Assessing the utility of real-time syndromic surveillance for monitoring the health effects of air pollution
PHE ePoster Library. Harcourt S. Sep 12, 2019; 274481; 42
Mrs. Sally Harcourt
Mrs. Sally Harcourt
Login now to access Regular content available to all registered users.

You may also access this content "anytime, anywhere" with the Free MULTILEARNING App for iOS and Android
Abstract
Rate & Comment (0)
Abstract Air pollution is the largest environmental risk to public health in the UK and evidence of negative effects on health is well documented. Air pollution is associated with cardiovascular disease, cancer, asthma and chronic obstructive pulmonary disease, and contributes to health inequalities. Young children, the elderly and those with underlying medical conditions are at greater risk from air pollution.We have undertaken a systematic approach to understanding the utility of real-time syndromic surveillance for monitoring the health impact of air pollution. Our approach uses historical air quality data (PM10, PM2.5, ozone, NO2, SO2) and syndromic surveillance data for 2012-17. We have used time series charts to describe the ‘asthma-type' syndromic indicators at national (England) and regional (PHE Centre) level and used generalised additive models to explore relationships between syndromic and air pollutant data. Our initial modelling focus was at UTLA level in an area (in the Midlands) where data availability was most complete across a range of predictive variables. In addition to individual pollutants, explanatory variables included meteorological data and other confounders including pollen, fungal spores and influenza laboratory positivity data. We also explored non-linear and lagged effects. Preliminary results using NHS 111 difficulty breathing calls and GP unscheduled consultations for asthma showed that temperature was significant in all models whereas air pollutants only in some models. The role of pollen and fungal spores varied by type. Viral infections and lightning strikes also had some significant associations. The implications of these findings, further analyses and future developments will be discussed. External funding details
    This eLearning portal is powered by:
    This eLearning portal is powered by MULTIEPORTAL
Anonymous User Privacy Preferences

Strictly Necessary Cookies (Always Active)

MULTILEARNING platforms and tools hereinafter referred as “MLG SOFTWARE” are provided to you as pure educational platforms/services requiring cookies to operate. In the case of the MLG SOFTWARE, cookies are essential for the Platform to function properly for the provision of education. If these cookies are disabled, a large subset of the functionality provided by the Platform will either be unavailable or cease to work as expected. The MLG SOFTWARE do not capture non-essential activities such as menu items and listings you click on or pages viewed.


Performance Cookies

Performance cookies are used to analyse how visitors use a website in order to provide a better user experience.


Save Settings