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Record W4320806913 · doi:10.2196/42678

COVID-19 Contact Tracing Strategies During the First Wave of the Pandemic: Systematic Review of Published Studies

2023· review· en· W4320806913 on OpenAlex
Anna Maria Vincenza Amicosante, Annalisa Rosso, Fabio Bernardini, Elisa Guglielmi, Erica Eugeni, Filippo Da Re, Giovanni Baglìo

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Public Health and Surveillance · 2023
Typereview
Languageen
FieldComputer Science
TopicCOVID-19 Digital Contact Tracing
Canadian institutionsnot available
FundersRegione del VenetoMinistero della Salute
KeywordsContact tracingPandemicCoronavirus disease 2019 (COVID-19)Public healthPsychological interventionMedicineComputer scienceMedical emergencyData sciencePathologyNursingInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: Contact tracing (CT) represented one of the core activities for the prevention and control of COVID-19 in the early phase of the pandemic. Several guidance documents were developed by international public health agencies and national authorities on the organization of COVID-19 CT activities. While most research on CT focused on the use digital tools or relied on modelling techniques to estimate the efficacy of interventions, poor evidence is available on the real-world implementation of CT strategies and on the organizational models adopted during the initial phase of the emergency to set up CT activities. OBJECTIVE: We aimed to provide a comprehensive picture of the organizational aspects of CT activities during the first wave of the pandemic through the systematic identification and description of CT strategies used in different settings during the period from March to June 2020. METHODS: A systematic review of published studies describing organizational models of COVID-19 CT strategies developed in real-world settings was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. PubMed, Embase, and Cochrane Library were searched. Studies not providing a description of the organizational aspects of CT strategies and studies reporting or modelling theoretical strategies or focusing on the description of digital technologies' properties were excluded. Quality of reporting was assessed by using the Template for Intervention Description and Replication Checklist for Population Health and Policy. We developed a narrative synthesis, using a conceptual framework to map the extracted studies broken down by target population. RESULTS: We retrieved a total of 1638 studies, of which 17 were included in the narrative synthesis; 7 studies targeted the general population and 10 studies described CT activities carried out in specific population subgroups. Our review identified some common elements across studies used to develop CT activities, including decentralization of CT activities, involvement of trained nonpublic health resources (eg, university students or civil servants), use of informatics tools for CT management, interagency collaboration, and community engagement. CT strategies implemented in the workplace envisaged a strong collaboration with occupational health services. Outreach activities were shown to increase CT efficiency in susceptible groups, such as people experiencing homelessness. Data on the effectiveness of CT strategies are scarce, with only few studies reporting on key performance indicators. CONCLUSIONS: Despite the lack of systematically collected data on CT effectiveness, our findings can provide some indication for the future planning and development of CT strategies for infectious disease control, mainly in terms of coordination mechanisms and the use of human and technical resources needed for the rapid development of CT activities. Further research on the organizational models of CT strategies during the COVID-19 pandemic would be required to contribute to a more robust evidence-making process.

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)0.008
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.187
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.144
GPT teacher head0.398
Teacher spread0.254 · 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