Philosophical Transactions of the Royal Society B: Biological Sciences

We compare the trajectory of deaths (both in hospitals and care homes) on a daily basis in Sweden and England and Wales (which constitute 90 per cent of the UK population) from 11 March to 7 August 2020, the latest date at which the relevant data is available for England and Wales. Deaths in both Sweden and England and Wales peaked on 8 April. The build up to the peak was very similar in both. Given the time lag between infection and death, the lockdown would have had little effect on the peak number of deaths. By the first week of August, the deaths are very similar in both. However, from early May the decline in England and Wales has been much sharper. We estimate that to 7 August, lockdown saved 17,700 lives in England and Wales, or just under 20,000 extrapolating to a UK level.

It has previously been thought that the social brain hypothesis applies in its full quantitative form only to primates. Using more appropriate brain indices and less error-prone statistical methods, we here show that it does in fact apply to both Insectivorans and Carnivorans, as well as to elephants and orcas. While Insectivorans form a grade on their own, reflecting a simple transition from small-brained solitary social systems to slightly larger-brained pairbonded monogamy, the Carnivorans map directly onto the primate socio-cognitive grades, dividing between loose sociality and more bonded sociality paralleling the pattern observed in monkeys. In addition, the subgroupings of species with multilevel social systems (including hyaenids elephants and orcas) map across the grades in the same way as do primates with similar societies. This suggests that common principles and trajectories underlie social evolution in mammals.

Human activity is transforming the shape, size, and resilience of Earths biosphere, degrading and augmenting Holocene baseline conditions at various scales, and replacing the wild biosphere with an anthropogenically modified one. We evaluate episodes of biosphere change throughout Earth history and compare them with contemporary and near-future anthropogenic changes, developing the concept of biosphere disruptors - agents that force global-scale macroevolutionary change. Transient disruptors are short-lived agents (mean 8.0x105 years), including massive volcanism and asteroid impacts. Persistent disruptors, including atmospheric and ocean oxygenation and land plant evolution, remain in the Earth System over long timescales (mean 1.6x108 years). In the geological record, transient disruptors are associated with temporary but sometimes massive biosphere degradation, whereas persistent disruptors are associated with sustained biosphere enhancement. Most anthropogenic biosphere impacts resemble those of past transient disruptors, globally degrading wild biomass and biodiversity. Humanity is driving the second highest rate of biosphere degradation in Earth history after the Cretaceous-Palaeogene bolide impact. However, humanity is the first disrupting agent capable of reflecting on and potentially transforming its impact on planetary habitability. If we can achieve this, humanity could drive the greatest rate of increase in planetary habitability in Earth history on centennial to millennial timescales.

Previous work has shown that environment affects SARS-CoV-2 transmission, but it is unclear whether emerging strains show similar responses. Here we show that, like other SARS-CoV-2 strains, lineage B.1.1.7 spread with greater transmission in colder and more densely populated parts of England. However, we also find evidence of B.1.1.7 having a transmission advantage at warmer temperatures compared to other strains. This implies that spring and summer conditions are unlikely to slow B.1.1.7s invasion in Europe and across the Northern hemisphere - an important consideration for public health interventions.

Tactical emotion communication has long been considered uniquely-human. As a species, we readily exaggerate, inhibit and modify emotional expressions according to social context and audience. Notably, emitting emotional displays, such as those pertaining to distress states, can evoke empathic responses in others such as the offering of consolation to victims after a fight. Animal emotion expressions, by contrast, are traditionally viewed as uncontrollable arousal responses. Our study challenges this view by assessing the level of control in the emotional signalling of sanctuary-living bonobo victims following aggressive attacks (N = 27 victims, N = 144 attacks) and its and its corresponding effect on receivers. Results show that the production of paedomorphic signals by adult bonobo victims increased chances of receiving consolation from bystanders and reduced risk of future aggression from former opponents, highlighting a strategic function. Victim signalling also increased with audience size, yet strategies differed by age: immature bonobos were more likely to cease signalling in proximity of close-social partners, whereas adults were more likely to cease signalling after having been consoled. These data suggest that bonobo emotion communication has a developmental trajectory and that tactical emotion signalling is a Pan-human capacity, preceding the split of Homo.

The capacity to inhibit prepotent actions (inhibitory self-control) plays an important role in many aspects of the behaviour of birds and mammals. Although a number of studies have used it as an index of foraging skills, inhibition is also crucial for maintaining the temporal and spatial coherence of bonded social groups. Using three different sets of comparative data, we show that, across primate species, the capacity for self-control correlates better with the demands of social contexts than with the demands of foraging contexts, whereas a more generalised capacity for causal reasoning correlates better with foraging contexts. In addition, we confirm the Passingham-Wise Conjecture that the capacity for self-control is unique to anthropoid primates. These results suggest that the capacity for self-control most likely evolved because it was crucial for the evolution of bonded social groups. Significance StatementThe capacity for self-control has commonly been viewed as an index of foraging skills. In fact, it plays a much more important role in the social domain by enabling groups of animals to maintain social cohesion as they travel through time and space. In this respect, it is particularly important for species that live in stable bonded social groups (congregations). We show that, in this respect, it is uniquely characteristic of the anthropoid primates, in contrast to other kinds of reasoning tasks such as causal reasoning on which primates often perform no better than other birds and mammals.

Close contacts between individuals provide opportunities for the transmission of diseases, including COVID-19. Individuals take part in many different types of interactions, including those with classmates, co-workers, and household members; the conglomeration of all of these interactions produces a complex social contact network interconnecting individuals across the population. Thus, while an individual might decide their own risk tolerance in response to a threat of infection, the consequences of such decisions are rarely so confined, propagating far beyond any one person. We asses the effect of different population-level risk-tolerance regimes, population structure in the form of age and household-size distributions, and different types of interactions on epidemic spread in plausible human contact networks to gain insight into how contact network structure affects pathogen spread through a population. In particular, we find that changes in behaviour of vulnerable individuals in isolation is insufficient to reduce those individuals infection risk, that population structure can have varied and counter-acting effects on epidemic outcomes, and that, in general, interactions among co-workers have a greater contribution to disease spread than do interactions among children at school. Taken together, these results promote a nuanced understanding of disease spread on contact networks, with implications for public health strategies.

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.

Background Social contact surveys, which measure who-contacts-whom, are widely used to inform infectious disease transmission models and estimate the reproduction number (R), a key metric for assessing epidemic risk. Despite their widespread use, sample size calculations are not routinely performed. Aims To assess the impact of sample size on estimates of R and determine a practical target sample size for social contact surveys used in epidemic modelling. Methods We conducted a review of social contact surveys (2008-2025) to characterise current practice. We characterised the impact of survey size on epidemic metrics using two social contact surveys, the UK Social Contact Survey and POLYMOD (Europe) and two methods. For each dataset and approach, we generated repeated subsamples and calculated the resulting reproduction numbers, characterised their distributions and measured uncertainty. Results We identified 107 unique social contact surveys from 57 studies. Sample sizes ranged from 30 to more than 10,000 participants, with a median of 1,438. One quarter of surveys contained fewer than 1,000 participants. From our simulations, we find that sample sizes below 200 individuals can result in highly variability reproduction numbers. Increasing sample size increases precision, and the most meaningful gains are up to 1,300 individuals. Increasing sample sizes over 3,000 individuals leads to smaller gains. Conclusions A minimum sample size of approximately 1,200-1,300 participants appears sufficient for general-purpose use. These findings support the inclusion of sample size considerations in the design, reporting and interpretation of social contact surveys used for epidemic intelligence and public health decision-making.

Although population-wide lockdowns have been successful in slowing the COVID-19 epidemic, there is a consensus among disease modellers that keeping the load on critical care services within manageable limits will require an adaptive social distancing strategy, alternating cycles of relaxation and reimposition until a vaccine is available. An alternative strategy that has been tentatively proposed is to shield the elderly and others at high risk of severe disease, while allowing immunity to build up in those at low risk until the entire population is protected. We examine the performance required from a classifier that uses information from medical records to assign risk status for a such a stratify-and-shield policy to be effective in limiting mortality when social distancing is relaxed. We show that under plausible assumptions about the level of immunity required for population-level immunity, the proportion shielded is constrained to be no more than 15% of the population. Under varying assumptions about the infection fatality ratio (from 0.1% to 0.4%) and the performance of the classifier (3 to 4.5 bits of information for discrimination), we calculate the expected number of deaths in the unshielded group. We show that with likely values of the performance of a classifier that uses information from age, sex and medical records, at least 80% of those who would die if unshielded would be allocated to the high-risk shielded group comprising 15% of the population. Although the proportion of deaths that would be prevented by effective shielding does not vary much with the infection fatality ratio, the absolute number of deaths in the unshielded varies from less than 10,000 if the infection fatality rate is 0.1% to more than 50,000 if the infection fatality rate is as high as 0.4%. For projecting the effect of an optimally applied stratify-and-shield policy, studies now under way should help to resolve key uncertainties: the extent to which infection confers immunity, the prevalence of immunity, the infection fatality ratio, and the performance of a classifier constructed using information from medical records. It is time to give serious consideration to a stratify-and-shield policy that could bring the COVID-19 epidemic to an end in a matter of months while restoring economic activity, avoiding overload of critical care services and limiting mortality.

A populations social structure, often represented as a social network, shapes fundamental biological processes including the spread of disease, information, and behaviour. The Friendship Paradox is a network phenomenon whereby the average individual has fewer friends than their friends do. This effect can be quantified as relationship disparity (the difference between an individuals connectedness and those they are connected to) which captures the local social environment. Previous work has shown that such relationship disparity can be exploited in effective outbreak monitoring, targeted health interventions and optimized contact tracing. Yet, how its magnitude varies across real-world social networks remains poorly understood. Here, we analyse relationship disparity across 391 empirical animal social networks to test how intrinsic network properties and biological attributes predict its extent. We find that smaller and sparser networks exhibit stronger relationship disparity, and that mammalian and avian social systems generally showed stronger relationship disparity than reptilian systems. After controlling for variation in individual sociability, mammalian and reptilian social networks displayed weaker relationship disparity than expected based on network structure alone. Together, these findings demonstrate that both network structure and biological attributes shape relationship disparity in natural social systems, providing a foundation for predicting how higher-order network architecture influences social processes such as contagion. Significance StatementIn natural populations, social connections are unevenly distributed, often resulting in a small subset of individuals that are highly connected while many are relatively peripheral. The Friendship Paradox is a measure of relationship disparity between individuals and their local social environment. Understanding how features of the social network and biological system are associated with relationship disparity can contribute to understanding what shapes social behaviour. Relationship disparity may not just be an emergent network property but could reflect a higher level of social structuring, and therefore shape processes that depend on social contacts. Our findings demonstrate the value of comparative network analysis for generating insights into fundamental principles structuring real-world societies.

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.

Group living and social interactions among animals provide key benefits, such as the exchange of beneficial social information and novel behaviours, but also pose the risk of spreading costly infectious diseases, presenting a social trade-off. While both information and infections spread across social networks, they typically have distinct mechanisms of transmission. Here, we model social information and behaviour spread as a complex contagion governed by a conformist learning rule, while pathogen transmission follows a simple contagion mechanism. Building on theoretical foundations, our study applies computational models to examine how subgroup structure (modularity) influences the spread of these contagions across diverse animal social structures sourced from the Animal Social Network Repository (ASNR). Our findings reveal that high modularity and subgroup structure slow simple contagion spread, whereas complex contagions are less impeded by this fragmentation. Consequently, our results suggest that social networks divided into small groups or subgroups can help balance the competing pressures of acquiring social information and avoiding infectious disease in real-world networks.

Multilevel social systems in birds and mammals have attracted considerable interest, not least because they share some similarities with the natural structural organisation of human societies. I use a fractal analysis of a taxonomically wide range of species reported to have multilevel social systems to show that these in fact involve two very different phenomena: those that are fractally modular and those that are casually modular. The first have a strictly fractal structure identical to that found in human societies; the second lack formal structural coherence and are closer in form to casual herds. The former are associated with larger neocortices than the latter, suggesting that they may be cognitively more demanding. Understanding the evolution of multilevel systems and the cognition that underpins them obliges us to adopt a more nuanced approach to social evolution.

Oscine songbirds have been an important study system for social learning, particularly because their learned songs provide an analog for human languages and music. Here we propose a different analogy; from an evolutionary perspective, could a birds song be more like an arrowhead than an aria? We modify a model of human tool evolution to accommodate cultural evolution of birdsong: each song learner chooses the most skilled available tutor to emulate, and each is more likely to produce an inferior copy than a superior one. Similarly to human tool evolution, we show that larger populations foster improvements in song over time, even when learners restrict their pool of tutors to a subset of individuals. We also demonstrate that songs could be simplified instead of lost after population bottlenecks if lower-quality traits are easier to imitate than higher-quality ones. We show that these processes could plausibly generate empirically observed patterns of song evolution, and we make predictions about the types of song elements most likely to be lost when populations shrink. More broadly, we aim to connect the modeling approaches used in human and non-human systems, moving toward a cohesive theoretical framework that accounts for both cognitive and demographic processes.

Although division of labor as a means to increase productivity is a common feature in animal social groups, most previous studies have focused almost exclusively on eusocial insects with extreme task partitioning. Empirical evidence of division of labor in vertebrates is scarce, largely because we lack a theoretical framework to explore the conditions under which division of labor is likely to evolve in cooperatively breeding systems where helpers remain capable of breeding throughout their lifetime. By explicitly considering alternative helping tasks with varying fitness costs, we model how individual decisions on task specialization may influence the emergence of division of labor under both direct and indirect fitness benefits. Surprisingly, we find that direct survival benefits of living in larger groups are the primary force driving the evolution of cooperation to enhance group productivity, and that indirect fitness benefits derived from related group members are only a non-essential facilitator of more stable forms of division of labor in cooperative breeders. In addition, we find that division of labor in vertebrates is favored by harsh environments. Ultimately, our model not only makes key predictions that are consistent with existing empirical data, but also proposes novel avenues for new empirical work in vertebrate and invertebrate systems alike.

BackgroundA structural governance failure sits at the intersection of international biodiversity law and the digital genomics revolution. The Convention on Biological Diversity (CBD) and the Nagoya Protocol on Access and Benefit-Sharing (ABS) were designed to ensure that countries of biological origin share equitably in commercial benefits from their genetic resources. Critically, these instruments apply exclusively to non-human genetic resources: plants, animals, fungi, and microbiota. Human genetic resources are deliberately excluded from the CBD and Nagoya ABS framework and are governed separately through bioethics instruments, including the World Health Organization (WHO) framework and the Declaration of Helsinki. This study focuses on non-human digital sequence information (DSI), nucleotide and protein sequence data derived from non-human organisms deposited in open-access databases, which underpins industries generating over USD 1.56 trillion in annual revenue. Africa, hosting approximately 25% of global terrestrial species and nine of the worlds 36 biodiversity hotspots, provides a disproportionate share of the genetic resources from which non-human DSI is derived, yet receives negligible monetary returns because digitisation severs the traceability chain that ABS governance requires. Human genomic data is presented here solely as a secondary indicator of Africas broader infrastructure; it does not constitute the legal basis for Africas modelled allocation share under the Cali Fund. ObjectivesThis study systematically characterises (i) Africas non-human biodiversity endowment as the basis for Cali Fund claims; (ii) ABS governance readiness across 54 African Union (AU) member states; (iii) the commercial trajectories of non-human DSI-dependent industries and projected Cali Fund benefit-sharing flows; and (iv) Africas human genomic representation as a secondary infrastructure indicator, explicitly distinguished from the non-human DSI benefit-sharing argument. MethodsA structured evidence synthesis was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 reporting elements, where applicable to a secondary data analysis design. Literature was searched across PubMed, Scopus, Web of Science, Google Scholar, and official repositories of the CBD, Food and Agriculture Organization of the United Nations (FAO), International Union for Conservation of Nature (IUCN), and United Nations Environment Programme (UNEP). The search was restricted to January 2022 - April 2026 to capture post-Kunming-Montreal Global Biodiversity Framework (KMGBF) literature. A total of 412 records were identified before screening; 34 peer-reviewed articles and 19 institutional documents met all inclusion criteria. Quantitative Cali Fund scenario modelling used the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) and KPMG (2024) non-human DSI sector revenue baseline (CBD/WGDSI/2/2/Add.2). The 12.5% net profit margin is a cross-sector proxy from that study; actual margins vary by sector. Africas modelled allocation share (20-25%) is the authors analytical construct based on Africas non-human species richness and hotspot share; it is not an internationally agreed formula. ResultsAfricas non-human biodiversity endowment is exceptional: 25% of terrestrial species, nine of 36 biodiversity hotspots, and the worlds second-largest tropical forest system. Non-human DSI from African genetic resources is a critical input to industries generating USD 1.56 trillion annually, yet Africa contributes a marginal and unmeasured fraction of International Nucleotide Sequence Database Collaboration (INSDC) sequences. As a secondary indicator, 94.48% of genome-wide association study (GWAS) participants as of 2024 were of European ancestry (Corpas et al., 2025); this human genomic data is presented for contextual illustration only and is not the basis for Africas Cali Fund modelled allocation share. Zero African Union member states have enacted legislation explicitly covering non-human DSI in their ABS framework. Africas modelled allocation share ranges from USD 312 million (Scenario A, 20% weight) to USD 5.83 billion (Scenario C, 25% weight) annually. ConclusionsAfrica is among the most biologically rich continents on Earth for non-human life, yet structurally excluded from the benefit-sharing framework the CBD intended to create. The Cali Fund represents the first mechanism capable of correcting this at scale. Realising Africas modelled allocation share requires urgent legislative reform, institutional capacity investment, sequencing infrastructure development, and a coordinated African position at COP17 scheduled in Yerevan, October 2026.

Close-contact and respiratory infectious diseases are spread through social interactions, which were affected by the COVID-19 pandemic and wider demographic and cultural changes. To estimate post-pandemic social contact patterns in the United Kingdom, we conducted a cross-sectional survey of 13,238 participants from November 2024 to March 2025. We calculated the mean number of daily contacts and contact matrices stratified by age, ethnicity, and socioeconomic status (SES). The mean number of daily contacts was 9.11 (95% confidence interval (CI): 8.73 - 9.50). Age-assortativity was high, while assortativity between ethnic groups was strongest in the home, and between SES groups in the workplace. In a novel respiratory pathogen outbreak, we found 2.29 times higher infection risk for Black people compared to White (95% CI: 2.08-2.55). This study provides crucial data to inform post-pandemic models of infectious disease transmission, and incorporate ethnicity and SES into such models.

* There are many ways of analyzing the progress of an epidemic, but when it comes to short term forecasting, it is very hard to beat a simple time series regression model. These are good at allowing for the noise in day to day observations, extracting the trend and projecting it forward. * Our regression models are designed to exploit this, using the daily statistics released by PHE and NHSE. These strongly suggest that the tide has turned and that taking one day with the next, the national figures for deaths from this virus will now fall back noticeably, easing the pressure on the NHS and its staff. * There is still a huge range of uncertainty associated with any forecast. The model is currently predicting a total of 113,000 admissions to UK hospitals by the end of April and that 19,000 people will die from the virus in English hospitals by then. There is a 1 in 20 chance that the mortality figures could flatten out more quickly, with around 1,000 more deaths occurring by the end of April. However, there is the same risk that this figure continues to mount, rising to a total of 24,000 by the end of the month. On current trends, the number of deaths in the UK is likely to be 10% higher than the number in England. * Longer term, the impact of the virus will depend critically upon the likely relaxation of the current government strategy of suppression.

People with chronic (long-lasting) infections face the problem that treatment options diminish in time as the pathogen evolves increasing resistance. To address this challenge, we exploit phage and bacterial co-evolution, producing dynamic selection pressures that can return the pathogen to a state of susceptibility to the initial (regulator-approved) therapy. We show that phage OMKO1 alone triggers Arms Race Dynamic (ARD) co-evolution with the pathogen Pseudomonas aeruginosa, leading to generalized phage resistance and crucially - failure at reuse. In contrast, co-administration of the phage with antibiotics triggers Fluctuating Selection Dynamics (FSD) co-evolution, allowing for effective reuse after 20 days of treatment. We pursue medical relevance in our experiments with the use of clinically important pathogens, antibiotics, phage, and a benchmarked synthetic sputum medium. Phenotypic and genomic characterization of evolved isolates demonstrates that efflux-targeting phage OMKO1 exerts continued selection for antibiotic susceptibility regardless of co-evolutionary dynamic or antibiotic co-treatment, opening the door for evolutionary robust phage therapy.