Automated biosurveillance is promising in terms of both improving public health response to natural disease outbreaks and minimizing potential casualties from the utilization of biological weapons.
This report discusses the public health capabilities necessarry to respond to biological incidents.
An unknown outbreak of the Zika virus swept across Cuba in 2017, a year after the global health emergency was declared over.
Projecting the risk of Nipah virus outbreaks in humans requires identification of reservoir animals along with Nipah virus dynamics within those animals, while machine learning can be the first step to understanding the mechanisms underpinning epidemiologically important cross-species contacts.
A nationwide Biosurveillance Pilot Program has been launched in Canada to track the epidemiology of equine respiratory pathogens and support equine clinics with response.
Researchers with Texas A&M University recently conducted a trial using electronic accelerometers attached to the legs of 364 high-risk feedyard calves in four research blocks. At the same time, trained animal-health-care personnel regularly observed the calves and recorded clinical illness scores and depression scores as indicators of bovine respiratory disease (BRD).
A new computational method called 'CATCH' designs molecular 'baits' for any virus known to infect humans and all their known strains. The approach can help small sequencing centers around the globe conduct disease surveillance, which is crucial for controlling outbreaks.
Researchers documented the losses associated with 137 pathogens and pests in five major food crops—wheat, rice, maize, potato and soybean—worldwide.
The deadly Marburg virus kills nine in 10. Experts know it starts in bats, they know when it spreads to humans it’s lethal, but they don’t know what happens in between.
During the two-week training course, vets, forest rangers and wildlife specialists trapped more than 30 bats for laboratory analysis in the jungles of Njala, central Sierra Leone.