A new model accurately predicted past-year infections with cholera-causing bacteria based on antibodies in a few drops of blood, researchers recently reported in Science Translational Medicine. The approach could be used to improve cholera incidence estimates, which are currently based on surveillance of acute watery diarrhea.
Globally, more than 100 000 people die of cholera each year. The World Health Organization aims to eliminate the disease as a public health threat by 2030, but counts of true cholera cases are needed to allocate limited resources, track progress in reducing cholera transmission, and assess the effectiveness of new interventions, according to Andrew Azman, PhD, of the Johns Hopkins Bloomberg School of Public Health in Baltimore, the study’s lead author.
Abbasi J. Better Cholera Counts Through Machine Learning Models. JAMA. 2019;321(14):1343. doi:10.1001/jama.2019.3459
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