ReviewEnvironmental monitoring and assessment2021
Coronavirus: occurrence, surveillance, and persistence in wastewater.
Review in Environmental monitoring and assessment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- How long do pathogens persist and survive in water? A systematic review.Frontiers in microbiology · 2025Pooled it
- Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review.Systematic reviews · 2024Pooled it
- Assessment of the clinical and analytical performance of three Seegene Allplex SARS-CoV-2 assays within the VALCOR framework.Microbiology spectrum · 2024Article
- Article
- Application of wastewater-based surveillance and copula time-series model for COVID-19 forecasts.The Science of the total environment · 2023Article
- SARS-CoV-2 Transmission by Arthropod Vectors: A Scoping Review.BioMed research international · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The coronavirus disease (COVID-19) outbreak reported in China in December 2019 has spread throughout the world. The WHO declared it as a pandemic in March 2020. The pandemic severely affected public health and the global economy. Many studies conducted on the coronavirus have helped us to elucidate its pathogenicity and pathophysiology. However, it is important to study the behavior of the pathogen in the environment to develop effective control measures. While studying the persistence and transmission of viruses in drinking water and wastewater systems, a low concentration of coronavirus and its nucleic acids have been detected in municipal wastewaters. This could be due to their high susceptibilities to degradation in aqueous environments. Epidemiological study on coronaviruses in wastewater will serve two purposes, i.e., in early detection of outbreak and in identifying asymptomatic carriers. In such cases, the epidemiological study will help in early detection of the presence of the virus in the community. Secondly, it will help in knowing if there are asymptomatic carriers, as such people do not show any signs of symptoms but shed the viruses in feces. The present review focuses on the epidemiological surveillance of wastewater for coronaviruses, as in recent years these are increasingly causing global pandemics. In this review we have discussed, the four pertinent areas of coronavirus study: (1) occurrence of coronavirus in wastewater, (2) wastewater based epidemiological surveillance of coronaviruses, (3) epidemiological surveillance tools used for detection of coronaviruses in sewage, and (4) persistence and sustainability of coronaviruses in wastewater.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.