Community structure plays a significant role in the analysis of social networks and similar graphs, yet this structure is little understood and not well captured by most models. We formally define a community to be a subgraph that is internally highly connected and has no deeper substructure. We use tools of combinatorics to show that any such community must contain a dense Erdős-Rényi (ER) subgraph. Based on mathematical arguments, we hypothesize that any graph with a heavy-tailed degree distribution and community structure must contain a scale-free collection of dense ER subgraphs. These theoretical observations corroborate well with empirical evidence. From this, we propose the Block Two-Level Erdős-Rényi (BTER) model, and demonstrate that it accurately captures the observable properties of many real-world social networks.
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http://dx.doi.org/10.1103/PhysRevE.85.056109 | DOI Listing |
J Infect Dev Ctries
December 2024
Faculty of Medicine, Eastern Mediterranean University, Famagusta, N. Cyprus via Mersin 10, Turkey.
Introduction: The global healthcare system faced unparalleled challenges during the coronavirus disease 2019 (COVID-19) pandemic, potentially reshaping antibiotic usage trends. This study aimed to evaluate the knowledge, perceptions, and observations of community pharmacists concerning antibiotic utilization during and after the pandemic; and offer crucial insights into its impact on antibiotic usage patterns and infection dynamics.
Methodology: This cross-sectional study involved 162 community pharmacists in Northern Cyprus.
J Infect Dev Ctries
December 2024
Faculdade de Medicina de Campos, Campos dos Goytacazes, Brazil.
Introduction: Despite efforts by health organizations to share evidence-based information, fake news hindered the promotion of social distancing and vaccination during the coronavirus disease 2019 (COVID-19) pandemic. This study analyzed COVID-19 knowledge and practices in a vulnerable area in northern Rio de Janeiro, acknowledging the influence of the complex social and economic landscape on public health perceptions.
Methodology: This cross-sectional study was conducted in Novo Eldorado - a low-income, conflict-affected neighborhood in Campos dos Goytacazes - using a structured questionnaire, following the peak of COVID-19 deaths in Brazil (July-December 2021).
J Infect Dev Ctries
December 2024
The Cancer Hospital Affiliated to Shandong First Medical University (Shandong Cancer Prevention Research Institute, Shandong Cancer Hospital), Jinan 250117, China.
Introduction: In this study, we analyzed the psychological aspects of coronavirus disease 2019 (COVID-19) patients who were discharged from the hospitals in Shanghai, China, and later had positive nucleic acid retest results for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant infection (re-positive COVID-19). The purpose was to gain clarity on the patients' needs and to provide evidence for the medical staff to deliver scientific and targeted health care to the patients.
Methodology: We screened patients who tested positive for SARS-CoV-2 Omicron variant infection by nucleic acid testing after having previously recovered from a COVID-19 infection and being discharged from Shanghai shelter hospitals or COVID-19-designated hospitals from April 3, 2022, to May 10, 2022.
BMC Health Serv Res
January 2025
Department of Health Policy and Management, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Family physician program is one of the effective reforms of the health system in Iran, but despite the implementation of this program in rural areas and the passage of ten years since its implementation in two provinces of Fars and Mazandaran, its implementation has faced problems. The aim of this study is to identify and prioritize implementation solutions related to the challenges of the family physician program in Iran.
Methods: This is a qualitative study using semi-structured interviews with 22 snowball-sampled experts and managers of basic health insurers to extract problems and executive solutions through coding and data analysis using Atlas Ti software and content analysis in the first stage.
BMC Nurs
January 2025
Nursing Department, Hamad Medical Corporation, Doha, P.O. Box 3050, Qatar.
Background: Artificial Intelligence (AI) is increasingly applied in healthcare to boost productivity, reduce administrative workloads, and improve patient outcomes. In nursing, AI offers both opportunities and challenges. This study explores nurses' perspectives on implementing AI in nursing practice within the context of Jordan, focusing on the perceived benefits and concerns related to its integration.
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