Epidemiology and Risk Analysis
This theme brings together a multidisciplinary team of scientists to gain insight into the epidemiology of key emerging and zoontoic infections. Studies will be designed and data analysed using state of the art statistical, epidemiological and dynamic modelling methods, to understand transmission, quanitify risks and, where possible, to evaluate potential control measures.
Long-term objectives:
- To inform diagnostic development and validation, outbreak control policies, and pathogenesis studies using samples and datasets from UKHSA/HPRU partners.
- Determine the distribution of Lyme Disease risk around the country to inform the provision of pubic health advice by the UKHSA and improve the awareness and management of Lyme disease by health professionals.
- Develop, test and implement methods for estimating HCID nosocomial transmission risk and the impact of interventions.
Project 4.1: Epidemiological analysis and modelling of COVID-19, MERS and other HCID transmission risks
Professor Christl Donnelly
Theme Lead
University of Oxford
Ruth McCabe
PhD Student
University of Oxford
The broad title and scope of this thesis provide an opportunity to develop a range of analyses, linked by the themes of mathematical modelling of transmission and disease control; parameter estimation; and under-reporting in official epidemiological data and means by which to account for this. While varied, all contribute to the overarching goal of improving understanding and opportunities for control of high-consequence pathogens in a variety of different settings. Although the work thus far has focussed primarily on COVID-19, work on MERS is also underway.
Project 4.2: Assessing and mitigating the risks of nosocomial transmission of HCIDs
Professor Peter Horby
Theme Co-Lead
University of Oxford
Mark Prithcard
PhD Student
University of Oxford
Importations of HCIDs into the UK are rare but inevitable events. HCIDs, such as MERS, CCHF and Ebola, can amplify in health care settings, often with very serious consequences for service delivery and public trust, as shown by the 2015 nosocomial MERS outbreak in South Korea. It is therefore crucial that cases are recognised and proper protections put in place to prevent infection of patients, visitors, and staff.
Mathematical models have previously informed the development of strategies for the control of other nosocomial infections, such as MRSA and Clostridium difficle. In this project, we will (i) collate and analyse data to identify those HCIDs that pose the greatest risk of nosocomial transmission in the UK; (ii) assemble data and reconstruct care pathways and transmission trees from selected HCID nosocomial outbreaks; (iii) develop mathematical models to estimate the effective reproduction rate of a range of HCID nosocomial outbreaks and make inferences about the impact of infection prevention and control practices; (iv) predict the impact of different screening and IPC strategies on the risk and size of nosocomial outbreaks of HCIDs.
Project 4.3: Exploring associations between ethnicity, in-hospital complications and COVID-19 outcomes in the United Kingdom, Brazil, and South Africa
Dr Shevin Jacob
Theme Co-Lead
Liverpool School of Tropical Medicine
Manuela Parnoffi
PhD Student
Liverpool School of Tropical Medicine
The severe acute respiratory syndrome coronavirus (SARS-CoV-2) has led to over 252 million confirmed cases of COVID-19 resulting in over 5 million recorded deaths. In response to the global pandemic, several cohort studies have described the clinical features of hospitalised patients with COVID-19 in order to better characterise the disease and the likelihood of severe outcomes. Some studies to date have explored the disproportionate impact of COVID-19 over ethnic minority groups. However, when characterising the relationship between the complications and ethnicity, this relation is limited to a description of the proportion of complications for different ethnic groups.
To support clinicians in the triage and management of patients with COVID-19, the ISARIC WHO CCP-UK derived and validated two pragmatic risk stratification tools, the 4C Deterioration model and the 4C Mortality Score. These models enable early detection of patients that are most at risk of severe outcomes (e.g., deterioration or death) and improve an efficient allocation of available resources and treatments. While both models have been further validated to demonstrate their consistent performance during the second pandemic wave of hospital admission in the UK, their performance should be further validated in ISARIC-associated cohorts outside of the UK and evaluated with the addition of patient factors, such as ethnicity and income deprivation.
Project 4.4: Serosurveillance of Lyme and other tick-borne diseases in England
Dr Amanda Semper
Theme Co-Lead
UK Health Security Agency
Eilish Hart
PhD Student
UK Health Security Agency
Initial work will focus on developing a definitive study powered to resolve regional differences in Lyme seroprevalence across England using a cross-section of residual plasma from NHS Blood & Transplant donors drawn from an archive held by UKHSA. Seroprevalence data will be compared with national Lyme disease incidence data over the same period, using UKHSA data on laboratory-confirmed cases. The student will also design and execute a second cross-sectional seroprevalence study using healthy volunteers recruited prospectively, to identify occupational/recreational risk factors for tick-borne disease exposure.