New Mexico Supercomputing Challenge

Predicting The Death Toll of Pathogens

Team: 131

School: Rio Rancho Cyber Academy

Area of Science: Epidemiology


Interim: My project is on the effects of multiple pathogens with different characteristics on the population. The pathogens have different spread rates and mortality rates individually, both are in most cases non-lethal but put together can cause many more deaths. The individual people of the population have characteristics that change with age, they are more susceptible to the disease when they are very young a very old. The population density allows for different spread rates to occur, the more people the faster it spreads. In the program there are two diseases, one with a much higher spread rate than the other, however if an individual is infected with one, it makes it substantially easier to become infected with the other. This is caused by the immune system being weakened from is fight against the current infection. There is also the possibility of a disease along the lines of the Spanish Flu, which attacks primarily young healthy adults. This is caused by the disease sending the immune system into an overload of sorts, causing the body to literally attack itself, this is a very fatal type of disease. As with most diseases, these can be overcome by certain individuals, even in combination. When someone survives a disease they become immune to it. The program represents two viral pathogens. This program takes records the deaths caused by the pathogens. If all the people left alive are immune the program stops. The program allows you to use one or both of the pathogens in a run. This will allow me to show the effects the diseases have when used individually as compared to when they are together. I will record the death toll and mortality rates of the pathogens. My goal is to represent a possible epidemic with realistic results. Pathogen #1 has a faster spread rate but a substantially smaller mortality rate, pathogen #2 is slower to spread but has a higher mortality rate. The pathogens also have different incubation times, #1 is a faster incubation time, while #2 is slower. This makes it to where when a person is infected with #2; they have a higher likely hood of dying than a person infected with #1, but it will take a bit longer in most cases for this too happen. The incubation time will also make it to where it takes longer for someone infected with #2 to become immune if they survive, then someone infected with #1. If a person fights off one pathogen while still infected with another, while the chance of death is lowered some, there is still a higher chance of death because they are still in a weakened state. I will run the program multiple times and record the mortality rates and number of deaths caused by infection to see if the values are similar for different runs. This will show accuracy in my program.


Team Members:

  Bryan Smith
  anthony cordova

Sponsoring Teacher: harry henderson

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