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At the time of writing this chapter, the world was facing the COVID-19 pandemic. In response to the immense scale and impact of the pandemic, researchers from all fields were being drawn to the issue and were applying their own techniques for dealing with complex systems in efforts to understand and suppress the disease. Neuroscientists, for example, were applying models that have been used to map the brain, one of the most complex systems we know of, to the pandemic (Friston et ah, 2020). Artificial intelligence was also being applied for the purposes of tracking and prediction, diagnosis and prognosis, and the development of treatments and vaccines (Naude, 2020). Interesting is the impact of social media, both in the rapid spread of (mis)information (the so-called infodemic) and its ability to help track the spread of the disease (Eysenbach, 2009; Cinelli et ah, 2020). Due to the scale of the pandemic, enormous amounts of data are available, and attempts to make sense of this data were ongoing on various fronts (Latif et ah, 2020). Indeed, entire journals were being created to collect the unprecedented amounts of new research.

How the lessons learned from the massive investment to understand the COVID- 19 pandemic will influence or advance the use of complexity theory in One Health cannot be forecast at the time of writing this chapter, but we hope that we have shown a place for complexity in conceiving, communicating, planning, and implementing One Health research and action. This chapter has not exhaustively reviewed and presented all potential avenues for complex systems thinking in One Health. Instead, we hope that the ideas and examples presented herein motivate readers to learn more about how to match the way we study One Health systems to the ways they exist in nature as complex, messy sets of dynamic interactions.


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