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Record W4381432080 · doi:10.1136/bmjopen-2022-068016

Expansion of testing, isolation, quarantine, e-health and telemonitoring strategies in socioeconomically vulnerable neighbourhoods at primary healthcare in the fight against COVID-19 in Brazil: a study protocol of a multisite testing intervention using a mixed method approach

2023· article· en· W4381432080 on OpenAlexfundno aff
Laio Magno, Thaís Régis Aranha Rossi, Débora Castanheira, Thiago S. Torres, Carina Carvalho dos Santos, Fabiane Soares, Valdiléa G. Veloso, Marcos Benedetti, Inês Dourado

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducation during COVID-19 pandemic
Canadian institutionsnot available
FundersUnitaidMinistério da SaúdeCanada Excellence Research Chairs, Government of CanadaWorld Health Organization
KeywordsMedicineCoronavirus disease 2019 (COVID-19)QuarantineIsolation (microbiology)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakProtocol (science)PandemicHealth careEnvironmental healthVirologyDiseaseBioinformaticsAlternative medicinePathologyInfectious disease (medical specialty)OutbreakEconomic growth

Abstract

fetched live from OpenAlex

INTRODUCTION: The key tools for mitigating the impact of COVID-19 and reducing its transmission include testing, quarantine and isolation, as well as telemonitoring. Primary healthcare (PHC) can be essential in increasing access to these tools. Therefore, the primary objective of this study is to implement and expand an intervention consisting of COVID-19 testing, isolation, quarantine and telemonitoring (TQT) strategies and other prevention measures at PHC services in highly socioeconomically vulnerable neighbourhoods of Brazil. METHODS AND ANALYSIS: This study will implement and expand COVID-19 testing in PHC services in two large Brazilian capital cities: Salvador and Rio de Janeiro. Qualitative formative research was conducted to understand the testing context in the communities and at PCH services. The TQT strategy was structured in three subcomponents: (1) training and technical support for tailoring the work processes of health professional teams, (2) recruitment and demand creation strategies and (3) TQT. To evaluate this intervention, we will conduct an epidemiological study with two stages: (1) a cross-sectional sociobehavioural survey among individuals from these two communities covered by PHC services, presenting symptoms associated with COVID-19 or being a close contact of a patient with COVID-19, and (2) a cohort of those who tested positive, collecting clinical data. ETHICS AND DISSEMINATION: The WHO Ethics Research Committee (ERC) (#CERC.0128A and #CERC.0128B) and each city's local ERC approved the study protocol (Salvador, ISC/UFBA: #53844121.4.1001.5030; and Rio de Janeiro, INI/Fiocruz: #53844121.4.3001.5240, ENSP/Fiocruz: #53844121.4.3001.5240 and SMS/RJ #53844121.4.3002.5279). Findings will be published in scientific journals and presented at meetings. In addition, informative flyers and online campaigns will be developed to communicate study findings to participants, members of communities and key stakeholders.

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)0.020
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.020
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.012
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0020.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0030.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.265
GPT teacher head0.549
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

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 designNot applicable
Domainnot available
GenreProtocol

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

Citations5
Published2023
Admission routes1
Has abstractyes

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