New Mexico Supercomputing Challenge

Getting Down and Dengue!

Team: 101

School: New Mexico School for the Arts

Area of Science: Epidemiology

Interim: Dengue fever is a disease distributed by Aedes aegypti, commonly called the Yellow Fever Mosquito, and effects 100 countries across the planet. There are four strands of the dengue virus, and it is common for people to catch one dengue virus. They recover in about two weeks, but this does not protect against the other dengue viruses. When people catch dengue a second time, they usually progress to severe dengue. It is severe dengue that is fatal. Dengue fever is a virus transmitted by mosquitoes, and it affects more than one-third of the planet.

The dengue virus (DENV) is not common in the United States of America, but it is the leading cause of illness and death in tropical and subtropical environments, such as Puerto Rico, Cuba, Latin America and Southeast Asia. Up to 10 million people are infected yearly, and DENV has no known vaccine. The best prevention method is those to prevent mosquitoes, and early detection can greatly increase the likelihood of avoiding severe disease. DENV has only been a worldwide problem since the 1950’s.

Cuba has had policies for integrating the community. The community of Cuba believes in attacking the problem biologically. They have lots campaigns were they involve social awareness of people and involving them in the fight against the Aedes aegypti. Cuban Ambassadors have gone around the world into places like Nicaragua, Venezuela, and other Latin American countries to help with their epidemic problem as well. As well as the biological program they have had experimentation in creating a vaccine for Dengue, with the help of the international company LABIOFAM.

Using GIS data we can create a digital topographical map that we can use to track the collection of rain. Combined with the rainfall data we can approximate the water collection and levels in a given month. Since mosquitoes breed in standing water, we can also approximate a basic mosquito amount for the agent based model. That will influence the spread of the disease because the mosquito is the carrier. The next and final step is using that data as a base we can introduce social awareness and source reduction to the model to see how it affects the spread of the disease.

We have made a great amount of progress thanks to assistance from Stephen Guerin and Kyle Smith. For our agent-based model, we have a working “rain” model with GIS elevation data imported for the entire island of Cuba. Before the interim presentation, we hope to also input correct rainfall data in order to begin modeling the breeding cycles of mosquioes and the spread of dengue fever in a human population throughout the country. We also have a fully developed system dynamics model which uses differential equations to monitor the number of people susceptible, infected, and recovered (SIR) as well as the number of vectors (mosquitoes) and their infection dynamics. Using birth, death, infection, and recovery rates from Cuba and dengue fever, we have created realistic approximations of the spread of dengue fever analytically and graphically. We hope to compare the results from our agent-based model with the results of the system dynamics model to ensure accuracy.

If we can successfully create a model that represents the spread of dengue in Cuba, we’ll have a better idea of its severity and can in turn can discover what disease preventative measures to take. By understanding the inner workings of the disease transmission, we can develop methods of social awareness. We predict that by making people aware that source reduction of susceptible water can reduce the spread of disease, infection rates will decline. If there is less stagnant water for mosquitoes to produce in, the less mosquitoes will be able to spread disease. We’re expecting to see that by increasing social awareness we can reduce the spread of disease. By using both system based models as well as agent based models, we’ll have enough data to support this claim. We’re hoping to discover consistency between the models, and thoroughly investigate any differences that occur.

Team Members:

  Mohit Dubey
  Kendra Carmona
  Lauren Sarkissian
  Erin Ice-Johnson

Sponsoring Teacher: acacia mccombs

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