Censored Regression Modeling To Predict Virus Inactivation in Wastewaters
- Submitting institution
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The University of Surrey
- Unit of assessment
- 12 - Engineering
- Output identifier
- 9001442_1
- Type
- D - Journal article
- DOI
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10.1021/acs.est.6b05190
- Title of journal
- Environmental Science & Technology
- Article number
- -
- First page
- 1795
- Volume
- 51
- Issue
- 3
- ISSN
- 0013-936X
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2017
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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- Research group(s)
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- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Following from a World Health Organisation (WHO) publication in which recommendations were formulated regarding Ebola contaminated waste (https://www.who.int/bulletin/volumes/94/6/15-163931/en/), this work develops a method to estimate the persistence of Ebola virus in wastewater. It can be used to predict inactivation rates of other enveloped viruses from virus and matrix characteristics, providing valuable input when formulating risk management strategies. Originally undertaken to inform decisions by WHO during the West Africa Ebola crisis in 2013, it is now cited in relation to Coronaviruses and wastewaters e.g. Foladori et al., 2020 (https://doi.org/10.1016/j.scitotenv.2020.140444); Guillier et al., 2020 (https://aem.asm.org/content/86/18/e01244-20), Aquino de Carvalho et al., 2020 (https://doi.org/10.1021/acs.est.7b01296)
- Author contribution statement
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- Non-English
- No
- English abstract
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