Prior to the emergence of COVID-19, there already was a movement to understand infectious disease emergence at the global scale. With the advent of the COVID-19 pandemic, this information has only become more relevant. The macroecology of infectious diseases is an important area of research with great promise for our ability to predict and prepare for epidemics while learning about the fundamentals of infectious diseases and how they influence our lives. But before really understanding what infectious disease macroecology is, it would be helpful to provide an overview of disease ecology and macroecology independently.
Disease ecology
As an ecologist, I am often met with surprise when I explain that I study infectious diseases. However, ecology can be generally defined as the study of the interactions between organisms and their environment, and infectious diseases are often just disorders caused by parasitic organisms. While most people might limit parasites to tapeworms or ticks, we broaden that category to any organism that requires a host to survive and inflicts harm on that host. This means that many viruses, bacteria, and fungi are considered parasites too. Disease ecology is the study of the interactions between organisms, their parasites, and the environment.
Macroecology
A term that might be even more elusive than disease ecology is macroecology. Even among ecologists, macroecology is difficult to define, and so it has been an objective of some to define it, but the motivations behind the subdiscipline are fairly clear. One of the major challenges of ecology has been the difficulty to develop any general laws of ecology; macroecology attempts to address this challenge. Because ecologists often study organisms in their natural habitats, we struggle to define the patterns that are consistent throughout all of life rather than the specific system we are studying. For instance, we now know that some spiders have a natural fear of other spiders (which is really cool to see!), but it can be difficult to generalize this kind of finding to that of other systems more broadly. To address this, ecologists have switched their thinking from focusing on particular systems to a broader perspective: a macroecological perspective. Because we have learned so much about individual systems we now have enough data available to create large-scale datasets that allow us to look for these broader patterns. For example, the latitudinal diversity gradient is a well-documented pattern of biodiversity where the number of different species is highest at the equator and decreases towards either pole. Studies that only focus at a single local scale cannot detect or explain this pattern, but a broader macroecological perspective has allowed for a deeper understanding of the factors driving it.
Macroecology of infectious diseases
In short, the macroecology of infectious diseases can be defined as the study of host-parasite interactions at large scales. Infectious disease macroecologists combine the methods and theories developed in both macroecology and disease ecology to find general principles that can be used to understand parasites globally. The types of questions that infectious disease macroecologists address include the global diversity of parasite species, risk factors associated with diseases spreading from animals to humans (zoonotic spillover), and whether a parasite is likely to infect one species or many different species. At UGA, scientists began the Macroecology of Infectious Disease Research Coordination Network in 2015 to answer these types of questions. Recently, much of this work has culminated into a special issue in the Royal Society's Philosophical Transactions B, an academic journal.
Why does it matter?
The macroecology of infectious diseases is important for our fundamental understanding of parasites and is vital for human health as well. This research provides a valuable tool – not only for understanding past epidemics but for helping us predict and prepare for future epidemics. Traditional disease ecology has been successful in understanding a lot about what is required for an epidemic to occur and how it will progress over time; however, these methods are not designed to predict when and where a new epidemic might occur. Macroecology takes advantage of the increasing volume of data related to infectious diseases and new methods for analyzing it in order to detect what types of factors can make populations at risk of zoonotic spillover.
For example, Garcia Pena et al. 2021 consider how different predictions for land-use change (i.e. altering natural land for human uses) will result in different levels of risk for zoonotic diseases from rodents (e.g. rats, mice, and squirrels) around the globe. The conversion of natural lands into crop lands is expected to increase zoonotic risk, and the authors find that low- and middle-income countries are at higher risk of harm compared to high-income countries that will have more resources to combat the threats of emerging infectious diseases.
In another study, Majewska et al. 2021 employ machine learning methods to study which predictors are the most important when considering the zoonotic spillover of helminths (parasitic worms) from wildlife to humans. They used a dataset of over 700 species of mammalian-infecting helminths and found that the ability to infect common companion animals, such as dogs and cats, is the most important predictor for spillover.
The macroecology of infectious diseases is not the answer to all our disease-related questions, but it has already taught us a lot about how parasites broadly operate. These and future findings will be essential as we adapt to COVID-19 and prepare for future outbreaks of infectious diseases.
About the Author
Daniel is a Ph.D. student in the Odum School of Ecology at the University of Georgia. He is interested in the relationship between host biodiversity and parasite transmission. Stemming from a background in freshwater ecology, Daniel often uses diverse communities of amphibians and their many pathogens as study systems.
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Daniel Suhhttps://athensscienceobserver.com/author/daniel-suh/March 24, 2022