Translational data analytics in exposure science and environmental health: a citizen science approach with high school students

Ayaz Hyder,Andrew A May

doi:10.1186/s12940-020-00627-5

Abstract

BackgroundTranslational data analytics aims to apply data analytics principles and techniques to bring about broader societal or human impact. Translational data analytics for environmental health is an emerging discipline and the objective of this study is to describe a real-world example of this emerging discipline.MethodsWe implemented a citizen-science project at a local high school. Multiple cohorts of citizen scientists, who were students, fabricated and deployed low-cost air quality sensors. A cloud-computing solution provided real-time air quality data for risk screening purposes, data analytics and curricular activities.ResultsThe citizen-science project engaged with 14 high school students over a four-year period that is continuing to this day. The project led to the development of a website that displayed sensor-based measurements in local neighborhoods and a GitHub-like repository for open source code and instructions. Preliminary results showed a reasonable comparison between sensor-based and EPA land-based federal reference monitor data for CO and NOx.ConclusionsInitial sensor-based data collection efforts showed reasonable agreement with land-based federal reference monitors but more work needs to be done to validate these results. Lessons learned were: 1) the need for sustained funding because citizen science-based project timelines are a function of community needs/capacity and building interdisciplinary rapport in academic settings and 2) the need for a dedicated staff to manage academic-community relationships.

Highlights

Translation of environmental health science from data to knowledge to action is valuable on several different levels and is a major theme of the 2018–2023 Strategic Plan for NIEHS [1]
In light of Frumkin’s call for consequential environmental epidemiology [5], which emphasizes the translation of knowledge to action, translational research in environmental health sciences must pay close attention to both of these enabling factors— community engagement and interdisciplinary research
We focus on community engagement that fits between citizen science and academic-community engagement where interactions take place between researchers and staff from a University or other academic institution and the community

Summary

Introduction

Translation of environmental health science from data to knowledge to action is valuable on several different levels and is a major theme of the 2018–2023 Strategic Plan for NIEHS [1]. Both partners learned about each other’s capabilities and resources, in terms of materials and equipment for sensor fabrication, the design and production of sensor enclosure, and computer programming, and shared knowledge, in terms of rules and regulations regarding access to local area schools (e.g., rooftop, Wi-Fi, and after-hours access) and which schools to prioritize for deploying a complete sensor package (Fig. 2) This prioritization process involved academic researchers educating students about the basics of atmospheric sciences as it related to exposure assessment, the influence of road types (e.g., highways, major arteries, local roads), wind direction and the association between socioeconomic disparities and health outcomes by reference to epidemiological studies. Translational data analytics for environmental health is an emerging discipline and the objective of this study is to describe a real-world example of this emerging discipline

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Conclusion