This article uses the theoretical framework of the capabilities approach to offer a structural assessment model of well-being in the context of Senegal. To this end, we mobilize the Senegalese data (ESPS-II) and an evaluation space including basic and central capabilities of [1] and [2], which are: living conditions, education and health body, non-institutional support and good governance, on the one hand, and the three dimensions of well-being (economic well-being, life satisfaction and subjective well-being), on the other hand. With the modeling technique by structural equations: PLS-PM (Partial Linear Square-Path Modeling), we find that the estimation model of well-being has built good predictive quality. In addition, it shows that the basic capabilities (education, living conditions and health of the body) positively determine well-being (economic well-being, subjective well-being and life satisfaction). Also, economic well-being and life satisfaction positively predict and cause subjective well-being. Contrariwise, non-institutional support and good governance do not significantly cause subjective well-being. Between these two capabilities, only good governance has a significant and positive effect on life satisfaction.

The objective of this paper is to design a multidimensional poverty index, based on the Alkire-Foster (AF) method, to identify people vulnerable to COVID-19 and risk factors. The use of the Demographic and Health Survey (DHS) dataset has led to the choice of the following dimensions: Education, Hygiene, Staying at home, Physical distance, and recovery capacity. Each dimension is composed of indicators found in the global multidimensional poverty index. The findings show that 61.4% of Senegalese are vulnerable to COVID-19 because they suffer deprivation in at least a third of the indicators. Also, among the vulnerable 47.05% are poor according to the wealth index. The deprivation in electricity, housing, sanitation, and cooking fuel are the most important risk factors in the Senegalese context. The regions located in the South and East are those where the populations are more vulnerable. However, the number of confirmed cases is higher in the northern and western regions where there are fewer vulnerable people. In these regions, the greatest risk factor is promiscuity. Difficulty in observing physical and social distance and having a suitable living environment are major factors of vulnerability to emerging infectious diseases such as COVID-19 in a developing country like Senegal.

This paper aims to test the invariance measures of subjective well-being and some of its determinants using Ghanaian and German data from the WVS (World Value Survey). From the WVS wave-6 data, the following dimensions are selected: religion, social capital, social trust, fear feeling or worry, political activities, personalities, security, economic conditions, and subjective well-being. To test the different types of invariance (configural invariance and metric invariance), MGCFA (Multi-group Confirmatory Factor Analysis) was used. The first result of our modeling was that all dimensions significantly determine subjective well-being in the local model with the German data. In contrast to the Ghanaian data, only the dimensions of political activity and the fear feeling or worries turn out not to be significant in explaining subjective well-being. Second, the configural invariance test revealed that social capital, religion, social trust, fear feelings or worries, and economic conditions are non-equivalent between the two countries. Security, political activities, and subjective well-being satisfy the partial invariance measurement. Only personality traits are fully invariant across the two countries. As a result, a comparison of the determinants of well-being across the two countries is only possible for personality traits (full invariance measurement) and security (partial invariance measurement).