A pair of Los Alamos National Laboratory researchers have developed a new mathematical tool that may help health experts and crisis managers know if 'Bird Flu', or avian influenza H5N1, may spread globally or not.
Luís Bettencourt and Ruy Ribeiro of Los Alamos' Theoretical Division have come up with a novel approach to see subtle changes in epidemiological data to gain insight into whether bird flu can turn into a deadly global pandemic.
"What we wanted to create was a mathematically rigorous way to account for changes in transmissibility. We now have a tool that will tell us in the very short term what is happening based on anomaly detection. What this method won't tell you is what's going to happen five years from now," said Bettencourt.
The duo started their study three years ago when the world was wondering whether avian influenza H5N1, with its relatively high human mortality rate, could become a frightening new pandemic, an many experts fearing if the virus could evolve into a form that would become transmissible from human to human.
The researchers wanted to create a "smart methodology" to look at changes in disease transmissibility, and for this, they developed an extension of standard epidemiological models that describes the probability of disease spread among a given population.
Then the model considered actual disease surveillance data gathered by health experts like the World Health Organization and looked for anomalies in the expected transmission rate versus the actual one. And thus, the model provides health experts actual transmission probabilities for the disease, based on this information.
Unlike other statistical models that require huge amounts of data for accuracy, the Los Alamos tool works on very small populations such as a handful of infected people in a remote village.
When they developed their Bayesian estimation of epidemic potential, Bettencourt went back and looked at actual epidemiological surveillance data collected during Bird Flu outbreaks in certain parts of the world. He found that their model accurately portrayed actual transmission scenarios, lending confidence to its methodology.
Besides its utility in understanding the transmissibility of emerging diseases, the new method is beneficial as it enables public health experts to study outbreaks of more common ailments such as seasonal influenza early on.
This may also help medical professionals in making better estimates of potential morbidity and mortality, along with assessments of intervention strategies and resource allocations that can help a population better cope with a developing seasonal outbreak.
The study is published recently in the Public Library of Science.