Spatial Analysis of Air Pollution and Cancer Incidence in Alabama
Topics:
Keywords: Air pollution, Population, Machine learning, Spatial modelling, Alabama
Abstract Type: Poster Abstract
Authors:
Masoumeh Mahtabi,
saeideh Gharechahi,
Vicki Tinnon Broc,
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Abstract
One of the most important environmental problems that is threatening public health is air pollution. In some regions of the world, this issue is becoming a severe health risk due to uncontrolled industrial activities, consumption of fossil fuels and population density. Air pollution can lead to cardiovascular disease and cancer especially in vulnerable population groups. Therefore, evaluation of cancer data related to the location of EPA’s Toxic Release Inventory (TRI) is a necessary component of responsible governmental policy interventions. Here, this study aims at spatial modelling of air pollution and cancer data in Alabama using a machine learning model. Initially, a spatial database consisting of air pollution parameters and demographic and cancer data will be collected and the spatial relationships between the air pollution and cancer incidence cases will be modelled and mapped to address the locations and population groups at risk.
Spatial Analysis of Air Pollution and Cancer Incidence in Alabama
Category
Poster Abstract
