Statistical Analysis of SARS-CoV-2 Using Wastewater-Based Data of Stockholm, Sweden

Aashlesha Chekkala, Merve Atasoy, Cecilia Williams and Zeynep Cetecioglu ()
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Aashlesha Chekkala: Department of Chemical Engineering, KTH Royal Institute of Technology, 10044 Stockholm, Sweden
Merve Atasoy: Department of Chemical Engineering, KTH Royal Institute of Technology, 10044 Stockholm, Sweden
Cecilia Williams: Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, 17121 Solna, Sweden
Zeynep Cetecioglu: Department of Chemical Engineering, KTH Royal Institute of Technology, 10044 Stockholm, Sweden

IJERPH, 2023, vol. 20, issue 5, 1-12

Abstract: 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.

Keywords: wastewater-based epidemiology; SARS-CoV-2; PMMoV; statistical analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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