SARS-CoV-2: fate in water environments and sewage surveillance as an early warning system

Techno-environmental study on the consequences of carwash wastewater and its management methods

Carwash wastewater (CWW) is an important source of environmental pollution. The aim of this study was to investigate the characteristics of CWW and technical comparison of its treatment methods. For this purpose, a systematic search was conducted and after three stages of screening the found articles, finally 30 articles were selected for this review. The results showed that due to the differences in the type of washing, the geological condition, the type of car, and the climatic conditions, the CWWs have temporal and spatial variation in the concentration of pollutants. However, the most important pollutants of CWW include oil, suspended solids, detergents, and organic compounds. The most widely used methods in CWW treatment in the main stages included chemical coagulation and electrocoagulation, which reduce turbidity by more than 90% and COD by more than 50% in the best efficiency. Also, membrane technology was a common method in CWW treatment systems to achieve proper effluent quality. COD reduction by ultrafiltration, nanofiltration, microfiltration, and reverse osmosis was 95-77%, more than 90%, 81-73%, and 87%, respectively. The efficiency of membrane technologies in reducing turbidity was often more than 90% and in few cases more than 50%. Sludge production in the coagulation process, energy consumption in electrochemical processes, and the low water recovery rate in membrane processes are important challenges in CWW treatment that must be managed by modifying the process or using combined methods.

Assessing wastewater-based epidemiology for the prediction of SARS-CoV-2 incidence in Catalonia

While wastewater-based epidemiology has proven a useful tool for epidemiological surveillance during the COVID-19 pandemic, few quantitative models comparing virus concentrations in wastewater samples and cumulative incidence have been established. In this work, a simple mathematical model relating virus concentration and cumulative incidence for full contagion waves was developed. The model was then used for short-term forecasting and compared to a local linear model. Both scenarios were tested using a dataset composed of samples from 32 wastewater treatment plants and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) incidence data covering the corresponding geographical areas during a 7-month period, including two contagion waves. A population-averaged dataset was also developed to model and predict the incidence over the full geography. Overall, the mathematical model based on wastewater data showed a good correlation with cumulative cases and allowed us to anticipate SARS-CoV-2 incidence in one week, which is of special relevance in situations where the epidemiological monitoring system cannot be fully implemented.

Comparison of analytical sensitivity and efficiency for SARS-CoV-2 primer sets by TaqMan-based and SYBR Green-based RT-qPCR

Abstract

The pandemic of coronavirus disease 2019 (COVID-19) continues to threaten public health. For developing countries where vaccines are still in shortage, cheaper alternative molecular methods for SARS-CoV-2 identification can be crucial to prevent the next wave. Therefore, 14 primer sets recommended by the World Health Organization (WHO) was evaluated on testing both clinical patient and environmental samples with the gold standard diagnosis method, TaqMan-based RT-qPCR, and a cheaper alternative method, SYBR Green-based RT-qPCR. Using suitable primer sets, such as ORF1ab, 2019_nCoV_N1 and 2019_nCoV_N3, the performance of the SYBR Green approach was comparable or better than the TaqMan approach, even when considering the newly dominating or emerging variants, including Delta, Eta, Kappa, Lambda, Mu, and Omicron. ORF1ab and 2019_nCoV_N3 were the best combination for sensitive and reliable SARS-CoV-2 molecular diagnostics due to their high sensitivity, specificity, and broad accessibility.

Key points

• With suitable primer sets, the SYBR Green method performs better than the TaqMan one.

• With suitable primer sets, both methods should still detect the new variants well.

• ORF1ab and 2019_nCoV_N3 were the best combination for SARS-CoV-2 detection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-022-11822-4.