Optimal Selection of Sampling Points for Detecting SARS-CoV-2 RNA in Sewer System Using NSGA-II Algorithm
Sampling and analysing urban wastewater are found to be a reliable indicator of the regional spread of infectious diseases. During the COVID-19 pandemic, several research groups around the globe sampled wastewater from treatment plants or other points throughout a sewer system and tried to identify...
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/15/23/4076 |
| _version_ | 1797399497347694592 |
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| author | Argyro Gkatzioura Antigoni Zafeirakou |
| author_facet | Argyro Gkatzioura Antigoni Zafeirakou |
| author_sort | Argyro Gkatzioura |
| collection | DOAJ |
| description | Sampling and analysing urban wastewater are found to be a reliable indicator of the regional spread of infectious diseases. During the COVID-19 pandemic, several research groups around the globe sampled wastewater from treatment plants or other points throughout a sewer system and tried to identify the presence of the virus. Since infected persons are found to excrete the virus in their feces and urine, urban wastewater analysis proved to be a valuable tool for the early detection of spikes in the disease. In the present study, an effort was made to investigate several fate and transport scenarios of SARS-CoV-2 in a sewer system. USEPA’s Storm Water Management Model (SWMM) was utilized for the analysis. The modelling results were then used as an input to an optimization procedure using an NSGA-II algorithm. The optimization procedure aimed to determine the appropriate number and combination of sampling points for a better assessment of the disease’s dispersion in the community. Four to six sampling points seem to offer a high likelihood of SARS-CoV-2 RNA detection in minimum time, representing the maximum population. |
| first_indexed | 2024-03-09T01:41:07Z |
| format | Article |
| id | doaj.art-72eb2e7ab31445cc8dad725768abf677 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-09T01:41:07Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-72eb2e7ab31445cc8dad725768abf6772023-12-08T15:28:20ZengMDPI AGWater2073-44412023-11-011523407610.3390/w15234076Optimal Selection of Sampling Points for Detecting SARS-CoV-2 RNA in Sewer System Using NSGA-II AlgorithmArgyro Gkatzioura0Antigoni Zafeirakou1Department of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceDepartment of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceSampling and analysing urban wastewater are found to be a reliable indicator of the regional spread of infectious diseases. During the COVID-19 pandemic, several research groups around the globe sampled wastewater from treatment plants or other points throughout a sewer system and tried to identify the presence of the virus. Since infected persons are found to excrete the virus in their feces and urine, urban wastewater analysis proved to be a valuable tool for the early detection of spikes in the disease. In the present study, an effort was made to investigate several fate and transport scenarios of SARS-CoV-2 in a sewer system. USEPA’s Storm Water Management Model (SWMM) was utilized for the analysis. The modelling results were then used as an input to an optimization procedure using an NSGA-II algorithm. The optimization procedure aimed to determine the appropriate number and combination of sampling points for a better assessment of the disease’s dispersion in the community. Four to six sampling points seem to offer a high likelihood of SARS-CoV-2 RNA detection in minimum time, representing the maximum population.https://www.mdpi.com/2073-4441/15/23/4076SARS-CoV-2EPA SWMMwastewaterwastewater surveillancesampling pointsoptimization |
| spellingShingle | Argyro Gkatzioura Antigoni Zafeirakou Optimal Selection of Sampling Points for Detecting SARS-CoV-2 RNA in Sewer System Using NSGA-II Algorithm Water SARS-CoV-2 EPA SWMM wastewater wastewater surveillance sampling points optimization |
| title | Optimal Selection of Sampling Points for Detecting SARS-CoV-2 RNA in Sewer System Using NSGA-II Algorithm |
| title_full | Optimal Selection of Sampling Points for Detecting SARS-CoV-2 RNA in Sewer System Using NSGA-II Algorithm |
| title_fullStr | Optimal Selection of Sampling Points for Detecting SARS-CoV-2 RNA in Sewer System Using NSGA-II Algorithm |
| title_full_unstemmed | Optimal Selection of Sampling Points for Detecting SARS-CoV-2 RNA in Sewer System Using NSGA-II Algorithm |
| title_short | Optimal Selection of Sampling Points for Detecting SARS-CoV-2 RNA in Sewer System Using NSGA-II Algorithm |
| title_sort | optimal selection of sampling points for detecting sars cov 2 rna in sewer system using nsga ii algorithm |
| topic | SARS-CoV-2 EPA SWMM wastewater wastewater surveillance sampling points optimization |
| url | https://www.mdpi.com/2073-4441/15/23/4076 |
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