Wastewater Monitoring Raises Privacy and Ethical Considerations

Jacobs, Danielle; McDaniel, Troy; Varsani, Arvind; Halden, Rolf U.; Forrest, Stephanie; Lee, Heewook

doi:10.1109/tts.2021.3073886

Cited by 23 publications

(13 citation statements)

References 22 publications

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“…However, this computational methodology also imposes some discussion about the ethical and privacy concerns ( Jacobs et al, 2021 ). Currently, the fast analysis of this huge amount of data in almost real-time allows the identification and understanding of the population viral spread and disease trends.…”

Section: Resultsmentioning

confidence: 99%

Mapping human pathogens in wastewater using a metatranscriptomic approach

Carneiro

Pascoal

Semedo

et al. 2023

Environmental Research

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Section: Resultsmentioning

confidence: 99%

Mapping human pathogens in wastewater using a metatranscriptomic approach

Carneiro

Pascoal

Semedo

et al. 2023

Environmental Research

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“…Differential privacy has been widely studied in the recent decade for privacy-preserving data mining [14]. We assume a scenario where we collect attribute values from each person while protecting their privacy based on differential privacy.…”

Section: B Differential Privacymentioning

confidence: 99%

Re-Identification in Differentially Private Incomplete Datasets

Sei

Okumura

Ohsuga

2022

IEEE Open J. Comput. Soc.

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Efforts to counter COVID-19 reaffirmed the importance of rich medical, behavioral, and sociological data. To make data available to many researchers who can conduct statistical analyses and machine learning, personally identifiable information must be excluded to protect individual privacy. It is essential to remove explicit identifiers, sample population data, and apply differential privacy, the de facto standard privacy metric. Despite the general belief that the risk of re-identification is insignificant when these techniques are applied, this study shows that even after applying these techniques, the risk of being re-identified is highly significant for some data. This study proposes in detail an algorithm for estimating the number of people in a population who have certain attribute values based on incomplete, differentially private databases. If the estimated number is one, the probability that only one person with that attribute value is present in the population is high, which means that there is a high probability of re-identification. Therefore, this study concludes that the re-identification risk must be evaluated even after applying state-of-the-art techniques to protect privacy.INDEX TERMS Differential privacy, ethical and privacy framework, re-identification.

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“…Even after several treatment steps, many concerns are raised by the authors, which include, preservation of genetic data, flora and fauna privacy issues, etc. A survey of these issues can be observed in Jacobs et al (2021), wherein authors have aggregated these issues, and suggested recommendations for countering them. Based on these recommendations, work in Iratni & Chang (2019) suggests different control techniques including proportional integral control (PI), PI differential control (PID), feedback-based control, etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Pragmatic analysis of wastewater treatment methods from a statistical perspective

Pande

Bhagat

2022

Water Practice and Technology

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Wastewater treatment is an environmental issue of utmost importance. Various models and architectures for wastewater treatment exist, each having its unique characteristics. In this study, an application-specific review of various treatment models is performed. Extensions to existing treatment models are discussed for improvement in process performance. The treatment models are compared statistically based on their performance metrics, namely the quality of treated water (Q), sludge percentage at output (SL), complexity of treatment (C), time needed for treatment (T), and deployment cost (DC). A novel parameter, model rank, is proposed that combines all the performance metrics into a single number so that the treatment models can be analyzed effectively. Results show that advanced oxidation processes with ozone treatment (AOPO), Kernel principal components analysis-based one-class support vector machine (KPCA SVM), electrochemical processes (EPs), membrane and absorption (MA), Nondominated Sorting Genetic Algorithm-based Optimal Controller (NSGAOC), and wet-type nonthermal plasma reactor (WTNPR) models have a rank above 3.5. The AOPO model has the highest model rank of 3.85 and thus has better overall performance than others. This study might aid major stakeholders in waste treatment industry including researchers in selecting the appropriate wastewater treatment method according to their requirements.

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Wastewater Monitoring Raises Privacy and Ethical Considerations

Cited by 23 publications

References 22 publications

Mapping human pathogens in wastewater using a metatranscriptomic approach

Mapping human pathogens in wastewater using a metatranscriptomic approach

Re-Identification in Differentially Private Incomplete Datasets

Pragmatic analysis of wastewater treatment methods from a statistical perspective

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