@article { author = {Adams, Samuel and Yahaya, Haruna and Mohammed, Tanimu}, title = {Cluster Analysis of HIV/AIDs Incidence in Sub-Saharan Africa (1990 – 2018)}, journal = {International Journal of Epidemiology and Health Sciences}, volume = {4}, number = {Continuous}, pages = {-}, year = {2023}, publisher = {}, issn = {2667-0941}, eissn = {2667-0941}, doi = {10.51757/IJEHS.4.2023.701311}, abstract = {Background: The HIV/AIDS epidemic has had a negative impact on Sub-Saharan Africa's development and has contributed to discrimination against those on the margins of society or those who are at risk of contracting the virus due to their behaviors, race, ethnicity, gender, sexual orientation, or social characteristics. Against this backdrop, the purpose of this study is to examine the countries that could be considered in the same category and to investigate the concentration of diseases in relation to the socioeconomic status of Sub-Saharan African countries.Methods: HIV prevalence rates in Sub-Saharan African countries were studied using Cluster Analysis techniques. It was implemented using hierarchical (Agglomerative nesting) and partitioning methods (K-Means) in general. For cluster validation (a mechanism for evaluating the correctness of clustering), the relative type of validation was used.Results: HIV/AIDS prevalence increased steadily from 1990 (6.74) to 1995 (9.13), after which it began to fall to (2.60) in 2018. The analysis produced three clusters based on the 44 observations provided. After clustering, only Lesotho and Eswatini are in the third cluster. Over the course of the study, South Africa, Zambia, Zimbabwe, Namibia, Malawi, Mozambique, and Botswana had the highest HIV/AIDS prevalence. The rest of the world is classified as part of the first cluster.Conclusion: The high prevalence of HIV/AIDS in Sub-Saharan African countries has had a far-reaching impact. Understanding the variables that have influenced the path of the HIV/AIDS scourge is therefore critical, both from a humanitarian and economic standpoint, because it is a significant step toward eradicating the virus.}, keywords = {cluster analysis,HIV/AIDS,Sub-Saharan Africa,K-means,Agglomerative Nesting}, url = {https://www.ijehs.com/article_701311.html}, eprint = {https://www.ijehs.com/article_701311_46bdf6b99dfc2561ca7f8f49b10d43c4.pdf} }