Evaluation and clustering of health security performance in Africa: A comparative analysis through the entropy-TOPSIS-K-means approach

ABSTRACT

This study presents an analysis and comparison of the health security practices (HSP) of 47 African countries based on 2019 and 2021 data. Its objective is to assess, rank, and cluster the countries based on their HSP performance and progress over this period. A comprehensive Entropy-TOPSIS-K-means-based evaluation system was constructed for this purpose. Initially, the entropy method was utilised to analyze and compare investment priorities. Subsequently, the Entropy-TOPSIS was used to evaluate and compare the level of health security (HS) performance and the degree of improvements made by countries over the study period. Finally, the K-means cluster analysis method was applied to classify countries based on their comprehensive evaluation scores. Among the six identified criteria, prevention, detection, reporting, and health system practices were deemed crucial for HS decision-making in both cases. The study revealed significant differences in HSP levels and changes in countries’ improvement levels between their practices in 2019 and 2021. The study classifies the security levels of African countries into five clusters and provides a detailed analysis, implications, and recommendations to aid decision-makers in enhancing HS outcomes. Its results offer empirical evidence to support planning, resource allocation, and reallocation for strengthening HSP in the region.

KEYWORDS:

• African countries
• health security
• clustering analysis
• entropy
• TOPSIS; K-means

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

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17 Chakraborty et al., ‘A Comprehensive and Systematic Review of Multi-Criteria Decision-Making Methods and Applications in Healthcare’;

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22 Zhang et al., ‘Analysis on the Differences of Health Resources Allocation in Undeveloped Areas of Chongqing, China’.

23 See also, Miškić, et al., ‘Assessment of the LPI of the EU Countries Using MCDM Model with an Emphasis on the Importance of Criteria’.

24 Paramanik, Sarkar, and Sarkar, ‘OSWMI: An Objective-Subjective Weighted Method for Minimizing Inconsistency in Multi-Criteria Decision Making’.

25 Nasser et al., ‘Assessing Equity in Healthcare Facility Resource Allocation in Yemen: An Entropy-TOPSIS Analysis’.

26 Bera et al., ‘Susceptibility of Deforestation Hotspots in Terai-Dooars Belt of Himalayan Foothills.’

27 Ikotun et al., ‘K-Means Clustering Algorithms’.

28 See also, Nasser et al., ‘Assessing Equity in Healthcare Facility Resource Allocation in Yemen: An Entropy-TOPSIS Analysis’.

29 See also, Nasser et al., ‘Assessing Equity in Healthcare Facility Resource Allocation in Yemen: An Entropy-TOPSIS Analysis’.

30 See also, Ikotun et al., ‘K-Means Clustering Algorithms’.

31 See also Global Health Security Index. ‘Global Health Security Index 2021’.

32 Bell and Nuzzo, Global Health Security Index.

33 See also Bell and Nuzzo, Global Health Security Index.

34 See also Omosigho et al., ‘Multiple Burden of Infectious Disease Outbreaks: Implications for Africa Healthcare System’.

35 See also Nasser et al., ‘Assessing Equity in Healthcare Facility Resource Allocation in Yemen: An Entropy-TOPSIS Analysis’.

36 See also Zhang et al., ‘Analysis on the Differences of Health Resources Allocation in Undeveloped Areas of Chongqing, China’.

37 See also Rusakaniko et al. ‘Strengthening National Health Research Systems in the WHO African Region – Progress towards Universal Health Coverage’.

38 See also Bell and Nuzzo, Global Health Security Index.

39 See also Zhang et al., ‘Analysis on the Differences of Health Resources Allocation in Undeveloped Areas of Chongqing, China’.

Additional information

Funding

This study is supported via funding from Deanship of Scientific Research, Prince Sattam bin Abdulaziz University [project number: PSAU/2024/R/1445].

Notes on contributors

Adel A. Nasser

Mr. Adel A. Nasser completed his Bachelor of Science degree in Information Technology and Computer Engineering at South-West State University in 2007. In 2009, he successfully completed his Master of Science degree in Devices and Systems of Wireless Communication Networks and later obtained a Ph.D. in Technical Sciences in 2012. Currently, he holds the position of Associate Professor and Vice President of Modern Specialized University, Sana’a, Yemen. Furthermore, he serves as the Head of the Information Systems and Computer Sciences Department at Sa’ada University in Yemen. His publication record is remarkable, having published over 50 research papers in well-regarded international journals and conferences. His primary research interests revolve around information security, information security management, decision support systems, MCDM methods and algorithms, fuzzy-based MCDM tools, and their applications in the health, education, and business sectors.

Abed Saif Ahmed Alghawli

Mr. Abed Saif Alghawli was born in Yemen in 1975. He received the BSc in Computer Engineering, the M.Sc. degree in Computer Intellect Systems and Network and the Ph.D. degree in Computerized Control Automated Systems and Progressive Information Technology from Kharkiv National University of Radio Electronics, Ukraine in 1999, 2000 and 2005, respectively. He has held lecturing positions at the University of Science and Technology, Yemen, and the King Saud University, KSA for several years. He is currently an associate professor in the Department of computer science at Prince Sattam Bin Abdulaziz University, KSA. From 2013 to 2017, he has been the Vice dean for academic affairs at College of Sciences and Humanities, Prince Sattam Bin Abdulaziz University, KSA. He is a member of the Executive Committee for the accreditation of the Business Administration Program and Computer Science Program at Prince Sattam Bin Abdulaziz University from the American ACBSP Foundation and from NCAAA, respectively. His main areas of research interest are machine learning and computer networks.