Enriching tuberculosis research by measuring poverty better: a perspective

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.

The relationship between monetary poverty and female (dis)empowerment has been extensively explored. In contrast, empirical research on the association between multidimensional poverty and female (dis)empowerment across low- and middle‐income countries (LMICs) remains limited. This study contributes to filling this gap by examining both the association and the overlap between non‐income multidimensional poverty and disempowerment, using data from partnered women aged 15–49 drawn from Demographic and Health Surveys in 32 LMICs across Africa, Asia, Latin America and the Caribbean, and Oceania. We measure poverty and disempowerment using two Alkire–Foster‐based indices: the global Multidimensional Poverty Index and the Multidimensional Women’s Disempowerment Index. We find a positive, albeit moderate, cross‐country association between multidimensional poverty and disempowerment. In most countries, poor women face higher disempowerment rates than non‐poor women. In half of the countries, over 29% of women are simultaneously poor and disempowered, with large variation—from 65% in Mali to under 1% in the Philippines and Armenia. In others, like Ethiopia or Tajikistan, many women are poor yet empowered or non‐poor yet disempowered, respectively. Individual-level regressions confirm a moderate positive association. These findings offer new cross-country evidence on the links between SDGs 1 (No Poverty) and 5 (Gender Equality).

This paper describes the database The global Multidimensional Poverty Index (MPI): Harmonised level estimates and their changes over time. The global MPI is an international poverty measure based on ten deprivation indicators in three dimensions: health, education, and living standards. The database contains estimates for the MPI itself (the adjusted headcount ratio); related partial indices such as headcount ratio, intensity, indicator-specific indices, and several auxiliary statistics; and changes over time for most quantities. For this database, all deprivation indicators have been harmonised over time. Our database covers estimates for 84 countries and 814 subnational regions for up to four points of observation. The estimates are based on 211 individual survey datasets, provided primarily by the Demographic Health Surveys (DHS) and the Multiple Indicator Cluster Surveys (MICS). Combining information about different dimensions of human wellbeing, the global MPI inherently invites interdisciplinary research.

Poverty is a multifaceted phenomenon that has always existed historically. In addition to discussions of poverty issues, aspects of poverty measurement are essential topics. A prominent poverty measurement system is the unidimensional measurement based on poverty line income (PLI). Therefore, the use of multidimensional poverty measurements is proposed, specifically the multidimensional poverty index (MPI), in assessing poverty, including non-monetary aspects. This study discusses the concept of unidimensional and multidimensional poverty measurement and the implementation of these concepts in Malaysia during the COVID-19 outbreak. Furthermore, it aims to contribute to the public debate on COVID-19 policy responses by quantifying the potential impact on global multidimensional poverty using the Global Multidimensional Poverty Index (MPI), which captures concurrent or overlapping deprivation at the household level. This study recommends policies by which members of the community and industry experts would be included in the poverty reduction program, in line with Maslow’s requirements. Overall, this research focuses on planning and orienting policy responses from a multidimensional perspective that integrates health, social and economic goals.

Foremost in the Sustainable Development Goals (SGDs) of the 2030 Agenda, is the goal of achieving “No Poverty”. With nearly a decade yet to go, it is imperative to know the true nature and extent of poverty so that steps can be taken to eradicate poverty in all its forms. Multidimensional Poverty is a problem that persists on a larger extent in a developing country such as India, particularly among its women. The study uses the Demographic Health Survey data – India’s National Family Health Survey (NFHS), a nationwide survey conducted with a representative sample of women aged 15 to 49 throughout the country, to shed light on the nature and extent of deprivations faced by them. The deprivations faced by the women are measured along the dimensions of education, health and standard of living as per the global Multidimensional Poverty Index (MPI) jointly developed by UNDP (United Nations Development Program) and Oxford Poverty and Human Development Initiative (OPHI). Findings reveal that one-fifth of women in India are multidimensionally poor. Further subgroup decomposition reveals that higher levels of deprivations are found in women living alone, with higher age, having more number of children, widowed or divorced, husbands having multiple wives, those having more than one union and married before the legal age of marriage. The Government needs to focus its attention on the most deprived groups of women. Based on the nature and the extent of deprivations that they face, appropriate measures must be taken to bring them out of their destitution.

The relationship between the socio-economic status of working equine owners and the welfare status of their animals is yet to be documented. The aim of this study was to provide an approach to understanding socio-economic status, quality of life and working aspects of working horse owners, in order to establish their social vulnerability index and to determine how these measures correlate with the welfare state of their horses. Seventy-two owners and their urban working horses (n = 122) were studied. Owners’ socioeconomic and educational status was established together with their quality of life perception and multi-dimensional poverty index. The animal welfare index was constructed using animal-based measures. Whilst over 90% of owners were considered vulnerable, only 28.3% of horses were classified as being in a poor welfare state (eg presence of lesions and morphology not adequate for draught type). There were no significant correlations between owners’ factors and the animal welfare index. We conclude, therefore, that social vulnerability of owners does not necessarily imply that their animals will be in a poor welfare state.

Tuberculosis (TB) active case-finding (ACF) among high-risk populations is recommended to detect the missing people with TB. In Rajasthan, India, a state with a high TB prevalence:notification ratio, leveraging digital annual health survey data could enhance ACF by targeting villages with a high burden of TB risk factors. We conducted an ecological study across 19 districts of Rajasthan using data from the digital annual health survey. High-risk villages were identified based on three factors: multidimensional poverty index (MDPI), high proportion (>60%) of socially marginalized populations and geographic access (distance to primary health centre >7km). The survey covered 24.6 million individuals across 20 803 villages. Thirty-five percent of individuals belonged to socially marginalized populations. At the household level, 39% used solid fuels, indicating potential exposure to indoor air pollution. Nine percent of villages had high poverty (MDPI >0.21) and 25% had a high proportion (>60%) of socially marginalized populations. Approximately 34% of villages had at least one of the three high-risk factors. This study demonstrates the potential of existing digital annual survey data for targeted ACF. Further research is being planned to assess the yield of ACF in identified high-risk villages and to advocate for similar data-driven interventions in other settings.

This study examined wealth trends in a rural Kenyan community between 2011 and 2018. Understanding wealth trends is important for understanding health outcomes and overall well-being of vulnerable communities, and for informing economic and health policy that can improve specific wealth challenges. Information regarding household materials, assets, education, and mortality from 20,370 households in the Kombewa Health and Demographic Surveillance System was used. Three indices were developed and compared to quantify wealth: a principal component analysis of assets, a multiple correspondence analysis of assets, and the multidimensional poverty index. Wealth quintiles and levels of deprivation relating to socioeconomic status were then created and analyzed over time. Wealth measured by the asset-based indices, suggested an increase in wealth during the assessment period with the percentage of households in the wealthiest quintile increasing from 19 to 23%. The multidimensional poverty index, however, suggests no change in socioeconomic status over time. Among other factors, a lack of access to sanitation and improved water seems to be the main justification. Our results indicate that households are accumulating assets, but their increased accumulation is not translating to changes in living conditions known to improve health. Hence, while houses may be getting wealthier, they may not necessarily be getting healthier.

Paper 2: Individual Specific Weighting Scheme to a Multidimensional Poverty Measure Abstract Weights in the estimation of multidimensional poverty have a central role by showing the relative importance of dimensions. This paper proposed two differentweighting schemes: endowment and distributional based weighting schemes.The later weighting scheme gives more weight to the dimension with small number of deprived individuals. On the other hand, the endowment based weighting scheme gives more weight to the dimension with large number of deprived individuals. The proposed weighting schemes considerboth distributional equity and simultaneous deprivations of indicators. Using the Ethiopian rural household survey (ERHS) data for the year 2004, the paper compared the proposed weighting schemes with the equal weighting scheme approach. The empirical result showed that, the multidimensional poverty index (MPI) estimation using endowment based equity weight has a lower estimate than the equal weighting approach. This happened because the indicators that have a small number of deprived individuals have got a higher weight under the equal weighting approach.

Do socioeconomic factors determine household multidimensional energy poverty? Empirical evidence from South Asia

Objetivo: Analizar la relación entre la pobreza y las actitudes hacia las prácticas de cuidado infantil en áreas rurales y urbanas de Colombia. Método: El presente artículo es un estudio transversal correlacional en el departamento del Atlántico, al norte de Colombia. Se indagó sobre las actitudes hacia el cuidado infantil y las condiciones de vida en 1189 cuidadores de niños en edad preescolar. Se tuvo en cuenta el índice de pobreza multidimensional y el área de procedencia de los participantes (urbana o rural). Resultados: No se encontró una relación directa entre las actitudes hacia el cuidado infantil y el índice de pobreza multidimensional. Sin embargo, se observó que los participantes de áreas urbanas provenientes de zonas vulnerables presentaron un mayor índice de pobreza y mostraron actitudes menos positivas hacia el cuidado infantil, especialmente en el cuidado cognitivo, del sueño y de la salud. Se evidenció un efecto moderador del área sobre las actitudes de cuidado. Conclusiones: El estudio destaca la influencia de la pobreza y la vulnerabilidad social en las actitudes de cuidado infantil, especialmente en áreas urbanas. Estos hallazgos subrayan la importancia de considerar las condiciones socioeconómicas y geográficas al abordar el cuidado infantil. Además, se resalta la necesidad de implementar estrategias específicas para promover prácticas de cuidado positivas en contextos más vulnerables, con el fin de mejorar el desarrollo de la primera infancia en Colombia

This paper explores the axiomatic foundation of multidimensional poverty indices. Departing from the income approach which measures poverty by aggregating shortfalls of incomes from a pre-determined poverty-line income, a multidimensional index is a numerical representation of shortfalls of basic needs from some pre-specified minimum levels. The class of subgroup consistent poverty indices introduced by Foster and Shorrocks (1991) is generalized to the multidimensional context. New concepts necessary for the design of distribution-sensitive multidimensional poverty measures are introduced. Specific classes of subgroup consistent multidimensional poverty measures are derived based on sets of reasonable axioms. This paper also highlights the fact that domain restrictions may have a critical role in the design of multidimensional indices.

Poverty has been dominantly an economic concept and dealt with income or expenditure in Malaysia. In many parts of the world, widespread support surface for the application of a multidimensional approach to poverty. Yet, in practice the vast majority of empirical work on poverty uses a unidimensional yardstick to judge a person’s well-being, usually expenditure or income per capita . While economic well-being, capability, political, and civic/cultural inclusion are integral parts of a multidimensional concept of poverty, a proper operationalization as well as comprehensive conceptualization of poverty based on multidimensional perspective is still lacking in Malaysia. With the introduction of the Multidimensional Poverty Index (MPI) this paper aims at bridging the gap between development and national policy from a multidimensional perspective. As a review paper, this study intends develop a coherent framework for measuring multidimensional poverty index in a smaller scale among the poor B40 Universiti Sains Malaysia (USM) students. Hence, by understanding the root causes of poverty as well as applying into an academic environment, the study will be able to bridge the gap between student’s academic performance with their quality of life from three major components; education, health and standard of living. The methodology of this paper is based solely on document research of secondary data. The findings of this study are envisaged to ascertain to what extent multidimensional poverty index is valid vis-a-vis the unidimensional measurement approach in the near future for a bigger scale research, both in the state of Penang and other states in Malaysia. Keywords : B40 students, Multidimensional Poverty Index, poverty, quality of life, unidimensional, Universiti Sains Malaysia students

Changing funding patterns in tuberculosis

As awareness of the limitations of relying solely on income to measure poverty has become more widespread, attention has been increasingly focused on multi-dimensional approaches, to the point where the European Union (EU) has adopted a multidimensional poverty and social exclusion target for 2020. The rationale advanced is that the computation of a multidimensional poverty index is an effective way of communicating in a political environment, and a necessary tool in order to monitor 27 different national situations. In contrast with the rather ad hoc way in which the EU 2020 poverty target has been framed and rationalized, the adjusted head count ratio applied here has a number of desirable axiomatic properties. It constitutes a significant improvement on union and intersection approaches and allows for the decomposition of multidimensional poverty in terms of dimensions of deprivation and socio-economic attributes. Since understanding poverty as multidimensional does not necessarily require constructing a multidimensional poverty index, on the basis of our analysis we provide a more general consideration of the value of developing a multidimensional index of poverty for the EU.