and cost savings.
It’s been done before.
By analysing data from social media, blogs, online forums and keyword searches, we were able to predict the 2012-2013 US flu season three months before the Center for Disease Control (CDC) issued its first official warning.
Imagine the impact if the same analytical power was applied across the entire healthcare spectrum – not only on a national and global level, but right down to the individual level.
In the past, health workers relied on manually intensive, paper-based systems to record infections and deaths during disease outbreaks. Not only was it easy for errors to slip through but because the data was anecdotal and historical, authorities did not get a complete understanding of the reach and impact of the outbreak.
During the Ebola outbreak, the CDC adopted a mobile data collection system that enabled health workers to instantly submit information to a database via text messages. This low-cost method of information gathering not only resulted in fewer errors but also allowed analysts to draw up detailed maps of population movements, which made it easier to understand how the disease was likely to spread, and where to set up treatment centres.
While this was certainly an improvement on the paper-based systems of old, the drawback was that mobile data was historic and did not provide researchers with the ability to track developments and population movements in real time.
But mobile phones are just one source of data. Today, health authorities can overlay thousands of data sources – including social media, health and physician reports, keyword searches, media reports, transactional data from retailers and pharmacies, airline ticket sales, geospatial data and more – to not only better manage diseases and outbreaks when they do happen, but to see them coming months in advance – and what could happen if we don’t act on the information.
By mining structured and unstructured data, we can track the movements of infected populations and who they come into contact with; we can measure the success of containment policies, education campaigns and treatments – and what to do if they’re not working; we can determine the effect of weather and other environmental factors on the spread of diseases.
Never before have we been able to act on information to save lives, not just during pandemics but through better understanding and treatment of diseases.
Until now, standard treatments for diseases such as cancer and HIV have been applied to all patients, regardless of their unique profiles and with little understanding as to why some people respond well to certain treatments and others don’t.
But by analysing and creating ‘medical maps’ of individuals that take into account their anatomy, physiology, DNA, RNA and chemical composition, doctors can prescribe personalised treatments that have a greater chance of success.
There are many other benefits of data analysis in healthcare:
· Personalised treatment can result in fewer hospital admissions and can produce faster results and better experiences for patients;
· By better understanding the impact of lifestyle and diet on health, medical aid providers can educate their members with the aim of improving their health, which could result in cost savings for both the provider and the member;
· Governments can use data to develop proactive approaches to protecting and promoting public health, to prioritise services and to find ways to cut costs so that they can provide healthcare to more citizens.
· By sharing data and results from clinical trials and combining that data with academic, patient and industry data, medical researchers can better understand the genetics of viruses, why some strains are more deadly than others, and why some people are more resistant to viruses. This could spark innovation and generate new insights that ultimately improve treatment and outcomes.
AI and machine learning
As the use of intelligent algorithms, machine learning and natural language processing becomes more entrenched in advanced data analytics, technology will increasingly supplement the skills of humans to produce faster and more accurate medical diagnoses.
Machine learning can extract valuable insights from unstructured data like clinical notes and academic journals to provide even larger datasets that will transform the medical industry into a proactive front against diseases.
There are plenty of doomsday theories about how machines will supersede our intelligence and rise against us. But there aren’t enough stories about the potential of data analytics, AI and machine learning to supplement human skills and knowledge to drastically changes lives for the better – and even save them. Right now, it’s looking more likely that machines will actually help us to live longer – and I don’t know many people who would object to that.
- ANESHAN RAMALOO, Data Scientist and Senior Business Solutions Manager at SAS.
Mastercard names 9 Africa projects for $9-million fund
The Mastercard Foundation Fund for Rural Prosperity (FRP) has announced that nine companies from seven countries will receive more than US$9 million to support projects that expand financial inclusion in rural Africa.
The nine companies were selected from more than 300 firms competing in the first two phases of the Fund’s 2017/2018 rolling competition, which launched in June 2017 and closed in January 2018.
The 2017/2018 rolling competition was one of the Fund’s largest in its efforts to find and support providers of innovative and scalable financial products and services that improve the lives of poor people living in rural areas of Africa. Financing for another group of companies, assessed as part of the third and fourth phases of the competition, will be announced in 2019.
The latest round of financial support will extend innovative transactions, green energy, asset finance, mobile banking, agency banking, and distribution/logistics solutions to excluded rural populations in the seven countries.
Phase #1 selected companies are:
- Equity Bank Congo SA
- FutureLink Technologies Limited
- Apollo Agriculture Limited
- SolarNow Services Limited
- Easy Solar Limited
- Dodore Kenya Limited
Phase #2 selected companies are:
- Farmerline Limited
- Stewards Globe Limited
- Microcred Limited
The nature and geographical diversity of the new projects saw the Fund expand its presence to four additional Sub-Saharan countries: Democratic Republic of Congo, Mali, Sierra Leone, and Zambia. The Mastercard Foundation Fund for Rural Prosperity portfolio now includes 30 projects in 11 countries in Africa (Côte d’Ivoire, Democratic Republic of Congo, Ethiopia, Ghana, Kenya, Mali, Mozambique, Sierra Leone, Tanzania, Uganda, and Zambia). The projects comprise a range of businesses from traditional banks and solar-energy leasing companies to agricultural off-taker firms.
“We are excited to add nine more companies to our growing portfolio that is having a positive impact on the lives of millions of people across Sub-Saharan Africa,” said Wambui Chege, Team Leader of the Fund for Rural Prosperity. “Today’s announcement reinforces our belief that there is a wide range of innovative, Africa-led projects that, with a little support, can drive financial inclusion across the continent.”
Lindsay Wallace, Director of Strategy and Learning at the Mastercard Foundation, said: “The aim of the FRP has always been to enable smallholder farmers and poor people living in rural Africa to reach their full potential by supporting new private sector initiatives that provide access to financial services. We’re very happy to see this latest round of selected firms, demonstrating the depth and breadth of ideas and action plans that will do just that.”
Continue reading about the companies on the next page.
IoT’s answer for Africa
IoT and digitization enables us to efficiently, proactively and predictively address the sustainability challenges that are faced globally and on the African continent, RESHAAD SHA, CEO of Liquid Telecom.
With Africa’s population set to increase from around 1.3-billion in 2018 to 1.7-billion in 2030, both challenges and opportunities are presented with regards managing issues including food production and security pose as well the utilization of limited natural resources in a sustainable manner.
Water scarcity and quality for example are realities that negatively impact health, food production and security. Population growth rates and climatic changes place an exponential demand on this scarce and dwindling resource. These are just some of the sustainability challenges facing not just the African continent, but other developing nations and the world as a whole. In addition to this, the demand for the delivery of basic services as healthcare and sanitation also increases.
Against this background of African population growth lies the grim projection that Africa will account for more than 50% of child deaths (under 5) by 2030, while each day, nearly 1000 children die owing to preventable water and sanitation-related diarrheal diseases according to the UNICEF 2017 trends in child mortality report. It’s an alarming fact, given that while some 2.6-billion people have gained access to improved drinking water sources since 1990, 663-million people still do not have access.
The department of Water Affairs and Forestry estimate that the agricultural sector accounts for more than 50% of water use in South Africa and experience water losses of between 30 and 40 per cent. Further, the department states that around 35% of irrigation system losses, often nutrient enriched and containing herbicides, pesticides, and other pollutants, return to rivers. These are just some of the ways in which reactive, inefficient, and manually driven processes have limited us in responding in an impactful manner and timeously mitigating these risks
It is for these reasons and other socio economic and environmental concerns that the United Nations has established its Sustainable Development Goals strategy, addressing the global challenges we face, including those related to poverty, inequality, climate, and environmental degradation.
We need to look at smarter ways that leverage technology in order to addressing these challenges. The situation requires a radical response that delivers a proactive, predictive and data driven approach to addressing these issues with exponentially growing levels of speed and impact.
The IoT ecosystem, comprising of sensors, connectivity, data analytics and workflow automation platforms, and applications are at the core of acquiring, analyzing and harnessing the insights that can be integrated into agriculture, service delivery, health and resource management processer – IoT is at the core of a digitization
One such sector which has benefited immensely from technology is in agriculture pest control, with the implementation of AI and IoT by Spanish startup AgroPestAlert. The innovation makes use of “smart” traps that capture insects and analyse their wing beats to identify their species and even their sex. Placed throughout the fields, the traps communicate with the system to predict an imminent invasion. The system will send alerts to phones, tablets and computers and use an easy-to-understand visual tool to cue farmers instantly.
Around 200-million Africans use approximately 1-million manual pumps across the continent to manually access clean drinking water. IoT applications have been utilised in assuring the delivery of water through manual these pumps, According to estimates, at least one-third of those pumps will break down at least once in its lifecycle, and up to 70% will break in the second year of operation. The impact of not having access to clean drinking water is dehydration or water borne pandemics.
In the Kenyan Region of Kyusoa, Oxford University began a proof of concept project in 2013, which made use of motion sensors) to capture the movements of the pumps’ handle which was transmitted and analysed in real time. A decision support system based on real data was used to predict pump malfunctions, allowing for a better planning and shortening the time needed to repair broken pumps, or avoiding malfunctions altogether, directly improving the access to clean drinking water for the rural population.
Liquid Telecom realise that the future of sustainability lies in technology and innovations such as IoT. We provide high speed fiber connectivity to interconnect as well as access platforms to build IoT solutions, in addition to access to Microsoft Azure suite of platforms for analytics and algorithm driven based processing and execution. Our Pan African network enables collaboration and cross border innovation and learning, fast well as the capability to efficiently scale out these solutions on Africa’s Liquid Cloud.