Wastewater-based epidemiology has been used as a tool for surveillance of COVID-19 infections. This approach is dependent on the detection and quantification of SARS-CoV-2 RNA in untreated/raw wastewater. However, the quantification of the viral RNA could be influenced by the physico-chemical properties of the wastewater. This study presents the first use of Adaptive Neuro-Fuzzy Inference System (ANFIS) to determine the potential impact of physico-chemical characteristics of wastewater on the detection and concentration of SARS-CoV-2 RNA in wastewater. Raw wastewater samples from four wastewater treatment plants were investigated over four months. The physico-chemical characteristics of the raw wastewater was recorded, and the SARS-CoV-2 RNA concentration determined via amplification with droplet digital polymerase chain reaction. The wastewater characteristics considered were chemical oxygen demand, flow rate, ammonia, pH, permanganate value, and total solids. The mean SARS-CoV-2 RNA concentrations ranged from 648.1(±514.6) copies/mL to 1441.0(±1977.8) copies/mL. Among the parameters assessed using the ANFIS model, ammonia and pH showed significant association with the concentration of SARS-CoV-2 RNA measured. Increasing ammonia concentration was associated with increasing viral RNA concentration and pH between 7.1 and 7.4 were associated with the highest SARS-CoV-2 concentration. Other parameters, such as total solids, were also observed to influence the viral RNA concentration, however, this observation was not consistent across all the wastewater treatment plants. The results from this study indicate the importance of incorporating wastewater characteristic assessment into wastewater-based epidemiology for a robust and accurate COVID-19 surveillance.
Contamination of contact surfaces with SARS-CoV-2 has been reported as a potential route for the transmission of COVID-19. This could be a major issue in developing countries where access to basic sanitation is poor, leading to the sharing of toilet facilities. In this study, we report SARS-CoV-2 contamination of key contact surfaces in shared toilets and the probabilistic risks of COVID-19 infections based on detection and quantification of the nucleic acid on the surfaces. We observed that 54–69% of the contact surfaces were contaminated, with SARS-CoV-2 loads ranging from 28.1 to 132.7 gene copies per cm 2 . Toilet seats had the highest contamination, which could be attributed to shedding of the virus in feces and urine. We observed a significant reduction in viral loads on the contaminated surfaces after cleaning, showing the potential of effective cleaning on the reduction of contamination. The pattern of contamination indicates that the most contaminated surfaces are those that are either commonly touched by users of the shared toilets or easily contaminated with feces and urine. These surfaces were the toilet seats, cistern handles and tap handles. The likelihood (probability) of infection with COVID-19 on these surfaces was highest on the toilet seat (1.76 × 10 −4 (1.58 × 10 −6 )) for one time use of the toilet. These findings highlight the potential risks for COVID-19 infections in the event that intact infectious viral particles are deposited on these contact surfaces. Therefore, this study shows that shared toilet facilities in densely populated areas could lead to an increase in risks of COVID-19 infections. This calls for the implementation of risk reduction measures, such as regular washing of hands with soap, strict adherence to wearing face masks, and effective and regular cleaning of shared facilities.
Reverse transcription loop-mediated isothermal amplification (RT-LAMP) has the potential to become a cheaper and faster option for monitoring COVID-19 infections through wastewater-based epidemiology. However, its application in COVID-19 surveillance has been limited to clinical testing only. We present in this paper two optimized RT-LAMP protocols based on colour change and fluorescence detection and application of these protocols for wastewater monitoring from four wastewater treatment plants over 4 weeks. The optimized RT-LAMP protocols have a limit of detection of 10 copies/25 µl reaction with positive amplification within 35 minutes. Over the 4 weeks of monitoring, the colorimetric protocol detected a prevalence of 12.5%, when 1 µl of extracted RNA with 92.7(± 28.2) ng/µl concentration was analysed. When the RNA template was increased by fivefold, the prevalence increased to 44%. The fluorescent RT-LAMP had a prevalence of 31% and 47% for starting templates of 92.7(± 28.2) ng/µl and 480(± 134.5) ng/µl of the extracted RNA, respectively. All samples were positive for SARS-CoV-2 when analysed with droplet digital PCR, with viral loads ranging from 18.1 to 195.6 gc/ml of wastewater. The RT-ddPCR, therefore, confirms the presence of the viral RNA in the wastewater samples, albeit at low concentrations. Additionally, the RT-LAMP protocols positively detected SARS-CoV-2 in wastewater samples with copies as low as 20.7 gc/ml. The results obtained in our study show the potential application of RT-LAMP for the detection of SARS-CoV-2 in wastewater, which could provide a cheaper and faster alternative to RT-qPCR or RT-ddPCR for wastewater-based epidemiological monitoring of COVID-19 and other viral infections.
Organic fertilizers are an essential source for plant nutrients and a soil conditioner in agriculture. Due to its sources and the composition of the organic inputs as well as the type, functionality and failures of the applied treatment process, the organic fertilizer may contain various amounts of infectious agents and toxic chemicals, especially the antibiotics that can be introduced to the subsequent food chain. " range of human and animal pathogens of bacterial, viral and parasitic origin have been the cause of foodborne epidemics due to unintended contamination from organic fertilizers. The use of antibiotics by humans and in animal feeds will also end up in the organic fertilizers. These antibiotics and other chemicals, depending on the sources of the organics, will enhance the likelihood of occurrence of resistant and multi-resistant strains of microorganisms in society and have been reported to cause ecotoxicological environmental effects and disruption of the ecological balance. Exposure of microorganisms to sublethal concentration of antibiotics in the organic products induces antibiotic resistance. WHO guidelines for the reuse of excreta and other organic matters identify the risk for the exposed groups to the reuse of the excreta and are applicable in the use of organic fertilizers in agriculture.
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