Statistical Analysis of Sars-CoV-2 Using Wastewater-Based Data of Stockholm, Sweden
Bibliographic Data
| ID | 15501985 |
|---|---|
| Authors | Aashlesha Chekkala Vivekanand (0000-0002-3821-5352, KTH Royal Institute of Technology), Merve Atasoy (0000-0003-4046-1592, KTH Royal Institute of Technology), Cecilia Williams (0000-0002-0602-2062, Science for Life Laboratory), Zeynep Çetecioğlu (0000-0002-8170-379X, AlbaNova, corresponding author) |
| Year | 2023 |
| Volume | 20 |
| Issue | 5 |
| Pages | 4181-4181 |
| Publication date | 2023-02-26 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph20054181 |
| PMID | 36901194 |
| OpenAlex | W4322501291 |
| Language | EN |
| References cited | 3 |
An approach based on wastewater epidemiology can be used to monitor the COVID-19 pandemic by assessing the gene copy number of SARS-CoV-2 in wastewater. In the present study, we statistically analyzed such data from six inlets of three wastewater treatment plants, covering six regions of Stockholm, Sweden, collected over an approximate year period (week 16 of 2020 to week 22 of 2021). SARS-CoV-2 gene copy number and population-based biomarker PMMoV, as well as clinical data, such as the number of positive cases, intensive care unit numbers, and deaths, were analyzed statistically using correlations and principal component analysis (PCA). Despite the population differences, the PCA for the Stockholm dataset showed that the case numbers are well grouped across wastewater treatment plants. Furthermore, when considering the data from the whole of Stockholm, the wastewater characteristics (flow rate m 3 /day, PMMoV Ct value, and SARS-CoV gene copy number) were significantly correlated with the public health agency's report of SARS-CoV-2 infection rates (0.419 to 0.95, p -value < 0.01). However, while the PCA results showed that the case numbers for each wastewater treatment plant were well grouped concerning PC1 (37.3%) and PC2 (19.67%), the results from the correlation analysis for the individual wastewater treatment plants showed varied trends. SARS-CoV-2 fluctuations can be accurately predicted through statistical analyses of wastewater-based epidemiology, as demonstrated in this study
Biology · Coronavirus disease 2019 (COVID-19 · Disease · Environmental health · Population · Principal component analysis · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Sewage treatment · Statistics · Wastewater · Biosensors and Analytical Detection · Demography · Environmental Science · Mathematics · Medicine · SARS-CoV-2 and COVID-19 Research · SARS-CoV-2 detection and testing · Environmental Engineering · Epidemiology · Internal Medicine
| Citation velocity | historical |
|---|---|
| Highly cited | No |