ORCID Profile
0000-0003-3002-6300
Current Organisation
Aalborg Universitet
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Cold Spring Harbor Laboratory
Date: 05-05-2020
DOI: 10.1101/2020.04.30.20085662
Abstract: The global impact of COVID-19 and the country-specific responses to the pandemic provide an unparalleled opportunity to learn about different patterns of the outbreak and interventions. We model the global pattern of trajectories of reported COVID-19 cases during the primary response period, with the aim of learning from the past to prepare for the future. Using Bayesian methods, we analyse the response to the COVID-19 outbreak for 158 countries for the period 22 January to 9 June 2020. This encompasses the period in which many countries imposed a variety of response measures and initial relaxation strategies. Instead of modelling specific intervention types and timings for each country explicitly, we adopt a stochastic epidemiological model including a feedback mechanism on virus transmission to capture complex nonlinear dynamics arising from continuous changes in community behaviour in response to rising case numbers. We analyse the overall effect of interventions and community responses across erse regions. This approach mitigates explicit consideration of issues such as period of infectivity and public adherence to government restrictions. Countries with the largest cumulative case tallies are characterised by a delayed response, whereas countries that avoid substantial community transmission during the period of study responded quickly. Countries that recovered rapidly also have a higher case identification rate and small numbers of undocumented community transmission at the early stages of the outbreak. We also demonstrate that uncertainty in numbers of undocumented infections dramatically impacts the risk of second waves. Our approach is also effective at pre-empting potential second waves and flare-ups. We demonstrate the utility of modelling to interpret community behaviour in the early epidemic stages. Two lessons learnt that are important for the future are: i) countries that imposed strict containment measures early in the epidemic fared better with respect to numbers of reported cases and ii) broader testing is required early in the epidemic to understand the magnitude of undocumented infections and recover rapidly. We conclude that clear patterns of containment are essential prior to relaxation of restrictions and show that modelling can provide insights to this end.
Publisher: Oxford University Press (OUP)
Date: 27-02-2018
DOI: 10.1093/JAC/DKY040
Abstract: Fluoroquinolone resistance (FQR) in third-generation cephalosporin-resistant Enterobacteriaceae (3GCRE) presents serious limitations to antibiotic therapy. The aim of this study was to investigate whether the FQR proportion among 3GCRE differs between community-acquired (CA) and hospital-acquired (HA) isolates. In a prospective observational study covering 2014 and 2015, we monitored the occurrence of 3GCRE in adult hospitalized patients in six German university hospitals. 3GCRE clinical isolates were sub ided into CA and HA. Multivariable analysis identified factors associated with in vitro non-susceptibility to ciprofloxacin. The dataset included 5721 3GCRE isolates of which 52.9% were HA and 52.7% exhibited FQR. Interestingly, the FQR proportion was higher in CA 3GCRE than in HA 3GCRE (overall, 60.1% versus 46.2%, respectively, P < 0.001). Multivariable analysis adjusting for age confirmed community acquisition as a risk factor for FQR [adjusted rate ratio (aRR) 1.33, 95% CI 1.17-1.53]. Escherichia coli and Klebsiella spp. were associated with a much higher FQR proportion than other Enterobacteriaceae species (aRR 8.14, 95% CI 6.86-9.65 and aRR 7.62 with 95% CI 6.74-8.61, respectively). The high FQR proportion observed among CA 3GCRE, particularly in E. coli and Klebsiella spp., indicates that selection pressure in the outpatient setting needs to be addressed with antibiotic stewardship and other interventions in order to limit further spread of MDR.
Publisher: Foundation for Open Access Statistic
Date: 2020
Publisher: Elsevier BV
Date: 10-2023
Publisher: MDPI AG
Date: 15-09-2021
DOI: 10.3390/MET11091464
Abstract: Lubricant has been widely applied to reduce wear and friction between the contact surfaces when they are in relative motion. In the current study, a nonequilibrium molecular dynamics (NEMD) simulation was specifically established to conduct a comprehensive investigation on the dynamic contact between two iron surfaces in a boundary friction system considering the mixed C4-alkane and nanoparticles as lubricant. The main research objective was to explore the effects of fluid and nanoparticles addition on the surface contact and friction force. It was found that nanoparticles acted like ball bearings between the contact surfaces, leading to a change of sliding friction mode to rolling friction mode. Under normal loads, plastic deformation occurred at the top surface because nanoparticles were mainly supporting the normal load. By increasing the number of C4-alkane molecules between two contact surfaces, the contact condition has been changed from partial to full lubrication. In addition, an attractive force from the solid–liquid LJ interaction between C4-alkane and surfaces was observed at the early stage of sliding, due to the large space formed by wall surfaces and nanoparticles. The findings in this paper would be beneficial for understanding the frictional behavior of a simple lubricant with or without nanoparticles addition in a small confinement.
Publisher: Oxford University Press (OUP)
Date: 06-2021
DOI: 10.1111/RSSC.12487
Abstract: Dynamic queueing networks (DQN) model queueing systems where demand varies strongly with time, such as airport terminals. With rapidly rising global air passenger traffic placing increasing pressure on airport terminals, efficient allocation of resources is more important than ever. Parameter inference and quantification of uncertainty are key challenges for developing decision support tools. The DQN likelihood function is, in general, intractable and current approaches to simulation make likelihood-free parameter inference methods, such as approximate Bayesian computation (ABC), infeasible since simulating from these models is computationally expensive. By leveraging a recent advance in computationally efficient queueing simulation, we develop the first parameter inference approach for DQNs. We demonstrate our approach with data of passenger flows in a real airport terminal, and we show that our model accurately recreates the behaviour of the system and is useful for decision support. Special care must be taken in developing the distance for ABC since any useful output must vary with time. We use maximum mean discrepancy, a metric on probability measures, as the distance function for ABC. Prediction intervals of performance measures for decision support tools are easily constructed using draws from posterior s les, which we demonstrate with a scenario of a delayed flight.
Publisher: Oxford University Press (OUP)
Date: 30-01-2023
DOI: 10.1093/ECCO-JCC/JJAC190.0011
Abstract: Early treatment of Crohn’s disease (CD) often involves biologics such as anti-tumor necrosis factor (anti-TNF) agents. Ileocecal resection (ICR), while a therapeutic option in early CD, is generally reserved for complicated CD or when medical treatment fails. We aimed to compare long-term outcomes of ICR and anti-TNF therapy as index treatment for ileocecal CD, initiated within one year of diagnosis, in the Danish nationwide cohort. Using cross-linked nationwide registers, we identified all in iduals who lived in Denmark and were diagnosed with ileal CD between 2003 and 2018. We included in iduals who underwent ICR or received anti-TNF drugs as index treatment for ileocecal CD within one year of diagnosis. We excluded patients who did not have pathology information confirming disease in the ileocecal region. The primary outcome was a composite of CD-related hospitalization, systemic corticosteroid exposure, CD-related surgery, and perianal CD diagnosis. We conducted Cox proportional hazards regression analyses to compare outcomes in the two groups after adjusting for potential confounders. We also determined the proportion of in iduals initiated on immunomodulator (IMM), anti-TNF, or no therapy at 5 years after ICR. Of the 16,443 in iduals diagnosed with ileocecal CD between 2003 and 2018, 581 (3.5%) and 698 (4.2%) in iduals with confirmed disease in the ileocecal region underwent ICR and received anti-TNF as the index treatment, respectively. The composite outcome occurred in 273 in iduals (IR 110.3/100,0 person years (PY)) in the ICR group and in 318 in iduals (IR 201.9/100,0 PY) in the anti-TNF group. The risk of the composite outcome was 33% lower in the ICR group compared to the anti-TNF group (aHR 0.67 95% CI 0.54, 0.83), after adjusting for demographic and clinical variables. On analysis of in idual outcomes, ICR was associated with reduced risk of systemic corticosteroid exposure and CD-related surgery, but not CD-related hospitalization or perianal CD diagnosis. Of in iduals who underwent ICR, the proportion that was initiated on IMM, anti-TNF treatment or no treatment at 5 years of follow up was 47.5%, 17.1%, and 50.3%, respectively. These data support the role of ICR as an index treatment for ileocecal CD and challenge the current paradigm of reserving surgery for complicated CD refractory or intolerant to medications. Further studies will help identify characteristics of in iduals who needed no treatment after ICR.
Publisher: MDPI AG
Date: 07-09-2021
DOI: 10.3390/STATS4030045
Abstract: Approximate Bayesian computation is a likelihood-free inference method which relies on comparing model realisations to observed data with informative distance measures. We obtain functional data that are not only subject to noise along their y axis but also to a random warping along their x axis, which we refer to as the time axis. Conventional distances on functions, such as the L2 distance, are not informative under these conditions. The Fisher–Rao metric, previously generalised from the space of probability distributions to the space of functions, is an ideal objective function for aligning one function to another by warping the time axis. We assess the usefulness of alignment with the Fisher–Rao metric for approximate Bayesian computation with four ex les: two simulation ex les, an ex le about passenger flow at an international airport, and an ex le of hydrological flow modelling. We find that the Fisher–Rao metric works well as the objective function to minimise for alignment however, once the functions are aligned, it is not necessarily the most informative distance for inference. This means that likelihood-free inference may require two distances: one for alignment and one for parameter inference.
Publisher: Wiley
Date: 12-08-2019
Publisher: Springer Science and Business Media LLC
Date: 12-2020
DOI: 10.1186/S12889-020-09972-Z
Abstract: The global impact of COVID-19 and the country-specific responses to the pandemic provide an unparalleled opportunity to learn about different patterns of the outbreak and interventions. We model the global pattern of reported COVID-19 cases during the primary response period, with the aim of learning from the past to prepare for the future. Using Bayesian methods, we analyse the response to the COVID-19 outbreak for 158 countries for the period 22 January to 9 June 2020. This encompasses the period in which many countries imposed a variety of response measures and initial relaxation strategies. Instead of modelling specific intervention types and timings for each country explicitly, we adopt a stochastic epidemiological model including a feedback mechanism on virus transmission to capture complex nonlinear dynamics arising from continuous changes in community behaviour in response to rising case numbers. We analyse the overall effect of interventions and community responses across erse regions. This approach mitigates explicit consideration of issues such as period of infectivity and public adherence to government restrictions. Countries with the largest cumulative case tallies are characterised by a delayed response, whereas countries that avoid substantial community transmission during the period of study responded quickly. Countries that recovered rapidly also have a higher case identification rate and small numbers of undocumented community transmission at the early stages of the outbreak. We also demonstrate that uncertainty in numbers of undocumented infections dramatically impacts the risk of multiple waves. Our approach is also effective at pre-empting potential flare-ups. We demonstrate the utility of modelling to interpret community behaviour in the early epidemic stages. Two lessons learnt that are important for the future are: i) countries that imposed strict containment measures early in the epidemic fared better with respect to numbers of reported cases and ii) broader testing is required early in the epidemic to understand the magnitude of undocumented infections and recover rapidly. We conclude that clear patterns of containment are essential prior to relaxation of restrictions and show that modelling can provide insights to this end.
No related grants have been discovered for Anthony Ebert.