Listeria is the third-leading cause of death among bacterial foodborne pathogens in the U.S. and pregnant individuals bear a disproportionate share of that burden. Yet the scientific models used to set food safety policy have rarely been designed with pregnant people specifically in mind. A new study to be published in Risk Analysis aims to change that.
Each year, approximately 1,250 Americans contract listeriosis, the illness caused by Listeria monocytogenes. The disease carries a staggering 86% hospitalization rate and is fatal in approximately 14% of cases. For pregnant individuals, the stakes are even higher: pregnancy-associated cases account for 14% of all listeriosis cases, and when listeria reaches the fetus, it causes stillbirth in 25% of those infections. Many pregnant individuals experience only mild, flu-like symptoms, or none at all, while the bacterium silently crosses the placenta. Recent outbreaks in 2021-2023 linked to ice cream, queso fresco, and enoki mushrooms resulted in five stillbirths in just three years.
Researchers Tyler Stump, Carly Gomez, Ph.D. and Jade Mitchell, Ph.D. of Michigan State University set out to fill this gap. By analyzing animal studies that tracked how pregnant hosts respond to specific doses of L. monocytogenes, the team developed new biologically plausible dose-response models – one for maternal infection and one for stillbirth – built on data from guinea pigs and gerbils, which share key biological traits with humans relevant to listeria pathogenesis.
The study found that fetal brain infection is a more precise and reliable indicator of stillbirth risk than direct stillbirth outcomes alone. Fetal brain infection was present in every observed stillbirth and absent in all non-stillbirth cases, making it a verifiable surrogate endpoint that significantly strengthened the model’s accuracy. By pooling this data with other stillbirth datasets, the researchers produced a better-fitting model than any previously available.
Public health agencies should use population-specific models like these when developing food safety guidance rather than applying generic population estimates. As listeria outbreaks continue to occur, having more precise risk assessment tools will support more informed and protective food safety policies.”
Jade Mitchell, Ph.D., Professor, Department of Biosystems and Agricultural Engineering, Michigan State University
The authors caution that pregnancy involves a unique combination of physiological, behavioral, and clinical variables that cannot be captured by applying general immunocompromised population models. Their work calls on public health agencies to use population-specific models when developing food safety guidelines for sensitive groups.
FDA guidance recommends that pregnant individuals avoid high-risk foods including unpasteurized cheeses, raw sprouts, deli meats, hot dogs, and smoked seafood unless heated thoroughly. Listeria is unusual among foodborne pathogens because it can grow even under refrigeration, making careful food handling particularly important. Symptoms of listeriosis such as fever, muscle aches, nausea, and diarrhea may appear anywhere from one day to several weeks after exposure.
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