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Record W4403683114 · doi:10.1016/j.ijregi.2024.100478

A deterministic analysis of an age-sex-structured model for malaria transmission dynamics

2024· article· en· W4403683114 on OpenAlexfundno aff
Marie Aimée Uwineza, Joseph Nzabanita, Innocent Ngaruye, Mohamed Sylla

Bibliographic record

VenueIJID Regions · 2024
Typearticle
Languageen
FieldMedicine
TopicMathematical and Theoretical Epidemiology and Ecology Models
Canadian institutionsnot available
FundersDivision of Mathematical SciencesGlobal Affairs CanadaAfrican Institute for Mathematical SciencesInternational Development Research CentreGovernment of Canada
KeywordsMalariaDynamics (music)Transmission (telecommunications)Computer sciencePsychologyMedicineTelecommunicationsImmunology

Abstract

fetched live from OpenAlex

• Malaria is a life threatening mosquito-borne disease and it constitutes a global health concern • Development of Mathematical model for malaria disease taking into account age-gender stratification of the population • Malaria model analysis • Malaria transmission control strategies Objectives: Children younger than 5 years and women, especially pregnant women, are at high risk of malaria and death because of their weak immunity and exposure to mosquitoes. Several studies have considered only the age-structured model and other factors but have not considered sex. The objective of this work is to develop and analyze the malaria transmission model including this structure, to contribute to existing measures and mechanisms to eradicate malaria in Rwanda. Methods: A dynamic malaria transmission model considering age and sex structure was developed and analyzed. To study the dynamics of disease, the basic reproduction number was analytically computed and numerically estimated, and the normalized forward sensitivity index was used to highlight its sensitive parameters. Results: The most positive sensitive parameters in the model are the force of infection and the infection rates for vectors and female humans aged 5 years or older. The most negative sensitive parameters are the per capita death rates for vectors and humans. Conclusion: To control the spread of malaria in Rwanda, the biting and infection rates should be decreased. Therefore, women must comply with government measures against malaria and educate children about it.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.336
Teacher spread0.297 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2024
Admission routes1
Has abstractyes

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