Researchers have developed a new real-time strategy that could help combat future outbreaks of foot-and-mouth disease (FMD) quickly, efficiently, and early on—when authorities have minimal information.
“It is crucial for policymakers to employ surveillance to resolve uncertainty in how the disease is spreading…”
Researchers from the University of Warwick discovered that the most effective policies for the start of a FMD outbreak, even when we know very little about it, focus on surveillance and vaccination.
Determining the optimal strategy to control FMD can be challenging in the first weeks of an epidemic, due to uncertainty about the nature of the outbreak and how the disease will be spread.
The researchers sought to resolve this uncertainty, enabling the spread of the disease to be controlled more rapidly and effectively than in the past.
Using data from previous FMD outbreaks—the UK in 2001 and Japan in 2010—they simulated the spread of disease, and at each stage of the outbreak analyzed the real-time efficacy of multiple different approaches.
These methods included:
- Culling only infected farms
- Culling infected farms, plus farms designated as dangerous contact
- Culling infected farms, dangerous contact farms and neighboring farms (contiguous culling)
- Ring culling at 3 kilometers (just under 2 miles), and at 10 kilometers (just over 6 miles)
- Vaccination at 3 kilometers (just under 2 miles), and at 10 kilometers (just over 6 miles)
Researchers found that, at every stage in an outbreak, regardless of the uncertainty in case reporting, local targeted approaches (culling of infected premises and ring vaccination around confirmed infected farms) were always the most effective.
On the other hand, ring culling was never an effective method. The researchers conclude that, owing to the spatial uncertainty in model predictions during the early stages of an epidemic, targeted surveillance is crucial to allow authorities to gain information and resolve uncertainty as quickly as possible, ultimately better controlling the spread of the disease earlier in an outbreak.
“This work highlights both the limitations and the benefits of using an infectious disease model in real time, during an ongoing outbreak,” says Michael Tildesley, an associate professor in the School of Life Sciences and Mathematics Institute.
“It is crucial for policymakers to employ surveillance to resolve uncertainty in how the disease is spreading as rapidly as possible, as this may have significant implications upon our ability to predict future epidemic behavior.”
Most mathematical models developed for disease control look back to previous outbreaks and make their calculations using all the information from the whole episode—this new strategy is rare in that it works out the best approach with only the information to hand in the middle of an outbreak.
The research appears in the journal Astrobiology.
Source: University of Warwick