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Author(s): Abdourahmane Ndao, Cheikh Tidiane Seck.

Volume/Issue: Volume 6 , Issue 3 (2023)

Abstract:

The aim of this work is to construct a typology of health districts in Senegal based on the distribution frequency of ten infectious diseases under surveillance. Our methodology utilizes HCPC (Hierarchical Classification on Principal Components) algorithm which combines two data analysis techniques, namely Principal Component Analysis (PCA) and Hierarchical Ascending Classification (HAC). The data come from the Prevention Department of the Ministry of Health and Social Action and cover the period from January 2018 to November 2022. The results show that health districts in Senegal can be divided into three clusters according to the number of confirmed cases recorded for each of the ten considered infectious diseases. Moreover, the parangons’ principle allows us to select from the obtained clusters a representative stratified sample of health districts in view to identifying risk factors associated with these ten pathologies.

Keywords:

Typology; Health districts; Number of confirmed cases; Infectious diseases; Health surveillance data.

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