Evidence map›Paper›PMID 41006342›Full record

ArticleScientific reports2025

Mathematical modeling and analysis of COVID-19 and typhoid fever co-dynamics with treatment.

Daniel S Mgonja, Alfred Hugo, Asha Hassan, Oluwole Daniel Makinde

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Daniel S MgonjaDepartment of Management Studies, Tanzania Institute of Accountancy, Box 9522, Dar es Salaam, Tanzania. mgonja_d@yahoo.com.
Alfred HugoDepartment of Mathematics and Statistics, University of Dodoma, P.O Box 259, Dodoma, Tanzania.
Asha HassanDepartment of Mathematics and Statistics, University of Dodoma, P.O Box 259, Dodoma, Tanzania.
Oluwole Daniel MakindeStellenbosch University, Faculty of Military Science, Private Bagx2, Saldanba, 7395, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A deterministic mathematical model for COVID-19 and typhoid fever co-infection was developed and analyzed to assess the effects of treatment on the transmission and control of COVID-19 and typhoid fever in the community. The model incorporates both human and pathogen populations and is subjected to analytical scrutiny, including investigations into the existence, boundedness, and positivity of the solution. The study employs the Next-Generation Matrix Method to calculate the effective reproduction number [Formula: see text], and the global stability of the disease-free equilibrium point is examined using the Lyapunov function method. Sensitivity analyses were conducted by computing Partial Rank Correlation Coefficients (PRCC) to determine the impact of each parameter on the spread or control of the diseases. The necessary conditions for the existence of optimal control and the optimality system for the model are established using Pontryagin's maximum principle. These include three control measures which are: improved COVID-19 treatment, improved typhoid fever treatment, and improved co-infection treatment. Numerical simulations of the model show that, treatment control can effectively reduce the spread of the diseases. Furthermore, increasing the treatment and screening rates can minimize the transmission of COVID-19 and typhoid fever in a population.

Indexed as

CoinfectionCOVID-19Models, TheoreticalTyphoid FeverBasic Reproduction NumberHumansSARS-CoV-2AnalysisCo-dynamicsCOVID-19ModelingTreatment controlTyphoid fever

Identifiers

PMID41006342
PMCPMC12475156

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.