Public Health Benefits and Ethical Aspects in the Collection and Open Sharing of Wastewater-Based Epidemic Data on COVID-19

Q2 Computer Science
R. Honda, M. Murakami, A. Hata, M. Ihara
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引用次数: 7

Abstract

Collection and open sharing of wastewater-based epidemic data potentially provide immense public health benefits during outbreak of infectious diseases such as COVID-19. By early detection and localization of unidentified infections, wastewater surveillance is expected to enable early and targeted containment of the local outbreak. Wastewater surveillance renders potentially high public health benefits when a small catchment is targeted;however, it possibly leads to stigmatization and discrimination against the targeted group. Therefore, public commitment is crucial for the collection and open sharing of wastewater-based epidemic data. With respect to the sharing of wastewater-based epidemic data, technical limitations and uncertainty of collected data also should be simultaneously shared on the basis of scientific communication. Useful application of wastewater-based epidemic data is to complement clinical epidemic data, which is possibly biased and overlooks unidentified infections. To acquire public commitment toward the collection and open sharing of wastewater-based epidemic data, stakeholders need to reach a consensus on possible options of restrictive measures taken with respect to the collected data as well as appropriate handling of the collected data to prevent stigmatization and discrimination. © 2021 The Author(s).
收集和公开共享基于废水的COVID-19流行病数据的公共卫生利益和伦理问题
在COVID-19等传染病爆发期间,收集和公开共享基于废水的流行病数据可能会带来巨大的公共卫生效益。通过早期发现和定位不明感染,预计废水监测将能够及早和有针对性地遏制当地疫情。当以小集水区为目标时,废水监测可能带来很高的公共卫生效益;然而,它可能导致对目标群体的污名化和歧视。因此,公众承诺对于收集和公开分享基于废水的流行病数据至关重要。关于共享基于废水的流行病数据,也应在科学交流的基础上同时共享所收集数据的技术限制和不确定性。基于废水的流行病数据的有用应用是补充临床流行病数据,这些数据可能有偏见,并且忽略了不明感染。为了获得公众对收集和公开分享基于废水的流行病数据的承诺,利益攸关方需要就对收集到的数据采取限制性措施的可能选择以及对收集到的数据的适当处理达成共识,以防止污名化和歧视。©2021作者。
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来源期刊
Data Science Journal
Data Science Journal Computer Science-Computer Science (miscellaneous)
CiteScore
5.40
自引率
0.00%
发文量
17
审稿时长
10 weeks
期刊介绍: The Data Science Journal is a peer-reviewed electronic journal publishing papers on the management of data and databases in Science and Technology. Details can be found in the prospectus. The scope of the journal includes descriptions of data systems, their publication on the internet, applications and legal issues. All of the Sciences are covered, including the Physical Sciences, Engineering, the Geosciences and the Biosciences, along with Agriculture and the Medical Science. The journal publishes papers about data and data systems; it does not publish data or data compilations. However it may publish papers about methods of data compilation or analysis.
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