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The emergence of SARS-CoV-2 into a highly susceptible global population was primarily driven by human mobility-induced introduction events. Especially in the early stages, understanding mobility was vital to mitigating the pandemic prior to widespread vaccine availability. We conducted a systematic review of studies published from January 1, 2020, to May 9, 2021, that used population-level human mobility data to understand SARS-CoV-2 transmission. Of the 5505 papers with abstracts screened, 232 were included in the analysis. These papers focused on a range of specific questions but were dominated by analyses focusing on the USA and China. The majority included mobile phone data, followed by Google Community Mobility Reports, and few included any adjustments to account for potential biases in population sampling processes. There was no clear relationship between methods used to integrate mobility and SARS-CoV-2 data and goals of analysis. When considering papers focused only on the estimation of the effective reproductive number within the US, there was no clear relationship identified between this measure and changes in mobility patterns. Our findings underscore the need for standardized, systematic ways to identify the source of mobility data, select an appropriate approach to using it in analysis, and reporting., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Background: The overall pandemic created enormous pressure on long-term care workers (LTCWs), making them particularly vulnerable to mental disorders. Despite this, most of the available evidence on professional well-being during COVID-19 has exclusively focused on frontline health care workers., Objective: This study aimed to identify the long-term psychological needs of LTCWs derived from the COVID-19 pandemic and to explore barriers and facilitators related to digital mental health tools. This is part of a project that seeks to develop a digital mental health intervention to reduce psychological distress in this population group., Methods: We performed a qualitative study with a rapid research approach. Participants were LTCWs of the autonomous community of Catalonia. We conducted 30 semistructured interviews between April and September 2022. We used a qualitative content analysis method with an inductive-deductive approach., Results: The period of the pandemic with the highest mental health burden was the COVID-19 outbreak, with almost all workers having experienced some form of emotional distress. Emotional distress persisted over time in more than half of the participants, with fatigue and nervousness being the main emotions expressed at the time of the interview. High workload, the feeling that pandemic times are not over, and poor working conditions that have remained since then have been the most frequently expressed determinants of such emotions. Potential barriers and facilitators to engagement with digital tools were also identified in terms of previous experience and beliefs of the target population, possibilities for the integration of a digital tool into daily life, preferences regarding the level of guidance, the possibility of social connectedness through the tool, and privacy and confidentiality. The identified factors may become especially relevant in the context of the pandemic remission phase., Conclusions: More than 2 years after the pandemic outbreak, emotional distress is still relevant. The persistent burden of psychological distress points to a need for institutions to take action to improve working conditions and promote employees' well-being. Considering factors that act as barriers and facilitators for the use of digital mental health tools, it is important to develop tailored tools that could offer valuable support to this population during and after a pandemic., (©Leticia González-Spinoglio, Anna Monistrol-Mula, Cecilia Vindrola-Padros, Salvatore Aguilar-Ortiz, Bernat Carreras, Josep Maria Haro, Mireia Felez-Nobrega. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 29.05.2024.)

Anthropologists explore sequential art, particularly comics, as an accessible medium to co-produce knowledge about trauma and disability with research collaborators. However, practices of image description developed by blind scholars and artists need to be integrated into these projects to ensure visual studies are accessible. Collaborating with sighted service users of drop-in centers in Denmark, we reflect on the process of creating comics and image descriptions about their experiences with digital access, trauma, and disability. By analyzing insights from both drawing and describing images, we propose this method in medical anthropology as one way to build research collaborations that embrace disability expertise.

Introduction: Psychological, socio-demographics, and clinical factors play an important role in patients with COVID-19, but their relationship is complex. The network approach might be used to disentangle complex interactions in different systems. Using data from a multicentre, cross-sectional, survey among patients with COVID-19 in Spain (July-November 2020), we investigated the network structure of mental disorders symptoms, social support, and psychological resilience, and changes in network structures according to the presence of a pre-existing mental disorder or hospitalization for COVID-19., Methods: Subjects completed a survey to evaluate sociodemographic characteristics, COVID-19 infection status, resilience, social support, and symptoms of depression, anxiety disorders, post-traumatic stress disorder, panic attacks, and substance use disorder. 2084 patients with COVID-19 were included in the analysis. Network analysis was conducted to evaluate network and bridge centrality, and the network properties were compared between COVID-19 patients with and without a history of lifetime mental disorder, and between hospitalized and non-hospitalized patients., Limitations: Generalization of our findings may be difficult since differences in network connectivity may exist in different populations or samples., Results: Anxiety and depression showed high centrality in patients with COVID-19 and anxiety showed the highest bridge influence in the network. Resilience and social support showed a low influence on mental disorder symptoms. Global network estimations show no statistically significant changes between patients with and without pre-existing mental disorders or between hospitalized and non-hospitalized patients., Conclusions: Anxiety might be a key treatment target in patients with COVID-19 since its treatment might prevent other mental health adverse outcomes., Competing Interests: Declaration of competing interest GA has received CME-related honoraria, or consulting fees from Janssen-Cilag, Lundbeck, Lundbeck/Otsuka, and Angelini, with no financial or other relationship relevant to the subject of this article. AF has received CME-related educational support from Lundbeck, not related to the subject of this article. AM has received grants and served as consultant, advisor or CME speaker for the following entities: Angelini, Idorsia, Lundbeck, Pfizer, Takeda, outside of the submitted work. EV has received grants and served as consultant, advisor or CME speaker for the following entities: AB-Biotics, AbbVie, Adamed, Angelini, Biogen, Boehringer-Ingelheim, Celon Pharma, Dainippon Sumitomo Pharma, Ferrer, Gedeon Richter, GH Research, Glaxo-Smith Kline, Janssen, Lundbeck, Merck, Novartis, Orion Corporation, Organon, Otsuka, Rovi, Sage, Sanofi-Aventis, Sunovion, Takeda, and Viatris, outside the submitted work., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Reconstructing the incidence of SARS-CoV-2 infection is central to understanding the state of the pandemic. Seroprevalence studies are often used to assess cumulative infections as they can identify asymptomatic infection. Since July 2020, commercial laboratories have conducted nationwide serosurveys for the U.S. CDC. They employed three assays, with different sensitivities and specificities, potentially introducing biases in seroprevalence estimates. Using models, we show that accounting for assays explains some of the observed state-to-state variation in seroprevalence, and when integrating case and death surveillance data, we show that when using the Abbott assay, estimates of proportions infected can differ substantially from seroprevalence estimates. We also found that states with higher proportions infected (before or after vaccination) had lower vaccination coverages, a pattern corroborated using a separate dataset. Finally, to understand vaccination rates relative to the increase in cases, we estimated the proportions of the population that received a vaccine prior to infection., (© 2023. The Author(s).)

Introduction: There has been an increase in the prescription of antidepressants (AD) in primary care (PC). However, it is unclear whether this was explained by a rise in diagnoses with an indication for AD. We investigated the changes in frequency and the variables associated with AD prescription in Catalonia, Spain., Methods: We retrieved AD prescription, sociodemographic, and health-related data using individual electronic health records from a population-representative sample (N=947.698) attending PC between 2010 and 2019. Prescription of AD was calculated using DHD (Defined Daily Doses per 1000 inhabitants/day). We compared cumulative changes in DHD with cumulative changes in diagnoses with an indication for AD during the study period. We used Poisson regression to examine sociodemographic and health-related variables associated with AD prescription., Results: Both AD prescription and mental health diagnoses with an indication for AD gradually increased. At the end of the study period, DHD of AD prescriptions and mental health diagnoses with an indication for AD reached cumulative increases of 404% and 49% respectively. Female sex (incidence rate ratio (IRR)=2.83), older age (IRR=25.43), and lower socio-economic status (IRR=1.35) were significantly associated with increased risk of being prescribed an AD., Conclusions: Our results from a large and representative cohort of patients confirm a steady increase of AD prescriptions that is not explained by a parallel increase in mental health diagnoses with an indication for AD. A trend on AD off-label and over-prescriptions in the PC system in Catalonia can be inferred from this dissociation., (Copyright © 2022 Sociedad Española de Psiquiatría y Salud Mental (SEPSM). Publicado por Elsevier España, S.L.U. All rights reserved.)

Background: Over a life course, human adaptive immunity to antigenically mutable pathogens exhibits competitive and facilitative interactions. We hypothesize that such interactions may lead to cyclic dynamics in immune responses over a lifetime., Methods: To investigate the cyclic behavior, we analyzed hemagglutination inhibition titers against 21 historical influenza A(H3N2) strains spanning 47 years from a cohort in Guangzhou, China, and applied Fourier spectrum analysis. To investigate possible biological mechanisms, we simulated individual antibody profiles encompassing known feedbacks and interactions due to generally recognized immunological mechanisms., Results: We demonstrated a long-term periodicity (about 24 years) in individual antibody responses. The reported cycles were robust to analytic and sampling approaches. Simulations suggested that individual-level cross-reaction between antigenically similar strains likely explains the reported cycle. We showed that the reported cycles are predictable at both individual and birth cohort level and that cohorts show a diversity of phases of these cycles. Phase of cycle was associated with the risk of seroconversion to circulating strains, after accounting for age and pre-existing titers of the circulating strains., Conclusions: Our findings reveal the existence of long-term periodicities in individual antibody responses to A(H3N2). We hypothesize that these cycles are driven by preexisting antibody responses blunting responses to antigenically similar pathogens (by preventing infection and/or robust antibody responses upon infection), leading to reductions in antigen-specific responses over time until individual's increasing risk leads to an infection with an antigenically distant enough virus to generate a robust immune response. These findings could help disentangle cohort effects from individual-level exposure histories, improve our understanding of observed heterogeneous antibody responses to immunizations, and inform targeted vaccine strategy., Funding: This study was supported by grants from the NIH R56AG048075 (DATC, JL), NIH R01AI114703 (DATC, BY), the Wellcome Trust 200861/Z/16/Z (SR), and 200187/Z/15/Z (SR). This work was also supported by research grants from Guangdong Government HZQB-KCZYZ-2021014 and 2019B121205009 (YG and HZ). DATC, JMR and SR acknowledge support from the National Institutes of Health Fogarty Institute (R01TW0008246). JMR acknowledges support from the Medical Research Council (MR/S004793/1) and the Engineering and Physical Sciences Research Council (EP/N014499/1). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript., Competing Interests: BY, JR, HZ, CM, JH, KK, RS, CJ, YG No competing interests declared, BG BGC received financial research support through his institution from Merck for unrelated work, JL JL receives research support from CDC and NIH-NIGMS for for unrelated work, SR SR receives grants from Wellcome Trust, DC DATC received financial research support through his institution from Merck for unrelated work, (© 2022, Yang et al.)

The mean age of dengue hemorrhagic fever (DHF) cases increased considerably in Thailand from 8.1 to 24.3 y between 1981 and 2017 (mean annual increase of 0.45 y). Alternative proposed explanations for this trend, such as changes in surveillance practices, reduced mosquito–human contact, and shifts in population demographics, have different implications for global dengue epidemiology. To evaluate the contribution of each of these hypothesized mechanisms to the observed data, we developed 20 nested epidemiological models of dengue virus infection, allowing for variation over time in population demographics, infection hazards, and reporting rates. We also quantified the effect of removing or retaining each source of variation in simulations of the age trajectory. Shifts in the age structure of susceptibility explained 58% of the observed change in age. Adding heterogeneous reporting by age and reductions in per-serotype infection hazard to models with shifts in susceptibility explained an additional 42%. Reductions in infection hazards were mostly driven by changes in the number of infectious individuals at any time (another consequence of shifting age demographics) rather than changes in the transmissibility of individual infections. We conclude that the demographic transition drives the overwhelming majority of the observed change as it changes both the age structure of susceptibility and the number of infectious individuals. With the projected Thai population age structure, our results suggest a continuing increase in age of DHF cases, shifting the burden toward individuals with more comorbidity. These insights into dengue epidemiology may be relevant to many regions of the globe currently undergoing comparable changes in population demographics.

Neutralizing antibodies are important correlates of protection against dengue. Yet, determinants of variation in neutralization across strains within the four dengue virus serotypes (DENV1-4) is imperfectly understood. Studies focus on structural DENV proteins, especially the envelope (E), the primary target of anti-DENV antibodies. Although changes in immune recognition (antigenicity) are often attributed to variation in epitope residues, viral processes influencing conformation and epitope accessibility also affect neutralizability, suggesting possible modulating roles of nonstructural proteins. We estimated effects of residue changes in all 10 DENV proteins on antigenic distances between 348 DENV collected from individuals living in Bangkok, Thailand (1994-2014). Antigenic distances were derived from response of each virus to a panel of twenty non-human primate antisera. Across 100 estimations, excluding 10% of virus pairs each time, 77 of 295 positions with residue variability in E consistently conferred antigenic effects; 52 were within ±3 sites of known binding sites of neutralizing human monoclonal antibodies, exceeding expectations from random assignments of effects to sites (p = 0.037). Effects were also identified for 16 sites on the stem/anchor of E which were only recently shown to become exposed under physiological conditions. For all proteins, except nonstructural protein 2A (NS2A), root-mean-squared-error (RMSE) in predicting distances between pairs held out in each estimation did not outperform sequences of equal length derived from all proteins or E, suggesting that antigenic signals present were likely through linkage with E. Adjusted for E, we identified 62/219 sites embedding the excess signals in NS2A. Concatenating these sites to E additionally explained 3.4% to 4.0% of observed variance in antigenic distances compared to E alone (50.5% to 50.8%); RMSE outperformed concatenating E with sites from any protein of the virus (ΔRMSE, 95%IQR: 0.01, 0.05). Our results support examining antigenic determinants beyond the DENV surface., Competing Interests: The authors have declared that no competing interests exist. Author Ananda Nisalak was unable to confirm their authorship contributions. On their behalf, the corresponding author has reported their contributions to the best of their knowledge.

The spatial distribution of dengue and its vectors (spp. Aedes) may be the widest it has ever been, and projections suggest that climate change may allow the expansion to continue. However, less work has been done to understand how climate variability and change affects dengue in regions where the pathogen is already endemic. In these areas, the waxing and waning of immunity has a large impact on temporal dynamics of cases of dengue haemorrhagic fever. Here, we use 51 years of data across 72 provinces and characterise spatiotemporal patterns of dengue in Thailand, where dengue has caused almost 1.5 million cases over the last 30 years, and examine the roles played by temperature and dynamics of immunity in giving rise to those patterns. We find that timescales of multiannual oscillations in dengue vary in space and time and uncover an interesting spatial phenomenon: Thailand has experienced multiple, periodic synchronisation events. We show that although patterns in synchrony of dengue are similar to those observed in temperature, the relationship between the two is most consistent during synchronous periods, while during asynchronous periods, temperature plays a less prominent role. With simulations from temperature-driven models, we explore how dynamics of immunity interact with temperature to produce the observed patterns in synchrony. The simulations produced patterns in synchrony that were similar to observations, supporting an important role of immunity. We demonstrate that multiannual oscillations produced by immunity can lead to asynchronous dynamics and that synchrony in temperature can then synchronise these dengue dynamics. At higher mean temperatures, immune dynamics can be more predominant, and dengue dynamics more insensitive to multiannual fluctuations in temperature, suggesting that with rising mean temperatures, dengue dynamics may become increasingly asynchronous. These findings can help underpin predictions of disease patterns as global temperatures rise., Competing Interests: The authors have declared that no competing interests exist.

Infection with one of dengue viruses 1 to 4 (DENV1-4) induces protective antibodies against homotypic infection. However, a notable feature of dengue viruses is the ability to use preexisting heterotypic antibodies to infect Fcγ receptor–bearing immune cells, leading to higher viral load and immunopathological events that augment disease. We tracked the antigenic dynamics of each DENV serotype by using 1944 sequenced isolates from Bangkok, Thailand, between 1994 and 2014 (348 strains), in comparison with regional and global DENV antigenic diversity (64 strains). Over the course of 20 years, the Thailand DENV serotypes gradually evolved away from one another. However, for brief periods, the serotypes increased in similarity, with corresponding changes in epidemic magnitude. Antigenic evolution within a genotype involved a trade-off between two types of antigenic change (within-serotype and between-serotype), whereas genotype replacement resulted in antigenic change away from all serotypes. These findings provide insights into theorized dynamics in antigenic evolution.

Comparison of coronavirus disease 2019 (COVID-19) case numbers over time and between locations is complicated by limits to virological testing to confirm severe acute respiratory syndrome coronavirus 2 infection. The proportion of tested individuals who have tested positive (test-positive proportion, TPP) can potentially be used to inform trends in incidence. We propose a model for testing in a population experiencing an epidemic of COVID-19 and derive an expression for TPP in terms of well-defined parameters related to testing and presence of other pathogens causing COVID-19-like symptoms. In the absence of dramatic shifts of testing practices in time or between locations, the TPP is positively correlated with the incidence of infection. We show that the proportion of tested individuals who present COVID-19-like symptoms encodes information similar to the TPP but has different relationships with the testing parameters, and can thus provide additional information regarding dynamic changes in TPP and incidence. Finally, we compare data on confirmed cases and TPP from US states up to October 2020. We conjecture why states might have higher or lower TPP than average. Collection of symptom status and age/risk category of tested individuals can increase the utility of TPP in assessing the state of the pandemic in different locations and times., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)

Non-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (R eff ) using a mechanistic metapopulation model and associated these with county-level characteristics and NPIs in the United States (US). Interventions that included school and leisure activities closure and nursing home visiting bans were all associated with a median R eff below 1 when combined with either stay at home orders (median R eff 0.97, 95% confidence interval (CI) 0.58-1.39) or face masks (median R eff 0.97, 95% CI 0.58-1.39). While direct causal effects of interventions remain unclear, our results suggest that relaxation of some NPIs will need to be counterbalanced by continuation and/or implementation of others.

Many public health responses and modeled scenarios for COVID-19 outbreaks caused by SARS-CoV-2 assume that infection results in an immune response that protects individuals from future infections or illness for some amount of time. The presence or absence of protective immunity due to infection or vaccination (when available) will affect future transmission and illness severity. Here, we review the scientific literature on antibody immunity to coronaviruses, including SARS-CoV-2 as well as the related SARS-CoV, MERS-CoV and endemic human coronaviruses (HCoVs). We reviewed 2,452 abstracts and identified 491 manuscripts relevant to 5 areas of focus: 1) antibody kinetics, 2) correlates of protection, 3) immunopathogenesis, 4) antigenic diversity and cross-reactivity, and 5) population seroprevalence. While further studies of SARS-CoV-2 are necessary to determine immune responses, evidence from other coronaviruses can provide clues and guide future research.

Elevated blood pressure (BP) is the single most important contributing risk factor to the global disease burden, leading to over 10 million deaths each year. In Spain, hypertension (HTN) affects around 20% of the adult population and remains the greatest attributable cause of cardiovascular mortality. May Measurement Month (MMM) is a worldwide initiative aimed at increasing awareness of HTN and to improve the lack of screening programmes worldwide. An opportunistic cross-sectional survey of volunteers aged 18 and over was carried out in May 2018. Blood pressure measurement, the definition of HTN and statistical analysis followed the standard MMM protocol. Anthropometric data and responses to questionnaires on demographic, lifestyle, and environmental factors were obtained as additional information. Screening sites mainly in community pharmacies, universities, primary care centres, HTN units, and cardiovascular departments in hospitals were set up across Spain as part of this initiative. In total, 7646 individuals (63.5% female) were screened during MMM18. After multiple imputation, 40.0% had HTN, of whom 74.4% were aware of their diagnosis and 69.6% were taking antihypertensive medication. Of individuals not receiving antihypertensive medication, 16.9% were hypertensive. Of individuals receiving antihypertensive medication, 36.4% had uncontrolled BP. MMM18 almost doubled the number of participants of MMM17 and was the largest BP screening campaign ever undertaken in Spain, showing that in the absence of systematic screening programmes for HTN, MMM can identify a great number of individuals at risk, increasing their awareness and attracting the interest of the healthcare system in Spain., (Published on behalf of the European Society of Cardiology. © The Author(s) 2020.)

The duration and nature of immunity generated in response to SARS-CoV-2 infection is unknown. Many public health responses and modeled scenarios for COVID-19 outbreaks caused by SARSCoV-2 assume that infection results in an immune response that protects individuals from future infections or illness for some amount of time. The timescale of protection is a critical determinant of the future impact of the pathogen. The presence or absence of protective immunity due to infection or vaccination (when available) will affect future transmission and illness severity. The dynamics of immunity and nature of protection are relevant to discussions surrounding therapeutic use of convalescent sera as well as efforts to identify individuals with protective immunity. Here, we review the scientific literature on antibody immunity to coronaviruses, including SARS-CoV-2 as well as the related SARS-CoV-1, MERS-CoV and human endemic coronaviruses (HCoVs). We reviewed 1281 abstracts and identified 322 manuscripts relevant to 5 areas of focus: 1) antibody kinetics, 2) correlates of protection, 3) immunopathogenesis, 4) antigenic diversity and cross-reactivity, and 5) population seroprevalence. While studies of SARS-CoV-2 are necessary to determine immune responses to it, evidence from other coronaviruses can provide clues and guide future research.

Understanding how the metabolic rates of prokaryotes respond to temperature is fundamental to our understanding of how ecosystem functioning will be altered by climate change, as these micro-organisms are major contributors to global carbon efflux. Ecological metabolic theory suggests that species living at higher temperatures evolve higher growth rates than those in cooler niches due to thermodynamic constraints. Here, using a global prokaryotic dataset, we find that maximal growth rate at thermal optimum increases with temperature for mesophiles (temperature optima [Formula: see text]C), but not thermophiles ([Formula: see text]C). Furthermore, short-term (within-day) thermal responses of prokaryotic metabolic rates are typically more sensitive to warming than those of eukaryotes. Because climatic warming will mostly impact ecosystems in the mesophilic temperature range, we conclude that as microbial communities adapt to higher temperatures, their metabolic rates and therefore, biomass-specific CO[Formula: see text] production, will inevitably rise. Using a mathematical model, we illustrate the potential global impacts of these findings.

Heat transport is studied in strongly heated fusion plasmas, far from thermodynamic equilibrium. The radial propagation of perturbations is studied using a technique based on the transfer entropy. Three different magnetic confinement devices are studied, and similar results are obtained. "Minor transport barriers" are detected that tend to form near rational magnetic surfaces, thought to be associated with zonal flows. Occasionally, heat transport "jumps" over these barriers, and this "jumping" behavior seems to increase in intensity when the heating power is raised, suggesting an explanation for the ubiquitous phenomenon of "power degradation" observed in magnetically confined plasmas. Reinterpreting the analysis results in terms of a continuous time random walk, "fast" and "slow" transport channels can be discerned. The cited results can partially be understood in the framework of a resistive Magneto-HydroDynamic model. The picture that emerges shows that plasma self-organization and competing transport mechanisms are essential ingredients for a fuller understanding of heat transport in fusion plasmas.

Relating the temperature dependence of photosynthetic biomass production to underlying metabolic rates in autotrophs is crucial for predicting the effects of climatic temperature fluctuations on the carbon balance of ecosystems. We present a mathematical model that links thermal performance curves (TPCs) of photosynthesis, respiration, and carbon allocation efficiency to the exponential growth rate of a population of photosynthetic autotroph cells. Using experiments with the green alga, Chlorella vulgaris , we apply the model to show that the temperature dependence of carbon allocation efficiency is key to understanding responses of growth rates to warming at both ecological and longer-term evolutionary timescales. Finally, we assemble a dataset of multiple terrestrial and aquatic autotroph species to show that the effects of temperature-dependent carbon allocation efficiency on potential growth rate TPCs are expected to be consistent across taxa. In particular, both the thermal sensitivity and the optimal temperature of growth rates are expected to change significantly due to temperature dependence of carbon allocation efficiency alone. Our study provides a foundation for understanding how the temperature dependence of carbon allocation determines how population growth rates respond to temperature., Competing Interests: The authors declare no conflict of interest.

Understanding how changes in temperature affect interspecific competition is critical for predicting changes in ecological communities with global warming. Here, we develop a theoretical model that links interspecific differences in the temperature dependence of resource acquisition and growth to the outcome of pairwise competition in phytoplankton. We parameterised our model with these metabolic traits derived from six species of freshwater phytoplankton and tested its ability to predict the outcome of competition in all pairwise combinations of the species in a factorial experiment, manipulating temperature and nutrient availability. The model correctly predicted the outcome of competition in 72% of the pairwise experiments, with competitive advantage determined by difference in thermal sensitivity of growth rates of the two species. These results demonstrate that metabolic traits play a key role in determining how changes in temperature influence interspecific competition and lay the foundation for mechanistically predicting the effects of warming in complex, multi-species communities., (© 2018 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.)

There is currently unprecedented interest in quantifying variation in thermal physiology among organisms, especially in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a rate, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data-the Sharpe-Schoolfield equation-can yield strongly inflated estimates of temperature-normalised rate values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e., when the enzyme governing the performance of the rate is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or rate performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised rate values for meta-analyses of thermal performance across species in climate change impact studies., Competing Interests: The authors declare there are no competing interests.

A long time ago in a galaxy far, far away, the Sith Lord Karness Muur engineered the rakghoul plague, a disease that transformed infected humans into near-mindless predatory rakghouls. At its peak, the disease infected millions of individuals, giving rise to armies of rakghouls on a number of planets. Whether rakghoul populations have persisted until this day is not known, making a rakghoul invasion on Earth not completely improbable. Further, a strategy for defence against an outbreak of the disease on Earth has not yet been proposed. To fill this glaring gap, we developed the first mathematical model of the population dynamics of humans and rakghouls during a rakghoul plague outbreak. Using New South Wales as a model site, we then obtained ensembles of model predictions for the outcome of the rakghoul plague in two different disease control strategy scenarios (population evacuation and military intervention), and in the absence thereof. Finally, based on these predictions, we propose a set of policy guidelines for successfully controlling and eliminating outbreaks of the rakghoul plague in Australian states.

Phytoplankton photosynthesis is a critical flux in the carbon cycle, accounting for approximately 40% of the carbon dioxide fixed globally on an annual basis and fuelling the productivity of aquatic food webs. However, rapid evolutionary responses of phytoplankton to warming remain largely unexplored, particularly outside the laboratory, where multiple selection pressures can modify adaptation to environmental change. Here, we use a decade-long experiment in outdoor mesocosms to investigate mechanisms of adaptation to warming (+4 °C above ambient temperature) in the green alga Chlamydomonas reinhardtii, in naturally assembled communities. Isolates from warmed mesocosms had higher optimal growth temperatures than their counterparts from ambient treatments. Consequently, warm-adapted isolates were stronger competitors at elevated temperature and experienced a decline in competitive fitness in ambient conditions, indicating adaptation to local thermal regimes. Higher competitive fitness in the warmed isolates was linked to greater photosynthetic capacity and reduced susceptibility to photoinhibition. These findings suggest that adaptive responses to warming in phytoplankton could help to mitigate projected declines in aquatic net primary production by increasing rates of cellular net photosynthesis.

How have North Sea skate and shark assemblages changed since the early 20th century when bottom trawling became widespread, whilst their environment became increasingly impacted by fishing, climate change, habitat degradation and other anthropogenic pressures? This article examines long-term changes in the distribution and occurrence of the elasmobranch assemblage of the southern North Sea, based on extensive historical time series (1902-2013) of fishery-independent survey data. In general, larger species (thornback ray, tope, spurdog) exhibited long-term declines, and the largest (common skate complex) became locally extirpated (as did angelshark). Smaller species increased (spotted and starry ray, lesser-spotted dogfish) as did smooth-hound, likely benefiting from greater resilience to fishing and/or climate change. This indicates a fundamental shift from historical dominance of larger, commercially valuable species to current prevalence of smaller, more productive species often of low commercial value. In recent years, however, some trends have reversed, with the (cold-water associated) starry ray now declining and thornback ray increasing. This shift may be attributed to (i) fishing, including mechanised beam trawling introduced in the 1960s-1970s, and historical target fisheries for elasmobranchs; (ii) climate change, currently favouring warm-water above cold-water species; and (iii) habitat loss, including potential degradation of coastal and outer estuarine nursery habitats. The same anthropogenic pressures, here documented to have impacted North Sea elasmobranchs over the past century, are likewise impacting shelf seas worldwide and may increase in the future; therefore, parallel changes in elasmobranch communities in other regions are to be expected., (© 2016 Crown Copyright. Global Change Biology published by John Wiley & Sons Ltd.)

A set of new criteria for the diagnosis of the possible occurrence of a large blackout are constructed, using the output from a model for the dynamics of the electric power grid (the OPA model). The approach used is to look for maximum values of the Transfer Entropy between time series of the system variables and the time series of large blackouts. The best criterion is found by looking at the number of overloaded lines at the beginning of the day.

Failures of the complex infrastructures society depends on having enormous human and economic cost that poses the question: Are there ways to optimize these systems to reduce the risks of failure? A dynamic model of one such system, the power transmission grid, is used to investigate the risk from failure as a function of the system size. It is found that there appears to be optimal sizes for such networks where the risk of failure is balanced by the benefit given by the size.

Population dynamics are affected by changes in both the mean and standard deviation of climate, e.g., changes in average temperature are likely to affect populations, but so are changes in the strength of year-to-year temperature variability. The impacts of increases in average temperature are extensively researched, while the impacts of changes in climate variability are less studied. Is the greater attention given to changes in mean environment justified? To help answer this question we developed a simple population model, explicitly linked to an environmental process. We used the model to compare the sensitivities of a population's long-term stochastic growth rate, a measure of fitness, to changes in the mean and standard deviation of the environment. Results are interpreted in light of a comparative analysis of the relative magnitudes of change in means and standard deviations of biologically relevant climate variables in the United States. Results show that changes in the variability of the environment can be more important for many populations. Changes in mean conditions are likely to have a greater impact than changes in variability on populations far from their ideal environment, for example, populations near species range boundaries and potentially of conservation concern. Populations near range centres and close to their ideal environment are more likely to be affected by changes in variability. Among pest and insect disease vectors, as well as species of commercial value, populations likely to be of greatest economic and public health significance are those near species range centers, living in a near-ideal environment for the species. Observed changes in the variability of climate variables may benefit these populations.

Objective: To demonstrate the need for bacteriological analysis for the rational treatment of infections of the corneal surface, including conjunctivitis., Methods: The results of 1,970 consecutive bacteriological analysis obtained from 2001 to 2008 in patients with ocular hyperemia and discharge were analysed and compared with a similar study done in 1982 in the same geographical area., Results: Bacterial growth was obtained in 1,044 cases (53%). The most frequent bacteria were Staphylococci spp. (56.6%), followed by Streptococci spp. (21.4%), Haemophili spp. (12.1%), and other gram-negative bacteria (9.9%). No antibiotic was effective against all the bacteria isolated. The frequency of resistant bacteria against neomycin, tobramycin, erythromycin and gentamicin was significantly increased with respect to the study of 1982., Conclusions: Bacteriological analysis of conjunctival specimens are necessary to ensure the choice of an effective antibiotic against bacteria of the ocular surface when the initial treatment fails., (Copyright © 2011 Sociedad Española de Oftalmología. Published by Elsevier Espana. All rights reserved.)

The dynamical coupling between density gradients and particle transport has been investigated using similar experimental tools in the plasma boundary of different tokamak (JET, ISTTOK) and stellarator (TJ-II) devices, showing that the size of turbulent events is minimum in the proximity of the most probable density gradient. Experimental results were found to be consistent with results from two very different models of plasma turbulence and transport. The present findings, common to several plasma devices, suggest the importance of self-regulation mechanisms between plasma transport and gradients in fusion devices.

Chemical insecticides may be toxic and cause environmental degradation. Consequently, biological control for insects represents an alternative with low ecological impact. In this work, three soil isolates (A21, A51 and C17) from different regions of the Cuban archipelago were identified, characterized and evaluated against Aedes aegypti and Culex quinquefasciatus. The new isolates were compared with reference IPS82 strain and two strains isolated from biolarvicides Bactivec and Bactoculicida, respectively. The differentiation was done by morphological, biochemical, bioassays activity and molecular methods (SDS-PAGE, plasmid profile and random amplified polymorphic analysis). All isolates were identified as Bacillus thuringiensis. The A21, A51 and C17 isolates showed higher larvicide activity than Bactivec's isolated reference strain, against both A. aegypti and C. quinquefasciatus. A21 isolate had a protein profile similar to IPS82 and Bactivec strain. A51 and C17 isolates produced a characteristic proteins pattern. A21 and A51 isolates had plasmid patterns similar to IPS82 standard strain, while C17 isolate had different both plasmid profile and protein bands. All the studied isolates showed a diverse RAPD patterns and were different from the strains previously used in biological control in Cuba.

1. The spectral colour of population dynamics and its causes have attracted much interest. The spectral colour of a time series can be determined from its power spectrum, which shows what proportion of the total variance in the time series occurs at each frequency. A time series with a red spectrum (a negative spectral exponent) is dominated by low-frequency oscillations, and a time series with a blue spectrum (a positive spectral exponent) is dominated by high-frequency oscillations. 2. Both climate variables and population time series are characterised by red spectra, suggesting that a population's environment might be partly responsible for its spectral colour. Laboratory experiments and models have been used to investigate this potential link. However, no study using field data has directly tested whether populations in redder environments are redder. 3. This study uses the Global Population Dynamics Database together with climate data to test for this effect. We found that the spectral exponent of mean summer temperatures correlates positively and significantly with population spectral exponent. 4. We also found that over the last century, temperature climate variables on most continents have become bluer. 5. Although population time series are not long or abundant enough to judge directly whether their spectral colours are changing, our two results taken together suggest that population spectral colour may be affected by the changing spectral colour of climate variables. Population spectral colour has been linked to extinction; we discuss the potential implications of our results for extinction probability., (© 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.)

A simple dynamic model of agent operation of an infrastructure system is presented. This system evolves over a long time scale by a daily increase in consumer demand that raises the overall load on the system and an engineering response to failures that involves upgrading of the components. The system is controlled by adjusting the upgrading rate of the components and the replacement time of the components. Two agents operate the system. Their behavior is characterized by their risk-averse and risk-taking attitudes while operating the system, their response to large events, and the effect of learning time on adapting to new conditions. A risk-averse operation causes a reduction in the frequency of failures and in the number of failures per unit time. However, risk aversion brings an increase in the probability of extreme events.

For the resistive pressure-gradient-driven turbulence model, the transition from laminar regime to fully developed turbulence is not simple and goes through several phases. For low values of the plasma parameter beta, a single quasicoherent structure forms. As beta increases, several of these structures may emerge and in turn take the dominant role. Finally, at high beta, fully developed turbulence with a broad spectrum is established. A suitable characterization of this transition can be given in terms of topological properties of the flow. Here, we analyze these properties that provide an understanding of the turbulence-induced transport and give a measure of the breaking of the homogeneity of the turbulence. To this end, an approach is developed that allows discriminating between topological properties of plasma turbulence flows that are relevant to the transport dynamics and the ones that are not. This is done using computational homology tools and leads to a faster convergence of numerical results for a fixed level of resolution than previously presented in Phys. Rev. E 78, 066402 (2008).

Visualization of turbulent flows is a powerful tool to help understand the turbulence dynamics and induced transport. However, it does not provide a quantitative description of the observed structures. In this paper, an approach to characterize quantitatively the topology of the flows is given. The technique, which can be applied to any type of turbulence dynamics, is illustrated through the example of resistive ballooning instabilities.

It is shown that the usual picture for the suppression of turbulent transport across a stable sheared flow based on a reduction of diffusive transport coefficients is, by itself, incomplete. By means of toroidal gyrokinetic simulations of electrostatic, collisionless ion-temperature-gradient turbulence, it is found that the nature of the transport is altered fundamentally, changing from diffusive to anticorrelated and subdiffusive. Additionally, whenever the flows are self-consistently driven by turbulence, the transport gains an additional non-Gaussian character. These results suggest that a description of transport across sheared flows using effective diffusivities is oversimplified.

A novel method to probe and characterize the nature of the transport of passive scalars carried out by a turbulent flow is introduced. It requires the determination of two exponents which encapsulate the statistical and correlation properties of the component of interest of the Lagrangian velocities of the flow. Numerical simulations of a magnetically confined, near-critical turbulent plasma, known to exhibit superdiffusive radial transport, are used to illustrate the method. It is shown that the method can easily detect the change in the dynamics of the radial transport that takes place after adding to the simulations a (subdominant) diffusive channel of tunable strength.

Long-distance coupling between edge parameters' fluctuations has been investigated in the TJ-II stellarator. Results show long-range correlations in potential fluctuations, which are amplified by the development of radial electric fields during transitions to improved-confinement regimes, whereas there is no correlation between ion saturation current signals. These experimental findings suggest the importance of long-range correlations as a new fingerprint of the plasma behavior during the development of edge shear flows and the key role of electric fields to amplify them.

In the study of transport in inhomogeneous systems it is common to construct transport equations invoking the inhomogeneous Fick law. The validity of this approach requires that at least two ingredients be present in the system. First, finite characteristic length and time scales associated with the dominant transport process must exist. Second, the transport mechanism must satisfy a microscopic symmetry: global reversibility. Global reversibility is often satisfied in nature. However, many complex systems exhibit a lack of finite characteristic scales. In this Letter we show how to construct a generalization of the inhomogeneous Fick law that does not require the existence of characteristic scales while still satisfying global reversibility.

For many years quasilinear renormalization has been applied to numerous problems in turbulent transport. This scheme relies on the localization hypothesis to derive a linear transport equation from a simplified stochastic description of the underlying microscopic dynamics. However, use of the localization hypothesis narrows the range of transport behaviors that can be captured by the renormalized equations. In this paper, we construct a renormalization procedure that manages to avoid the localization hypothesis completely and produces renormalized transport equations, expressed in terms of fractional differential operators, that exhibit much more of the transport phenomenology observed in nature. This technique provides a first step toward establishing a rigorous link between the microscopic physics of turbulence and the fractional transport models proposed phenomenologically for a wide variety of turbulent systems such as neutral fluids or plasmas.

The paper describes the complex topological structure of invariant surfaces that appears in a quasi-stationary regime of the tokamak plasma, and it considers in detail anomalous transport of particles along the invariant surfaces (isosurfaces) that have topological genus greater than 1. Such dynamics is pseudochaotic; i.e. it has a zero Lyapunov exponent. Simulations discover such surfaces in confined plasmas under a fairly low ratio of pressure to the magnetic field energy (beta). The isosurfaces correspond to quasi-coherent structures called "streamers" and the streamers are connected by filaments. We study distribution of time of particle separation, Poincaré; recurrences of trajectories, and first time arrival to the system's edge. A model of a multibar-in-square billiard, introduced by Carreras et al. [Chaos 13, 1175 (2003)] is studied with renormalization group method to obtain a distribution of the first time of particles arrival to the edge as a function of the number of bars, which appears to be power-like. The characteristic exponent of this distribution is discussed with respect to its dependence on the number of filaments that connect adjacent streamers.

Numerical evidence of nondiffusive transport in three-dimensional, resistive pressure-gradient-driven plasma turbulence is presented. It is shown that the probability density function (pdf) of tracer particles' radial displacements is strongly non-Gaussian and exhibits algebraic decaying tails. To model these results we propose a macroscopic transport model for the pdf based on the use of fractional derivatives in space and time that incorporate in a unified way space-time nonlocality (non-Fickian transport), non-Gaussianity, and nondiffusive scaling. The fractional diffusion model reproduces the shape and space-time scaling of the non-Gaussian pdf of turbulent transport calculations. The model also reproduces the observed superdiffusive scaling.

The fluid limit of a recently introduced family of nonintegrable (nonlinear) continuous-time random walks is derived in terms of fractional differential equations. In this limit, it is shown that the formalism allows for the modeling of the interaction between multiple transport mechanisms with not only disparate spatial scales but also different temporal scales. For this reason, the resulting fluid equations may find application in the study of a large number of nonlinear multiscale transport problems, ranging from the study of self-organized criticality to the modeling of turbulent transport in fluids and plasmas.

In order to study the complex global dynamics of a series of blackouts in power transmission systems a dynamical model of such a system has been developed. This model includes a simple representation of the dynamical evolution by incorporating the growth of power demand, the engineering response to system failures, and the upgrade of generator capacity. Two types of blackouts have been identified, each having different dynamical properties. One type of blackout involves the loss of load due to transmission lines reaching their load limits but no line outages. The second type of blackout is associated with multiple line outages. The dominance of one type of blackout over the other depends on operational conditions and the proximity of the system to one of its two critical points. The model displays characteristics such as a probability distribution of blackout sizes with power tails similar to that observed in real blackout data from North America., (Copyright 2004 American Institute of Physics)

In dynamical systems with a zero Lyapunov exponent, weak mixing can be governed by a specific topological structure of some surfaces that are invariant with respect to particle dynamics. In particular, when the genus of the invariant surfaces is more than one, they may have weak mixing and the corresponding fractional kinetics. This possibility is demonstrated by using a typical example from plasma physics, a three-dimensional resistive pressure-gradient-driven turbulence model. In a toroidal geometry and with a low-pressure gradient, this model shows the emergence of quasicoherent structures. In this situation, the isosurfaces of the velocity stream function have a web structure with filamentary surfaces emerging from the outer region of the torus and covering the inner region. The filamentary surfaces can result in stochastic jets of particles that cause a "topological instability." In such a situation, particle transport along the surfaces is of the anomalous superdiffusion type., (Copyright 2003 American Institute of Physics.)

The use of reaction-diffusion models rests on the key assumption that the diffusive process is Gaussian. However, a growing number of studies have pointed out the presence of anomalous diffusion, and there is a need to understand reactive systems in the presence of this type of non-Gaussian diffusion. Here we study front dynamics in reaction-diffusion systems where anomalous diffusion is due to asymmetric Levy flights. Our approach consists of replacing the Laplacian diffusion operator by a fractional diffusion operator of order alpha, whose fundamental solutions are Levy alpha-stable distributions that exhibit power law decay, x(-(1+alpha)). Numerical simulations of the fractional Fisher-Kolmogorov equation and analytical arguments show that anomalous diffusion leads to the exponential acceleration of the front and a universal power law decay, x(-alpha), of the front's tail.

The statistics of the quiet times between successive turbulent flux bursts measured at the edge of the JET tokamak and the W7-AS and TJ-II stellarators are analyzed in search for evidence of self-organized critical behavior. The results obtained are consistent with what would be expected in the situation where the underlying plasma is indeed in a near critical state.

Cascading failures in large-scale electric power transmission systems are an important cause of blackouts. Analysis of North American blackout data has revealed power law (algebraic) tails in the blackout size probability distribution which suggests a dynamical origin. With this observation as motivation, we examine cascading failure in a simplified transmission system model as load power demand is increased. The model represents generators, loads, the transmission line network, and the operating limits on these components. Two types of critical points are identified and are characterized by transmission line flow limits and generator capability limits, respectively. Results are obtained for tree networks of a regular form and a more realistic 118-node network. It is found that operation near critical points can produce power law tails in the blackout size probability distribution similar to those observed. The complex nature of the solution space due to the interaction of the two critical points is examined.(c) 2002 American Institute of Physics.

A method is presented that allows one to obtain information about the underlying dynamics of a self-organized-criticality system even when the strong-overlapping or hydrodynamic regime (in which individual avalanches are no longer distinguishable) is the only one amenable of probing. The method is based on the analysis of the statistics of the lapses of time between activity bursts or quiet times. The case of a randomly driven running sandpile is used to illustrate the use and capabilities of this technique.

The probability distribution function of the avalanche size in the sandpile model does not verify strict self-similarity under changes of the sandpile size. Here we show the existence of avalanches with different space-time structure, and each type of avalanche has a different scaling with the sandpile size. This is the main cause of the lack of self-similarity of the probability distribution function of the avalanche sizes, although the boundary effects can also play a role.