Regional and temporal differences in the relation between SARS-CoV-2 biomarkers in wastewater and estimated infection prevalence - Insights from long-term surveillance.

Wastewater-based epidemiology provides a conceptual framework for the evaluation of the prevalence of public health related biomarkers. In the context of the Coronavirus disease-2019, wastewater monitoring emerged as a complementary tool for epidemic management. In this study, we evaluated data from six wastewater treatment plants in the region of Saxony, Germany. The study period lasted from February to December 2021 and covered the third and fourth regional epidemic waves. We collected 1065 daily composite samples and analyzed SARS-CoV-2 RNA concentrations using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Regression models quantify the relation between RNA concentrations and disease prevalence. We demonstrated that the relation is site and time specific. Median loads per diagnosed case differed by a factor of 3-4 among sites during both waves and were on average 45 % higher during the third wave. In most cases, log-log-transformed data achieved better regression performance than non-transformed data and local calibration outperformed global models for all sites. The inclusion of lag/lead time, discharge and detection probability improved model performance in all cases significantly, but the importance of these components was also site and time specific. In all cases, models with lag/lead time and log-log-transformed data obtained satisfactory goodness-of-fit with adjusted coefficients of determination higher than 0.5. Back-estimation of testing efficiency from wastewater data confirmed state-wide prevalence estimation from individual testing statistics, but revealed pronounced differences throughout the epidemic waves and among the different sites.

Regional and temporal differences in the relation between SARS-CoV-2 biomarkers in wastewater and estimated infection prevalence – Insights from long-term surveillance

Wastewater-based epidemiology provides a conceptual framework for the evaluation of the prevalence of public health related biomarkers. In the context of the Coronavirus disease-2019, wastewater monitoring emerged as a complementary tool for epidemic management. In this study, we evaluated data from six wastewater treatment plants in the region of Saxony, Germany. The study period lasted from February to December 2021 and covered the third and fourth regional epidemic waves. We collected 1065 daily composite samples and analyzed SARS-CoV-2 RNA concentrations using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Regression models quantify the relation between RNA concentrations and disease prevalence. We demonstrated that the relation is site and time specific. Median loads per diagnosed case differed by a factor of 3–4 among sites during both waves and were on average 45 % higher during the third wave. In most cases, log-log-transformed data achieved better regression performance than non-transformed data and local calibration outperformed global models for all sites. The inclusion of lag/lead time, discharge and detection probability improved model performance in all cases significantly, but the importance of these components was also site and time specific. In all cases, models with lag/lead time and log-log-transformed data obtained satisfactory goodness-of-fit with adjusted coefficients of determination higher than 0.5. Back-estimation of testing efficiency from wastewater data confirmed state-wide prevalence estimation from individual testing statistics, but revealed pronounced differences throughout the epidemic waves and among the different sites. Graphical Unlabelled Image

Transmission risk of SARS-CoV-2 in the watershed triggered by domestic wastewater discharge.

The outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has already become an unprecedented global pandemic. However, the transmission of SARS-CoV-2, especially the protected SARS-CoV-2 RNA (pRNA) with infectious particles in waterways, is still largely unexplored. In this study, we developed a model to estimate SARS-CoV-2 transmission from the risk source in the excretion of patients to the final exposure in surface water. The model simulated the spatial and temporal distribution of the viral pRNA concentrations in the surface water of the Elbe watershed from March 2020 to January 2021. The results show that the WWTPs with the maximum capacity of >10,000 population equivalents were responsible for 95% of the viral load discharged into the surface water. We estimated the pRNA concentrations in surface water to be 1.33 × 10-2 copies·L-1 on average in the watershed based on the model simulation on viral transmission. It had considerable variations in spatial and temporal scales, which are dominantly controlled by epidemic situations and virus transport with decay in water, respectively. A quantitative microbial risk assessment was conducted to estimate the viral infection probability from surface water ingestion with consideration of the influence of toilet usage frequency and gender/age population groups. All the infection probabilities in the study period were lower than the reference risk levels of 10-4 and 10-5. The individuals aged 15-34 years had the highest infection probability of 4.86 × 10-9 on average from surface water ingestion during swimming activities. The data provided herein suggest that the low pRNA concentrations and infection probability reflected that the waterways were unlikely to be a significant transmission route for SARS-CoV-2.

Is There a Role for Environmental and Metabolic Factors Predisposing to Severe COVID-19?

The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pandemic affects people around the world. However, there have been striking differences in the number of infected individuals and deaths in different countries. Particularly, within Central Europe in countries that are similar in ethnicity, age, and medical standards and have performed similar steps of containment, such differences in mortality rates remain inexplicable. We suggest to consider and explore environmental factors to explain these intriguing variations. Countries like Northern Italy, France, Spain, and UK have suffered from 5 times more deaths from the corona virus infection than neighboring countries like Germany, Switzerland, Austria, and Denmark related to the size of their respective populations. There is a striking correlation between the level of environmental pollutants including pesticides, dioxins, and air pollution such as NO2 known to affect immune function and healthy metabolism with the rate of mortality in COVID-19 pandemic in these European countries. There is also a correlation with the use of chlorination of drinking water in these regions. In addition to the improvement of environmental protective programs, there are possibilities to lower the blood levels of these pollutants by therapeutic apheresis. Furthermore, therapeutic apheresis might be an effective method to improve metabolic inflammation, altered vascular perfusion, and neurodegeneration observed as long-term complications of COVID-19 disease.