Wastewater-based surveillance data to determine the COVID-19 trends in communities with low populationMendeley Data
The data presented in this article show SARS-CoV-2 viral concentration and trends in wastewater among communities with different population size. Particularly, the data show that wastewater SARS-CoV-2 concentration can better predict COVID-19 transmission in communities than clinical data. The artic...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925004834 |
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| author | Aiswarya Rani Pappu Ashley Green Melanie Oakes Sunny Jiang |
| author_facet | Aiswarya Rani Pappu Ashley Green Melanie Oakes Sunny Jiang |
| author_sort | Aiswarya Rani Pappu |
| collection | DOAJ |
| description | The data presented in this article show SARS-CoV-2 viral concentration and trends in wastewater among communities with different population size. Particularly, the data show that wastewater SARS-CoV-2 concentration can better predict COVID-19 transmission in communities than clinical data. The article also reports PMMoV data in wastewater and population data in each community, and their effects on the correlation between wastewater SARS-CoV-2 and clinical COVID-19 data. The wastewater and clinical data reported in this article are collected from 7 students’ housing communities with population ranging between 300 and 4000 residents per community. The dataset presents SARS-CoV-2 N2 and E gene as well as PMMoV concentrations in the raw wastewater samples collected from 13 sewer manholes at these communities roughly three times per week for a period of 6-months between December 2021 and June 2022. This dataset will help to 1) improve future wastewater based epidemiological models, 2) improve understanding on PMMoV concentration ranges in wastewater at low population communities, 3) develop methods to support data interpretation, and 4) understand the effects of spatial scales on sampling frequency and infection outbreak detection. |
| format | Article |
| id | doaj-art-5c480b44e08741cd80bac6484b34cc22 |
| institution | Kabale University |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-5c480b44e08741cd80bac6484b34cc222025-08-20T03:57:32ZengElsevierData in Brief2352-34092025-08-016111175610.1016/j.dib.2025.111756Wastewater-based surveillance data to determine the COVID-19 trends in communities with low populationMendeley DataAiswarya Rani Pappu0Ashley Green1Melanie Oakes2Sunny Jiang3Department of Civil and Environmental Engineering, University of California Irvine, Irvine, USADepartment of Civil and Environmental Engineering, University of California Irvine, Irvine, USADepartment of Biological Chemistry, University of California Irvine, Irvine, USADepartment of Civil and Environmental Engineering, University of California Irvine, Irvine, USA; Corresponding author.The data presented in this article show SARS-CoV-2 viral concentration and trends in wastewater among communities with different population size. Particularly, the data show that wastewater SARS-CoV-2 concentration can better predict COVID-19 transmission in communities than clinical data. The article also reports PMMoV data in wastewater and population data in each community, and their effects on the correlation between wastewater SARS-CoV-2 and clinical COVID-19 data. The wastewater and clinical data reported in this article are collected from 7 students’ housing communities with population ranging between 300 and 4000 residents per community. The dataset presents SARS-CoV-2 N2 and E gene as well as PMMoV concentrations in the raw wastewater samples collected from 13 sewer manholes at these communities roughly three times per week for a period of 6-months between December 2021 and June 2022. This dataset will help to 1) improve future wastewater based epidemiological models, 2) improve understanding on PMMoV concentration ranges in wastewater at low population communities, 3) develop methods to support data interpretation, and 4) understand the effects of spatial scales on sampling frequency and infection outbreak detection.http://www.sciencedirect.com/science/article/pii/S2352340925004834Wastewater SARS-CoV-2Wastewater PMMoVGISEpidemiological trend analysisLow population communities |
| spellingShingle | Aiswarya Rani Pappu Ashley Green Melanie Oakes Sunny Jiang Wastewater-based surveillance data to determine the COVID-19 trends in communities with low populationMendeley Data Data in Brief Wastewater SARS-CoV-2 Wastewater PMMoV GIS Epidemiological trend analysis Low population communities |
| title | Wastewater-based surveillance data to determine the COVID-19 trends in communities with low populationMendeley Data |
| title_full | Wastewater-based surveillance data to determine the COVID-19 trends in communities with low populationMendeley Data |
| title_fullStr | Wastewater-based surveillance data to determine the COVID-19 trends in communities with low populationMendeley Data |
| title_full_unstemmed | Wastewater-based surveillance data to determine the COVID-19 trends in communities with low populationMendeley Data |
| title_short | Wastewater-based surveillance data to determine the COVID-19 trends in communities with low populationMendeley Data |
| title_sort | wastewater based surveillance data to determine the covid 19 trends in communities with low populationmendeley data |
| topic | Wastewater SARS-CoV-2 Wastewater PMMoV GIS Epidemiological trend analysis Low population communities |
| url | http://www.sciencedirect.com/science/article/pii/S2352340925004834 |
| work_keys_str_mv | AT aiswaryaranipappu wastewaterbasedsurveillancedatatodeterminethecovid19trendsincommunitieswithlowpopulationmendeleydata AT ashleygreen wastewaterbasedsurveillancedatatodeterminethecovid19trendsincommunitieswithlowpopulationmendeleydata AT melanieoakes wastewaterbasedsurveillancedatatodeterminethecovid19trendsincommunitieswithlowpopulationmendeleydata AT sunnyjiang wastewaterbasedsurveillancedatatodeterminethecovid19trendsincommunitieswithlowpopulationmendeleydata |