The aim of this research is to reduce the frequency of hospital and GP visits by patients with
chronic obstructive pulmonary disease (COPD). This will be achieved by utilising a combination
of miniature sensors that measure an individual's exposure to air pollution, mathematical models
that predict air pollution at any location in a city and people's GP health records.
Despite substantial evidence of the adverse health effects of air pollution, ranging from respiratory symptoms through to cancer and cardiovascular mortality, gaps and uncertainties exist in our understanding of why this happens. This has been attributed to over-simplified estimates of how much air pollution (and other environmental stress) individuals are exposed to as they go about their daily lives. This project addresses this limitation by bringing together two fields of research that have made rapid advancements in recent years - time-activity exposure models and personal pollution sensors. The research will be applied to a public health challenge requiring urgent knowledge advancement; prediction and management of COPD exacerbations.
COPD patients are at risk of severe episodes of deterioration - 'exacerbations'. Exacerbations are the second commonest cause of adult emergency medical hospital admission in the UK and are associated with shortened lives and decreased quality of life.
The first phase of the study will comprise the largest real time patient exposure measurement campaign yet carried out in the UK. Micro pollution, temperature and humidity sensors will be carried by 150 COPD patients for six months, with movements tracked by satellite navigation (GPS). During this period patients will keep records of symptoms relating to their condition (such as breathlessness, cough and wheeze) on diary cards and take daily exhaled breath flow tests. We will use this extensive measurement dataset to relate COPD symptoms and exacerbations to air pollution, temperature and humidity levels and activities such as travelling, cooking and exposure to tobacco smoke.
The measurements will then be used to assess and improve the performance of a high resolution 'time-activity' exposure model recently developed for London. Time-activity computer models allow the calculation of an individual's exposure to pollution as they move about a city throughout the day. However, their accuracy is unproven. The pollution measurements taken during the first phase of the study will provide a means of testing the performance of the exposure model by comparing modelled and measured exposure estimates for the 150 COPD patients.
Links between COPD exacerbations and environmental exposure identified in the first phase will be combined with the exposure model validated in the second phase to create a new model for predicting COPD exacerbations. The performance of this model will be evaluated by comparing modelled predictions against GP and hospital records of exacerbations between 2005 and 2011.
If the predictive performance of this model is proven, it presents a means of forming a validated COPD forecasting tool for public health providers in London. The predictive algorithms used in the model will be made available for application across the UK, providing an opportunity for the development of a national COPD forecasting service with proven performance in predicting increased risk of exacerbations.
The final project outcome will be the production of a patient-orientated report describing associations between environmental exposure and COPD symptoms, clearly illustrating how COPD patients can adjust their behaviour to reduce their risk of exacerbation and improve their quality of life.
COPE is funded by the UK Medical Research Council and is a collaboration between King’s College London, Imperial College London and the University of Cambridge.
Further information http://gtr.rcuk.ac.uk/project/19826905-8661-48A5-9423-BB8035044163