NIHRDataInsights/HRCSData huggingface dataset:
Title: Optimising antibiotic prescribing for children with respiratory tract infections in general practice
Funder: Department of Health (England)

Abstract: OBJECTIVES: (1) To identify clinical consultation patterns, predisposing clinical risk factors and protective factors associated with childhood respiratory tract infection (RTI) complications. (2) To describe the socio-demographic profile of children presenting with common RTIs. (3) To explore the association between child socio-demographic factors and GPs' antibiotic prescribing for common childhood RTIs.DESIGN: Series of cohort, case-control and cross-sectional analyses. SETTING: General practiceEXPECTED OUTCOMES: (1) Mean consultation rates for children with different risk and protective factor profiles associated with RTI complications (bacterial pneumonia and recurrent tonsillitis, in particular). Risk profiles for mastoiditis and quinsy. (2) RTI consultation rates by age, sex, socio-economic status and ethnic group. (3) Antibiotic prescribing rates for children by age, sex, socio-economic status and ethnic group. ANTICIPATED BENEFITS: (1) A more comprehensive picture of preceding clinical patterns, potential risk and protective factors associated with RTI complications, including the effects of immunization. The development of risk profiling to assist practitioners regarding which children are at risk of RTI complications. This can be developed into an algorithm/template for history taking and decision-making to help prevent bacterial pneumonia, in particular. (2) and (3) Socio-demographic profiling of children presenting with RTIs will help to direct health promotion and public health resources. For example, providing education for parent groups whose children are frequent attenders for RTIs and/or who are prescribed higher levels of antibiotics (eg from specific ethnic groups).


Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS;6.1 PHARMACEUTICALS
Health categories: INFECTION
Title: How can we predict the outcome of therapy in genotype 3 hepatitis C infection?
Funder: Department of Health (England)

Abstract: Genotype 3 hepatitis C (HCV) is a major cause of liver disease in the UK. Many people who receive anti-viral treatment for genotype 3 HCV either do not respond, or the virus returns after the end of treatment. The reasons for this are unclear. We will examine specific genetic and immune features that may lead to treatment failure in a large group of patients with genotype 3 HCV. We expect to identify markers that predict how individuals will respond to anti-viral therapy, which will then be used to help guide treatment decisions for patients with genotype 3 HCV.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: INFECTION
Title: Herpes Simplex Virus encephalitis - the role of the inflammatory response in relation to outcome?
Funder: Department of Health (England)

Abstract: Encephalitis is a condition in which there is inflammation of the brain. Excluding epidemics, the most common cause is herpes simplex virus (HSV). Despite best treatment, 10-30% of patients die and 60% of survivors suffer nervous system disability. There is mounting evidence that a poor outcome is a result of excessive brain inflammation rather than by the virus killing nerve cells. Previous work by my supervisor, Professor Solomon, has shown that high levels of certain protein molecules that cause inflammation are present in spinal fluid of patients with poor outcomes when infected with a different virus. However, few have studied HSV, assessing a narrow protein range and not the amount of virus. Therefore, these studies cannot tell us whether the proteins present are due to a large amount of virus or excessive inflammation. I will undertake research to address the questions: In humans, which of these protein molecules causes the inflammation in HSV encephalitis and are they more closely related to a poor outcome than the amount of virus? This fellowship will extend Professor Solomon’s work by assessing viral load and specific targeted inflammation proteins and the all proteins in HSV encephalitis comparing between patients with severe and mild disease.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: INFECTION
Title: Barriers to access among HIV positive migrants in England: improving HIV testing, prevention and treatment services
Funder: Department of Health (England)

Abstract: BACKGROUND: Many migrants are unaware of their HIV infection and are more likely to be diagnosed late. Existing HIV prevention strategies need to be enhanced for migrant populations.OVERALL AIM: To improve access to HIV testing, prevention and treatment services for migrants in England by identifying the structural, cultural and socioeconomic barriers to service uptake. METHODS: 500 service users from seven HIV clinics and 1000 community-recruited migrants will complete an electronic survey. In-depth exploration of the issues will come from interviews with 25 survey respondents and 15 key informants from community organisations.RESULTS: Data will be integrated to provide understanding about how to improve HIV services. Results will also provide a platform for developing HIV interventions.


Research activity codes: 3.1 PRIMARY PREVENTION INTERVENTIONS TO MODIFY BEHAVIOURS OR PROMOTE WELL-BEING;4.5 RESOURCES AND INFRASTRUCTURE (DETECTION)
Health categories: INFECTION
Title: 2011 Doctoral Fellowships: An investigation into the effect of an antibotic cycling policy, based on retrospective time series analysis data, on the incidence of hospital acquired Mrs.A and CDAD
Funder: Health and Social Care Research and Development Division (HSC R&D) of Public Health Agency, Northern Ireland

Abstract: Healthcare associated infections are estimated to cost the NHS £1 billion per year with Methicillin Resistant Staphylococcus Aureus (Mrs.A) identified as the cause of one fifth of these infections. In addition, each case Clostridium Difficile-Associated Diarrhoea (CDAD) is estimated to cost the health service an extra £4000 which is incurred by an extra 21 days in hospital. These organisms are multifactorial problems and guidelines on controlling these infections focus on the importance of optimal infection control practices and the prudent use of antibiotics. The aim of this research is to test whether time series analysis can inform an antibiotic cycling policy such that hospital acquired Mrs.A and CDAD can be significantly reduced in Antrim Hospital. The relationship between antibiotic use, infection control practices and the incidence of Mrs.A and CDAD in Antrim Hospital between January 2006 and December 2010 will be studied using time series analysis. The results of this analysis will inform the optimal design of an antibiotic cycling policy according to the size and delay effects on Mrs.A and CDAD rates. This policy will be introduced into Antrim Hospital over a fourteen month period. During the first two months educational seminars will be run for medical, nursing and pharmacy staff to increase awareness of the new policy. Weekly audits will be carried out by pharmacy staff on all wards in the hospital to measure compliance with the cycling policy. The effects of the antibiotic cycling policy on Mrs.A and CDAD rates will be assessed using time series analysis.


Research activity codes: 8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE;6.1 PHARMACEUTICALS
Health categories: INFECTION
Title: Molecular mechanisms of antimicrobial peptides: phase changes induced in endotoxic bacterial lipopolysaccharide.
Funder: Engineering and Physical Sciences Research Council

Abstract: Antibiotics have long been used for treating a variety of diseases in humans. They are generally very useful as drugs because they are able to kill off the disease-causing organisms without producing harmful side effects in patients. Over recent years, however, many of these drugs have become less effective, and in some cases are now totally useless. The reason for this is that the disease-causing organisms have developed a resistance to the drugs / which means quite simply that they have found ways to avoid the drugs' toxic effects.This alarming rise in infections due to drug-resistant bacteria - like MRSA - has given rise to growing public concern, and has prompted a call for new antibiotics that can be used to treat patients infected with the drug-resistant organisms To trust to luck and hope for some chance discovery of a new drug (as with Fleming's discovery of penicillin, for example) is clearly not satisfactory: the problem of resistance is with us in the clinics now, and must be dealt with more speedily.A more sensible way forward is to design new drugs that work in novel ways, and one such class of compounds that might be exploited are the family of anti-bacterial peptides. Such an approach, of course, requires that we fully understand how these anti-bacterial peptides work, and unfortunately this is not the case. It is thought that the peptides might somehow interact with the bacterial outer surface - most likely with the fever-causing molecular building-blocks known as lipopolysaccharides. Precisely how the peptides interact with these lipopolysaccharides, however, is not yet established.In the research to be carried out at King's College London, the aim is to find out how anti-bacterial peptides work, looking in particular at the nature of their interaction with the bacterial lipopolysaccharides. The research will involve using microscopic, bubble-like structures known as liposomes or very thin layers of material which are the thickness of only one or two molecules, prepared using different bacterial lipoploysaccharides, so that they mimic bacterial cells and their surfaces. These bacterial structure mimics will then be studied using a combination of advanced analytical techniques, looking also at how the membrane structures are changed in the presence of the anti-microbial peptides. From the knowledge gained in these investigations, it is hoped to pave the way for others to design new and improved forms of antibiotic for use against antibiotic-resistant bacterial infections.


Research activity codes: 5.1 PHARMACEUTICALS
Health categories: INFECTION
Title: The interaction between host demography and tuberculosis transmission: disease dynamics, control and evolution.
Funder: Engineering and Physical Sciences Research Council

Abstract: TB is the leading single cause of death in humans due to an infectious agent. Approximately 30% of the world's population is latently infected and 0.1% has active disease. TB is characterised by long-term asymptomatic infection that can progress to active


Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS;8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE
Health categories: INFECTION
Title: Structure-function studies of antimicrobial and fusogenic peptides by solid state NMR spectroscopy and MD simulation
Funder: Engineering and Physical Sciences Research Council

Abstract: Context: Learning from biology, the focus for this work is the design of versatile and novel antibiotics, based around natural antimicrobial-active peptides, with significant potential for intelligent design and delivery - this will address a major health


Research activity codes: 5.1 PHARMACEUTICALS
Health categories: INFECTION
Title: ROADBLOCK: Towards Programmable Defensive Bacterial Coatings & Skins
Funder: Engineering and Physical Sciences Research Council

Abstract: This project fits the EPSRC Synthetic Biology Signpost.This application-driven research project will seek to integrate the creation of new computational algorithms, tools and theories for synthetic biology (SB) with well-established wet lab techniques t


Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES);5.3 MEDICAL DEVICES
Health categories: INFECTION
Title: Disease transmission and control in complex, structured populations
Funder: Engineering and Physical Sciences Research Council

Abstract: Infectious disease is the main thing that kills people. Some of the greatest improvements to human health have involved improvements in our understanding and control of germs - from John Snow's pioneering work on cholera in the 19th century to the eradication of smallpox in the 20th century. The 21st century sees a new set of challenges in the understanding and control of infections - while the eradication of polio progresses, we see new influenza strains causing or threatening pandemics, the continued progression of HIV and a massive health burden of often simply but expensively preventable diseases in the developing world.Epidemiology - the science of looking for significant patterns in cases of disease - has always been at the heart of controlling infectious diseases, and mathematics has always been central epidemiology.This project applies advanced mathematics to the science of epidemiology, making use of the large datasets and modern computational resources that are available. New insights about the structure of complex systems offer the promise of making massive advances in this field, through enhanced understanding of transmission routes of infection, risk factors and changes in the disease over time. These insights can in turn be combined with mathematical methods to design optimised interventions against infection so that diseases can be controlled in the most effective way.


Research activity codes: 3.2 INTERVENTIONS TO ALTER PHYSICAL AND BIOLOGICAL ENVIRONMENTAL RISKS;2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: INFECTION
Title: Novel simulation-based statistical inference with applications to epidemic models
Funder: Engineering and Physical Sciences Research Council

Abstract: Parametric models play a key role in statistical modelling. Parametric models assume that there is an underlying model giving rise to the data we observe with the data dependent upon certain parameters and random quantities. For example, for the spread of a disease, the model parameters dictate the infectiveness of the disease but who becomes infected will depend upon the model setup and randomness. In practice, we rarely know the parameters of the model and a key element of statistics is to obtain good estimates of the parameters. In Bayesian statistics the parameters have a posterior distribution which quantifies the uncertainty in the parameters of the model. By studying the posterior distribution we can calculate any summary statistics of the parameters we are interested in. However, a major drawback of Bayesian statistics is that the posterior distribution is rarely available in a form which we can easily use. There are a number of approaches for obtaining samples from the posterior distribution, the most common of which is MCMC. Recently a range of practical problems in statistical genetics have been identified where MCMC can either not be used or it is particularly difficult to do so. A solution has been provided in the form of the ABC (approximate Bayesian computation) algorithm. The ABC algorithm uses simulation from the model with parameters chosen via an appropriate mechanism, often the prior distribution, to estimate the parameters. (The prior distribution represents our prior beliefs about the model parameters.) The ABC algorithm formalises the idea that we simulate from the model with different parameters, accepting those parameter values which lead to simulated data in close agreement with the observed data. Both the MCMC and the ABC algorithms are iterative algorithms producing a single parameter from the posterior distribution at each iteration. Recently the investigator has introduced a new ABC algorithm which produces a set of parameters from the posterior distribution at each iteration. This new ABC algorithm is shown to be considerably more efficient than standard ABC algorithms, and has straightforwardly been applied to the analysis of epidemic models for the spread of infectious diseases. The aim of the proposed research is two-fold. Firstly, to develop more efficient MCMC and ABC algorithms which obtain sets of values from the posterior distribution. This should lead to more robust parameter estimation with lower uncertainty in parameter estimates based upon a sample of a given size. Secondly, to apply the new methods to a range of epidemic models to gain a better understanding of the spread of infectious diseases. In particular, the development of procedures which are easy to use and interpret by non-experts.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: INFECTION
Title: Bayesian Nonparametric Inference for Stochastic Epidemic Models
Funder: Engineering and Physical Sciences Research Council

Abstract: Understanding the spread of communicable infectious diseases is of great importance in order to prevent major future outbreaks and therefore it remains high on the global scientific agenda. It has been widely recognised that mathematical and statistical modelling has become a valuable tool in the analysis of infectious disease dynamics by supporting the development of control strategies, informing policy-making at the highest levels, and in general playing a fundamental role in the fight against the spread of disease. Despite the enormous attention given to the development of methods for efficient parameter estimation, there has been relatively little activity in the area of non-parametric inference. That is, drawing inference for the quantities which govern transmission, i) the force of infection and ii) the period during which an individual remains infectious, without making certain modelling assumptions about its (parametric) functional form or that it belongs to a certain family of parametric distributions. The proposed research is concerned with the development of new methodology which will enable non-parametric estimation of the parameters which govern transmission within a Bayesian framework and the application of the proposed methods to large disease outbreak datasets.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: INFECTION
Title: Towards NanoMedicine Interventions for HIV/AIDS
Funder: Engineering and Physical Sciences Research Council

Abstract: Nanomedicines have proven extremely valuable in recent years and many are used daily to treat patients with a range of conditions or needs - from the treatment of cancer and menopausal symptoms to the prevention of organ rejection or malnutrition/weight loss. A range of unmet clinical needs may benefit considerably from the research and application of new nanoparticle synthesis techniques and the development of appropriate nanomedicines and provision of scale-able, commercially viable technologies that can impact patient outcomes is a key goal of nanomedicine research. Validation of new technologies through optimisation of product performance, demonstration of pharmaceutically relevant manufacturing and in-man pharmacokinetic studies is critical for progression as is the study of nanotoxicology to establish a safety assessment that supports future investment. To date, a series of candidate nanomedicines for HIV/AIDS treatment have been generated at the University of Liverpool in collaboration with IOTA NanoSolutions Ltd, a specialist start-up company in the UK, and supported by RCUK funding. IOTA is commercialising a novel nanoparticle synthesis technology (initially developed at UoL with EPSRC funding support) that rivals the most successful commercial top-down nanomedicine technology - nanomilling. The HIV/AIDS nanomedicine candidates have been the subject of 3 patent filings and funds are sought to optimise their production and establish their behaviour using clinical research techniques. Additionally the project will seek to dramatically increase the understanding of nanomedicine through fundamental mechanistic studies, thereby producing new insight into the mode of action and the safety of future nanomedicines. If successful, the programme will produce the first nanomedicine options for HIV/AIDS therapy with benefits for patient care potentially including lower dosing, reduced side effects, better patient-to-patient consistency and a reduction of tablet size. Significant interest has been generated within Medecins Sans Frontiere who are keen to utilise the outputs for charitable medicines in the developing world, treating children with HIV infection with better products and prevent HIV infection in newborns. Currently, to prevent transmission of HIV to children from infected mothers, the World Heath Organisation has recommended dosing from 3 weeks after birth with antiretrovirals. The only children's medicines available include high levels of alcohol to dissolve the poorly water-soluble drugs. The nanomedcines within this programme are dispersible in water and offer a step-forward in paediatric therapy. The successful establishment of the fundamental research underpinning new nanomedicines will provide a clear advance in the UK's global standing in this emerging area, currently valued at >US$75bn and growing rapidly, with expectations to reach >US$100bn within 3 years.


Research activity codes: 5.1 PHARMACEUTICALS
Health categories: INFECTION
Title: Microplasma-assisted manipulation of intact airborne bacteria for real-time autonomous detection
Funder: Engineering and Physical Sciences Research Council

Abstract: In this project we are proposing a new method of directly detecting airborne bacteria. In many fields, the dangers of infection by pathogens, for example anthrax, need to be faced and there are major challenges with existing techniques in quickly assessing the danger so that rapid public safety responses are possible . Current techniques may be slow, expensive or need trained people and specialised laboratories. We want to devise a detection technique based on accurate measurement of a number of physical characteristics of bacteria that will allow differentiation of even similar strains so that the true pathogens can be clearly identified. This is a difficult challenge and further, we aim to show in our proof of principle, that it will be possible to design a detector that is low cost, reasonably portable and can work autonomously i.e. without continuous human intervention. Success would then encourage the development and deployment of this remote monitoring technology in critical public spaces, for example large public events and hospitals.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: INFECTION