ProjectBlog: Mitigating the Impact of Parasitic Outbreaks

Blog: Mitigating the Impact of Parasitic Outbreaks

Throughout history, humans have always been exposed to diseases (sometimes immensely fatal ones like the Spanish Flu or Black Plague) in chain reactions. These chain reactions cause significant epidemics, even today, which is why Prohibio Health plans to prevent these epidemics through the use of artificial intelligence. Our mission is to radically transform the historical approach in preparing for diseases to mitigate their impact. Specifically, we are using artificial intelligence to simulate insect populations so we can predict where aid is most needed. Through this, we can help reduce the impact of ever-present insect-borne diseases (like malaria) and reduce the risk of disease outbreaks (like Zika).

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Mosquitoes Infect Hundreds of Millions Annually

There are three main types of parasites that cause parasitic diseases:

  1. Protozoa — single-celled organisms that can live and multiply inside your body.
  2. Helminths — multi-celled organisms that can live in or outside your body.
  3. Ectoparasites — multi-celled organisms that can live on or feed off your skin.

Of these, the ectoparasites are the most worrying for Prohibio Health. They include many of the troublesome pests you always hear about (like mosquitoes and ticks), but also some that seem less familiar (like the tsetse fly). Out of these ectoparasites, the mosquito is undoubtedly the most common transmitter for many diseases. Specifically, female mosquitoes can bite humans for blood, inadvertently picking up any parasites in that human blood. The parasites can then develop inside the mosquito, before being transmitted to another human with the next bite.

Due to the immense population of mosquitoes, they are able to transmit parasitic diseases to people nearby, gradually creating an outbreak. For instance, there are 500 million malaria cases annually and malaria can only be transmitted by Anopheles mosquitoes. Similarly, the Aedes mosquito spreads Dengue to 96 million every year. Furthermore, mosquitoes can rapidly spread parasitic diseases all over the world by infecting tourists, livestock that is being transported, and birds who are migrating. For example, mosquitoes unpredictably spread the Zika virus from Western Africa to South America, causing an outbreak of the disease starting in 2014.

Insect Populations Change in Complicated Ways

Evidently, the current approach to address diseases does not work; we do not understand how insect populations change and are, thus, unable to effectively prepare for potential disease outbreaks. This is especially true due to the complicated factors involved in insect migration and breeding, including:

  • Temperature and humidity;
  • Rainfall and standing water;
  • Waste and sewage systems;
  • And human and livestock movement.

These are just some of the factors involved in insect migration and breeding, making it clear why it has been so hard to understand these factors (especially for developing countries, which are often the hardest hit by insect-borne diseases). Up until recently, we simply did not have the technology to feasibly analyze these relationships, but that is where our solution comes in.

Photo by Jeremiah Mott on Unsplash

By simulating insect breeding and migration with artificial intelligence models, we will predict which areas are most at risk for a parasitic outbreak. First, we will use existing data like factors that affect insect breeding and migration to train neural networks, a type of artificial intelligence that can find complex relationships in this data. The neural networks will be trained on the Microsoft Azure cloud to predict existing breeding and migration until it generates results that are accurate to real life. Next, real-time data will be gathered using internet of things (IoT) sensors, which will be fed to the cloud to be processed. The neural networks use that data to make predictions about breeding and migration, identifying at-risk areas for disease outbreaks so effective resources can be deployed to prevent them.

Many Industries Use our Predictions on Disease Transmission

Through these predictions, we help charities and governments effectively deploy resources where they’re needed most. In addition, our neural networks can analyze data stemming from a region to identify whether a particular transmission factor (like a major shipping industry) needs to be addressed, mitigating the risk of insect-borne diseases in the future. Moreover, these predictions help future housing/tourism developers know where the most reliable locations to build are to avoid the risk of future disease outbreaks and mosquito migration. In essence, these predictions can be used by our clients to not only address the impacts of disease as they occur but understand how to prevent them before they occur.

This broad usability of our product is fuelled by the back-end of our operations on the cloud. Specifically, we are able to easily scale up our operations using the Microsoft Azure platform. For instance, we can increase the amount of data our neural networks train on and make predictions for additional clients without worrying about hardware constraints due to our work on the cloud. Additionally, our IoT sensors are able to easily relay information back to the cloud in real-time, allowing us to scale up our system without worrying about how to get this data back to our neural networks. These key partners and clients allow us to have an effective market strategy to mitigate risk.

Effectively Scaling our Services to Maximise our Potential

Photo by John Schnobrich on Unsplash

In particular, we have a three-phase market plan:

  1. We use research funding and grants to develop our artificial intelligence models on the cloud. This gives us a proof-of-concept for clients.
  2. We target clients with existing data or existing IoT systems measuring insect transmission factors. This allows us to avoid the costs of IoT systems while establishing credibility.
  3. We offer our services to new clients that are most at-risk for diseases like malaria but may not have existing IoT systems. We use our working capital and credibility from previous projects to implement these new IoT systems.

With this approach, we use revenue to expand our services and reach new clients at each step, allowing us to quickly scale our company.

As can be seen, this gives us enormous potential to maximize the efforts of our clients in preventing and preparing for some of the largest diseases in the world. Prohibio Health has the opportunity to get aid to hundreds of millions who do not have access to it, allowing us to transform the historical prevention of major disease outbreaks at an unprecedented scale. If you’d like to learn more about our progress, check out our landing page!

Source: Artificial Intelligence on Medium

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