Malaria remains an extremely prevalent disease in the world, yet there exist few solutions that provide critical tools, such as mosquito nets, to battle it. After hearing about Stephen Curry's parternship with Nothing but Nets, we decided to create a map with Esri that identifies the most critical areas in Africa that need or replace nets, using demographics, climate, ages of the nets, and other factors for workers in organizations, such as the United Nations, to better allocate a use for limited resources like nets.

What it does

Our web app locates areas in Sub-Saharan Africa in which nets are most needed (by precipitation, climate, age, and age of net). Workers are able to login through our site to access the map, so they can better decide where to distribute their nets. Furthermore, they can add their own data on where and when nets have already been distributed, so the nets can be replaced in two years. While the website is primarily catered to those that work with organizations aiding in the fight against malaria, we also have places to direct donations to the cause and learn more about how to help, whether it is through news articles or volunteering.

How we built it

The primary languages used were HTML/CSS, Javascript, and Esri's API to create the map.

Challenges I ran into

It was quite difficult to understand how Esri worked at first, and we spent quite some time on adding layers. Another issue we had was the sensitivity of CSV files after being converted from Excel. It took a couple tries to successfully upload them onto Esri and plot the datapoints on the map. As we were new to Esri's JS API, it presented another new, yet exciting challenge to solve.

Accomplishments that I'm proud of

While there are many products that raise awareness and support the fight against malaria, we were proud that ours provides a direct link to solving the crisis. Our product provides information crucial to understanding where the nets could be best used and also when they should be replaced. Essentially, we are digitizing the distribution and age of mosquito nets onto a map.

What we learned

Perhaps the greatest outcome of the project was learning how to work with Esri's ArcGIS, an extremely useful tool for analyzing various trends, such as mosquito nets.

What's next for Malaria Map

In the future, we hope to alter our algorithm to target more specific areas, such as cities, that have a large need for the nets. Additional layers will also improve analysis of these regions, providing the workers with more accurate results. Moreover, we hope to extend the idea to other mosquito-borne diseases such as Zika and West Nile Virus.

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