411 research outputs found

    Alternative Covid-19 mitigation measures in school classrooms:analysis using an agent-based model of SARS-CoV-2 transmission

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    The SARS-CoV-2 epidemic has impacted children's education, with schools required to implement infection control measures that have led to periods of absence and classroom closures. We developed an agent-based epidemiological model of SARS-CoV-2 transmission in a school classroom that allows us to quantify projected infection patterns within primary school classrooms, and related uncertainties. Our approach is based on a contact model constructed using random networks, informed by structured expert judgement. The effectiveness of mitigation strategies in suppressing infection outbreaks and limiting pupil absence are considered. COVID-19 infections in primary schools in England in autumn 2020 were re-examined and the model was then used to estimate infection levels in autumn 2021, as the Delta variant was emerging and it was thought likely that school transmission would play a major role in an incipient new wave of the epidemic. Our results were in good agreement with available data. These findings indicate that testing-based surveillance is more effective than bubble quarantine, both for reducing transmission and avoiding pupil absence, even accounting for insensitivity of self-administered tests. Bubble quarantine entails large numbers of absences, with only modest impact on classroom infections. However, maintaining reduced contact rates within the classroom can have a major benefit for managing COVID-19 in school settings

    Alternative Covid-19 mitigation measures in school classrooms:analysis using an agent-based model of SARS-CoV-2 transmission

    Get PDF
    The SARS-CoV-2 epidemic has impacted children's education, with schools required to implement infection control measures that have led to periods of absence and classroom closures. We developed an agent-based epidemiological model of SARS-CoV-2 transmission in a school classroom that allows us to quantify projected infection patterns within primary school classrooms, and related uncertainties. Our approach is based on a contact model constructed using random networks, informed by structured expert judgement. The effectiveness of mitigation strategies in suppressing infection outbreaks and limiting pupil absence are considered. COVID-19 infections in primary schools in England in autumn 2020 were re-examined and the model was then used to estimate infection levels in autumn 2021, as the Delta variant was emerging and it was thought likely that school transmission would play a major role in an incipient new wave of the epidemic. Our results were in good agreement with available data. These findings indicate that testing-based surveillance is more effective than bubble quarantine, both for reducing transmission and avoiding pupil absence, even accounting for insensitivity of self-administered tests. Bubble quarantine entails large numbers of absences, with only modest impact on classroom infections. However, maintaining reduced contact rates within the classroom can have a major benefit for managing COVID-19 in school settings

    Age-dependent patterns of bovine tuberculosis in cattle.

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    Bovine tuberculosis (BTB) is an important livestock disease, seriously impacting cattle industries in both industrialised and pre-industrialised countries. Like TB in other mammals, infection is life long and, if undiagnosed, may progress to disease years after exposure. The risk of disease in humans is highly age-dependent, however in cattle, age-dependent risks have yet to be quantified, largely due to insufficient data and limited diagnostics. Here, we estimate age-specific reactor rates in Great Britain by combining herd-level testing data with spatial movement data from the Cattle Tracing System (CTS). Using a catalytic model, we find strong age dependencies in infection risk and that the probability of detecting infection increases with age. Between 2004 and 2009, infection incidence in cattle fluctuated around 1%. Age-specific incidence increased monotonically until 24-36 months, with cattle aged between 12 and 36 months experiencing the highest rates of infection. Beef and dairy cattle under 24 months experienced similar infection risks, however major differences occurred in older ages. The average reproductive number in cattle was greater than 1 for the years 2004-2009. These methods reveal a consistent pattern of BTB rates with age, across different population structures and testing patterns. The results provide practical insights into BTB epidemiology and control, suggesting that targeting a mass control programme at cattle between 12 and 36 months could be beneficial.EBP is funded by an Engineering and Physical Sciences Research Council (EPSRC) fellowship. JLNW is supported by the Alborada Trust and the RAPIDD program of the Science & Technology Directorate, U.S. Department of Homeland Security, and the Fogarty International Center, U.S. National Institutes of Health. AJKC is supported by Defra grant no. SE-3127. TJM is supported by the BBSRC. We thank Steve Holdship and Rose Nicholson at Defra the AHVLA team for providing access to the CTS and VetNet

    Economic Pressure and Intention to Complete Colorectal Cancer Screening: A Cross-Sectional Analysis Among U.S. Men

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    Although men’s lives can be saved by colorectal cancer (CRC) screening, its utilization remains below national averages among men from low-income households. However, income has not been consistently linked to men’s CRC screening intent. This study tested the hypothesis that men who perceive more economic pressure would have lower CRC screening intent. Cross-sectional data were collected via an online survey in February 2022. Men (aged 45–75 years) living in the U.S. (N = 499) reported their CRC screening intent (outcome) and their perception of their economic circumstances (predictors). Adjusted binary and ordinal logistic analyses were conducted. All analyses were conducted in March 2022. Men who perceived greater difficulty paying bills or affording the type of clothing or medical care they needed (i.e., economic strain) were less likely to have CRC screening intent (OR = 0.67, 95% CI: 0.49, 0.93). This association was no longer significant when prior screening behavior was accounted for (OR = 0.75, 95% CI: 0.52, 1.10). Contrary to our hypothesis, men who reported more financial cutbacks were more likely to report wanting to be screened for CRC within the next year (OR = 1.06, 95% CI: 1.01, 1.11). This is one of the first studies to demonstrate that men’s perceptions of their economic circumstances play a role in their intent to complete early-detection screening for CRC. Future research should consider men’s perceptions of their economic situation in addition to their annual income when aiming to close the gap between intent and CRC screening uptake

    Social network analysis and whole genome sequencing in a cohort study to investigate TB transmission in an educational setting

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    Abstract Background TB outbreaks in educational institutions can result in significant transmission and pose a considerable threat to TB control. Investigation using traditional microbiological and epidemiological tools can lead to imprecise screening strategies due to difficulties characterising complex transmission networks. Application of whole genome sequencing (WGS) and social network analysis can provide additional information that may facilitate rapid directed public health action. We report the utility of these methods in combination with traditional approaches for the first time to investigate a TB outbreak in an educational setting. Methods Latent tuberculosis infection (LTBI) cases were screenees with a positive T-SPOT®.TB test. Active TB cases were defined through laboratory confirmation of M. tuberculosis on culture or through clinical or radiological findings consistent with infection. Epidemiological data were collected from institutional records and screenees. Samples were cultured and analysed using traditional M. tuberculosis typing and WGS. We undertook multivariable multinomial regression and social network analysis to identify exposures associated with case status and risk communities. Results We identified 189 LTBI cases (13.7% positivity rate) and nine active TB cases from 1377 persons screened. The LTBI positivity rate was 39.1% (99/253) among persons who shared a course with an infectious case (odds ratio 7.3, 95% confidence interval [CI] 5.2 to 10.3). The community structure analysis divided the students into five communities based on connectivity, as opposed to the 11 shared courses. Social network analysis identified that the community including the suspected index case was at significantly elevated risk of active disease (odds ratio 7.5, 95% CI 1.3 to 44.0) and contained eight persons who were lost to follow-up. Five sputum samples underwent WGS, four had zero single nucleotide polymorphism (SNP) differences and one had a single SNP difference. Conclusion This study demonstrates the public health impact an undiagnosed case of active TB disease can have in an educational setting within a low incidence area. Social network analysis and whole genome sequencing provided greater insight to evolution of the transmission network and identification of communities of risk. These tools provide further information over traditional epidemiological and microbiological approaches to direct public health action in this setting

    Facial trustworthiness and criminal sentencing: A comment on Wilson and Rule (2015)

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    Our first impressions of others, whether accurate or unfounded, have real-world consequences in terms of how we judge and treat those people. Previous research has suggested that criminal sentencing is influenced by the perceived facial trustworthiness of defendants in murder trials. In real cases, those who appeared less trustworthy were more likely to receive death rather than life sentences. Here, we carried out several attempts to replicate this finding, utilizing the original set of stimuli (Study 1), multiple images of each identity (Study 2), and a larger sample of identities (Study 3). In all cases, we found little support for the association between facial trustworthiness and sentencing. Furthermore, there was clear evidence that the specific image chosen to depict each identity had a significant influence on subsequent judgments. Taken together, our findings suggest that perceptions of facial trustworthiness have no real-world influence on sentencing outcomes in serious criminal cases

    High COVID-19 transmission potential associated with re-opening universities can be mitigated with layered interventions

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    Reopening of universities to students following COVID-19 restrictions risks increased transmission due to high numbers of social contacts and the potential for asymptomatic transmission. Here, the authors use a mathematical model with social contact data to estimate the impacts of reopening a typical non-campus based university in the UK

    Meta-analysis for individual participant data with a continuous exposure: A case study

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    OBJECTIVE: Methods for meta-analysis of studies with individual participant data and continuous exposure variables are well described in the statistical literature but are not widely used in clinical and epidemiological research. The purpose of this case study is to make the methods more accessible. STUDY DESIGN AND SETTING: A two-stage process is demonstrated. Response curves are estimated separately for each study using fractional polynomials. The study-specific curves are then averaged pointwise over all studies at each value of the exposure. The averaging can be implemented using fixed effects or random effects methods. RESULTS: The methodology is illustrated using samples of real data with continuous outcome and exposure data and several covariates. The sample data set, segments of Stata and R code, and outputs are provided to enable replication of the results. CONCLUSION: These methods and tools can be adapted to other situations, including for time-to-event or categorical outcomes, different ways of modelling exposure-outcome curves, and different strategies for covariate adjustment

    Contacts and behaviours of university students during the COVID-19 pandemic at the start of the 2020/2021 academic year

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    University students have unique living, learning and social arrangements which may have implications for infectious disease transmission. To address this data gap, we created CONQUEST (COroNavirus QUESTionnaire), a longitudinal online survey of contacts, behaviour, and COVID-19 symptoms for University of Bristol (UoB) staff/students. Here, we analyse results from 740 students providing 1261 unique records from the start of the 2020/2021 academic year (14/09/2020–01/11/2020), where COVID-19 outbreaks led to the self-isolation of all students in some halls of residences. Although most students reported lower daily contacts than in pre-COVID-19 studies, there was heterogeneity, with some reporting many (median = 2, mean = 6.1, standard deviation = 15.0; 8% had ≥ 20 contacts). Around 40% of students’ contacts were with individuals external to the university, indicating potential for transmission to non-students/staff. Only 61% of those reporting cardinal symptoms in the past week self-isolated, although 99% with a positive COVID-19 test during the 2 weeks before survey completion had self-isolated within the last week. Some students who self-isolated had many contacts (mean = 4.3, standard deviation = 10.6). Our results provide context to the COVID-19 outbreaks seen in universities and are available for modelling future outbreaks and informing policy
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