Login / Signup

Mapping Mobility: Utilizing Local-Knowledge-Derived Activity Space to Estimate Exposure to Ambient Air Pollution among Individuals Experiencing Unsheltered Homelessness.

Maeve G MacMurdoKaren B MulloyDaniel A CulverCharles W FelixAndrew J CurtisJayakrishnan AjayakumarJacqueline Curtis
Published in: International journal of environmental research and public health (2022)
Individuals experiencing homelessness represent a growing population in the United States. Air pollution exposure among individuals experiencing homelessness has not been quantified. Utilizing local knowledge mapping, we generated activity spaces for 62 individuals experiencing homelessness residing in a semi-rural county within the United States. Satellite derived measurements of fine particulate matter (PM2.5) were utilized to estimate annual exposure to air pollution experienced by our participants, as well as differences in the variation in estimated PM2.5 at the local scale compared with stationary monitor data and point location estimates for the same period. Spatial variation in exposure to PM2.5 was detected between participants at both the point and activity space level. Among all participants, annual median PM2.5 exposure was 16.22 μg/m 3 , exceeding the National Air Quality Standard. Local knowledge mapping represents a novel mechanism to capture mobility patterns and investigate exposure to air pollution within vulnerable populations. Reliance on stationary monitor data to estimate air pollution exposure may lead to exposure misclassification, particularly in rural and semirural regions where monitoring is limited.
Keyphrases
  • air pollution
  • particulate matter
  • lung function
  • healthcare
  • mental illness
  • high resolution
  • south africa
  • electronic health record
  • big data
  • high density
  • risk assessment
  • deep learning
  • artificial intelligence