AIME

AIME predicts Dengue and Zika outbreaks in tropical countries with Artificial Intelligence in order to improve the ability of public health professionals to make informed decisions. This enables public health professionals to reduce the high cost of vector­borne diseases control and to increase the effectiveness of existing vector control methods, saving lives and resources.

At a Glance

Comments 0
Favorites 1
Evidence 0

How Can You Help?

No assistance needed at this time.

Point of Contact

About This Innovation

Innovation Stats

Innovation Type: 
Where did you create your innovation?: 
Where have you implemented your innovation?: 
Are there any related Programs?: 
In what sectors does your innovation belong?: 

How does your innovation work?

Multi-platform SYSTEM, which involves responsive web applications and mobile apps, all connected through the same backbone database, scalable by design and modular enough to be able to keep innovating with new solutions to public health problems (for example not only regarding Zika or Dengue, but modular enough to even integrate diseases like Tuberculosis or Diabetes).

This solution is unique because: 1. It leverages itself in the convergence of epidemiology and an “exponential” technology, which is Artificial Intelligence, though the use of machine learning techniques. Enabling for automated processing of data, higher accuracy and adaptive results. The model understands the disease, its trends and how it behaves according to the inputs we give to it. 2. It is build with the assistance of experienced public health officers, for public health officers. AIME provides a solution to the issue of importance of its target users, because it is designed by people that belonged and served in the public health environment. 3. Although the platform uses a great amount of computing knowledge, its backbone is epidemiological research, rather than computing research. This is of highest importance, as the variables used to analyze the disease was obtained after cumulative years of work in epidemiology. Having a health platform backed by health research ensures the impact it can have if implemented. 4. The platform has been field tested in multiple environments, and has been proven to [accurately] work even with limited sets of data. 5. The platform itself is easy to implement and replicable in different countries. 6. It has the ability to evolve, by researching new disease the platform will grow to become the premier analytics platform. The “Bloomberg” of public health, with a “Palantir” methodology.

Next Steps

The implementation process of our solution, has 2 major components: 1. The first one is the R&D component. Our solution is heavily focused on the merge of Epidemiology and Data Science. With the mix of this two sciences, we are able to obtain information that would be impossible to obtain for humans in a timely manner. This component has a long process of research and then development, usually can last from 3 months to 2 years. 2. The second component is what we like to call the ¨Business¨. In this stage, we make use of our existing relations to obtain new relationship with possible stakeholders that would like to acquire our solutions. This component has a strong entry barrier, but once passed, we are able to make lasting relationships, with both the public and private sectors. In order to scale the solution, we only need to focus on development the second component with every potential client.

Discuss