Time-series analysis of satellite-derived fine particulate matter pollution and asthma morbidity in Jackson, MS.

In order to examine associations between asthma morbidity and local ambient air pollution in an area with relatively low levels of pollution, we conducted a time-series analysis of asthma hospital admissions and fine particulate matter pollution (PM2.5) in and around Jackson, MS, for the period 2003 to 2011. Daily patient-level records were obtained from the Mississippi State Department of Health (MSDH) Asthma Surveillance System. Patient geolocations were aggregated into a grid with 0.1° × 0.1° resolution within the Jackson Metropolitan Statistical Area. Daily PM2.5 concentrations were estimated via machine-learning algorithms with remotely sensed aerosol optical depth and other associated parameters as inputs. Controlling for long-term temporal trends and meteorology, we estimated a 7.2% (95% confidence interval 1.7-13.1%) increase in daily all-age asthma emergency room admissions per 10 µg/m3 increase in the 3-day average of PM2.5 levels (current day and two prior days). Stratified analyses reveal significant associations between asthma and 3-day average PM2.5 for males and blacks. Our results contribute to the current epidemiologic evidence on the association between acute ambient air pollution exposure and asthma morbidity, even in an area characterized by relatively good air quality.

GeoMedStat: an integrated spatial surveillance system to track air pollution and associated healthcare events.

Air pollutants, such as particulate matter with a diameter ≤2.5 microns (PM2.5) and ozone (O3), are known to exacerbate asthma and other respiratory diseases. An integrated surveillance system that tracks such air pollutants and associated disease incidence can assist in risk assessment, healthcare preparedness and public awareness. However, the implementation of such an integrated environmental health surveillance system is a challenge due to the disparate sources of many types of data and the implementation becomes even more complicated for a spatial and real-time system due to lack of standardised technological components and data incompatibility. In addition, accessing and utilising health data that are considered as Protected Health Information (PHI) require maintaining stringent protocols, which have to be supported by the system. This paper aims to illustrate the development of a spatial surveillance system (GeoMedStat) that is capable of tracking daily environmental pollutants along with both daily and historical patient encounter data. It utilises satellite data and the groundmonitor data from the US National Aeronautics and Space Administration (NASA) and the US Environemental Protection Agenecy (EPA), rspectively as inputs estimating air pollutants and is linked to hospital information systems for accessing chief complaints and disease classification codes. The components, developmental methods, functionality of GeoMedStat and its use as a real-time environmental health surveillance system for asthma and other respiratory syndromes in connection with with PM2.5 and ozone are described. It is expected that the framework presented will serve as an example to others developing real-time spatial surveillance systems for pollutants and hospital visits.