Surveillance of omicron variants through wastewater epidemiology: Latest developments in environmental monitoring of pandemic

Reviewing the progress of infectious disease early warning systems and planning for the future

BACKGROUND

Past reviews of infectious disease early warning systems have encountered some limitations, such as a focus on specific diseases or regions in certain studies and constraints imposed by time delays in others. This study conducts a comprehensive analysis of infectious disease early warning systems, with a particular emphasis on assessing the development of these systems in the recent five years (2019 to 2023). The goal is to provide insights for future related research.

METHODS

A comprehensive retrospective review was undertaken, utilizing data sourced from four prominent databases: WanFang Data, China National Knowledge Infrastructure (CNKI), Web of Science, and PubMed. Following a meticulous classification process, a total of 49 articles aligning with our inclusion criteria were identified. To streamline the data collection and organization process, standardized extraction forms were employed, and data were efficiently organized using Microsoft Excel spreadsheet.

RESULTS

This study uncovered various warning systems, including health departments, hospitals, social media platforms, statistical bureaus, meteorological departments, and wastewater monitoring systems. Drawbacks of traditional manual and statistical models included slow responsiveness and a surge in suspected cases. In contrast, hospital-based systems utilizing blockchain and smart contract technologies efficiently shared patient data, facilitating precise disease identification. Social media systems harnessed sentiment analysis for outbreak prediction, while statistical bureau systems integrated economic and population data for a novel perspective. Meteorological systems served as valuable complements, particularly for locally transmitted diseases. Wastewater monitoring systems added support by detecting crucial biological markers.

CONCLUSION

This article conducts an in-depth analysis of infectious disease early warning systems, including systems based on various data sources. Future efforts should integrate new technologies, along with healthcare and social data, to enhance the capabilities of early warning and prediction.

Development of a wastewater based infectious disease surveillance research system in South Korea

Wastewater-based epidemiology has been used in pathogen surveillance for microorganisms at the community level. This study was conducted to determine the occurrence and trends of infectious pathogens in sewage from Yongin city and the relationships between these pathogens and the incidence of infectious diseases in the community. From December 2022 to November 2023, we collected inflow water from six wastewater treatment plants in Yongin city twice a month. The analyzed microorganisms included 15 respiratory viruses, 7 pneumonia-causing bacteria, 19 acute diarrhea-causing pathogens, SARS-CoV-2, Zika virus, hepatitis A virus, poliovirus, Mpox, and measles. They were detected through real-time PCR and conventional PCR. The concentrations of 9 pathogens among them were additionally analyzed using quantitative real time PCR. The correlation was confirmed through statistical analysis with the rate of detection for pathogens reported by the Korea Disease Control and Prevention Agency. Influenza A virus, human adenovirus, and human rhinovirus were moderately correlated (rho values of 0.45 to 0.58). Campylobacter spp. and sapovirus were strong correlated (rho values of 0.62, 0.63). Enteropathogenic E. coli, human coronavirus, and norovirus GII were very strong correlated (rho values of 0.86 to 0.92). We were able to identify the prevalence of respiratory viral infections, pneumonia, and acute diarrhea-causing pathogens in the community through wastewater-based epidemiology data. This study will be helpful in establishing a system for future surveillance of infectious diseases present in sewage.

"Long COVID" and Its Impact on The Environment: Emerging Concerns and Perspectives

The COVID-19 pandemic has caused unprecedented global health and economic crises. The emergence of long COVID-19 has raised concerns about the interplay between SARS-CoV-2 infections, climate change, and the environment. In this context, a concise analysis of the potential long-term effects of the COVID-19 epidemic along with the awareness aboutenvironmental issues are realized. While COVID-19 effects in the short-term have reduced environmental air pollutants and pressures, CO2 emissions are projected to increase as the economy recovers and growth rates return to pre-COVID-19 levels. This review discusses the systematic effects of both the short-term and long-term effects of the pandemic on the clean energy revolution and environmental issues. This article also discusses opportunities to achieve long-term environmental benefits and emphasizes the importance of future policies in promoting global environmental sustainability. Future directions for growth and recovery are presented to cope with long COVID-19 epidemic along with the critical findings focussing on various aspects: waste management, air quality improvement.

Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic

The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.

SARS-CoV-2 Monitoring in Wastewater Reveals Novel Variants and Biomarkers of Infection

Wastewater-based epidemiology (WBE) is a popular tool for the early indication of community spread of infectious diseases. WBE emerged as an effective tool during the COVID-19 pandemic and has provided meaningful information to minimize the spread of infection. Here, we present a combination of analyses using the correlation of viral gene copies with clinical cases, sequencing of wastewater-derived RNA for the viral mutants, and correlative analyses of the viral gene copies with the bacterial biomarkers. Our study provides a unique platform for potentially using the WBE-derived results to predict the spread of COVID-19 and the emergence of new variants of concern. Further, we observed a strong correlation between the presence of SARS-CoV-2 and changes in the microbial community of wastewater, particularly the significant changes in bacterial genera belonging to the families of Lachnospiraceae and Actinomycetaceae. Our study shows that microbial biomarkers could be utilized as prediction tools for future infectious disease surveillance and outbreak responses. Overall, our comprehensive analyses of viral spread, variants, and novel bacterial biomarkers will add significantly to the growing body of literature on WBE and COVID-19.