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COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. Considering the restricted and enclosed nature of prisons and closed environments and the prolonged and close contact between individuals, COVID-19 is more likely to have a higher incidence in these settings. This study aims to assess the prevalence of COVID-19 among prisoners.

Papers published in English from 2019 to July 7, 2023, were identified using relevant keywords such as prevalence, COVID-19 and prisoner in the following databases: PubMed/MEDLINE, Scopus and Google Scholar. For the meta-analysis of the prevalence, Cochrane’s Q statistics were calculated. A random effect model was used due to the heterogeneity in COVID-19 prevalence across included studies in the meta-analysis. All analyses were performed in STATA-13.

The pooled data presented a COVID-19 prevalence of 20% [95%CI: 0.13, 0.26] and 24% [95%CI: 0.07, 0.41], respectively, in studies that used PCR and antibody tests. Furthermore, two study designs, cross-sectional and cohort, were used. The results of the meta-analysis showed studies with cross-sectional and cohort designs reported 20% [95%CI: 0.11, 0.29] and 25% [95%CI: 0.13, 0.38], respectively.

Through more meticulous planning, it is feasible to reduce the number of individuals in prison cells, thereby preventing the further spread of COVID-19.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

The purpose of this paper is to systematically review how agency and stakeholder theories are integrated within corporate governance and environmental disclosure practices in the UAE, highlighting their relevance and adaptation to a distinct economic and regulatory environment.

Using a comprehensive qualitative methodology, this study synthesises a broad spectrum of existing theoretical and empirical research to explore the dynamics of corporate governance mechanisms regarding environmental sustainability. This approach enables a detailed examination of how agency theory’s focus on principal–agent relationships complements stakeholder theory’s broader view of corporate responsibilities.

This research uncovers significant insights into corporate conduct and responsibility, emphasising the need to balance shareholder objectives with broader stakeholder interests. It identifies key challenges in this integration, such as managing the complexities and potential conflicts between different stakeholder demands. The findings underscore the crucial role of specialised governance mechanisms, like board characteristics and committees, in enhancing environmental transparency and accountability.

This study contributes to the academic discourse by shedding light on the interplay between corporate governance frameworks and environmental disclosure practices within the UAE. It offers fresh insights into applying established theories in a non-Western context. These insights are precious for academics, practitioners and policymakers interested in refining corporate governance and promoting environmental responsibility. The practical implications drawn from the findings empower stakeholders to implement effective strategies that can enhance a firm’s reputation, legitimacy and long-term viability.

The advancement of medical care during the late 19th century and the rising importance of public health led to the creation of a healthcare infrastructure in Iran in the early decades of the 20th century. The study focuses on the formation of this infrastructure through the study of historical materials as well as the study of case studies built in the Gilan region in the north of Iran.

This paper begins with a review of medical, sociological and historical resources, then turns to field studies and interviews as methods to focus on the medical transformations in the Gilan region.

This study offers four key findings: First of all, most studies tend to focus more on traditional medicine in Iran than on the initiation and spread of modern medicine. Secondly, foreign physicians and missionaries played an influential role in shaping the culture of Iranian hospital care. Thirdly, the interactions with and influences coming from Iran’s northern neighbors in Gilan transformed the province into an educated, freedom-seeking society. And finally, in its early stages, hospital construction in Iran followed local architectural traditions.

In the case of Gilan, the core structures of urban hospitals were similar in their pavilion typology to those that had been common in Gilan for centuries.

The primary goal of this research is to introduce a data-driven Problem-Solving Approach for Performance Improvement in Healthcare Systems (DPAPIH). This approach combines process mining and data mining techniques to enhance operational efficiency by identifying bottlenecks in Coronary Artery Bypass Grafting (CABG) procedures, particularly focusing on variability in Length of Stay (LOS) in the Intensive Care Unit (ICU). The study, implemented at Tehran Heart Center, aims to optimize patient flow, reduce ICU congestion and improve hospital efficiency by predicting and managing the occurrence of postoperative Atrial Fibrillation (AF), a significant cause of prolonged ICU stays.

The study introduces a data-driven problem-solving approach that integrates process mining and data mining techniques to improve performance in healthcare systems. Focusing on coronary artery bypass grafting (CABG) at Tehran Heart Center, the approach identifies bottlenecks, particularly variability in ICU length of stay (LOS) and predicts postoperative atrial fibrillation (AF). A mixed-methods approach is employed, combining quantitative process mining analyses with qualitative insights from expert consultations. The CHAID decision tree algorithm, alongside other models, is used to predict AF, enabling preemptive interventions, improving patient flow and optimizing resource allocation to reduce hospital congestion and costs.

The study reveals that postoperative Atrial Fibrillation (AF) significantly increases the length of stay (LOS) in the Intensive Care Unit (ICU), creating bottlenecks that delay subsequent surgeries and elevate hospital costs. A predictive model developed using CHAID decision tree algorithms achieved a prediction accuracy of 71.4%, allowing healthcare providers to anticipate AF occurrences. This capability enables proactive measures to reduce ICU congestion, improve patient flow and optimize resource allocation. The findings emphasize the importance of AF management in enhancing operational efficiency and improving patient outcomes in Coronary Artery Bypass Grafting (CABG) procedures.

This study presents an innovative integration of fuzzy process mining and data mining algorithms to address performance bottlenecks in healthcare systems, specifically within the coronary artery bypass surgery process. By identifying atrial fibrillation as a key factor in length of stay fluctuations and developing a robust predictive model, the research offers a novel, data-driven approach to performance improvement. The implementation at Tehran Heart Center validates the model’s practical applicability, demonstrating significant potential for enhancing patient outcomes, optimizing resource allocation and informing decision-making in healthcare management.

This study attempts to analyze the overall effectiveness of Lean System (LS)-based India post facility layout design (FLD) selection.

We have grouped all Lean Six Sigma elements into three different categories: Lean Technical Practices, Lean Workplace Environment Practices, and Lean Ergonomics Practices based on literature support and field surveys in the Indian postal service. Further, it employs a mathematical model known as the graph theory (GT) method. From the GT approach, interactions were identified through LS tools represented through the digraph, matrix model approach. This study was directed at the National Sorting Hub in Mysuru, Karnataka, in the southern part of India. A number of insights were given in the GT area where FLD is possible to evaluate.

The results showed that Layout five has the highest value, followed by Layout one from the GT approach. The relative relevance and effect values are given as inputs to the permanent function in the digraph technique, and an evaluation index is obtained as an output.

When solving any optimization issue with a high number of attributes, the digraph and matrix technique is successful. The layouts that have been identified have yielded valuable insights into how to enhance critical decision-making processes, which are necessary to accomplish company strategic objectives like growing postal business services.

The process operations carried out in India post service as well as its heterogeneity of articles and the intangible measures of production are the significant challenges to keenly analyze the layout design through lean service principles.