Long-term SARS-CoV-2 surveillance in wastewater and estimation of COVID-19 cases: An application of wastewater-based epidemiology

Sadhana Shrestha; Bikash Malla; Made Sandhyana Angga; Niva Sthapit; Sunayana Raya; Soichiro Hirai; Aulia Fajar Rahmani; Ocean Thakali; Eiji Haramoto

doi:10.1016/j.scitotenv.2023.165270

Long-term SARS-CoV-2 surveillance in wastewater and estimation of COVID-19 cases: An application of wastewater-based epidemiology

Sci Total Environ. 2023 Oct 20:896:165270. doi: 10.1016/j.scitotenv.2023.165270. Epub 2023 Jul 1.

Authors

Sadhana Shrestha¹, Bikash Malla¹, Made Sandhyana Angga², Niva Sthapit¹, Sunayana Raya², Soichiro Hirai², Aulia Fajar Rahmani², Ocean Thakali², Eiji Haramoto³

Affiliations

¹ Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan.
² Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan.
³ Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan. Electronic address: eharamoto@yamanashi.ac.jp.

PMID: 37400022
DOI: 10.1016/j.scitotenv.2023.165270

Abstract

The role of wastewater-based epidemiology (WBE), a powerful tool to complement clinical surveillance, has increased as many grassroots-level facilities, such as municipalities and cities, are actively involved in wastewater monitoring, and the clinical testing of coronavirus disease 2019 (COVID-19) is downscaled widely. This study aimed to conduct long-term wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Yamanashi Prefecture, Japan, using one-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assay and estimate COVID-19 cases using a cubic regression model that is simple to implement. Influent wastewater samples (n = 132) from a wastewater treatment plant were collected normally once weekly between September 2020 and January 2022 and twice weekly between February and August 2022. Viruses in wastewater samples (40 mL) were concentrated by the polyethylene glycol precipitation method, followed by RNA extraction and RT-qPCR. The K-6-fold cross-validation method was used to select the appropriate data type (SARS-CoV-2 RNA concentration and COVID-19 cases) suitable for the final model run. SARS-CoV-2 RNA was successfully detected in 67 % (88 of 132) of the samples tested during the whole surveillance period, 37 % (24 of 65) and 96 % (64 of 67) of the samples collected before and during 2022, respectively, with concentrations ranging from 3.5 to 6.3 log₁₀ copies/L. This study applied a nonnormalized SARS-CoV-2 RNA concentration and nonstandardized data for running the final 14-day (1 to 14 days) offset models to estimate weekly average COVID-19 cases. Comparing the parameters used for a model evaluation, the best model showed that COVID-19 cases lagged 3 days behind the SARS-CoV-2 RNA concentration in wastewater samples during the Omicron variant phase (year 2022). Finally, 3- and 7-day offset models successfully predicted the trend of COVID-19 cases from September 2022 until February 2023, indicating the applicability of WBE as an early warning tool.

Keywords: COVID-19; Cubic regression; Prediction; SARS-CoV-2; Wastewater-based epidemiology.

MeSH terms

COVID-19* / epidemiology
Humans
RNA, Viral
SARS-CoV-2
Wastewater
Wastewater-Based Epidemiological Monitoring

Substances

Wastewater
RNA, Viral

Supplementary concepts

SARS-CoV-2 variants