Surveillance of Wastewater for Early Epidemic Prediction (SWEEP): Environmental and health security perspectives in the post COVID-19 Anthropocene

Wastewater surveillance for viral pathogens: A tool for public health

A focus on water quality has intensified globally, considering its critical role in sustaining life and ecosystems. Wastewater, reflecting societal development, profoundly impacts public health. Wastewater-based epidemiology (WBE) has emerged as a surveillance tool for detecting outbreaks early, monitoring infectious disease trends, and providing real-time insights, particularly in vulnerable communities. WBE aids in tracking pathogens, including viruses, in sewage, offering a comprehensive understanding of community health and lifestyle habits. With the rise in global COVID-19 cases, WBE has gained prominence, aiding in monitoring SARS-CoV-2 levels worldwide. Despite advancements in water treatment, poorly treated wastewater discharge remains a threat, amplifying the spread of water-, sanitation-, and hygiene (WaSH)-related diseases. WBE, serving as complementary surveillance, is pivotal for monitoring community-level viral infections. However, there is untapped potential for WBE to expand its role in public health surveillance. This review emphasizes the importance of WBE in understanding the link between viral surveillance in wastewater and public health, highlighting the need for its further integration into public health management.

Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review

BACKGROUND

Public health surveillance plays a vital role in informing public health decision-making. The onset of the COVID-19 pandemic in early 2020 caused a widespread shift in public health priorities. Global efforts focused on COVID-19 monitoring and contact tracing. Existing public health programs were interrupted due to physical distancing measures and reallocation of resources. The onset of the COVID-19 pandemic intersected with advancements in technologies that have the potential to support public health surveillance efforts.

OBJECTIVE

This scoping review aims to explore emergent public health surveillance methods during the early COVID-19 pandemic to characterize the impact of the pandemic on surveillance methods.

METHODS

A scoping search was conducted in multiple databases and by scanning key government and public health organization websites from March 2020 to January 2022. Published papers and gray literature that described the application of new or revised approaches to public health surveillance were included. Papers that discussed the implications of novel public health surveillance approaches from ethical, legal, security, and equity perspectives were also included. The surveillance subject, method, location, and setting were extracted from each paper to identify trends in surveillance practices. Two public health epidemiologists were invited to provide their perspectives as peer reviewers.

RESULTS

Of the 14,238 unique papers, a total of 241 papers describing novel surveillance methods and changes to surveillance methods are included. Eighty papers were review papers and 161 were single studies. Overall, the literature heavily featured papers detailing surveillance of COVID-19 transmission (n=187). Surveillance of other infectious diseases was also described, including other pathogens (n=12). Other public health topics included vaccines (n=9), mental health (n=11), substance use (n=4), healthy nutrition (n=1), maternal and child health (n=3), antimicrobial resistance (n=2), and misinformation (n=6). The literature was dominated by applications of digital surveillance, for example, by using big data through mobility tracking and infodemiology (n=163). Wastewater surveillance was also heavily represented (n=48). Other papers described adaptations to programs or methods that existed prior to the COVID-19 pandemic (n=9). The scoping search also found 109 papers that discuss the ethical, legal, security, and equity implications of emerging surveillance methods. The peer reviewer public health epidemiologists noted that additional changes likely exist, beyond what has been reported and available for evidence syntheses.

CONCLUSIONS

The COVID-19 pandemic accelerated advancements in surveillance and the adoption of new technologies, especially for digital and wastewater surveillance methods. Given the investments in these systems, further applications for public health surveillance are likely. The literature for surveillance methods was dominated by surveillance of infectious diseases, particularly COVID-19. A substantial amount of literature on the ethical, legal, security, and equity implications of these emerging surveillance methods also points to a need for cautious consideration of potential harm.

Response of wastewater-based epidemiology predictor for the second wave of COVID-19 in Ahmedabad, India: A long-term data Perspective

In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1-2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions.

Municipal wastewater viral pollution in Saudi Arabia: effect of hot climate on COVID-19 disease spreading

The viral RNA of SARS-Coronavirus-2 is known to be contaminating municipal wastewater. We aimed to assess if COVID-19 disease is spreading through wastewater. We studied the amount of viral RNA in raw sewage and the efficiency of the sewage treatment to remove the virus. Sewage water was collected before and after the activated sludge process three times during summer 2020 from three different sewage treatment plants. The sewage treatment was efficient in removing SARS-CoV-2 viral RNA. Each sewage treatment plant gathered wastewater from one hospital, of which COVID-19 admissions were used to describe the level of disease occurrence in the area. The presence of SARS-CoV-2 viral RNA-specific target genes (N1, N2, and E) was confirmed using RT-qPCR analysis. However, hospital admission did not correlate significantly with viral RNA. Moreover, viral RNA loads were relatively low, suggesting that sewage might preserve viral RNA in a hot climate only for a short time.

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

This article proposes a novel method for detecting coronavirus disease 2019 (COVID-19) in an underground channel using visible light communication (VLC) and machine learning (ML). We present mathematical models of COVID-19 Deoxyribose Nucleic Acid (DNA) gene transfer in regular square constellations using a CSK/QAM-based VLC system. ML algorithms are used to classify the bands present in each electrophoresis sample according to whether the band corresponds to a positive, negative, or ladder sample during the search for the optimal model. Complexity studies reveal that the square constellation N=22i×22i,(i=3) yields a greater profit. Performance studies indicate that, for BER = 10-3, there are gains of -10 [dB], -3 [dB], 3 [dB], and 5 [dB] for N=22i×22i,(i=0,1,2,3), respectively. Based on a total of 630 COVID-19 samples, the best model is shown to be XGBoots, which demonstrated an accuracy of 96.03%, greater than that of the other models, and a recall of 99% for positive values.

COVID-19 and Water Variables: Review and Scientometric Analysis

COVID-19 has changed the world since 2020, and the field of water specifically, boosting scientific productivity (in terms of published articles). This paper focuses on the influence of COVID-19 on scientific productivity with respect to four water variables: (i) wastewater, (ii) renewable water resources, (iii) freshwater withdrawal, and (iv) access to improved and safe drinking water. The field's literature was firstly reviewed, and then the maps were built, emphasizing the strong connections between COVID-19 and water-related variables. A total of 94 countries with publications that assess COVID-19 vs. water were considered and evaluated for how they clustered. The final step of the research shows that, on average, scientific productivity on the water topic was mostly conducted in countries with lower COVID-19 infection rates but higher development levels as represented by gross domestic product (GDP) per capita and the human development index (HDI). According to the statistical analysis, the water-related variables are highly significant, with positive coefficients. This validates that countries with higher water-related values conducted more research on the relationship with COVID-19. Wastewater and freshwater withdrawal had the highest impact on the scientific productivity with respect to COVID-19. Access to safe drinking water becomes insignificant in the presence of the development parameters.

The one health perspective to improve environmental surveillance of zoonotic viruses: lessons from COVID-19 and outlook beyond

The human population has doubled in the last 50 years from about 3.7 billion to approximately 7.8 billion. With this rapid expansion, more people live in close contact with wildlife, livestock, and pets, which in turn creates increasing opportunities for zoonotic diseases to pass between animals and people. At present an estimated 75% of all emerging virus-associated infectious diseases possess a zoonotic origin, and outbreaks of Zika, Ebola and COVID-19 in the past decade showed their huge disruptive potential on the global economy. Here, we describe how One Health inspired environmental surveillance campaigns have emerged as the preferred tools to monitor human-adjacent environments for known and yet to be discovered infectious diseases, and how they can complement classical clinical diagnostics. We highlight the importance of environmental factors concerning interactions between animals, pathogens and/or humans that drive the emergence of zoonoses, and the methodologies currently proposed to monitor them-the surveillance of wastewater, for example, was identified as one of the main tools to assess the spread of SARS-CoV-2 by public health professionals and policy makers during the COVID-19 pandemic. One-Health driven approaches that facilitate surveillance, thus harbour the potential of preparing humanity for future pandemics caused by aetiological agents with environmental reservoirs. Via the example of COVID-19 and other viral diseases, we propose that wastewater surveillance is a useful complement to clinical diagnosis as it is centralized, robust, cost-effective, and relatively easy to implement.

Assessment of two types of passive sampler for the efficient recovery of SARS-CoV-2 and other viruses from wastewater

Wastewater-based epidemiology (WBE) has proven to be a useful surveillance tool during the ongoing SARS-CoV-2 pandemic, and has driven research into evaluating the most reliable and cost-effective techniques for obtaining a representative sample of wastewater. When liquid samples cannot be taken efficiently, passive sampling approaches have been used, however, insufficient data exists on their usefulness for multi-virus capture and recovery. In this study, we compared the virus-binding capacity of two passive samplers (cotton-based tampons and ion exchange filter papers) in two different water types (deionised water and wastewater). Here we focused on the capture of wastewater-associated viruses including Influenza A and B (Flu-A & B), SARS-CoV-2, human adenovirus (AdV), norovirus GII (NoVGII), measles virus (MeV), pepper mild mottle virus (PMMoV), the faecal marker crAssphage and the process control virus Pseudomonas virus phi6. After deployment, we evaluated four different methods to recover viruses from the passive samplers namely, (i) phosphate buffered saline (PBS) elution followed by polyethylene glycol (PEG) precipitation, (ii) beef extract (BE) elution followed by PEG precipitation, (iii) no-elution into PEG precipitation, and (iv) direct extraction. We found that the tampon-based passive samplers had higher viral recoveries in comparison to the filter paper. Overall, the preferred viral recovery method from the tampon passive samplers was the no-elution/PEG precipitation method. Furthermore, we evidenced that non-enveloped viruses had higher percent recoveries from the passive samplers than enveloped viruses. This is the first study of its kind to assess passive sampler and viral recovery methods amongst a plethora of viruses commonly found in wastewater or used as a viral surrogate in wastewater studies.

Changes in water use and wastewater generation influenced by the COVID-19 pandemic: A case study of China

This paper examines and projects the water use and wastewater generation during and after the SARS-CoV-2 (COVID-19) in China, and discussed the water use/wastewater generation pattern changes among different sectors. Existing studies on the impact of pandemic spread-prevention measures on water consumption and wastewater treatment during the pandemic are reviewed. The water use and wastewater discharge in China through the COVID-19 period are then projected and analyzed using Multivariate Linear Regression. The projection is carried out for years 2019-2023 and covers an (estimated) full process of pre-pandemic, pandemic outbreak, and recovery phase and provides essential information for determining the complete phase impact of the COVID-19. Two scenarios, i.e. the recovery scenario and the business as usual scenario, are set to investigate the water use and wastewater generation characteristics after the pandemic. The results imply that in both scenarios, the water use in China shows a V-shaped trend from 2019 to 2023 and reached a low point in 2020 of 5,813✕108 m3. The wastewater discharge shows an increasing trend throughout the COVID period in both scenarios. The results are also compared with the water consumption and wastewater generation during the SARS-CoV-1 period. The implication for policymakers is the possible increase of water use and wastewater discharge in the post COVID period and the necessity to ensure the water supply and control of water pollution and wastewater discharge.

Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis

Continuous surveillance of COVID-19 diffusion remains crucial to control its diffusion and to anticipate infection waves. Detecting viral RNA load in wastewater samples has been suggested as an effective approach for epidemic monitoring and the development of an effective warning system. However, its quantitative link to the epidemic status and the stages of outbreak is still elusive. Modelling is thus crucial to address these challenges. In this study, we present a novel mechanistic model-based approach to reconstruct the complete epidemic dynamics from SARS-CoV-2 viral load in wastewater. Our approach integrates noisy wastewater data and daily case numbers into a dynamical epidemiological model. As demonstrated for various regions and sampling protocols, it quantifies the case numbers, provides epidemic indicators and accurately infers future epidemic trends. Following its quantitative analysis, we also provide recommendations for wastewater data standards and for their use as warning indicators against new infection waves. In situations of reduced testing capacity, our modelling approach can enhance the surveillance of wastewater for early epidemic prediction and robust and cost-effective real-time monitoring of local COVID-19 dynamics.

Wastewater surveillance for SARS-CoV-2 to support return to campus: Methodological considerations and data interpretation

The COVID-19 pandemic has been challenging for various institutions such as school systems due to widespread closures. As schools re-open their campuses to in-person education, there is a need for frequent screening and monitoring of the virus to ensure the safety of students and staff and to limit risk to the surrounding community. Wastewater surveillance (WWS) of SARS-CoV-2 is a rapid and economical approach to determine the extent of COVID-19 in the community. The focus of this review is on the emergence of WWS as a tool for safe return to school campuses, taking into account methodological considerations such as site selection, sample collection and processing, SARS-CoV-2 quantification, and data interpretation. Recently published studies on the implementation of COVID-19 WWS on school and college campuses were reviewed. While there are several logistical and technical challenges, WWS can be used to inform decision-making at the school campus and/or building level.

Sampling strategies for wastewater surveillance: Evaluating the variability of SARS-COV-2 RNA concentration in composite and grab samples

The shedding of SARS-CoV-2 RNA titers by infected individuals, even asymptomatic and oligosymptomatic ones, allows the use of wastewater monitoring to track the COVID-19 spread in a community. This approach is interesting especially for emerging countries with limited clinical testing capabilities. However, there are still important methodological aspects that need validation so that wastewater monitoring data become more representative and useful for public health. This study evaluated the between-day and within-day variability of SARS-CoV-2 RNA concentrations in 24-hour composite and grab samples from three different sampling points, including two wastewater treatment plants (WTTP) and a sewer manhole. In the between-day evaluation (17 weeks of monitoring), a good agreement between the SARS-CoV-2 RNA concentration of each sampling method was observed. There were no significant differences between the mean concentrations of the grab and composite samples (p-value > 0.05), considering N1 and N2 gene assays. The strong relationship between composite and grab samples was proven by correlation coefficients: Pearson's r of 0.83 and Spearman's rho of 0.78 (p-value < 0.05). In within-day evaluation, 24-hour cycles were analyzed and low variability in hourly viral concentrations was observed for three sampling points. The coefficient of variation (CV) values ranged from 3.0% to 11.5%. Overall, 24-hour profiles showed that viral RNA concentrations had less variability and greater agreement with the mean values between 8 a.m. and 10 a.m, the recommended time for grab sampling. Therefore, this study provides important information on wastewater sampling techniques for COVID-19 surveillance. Wastewater monitoring information will only be useful to public health and decision-makers if we ensure data quality through best practices.

Detection of SARS-CoV-2 RNA in wastewater and importance of population size assessment in smaller cities: An exploratory case study from two municipalities in Latvia

Wastewater-based epidemiology (WBE) has regained global importance during the COVID-19 pandemic. The mobility of people and other factors, such as precipitation and irregular inflow of industrial wastewater, are complicating the estimation of the disease prevalence through WBE, which is crucial for proper crisis management. These estimations are particularly challenging in urban areas with moderate or low numbers of inhabitants in situations where movement restrictions are not adopted (as in the case of Latvia) because residents of smaller municipalities tend to be more mobile and less strict in following the rules and measures of disease containment. Thus, population movement can influence the outcome of WBE measurements significantly and may not reflect the actual epidemiological situation in the respective area. Here, we demonstrate that by combining the data of detected SARS-CoV-2 RNA copy number, 5-hydroxyindoleacetic acid (5-HIAA) analyses in wastewater and mobile call detail records it was possible to provide an accurate assessment of the COVID-19 epidemiological situation in towns that are small (COVID-19 28-day cumulative incidence r = 0.609 and 35-day cumulative incidence r = 0.89, p < 0.05) and medium-sized towns (COVID-19 21-day cumulative incidence r = 0.997, 28-day cumulative incidence r = 0.98 and 35-day cumulative incidence r = 0.997, p < 0.05). This is the first study demonstrating WBE for monitoring COVID-19 outbreaks in Latvia. We demonstrate that the application of population size estimation measurements such as total 5-HIAA and call detail record data improve the accuracy of the WBE approach.

Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fragmented sewerage systems-a case study of Jaipur (India)

The present study tracked the city-wide dynamics of severe acute respiratory syndrome-corona virus 2 ribonucleic acids (SARS-CoV-2 RNA) in the wastewater from nine different wastewater treatment plants (WWTPs) in Jaipur during the second wave of COVID-19 out-break in India. A total of 164 samples were collected weekly between February 19th and June 8th, 2021. SARS-CoV-2 was detected in 47.2% (52/110) influent samples and 37% (20/54) effluent samples. The increasing percentage of positive influent samples correlated with the city's increasing active clinical cases during the second wave of COVID-19 in Jaipur. Furthermore, wastewater-based epidemiology (WBE) evidence clearly showed early detection of about 20 days (9/9 samples reported positive on April 20th, 2021) before the maximum cases and maximum deaths reported in the city on May 8th, 2021. The present study further observed the presence of SARS-CoV-2 RNA in treated effluents at the time window of maximum active cases in the city even after tertiary disinfection treatments of ultraviolet (UV) and chlorine (Cl2) disinfection. The average genome concentration in the effluents and removal efficacy of six commonly used treatments, activated sludge process + chlorine disinfection (ASP + Cl2), moving bed biofilm reactor (MBBR) with ultraviolet radiations disinfection (MBBR + UV), MBBR + chlorine (Cl2), sequencing batch reactor (SBR), and SBR + Cl2, were compared with removal efficacy of SBR + Cl2 (81.2%) > MBBR + UV (68.8%) > SBR (57.1%) > ASP (50%) > MBBR + Cl2 (36.4%). The study observed the trends and prevalence of four genes (E, RdRp, N, and ORF1ab gene) based on two different kits and found that prevalence of N > ORF1ab > RdRp > E gene suggested that the effective genome concentration should be calculated based on the presence/absence of multiple genes. Hence, it is imperative to say that using a combination of different detection genes (E, N, RdRp, & ORF1ab genes) increases the sensitivity in WBE.

Passive sampling, a practical method for wastewater-based surveillance of SARS-CoV-2

In search of practical and affordable tools for wastewater-based surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), three independent field experiments were conducted using three passive sampler sorbents (electronegative membrane, cotton bud, and gauze) in Guelph, Ontario, Canada. Total daily cases during this study ranged from 2 to 17/100,000 people and 43/54 traditionally collected wastewater samples were positive for SARS-CoV-2 with mean detectable concentrations ranging from 8.4 to 1780 copies/ml. Viral levels on the passive samplers were assessed after 4, 8, 24, 48, 72, and 96 hrs of deployment in the wastewater and 43/54 membrane, 42/54 gauze, and 27/54 cotton bud samples were positive. A linear accumulation rate of SARS-CoV-2 on the membranes was observed up to 48 hours, suggesting the passive sampler could adequately reflect wastewater levels for up to two days of deployment. Due the variability in accumulation observed for the cotton buds and gauzes, and the pre-processing steps required for the gauzes, we recommend membrane filters as a simple cost-effective option for wastewater-based surveillance of SARS-CoV-2.

SARS-CoV-2 and other pathogens in municipal wastewater, landfill leachate, and solid waste: A review about virus surveillance, infectivity, and inactivation

This review discusses the techniques available for detecting and inactivating of pathogens in municipal wastewater, landfill leachate, and solid waste. In view of the current COVID-19 pandemic, SARS-CoV-2 is being given special attention, with a thorough examination of all possible transmission pathways linked to the selected waste matrices. Despite the lack of works focused on landfill leachate, a systematic review method, based on cluster analysis, allows to analyze the available papers devoted to sewage sludge and wastewater, allowing to focalize the work on technologies able to detect and treat pathogens. In this work, great attention is also devoted to infectivity and transmission mechanisms of SARS-CoV-2. Moreover, the literature analysis shows that sewage sludge and landfill leachate seem to have a remote chance to act as a virus transmission route (pollution-to-human transmission) due to improper collection and treatment of municipal wastewater and solid waste. However due to the incertitude about virus infectivity, these possibilities cannot be excluded and need further investigation. As a conclusion, this paper shows that additional research is required not only on the coronavirus-specific disinfection, but also the regular surveillance or monitoring of viral loads in sewage sludge, wastewater, and landfill leachate. The disinfection strategies need to be optimized in terms of dosage and potential adverse impacts like antimicrobial resistance, among many other factors. Finally, the presence of SARS-CoV-2 and other pathogenic microorganisms in sewage sludge, wastewater, and landfill leachate can hamper the possibility to ensure safe water and public health in economically marginalized countries and hinder the realization of the United Nations' sustainable development goals (SDGs).

Wastewater surveillance-based city zonation for effective COVID-19 pandemic preparedness powered by early warning: A perspectives of temporal variations in SARS-CoV-2-RNA in Ahmedabad, India

Following the proven concept, capabilities, and limitations of detecting the RNA of Severe Acute Respiratory Coronavirus 2 (SARS-CoV-2) in wastewater, it is pertinent to understand the utility of wastewater surveillance data on various scale. In the present work, we put forward the first wastewater surveillance-based city zonation for effective COVID-19 pandemic preparedness. A three-month data of Surveillance of Wastewater for Early Epidemic Prediction (SWEEP) was generated for the world heritage city of Ahmedabad, Gujarat, India. In this expedition, 116 wastewater samples were analyzed to detect SARS-CoV-2 RNA, from September 3rd to November 26th, 2020. A total of 111 samples were detected with at least two out of three SARS-CoV-2 genes (N, ORF 1ab, and S). Monthly variation depicted a significant decline in all three gene copies in October compared to September 2020, followed by a sharp increment in November 2020. Correspondingly, the descending order of average effective gene concentration was: November (~10,729 copies/L) > September (~3047 copies/L) > October (~454 copies/L). Monthly variation of SARS-CoV-2 RNA in the wastewater samples may be ascribed to a decline of 20.48% in the total number of active cases in October 2020 and a rise of 1.82% in November 2020. Also, the monthly recovered new cases were found to be 16.61, 20.03, and 15.58% in September, October, and November 2020, respectively. The percentage change in the gene concentration was observed in the lead of 1-2 weeks with respect to the percentage change in the provisional figures of confirmed cases. SWEEP data-based city zonation was matched with the heat map of the overall COVID-19 infected population in Ahmedabad city, and month-wise effective gene concentration variations are shown on the map. The results expound on the potential of WBE surveillance of COVID-19 as a city zonation tool that can be meaningfully interpreted, predicted, and propagated for community preparedness through advanced identification of COVID-19 hotspots within a given city.

Impacts of COVID-19 on the Aquatic Environment and Implications on Aquatic Food Production

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulted in ecological changes of aquatic ecosystems, affected the aquatic food supply chain, and disrupted the socio-economy of global populations. Due to reduced human activities during the pandemic, the aquatic environment was reported to improve its water quality, wild fishery stocks, and biodiversity. However, the sudden surge of plastics and biomedical wastes during the COVID-19 pandemic masked the positive impacts and increased the risks of aquatic pollution, especially microplastics, pharmaceuticals, and disinfectants. The transmission of SARS-CoV-2 from wastewater treatment plants to natural water bodies could have serious impacts on the environment and human health, especially in developing countries with poor waste treatment facilities. The presence and persistence of SARS-CoV-2 in human excreta, wastewaters, and sludge and its transmission to aquatic ecosystems could have negative impacts on fisheries and aquaculture industries, which have direct implications on food safety and security. COVID-19 pandemic-related environmental pollution showed a high risk to aquatic food security and human health. This paper reviews the impacts of COVID-19, both positive and negative, and assesses the causes and consequences of anthropogenic activities that can be managed through effective regulation and management of eco-resources for the revival of biodiversity, ecosystem health, and sustainable aquatic food production.

SARS-CoV-2 and other pathogenic microorganisms in the environment

The title of the Virtual Special Issue (VSI) "SARS-CoV-2 and other pathogenic microorganisms in the environment", clearly indicates a main focus not only on the virus causing the current pandemic, but also on other pathogenic microorganisms and their spatial and temporal dynamics in environmental compartments. Overall, the VSI has received more than 100 submissions relating to most of the possible fields connected to the pandemic, many of them of high scientific value. A rigorous peer-reviewing process has been carried out, with a panel of experts making a great work to evaluate that important number of submissions. As a result, those manuscripts reaching the highest scientific standards were selected for publication. We think that the papers included constitute a set of high-quality contributions, which should help to improve the overall scientific perspective regarding this crucial issue. In this piece, the Editors comment some issues on the papers accepted for publication, and include additional reflections.