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Background: The prevention of methicillin-resistant S. aureus (MRSA) transmission in the healthcare setting is a priority in Infection Control practices. A cornerstone of this policy is contact tracing of nosocomial contacts after an unexpected MRSA finding. The objective of this retrospective study was to quantify the rates of MRSA transmission in different clinical settings., Methods: This multi-centre study included MRSA contact screening results from two regional hospitals and one academic hospital. MRSA contact tracing investigations from 2000 until 2019 were reviewed and post-contact screening results were included of index patients with an MRSA-positive culture and their unprotected contacts. Available typing results were used to rule out incidental findings., Results: Of 27,377 contacts screened after MRSA exposure, 21,488 were Health Care Workers (HCW) and 4816 patients. Post-contact screening was initiated for a total of 774 index cases, the average number of screened contacts per index case was 35.7 (range 1 to 640). MRSA transmission was observed in 0.15% (41) of the contacts, 19 (0.09%) HCW and 22 (0.46%) patients. The number needed to screen to detect one MRSA transmission was 667. The highest risk of MRSA transmission occurred during patient-to-patient contacts, with transmission rates varying from 0.32 to 1.32% among the participating hospitals. No transmissions were detected in HCW (n=2834) in the outpatient setting, and the rate of transmissions among HCW contacts on the wards was 0.13% (19 of 15,874). Among 344 contacts of patients with contact precautions, no transmissions were detected., Conclusions: Reconsidering current MRSA contact tracing practices may lead to a more targeted approach with a lower number needed to screen., (© 2024. The Author(s).)

The high tree diversity in tropical forests has long been a puzzle to ecologists. In the 1970s, Janzen and Connell proposed that tree species (hosts) coexist due to the stabilizing actions of specialized enemies. This Janzen-Connell hypothesis was subsequently supported by theoretical studies. Yet, such studies have taken the presence of specialized pathogens for granted, overlooking that pathogen coexistence also requires an explanation. Moreover, stable ecological coexistence does not necessarily imply evolutionary stability. What are the conditions that allow Janzen-Connell effects to evolve? We link theory from community ecology, evolutionary biology and epidemiology to tackle this question, structuring our approach around five theoretical frameworks. Phenomenological Lotka-Volterra competition models provide the most basic framework, which can be restructured to include (single- or multi-)pathogen dynamics. This ecological foundation can be extended to include pathogen evolution. Hosts, of course, may also evolve, and we introduce a coevolutionary model, showing that host-pathogen coevolution can lead to highly diverse systems. Our work unpacks the assumptions underpinning Janzen-Connell and places theoretical bounds on pathogen and host ecology and evolution. The five theoretical frameworks taken together provide a stronger theoretical basis for Janzen-Connell, delivering a wider lens that can yield important insights into the maintenance of diversity in these increasingly threatened systems., (© 2023 The Authors. Ecology Letters published by John Wiley & Sons Ltd.)

Background: Host genetics can shape microbiome composition, but to what extent it does, remains unclear. Like any other complex trait, this important question can be addressed by estimating the heritability (h 2 ) of the microbiome-the proportion of variance in the abundance in each taxon that is attributable to host genetic variation. However, unlike most complex traits, microbiome heritability is typically based on relative abundance data, where taxon-specific abundances are expressed as the proportion of the total microbial abundance in a sample., Results: We derived an analytical approximation for the heritability that one obtains when using such relative, and not absolute, abundances, based on an underlying quantitative genetic model for absolute abundances. Based on this, we uncovered three problems that can arise when using relative abundances to estimate microbiome heritability: (1) the interdependency between taxa can lead to imprecise heritability estimates. This problem is most apparent for dominant taxa. (2) Large sample size leads to high false discovery rates. With enough statistical power, the result is a strong overestimation of the number of heritable taxa in a community. (3) Microbial co-abundances lead to biased heritability estimates., Conclusions: We discuss several potential solutions for advancing the field, focusing on technical and statistical developments, and conclude that caution must be taken when interpreting heritability estimates and comparing values across studies. Video Abstract., (© 2023. BioMed Central Ltd., part of Springer Nature.)

The absence of microbial exposure early in life leaves individuals vulnerable to immune overreaction later in life, manifesting as immunopathology, autoimmunity, or allergies. A key factor is thought to be a "critical window" during which the host's immune system can "learn" tolerance, and beyond which learning is no longer possible. Animal models indicate that many mechanisms have evolved to enable critical windows, and that their time limits are distinct and consistent. Such a variety of mechanisms, and precision in their manifestation suggest the outcome of strong evolutionary selection. To strengthen our understanding of critical windows, we explore their underlying evolutionary ecology using models encompassing demographic and epidemiological transitions, identifying the length of the critical window that would maximize fitness in different environments. We characterize how direct effects of microbes on host mortality, but also indirect effects via microbial ecology, will drive the optimal length of the critical window. We find that indirect effects such as magnitude of transmission, duration of infection, rates of reinfection, vertical transmission, host demography, and seasonality in transmission all have the effect of redistributing the timing and/or likelihood of encounters with microbial taxa across age, and thus increasing or decreasing the optimal length of the critical window. Declining microbial population abundance and diversity are predicted to result in increases in immune dysfunction later in life. We also make predictions for the length of the critical window across different taxa and environments. Overall, our modeling efforts demonstrate how critical windows will be impacted over evolution as a function of both host-microbiome/pathogen interactions and dispersal, raising central questions about potential mismatches between these evolved systems and the current loss of microbial diversity and/or increases in infectious disease., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors. Evolution Letters published by Wiley Periodicals LLC on behalf of Society for the Study of Evolution (SSE) and European Society for Evolutionary Biology (ESEB).)

How and when the microbiome modulates host adaptation remains an evolutionary puzzle, despite evidence that the extended genetic repertoire of the microbiome can shape host phenotypes and fitness. One complicating factor is that the microbiome is often transmitted imperfectly across host generations, leading to questions about the degree to which the microbiome contributes to host adaptation. Here, using an evolutionary model, we demonstrate that decreasing vertical transmission fidelity can increase microbiome variation, and thus phenotypic variation, across hosts. When the most beneficial microbial genotypes change unpredictably from one generation to the next (for example, in variable environments), hosts can maximize fitness by increasing the microbiome variation among offspring, as this improves the chance of there being an offspring with the right microbial combination for the next generation. Imperfect vertical transmission can therefore be adaptive in varying environments. We characterize how selection on vertical transmission is shaped by environmental conditions, microbiome changes during host development and the contribution of other factors to trait variation. We illustrate how environmentally dependent microbial effects can favour intermediate transmission and set our results in the context of examples from natural systems. We also suggest research avenues to empirically test our predictions. Our model provides a basis to understand the evolutionary pathways that potentially led to the wide diversity of microbe transmission patterns found in nature., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

The emergence of infectious agents with pandemic potential present scientific challenges from detection to data interpretation to understanding determinants of risk and forecasts. Mathematical models could play an essential role in how we prepare for future emergent pathogens. Here, we describe core directions for expansion of the existing tools and knowledge base, including: using mathematical models to identify critical directions and paths for strengthening data collection to detect and respond to outbreaks of novel pathogens; expanding basic theory to identify infectious agents and contexts that present the greatest risks, over both the short and longer term; by strengthening estimation tools that make the most use of the likely range and uncertainties in existing data; and by ensuring modelling applications are carefully communicated and developed within diverse and equitable collaborations for increased public health benefit., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

The microbiome shapes many host traits, yet the biology of microbiomes challenges traditional evolutionary models. Here, we illustrate how integrating the microbiome into quantitative genetics can help untangle complexities of host-microbiome evolution. We describe two general ways in which the microbiome may affect host evolutionary potential: by shifting the mean host phenotype and by changing the variance in host phenotype in the population. We synthesize the literature across diverse taxa and discuss how these scenarios could shape the host response to selection. We conclude by outlining key avenues of research to improve our understanding of the complex interplay between hosts and microbiomes., (© 2021. The Author(s).)

A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (for example, warmer environments 1 , younger populations 2-4 ) have yet to be framed within a comprehensive analysis. We synthesized factors hypothesized to drive the pace and burden of this pandemic in SSA during the period from 25 February to 20 December 2020, encompassing demographic, comorbidity, climatic, healthcare capacity, intervention efforts and human mobility dimensions. Large diversity in the probable drivers indicates a need for caution in interpreting analyses that aggregate data across low- and middle-income settings. Our simulation shows that climatic variation between SSA population centers has little effect on early outbreak trajectories; however, heterogeneity in connectivity, although rarely considered, is likely an important contributor to variance in the pace of viral spread across SSA. Our synthesis points to the potential benefits of context-specific adaptation of surveillance systems during the ongoing pandemic. In particular, characterizing patterns of severity over age will be a priority in settings with high comorbidity burdens and poor access to care. Understanding the spatial extent of outbreaks warrants emphasis in settings where low connectivity could drive prolonged, asynchronous outbreaks resulting in extended stress to health systems.

Background: During a meticillin-resistant Staphylococcus aureus contact tracing and screening investigation, two borderline oxacillin-resistant Staphylococcus aureus (BORSA)-positive screening cultures were encountered among neonatal intensive care unit (NICU) healthcare workers (HCWs). This finding led to further investigations., Aim: To assess the likelihood of an outbreak with direct transmission among HCWs., Methods: An infection control team was initiated after the discovery. The team initiated additional infection control measures and evaluated new findings. All NICUs and paediatric ward HCWs were screened for BORSA carriage, and a prospective BORSA seven-week monitoring period for patients was observed. To assess the likelihood of an outbreak with direct transmission among HCWs, the BORSA isolates were analysed using augmented fragment length polymorphism and whole-genome sequencing (WGS)., Findings: Positive HCWs were prohibited from clinical work while awaiting the results from the screening programme. In all, 127 NICU and 77 general paediatric ward HCWs were screened for BORSA carriage; five HCWs were BORSA positive. Seventy-two patients were screened during the seven-week period yielding a total of 138 cultures, ranging from one to nine cultures per patient. No spread from HCWs to patients occurred, and the BORSA screening programme was discontinued. WGS analysis with core genome multi-locus sequence typing of all five BORSA strains showed relatedness between two NICU strains., Conclusion: During a seven-week period, no transmission from BORSA-positive HCWs to neonates was observed in either screening or clinical cultures. More vigilance and experience is needed to design adequate evidence-based interventions in the future for this vulnerable population., (Copyright © 2020. Published by Elsevier Ltd.)

Genetically identical individuals can be phenotypically variable, even in constant environmental conditions. The ubiquity of this phenomenon, known as 'intra-genotypic variability', is increasingly evident and the relevant mechanistic underpinnings are beginning to be understood. In parallel, theory has delineated a number of formal expectations for contexts in which such a feature would be adaptive. Here, we review empirical evidence across biological systems and theoretical expectations, including nonlinear averaging and bet hedging. We synthesize existing results to illustrate the dependence of selection outcomes both on trait characteristics, features of environmental variability, and species' demographic context. We conclude by discussing ways to bridge the gap between empirical evidence of intra-genotypic variability, studies demonstrating its genetic component, and evidence that it is adaptive., (Copyright © 2019. Published by Elsevier Ltd.)

Changes in population dynamics due to interacting evolutionary and ecological processes are the direct result of responses in vital rates, that is stage-specific growth, survival and fecundity. Quantifying through which vital rates population fitness is affected, instead of focusing on population trends only, can give a more mechanistic understanding of eco-evolutionary dynamics. The aim of this study was to estimate the underlying demographic rates of aphid (Myzus persicae) populations. We analysed unpublished stage-structure population dynamics data of a field experiment with caged and uncaged populations in which rapid evolutionary dynamics were observed, as well as unpublished results from an individual life table experiment performed in a glasshouse. Using data on changes in population abundance and stage distributions over time, we estimated transition matrices with inverse modelling techniques, in a Bayesian framework. The model used to fit across all experimental treatments included density as well as clone-specific caging effects. We additionally used individual life table data to inform the model on survival, growth and reproduction. Results suggest that clones varied considerably in vital rates, and imply trade-offs between reproduction and survival. Responses to densities also varied between clones. Negative density dependence was found in growth and reproduction, and the presence of predators and competitors further decreased these two vital rates, while survival estimates increased. Under uncaged conditions, population growth rates of the evolving populations were increased compared to the expectation based on the pure clones. Our inverse modelling approach revealed how much vital rates contributed to the eco-evolutionary dynamics. The decomposition analysis showed that variation in population growth rates in the evolving populations was to a large extent shaped by plant size. Yet, it also revealed an impact of evolutionary changes in clonal composition. Finally, we discuss that inverse modelling is a complex problem, as multiple combinations of individual rates can result in the same dynamics. We discuss assumptions and limitations, as well as opportunities, of this approach., (© 2019 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)

Dioecy has a demographic disadvantage compared with hermaphroditism: only about half of reproductive adults produce seeds. Dioecious species must therefore have fitness advantages to compensate for this cost through increased survival, growth, and/or reproduction. We used a full life cycle approach to quantify the demographic costs and benefits associated with dioecy while controlling for demographic differences between dioecious and hermaphroditic species related to other functional traits. The advantage of this novel approach is that we can focus on the effect of breeding system across a diverse tree community. We built a composite integral projection model for hermaphroditic and dioecious tree populations from Barro Colorado Island, Panama, using long-term demographic and newly collected reproductive data. Integration of all costs and benefits showed that compensation was realized through increased seed production, resulting in no net costs of dioecy. Compensation was also facilitated by the low contribution of reproduction to population growth. Estimated positive effects of dioecy on tree growth and survival were small and insignificant for population growth rates. Our model revealed that, for long-lived organisms, the cost of having males is smaller than generally expected. Hence, little compensation is required for dioecious species to maintain population growth rates similar to those of hermaphroditic species.