An Exploration of Features Impacting Respiratory Diseases in Urban Areas

Ihsane Gryech, Mounir Ghogho, Chafiq Mahraoui and Abdellatif Kobbane
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Ihsane Gryech: TICLab Research Laboratory, International University of Rabat, Rabat 11103, Morocco
Mounir Ghogho: TICLab Research Laboratory, International University of Rabat, Rabat 11103, Morocco
Chafiq Mahraoui: Centre Hospitalo-Universitaire Ibn Sina de Rabat—CHUIS, Rabat 10100, Morocco
Abdellatif Kobbane: ENSIAS, Mohammed V University in Rabat, Rabat 10100, Morocco

IJERPH, 2022, vol. 19, issue 5, 1-21

Abstract: Air pollution exposure has become ubiquitous and is increasingly detrimental to human health. Small Particulate matter (PM) is one of the most harmful forms of air pollution. It can easily infiltrate the lungs and trigger several respiratory diseases, especially in vulnerable populations such as children and elderly people. In this work, we start by leveraging a retrospective study of 416 children suffering from respiratory diseases. The study revealed that asthma prevalence was the most common among several respiratory diseases, and that most patients suffering from those diseases live in areas of high traffic, noise, and greenness. This paved the way to the construction of the MOREAIR dataset by combining feature abstraction and micro-level scale data collection. Unlike existing data sets, MOREAIR is rich in context-specific components, as it includes 52 temporal or geographical features, in addition to air-quality measurements. The use of Random Forest uncovered the most important features for the understanding of air-quality distribution in Moroccan urban areas. By linking the medical data and the MOREAIR dataset, we observed that the patients included in the medical study come mostly from neighborhoods that are characterized by either high average or high variations of pollution levels.

Keywords: air quality; respiratory health; features abstraction; geographical information systems; open data set; random forest (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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