Related Experiment Video
Updated: Sep 8, 2025
14:27
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
15.8K
Unveiling Health Security Patterns in the European Union through a Hybrid Entropy-CoCoSo and K-Means Clustering
Adel A Nasser1,2, Yahya Ali Al-Samawi3, Abed Saif Ahmed Alghawli4
1Department of Information Systems and Computer Science, Sa'adah University, Sa'adah University, Sa'adah, Yemen.
F1000Research
|August 20, 2025
Summary
European Union health security varies significantly, with detection, reporting, and rapid response being key. Targeted investments are crucial to harmonize preparedness and address disparities across member states.
Area of Science:
- Global Health Security
- Public Health Policy
- International Relations
Background:
- Significant intra-regional disparities in health security (HeS) exist within the European Union (EU).
- Harmonizing preparedness measures across EU member states is essential for effective public health policy.
- Addressing national sovereignty while aligning with EU-wide HeS objectives presents a complex challenge.
Purpose of the Study:
- To examine health security (HeS) patterns across European Union (EU) member states.
- To address intra-regional disparities in health security.
- To propose evidence-based recommendations for harmonizing preparedness measures.
Main Methods:
- A hybrid multi-criteria decision-making framework (Entropy Weight Method and Combined Compromise Solution - CoCoSo) was utilized.
- Six Global Health Security Index (GHSI) indicators were employed to assess and rank EU countries.
- K-means clustering categorized countries into High, Intermediate, and Dangerous performance tiers, with temporal analysis of GHSI data (2019, 2021, 2017-2021).
Main Results:
- Detection and Reporting, and Rapid Response were the most critical HeS dimensions; Risk Environment and Compliance with Norms showed minimal differentiation.
- High-performing countries (e.g., Finland, Germany) excelled in surveillance and rapid response, while lower-tier nations (e.g., Cyprus, Luxembourg, Malta, Romania) showed vulnerabilities in biosecurity and emergency planning.
- Post-2019, health system resilience became more prominent, while compliance and risk environment were neglected, highlighting post-pandemic shifts in disparities.
Conclusions:
- Targeted investments in surveillance, laboratory infrastructure, and crisis preparedness are necessary to address specific HeS gaps.
- A metrics-driven framework can reduce regional disparities and promote equitable preparedness across the EU.
- Collaborative approaches and benchmarking against high-performing states are recommended for policymakers to mitigate health crises.
Related Concept Videos
01:25Statistical Methods for Analyzing Epidemiological Data
525
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
525
01:20Cluster Sampling Method
12.7K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.7K
01:26Principles of Disease Surveillance
179
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
179
01:20Integrated Healthcare System
1.8K
An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
1.8K
01:17Classification of Illness
7.9K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
7.9K
01:30Health Information Technology and Healthcare Information System
912
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
912