Bioscientists develop coinfection model to predict multipathogen epidemics

Bioscientists develop coinfection model to predict multipathogen epidemics

Diseases often pile on, coinfecting people, animals and other organisms that are already fighting an infection. In one of the first studies of its kind, bioscientists from Rice University and the University of Michigan have shown that interactions between pathogens in individual hosts can predict the severity of multipathogen epidemics. In lab experiments, scientists explored how the timing of bacterial and fungal infections in individual zooplankton impacted the severity of bacterial and fungal epidemics in zooplankton populations. The study, published this week in the Proceedings of the Royal Society B , showed that the order of infections in individual hosts can change the course of an epidemic. "It's well known that the way parasites and pathogens interact within hosts can alter disease transmission, but the question has been, 'What information do you need to gather about those interactions to be able to predict the severity of an epidemic?'" said corresponding author Patrick Clay, a University of Michigan postdoctoral associate who conducted the research during his Ph.D. studies at Rice. "What we showed is that you need to understand how infection order alters within-host interactions to be able to predict the severity of epidemics," he said. "We particularly need this information to predict how changes in the timing of an epidemic relative to co-occurring epidemics alters epidemic severity." The research does not apply to the coronavirus. "This applies to situations where multiple epidemics are simultaneously occurring and where the co-occurring pathogens interact within hosts," said study co-author Volker Rudolf, Clay's Ph.D. adviser at Rice. "There is no data to suggest that this is the case for COVID-2019." But coinfections are common in humans and wildlife populations, and because they are difficult to study, much is still unknown about how they alter epidemic dynamics, Rudolf said. Disease biology and epidemiology have historically focused on one-on-one interactions: one pathogen, one hos. However, scientists increasingly recognize that diseases don't exist in a vacuum. In reality, a diverse community of parasites and pathogens are out there, and they interact with each other. This study emphasizes a more holistic, almost community type of approach to studying infectious diseases." Volker Rudolf, professor of biosciences at Rice University The study combined experiments with epidemiology models and computer simulations. The zooplankton species used in the experiments, Daphnia dentifera, is a small crustacean that's both abundant and ecologically important in lakes across the U.S. Midwest. Zooplankton are also transparent, and Clay used a microscope to detect and monitor the growth of fungal and bacterial spores inside the animals. By altering the order of infection in test populations and examining thousands of individuals, he was able to document crucial differences in the way the pathogens interacted inside hosts. Related Stories



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