Evidence map›Paper›PMID 41438606›Full record

ArticleInfectious Disease Modelling2026

Stochastic dynamics of Chikungunya virus infection model incorporating general incidence rate and immune responses.

Jingze Ma, Yan Wang

Abstract read
In one paragraph

Article in Infectious Disease Modelling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Jingze MaCollege of Science, China University of Petroleum (East China), Qingdao, Shandong, 266580, China.
Yan WangCollege of Science, China University of Petroleum (East China), Qingdao, Shandong, 266580, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates a stochastic model of Chikungunya virus (CHIKV) infection that incorporates a general incidence rate along with B-cell and CTL immune responses. Stochasticity is modeled through a log-normal Ornstein-Uhlenbeck process. We first establish the existence of a unique and globally positive solution. Then, the solution's dynamic behavior around the two steady states is examined, and it is shown that the stochastic model's dynamics at the steady state generalizes the global asymptotic stability of the deterministic model. We prove the existence of the stationary distribution by constructing suitable Lyapunov functions when the stochastic reproduction number is greater than one. The probability density function near the quasi-steady state is subsequently derived. Sufficient conditions for CHIKV extinction are provided by spectral radius analysis. Furthermore, we conduct uncertainty and sensitivity analyses to investigate the effects of key parameters on each population and the value of the stochastic reproduction number. Finally, numerical simulations are carried out to explore the impact of noise intensity and the average incidence rate on the dynamic behavior of the model.

Indexed as

CHIKV infectionOrnstein-Uhlenbeck processProbability density functionStationary distributionStochastic differential equations

Identifiers

PMID41438606
PMCPMC12721054

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.