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Record W4404136262 · doi:10.15407/microbiolj86.05.102

Virological Monitoring of Wastewater as an Element of Surveillance for Emergent and Re-Emergent Infections

2024· article· en· W4404136262 on OpenAlexaboutno aff
В. І. Задорожна, Mariia Liulchuk, Alla Podavalenko, Нина Григорьевна Малыш, O.V. Surmasheva, Олена Ракша-Слюсарева, O.V. Murashko

Bibliographic record

VenueMikrobiolohichnyi Zhurnal · 2024
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsnot available
Fundersnot available
KeywordsWastewaterEnvironmental healthMedicineIntensive care medicineVirologyEnvironmental scienceMicrobiologyBiologyEnvironmental engineering

Abstract

fetched live from OpenAlex

The risk of biological threats has been constantly increasing in recent years. This is due both to the adaptation of avian and animal pathogens to the human organism as a result of the expansion of the area of human activity and to the development of biotechnologies. Viruses predominate among these pathogens. Examples in recent years are the COVID-19 pandemic and the continued spread of monkeypox (MPX). The situation requires the search for objects for research that would have a high informative value and could help in assessing and predicting the spread of infections. The article analyzed and assessed the potential and importance of virological monitoring of wastewater as an element of surveillance for emergent and re-emergent infections, using the example of some of them (enterovirus infections – poliomyelitis and infection caused by enterovirus D68, COVID-19, and MPX). Monitoring of enteroviruses in wastewater is a routine practice in many countries. Poliomyelitis is subject to eradication, and its incidence is extremely low. The study of wastewater makes it possible to indirectly detect the circulation of poliovirus among people, determine its molecular genetic characteristics (“wild”, vaccine, vaccine-derived poliovirus), the duration of circulation, and ways of spread and take appropriate measures in a timely manner. Enterovirus type D68 gained relevance as a re-emergent infection starting in 2014. Large outbreaks caused by it began to be registered in the USA, Canada, and then in the European region. Previously, the virus caused minor respiratory symptoms, but now it has become the cause of severe acute respiratory disease, particularly in children, and has also acquired neurovirulent properties. Its monitoring in wastewater allows for assessing the actual intensity of the epidemic process of this infection in certain territories and in certain countries, which cannot always be done based on clinical diagnosis without an additional etiological diagnosis. During the 3 years of the pandemic, SARS-CoV-2 has taken root in the human population, but a new parasitic system continues to develop. Wastewater monitoring makes it possible to assess the intensity of the epidemic process of COVID-19, which is supported by manifest forms of infection, asymptomatic persistence of the virus, and convalescents. It also allows for analyzing the effectiveness of quarantine and other restrictive measures, detecting genetic changes in the virus and trends in the formation of new variants of the virus. Since May 2022, MРХ has gone beyond the borders of endemic countries and began to spread rapidly, acquiring the character of a re-emergent infection. A variant of the pathogen (clade 3) began to evolve and became transmissible from person to person. The disease it causes began to radically differ from the previously known MRC due to changes in pathogenesis and epidemiological features. First of all, this concerns the pronounced anthroponotic characteristics of re-emergent MРХ in comparison with the zoonotic manifestations of the previously known endemic MРХ. The article discusses the results of studies conducted in different countries on the determination of MPX virus (MPXV) nucleic acids in wastewater samples using OPG002 gene analysis of all MPXVs (G2R_G), the West African clade (G2R_WA), and virus reference genomes of MPXV of the outbreak in 2022 (G2R_NML). Thus, virological monitoring of wastewater can be used as an effective element of surveillance for most infectious diseases, in particular, emergent and re-emergent ones.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.346
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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