Evidence map›Paper›PMID 39627269›Full record

ArticleScientific reports2024

Mathematical modeling of cholera dynamics in the presence of antimicrobial utilization strategy.

Josiah Mushanyu, Lunga Matsebula, Farai Nyabadza

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Josiah MushanyuDepartment of Computing, Mathematical & Statistical Science, University of Namibia, Windhoek, 13301, Namibia. mushanyuj@gmail.com.
Lunga MatsebulaDepartment of Mechanical & Metallurgical Engineering, University of Namibia, Ongwediva, 13301, Namibia.
Farai NyabadzaDepartment of Mathematics and Applied Mathematics, University of Johannesburg, Johannesburg, 2006, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance poses a significant threat to public health, particularly in cholera treatment. The emergence of antibiotic resistance, coupled with the sharp decline in pharmaceutical companies developing new cholera antibiotics, is a cause for concern. We formulate a multidrug-resistant (MDR) cholera epidemic model that incorporates a stage-switching strategy between two antibiotics to reduce the magnitude of resistance. The model is analyzed mathematically, and sensitivity analysis of the reproduction number is performed using sub-reproduction numbers. Stability analysis of the cholera-sensitive-only and cholera-resistant-only equilibria is investigated using Centre Manifold Theory. The model is calibrated through Markov Chain Monte Carlo simulations in Stan, showing stability at equilibrium points, which is further verified through numerical simulations. The simulations demonstrate an inverse relationship between the number of MDR cholera cases and the number of individuals receiving second-line treatment for cholera. This study suggests that the correct use of antibiotics can effectively manage the emergence of antimicrobial resistance. From a public health policy perspective, these findings emphasize the importance of antibiotic stewardship programs and the need for policies that promote the responsible use of existing antibiotics while encouraging the development of new treatment options. Such measures could help mitigate the global burden of MDR cholera and prevent further escalation of resistance.

Indexed as

Anti-Bacterial AgentsCholeraComputer SimulationDrug Resistance, Multiple, BacterialHumansMarkov ChainsModels, TheoreticalMonte Carlo MethodVibrio choleraeAnti-Bacterial Agents

Identifiers

PMID39627269
PMCPMC11615286

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.