Philosophical Transactions of the Royal Society B: Biological Sciences

Cooperation is foundational to complex sociality, yet presents profound evolutionary dilemmas - costs and benefits are rarely distributed evenly and the decision to collaborate or defect can involve a complex contextual calculus. These challenges are compounded when cooperation scales from pairs to groups. Group-level cooperation is fundamental to many species success, but how is it sustained and regulated in nature? One promising route to addressing this question is to examine how individuals reorganise their affiliative interactions in anticipation of group-level cooperation. We examine such pre-cooperative reorganisation using long-term data (2013-2018) from three neighbouring groups of wild chimpanzees at the Tai National Park, Cote dIvoire, who routinely cooperate as a collective to defend their territory against other groups. We found that chimpanzees adjusted the distribution of their social contacts in anticipation of risky and proactive territorial defence by forming more broadly connected, yet more diffuse, affiliative networks. Specifically, adult chimpanzees groomed and played with more group members on days of proactive territorial defence, and this pattern was temporally-sensitive, with increased affiliation occurring before, rather than after, the cooperative act. Chimpanzees accessed a broader range of partners through increased interaction efficiency by switching between more partners with shorter interactions per partner. This pattern suggests a shared evolutionary basis of dynamic social readjustment in preparation for group-level social dilemmas in hominids, potentially providing the foundation for the formalized systems of affiliation found in human societies.

Recent evidence of extensive call sequence use in non-human primates has led to the theory that syntax evolved to mitigate the constraints of their genetically fixed repertoires, before vocal production learning later emerged in humans. However, evidence of similarly extensive sequence repertoires in an open-ended vocal production learner--the Western Australian magpie (Gymnorhina tibicen dorsalis)--offers a unique opportunity to explore potential alternative pathways to syntactic communication. Our previous work revealed fledgling magpies learn group-specific repertoires of structured call sequences from their social contacts, with more sociable individuals acquiring larger repertoires earlier in development. Notably however, the individual vocal segments that combine to form their calls and call sequences were shared across groups and emerged as early as the first week post-fledging--suggesting the underlying vocal elements may not be learned. Here we utilised acoustic neighbourhood-based dimensionality reduction to compare clustering patterns of vocal segments across magpie fledgling developmental stages, and between fledglings and adults. We found no evidence of acoustic development over time, and no significant distinction between fledgling and adult productions of the same vocal segments. The same coarticulatory effects--where a vocal element is produced differently when combined with another--and geographic variation established previously in adults were supported in fledglings too. These findings support that the vocal building blocks underpinning magpie call sequences are innate, suggesting usage learning better explains how fledglings learn to combine calls. In a species capable of open-ended production learning, this suggests learning to combine existing signals may be more adaptive than productively learning new ones. Rather than evolving solely to compensate for genetically fixed repertoires, syntax may have evolved as a flexible, convergent solution to the various challenges of expanding communicative capacity--whether due to genetic constraints, cognitive limitations or the cost of establishing new meaning in novel signals.

Our biosphere exhibits remarkable diversity yet is constrained by universal organizational principles, including molecular homochirality. Advances in synthetic biology have raised the possibility of engineering alternative life forms based on mirror-image biomolecules, prompting both technological interest and biosecurity concerns. While current discussions of mirror life largely emphasize molecular feasibility and cellular function, its potential establishment in natural environments remains poorly understood. Here, we develop a theoretical framework to assess the invasion potential of mirror organisms within existing ecosystems. Using population-level models that incorporate resource competition, metabolic constraints, and ecological network interactions, we show that mirror life faces severe limitations arising from both nutrient incompatibility and competitive exclusion by established biota. In particular, the reliance on rare or achiral substrates and the asymmetry of interactions with natural organisms constrain growth and persistence across a broad range of ecological conditions. These results indicate that, beyond engineering challenges, the structure and dynamics of the biosphere itself act as a strong barrier to the spread of mirror life. We conclude that the widespread establishment of mirror organisms in the extant biosphere is highly unlikely, highlighting the importance of ecological constraints in evaluating the risks and feasibility of synthetic life.

Aims: Antimicrobial peptide (AMP) combinations have been proposed to delay resistance evolution, but it remains unclear what properties of a peptide pair determine whether a combination reduces resistance evolution relative to its component AMPs used alone. One suggested factor is mode of action, yet this has rarely been tested experimentally. In the current study we have asked whether mode of action or physicochemical similarity between peptides better predicts which combinations delay resistance. Methods: We evolved Staphylococcus aureus with six AMPs with reported membrane-targeting and intracellular-targeting activity, individually and in all 15 pairwise combinations. We quantified resistance evolution, cross-resistance and fitness costs across the full AMP panel, and performed whole-genome sequencing on 126 evolved lineages. Results: Resistance varied across AMPs and correlated with peptide chain length, not mode of action. Cross-resistance was associated with physicochemical similarity, and similar peptides selected for overlapping mutations. Most combinations reduced resistance relative to single-AMP treatment, but those whose components shared cross-resistance were less effective, channeling evolution into convergent trajectories that resolve both selective pressures at once. Notably, mode of action did not predict combination outcome. Conclusions: Cross-resistance, not mode of action, is a key factor in determining AMP combination efficacy. Physicochemical distance between peptides may serve as a practical predictor for cross-resistance, enabling selection of AMP combinations that are more likely to constrain resistance evolution.

Acoustic interference is a critical factor driving the evolution of communication systems. In mixed-species aggregations, competition for acoustic space is expected to drive signal differentiation among heterospecifics. The acoustic space partitioning hypothesis proposes that species differentiate their signals to reduce overlap and thereby acoustic interference. Despite ongoing debates in niche theory, studies in animal communication have remained disconnected from these conversations, and no critical evaluation of this hypothesis has been conducted. We performed a systematic review to assess empirical support for acoustic space partitioning and evaluate the conceptual and methodological approaches used to test it. We found that two-thirds of studies conclude that the acoustic space is partitioned, albeit with a strong taxonomic bias toward anurans. However, studies rarely account for key assumptions of the hypothesis, including cosignaling, limited acoustic space, and masking of the signal at the receiver. Without explicit evidence of conditions for acoustic interference, signal differentiation alone is insufficient to infer competition as the main mechanism driving partitioning, since this outcome may also arise from alternative processes. By integrating coexistence theory and sensory ecology, we provide a framework to reconcile signal-structure differentiation with receiver perception, thereby improving our understanding of how communication systems evolve in mixed-species aggregations.

Transposon insertion sequencing (Tn-seq) has become a powerful tool for assigning gene fitness and essentiality in bacteria, and has recently been extended to bacteriophages. A core but rarely examined assumption of these screens is that fitness is measured in an asocial environment, where each mutant succeeds or fails on its own. Yet many genes act socially: their products can be shared among neighbors, allowing defective mutants to be complemented in trans. In phages multiple genotypes routinely coinfect the same cell. Here we show that social interactions distort gene essentiality. Using paired quorum-sensing microarray and Tn-seq data from Pseudomonas aeruginosa, we find that quorum-sensing-regulated genes are over-represented among genes scored as non-essential, confirming that social genes are under-reported as essential. We then build a stochastic, agent-based model of phage Tn-seq across an MOI gradient, assigning each gene an intrinsic fitness effect and a complementation fraction. Complementable ("social") genes rise in frequency as MOI increases, masking their true fitness cost, whereas non-complementable ("private") genes, do not. Partitioning genes by life-cycle stage and applying a two-round high-then-low-MOI design, further separates gene functions by life cycle stage. We argue that deliberate MOI manipulation turns a confound into a tool, enabling systematic classification of phage sociality.

Cooperative interactions often unfold in environments that are shaped by collective behavior, yet how knowledge about such changing environments feeds back into evolutionary dynamics remains poorly understood. While network reciprocity explains how spatial structure enables clusters of cooperators to emerge and grow under certain conditions, it typically ignores how individuals respond to environmental change. Here, we integrate stochastic environmental feedback with network reciprocity to examine how knowledge about environmental state shapes the evolution of cooperation in structured populations. We compare regimes in which individuals either condition their behavior on the current state or remain unaware of it. Under weak selection, we derive a simple condition showing that cooperation is favored when the benefit-to-cost ratio exceeds a modified classic reciprocity threshold accounting for the effect of environmental transitions and state knowledge. Environmental shifts can either promote or hinder cooperation depending on accessibility and fidelity of state knowledge. Counterintuitively, greater knowledge does not universally enhance cooperation: for certain transition rules, state awareness raises the critical threshold for cooperation, a phenomenon we term a "knowledge curse". Our results reveal that, in an ever-changing environment, cooperation in structured populations emerges from a subtle interplay between environmental feedback and information availability.

Syntax was long considered to distinguish human language from other vocal systems, with parallels in non-human animals historically limited to song. However, song lacks discrete meaning, which is a crucial pre-requisite of linguistic syntax. Over the last two decades evidence of combinatoriality in the discrete, semantic calls of an array of taxa has accumulated, providing the opportunity to investigate potentially closer parallels to language. However, most examples remain limited to small repertoires of simple two-call sequences, preventing evidence of complex internal structuring like that seen in human sentences. The recent discovery that several species produce extensive repertoires of much longer call sequences, has provided the opportunity to investigate the full extent of syntactic structure in non-human call systems. Here we demonstrate that Western Australian magpies (Gymnorhina tibicen dorsalis) use multi-level structured ordering rules within their semantic call sequences and that these ordering rules are learned during development. Specifically, we find that calls within sequences up to 15 calls long depend on the two calls given prior and that independently produced segments ( phonemes), calls, and sequences recombine into longer structures, indicating hierarchical organisation. This represents the first evidence of multi-level non-adjacent organisation and learned syntactic structure in a semantic non-human system.

The deepest ocean is one of the most extreme environments for life on our planet, combining near-freezing temperatures, low oxygen levels, and hydrostatic pressures reaching 111 MPa (1100 atm). Extreme pressures are predicted to alter many aspects of biology, including the physical properties of biological hydrogels, protein structure, and the solubility of gases in water. How organisms have adapted to live in these conditions is poorly understood. Studying these organisms in situ is difficult and requires specialized deep-sea equipment capable of withstanding the extreme pressure; raising these organisms in captivity is also challenging due to their extreme habitat requirements. Given these difficulties in studying deep-sea organisms, we set out to identify the problems shallow-dwelling organisms face due to increased pressure. These can provide insights into how organisms tolerate life in the deepest parts of the ocean. This project aims to take embryos of the shallow-dwelling aquatic organism Xenopus laevis, determine how surface-dwelling organisms fail under high hydrostatic pressure, and identify a means to survive this deadly pressure. We have designed a system to expose different embryonic stages of X. laevis to high pressures and observe its effects. After identifying the limits of survivability, we sought to understand how these embryos can acclimate to changing pressures. Comparative RNA-seq and cross-species analyses revealed a conserved, pressure-induced transcriptional response across phyla, with the heat shock pathway among the most strongly activated. Pre-activation of this pathway via prior pressure or other stressors enhances survival under otherwise lethal hydrostatic conditions.

Growing evidence of animals combining discrete, meaningful calls into sequences--a feature once thought unique to linguistic syntax--has presented the opportunity to investigate the evolutionary origins of syntactic communication. The arbitrary assignment of meaning to words marks an important step in human language evolution, and a necessary precursor to generating further meaning through sentences. Studying how other animals that produce call sequences learn the meaning of these signals could help shed light on how referentiality and semantic combinatoriality evolved. Given the presence of meaningful call sequences has only recently been revealed in several non-human animals, ontogenetic studies of the comprehension of these vocalisations are, to date, non-existent. Western Australian magpies (Gymnorhina tibicen dorsalis) combine discrete calls into a diverse array of call sequences. Recent evidence shows these sequences are socially learned, but the developmental stage at which fledglings respond correctly to them remains unstudied. We performed playbacks of a discrete alarm call and call sequence to fledglings over the course of their first 18 weeks out of the nest, identifying when they differentiate between the low-level disturbance associated with the discrete call and the high-grade aerial threat associated with the sequence. Fledglings showed immediate vigilance to both vocalisations but exhibited significantly greater vigilance and upward scanning following the sequence. Critically, fledglings showed this response to the sequence from the first week of testing, with no effect of age on the response to either vocalisation. These findings suggest that comprehension precedes production of sequences in magpies and that sequence meanings are either learned rapidly or have an innate basis. While further investigation is essential, this study offers the first empirical insight into the ontogenetic emergence of combinatorial comprehension in a non-human animal.

There are some disputed hypotheses for the recurrent observations of insular gigantism and dwarfism, like the island rule: small organisms would become larger on islands, while large organisms would become smaller. But, why is the latter? In addition, not all the observations fit this rule. Here I propose a causal model. Following the Island Biogeography Theory (IBT), insular aspects influence the census N. Observations suggest that variation in N is associated with variation in effective population size (Ne). The body size of insular colonisers might change, following Damuths law, as Ne can decrease at a differential rate from the island area A, resulting in a distinctive effective density [Formula]. Interestingly, a prediction of the drift-barrier hypothesis is that Ne is affecting mutation rates. Consequently, body mass, genome size and {micro} may be predicted to some extent by island area, as they are influenced by De and Ne. Falsification of the latter hypothesis is feasible by determining changes in genomic features of insular species. We now have the opportunity to interrogate the extensive data available. Here I ask: (i) How is decreasing island area predicting average body sizes? (ii) To which levels does this prediction apply (species, cells, genomes)? (iii) How well does the model fare on predicting {micro} over paradigmatic case studies? The resolution of these questions may provide a more reliable diagnosis of the evolutionary causes for somatic size variation. Significance statementNaturalists have long reported that insular species tend to become unusually large or small compared to their mainland relatives. Despite the familiarity of this "island rule", there is still no broad mechanistic explanation for why these changes occur so consistently across different groups of organisms. This work proposes that an important neutral factor can be the change in effective density of isolated populations. By combining the expectations of Damuths law, the IBT model, and the nearly-neutral theory it offers unified predictions on how sudden constraints in island area can influence not only the evolution of body size, but also the direction of changes in genome size and evolutionary rates.

Different plasmids exist at different copy numbers per cell, and there is an inverse relationship between a plasmids copy number and its size. Two recent studies quantified this relationship into a scaling law, but both the form and the interpretation of this law are contested. Here, I explore the issues with fitting a single law across plasmid diversity and suggest a consistent synthesis. First, I explore some potential problems with using sequencing-based estimates of copy number. Then, I discuss plasmid copy number through a series of case studies. I argue in favour of interpreting plasmid copy numbers not through a single law, but through the lens of two dominant evolutionary strategies. I suggest that small plasmids which lack active segregation mechanisms have a resulting tradeoff between plasmid inheritance and fitness cost to the host, which is responsible for an inverse relationship between copy number and size. In contrast, larger plasmids with active segregation mechanisms show a much weaker relationship, in line with evidence that their metabolic costs are dominated by the expression of specific genes rather than their size. Where plasmids in the 20-100kb range have higher copy numbers, I argue these probably arise more from selection at the level of the host cell for plasmid-associated phenotypes (e.g. antibiotic resistance) rather than from plasmid-level selection for inheritance.

Stressful environments can pose a threat to microbial populations, but resistant individuals can emerge and avoid extinction. Adaptation to stress is classically studied in isolated microbial species, ignoring ecological interactions, a key component of natural ecosystems. A growing body of experimental work has shown that community context can affect resistance evolution due to a large variety of mechanisms. Here we set out to identify the minimal components needed to predict the likelihood of acquiring resistance in a focal species embedded within a simple community. To achieve this, we developed a mathematical model based on evolutionary rescue theory and validated it with two experimental systems: Escherichia coli evolving on exposure to the antibiotic nitrofurantoin alone or with one of 14 bacterial isolates from urinary tract infections, and Microbacterium liquefaciens evolving in ampicillin alone or with ampicillin-degrading Comamonas testosteroni. One key factor that emerged from our analyses - the relative strength of competition versus protection - could explain whether a focal species is more or less likely to evolve resistance in the presence of a partner species. While competition always hinders the emergence of resistance, protection can rescue the focal species in two ways: (i) ecological rescue, when the partner species completely removes the antibiotic and favors the survival of the susceptible population, or (ii) evolutionary rescue, when the partner only lowers antibiotic concentrations and favors the emergence of resistant variants, a previously overlooked evolutionary consequence of detoxification. Overall, by integrating theory and experiments, we propose a framework that clarifies how ecological interactions favor or hinder the evolution of resistance to antibiotics or potentially other stressors. SignificanceBacteria can rapidly adapt to resist stressors, such as antibiotics. While resistance evolution in single populations or species is well understood, it remains unclear how ecological interactions with other species influence this process. We develop a mathematical framework to predict what interactions should favor resistance evolution and validate it with two sets of experiments where bacteria adapt to antibiotics in small communities. Our work demonstrates that interactions with other species shape the probability of evolving resistance in a predictable way, determined by the balance between competition and protection against the stressor. By identifying the key factors that drive these dynamics, our work helps explain how bacteria adapt to environmental challenges within species-rich ecosystems.

Global epistasis refers to the observation that the effect of a mutation or modification depends on the state of a biological system, not its detailed composition. Such patterns have been reported across biological scales, from proteins to organisms and ecosystems. In its simplest form, global epistasis appears as a linear relationship between the change in function or fitness due to a perturbation, and the background level of function or fitness. The mechanistic basis of global epistasis, particularly in ecological systems, remains unresolved. Here, we propose that in microbial communities, global epistasis describing the impact of adding a species to a community on function arises generically from constraints imposed by shared resource pools. We illustrate this mechanism in a single-species system growing on multiple substitutable resources, where global epistasis follows directly from nutrient limitation by an essential non-substitutable resource. We then extend this framework to multi-species communities competing for a single resource and show that the marginal effect of adding a species depends linearly on background community function, with a slope determined by the fraction of the resource claimed by the added species. We show that global epistasis persists in trophic cascades, but that facilitation and niche partitioning qualitatively break the linear dependence. This study provides a simple explanation for the appearance of global epistasis in ecosystems, and suggests that global epistasis should be a null expectation in ecosystems governed by competition. Our results propose that coupling between perturbations and shared resource pools might also help explain global epistasis at the organismal level.

Principles of collective motion are now well established, though research has largely focused on homogeneous groups. Heterogeneity is widespread in animal groups, e.g. arising from sex, size or even species, raising a central question: can collective behaviour emerge when individuals have distinct behaviours? Here, we combine experiments and modelling to investigate mixed-species collective motion using two closely related fish species, rosy barbs and tiger barbs. In conspecific groups, both species exhibit collective motion, but they differ strikingly in their intrinsic movement: tiger barbs exhibit slowand fast-swimming, whereas rosy barbs display fast swimming only. Despite this difference, these species readily form mixed-species schools where the slow swimming speed of tiger barbs disappears, and the collective motion is dominated by a single fast-swimming mode. We develop an individual-based model incorporating local interactions involving speed matching. Our model demonstrates that bimodal speed in conspecific schools of tiger barbs is an emergent property that is lost in mixed-species groups. Additionally, despite high cohesion, we observe spatial sorting of the two species within the mixed-species groups, which our model explains through differences in inter- and intra-specific interactions. Our results provide experimental evidence that canonical principles of collective motion extend to heterogeneous mixed-species groups.

Gene drives, genetic constructs that can spread deleterious alleles in wild populations, have the potential to address some of the major pressing challenges of the Anthropocene such as invasive species, spread of disease vectors, and agricultural pests. However, responsible and effective deployment of gene drive requires taking into account the complex nature of real-world population connectivity networks. In particular, it is unclear how the topological position of the deployment site affects the spread process and its final outcome. Here we develop a framework for modeling gene drive spread in population connectivity networks, and study the eco-evolutionary dynamics of gene drive spread under complex population structures. We investigated the relationship between the position of the deployment site in the topology of the network and whether the gene drive is eventually lost, fixed, or maintained at an intermediate frequency. We identified network centrality measures of deployment sites that are highly correlated with the outcome of deployment for different gene drive designs and across diverse network topologies. We also show that there is a trade-off between the time-to-fixation and the final outcome, implying that multiple centrality measures of the deployment site would need to be considered when aiming to achieve rapid and successful population control using gene drives.

Super-Recognisers show exceptional ability in face recognition, providing a natural model of how perceptual systems optimise for individuating visually similar stimuli in variable viewing conditions. However, the neural representations supporting this extreme perceptual expertise are unknown. Here, we tested whether Super-Recognisers (n = 23) differed from typical recognisers (n = 21) in the dimensional organisation of neural face identity coding. We recorded 64-channel electroencephalography while participants viewed random and rapidly-presented sequences containing 10 naturally varying images of 40 unfamiliar identities. Using time-resolved representational similarity analysis we measured the geometry of identity representations, their consistency across observers, and how clearly they specified face identity. Although neural expression of identity information was robust in both groups, we found three key differences between Super-Recognisers and typical recognisers. First, the geometry of face identity representations differed between groups. Second, Super-Recognisers showed greater inter-individual consistency in representational geometry. Third, Super-Recognisers' neural signals discriminated between face identities more strongly than those of typical recognisers. Differences in the coding of broader face categories (sex, age, ethnicity) were notably weaker, suggesting that the observed group differences reflected fine-scale differences in identity coding rather than global reshaping of representational geometry. Strikingly, all three differences emerged within a common mid-latency interval (~300-500ms), implicating higher-stages of face processing associated with representations that are sensitive to face familiarity and link between perceptual and semantic domains. Together, these findings indicate that individual differences in face recognition ability reflect higher-level differences in neural identity coding, rather than enhanced early sensory processing.

Habitat loss driven by climate and anthropogenic pressures alters patch morphology, with critical consequences for population persistence. Geometric and mechanistic metrics are commonly used to quantify degradation, yet their respective limitations remain poorly understood. Here, we address this gap using a reaction-diffusion framework for population growth and dispersal in a viable patch embedded in a hostile environment. We compare geometric descriptors of patch shape with a mechanistic metric derived from population growth near the extinction threshold. Along degradation trajectories, we find that geometric metrics systematically overestimate persistence, suggesting moderate and decelerating impacts, whereas mechanistic indicators reveal rapid, accelerating approaches to extinction. These results highlight fundamental limitations of geometric approaches and underscore the need for mechanistic assessments when evaluating biodiversity loss in complex landscapes.

Phage therapy offers a promising solution to the antimicrobial resistance crisis. However, a major concern preventing the adoption of phage therapy is the potential for unintended consequences of phage release; both in regard to preventing the spread of phage resistance, and the proliferation of a non-endemic virus into the microbial ecosystem. Conditional replication (biocontainment) of phages through bioengineering may address these concerns, but the impact on bactericidal efficacy is unknown. Here, we created a biocontained T7 phage (T7{Delta}capsid) lacking the major structural capsid gene, gp10AB, that can only replicate on Escherichia coli strains expressing gp10AB in trans, and assessed its bactericidal efficacy compared with wild-type T7. Congruent with model predictions, T7{Delta}capsid was only able to clear a well-mixed culture of E. coli at a multiplicity of infection (MOI) of 10 or higher, whereas wild-type T7 prohibited growth at an MOI of 0.1. The reduction in efficacy was more evident in a complex structured environment within a microfluidic device, where phage success depends on its ability to penetrate a microbial niche via propagation. In this environment, T7{Delta}capsid was unable to propagate into the bacterial population and unlike wild-type T7, had no impact on the population's growth. This study shows that whilst biocontainment of phages may improve the biosafety of phage therapy, it comes at the cost of its propagation efficacy and niche penetration in relevant environments.

Demographic shifts are reshaping population age structures worldwide, with implications for infectious disease dynamics. Since contact patterns, susceptibility and infectiousness often vary by age, the risk that pathogen introductions initiate a substantial outbreak depends on the populations age distribution and associated behavioural characteristics. We develop an age-structured mathematical model to estimate the risk that a single pathogen introduction leads to sustained transmission (the probability of a major outbreak) under long-term demographic transitions, incorporating changes in age-specific contact patterns and behavioural adaptation. Using the Republic of Korea (projected to become the worlds oldest population by 2050) as a case study, we show that population ageing generally reduces the probability of a major outbreak due to older individuals lower contact rates. However, this effect is attenuated for pathogens with increasing susceptibility or infectiousness with age, and if future older cohorts have higher contact levels than at present (e.g. through extended workforce participation in an ageing society). These findings demonstrate that, while outbreak risks are affected by demographic changes, they are further modified by associated behavioural responses, highlighting the importance of accounting for demographic and socio-behavioural context when assessing future infectious disease outbreak risks. Author SummaryIn the early stages of an infectious disease outbreak, the risk that initial cases lead to a substantial outbreak is shaped by a range of factors including the characteristics of the host population. Demographic changes, such as population ageing, are transforming societies worldwide, yet their implications for infectious disease emergence remain unclear. Here, we show that ageing populations reduce the likelihood that imported infections trigger major infectious disease outbreaks due to lower contact rates between individuals of older ages. However, this effect depends on how susceptibility, infectiousness and host behaviour vary with age. For example, increased social and economic activity among future older adults (due to a higher retirement age) could offset the decrease in the outbreak risk. These findings underscore the need to account for demographic and socio-behavioural factors, in addition to biological factors, when assessing future outbreak risks and designing robust public health strategies, particularly in societies undergoing rapid demographic change.