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Ageing is associated with profound changes in behaviour that could influence exposure and susceptibility to infectious disease. As well as determining emergent patterns of infection across individuals of different ages, behavioural ageing could interact with, confound, or counteract age-related changes in other traits. Here, we examine how behavioural ageing can manifest and influence patterns of infection in wild animals. We discuss a range of age-related changes that involve interactions between behaviour and components of exposure and susceptibility to infection, including social ageing and immunosenescence, acquisition of novel parasites with age, changes in spatial behaviours, and age-related hygiene and sickness behaviours. Overall, most behavioural changes are expected to result in a reduced exposure rate, but there is relatively little evidence for this phenomenon, emerging largely from a rarity of explicit tests of exposure changes over the lifespan. This review offers a framework for understanding how ageing, behaviour, immunity, and infection interact, providing a series of hypotheses and testable predictions to improve our understanding of health in ageing societies. 

Animal sociality emerges from individual decisions on how to balance the costs and benefits of being sociable. Novel pathogens introduced into wildlife populations should increase the costs of sociality, selecting against gregariousness. Using an individual-based model that captures essential features of pathogen transmission among social hosts, we show how novel pathogen introduction provokes the rapid evolutionary emergence and coexistence of distinct social movement strategies. These strategies differ in how they trade the benefits of social information against the risk of infection. Overall, pathogen-risk-adapted populations move more and have fewer associations with other individuals than their pathogen-risk-naive ancestors, reducing disease spread. Host evolution to be less social can be sufficient to cause a pathogen to be eliminated from a population, which is followed by a rapid recovery in social tendency. Our conceptual model is broadly applicable to a wide range of potential host–pathogen introductions and offers initial predictions for the eco-evolutionary consequences of wildlife pathogen spillover scenarios and a template for the development of theory in the ecology and evolution of animals’ movement decisions. 

ABSTRACT. Arboviruses receive heightened research attention during major outbreaks or when they cause unusual or severe clinical disease, but they are otherwise undercharacterized. Global change is also accelerating the emergence and spread of arboviral diseases, leading to time-sensitive questions about potential interactions between viruses and novel vectors. Vector competence experiments help determine the susceptibility of certain arthropods to a given arbovirus, but these experiments are often conducted in real time during outbreaks, rather than with preparedness in mind. We conducted a systematic review of reported mosquito–arbovirus competence experiments, screening 570 abstracts to arrive at 265 studies testing in vivo arboviral competence. We found that more than 90% of potential mosquito–virus combinations are untested in experimental settings and that entire regions and their corresponding vectors and viruses are undersampled. These knowledge gaps stymie outbreak response and limit attempts to both build and validate predictive models of the vector–virus network. 

Abstract The growing threat of vector-borne diseases, highlighted by recent epidemics, has prompted increased focus on the fundamental biology of vector-virus interactions. To this end, experiments are often the most reliable way to measure vector competence (the potential for arthropod vectors to transmit certain pathogens). Data from these experiments are critical to understand outbreak risk, but – despite having been collected and reported for a large range of vector-pathogen combinations – terminology is inconsistent, records are scattered across studies, and the accompanying publications often share data with insufficient detail for reuse or synthesis. Here, we present a minimum data and metadata standard for reporting the results of vector competence experiments. Our reporting checklist strikes a balance between completeness and labor-intensiveness, with the goal of making these important experimental data easier to find and reuse in the future, without much added effort for the scientists generating the data. To illustrate the standard, we provide an example that reproduces results from a study ofAedes aegyptivector competence for Zika virus. 

Abstract The fields of viral ecology and evolution are rapidly expanding, motivated in part by concerns around emerging zoonoses. One consequence is the proliferation of host–virus association data, which underpin viral macroecology and zoonotic risk prediction but remain fragmented across numerous data portals. In the present article, we propose that synthesis of host–virus data is a central challenge to characterize the global virome and develop foundational theory in viral ecology. To illustrate this, we build an open database of mammal host–virus associations that reconciles four published data sets. We show that this offers a substantially richer view of the known virome than any individual source data set but also that databases such as these risk becoming out of date as viral discovery accelerates. We argue for a shift in practice toward the development, incremental updating, and use of synthetic data sets in viral ecology, to improve replicability and facilitate work to predict the structure and dynamics of the global virome.