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Data Science in Public Health: Building Next Generation Capacity.

Nicholas Mirin1, Heather Mattie2, Latifa Jackson3

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Summary
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Public health data science education is crucial for addressing health disparities. This review of top schools offers a 4-point formula to enhance data science training for a diverse public health workforce.

Keywords:
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Area of Science:

  • Public Health
  • Data Science Education

Background:

  • The rapid evolution of technology and data necessitates data science skills in public health.
  • Novel data types and analysis methods can address research gaps but also risk perpetuating health disparities.

Purpose of the Study:

  • To summarize existing public health data science educational efforts at top-ranked schools.
  • To inform curriculum development for broader reach and to integrate data science ethics.
  • To synthesize 'outside-the-classroom' training to increase diversity in the field.

Main Methods:

  • Review of public health courses and programs at top 10 U.S. and globally ranked schools.
  • Examination of data science ethics course offerings.
  • Synthesis of domestic and international training programs.

Main Results:

  • Identified current educational practices in public health data science.
  • Assessed the integration of data science ethics and population health principles.
  • Synthesized findings from formal and informal training initiatives.

Conclusions:

  • A 4-point formula is proposed to advance public health data science education.
  • The goal is to cultivate a critical, inclusive workforce skilled in leveraging data for public health.
  • This aims to improve public health outcomes and quality of life in the digital age.