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Record W4401798793 · doi:10.1016/s2666-5247(24)00126-5

Early warning COVID-19 outbreak in long-term care facilities using wastewater surveillance: correlation, prediction, and interaction with clinical and serological statuses

2024· article· en· W4401798793 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Lancet Microbe · 2024
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsCanadian Bio-Systems (Canada)Alberta Health ServicesProvincial Laboratory of Public HealthUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsOutbreakCoronavirus disease 2019 (COVID-19)SerologyWarning systemTerm (time)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Environmental healthMedicineVirologyComputer scienceImmunologyInternal medicineAntibodyInfectious disease (medical specialty)Telecommunications

Abstract

fetched live from OpenAlex

BACKGROUND: The unprecedented COVID-19 pandemic has highlighted the strategic value of wastewater-based surveillance (WBS) of SARS-CoV-2. This multisite 28-month-long study focused on WBS for older residents in 12 long-term care facilities (LTCFs) in Edmonton (AB, Canada) by assessing relationships between COVID-19, WBS, and serostatus during the pandemic. METHODS: Wastewater samples collected two to three times per week were tested for SARS-CoV-2 using RT-quantitative PCR. The serostatus of antibodies was examined using immunoassays. The data of clinical COVID-19 outbreaks based on extensive testing were obtained from local public health officials. Analyses included calculating correlations between 7-day rolling averages for WBS and COVID-19 cases and investigating whether WBS led or lagged confirmed outbreaks using a multinomial test. FINDINGS: Wastewater results correlated well with clinical COVID-19 infections and outbreaks at participating LTCFs. 1058 (36·0%) of 2936 collected wastewater samples were SARS-CoV-2 positive, compared with 1247 people (resident n=671, staff n=572, and unknown n=4) reporting positive test results of 21 673 clinical samples assessed (5·8%). WBS led clinical testing in 32 (60·4%) confirmed outbreaks, which was significantly different from WBS lagged (12 outbreaks [22·6%, 95% CI 11·3-33·7]). Non-detection of WBS SARS-CoV-2 served as a negative predictor for outbreaks. WBS results attested protective immunity in vaccinated individuals before the omicron wave. A parallel increase in the proportions of positive WBS SARS-CoV-2 and anti-nucleocapsid antibodies underlined that omicron was an immunity-evading variant despite high seropositivity of neutralising antibodies after multiple doses of vaccine. INTERPRETATION: Implementation of WBS could enable targeted clinical investigations and improve cost-effectiveness of COVID-19 outbreak management in LTCFs. WBS and serostatus provided informed dynamic changes of infections and immunity. Critical evidence was that LTCF WBS is an effective early warning system to support rapid public health outbreak management and protect vulnerable older populations. FUNDING: Canadian Immunity Task Force for COVID-19 and Alberta Health.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.005
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.075
GPT teacher head0.359
Teacher spread0.284 · 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