A deterministic analysis of an age-sex-structured model for malaria transmission dynamics
Bibliographic record
Abstract
• 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".