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Peer reviewedOpen accessTuberculosis

Mathematical Analysis and Optimal Control of a Tuberculosis Model with Early Diagnosed Latent Infections

International Journal of Analysis and Applications·

Abdelfatah Abasher, Yasser Salah S. Abougamea, Elsiddeg Ali, Ibrahim Bashir

DOI
10.28924/2291-8639-24-2026-260
PMID
PMCID
OpenAlex
Study type
Journal article
Publisher
SCIK Publishing Corporation
Article type
journal-article
Integrity
current

Why this research matters now

The quantitative comparisons assist decision-makers in balancing budgetary limits against the desired magnitude of case reduction during tuberculosis management.

01

Structured evidence summary

Research question

The investigation examines how integrating early detection of latent tuberculosis into a transmission framework influences disease progression and determines the most efficient control measures.

Study design

Researchers constructed a deterministic SEIR compartmental model and applied optimal control theory to simulate various intervention scenarios.

Population and setting

The analysis operates within a theoretical computational environment without referencing a specific clinical cohort or geographic region.

Main findings

Implementing all four evaluated interventions simultaneously lowers overall financial expenditures, while isolating transmission reduction produces the largest decrease in active cases.

Public-health relevance

The quantitative comparisons assist decision-makers in balancing budgetary limits against the desired magnitude of case reduction during tuberculosis management.

Important limitations

The outcomes depend exclusively on modeled parameters and hypothetical scenarios, omitting empirical verification from actual patient or community datasets.

GIDS interpretation

This article situates itself within scholarly discussions on infectious disease mathematics and outlines analytical techniques for assessing combined preventive measures.

02

Related GIDS surveillance

Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.

03

Evidence relationships

This article has 8 auditable classifier relationships to diseases, places, topics, and study design.

about diseaseaddresses topicaddresses topicaddresses topicevaluates interventionevaluates interventionstudied population settinguses study design