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Data science in public health: building next generation capacity | | Nicholas Mirin
; Heather Mattie
; Latifa Jackson
; Zainab Samad
; Rumi Chunara
; | | Date: |
6 Aug 2022 | | Abstract: | Rapidly evolving technology, data and analytic landscapes are permeating many
fields and professions. In public health, the need for data science skills
including data literacy is particularly prominent given both the potential of
novel data types and analysis methods to fill gaps in existing public health
research and intervention practices, as well as the potential of such data or
methods to perpetuate or augment health disparities. Through a review of public
health courses and programs at the top 10 U.S. and globally ranked schools of
public health, this article summarizes existing educational efforts in public
health data science. These existing practices serve to inform efforts for
broadening such curricula to further schools and populations. Data science
ethics course offerings are also examined in context of assessing how
population health principles can be blended into training across levels of data
involvement to augment the traditional core of public health curricula.
Parallel findings from domestic and international ’outside the classroom’
training programs are also synthesized to advance approaches for increasing
diversity in public health data science. Based on these program reviews and
their synthesis, a four-point formula is distilled for furthering public health
data science education efforts, toward development of a critical and inclusive
mass of practitioners with fluency to leverage data to advance goals of public
health and improve quality of life in the digital age. | | Source: | arXiv, 2208.03461 | | Services: | Forum | Review | PDF | Favorites | |
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