A Systematic Literature Review of Mathematical Models for Coinfections: Tuberculosis, Malaria, and HIV/AIDS.

J Multidiscip Healthc

Mathematics Discipline, Science, Engineering and Technology School, Khulna University, Khulna 9208, Bangladesh.

Published: March 2024

AI Article Synopsis

  • Tuberculosis, malaria, and HIV are severe diseases that, when occurring together, can significantly increase health risks and mortality.
  • Mathematical models have been developed to analyze the complexities of these coinfections, as discussed in a systematic review of relevant research articles from credible sources.
  • The review highlights important findings on model development and analysis, while also providing recommendations for future research in the field of infectious disease coinfections.

Article Abstract

Tuberculosis, malaria, and HIV are among the most lethal diseases, with AIDS (Acquired Immune Deficiency Syndrome) being a chronic and potentially life-threatening condition caused by the human immunodeficiency virus (HIV). Individually, each of these infections presents a significant health challenge. However, when tuberculosis, malaria, and HIV co-occur, the symptoms can worsen, leading to an increased mortality risk. Mathematical models have been created to study coinfections involving tuberculosis, malaria, and HIV. This systematic literature review explores the importance of coinfection models by examining articles from reputable databases such as Dimensions, ScienceDirect, Scopus, and PubMed. The primary emphasis is on investigating coinfection models related to tuberculosis, malaria, and HIV. The findings demonstrate that each article thoroughly covers various aspects, including model development, mathematical analysis, sensitivity analysis, optimal control strategies, and research discoveries. Based on our comprehensive evaluation, we offer valuable recommendations for future research efforts in this field.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10951863PMC
http://dx.doi.org/10.2147/JMDH.S446508DOI Listing

Publication Analysis

Top Keywords

tuberculosis malaria
20
malaria hiv
16
systematic literature
8
literature review
8
mathematical models
8
coinfection models
8
tuberculosis
5
malaria
5
hiv
5
review mathematical
4

Similar Publications

Background/objectives: Pharmacogenetics (PGx) aims to identify individuals more likely to suffer from adverse reactions or therapeutic failure in drug treatments. However, despite most of the evidence in this area being from European populations, some diseases have also been neglected, such as HIV infection, malaria, and tuberculosis. With this review, we aim to emphasize which pharmacogenetic tests are ready to be implemented in treating neglected diseases that have some evidence and call attention to what is missing for these three diseases.

View Article and Find Full Text PDF

Background: There are few data on the treatment of children and adolescents with multidrug-resistant (MDR) or rifampicin-resistant (RR) tuberculosis, especially with more recently available drugs and regimens. We aimed to describe the clinical and treatment characteristics and their associations with treatment outcomes in this susceptible population.

Methods: We conducted a systematic review and individual participant data meta-analysis.

View Article and Find Full Text PDF

Objective: For more than a century, developing novel and effective vaccines against malaria and Tuberculosis (TB) infections has been a challenge. This review sought to investigate the reasons for the slow progress of malaria and TB vaccine candidates in sub-Saharan African clinical trials.

Methods: The systematic review protocol was registered on PROSPERO on July 26, 2023 (CRD42023445166).

View Article and Find Full Text PDF

Mapping Drug-Resistant Tuberculosis Treatment Outcomes in Hunan Province, China.

Trop Med Infect Dis

December 2024

School of Population Health, Faculty of Health Sciences, Curtin University, Perth, WA 6102, Australia.

Background: Drug-resistant tuberculosis (DR-TB) remains a major public health challenge in China, with varying treatment outcomes across different regions. Understanding the spatial distribution of DR-TB treatment outcomes is crucial for targeted interventions to improve treatment success in high-burden areas such as Hunan Province. This study aimed to map the spatial distribution of DR-TB treatment outcomes at a local level and identify sociodemographic and environmental factors associated with poor treatment outcomes in Hunan Province, China.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!