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How AI Is Driving the Eradication of Malaria By Arnon Houri-Yafin

Arnon Houri-Yafin is the Founder and CEO of Zzapp Malaria, a developer of software tools for malaria elimination. Arnon’s prior roles include Director of Research at Sight Diagnostics and Lecturer in Statistics at The Hebrew University of Jerusalem. His specialisms include data analysis, statistics and machine learning.
In this interview, Arnon discusses the breakthroughs Zzapp Malaria has made in the fight against this deadly disease. He explains how AI and data modelling have played crucial roles in developing Zzapp’s strategies:

So, if we start with your personal journey Arnon, could you tell us how you ended up working in both AI and in the field of malaria eradication?I have two answers. One is a personal story, where my friend took me to see malaria first-hand and then another one is poverty.

Back when I had to decide what to study in university, I chose economics. My goal was to become an economist in the context of developing countries, and specifically African countries. I believed that reducing poverty was the key to significantly improving the wellbeing of whole communities.

Just before I completed my MA, a friend called and told me that he was starting a company (Sight Diagnostics) dealing with malaria. I knew at the time that malaria was a huge problem in terms of public health, and that it’s one of the primary reasons for poverty. The disease prevents people from going to work, either because they are sick or they attend to sick family members, which reduces productivity. Malaria is also one of the primary reasons why children in Africa miss school, which obviously harms their ability to progress.
Sight Diagnostics developed a malaria diagnostics device, and one of my jobs was to test them. We ran these tests in public hospitals in Mangalore and Mumbai, India.

In India, you have some places with a lot of malaria and others without. I was in an area with a lot of malaria. Now, I’m a nervous parent – when my children have a fever; I get really stressed out. But then you see the moms with young children who are very feverish, they are scared, because it’s not just a fever that will probably be gone by tomorrow, it’s malaria. And when I saw that, the difference between malaria diagnostics and malaria elimination struck me.

In many countries, Israel for example, malaria was a problem – a big problem. Here, malaria was all but eliminated in the 1920s and 1930s, after the stagnant water bodies where the Anopheles mosquito breed were thoroughly targeted. So, if we have such a big problem, but one that could be fully eliminated, why don’t we do it? This is what caused me to say, okay, diagnostics are very important, but we need something more radical. We need to recreate in modern Africa the successful malaria elimination operations of Cyprus, Egypt and many other countries.

Is that why you specifically founded Zzapp Malaria?
Exactly. Zzapp Malaria is about moving from malaria control to malaria elimination. This takes artificial intelligence and data. When people tried to treat water bodies in Africa, they did it with partial success. This is because tropical Africa has two rainy seasons and there are wide areas that must be searched for water bodies that once detected need to be treated regularly. A very high percentage of water body coverage is required, which is a difficult result to reach.

With our system, fieldworkers go into the field with a smartphone that guides them exactly to the areas they need to search, enables them to upload information about the water bodies they find, and, once water bodies are detected, shows them which water body has already been treated, which needs to be treated again, which houses should be sprayed etc. So we really have a lot of information about the exact location of water bodies and the overall situation of the operation in terms of the treatment of houses and mosquito breeding sites.

To find out more about Zzapp Malaria’s technologies and their impact on countries affected by malaria, head over to our magazine and read the interview in full: https://issuu.com/datasciencetalent/docs/the_data_scientist_mag_issue_3_digital/s/28606519

 

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