A5091549401- COVID-19 epidemiological studies
- Statistical Methods and Bayesian Inference
- Bayesian Methods and Mixture Models
- Markov Chains and Monte Carlo Methods
- Gaussian Processes and Bayesian Inference
- Antimicrobial Resistance in Staphylococcus
- Bacterial Identification and Susceptibility Testing
- Quantum Information and Cryptography
- Influenza Virus Research Studies
- Animal Disease Management and Epidemiology
- Hearing, Cochlea, Tinnitus, Genetics
- Statistical Distribution Estimation and Applications
- Advanced Statistical Process Monitoring
- Complex Systems and Time Series Analysis
- Antibiotic Resistance in Bacteria
- Banking stability, regulation, efficiency
- Plant and animal studies
- Insect-Plant Interactions and Control
- Virology and Viral Diseases
- Hearing Loss and Rehabilitation
- Gene Regulatory Network Analysis
- Clostridium difficile and Clostridium perfringens research
- Advanced Neuroimaging Techniques and Applications
- Plant Parasitism and Resistance
- Bacillus and Francisella bacterial research
University of Nottingham
2016-2025
Karolinska Institutet
2021
Charité - Universitätsmedizin Berlin
2017
Laboratoire d’Analyse et de Mathématiques Appliquées
2016
Université Gustave Eiffel
2016
University of Manchester
2016
Infectious diseases both within human and animal populations often pose serious health socioeconomic risks. From a statistical perspective, their prediction is complicated by the fact that no two epidemics are identical due to changing contact habits, mutations of infectious agents, behaviour in response presence an epidemic. Thus model parameters governing mechanisms will typically be unknown. On other hand, epidemic control strategies need decided rapidly as data accumulate. In this paper...
Background Identifying and tackling the social determinants of infectious diseases has become a public health priority following recognition that individuals with lower socioeconomic status are disproportionately affected by diseases. In many parts world, epidemiologically genotypically defined community-associated (CA) methicillin-resistant Staphylococcus aureus (MRSA) strains have emerged to frequent causes hospital infection. The aim this study was use spatial models adjustment for...
Tinnitus is a common medical condition which interfaces many different disciplines, yet it not priority for any individual discipline. A change in its scientific understanding and clinical management requires shift toward multidisciplinary cooperation, only research but also training. The European School Interdisciplinary (ESIT) brings together unique consortium of practitioners, academic researchers, commercial partners, patient organizations, public health experts to conduct innovative...
The heterogeneity of tinnitus is substantial. Its numerous pathophysiological mechanisms and clinical manifestations have hampered fundamental treatment research significantly. A decade ago, the Tinnitus Research Initiative introduced Sample Case History Questionnaire, a case history instrument for standardised collection information about characteristics patient. Since then, number studies been published which characterise individuals groups using data collected with this questionnaire....
Screening and isolation are central components of hospital methicillin-resistant Staphylococcus aureus (MRSA) control policies. Their prevention patient-to-patient spread depends on minimizing undetected unisolated MRSA-positive patient days. Estimating these days the reduction in transmission due to presents a major methodological challenge, but is essential for assessing both value existing policies potential benefit new rapid MRSA detection technologies. Recent developments have made it...
Whole genome sequencing of pathogens from multiple hosts in an epidemic offers the potential to investigate who infected whom with unparalleled resolution, potentially yielding important insights into disease dynamics and impact control measures. We considered outbreaks a setting dense genomic sampling, formulated stochastic models person-to-person transmission, based on observed epidemiological data. constructed which genetic distance between sampled genotypes depends relationship hosts. A...
Monitoring the incidence of new infections during a pandemic is critical for an effective public health response. General population prevalence surveys SARS-CoV-2 can provide high-quality data to estimate incidence. However, estimation relies on understanding distribution duration that remain detectable. This study addresses this need using from Coronavirus Infection Survey (CIS), long-term, longitudinal, general survey conducted in UK. Analyzing these presents unique challenges, such as...
Infection control for hospital pathogens such as methicillin-resistant Staphylococcus aureus (MRSA) often takes the form of a package interventions, including use patient isolation and decolonization treatment. Such though widely used, have generated controversy because their significant resource implications lack robust evidence with regard to effectiveness at reducing transmission. The aim this study was estimate measures in MRSA transmission general wards. Prospectively collected...
Mutual interference involves direct interactions between individuals of the same species that may alter their foraging success. Larvae aphidophagous coccinellids typically stay within a patch during lifetime, displaying remarkable aggregation to prey. Thus, as larvae are exposed each other, frequent encounters affect A study was initiated in order determine effect mutual coccinellids' feeding rate. One four 4th larval instars fourteen-spotted ladybird beetle Propylea quatuordecimpunctata...
As quantum tomography is becoming a key component of the engineering toolbox, there need for deeper understanding multitude estimation methods available. Here we investigate and compare several such methods: maximum likelihood, least squares, generalised positive thresholded squares projected squares. The common thread analysis that each estimator projects measurement data onto parameter space with respect to specific metric, thus allowing us study relationships between different estimators.
This paper considers novel Bayesian non-parametric methods for stochastic epidemic models. Many standard modeling and data analysis use underlying assumptions (e.g. concerning the rate at which new cases of disease will occur) are rarely challenged or tested in practice. To relax these assumptions, we develop a approach using Gaussian Processes, specifically to estimate infection process. The illustrated with both simulated real sets, former illustrating that can recover true process quite...
Abstract Dairy slurry is a major source of environmental contamination with antimicrobial resistant genes and bacteria. We developed mathematical models conducted on-farm research to explore the impact wastewater flows management practices on resistance (AMR) in slurry. Temporal fluctuations cephalosporin-resistant Escherichia coli were observed attributed farm activities, specifically disposal spent copper zinc footbath into system. Our model revealed that should be more frequently relevant...
Introduction. Antimicrobial resistance and bacterial virulence factors may increase the risk of hematogenous complications during methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infection (BSI). This study reports on impact increasing vancomycin minimum inhibitory concentrations (V-MICs) MRSA clone type from BSI implementation an effective control program. Methods. In sum, spa typing, staphylococcal cassette chromosome mec allotyping, teicoplanin MICs were performed 821...
The statistical analysis of measurement data has become a key component many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional systems, one needs to exploit prior information and the 'sparsity' properties experimental in order reduce dimensionality estimation problem. In this paper we propose model selection as general principle finding simplest, or most parsimonious explanation data, by fitting different models choosing estimator...
The packet loss characteristics of Internet paths that include residential broadband links are not well understood, and there no good models for their behaviour. This complicates the design real-time video applications targeting home users, since it is difficult to choose appropriate error correction concealment algorithms without a model types observed. Using measurements networks in UK Finland, we show existing loss, such as Gilbert simple hidden Markov models, do effectively patterns seen...
An important determinant of a pathogen's success is the rate at which it transmitted from infected to susceptible hosts. Although there are anecdotal reports that methicillin-resistant Staphylococcus aureus (MRSA) clones vary in their transmissibility hospital settings, attempts quantify such variation lacking for common subtypes, as methods addressing this question using routinely-collected MRSA screening data endemic settings. Here we present method time-varying different subtypes...
Waste from dairy production is one of the largest sources contamination antimicrobial resistant bacteria (ARB) and genes (ARGs) in many parts world. However, studies to date do not provide necessary evidence inform resistance (AMR) countermeasures. We undertook a detailed, interdisciplinary, longitudinal analysis slurry waste. The contained population ARB ARGs, with resistances current, historical never-used on-farm antibiotics; were associated Gram-negative Gram-positive mobile elements...
Abstract. A stochastic epidemic model is defined in which each individual belongs to a household, secondary grouping (typically school or workplace) and also the community as whole. Moreover, infectious contacts take place these three settings according potentially different rates. For this model, we consider how kinds of data can be used estimate infection rate parameters with view understanding what cannot inferred. Among other things find that temporal considerable inferential benefit...
Many modern statistical applications involve inference for complicated stochastic models which the likelihood function is difficult or even impossible to calculate, and hence conventional likelihood-based inferential techniques cannot be used. In such settings, Bayesian can performed using Approximate Computation (ABC). However, in spite of many recent developments ABC methodology, computational cost necessitates choice summary statistics tolerances that potentially severely bias estimate...
Background and Purpose— Chronic hypoperfusion in the mouse brain has been suggested to mimic aspects of vascular cognitive impairment, such as white matter damage. Although this model attracted attention, our group struggled generate a reliable pathological phenotype. This study aimed identify neuroimaging biomarkers pathology aged, more severely hypoperfused mice. Methods— We used magnetic resonance imaging characterize degeneration mice by refining surgical procedure use smallest reported...