Healthcare analytics (New York, N.Y.)最新文献

An electrocardiogram signal classification using a hybrid machine learning and deep learning approach 利用机器学习和深度学习混合方法进行心电图信号分类

Healthcare analytics (New York, N.Y.) Pub Date : 2024-10-09 DOI: 10.1016/j.health.2024.100366

{"title":"An electrocardiogram signal classification using a hybrid machine learning and deep learning approach","authors":"","doi":"10.1016/j.health.2024.100366","DOIUrl":"10.1016/j.health.2024.100366","url":null,"abstract":"<div><div>An electrocardiogram (ECG) is a diagnostic tool that captures the electrical activity of the heart. Any irregularity in the heart's electrical system is referred to as an arrhythmia, which can be identified through the analysis of ECG signals. Timely diagnosis of cardiac arrhythmias is crucial in order to mitigate their potentially harmful consequences. However, manual analysis of ECG signals is time-consuming and prone to inaccuracies. Therefore, researchers have developed medical decision support systems that utilize machine learning techniques to automate the analysis of ECG signals. In this study, we propose a novel method for classifying ECG signals into four distinct types of heartbeats: normal, supraventricular, ventricular, and fusion. Our method consists of two subsystems that integrate both machine learning and deep learning approaches. The first subsystem uses a residual network block to extract features from the input ECG signal, followed by an LSTM network for learning and classification of these features. The second subsystem uses several feature extraction methods and a random forest to classify the ECG signals. Furthermore, it employs a Synthetic Minority Over-Sampling Technique to improve dataset balance and overall performance. The ultimate result is achieved by merging the results of both subsystems together. An assessment of our approach was carried out on the MIT-BIH dataset, which acts as a recognized ECG signal classification benchmark. Our technique attained an impressive accuracy rate of 99.26%, ranking it as one of the most superior methods in the current literature. Our findings demonstrate the effectiveness and efficiency of our approach in accurately classifying ECG signals for arrhythmia detection.</div></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An inter-hospital performance assessment model for evaluating hospitals performing hip arthroplasty 用于评估髋关节置换术医院的医院间绩效评估模型

Healthcare analytics (New York, N.Y.) Pub Date : 2024-09-24 DOI: 10.1016/j.health.2024.100365

{"title":"An inter-hospital performance assessment model for evaluating hospitals performing hip arthroplasty","authors":"","doi":"10.1016/j.health.2024.100365","DOIUrl":"10.1016/j.health.2024.100365","url":null,"abstract":"<div><div>The value of hospital care to patients is expressed as a combination of reduced healthcare costs, fewer medical complications, and improved patient satisfaction. Few studies highlight the value hospitals provide to their patients through hip replacement surgery.</div><div>This study aims to define a methodology for inter-hospital comparison purposes that can assess the value of hip replacement management to patients by using indicators of costs, medical complications, and patient outcomes.</div><div>We identified medical complications and costs from medico-administrative data collected by three hospitals. We associated a Disability Adjusted Life Years (DALYs) impact with medical complications, readmissions (within 30 days), and hospital mortality. Costs were analysed from a social security perspective. Patient outcomes were collected through a questionnaire-based survey after hip surgery. To compare the three hospitals, we created a composite indicator by standardizing each dependent variable and combining a weighting of importance provided by patients.</div><div>This study analysed 342 hospital stays. The mean (standard deviation) number of DALYs per stay was estimated to be more than 0.0028 (0.016) for a mean (standard deviation) cost of €4,834 (€3,665). The composite indicator allowed hospitals to be ranked and areas for improvement to be identified. In our case mix, Hospital 3 is the lowest-ranked hospital, with excessively high costs and a relatively low level of satisfaction compared to the others.</div><div>The simultaneous evaluation of medical complications, patient outcomes, and costs is a prerequisite for quality improvement efforts by managers and practitioners. In our opinion, this experiment, which sought to estimate the value hospitals bring to patients, may be viewed as the first step towards value-based purchasing in Belgium.</div></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A data envelopment analysis model for optimizing transfer time of ischemic stroke patients under endovascular thrombectomy 优化血管内血栓切除术下缺血性脑卒中患者转院时间的数据包络分析模型

Healthcare analytics (New York, N.Y.) Pub Date : 2024-09-19 DOI: 10.1016/j.health.2024.100364

{"title":"A data envelopment analysis model for optimizing transfer time of ischemic stroke patients under endovascular thrombectomy","authors":"","doi":"10.1016/j.health.2024.100364","DOIUrl":"10.1016/j.health.2024.100364","url":null,"abstract":"<div><div>This study applies Data Envelopment Analysis (DEA) to optimize transfer times and futile transfers of eligible ischemic stroke patients receiving Endovascular Thrombosis (EVT) in Primary Stroke Centers (PSC) in Nova Scotia. The study aims to assess healthcare delivery in Nova Scotia over two periods. It seeks to improve stroke care for rural populations by examining nine inputs, including age and distance between PSCs and the Comprehensive Stroke Centre (CSC) that provided EVT treatment, concerning a single output variable: whether EVT is performed or not. In the first phase, 115 patients were treated as Decision-Making Units (DMUs) for ten PSCs by applying an input-oriented Variable Returns to Scale (VRS) assisted by super-efficiency analysis using the Python-based PyDEA tool. This tool is known for its unrestricted capacity to handle DMUs, inputs, and outputs. In the second phase, eight PSCs with low patient numbers were merged into four DMUs, each consisting of two PSCs. These two merged PSCs have limited patients, and the selected PSCs are also geographically close. Two PSCs have been kept separate because they had sufficient patient volume. In the first phase, VRS generated more reasonable efficiency scores for evaluation, while in the second phase, Constant Returns to Scale (CRS) outperformed VRS, yielding better results. In the initial stage of the second phase, ten PSCs were considered as six DMUs using the input-oriented CRS and VRS for 115 patients. Super-efficiency measures were applied in this stage to improve the evaluation process further. In the second part of the second phase, a comparison between the first period (2018–2019) and the second period (2020–2021) was conducted using the Malmquist Productivity Index (MPI), considering CRS and VRS to evaluate the relative efficiency and productivity change of six DMUs over time.</div></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An investigation of Susceptible–Exposed–Infectious–Recovered (SEIR) tuberculosis model dynamics with pseudo-recovery and psychological effect 带假康复和心理效应的易感-暴露-感染-康复（SEIR）结核病模型动力学研究

Healthcare analytics (New York, N.Y.) Pub Date : 2024-09-17 DOI: 10.1016/j.health.2024.100361

{"title":"An investigation of Susceptible–Exposed–Infectious–Recovered (SEIR) tuberculosis model dynamics with pseudo-recovery and psychological effect","authors":"","doi":"10.1016/j.health.2024.100361","DOIUrl":"10.1016/j.health.2024.100361","url":null,"abstract":"<div><div>Tuberculosis is one of the most pressing issues of the modern era, posing a severe health risk to humans in recent decades. This study proposes a Susceptible–Exposed–Infectious–Recovered (SEIR) tuberculosis epidemic transmission model with psychological effects and pseudo-recovery. We consider a compartmental mathematical model in which the entire population is divided into four compartments based on their natural features. The model is validated, and parameter values are estimated using Indonesian data from 2002 to 2022. To investigate their epidemiological significance, we proved the positivity and boundedness of solutions, as well as the local and global stability of equilibria. Sensitivity analysis is used to find the most influential parameters with the most significant influence on the basic reproduction number, <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>. The bifurcation procedure tools of the center manifold theory are used to conduct a bifurcation study. Mathematical conditions ensure the inferred event of forward bifurcation. We performed numerical simulations that support our theoretical findings.</div></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel integrated logistic regression model enhanced with recursive feature elimination and explainable artificial intelligence for dementia prediction 利用递归特征消除和可解释人工智能增强痴呆症预测的新型综合逻辑回归模型

Healthcare analytics (New York, N.Y.) Pub Date : 2024-09-14 DOI: 10.1016/j.health.2024.100362

{"title":"A novel integrated logistic regression model enhanced with recursive feature elimination and explainable artificial intelligence for dementia prediction","authors":"","doi":"10.1016/j.health.2024.100362","DOIUrl":"10.1016/j.health.2024.100362","url":null,"abstract":"<div><p>Dementia is a major global health issue that significantly impacts millions of individuals, families, and societies worldwide, creating a substantial burden on healthcare systems. This study introduces a novel approach for predicting dementia by employing the Logistic Regression (LR) model, enhanced with Recursive Feature Elimination (RFE), applied to a unique dataset comprising 1000 patients, with 49.60% male and 50.40% female. The LR model, recognized for its simplicity and effectiveness in binary classification tasks, is optimized through RFE, a technique that iteratively eliminates less significant features to improve model performance. The model’s effectiveness was assessed using comprehensive metrics, including accuracy, precision, recall, F1-score, Matthews Correlation Coefficient (MCC), and Kappa score. Furthermore, SHapley Additive exPlanations (SHAP) values were employed to increase the interpretability of the model, providing insights into the most influential features for dementia prediction. To address the issue of overfitting, a standardization technique was implemented, which enhanced the model’s predictive performance. The findings of this study hold potential implications for early dementia detection, informing intervention strategies, and optimizing healthcare resource allocation.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442524000649/pdfft?md5=1b759d8a985cabb4b185f0a36f88797f&pid=1-s2.0-S2772442524000649-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Markov cohort model for Endoscopic surveillance and management of Barrett’s esophagus 内镜监测和管理巴雷特食管的马尔科夫队列模型

Healthcare analytics (New York, N.Y.) Pub Date : 2024-08-29 DOI: 10.1016/j.health.2024.100360

{"title":"A Markov cohort model for Endoscopic surveillance and management of Barrett’s esophagus","authors":"","doi":"10.1016/j.health.2024.100360","DOIUrl":"10.1016/j.health.2024.100360","url":null,"abstract":"<div><p>Barrett's esophagus is an asymptomatic precursor to esophageal adenocarcinoma. Its rising incidence due to lifestyle factors, coupled with healthcare costs, requires cost-effective alternatives for surveillance. We propose a decision-analytic Markov cohort model to simulate Barrett's esophagus's natural progression to esophageal adenocarcinoma using TreeAge Pro. Health states include metaplasia (non-dysplastic Barrett's esophagus), low-grade dysplasia, high-grade dysplasia, and esophageal adenocarcinoma. Triplicates of these health states represent one non-stratified and two risk-stratified cohorts for devising risk-based strategies. A cycle length of six months and a time horizon of 35 years, totaling 70 cycles, is considered. Model inputs are derived from literature and, when unavailable from an extensive local database of 1087 patients (5081 person-years) from March 2003–2021, cleaned and analyzed with Rstudio (R version 3.6.3). Specific tests included descriptive statistics, Cox-proportional hazard models, and graphing. A seven-step calibration process is performed for risk-stratified and non-stratified groups simultaneously to match the progression to high-grade dysplasia and esophageal adenocarcinoma. This allows comparison between risk- and non-risk-based strategies. The calibration process included input parameterization, optimization, goodness of fit calculation, selection of sets meeting convergence criteria, and integration into probabilistic sensitivity analysis. This process generated 10,187 sets of transition probabilities, with 4358 meeting convergence criteria, ensuring equal model outputs in all groups. Mortality was 10.7% for cancer-related deaths, matching literature values. This process provides a robust framework for evaluating Barrett's esophagus progression and management strategies, supporting informed decision-making in healthcare.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442524000625/pdfft?md5=39571667386e7018b829933792fd6ca7&pid=1-s2.0-S2772442524000625-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the impact on quality of prediction and inference from balancing in multilevel logistic regression 评估多级逻辑回归中的平衡对预测和推断质量的影响

Healthcare analytics (New York, N.Y.) Pub Date : 2024-08-22 DOI: 10.1016/j.health.2024.100359

{"title":"Assessing the impact on quality of prediction and inference from balancing in multilevel logistic regression","authors":"","doi":"10.1016/j.health.2024.100359","DOIUrl":"10.1016/j.health.2024.100359","url":null,"abstract":"<div><p>The primary goal of this research is to examine the impact of balancing data on the prediction quality and inference in multilevel logistic regression models. Logistic regression is a valuable approach for modeling binary outcomes expected in health applications. The class imbalance problem, where one of the two outcome categories occurs much more often than the other, is common in healthcare data, such as when modeling the risk factors for rare diseases. The issue is particularly relevant for medical data that contains individual measurements and other data sources measured at a geographic region level, such as environmental risk factors. For this work, both prediction and model interpretation are of interest. A simulation model is proposed to test the impact of balancing strategies on the logistic multilevel model's parameter estimation, inference, and predictive performance. The simulated information emulates characteristics of a Gestational Diabetes Mellitus (GDM) dataset from Indiana's Medicaid program. Several datasets were simulated with varying levels of complexity, involving the balance of the outcome variable and predictors. These datasets exhibited high- or low-frequency occurrences in specific intersections of variables, often called ‘cells.’ The impact of the balancing strategies on prediction and inference was assessed using different techniques, such as the Equivalence (TOST) Test, power analysis, and predictive measures. To the best of our knowledge, this is the first research that explores the impact of using balanced samples on coefficient estimation and prediction measures when using logistic multilevel modeling, finding evidence about the benefits of using balanced samples in this context.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442524000613/pdfft?md5=61d70749e6aeada54ee254cabcd3c429&pid=1-s2.0-S2772442524000613-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A comparative analysis of machine learning algorithms with tree-structured parzen estimator for liver disease prediction 机器学习算法与树状结构帕尔森估计器在肝病预测方面的比较分析

Healthcare analytics (New York, N.Y.) Pub Date : 2024-08-16 DOI: 10.1016/j.health.2024.100358

{"title":"A comparative analysis of machine learning algorithms with tree-structured parzen estimator for liver disease prediction","authors":"","doi":"10.1016/j.health.2024.100358","DOIUrl":"10.1016/j.health.2024.100358","url":null,"abstract":"<div><p>The liver is one of the most essential organs in the body, which helps with metabolism and keeping the body healthy. Successful treatments and better patient outcomes depend on early and correct Liver Disease (LD) diagnosis and identification. This study proposes a system for predicting the LD by combining the techniques of Machine Learning (ML) algorithms that include the Decision Tree, Random Forest, Extra Tree Classifier (ETC), LightGBM, and Adaboost, with the Tree-Structured Parzen Estimator (TPE) method for hyperparameter tuning. No previous literature research has utilized ML algorithms with TPE to predict LD. For this research, the Indian Liver Patients’ Dataset with 583 instances and 11 attributes was used. In the pre-processing of the data, techniques such as upsampling have been utilized to address the class imbalance problem. Normalization has been employed to scale the dataset, and feature selection has been applied to choose important features. The proposed model has been analyzed and compared using a 10-fold cross-validation process, with various evaluation metrics including accuracy, precision, recall, and F1-score. The model proposed in this study achieved the best level of accuracy while employing the ETC with the TPE approach, with a recorded accuracy of 95.8%.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442524000601/pdfft?md5=3aa72f3755c5377eba838fab77bd6aa3&pid=1-s2.0-S2772442524000601-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142006485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Malmquist fuzzy data envelopment analysis model for performance evaluation of rural healthcare systems 用于农村医疗系统绩效评估的马尔奎斯特模糊数据包络分析模型

Healthcare analytics (New York, N.Y.) Pub Date : 2024-08-08 DOI: 10.1016/j.health.2024.100357

{"title":"A Malmquist fuzzy data envelopment analysis model for performance evaluation of rural healthcare systems","authors":"","doi":"10.1016/j.health.2024.100357","DOIUrl":"10.1016/j.health.2024.100357","url":null,"abstract":"<div><p>The primary purpose of this article is to measure the relative efficiency and productivity change over time in rural healthcare systems in the presence of fuzzy data. First, a novel ranking function based on the lower and upper bounds of alpha-cut of the trapezoidal fuzzy numbers (TrFNs) is proposed to compare the TrFNs. The suggested ranking technique is used to construct the fuzzy data envelopment analysis (FDEA), Malmquist fuzzy DEA (Mal-FDEA), and undesirable Malmquist fuzzy DEA (UN-Mal-FDEA ) models. The proposed models evaluate the efficiency and productivity of decision-making units (DMUs) when the input and output data are given in the form of TrFNs. In addition, a case study of the rural healthcare system in a developing country has been considered to demonstrate the applicability of the developed models. The work considers number of sub-centers (SCs), the number of primary health centers (PHCs), the number of community health centers (CHCs), nursing Staff at PHCs, an auxiliary nurse and midwives (ANM) at SCs, doctors at PHCs, pharmacists at PHCs, laboratory technicians at PHCs, radiographers at CHCs, and specialists at CHCs as input parameters and average population covered by CHCs, average village covered by CHCs, number of patients, and infant mortality rates as output parameters to analyze the performance of the rural healthcare systems. We show the UN-Mal-FDEA model has a higher production value than the Mal-FDEA model. The results of our proposed models enable us to recognize inefficiencies that states may rectify without compromising healthcare quality.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442524000595/pdfft?md5=c60ff4997d73b3069e87498e704b3717&pid=1-s2.0-S2772442524000595-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An optimal control model for monkeypox transmission dynamics with vaccination and immunity loss following recovery 猴痘传播动态的优化控制模型，包括疫苗接种和恢复后的免疫力丧失

Healthcare analytics (New York, N.Y.) Pub Date : 2024-07-10 DOI: 10.1016/j.health.2024.100355

{"title":"An optimal control model for monkeypox transmission dynamics with vaccination and immunity loss following recovery","authors":"","doi":"10.1016/j.health.2024.100355","DOIUrl":"10.1016/j.health.2024.100355","url":null,"abstract":"<div><p>The viral illness known as monkeypox causes symptoms such a rash that can appear on the hands, feet, chest, face, and lips or near the genitalia. This study presents a mathematical model for the kinetics of monkeypox transmission with vaccination and immunity loss following recovery. The theories of positivity and boundedness are used to analyze the model’s well-posedness. The next generation matrix is used to determine the model’s basic reproduction number. The model’s equilibrium points are discovered. We demonstrate that the disease-free equilibrium was locally asymptotically stable. The center manifold theory is used to establish the bifurcation analysis. The impact of the parameters related to the fundamental reproduction number <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> is investigated using the normalized forward sensitivity index. In addition, the model is expanded to incorporate time-dependent management of preventing interaction with contaminated rodents, avoiding contact with contaminated people, wearing personal protective equipment, and reducing rodent populations by utilizing an integrated pest management strategy. The model’s qualitative analysis is supported by numerical simulation.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442524000571/pdfft?md5=c42d8831c6521c0f5e1b1f9045af04e9&pid=1-s2.0-S2772442524000571-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141630149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0