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Record W4224134511 · doi:10.21203/rs.3.rs-927478/v1

A rapid assessment of the impact of COVID-19 on the utilization of hospital services in Ondo State of South Western Nigeria

2022· preprint· en· W4224134511 on OpenAlexaff
Mahmud Zubairu, Fatiregun Akin, Onoja Attah, Gboyega Famokun, Mustafa Mahmud, Kebba Touray, Itse Olaoye

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldMedicine
TopicCOVID-19 diagnosis using AI
Canadian institutionsFields Institute for Research in Mathematical Sciences
Fundersnot available
KeywordsMedicineCoronavirus disease 2019 (COVID-19)Proxy (statistics)Incidence (geometry)Environmental healthTransmission (telecommunications)Hospital admissionPediatricsMedical emergencyDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Abstract Background: There is no doubt that COVID_19 has impacted on all facets of human activities everywhere, including ONDO state, Nigeria. However, empirical evidence of the extent of this impact in ONDO is lacking. The objective of this study was to evaluate the impact of COVID_19 epidemic on the utilization of hospital services & determine the existence of community transmission of COVID_19 in ONDO state using a proxy “Respiratory Tract Infections, RTIs”.Methods: The study used resident clinicians to conduct peer review of hospital utilization records. The review was retrospectively for the months of January to May for four consecutive years (2018 to 2021). The team reviewed outpatient records from 11 health facilities before the advent of COVID_19 (2018) to date (2021). Thousands of such records were scrutinized to reveal six parameters: number of antenatal visits; number of live births and total number of infants served BCG; number RDTs conducted for Malaria, number of RTIs seen and total number of patients for all other illnesses. Results: Results showed a decline in all parameters investigated except RTIs. Indeed, the proportion of RTIs - related hospital visits increased by about 22.8%.Discussion: The decline in the utilization of hospital services is expected given the lock down measures implemented to halt transmission of COVID_19 that makes it difficult to access health facilities. The rise in the incidence of RTIs may probably be that, they were COVID cases that were undetected due to limited COVID_19 testing capacity.Conclusion: The study concludes that COVID_19 epidemic impacted negatively on all aspect of hospital services except RTIs. The increment is statistically significant. As the most prominent of all symptoms of COVID_19 presents as respiratory tract disorder, a continued rise in RTIs despite declining rates of confirmed COVID19 cases in the state at the moment suggests that, there’s an ongoing community transmission.

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)0.003
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 score0.024
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.120
GPT teacher head0.486
Teacher spread0.366 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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