Over the past few years, there has been a growing awareness of the dangers of foodborne illnesses and the need for better methods of early detection. A new study published in the journal PLOS ONE has found that a simple approach to early detection of foodborne illness could save lives and reduce the cost of medical care.

In the study, researchers developed a predictive model that uses data from foodborne illness outbreaks to identify regions of the United States that may be at an increased risk for foodborne illness. By focusing on areas with higher risk, health departments and other public health organizations can be better prepared to respond to foodborne illness outbreaks.

The results of the study suggest that early detection of foodborne illness is possible and can have a significant impact on public health. By targeting regions with an increased risk of foodborne illness, health departments can be better prepared to respond to outbreaks and reduce the cost of medical care.

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source: Phys.org