Pandemics -- the spread of disease through large populations rapidly -- is something that has affected our world at various points for as long as humans have been around, and something that remains an ever-present threat despite increases in medical sciences and research. One of the biggest issue with pandemics is how rapidly they can be transmitted over large populations, and to help envision this issue to, ultimately, serve as an aid in neutralizing transmission, researchers have made a model breakthrough demonstrated through a simulation.
In a paper published in the journal Science today, theoretical physicist Dirk Brockman and co-author Dirk Hebling report on the model breakthrough and how it came about, as well as the mapping simulation they created using it, which you can see in both the image above and video below. Like all great breakthroughs, the notion came from a simple, unassuming comment by one of his students, Daniel Grady.
Grady had made a rather innocent comment that regardless of what method he used to travel to school -- by bicycle, subway, or bus -- it always ended up taking just as long to arrive. Such spawned an idea in the physicist, one that led him and his team of researchers to a new model that takes into account the changes in how pandemics spread in modern times -- something substantially different than in the past, when countries were more or less isolated from each other.
Because of how the world is connected, a plain geographical distance is less relevant when it comes to the spreading of contagions. Airplanes are obviously the quickest way by which a pandemic could spread across a nation and across the globe. Using what is referred to as effective distance, the researchers poured over three years of data from airlines to map the way distances interact with each other, ultimately seeking to find a common denominator, so to speak, that brings it all together.
As the report shows, Brockmann and his team finally made this breakthrough, coming up with a model by which simplistic wave patterns based upon effective distances can be used to predict a sort of global network for the spreading of pandemics. This is further substantiated by comparing it to recent pandemic spreads, such as SARS and the flu, in which the researchers demonstrate a correlation.
VIA: Fast Coexist