With the recent outbreak of Ebola hanging on the World's shoulders, we've found a lack of accessible prediction simulations. To address this, we've created a cross-platform web app to model the spread of disease.
Our MVP for the TechCrunch Distrupt EU Hackathon is a true-to-life simulation of Ebola infection. The magic of the product lies in the disease model, coded from scratch using differential equations, created by one of our team members currently doing his PhD. Our model considers people in one of four states: Susceptible, Exposed, Infected or Recovered. Together, these groups make up the population of a given country (S+E+I+R=Population). A person's state changes based on disease specific data of infectivity, incubation time and population density (amongst other data sets). Our model focuses on air-travel as a disease carrier across borders, taking real flight path data into account, including source city, source airport, flight time, destination airport and destination city - all of which have infectivity coefficients, population densities and time is spent in each area.
Our incredible model is brought to life by visualising how the disease spreads across the globe over time. Immersive interactivity is further achieved by allowing the user to manipulate the world conditions (such as health care conditions) to see the effect on disease spread. By showing the positive effect of these basic needs on disease spread, the user is encouraged to donate money to buy the same healthcare essentials they experimented with. This makes our product very investable by an organisation like Save the Children or the UN.
Our typical user is an interested professional who would casually like to know more about diseases and how they spread. A typical visit would be 10 minutes over lunch, playing with the simulation and parameters to understand the disease while feeling a sense of control over it - ending in a donation with a real-life impact.