Smithsonian scientists propose a new approach to modeling infectious diseases that 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, according to a news release from the Smithsonian.
In the midst of a devastating global pandemic of wildlife origin and with future spillovers imminent as humans continue to come into closer contact with wildlife, infectious-disease models that consider the full ecological and anthropological contexts of disease transmission are critical to the health of all life. Existing models are limited in their ability to predict disease emergence, since they rarely consider the dynamics of the hosts and ecosystems from which pandemics emerge.
In a report in Nature Ecology and Evolution, Smithsonian scientists and partners provide a framework for a new approach to modeling infectious diseases. 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, which cause about 75% of infectious diseases affecting human health. Predicting where, how, and when people and animals are at risk from emerging pathogens — and the best ways to manage this — remains a significant challenge. Risks for spillover include, but are not limited to, habitat encroachment, illegal wildlife trade and bush meat consumption.
Despite advances in the understanding of how infectious diseases are transmitted, the models these efforts are based on are relatively limited in scope, focusing on specific pathogens and often overlooking how pathogens interact within their hosts. While scientists and global health organizations are putting a lot of effort into studying the diversity of disease-causing organisms, existing models do not link this diversity to their roles within ecosystems.
Researchers say this new model will require expertise and collaboration across fields such as veterinary and human medicine, disease ecology, biodiversity conservation, biotechnology and anthropology.
General ecosystem models are essentially complex models that can predict how food chains are assembled — the processes of energy transfer between plants and animals are what structure ecosystems — and determine the plants and animals that compose an ecosystem. With the new version, general “episystem” models, the paper’s authors outline a framework for integrating disease agents (including parasites, viruses and bacteria) into these models. By identifying general rules for how food chains that include disease entities are structured, it should be possible to predict the types of pathogens that are present in any given ecosystem.
This would allow scientists to better understand the characteristics of an ecosystem (such as disturbance) that would make it more likely to contain zoonotic pathogens, predict the threat it poses to people who interact with this ecosystem and even permit computer simulation and testing of interventions aimed at reducing these threats.
While the amount of data that would be required to create these models is daunting, long-term studies of intact ecosystems where parasite data has been collected are excellent places to initiate these studies. Efforts to refine them more broadly could then leverage large-scale ecological studies that span continents such as the Smithsonian’s ForestGEO and MarineGEO programs.
