Colleen Reid - Academia.edu (original) (raw)

Papers by Colleen Reid

Research paper thumbnail of Climate change, heat waves, and population vulnerability: Using the environmental public health tracking network for validity testing of the heat vulnerability index

Heat waves and extreme hot weather conditions have been associated with increased burdens of morb... more Heat waves and extreme hot weather conditions have been associated with increased burdens of morbidity and mortality, but the risks are not evenly distributed throughout the population. Mapping the spatial distribution of risk for heat-related morbidity and mortality would allow public health departments to target interventions known to prevent illness and deaths during heat waves to the most vulnerable areas. Previously, a heat vulnerability index (HVI) was created that combined factors of environmental and social vulnerability, social isolation, air conditioning prevalence, and pre-existing health conditions to locate vulnerability to heat in geographic space in metropolitan areas throughout the United States. Our study attempts to verify that the intra-urban spatial distribution of vulnerability demonstrated by the HVI is valid using local health information from several public health departments that are participating in the Center for Disease Control's Environmental Public ...

Research paper thumbnail of Diurnal temperature range and short-term mortality in large US communities

International journal of biometeorology, Jan 3, 2014

Research has shown that diurnal temperature range (DTR) is significantly associated with mortalit... more Research has shown that diurnal temperature range (DTR) is significantly associated with mortality and morbidity in regions of Asia; however, few studies have been conducted in other regions such as North America. Thus, we examined DTR effects on mortality in the USA. We used mortality and environmental data from the National Morbidity Mortality Air Pollution Study (NMMAPS). The data are daily mortality, air pollution, and temperature statistics from 95 large US communities collected between 1987 and 2000. To assess community-specific DTR effects on mortality, we used Poisson generalized linear models allowing for over-dispersion. After assessing community-specific DTR effects on mortality, we estimated region- and age-specific effects of DTR using two-level normal independent sampling estimation. We found a significant increase of 0.27 % [95 % confidence intervals (CI), 0.24-0.30 %] in nonaccidental mortality across 95 communities in the USA associated with a 1 °C increase in DTR, ...

Research paper thumbnail of 1.1 Scope and Approach of Sap 4.6

Research paper thumbnail of Aeroallergens, Allergic Disease, and Climate Change: Impacts and Adaptation

EcoHealth, 2009

Recent research has shown that there are many effects of climate change on aeroallergens and thus... more Recent research has shown that there are many effects of climate change on aeroallergens and thus allergic diseases in humans. Increased atmospheric carbon dioxide concentration acts as a fertilizer for plant growth. The fertilizing effects of carbon dioxide, as well as increased temperatures from climate change, increase pollen production and the allergen content of pollen grains. In addition, higher temperatures are changing the timing and duration of the pollen season. As regional climates change, plants can move into new areas and changes in atmospheric circulation can blow pollen-and spore-containing dust to new areas, thus introducing people to allergens to which they have not been exposed previously. Climate change also influences the concentrations of airborne pollutants, which alone, and in conjunction with aeroallergens, can exacerbate asthma or other respiratory illnesses. The few epidemiological analyses of meteorological factors, aeroallergens, and allergic diseases demonstrate the pathways through which climate can exert its influence on aeroallergens and allergic diseases. In addition to the need for more research, there is the imperative to take preventive and adaptive actions to address the onset and exacerbation of allergic diseases associated with climate variability and change.

Research paper thumbnail of Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning

Environmental Science & Technology, 2015

Estimating population exposure to particulate matter during wildfires can be difficult because of... more Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM 2.5 during wildfires. We estimated PM 2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R 2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM 2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM 2.5 concentrations during a major wildfire event.

Research paper thumbnail of Climate change, heat waves, and population vulnerability: Using the environmental public health tracking network for validity testing of the heat vulnerability index

Heat waves and extreme hot weather conditions have been associated with increased burdens of morb... more Heat waves and extreme hot weather conditions have been associated with increased burdens of morbidity and mortality, but the risks are not evenly distributed throughout the population. Mapping the spatial distribution of risk for heat-related morbidity and mortality would allow public health departments to target interventions known to prevent illness and deaths during heat waves to the most vulnerable areas. Previously, a heat vulnerability index (HVI) was created that combined factors of environmental and social vulnerability, social isolation, air conditioning prevalence, and pre-existing health conditions to locate vulnerability to heat in geographic space in metropolitan areas throughout the United States. Our study attempts to verify that the intra-urban spatial distribution of vulnerability demonstrated by the HVI is valid using local health information from several public health departments that are participating in the Center for Disease Control's Environmental Public ...

Research paper thumbnail of Diurnal temperature range and short-term mortality in large US communities

International journal of biometeorology, Jan 3, 2014

Research has shown that diurnal temperature range (DTR) is significantly associated with mortalit... more Research has shown that diurnal temperature range (DTR) is significantly associated with mortality and morbidity in regions of Asia; however, few studies have been conducted in other regions such as North America. Thus, we examined DTR effects on mortality in the USA. We used mortality and environmental data from the National Morbidity Mortality Air Pollution Study (NMMAPS). The data are daily mortality, air pollution, and temperature statistics from 95 large US communities collected between 1987 and 2000. To assess community-specific DTR effects on mortality, we used Poisson generalized linear models allowing for over-dispersion. After assessing community-specific DTR effects on mortality, we estimated region- and age-specific effects of DTR using two-level normal independent sampling estimation. We found a significant increase of 0.27 % [95 % confidence intervals (CI), 0.24-0.30 %] in nonaccidental mortality across 95 communities in the USA associated with a 1 °C increase in DTR, ...

Research paper thumbnail of 1.1 Scope and Approach of Sap 4.6

Research paper thumbnail of Aeroallergens, Allergic Disease, and Climate Change: Impacts and Adaptation

EcoHealth, 2009

Recent research has shown that there are many effects of climate change on aeroallergens and thus... more Recent research has shown that there are many effects of climate change on aeroallergens and thus allergic diseases in humans. Increased atmospheric carbon dioxide concentration acts as a fertilizer for plant growth. The fertilizing effects of carbon dioxide, as well as increased temperatures from climate change, increase pollen production and the allergen content of pollen grains. In addition, higher temperatures are changing the timing and duration of the pollen season. As regional climates change, plants can move into new areas and changes in atmospheric circulation can blow pollen-and spore-containing dust to new areas, thus introducing people to allergens to which they have not been exposed previously. Climate change also influences the concentrations of airborne pollutants, which alone, and in conjunction with aeroallergens, can exacerbate asthma or other respiratory illnesses. The few epidemiological analyses of meteorological factors, aeroallergens, and allergic diseases demonstrate the pathways through which climate can exert its influence on aeroallergens and allergic diseases. In addition to the need for more research, there is the imperative to take preventive and adaptive actions to address the onset and exacerbation of allergic diseases associated with climate variability and change.

Research paper thumbnail of Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning

Environmental Science & Technology, 2015

Estimating population exposure to particulate matter during wildfires can be difficult because of... more Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM 2.5 during wildfires. We estimated PM 2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R 2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM 2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM 2.5 concentrations during a major wildfire event.