Modelling the Seasonal Epidemics of Respiratory Syncytial Virus in Young Children

BACKGROUND Respiratory syncytial virus (RSV) is a major cause of paediatric morbidity. Mathematical models can be used to characterise annual RSV seasonal epidemics and are a valuable tool to assess the impact of future vaccines. OBJECTIVES Construct a mathematical model of seasonal epidemics of RSV and by fitting to a population-level RSV dataset, obtain a better understanding of RSV transmission dynamics. METHODS We obtained an extensive dataset of weekly RSV testing data in children aged less than 2 years, 2000-2005, for a birth cohort of 245,249 children through linkage of laboratory and birth record datasets. We constructed a seasonally forced compartmental age-structured Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) mathematical model to fit to the seasonal curves of positive RSV detections using the Nelder-Mead method. RESULTS From 15,830 specimens, 3,394 were positive for RSV. RSV detections exhibited a distinct biennial seasonal pattern with alternating sized peaks in winter months. Our SEIRS model accurately mimicked the observed data with alternating sized peaks using disease parameter values that remained constant across the 6 years of data. Variations in the duration of immunity and recovery periods were explored. The best fit to the data minimising the residual sum of errors was a model using estimates based on previous models in the literature for the infectious period and a slightly lower estimate for the immunity period. CONCLUSIONS Our age-structured model based on routinely collected population laboratory data accurately captures the observed seasonal epidemic curves. The compartmental SEIRS model, based on several assumptions, now provides a validated base model. Ranges for the disease parameters in the model that could replicate the patterns in the data were identified. Areas for future model developments include fitting climatic variables to the seasonal parameter, allowing parameters to vary according to age and implementing a newborn vaccination program to predict the effect on RSV incidence.HCM is funded by National Health and Medical Research Council Fellowship #1034254

Modeling the impact of COVID-19 nonpharmaceutical interventions on respiratory syncytial virus transmission in South Africa

Background: The South African government employed various nonpharmaceutical interventions (NPIs) to reduce the spread of SARS-CoV-2. Surveillance data from South Africa indicates reduced circulation of respiratory syncytial virus (RSV) throughout the 2020–2021 seasons. Here, we use a mechanistic transmission model to project the rebound of RSV in the two subsequent seasons. Methods: We fit an age-structured epidemiological model to hospitalization data from national RSV surveillance in South Africa, allowing for time-varying reduction in RSV transmission during periods of COVID-19 circulation. We apply the model to project the rebound of RSV in the 2022 and 2023 seasons. Results: We projected an early and intense outbreak of RSV in April 2022, with an age shift to older infants (6–23 months old) experiencing a larger portion of severe disease burden than typical. In March 2022, government alerts were issued to prepare the hospital system for this potentially intense outbreak. We then assess the 2022 predictions and project the 2023 season. Model predictions for 2023 indicate that RSV activity has not fully returned to normal, with a projected early and moderately intense wave. We estimate that NPIs reduced RSV transmission between 15% and 50% during periods of COVID-19 circulation. Conclusions: A wide range of NPIs impacted the dynamics of the RSV outbreaks throughout 2020–2023 in regard to timing, magnitude, and age structure, with important implications in a low- and middle-income countries (LMICs) setting where RSV interventions remain limited. More efforts should focus on adapting RSV models to LMIC data to project the impact of upcoming medical interventions for this disease.</p

Long term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: a modelling study

BACKGROUND: Vaccines have reduced severe disease and death from Coronavirus Disease 2019 (COVID-19). However, with evidence of waning efficacy coupled with continued evolution of the virus, health programmes need to evaluate the requirement for regular booster doses, considering their impact and cost-effectiveness in the face of ongoing transmission and substantial infection-induced immunity.METHODS AND FINDINGS: We developed a combined immunological-transmission model parameterised with data on transmissibility, severity, and vaccine effectiveness. We simulated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccine rollout in characteristic global settings with different population age-structures, contact patterns, health system capacities, prior transmission, and vaccine uptake. We quantified the impact of future vaccine booster dose strategies with both ancestral and variant-adapted vaccine products, while considering the potential future emergence of new variants with modified transmission, immune escape, and severity properties. We found that regular boosting of the oldest age group (75+) is an efficient strategy, although large numbers of hospitalisations and deaths could be averted by extending vaccination to younger age groups. In countries with low vaccine coverage and high infection-derived immunity, boosting older at-risk groups was more effective than continuing primary vaccination into younger ages in our model. Our study is limited by uncertainty in key parameters, including the long-term durability of vaccine and infection-induced immunity as well as uncertainty in the future evolution of the virus.CONCLUSIONS: Our modelling suggests that regular boosting of the high-risk population remains an important tool to reduce morbidity and mortality from current and future SARS-CoV-2 variants. Our results suggest that focusing vaccination in the highest-risk cohorts will be the most efficient (and hence cost-effective) strategy to reduce morbidity and mortality.</p

Timescales of Massive Human Entrainment

The past two decades have seen an upsurge of interest in the collective behaviors of complex systems composed of many agents entrained to each other and to external events. In this paper, we extend concepts of entrainment to the dynamics of human collective attention. We conducted a detailed investigation of the unfolding of human entrainment - as expressed by the content and patterns of hundreds of thousands of messages on Twitter - during the 2012 US presidential debates. By time locking these data sources, we quantify the impact of the unfolding debate on human attention. We show that collective social behavior covaries second-by-second to the interactional dynamics of the debates: A candidate speaking induces rapid increases in mentions of his name on social media and decreases in mentions of the other candidate. Moreover, interruptions by an interlocutor increase the attention received. We also highlight a distinct time scale for the impact of salient moments in the debate: Mentions in social media start within 5-10 seconds after the moment; peak at approximately one minute; and slowly decay in a consistent fashion across well-known events during the debates. Finally, we show that public attention after an initial burst slowly decays through the course of the debates. Thus we demonstrate that large-scale human entrainment may hold across a number of distinct scales, in an exquisitely time-locked fashion. The methods and results pave the way for careful study of the dynamics and mechanisms of large-scale human entrainment.Comment: 20 pages, 7 figures, 6 tables, 4 supplementary figures. 2nd version revised according to peer reviewers' comments: more detailed explanation of the methods, and grounding of the hypothese

Psychometric properties of the Spanish version of the Jefferson Scale of Empathy: making sense of the total score through a second order confirmatory factor analysis

Background: Empathy is a key aspect of the physician-patient interactions. The Jefferson Scale of Empathy (JSE) is one of the most used empathy measures of medical students. The development of cross-cultural empathy studies depends on valid and reliable translations of the JSE. This study sought to: (1) adapt and assess the psychometric properties in Spanish students of the Spanish JSE validated in Mexican students; (2) test a second order latent factor model. Methods: The Spanish JSE was adapted from the Spanish JSE-S, resulting in a final version of the measure. A non-probabilistic sample of 1104 medical students of two Spanish medical schools completed a socio-demographic and the Spanish JSE-S. Descriptive statistics, along with a confirmatory factor analysis, the average variance extracted (AVE), Cronbach's alphas and composite reliability (CR) coefficients were computed. An independent samples t-test was performed to access sex differences. Results: The Spanish JSE-S demonstrated acceptable to good sensitivity (individual items - except for item 2 - and JSE-S total score: -2.72 < Sk < 0.35 and -0.77 < Ku < 7.85), convergent validity (AVE: between 0.28 and 0.45) and reliability (Cronbach's alphas: between 0.62 and 0.78; CR: between 0.62 and 0.87). The confirmatory factor analysis supported the three-factor solution and the second order latent factor model. Conclusions: The findings provide support for the sensitivity, construct validity and reliability of the adapted Spanish JSE-S with Spanish medical students. Data confirm the hypothesized second order latent factor model. This version may be useful in future research examining empathy in Spanish medical students, as well as in cross-cultural studies.info:eu-repo/semantics/publishedVersio

Alterations in Epithelial and Mesenchymal Intestinal Gene Expression During Doxorubicin-Induced Mucositis in Mice

In the current study we aimed to gain insight into epithelial-mesenchymal cross-talk and progenitor compartment modulation during doxorubicin (DOX)-induced mucositis in mice. Intestinal segments were collected on various days after DOX treatment. DOX-induced damage at day 1–2 was characterized by increased epithelial proliferation and apoptosis and a decrease in the expression of epithelial differentiation markers. Concurrently, T-cell factor-4 (TCF4) levels increased and the epithelial differentiation enhancing factor, bone morphogenic protein-4 (BMP4), decreased. During severe damage (day 3), BMP4 levels were significantly increased, which inversely correlated with epithelial proliferation. At the same time, the expression of the epithelial differentiation markers was increasing again. At day 7, BMP4 levels were down-regulated, while the levels of the epithelial differentiation markers and TCF4 were normalized again. These data suggest that in response to DOX-induced damage, BMP4 and TCF4 are modulated in such a way that homeostasis of the progenitor compartment is partly preserved

Tsukushi Modulates Xnr2, FGF and BMP Signaling: Regulation of Xenopus Germ Layer Formation

Cell-cell communication is essential in tissue patterning. In early amphibian development, mesoderm is formed in the blastula-stage embryo through inductive interactions in which vegetal cells act on overlying equatorial cells. Members of the TGF-beta family such as activin B, Vg1, derrière and Xenopus nodal-related proteins (Xnrs) are candidate mesoderm inducing factors, with further activity to induce endoderm of the vegetal region. TGF-beta-like ligands, including BMP, are also responsible for patterning of germ layers. In addition, FGF signaling is essential for mesoderm formation whereas FGF signal inhibition has been implicated in endoderm induction. Clearly, several signaling pathways are coordinated to produce an appropriate developmental output; although intracellular crosstalk is known to integrate multiple pathways, relatively little is known about extracellular coordination

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.Peer reviewe

Report from Working Group 3: Beyond the standard model physics at the HL-LHC and HE-LHC

This is the third out of five chapters of the final report [1] of the Workshop on Physics at HL-LHC, and perspectives on HE-LHC [2]. It is devoted to the study of the potential, in the search for Beyond the Standard Model (BSM) physics, of the High Luminosity (HL) phase of the LHC, defined as $3$ ab$^{-1}$ of data taken at a centre-of-mass energy of 14 TeV, and of a possible future upgrade, the High Energy (HE) LHC, defined as $15$ ab$^{-1}$ of data at a centre-of-mass energy of 27 TeV. We consider a large variety of new physics models, both in a simplified model fashion and in a more model-dependent one. A long list of contributions from the theory and experimental (ATLAS, CMS, LHCb) communities have been collected and merged together to give a complete, wide, and consistent view of future prospects for BSM physics at the considered colliders. On top of the usual standard candles, such as supersymmetric simplified models and resonances, considered for the evaluation of future collider potentials, this report contains results on dark matter and dark sectors, long lived particles, leptoquarks, sterile neutrinos, axion-like particles, heavy scalars, vector-like quarks, and more. Particular attention is placed, especially in the study of the HL-LHC prospects, to the detector upgrades, the assessment of the future systematic uncertainties, and new experimental techniques. The general conclusion is that the HL-LHC, on top of allowing to extend the present LHC mass and coupling reach by $20-50\%$ on most new physics scenarios, will also be able to constrain, and potentially discover, new physics that is presently unconstrained. Moreover, compared to the HL-LHC, the reach in most observables will, generally more than double at the HE-LHC, which may represent a good candidate future facility for a final test of TeV-scale new physics

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic