Role Of Long-Distance Travel In Epidemics Examined

Chuck Bednar for redOrbit.com – Your Universe Online
While the current spread of Ebola from West Africa into other parts of the world demonstrates how quickly diseases can spread in the age of high-speed jet travel, new research from the University of California, Berkeley set out to better understand how computer models can be used to predict the spread of potential epidemics.
In the study, assistant physics professor Oskar Hallatschek and his colleagues used a simple model of disease to prove that, despite commonly held assumptions, most simulations take for granted that outbreaks quickly morph into epidemics once disease carriers such as humans are able to “jump” outside of the initially-infected area.
Instead, he and co-author Daniel Fisher of Stanford University found that if the chance of long-distance dispersal is low enough, the disease spreads far more slowly, like a wave rippling outward from the initial outbreak. This type of spread was common centuries ago, when humans rarely traveled, the university explained in a statement Tuesday.

However, if the chance of jumping passes a certain threshold (as is often the case with today’s air travel), then diseases can generate enough satellite outbreaks to cause a far-quicker spread of the disease. They also found that the chances of a disease spreading rapidly increases as people are able to travel internationally more easily.
“With our simple model, we clearly show that one of the key factors that controls the spread of infection is how common long-range jumps are in the dispersal of a disease,” explained Hallatschek, who is the William H. McAdams Chair in physics at UC Berkeley. “And what matters most are the rare cases of extremely long jumps, the individuals who take plane trips to distant places and potentially spread the disease.”
The study, which appeared in last week’s online early edition of Proceedings of the National Academy of Sciences (PNAS), provides a new understanding of disease transmission that could ultimately help epidemiologists better predict how epidemics originate, as well as how cancer metastases, genes mutate, species invade, wildfires spread and even how rumors spread in this day and age.
Robert Sanders of UC Berkeley Media Relations said that Hallatschek usually studies mutations spread in colonies of microbes, and then mathematically models that activity to better understand how new traits evolve in a population. While reviewing simple theories of epidemic spread, he was reportedly shocked to find out that nobody could explain how the long-distance dispersal of individuals during an outbreak impacts the spread of the disease.
According to simulations, if the chance of people traveling away from the center of an outbreak is exponentially reduced with distance (i.e. the likelihood of distant travel drops by 50 percent every 10 miles) the disease spreads like a slow wave. The models also suggested that a slower reduction rate (for instance, if the chance of distant travel decreases by half every time the distance is doubled) could cause the disease to quickly spiral out of control.
Hallatschek said that he was “shocked to see that this had not been demonstrated,” and that he and Fisher “saw a chance to prove something really fundamental.” While the simple model they used did not account for the complexity of real-world conditions, it did contain the essential ingredients required to predict evolutionary spread, the university said. More importantly, it could be captured using a mathematical formula.

Image Above: When long-distance travel is rare, epidemics spread like a slow, rippling wave, as demonstrated by the simulation (left) and the actual historical spread of the black death during the Middle Ages. Credit: Oskar Hallatschek and D. Sherman and J. Salisbury
In all, Hallatschek and Fisher discovered three types of epidemic situations involving these so-called power-law distributions: one in which long-range travel is very rare, causing epidemics to spread in a slow wave (such as the Black Death); another in which long-range travel is common, causing disease to spread very rapidly (such as SARS); and third, intermediate scenario in which satellite outbreaks occur, but far more slowly than SARS-like cases.
“Hallatschek said that previous studies failed to take into account the randomness of jumps, which led people to think that any long-range jump would lead to new outbreaks and rapid spread,” the university noted. “But if long-range jumps are extremely rare, distant outbreaks tend to be overtaken by the slow, wavelike spread of the initial outbreak before they can contribute much to the overall epidemic.”
“In the future, he plans to make his model more and more realistic, first by incorporating networks to mimic the real world where people do not jump randomly, but must travel through airport hubs or train stations,” Sanders added. “Hallatschek also hopes to test his model by using data on the evolving genome sequences of pathogens as they spread, which provide one measure of where and when satellite outbreaks occur.”
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