Tool could forecast flu outbreaks weeks in advance

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A new tool could help forecast an influenza pandemic or outbreak of disease in the event of a bioterrorist attack, researchers report.

EpiFX, which researchers at the University of Melbourne and the Defence Science Technology Group developed, is already predicting the start and extent of the Australian winter influenza season, sometimes up to weeks in advance. In the event of a pandemic, it can also be used to identify an appropriate response.

The collaboration has drawn the attention of the US Government’s Department of Defense, which is now working with researchers to develop a new tool to identify the level of threat from a bioterrorism attack and recommend appropriate response options.

Tracing the spread of disease

James McCaw, professor of mathematical biology at the University of Melbourne, has been at the forefront of infectious diseases modeling since its early days in Australia about 12 years ago, and leads the EpiFX team.

flu modeling graph
An illustration of the July 2016 influenza forecast for Melbourne. (Credit: U. Melbourne)

“We have to start with what we know about these pathogens and how they might spread,” says McCaw, coauthor of a paper describing the team’s work on modeling influenza’s spread in the journal Infectious Disease Modelling.

“When an outbreak occurs, either naturally or through an act of bioterrorism, the forecasting tool provides the crucial link between scenario planning, which has been conducted in preparation for future events, and real-time data analysis,” says McCaw.

“That kicks in when people affected by the virus start to arrive at emergency departments, or when in a particular environment, such as a barracks, soldiers start displaying symptoms. Analysis of that data shows us how quickly a virus is spreading, and initiates an appropriate and proportionate response,” he says.

In extreme cases, this could mean recommending the closure of schools or shutting down public transport to minimize opportunities for a virus to spread.

“Better forecasting means we can use state or national resources more efficiently…”

Tony Lau, who leads DST Group’s epidemic detection and forecasting program, says the tool combines the concept of probability inference—which updates the probability of a hypothesis as more information becomes available—with susceptible, exposed, infected, and recovered (SEIR) compartmental disease models.

“This provides a mathematical framework for understanding the establishment and spread of infectious diseases,” he says.

This modeling can potentially predict how quickly an epidemic will spread, and identify those most at risk so preventive action can be taken through measures like targeted vaccination.

“In general, it is the young, the old, and the weak who are most at risk from viruses like influenza,” says Lau. “Better forecasting means we can use state or national resources more efficiently, with those people in mind.”

Advance warning

In Victoria, EpiFX has accurately predicted flu outbreaks up to five weeks in advance. Weekly forecasts of the incidence of flu are shared with the health sector to gain further insight into the influenza season and continue its refinement.

Despite early success, challenges remain.

The 2017 influenza season in Australia was severe, with an extreme case count recorded in many jurisdictions.

Rob Moss, mathematical biologist and EpiFX technical project lead, says the underlying causes for this increase are not yet understood but may stem in part from behavioral changes.

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“Our statistical tools are similar to those used to predict the weather, but we face the additional challenge of having to account for changes in human behaviors,” says Moss.

“Individuals may change their health seeking behavior based on media attention and general practitioners could have also changed their testing practices. We’ve only just started to scratch the surface in unpacking these complex interactions.”

The researchers are investigating highly contagious diseases and viruses like Ebola and influenza, as well as emerging diseases such as Zika, as part of the tool’s development.

“We are still developing and refining our forecasting, but in the event of a health emergency, we are in a better position to respond than we have ever been, as we improve our ability to integrate forecasting with our scenario analyses,” says McCaw.

This new tool researchers are working on with the US Government’s Department of Defense is a partnership among the DST Group, the University of Melbourne, and the University of Adelaide. Other countries including the United Kingdom, South Korea, and Singapore are interested in using the tool’s epidemic modeling capabilities.

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The collaborative work of the DST Group and the University of Melbourne receives ongoing assistance from, and engagement with, data custodians and public health staff, as well as the Victorian Department of Health and Human Service’s Health Protection Branch, Health Protection NSW, and the Queensland Department of Health’s Communicable Diseases Branch.

The researchers also thank the National Influenza Surveillance Committee (NISC), a sub-committee of the Communicable Diseases Network Australia, and the NISC Secretariat of the Australian Government Department of Health for their input to this project.

Source: University of Melbourne