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Data Science in Environmental Health Research

Current Epidemiology Reports volume 6, pages 291–299 (2019)Cite this article

Abstract

Purpose of Review

Data science is an exploding trans-disciplinary field that aims to harness the power of data to gain information or insights on researcher-defined topics of interest. In this paper, we review how data science can help advance environmental health research.

Recent Findings

We discuss the concepts of computationally scalable handling of big data and the design of efficient research data platforms and how data science can provide solutions for methodological challenges in environmental health research, such as high-dimensional outcomes and exposures and prediction models. Finally, we discuss tools for reproducible research.

Summary

In this paper, we present opportunities to improve environmental research capabilities by embracing data science and the pitfalls that environmental health researchers should avoid when employing data scientific approaches. Throughout the paper, we emphasize the need for environmental health researchers to collaborate more closely with biostatisticians and data scientists to ensure robust and interpretable results.

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Funding

This work was supported by NIEHS P30 ES009089 and R01 ES028805. This work was partially supported by HEI grant 4953-RFA14-3/16-4; the Health Effects Institute (HEI) is an organization jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No.CR-83467701) and certain motor vehicle and engine manufacturers.

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Authors and Affiliations

  1. Swiss Data Science Center, ETH Zurich and EPFL, Zurich, Switzerland

    Christine Choirat

  2. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Danielle Braun

  3. Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA

    Danielle Braun

  4. Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA

    Marianthi-Anna Kioumourtzoglou

Authors
  1. Christine Choirat
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  3. Marianthi-Anna Kioumourtzoglou
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Correspondence to Marianthi-Anna Kioumourtzoglou.

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Choirat, C., Braun, D. & Kioumourtzoglou, MA. Data Science in Environmental Health Research. Curr Epidemiol Rep 6, 291–299 (2019). https://doi.org/10.1007/s40471-019-00205-5

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  • DOI: https://doi.org/10.1007/s40471-019-00205-5

Keywords

  • Data science
  • Big data
  • Environmental health research
  • Reproducibility
  • Environmental mixtures
  • High-dimensional
  • Research data platforms