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Record W4388928821 · doi:10.3389/fpubh.2023.1252428

Barriers and enablers to the implementation of one health strategies in developing countries: a systematic review

2023· review· en· W4388928821 on OpenAlexaff
Danièle Sandra Yopa, Douglas Mbang Massom, Gbètogo Maxime Kiki, Ramde Wendkoaghenda Sophie, Fasine Sylvie, Oumou Thiam, Lassane Zinaba, Patrice Ngangue

Bibliographic record

VenueFrontiers in Public Health · 2023
Typereview
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversité LavalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsCINAHLPsychological interventionSystematic reviewDeveloping countryGlobal healthMEDLINEBusinessCorporate governancePublic relationsMedicinePolitical sciencePublic healthNursingEconomic growthFinanceEconomics

Abstract

fetched live from OpenAlex

Introduction: One Health is a concept that establishes the link between humans, animals and the environment in a collaborative approach. Since One Health's inception, several interventions have been developed in many regions and countries worldwide to tackle complex health problems, including epidemics and pandemics. In the developed world, many collaborative platforms have been created with an international strategy to address issues specific or not to their environment. Unfortunately, there is a lack of synthesis on the challenges and opportunities Low and Middle-Income Countries (LMICs) face. Methods: Following The Preferred Reporting Elements for PRISMA Systematic Reviews and Meta-Analyses (PRISMA), we conducted a systematic review. We applied a search strategy to electronic bibliographic databases (PubMed, Embase, Global Health, Web of Science and CINAHL). We assessed the included articles' quality using the Mixed Methods Appraisal tool (MMAT). Results and discussion: A total of 424 articles were initially identified through the electronic database search. After removing duplicates (n = 68), 356 articles were screened for title and abstract, and 16 were retained for full-text screening. The identified barriers were the lack of political will, weak governance and lack of human, financial and logistics resources. Concerning the enablers, we listed the existence of a reference framework document for One Health activities, good coordination between the different sectors at the various levels, the importance of joint and multisectoral meetings that advocated the One Health approach and the Availability of funds and adequate resources coupled with the support of Technical and Financial partners. Conclusion: One Health strategy and interventions must be implemented widely to address the rising burden of emerging infectious diseases, zoonotic diseases, and antimicrobial resistance. Addressing those challenges and reinforcing the enablers to promote managing global health challenges is necessary. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/record_email.php, Unique Identifier: CRD42023393693.

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)0.061
metaresearch head score (Gemma)0.182
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.061
Threshold uncertainty score0.321

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.182
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0110.012
Bibliometrics0.0160.019
Science and technology studies0.0010.002
Scholarly communication0.0070.007
Open science0.0030.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.097
GPT teacher head0.422
Teacher spread0.324 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations78
Published2023
Admission routes1
Has abstractyes

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