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Over the past two decades, research on bat-associated microbes such as viruses, bacteria and fungi has dramatically increased. Here, we synthesize themes from a conference symposium focused on advances in the research of bats and their microbes, including physiological, immunological, ecological and epidemiological research that has improved our understanding of bat infection dynamics at multiple biological scales. We first present metrics for measuring individual bat responses to infection and challenges associated with using these metrics. We next discuss infection dynamics within bat populations of the same species, before introducing complexities that arise in multi-species communities of bats, humans and/or livestock. Finally, we outline critical gaps and opportunities for future interdisciplinary work on topics involving bats and their microbes. 

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’. 

Predicting and simplifying which pathogens may spill over from animals to humans is a major priority in infectious disease biology. Many efforts to determine which viruses are at risk of spillover use a subset of viral traits to find trait-based associations with spillover. We adapt a new method—phylofactorization—to identify not traits but lineages of viruses at risk of spilling over. Phylofactorization is used to partition the International Committee on Taxonomy of Viruses viral taxonomy based on non-human host range of viruses and whether there exists evidence the viruses have infected humans. We identify clades on a range of taxonomic levels with high or low propensities to spillover, thereby simplifying the classification of zoonotic potential of mammalian viruses. Phylofactorization by whether a virus is zoonotic yields many disjoint clades of viruses containing few to no representatives that have spilled over to humans. Phylofactorization by non-human host breadth yields several clades with significantly higher host breadth. We connect the phylogenetic factors above with life-histories of clades, revisit trait-based analyses, and illustrate how cladistic coarse-graining of zoonotic potential can refine trait-based analyses by illuminating clade-specific determinants of spillover risk.