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28th August 2020

Tracking SARS-CoV-2 via Municipal Wastewater

Tracking SARS-COV2 via Municipal Wastewater. Cover photographs courtesy of : John Barr and David Wills (Scottish Water) and Alison  Tidswell (Roslin Institute)

Sampling wastewater from a community can be a relatively straightforward way to determine if specific agents are being excreted by that population. As SARSCoV-2, the causative agent of COVID19, can be present in the faeces of infected people, then it may be possible to determine if a community has infected individuals by monitoring the wastewater or other sewage samples for the presence of the virus. The most sensitive method for detection of the virus is to amplify sections of its RNA genome, a practice that is now applied to respiratory tract swabs worldwide to determine whether people are infected. This three-month project had two main objectives: (1) to test methods to concentrate, extract and amplify viral RNA from different wastewater samples to work out whether the virus can be detected; (2) to add a safe ‘control’ virus into wastewater samples to compare the efficiency of methods between different laboratories and to account for losses during processing to help determine exactly how many SARS-CoV-2 viral particles were in the wastewater sample. A key point is that this project was not assessing whether any detected SARS-CoV-2 RNA represented the presence of infectious viral particles. The focus was to develop a detection tool for the virus in communities that could help to identify infected populations. The project compared several published methods for viral extraction from wastewater and then looked at other sewage plant samples such as ‘sludge’ and ‘cake’ as well as some of the outflow water that is released into the environment. The main results were as follows: (1) A safe control virus was compared against SARS-CoV-2 as a way to measure detection efficiency from different types of samples. This control virus behaved in a very similar way to the pandemic virus and is now being supplied to other laboratories as a safe way to test any concentration and extraction methods. We used both this virus and SARS-CoV-2 to measure the efficiency of the methods trialled. (2) SARS-CoV-2 virus was detected in certain wastewater samples collected during the initial wave of the pandemic in Scotland. The different methods tested offer different pros and cons. The two main methods, spin filter columns and PEG precipitation can both work, but both can have high losses of virus. Columns are quite expensive and may be subject to supply problems, whereas precipitation can more easily handle larger volumes, but requires a high-speed spin step needing more specialised equipment. (3) Direct extraction from more solid samples such as ‘sludge’ and ‘cake’ does not require a concentration step and while this was more sensitive, it was only possible to test a small number of samples, so further work is needed to confirm this. (4) No SARS-CoV-2 RNA was detected in the outflow water during the tests, whilst given that primary sludge is treated (e.g. pasteurized, heat-dried, alkali-lime treated), as per legislative requirements, concentration of viral RNA in the solid phase should pose no further risk to human health. In summary, wastewater and other samples from wastewater plants can be used to determine the presence of SARS-CoV-2 in the local population. The sensitivity of this approach needs to be evaluated, but it offers the potential to monitor populations with much lower levels of sample processing than testing of individuals. More work is required to translate levels of viral RNA in wastewater to the level of infection within the community. While more samples need to be evaluated, SARS-CoV-2 virus was not detected in outflow water released from a wastewater plant receiving wastewater containing the virus. Infectivity was not assessed, but the low levels of SARS-CoV-2 RNA detected are unlikely to represent an additional threat to the health of individuals that work with wastewater taking standard precautions in their work environment.