The potential health benefits to species, communities and environments are enormous

In the midst of a devastating global wildlife pandemic and with impacts imminent as humans continue to come in closer contact with wildlife, infectious disease models that take into account the full ecological and anthropological context of disease transmission are vital to the health of all life. Existing models are limited in their ability to predict the occurrence of disease because they rarely take into account the dynamics of the hosts and ecosystems that give rise to pandemics.

Posted on May 17th in Natural ecology and evolution Smithsonian scientists and partners provide a framework for a new approach to infectious disease modeling. It adapts established methods developed to study the planet’s natural systems, including climate change, ocean circulation, and forest growth, and applies them to parasites and pathogens that cause disease.

Increased human-animal interactions lead to the emergence and spread of zoonotic pathogens that cause around 75% of infectious diseases that affect human health. Predicting where, how and when humans and animals are at risk from emerging pathogens – and how this can best be managed – remains a major challenge. Risks to spillover include interfering with habitats, illegal wildlife trade and consumption of bush meat.

Despite incredible advances in understanding how infectious disease is transmitted, the models on which these efforts are based are relatively limited, focused on specific pathogens, and often overlooked how pathogens interact in their hosts. While scientists and global health organizations go to great lengths to study the diversity of disease-causing organisms, existing models do not link this diversity to their role within ecosystems.

“Just as a mechanic needs to understand how the components of a car interact and how it was designed to improve performance, so must our ability to model infectious diseases,” said lead author Dr. James Hassell, veterinarian, epidemiologist and Keller Skorton family scholar for the Smithsonian Conservation Biology Institute (SCBI) Global Health Program. “Applying systems-level thinking to predict the occurrence of disease requires a fundamental change in the way infectious disease is conceptualized. This presents significant challenges, but in this article we explain why they are not insurmountable. When you weigh the cost of prevention and remediation, investing in our shared global health, especially the links between nature and human health, is crucial. ”

Researchers say this new model will require expertise and collaboration in areas such as veterinary and human medicine, disease ecology, biodiversity conservation, biotechnology, and anthropology.

“Disease and health are largely viewed as a human construct, and the role the environment plays in disease is often overlooked,” said Yvonne-Marie Linton, research director, Walter Reed Biosystematics Unit, Smithsonian National Museum of Natural History and Walter Reed Army Research Institute. “The health of other organisms, from parasites and insects to birds and aquatic organisms, can alter the structure of ecosystems. What we are proposing is a new approach to modeling infectious diseases circulating in nature that would allow scientists to better simulate the behavior of these pathogens in wildlife populations, how they react to human activity, and the risk they pose to humans determine. ”

General ecosystem models are essentially complex models that can predict how food chains are composed – the processes of energy transfer between plants and animals structure ecosystems – and determine the plants and animals that make up an ecosystem. With the new version, general “episystem” models, the authors of the paper outline a framework for the integration of pathogens (including parasites, viruses and bacteria) into these models. By identifying general rules for the structure of food chains containing disease entities, it should be possible to predict the types of pathogens that are present in a given ecosystem. This would allow scientists to better understand the characteristics of an ecosystem (e.g. disturbances) that would make it more likely to contain zoonotic pathogens, predict the threat to humans who interact with that ecosystem, and even computer simulations and tests of enable targeted interventions in reducing these threats.

While the amount of data that would be required to build these models is daunting, long-term studies of intact ecosystems from which parasite data has been collected are excellent places to initiate these studies. Efforts to refine it further could then leverage large-scale environmental studies that span continents such as Smithsonian’s ForestGEO and MarineGEO programs.

The potential impact of this new model goes beyond reducing the human interface for disease spread to economics. “With this new approach, not only can you study human diseases, but also the best way to conduct aquaculture or raise healthy animals,” said Katrina M. Pagenkopp Lohan, marine disease ecologist at the Smithsonian Environmental Research Center. “When you reintroduce a species into the wild, what does that ecosystem have to be like for you to be successful? We could actually model that. It’s amazing. ”

The cost of such a new approach is substantial, according to researchers, and will require the collaboration and commitment of scientists, communities, non-governmental organizations and nations around the world. In an age of big data and massive technological advances, such an approach is achievable, but requires improved data collection, sharing, and testing on a much larger scale than is currently the case.


The co-authors of the paper are Hassell, Global Health Program, SCBI and Department of Microbial Disease Epidemiology, Yale School of Public Health; Tim Newbold, Center for Biodiversity and Environmental Research, Department of Genetics, Evolution and Environment, University College London; Andrew P. Dobson, Department of Ecology and Evolutionary Biology, Princeton University and Santa Fe Institute; Linton, Doctor of Zoology, Walter Reed Biosystematics Unit, Smithsonian Museum Support Center, Department of Entomology, Smithsonian National Museum of Natural History, and Walter Reed Army Institute of Research; Lydia HV Franklinos, Center for Biodiversity and Environmental Research, Department of Genetics, Evolution and Environment, University College London; Dr. Dawn Zimmerman, Veterinarian, Global Health Program, SCBI and Department of Microbial Disease Epidemiology, Yale School of Public Health; and Pagenkopp Lohan, PhD in Marine Science, Marine Disease Ecology Laboratory, Smithsonian Environmental Research Center.

https: //.National /News/New infectious disease model could better predict future pandemics


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