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Microcomputer-controlled plotting of environmental health data.

R R Eckert, E Lopez, V Perez

    International Journal of Bio-Medical Computing
    |March 1, 1983
    PubMed
    Summary
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    A new computer program visualizes air quality and respiratory illness data. It maps geographic and time-based trends for airborne particulate matter and related health issues.

    Area of Science:

    • Environmental Science
    • Epidemiology
    • Computer Science

    Background:

    • Assessing the relationship between environmental factors and public health requires robust data visualization tools.
    • Analyzing airborne particulate matter and respiratory illness incidence involves complex datasets.
    • Current methods for correlating environmental exposures with health outcomes can be labor-intensive.

    Purpose of the Study:

    • To develop a versatile microcomputer program for plotting geographical and temporal variations in environmental and health data.
    • To facilitate the analysis of airborne particulate matter concentrations, including metallic and organic components.
    • To aid in visualizing the incidence of respiratory illnesses and related epidemiological information.

    Main Methods:

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  • Development of a general microcomputer program.
  • Inputting data on airborne particulate matter concentrations (total, metallic, organic).
  • Integrating epidemiological data on respiratory illnesses from various sources (physicians, hospitals, pharmacies, schools).
  • Generating graphical representations of data variations over space and time.
  • Main Results:

    • The program successfully generates finished plots illustrating environmental and health data trends.
    • Visualizations include geographical distributions and temporal changes in particulate matter and illness incidence.
    • The program provides a comprehensive tool for exploring correlations between environmental exposures and health outcomes.

    Conclusions:

    • A user-friendly microcomputer program has been created to effectively visualize complex environmental and epidemiological data.
    • This tool enhances the understanding of spatial and temporal relationships between air quality and respiratory health.
    • The program includes detailed explanations and a full listing for accessibility and further development.