Dynamic analysis and optimal control of a hybrid fractional monkeypox disease model in terms of external factors
Bibliographic record
Abstract
The monkeypox virus (MPXV), which is a member of the Orthopoxvirus genus in the class Poxviridae, is the causative agent of the zoonotic viral infection MPXV. The disease is similar to smallpox, but it is usually less dangerous. This study examines the evolution of the MPXV epidemic in Canada with an emphasis on the effects of control employing actual data. The main challenge is accurately estimating the virus's rate of transmission and assessing the effectiveness of vaccination campaigns. By taking into account the modified Atangana-Baleanu-Caputo (mABC) fractional difference operator, we develop an analytical framework for an outbreak caused by MPXV and broaden it to accommodate the fractional scenario. The non-negativity and boundedness are guaranteed by the computation of the fractional-order MPXV system. At the disease-free equilibrium (DFE) [Formula: see text], we perform a local asymptotical stability analysis (LAS) and display the outcome for [Formula: see text]. When [Formula: see text] and [Formula: see text], the single endemic equilibrium point (EEP) of infectious rodents is globally asymptotically stable (GAS). Lyapunov's approach and LaSalle's invariant criterion demonstrate that the GAS in terms of EEP for infectious persons occurs when [Formula: see text] and [Formula: see text]. Through the application of nonlinear least squares, we determine the parameter values applying actual cases collected from Canada. To further bolster the operator's effectiveness, a number of tests of this novel kind of operator were conducted. We remark that in various time scale domains [Formula: see text], the investigated discrete formulations will be [Formula: see text]-nonincreasing or [Formula: see text]-nondecreasing by examining ρ-monotonicity formulations and the basic properties of the suggested operator. Algorithms are constructed in the discrete generalized Mittag-Leffler (GML) kernel for mathematical simulations, emphasizing the effects of the infection resulting from multiple factors. The dynamical technique used to build the MPXV framework was significantly impacted by fractional-order. In order to lessen the infections, severity, five time-dependent control factors are also implemented. The optimality criteria are produced by applying Pontryagin's maximal argument to prove the validity of the most effective control. Various combos of control factors are offered to reduce the incidence of MPXV. The results of the current research provide governmental officials and healthcare professionals with practical steps to take in order to establish efficient and ideal preventive approaches to reduce the MPXV outbreaks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".