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Transmission of Salmonella in Humans and Animals and its Epidemiological Factors

2023· article· en· W4362661265 on OpenAlexaff
Oladapo Oyedeji Oludairo, Jacob K. P. Kwaga, Junaidu Kabir, Paul Ayuba Abdu, Gitanjali Arya, Ann Perrets, Veronica Cibin, Antonia Lettini, Julius Olaniyi Aiyedun, Oluwafemi Babatunde Daodu, Isaac Olorunshola, Uduak Akpabio

Bibliographic record

VenueZagazig Veterinary Journal/Zagazig Veterinary Journal (Online) · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsSalmonellaEpidemiologyTransmission (telecommunications)Environmental healthBiologyVirologyMedicineComputer scienceTelecommunicationsPathologyBacteriaGenetics

Abstract

fetched live from OpenAlex

Over 2,500 Salmonella serovars cause typhoidal and non-typhoidal salmonellosis, which has economic and public health importance worldwide. The routes, modes, and vectors of Salmonella transmission in humans and animals, including the factors that affect them are important in the understanding of the epidemiology, prevention, and control of the disease. This study aims to identify the routes, modes, and vectors of transmission of Salmonella, including the factors that enhance the spread, maintenance, and persistence of the organism in humans and animals. This was achieved by using a Google search engine to obtain peer-reviewed articles on the keywords of this study. The major route of transmission of Salmonella in humans is faecal-oral, while the transovarial route has also been reported in poultry. Ingestion of contaminated food or water, contaminated materials from pets/wildlife, infected persons, and transmission to the young through the placenta are described as modes of transmission of Salmonella in humans. Salmonella Typhimurium (S.Typhimurium), Salmonella Enteritidis (S. Enteritidis) and Salmonella Senftenberg (S. Senftenberg) attach efficiently to vectors like fruits and vegetables with the aid of AgfD-regulated-adhesin, biofilms, and flagella. The organism can also invade plant tissues before transmission to humans and animals. Phytophagous hemipteran and cynanthropia/coprophagic insects serve as vectors of transmission by forcibly excreting ingested Salmonella and through their intermittent habitat and diet changes, respectively. Lice serve as vectors by ingesting viable strains of the organism, after they reach a maximum titre of 0.5–5.0 ×107 within 6–8 hours; Salmonella is thereafter shed and transmitted through their faeces. Factors that affect the transmission of Salmonella include pathogen, host and environment-related factors like increased antimicrobial resistance, intermittent shedding of the organism and rainfall, respectively. The knowledge of the routes, modes, vectors, and factors that affect the transmission of Salmonella will contribute to the body of knowledge on the epidemiology, prevention, and control of salmonellosis.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.131
GPT teacher head0.327
Teacher spread0.195 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

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