California wildfire smoke may put pregnant women, children, those with asthma at greater risk

Research by recent Harvard RWJF Health & Society Scholar program alumna Colleen Reid, PhD, on the health hazards of wildfire smoke is featured in this release by University of Colorado Boulder. Photo: Cameron Strandberg, Fitzhugh Newspaper. Jasper, Alberta

Trees (over grass) to promote health in urban settings

Recent Harvard RWJF Health & Society Scholar Colleen Reid, along with Harvard Pop Center faculty member Laura Kubzansky, are authors on a paper that suggests that trees—more than grass and apart from parks—may be a key element to green space when it comes to promoting health in urban settings. Photo: Dylan Passmore on Flickr

Increase in asthma symptoms linked to wildfire smoke, fine particulate matter air pollution

Harvard RWJF Health & Society Scholar Colleen Reid, PhD, is lead author on a study published in Environmental Research that contributes to the growing body of knowledge of health risks associated with wildfire smoke. Photo: Cameron Strandberg, Fitzhugh Newspaper. Jasper, Alberta

Wildfire smoke consistently linked to respiratory health effects, growing evidence of link to mortality

Harvard RWJF Health & Society Scholar Colleen Reid, PhD, is lead author on a study in Environmental Health Perspectives that reviews a range of scientific studies on health effects from exposure to wildfire smoke, and seeks to identify particularly susceptible populations. Photo: Cameron Strandberg, Fitzhugh Newspaper. Jasper, Alberta

Study shows using machine learning algorithms can reliably predict air quality during major wildfire

Harvard Robert Wood Johnson Health & Society Scholar Colleen Reid, PhD, is lead author on a study published Environmental Science & Technology that applied machine learning algorithms that combine data from satellites and chemical transport models (CMTs) – a type of computer numerical model – to predict fine particulate matter during the 2008 northern California … Continue reading “Study shows using machine learning algorithms can reliably predict air quality during major wildfire”