A recent study published in Emerging Infectious Diseases assesses correlations between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) load in untreated wastewater with coronavirus disease 2019 (COVID-19) cases and associated hospitalizations.
Study: Omicron COVID-19 case estimates based on previous SARS-CoV-2 wastewater load, Regional Municipality of Peel, Ontario, Canada. Image Credit: hxdyl / Shutterstock.com
Advantages of wastewater surveillance
Early COVID-19 studies suggested that wastewater SARS-CoV-2 surveillance could help determine disease prevalence. Numerous studies have since demonstrated the viability of wastewater surveillance, which can be particularly relevant when the eligibility for polymerase chain reaction (PCR) testing changes or healthcare facilities are facing overwhelmed testing capacity.
By July 2022, COVID-19 incidence in the Peel regional municipality in Ontario, Canada, was among the highest in the province. Due to the surge in COVID-19 cases after the emergence of the SARS-CoV-2 Omicron variant, clinical SARS-CoV-2 testing in Ontario was restricted to at-risk groups beginning December 30, 2021. As a result, wastewater surveillance has become an essential tool to monitor COVID-19 levels in the community.
About the study
Untreated wastewater was sampled three to five days a week from the two wastewater treatment plants of G.E. Booth and Clarkson in Peel. Composite wastewater samples were collected before screening and grit removal.
Subsequently, viral ribonucleic acid (RNA) was extracted and purified for reverse-transcription PCR (RT-PCR) testing. COVID-19 case data extraction was restricted to patients who were permanent Peel residents at the time of diagnosis between August 30, 2020, and June 18, 2022. Additionally, aggregate data on COVID-19 hospitalization from the provincial Health Ministry’s daily bed census was obtained during the study period.
Data were stratified by each successive COVID-19 wave. Pearson correlation coefficients were calculated to determine the associations between wastewater SARS-CoV-2 loads and COVID-19 cases using a lag of zero to five days between the dates of sampling and reported COVID-19 cases. Since COVID-19-related hospitalizations were not specific to sewer sheds across Peel hospitals, daily viral loads at the two plants were aggregated.
Correlation coefficients were determined between total viral loads and hospitalizations between one- and 14-day from sampling and hospitalization dates. The researchers estimated the median ratio between daily wastewater loads and COVID-19 cases for each epidemic wave. Simple linear regression modeling was used to predict COVID-19 incidence during the Omicron wave(s) using pre-Omicron data on wastewater SARS-CoV-2 loads and reported cases.
Clinical testing underestimates local transmission of SARS-CoV-2
During the second, third, and fourth COVID-19 waves, the median daily load of SARS-CoV-2 in wastewater from G.E. Booth was twice that of Clarkson. The number of mean weekly PCR tests and test positivity were similar during the second and third COVID-19 waves. Clinical PCR testing and test positivity were low during the Delta variant-predominant fourth wave, with fewer COVID-19 cases and hospitalizations.
During the fifth wave, which was dominated by the Omicron BA.1 variant, the magnitude of COVID-19 cases did not align with the load of SARS-CoV-2 in wastewater samples. In fact, the daily median viral load in wastewater was much higher during the Omicron BA.2-predominant sixth wave than in preceding waves.
Correlations between wastewater SARS-CoV-2 loads and reported cases were strongest on the sampling date. Pre-Omicron, these correlations were the highest on the sampling date at G.E. Booth and one day after sampling at Clarkson. The correlation was the strongest during the Alpha-dominant third wave.
The correlations between total viral loads and COVID-19 hospitalizations were strongest during the third and fifth waves. Weak associations were noted during the Delta wave.
The highest correlation between wastewater viral loads and hospitalizations occurred four days after sampling. The median wastewater viral load-to-case ratios were not statistically different for the second, third, or fourth COVID-19 waves. Nevertheless, these ratios were significantly higher during the fifth and sixth waves.
The linear regression model predicted 7,515 cases at the peak of wastewater viral load during the fifth wave, which was much higher than the actual report of 1,160 cases. Likewise, the model predicted 3,170 cases at the peak of wastewater viral load in the sixth wave, more than 18-fold higher than what was reported.
Well into the COVID-19 pandemic, the provincial government of Ontario introduced changes in clinical PCR testing policy and eligibility. Consequently, the number of PCR tests declined, and the percent positivity and wastewater viral load-to-case ratio increased in Peel.
The study findings suggest a 6.5- and 18.7-fold underestimation of COVID-19 cases at the peak of the fifth and sixth COVID-19 waves, respectively. Thus, wastewater data can be helpful in COVID-19 surveillance and local decision-making.
- Cheng, L., Dhiyebi, H., Varia, M., et al. (2023). Omicron COVID-19 case estimates based on previous SARS-CoV-2 wastewater load, Regional Municipality of Peel, Ontario, Canada. Emerging Infectious Diseases. doi:10.3201/eid2908.221580
Posted in: Medical Science News | Medical Research News | Medical Condition News | Disease/Infection News | Healthcare News
Tags: Clinical Testing, Coronavirus, Coronavirus Disease COVID-19, covid-19, Healthcare, Infectious Diseases, Omicron, Pandemic, Polymerase, Polymerase Chain Reaction, Respiratory, Ribonucleic Acid, RNA, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Syndrome, Transcription
Tarun Sai Lomte
Tarun is a writer based in Hyderabad, India. He has a Master’s degree in Biotechnology from the University of Hyderabad and is enthusiastic about scientific research. He enjoys reading research papers and literature reviews and is passionate about writing.
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