A scientist has visualised which countries are most susceptible to an Ebola outbreak using Wolfram technologies.
Although the Wolfram-based computer model is conceptual, it could help policy-makers put effective measures in place to slow the virus' spread, Dr Marco Thiel from Aberdeen University, said.
Thiel combined publicly available data including population and population density, which is built into Wolfram Mathematica's databases, with transport networks to calculate which countries are most at risk of an Ebola outbreak.
Thiel was able to represent the airport where the first outbreak occurred, a layer around this representing all the airports that could be reached with one connection flight - and the next to be infected.
"This shows that the structure of the network, rather than geographical distance, is important," he said.
Flight connection patterns reveal that some European countries are more susceptible than others because of their flight paths, the model revealed.
He said: "Certain countries in Europe, such as Germany, UK, France etc. are more at risk than others because of their flight connections."
While the US has taken drastic measures in comparison to Europe in terms of Ebola screening, it may not be the next in line for an outbreak, Thiel's model showed.
He said: "The US would be less at risk than the European countries, that is, it would get significant numbers of infected later. All of that seems to be qualitatively quite correct. Australia and Greenland would get the disease very late, or not at all, again in agreement with our model."
"The model shows that the highest probability of spreading is between neighbouring African countries, which is what larger models predict as well."
The probability of infection, the rate of recovery and the factor of migration all had to be considered to make the model as accurate as possible. These parameters are all dependant on trends like local behaviour of people, health education, health insurance and the wealth of a population in relation to how often they travel.
However, Thiel warned that the model is only conceptual, and therefore the results are not definitive.
He said: "The conceptual nature of the model allows us to look at different scenarios: What if infection rate versus recovery rate changes? What if there is more mobility? What if we also use local transport? We did not try to fit the parameters or network to optimally describe the Ebola outbreak; rather, we provide the basic model to develop several scenarios and to understand the basic ingredients for this type of modelling."
Along with virus patterns like Ebola, construction machinery, chemical battery and bio-chemical systems for industry can be modelled more easily with Wolfram's latest software update. SystemModeler was launched in July this year.
This story, "Computer Model Predicts Where Ebola is Most Likely to Hit Next" was originally published by Techworld.com.