Methods matter: computational modelling in public health policy and planning

This work is aimed at understanding and unifying information on epidemiological modelling methods and how those methods relate to public policy addressing human health, specifically in the context of infectious disease prevention, pandemic planning, and health behaviour change. This thesis employs multiple qualitative and quantitative methods, and presents as a manuscript of several individual, data-driven projects that are combined in a narrative arc. The first chapter introduces the scope and complexity of this interdisciplinary undertaking, describing several topical intersections of importance. The second chapter begins the presentation of original data, and describes in detail two exercises in computational epidemiological modelling pertinent to pandemic influenza planning and policy, and progresses in the next chapter to present additional original data on how the confidence of the public in modelling methodology may have an effect on their planned health behaviour change as recommended in public health policy. The thesis narrative continues in the final data-driven chapter to describe how health policymakers use modelling methods and scientific evidence to inform and construct health policies for the prevention of infectious diseases, and concludes with a narrative chapter that evaluates the breadth of this data and recommends strategies for the optimal use of modelling methodologies when informing public health policy in applied public health scenarios.

Analysis and modelling of immune cell behaviour in lymph nodes based on multi-photon imaging

This thesis presents quantitative studies of T cell and dendritic cell (DC) behaviour in mouse lymph nodes (LNs) in the naive state and following immunisation. These processes are of importance and interest in basic immunology, and better understanding could improve both diagnostic capacity and therapeutic manipulations, potentially helping in producing more effective vaccines or developing treatments for autoimmune diseases. The problem is also interesting conceptually as it is relevant to other fields where 3D movement of objects is tracked with a discrete scanning interval. A general immunology introduction is presented in chapter 1. In chapter 2, I apply quantitative methods to multi-photon imaging data to measure how T cells and DCs are spatially arranged in LNs. This has been previously studied to describe differences between the naive and immunised state and as an indicator of the magnitude of the immune response in LNs, but previous analyses have been generally descriptive. The quantitative analysis shows that some of the previous conclusions may have been premature. In chapter 3, I use Bayesian state-space models to test some hypotheses about the mode of T cell search for DCs. A two-state mode of movement where T cells can be classified as either interacting to a DC or freely migrating is supported over a model where T cells would home in on DCs at distance through for example the action of chemokines. In chapter 4, I study whether T cell migration is linked to the geometric structure of the fibroblast reticular network (FRC). I find support for the hypothesis that the movement is constrained to the fibroblast reticular cell (FRC) network over an alternative 'random walk with persistence time' model where cells would move randomly, with a short-term persistence driven by a hypothetical T cell intrinsic 'clock'. I also present unexpected results on the FRC network geometry. Finally, a quantitative method is presented for addressing some measurement biases inherent to multi-photon imaging. In all three chapters, novel findings are made, and the methods developed have the potential for further use to address important problems in the field. In chapter 5, I present a summary and synthesis of results from chapters 3-4 and a more speculative discussion of these results and potential future directions.

Quantitative measurement using scanning thermal microscopy

This thesis reports on the development of quantitative measurement using micromachined scanning thermal microscopy (SThM) probes. These thermal probes employ a resistive element at their end, which can be used in passive or active modes. With the help of a review of SThM, the current issues and potentials associated with this technique are revealed. As a consequence of this understanding, several experimental and theoretical methods are discussed, which expand our understanding of these probes. The whole thesis can be summarized into three parts, one focusing on the thermal probe, one on probe-sample thermal interactions, and the third on heat transfer within the sample. In the first part, a series of experiments are demonstrated, aimed at characterizing the probe in its electrical and thermal properties, benefiting advanced probe design, and laying a fundamental base for quantifying the temperature of the probe. The second part focuses on two artifacts observed during the thermal scans – one induced by topography and the other by air conduction. Correspondingly, two devices, probing these artifacts, are developed. A topography-free sample, utilizing a pattern transfer technique, minimises topography-related artifacts that limited the reliability of SThM data; a controlled temperature ‘Johnson noise device’, with multiple-heater design, offers a uniform, accurate, temperature distribution. Analyzing results of scan from these samples provides data for studying the thermal interactions within the probe and the tip-sample interface. In the final part, the observation is presented that quantification of measurements depends not only on an accurate measurement tool, but also on a deep understanding of the heat transfer within the sample resulting from the nanoscopic contact. It is believed that work in this thesis contributes to SThM gaining wider application in the scientific community.

Mindfulness-Based Cognitive Therapy for older people in a community setting: a mixed methods feasibility study

Rationale: In line with complex intervention development, this research takes a systematic approach to examining the feasibility and acceptability of delivering Mindfulness-Based Cognitive Therapy (MBCT) to older people who experience symptoms of depression. Methods: A mixed methods approach was adopted in line with recommendations made by the MRC Complex Intervention Development framework. Quantitative and qualitative methods were combined by administering questionnaires as well as conducting post intervention interviews. A number of trial feasibility factors were examined such as recruitment and attrition rates. Qualitative data was analysed using Braun and Clarke’s thematic analysis framework. Results: Nine participants started the MBCT intervention and six completed the 8-week programme. The results suggest that MBCT for older people is feasible and acceptable. Participants reported improved mindfulness skills. Participants responded positively to being asked to take part in research and appeared to particularly value the group delivery format of the intervention. Conclusions: MBCT is both feasible and acceptable for older people experiencing symptoms of depression. Further research is required with larger sample sizes to allow for more robust statistical exploration of outcome measures, including mechanisms of change.