Health Equity Assessment Toolkit (HEAT and HEAT Plus): exploring inequalities in the COVID-19 pandemic era.

BACKGROUND: The Sustainable Development Goals have helped to focus attention on the importance of reducing inequality and 'leaving no one behind'. Monitoring health inequalities is essential for providing evidence to inform policies, programmes and practices that can close existing gaps and achieve health equity. The Health Equity Assessment Toolkit (HEAT and HEAT Plus) software was developed by the World Health Organization to facilitate the assessment of within-country health inequalities. RESULTS: HEAT contains a built-in database of disaggregated health data, while HEAT Plus allows users to upload and analyze inequalities using their own datasets. Version 4.0 of the software incorporated enhancements to the toolkit's capacity for equity assessments. This includes a multilingual interface, interactive and downloadable visualizations, flexibility to analyze inequalities using any dataset of disaggregated data, and the built-in calculation of 19 summary measures of inequality. This paper outlines the improved features and functionalities of the HEAT and HEAT Plus software since their original release, highlighted through an example of how the toolkit can be used to assess inequalities in the COVID-19 pandemic era. CONCLUSIONS: The features of the HEAT and HEAT Plus software make it a valuable tool for analyzing and reporting inequalities related to the COVID-19 pandemic, as well as its indirect impacts on inequalities in other health and non-health areas, providing evidence to inform equity-oriented interventions and strategies.

Education-related inequalities in beliefs and behaviors pertaining to COVID-19 non-pharmaceutical interventions.

BACKGROUND: The coronavirus pandemic has exposed existing social inequalities in relation to disease preventive behaviors, risk of exposure, testing and healthcare access, and consequences as a result of illness and containment measures across different population groups. However, due to a lack of data, to date there has been limited evidence of the extent of such within-country inequalities globally. METHODS: We examined education-related inequalities in four COVID-19 prevention and testing indicators within 90 countries, using data from the University of Maryland Social Data Science Center Global COVID-19 Trends and Impact Survey, in partnership with Facebook, over the period 1 June 2021 to 31 December 2021. The overall level of education-related inequalities, as well as how they differ across country income groups and how they have changed over time were analyzed using the Slope Index of Inequality (SII) and the Relative Index of Inequality (RII). We also assessed whether these education-related inequalities were associated with government policies and responses. RESULTS: Education-related inequalities in beliefs, mask wearing, social distancing and testing varied across the study countries. Mask wearing and beliefs in the effectiveness of social distancing and mask wearing were overall more common among people with a higher level of education. Even after controlling for other sociodemographic and health-related factors, social distancing practice was higher among the most educated in low/lower middle income countries, but was higher overall among the least educated in high income countries. Overall there were low education-related inequalities in COVID-19 testing, though there was variation across countries. CONCLUSIONS: The study highlights important within-country education-related differences in COVID-19 beliefs, preventive behaviors and testing, as well as differing trends across country income groups. This has implications for considering and targeting specific population groups when designing public health interventions and messaging during the COVID-19 pandemic and future health emergencies.

Health Inequality Monitoring channel on OpenWHO: capacity strengthening through eLearning.

BACKGROUND: Health inequality monitoring can generate important evidence to inform and motivate changes to policy, programmes and practices. However, the potential of health inequality monitoring practices to quantify inequalities between population subgroups and track progress on the advancement of health equity is under-realized. Capacity strengthening on health inequality monitoring can play an important role in enhancing political will for the generation and use of disaggregated data and for wider adoption of this practice to inform health decision-making. There is a lack of widely available and accessible training materials related to health inequality monitoring that may be used by a range of stakeholders. OBJECTIVE: In this paper, we describe the design, development and implementation of the Health Inequality Monitoring channel on the OpenWHO eLearning platform. We discuss the anticipated impact and potential opportunities for these eLearning courses to contribute to strengthened health inequality monitoring practices. RESULTS: The Health Inequality Monitoring channel on the OpenWHO platform is a self-directed learning environment, designed to meet the immediate learning needs of users. The channel contains three series of courses: health inequality monitoring foundations courses; topic-specific health inequality monitoring courses; and health inequality monitoring skill building courses. Courses are primarily targeted to monitoring and evaluation officers, data analysts, academics and researchers, public health professionals, medical and public health students, and others with a general interest in health data and inequality monitoring. CONCLUSIONS: WHO eLearning courses on health inequality monitoring are addressing the need for capacity strengthening in the collection, analysis and reporting of inequality data. They introduce learners to the foundational concepts, best practices, tools and skills required to conduct health inequality monitoring. The courses on the Health Inequality Monitoring channel demonstrate how technical information can be simplified and presented to broad audiences in a manner that is highly accessible to learners. The Health Inequality Monitoring channel on OpenWHO is an innovative and necessary addition to existing tools and resources to support the advancement of health equity.

The Association between Childhood Immunization and Gender Inequality: A Multi-Country Ecological Analysis of Zero-Dose DTP Prevalence and DTP3 Immunization Coverage.

This study explores the association between childhood immunization and gender inequality at the national level. Data for the study include annual country-level estimates of immunization among children aged 12-23 months, indicators of gender inequality, and associated factors for up to 165 countries from 2010-2019. The study examined the association between gender inequality, as measured by the gender development index and the gender inequality index, and two key outcomes: prevalence of children who received no doses of the DTP vaccine (zero-dose children) and children who received the third dose of the DTP vaccine (DTP3 coverage). Unadjusted and adjusted fractional logit regression models were used to identify the association between immunization and gender inequality. Gender inequality, as measured by the Gender Development Index, was positively and significantly associated with the proportion of zero-dose children (high inequality AOR = 1.61, 95% CI: 1.13-2.30). Consistently, full DTP3 immunization was negatively and significantly associated with gender inequality (high inequality AOR = 0.63, 95% CI: 0.46-0.86). These associations were robust to the use of an alternative gender inequality measure (the Gender Inequality Index) and were consistent across a range of model specifications controlling for demographic, economic, education, and health-related factors. Gender inequality at the national level is predictive of childhood immunization coverage, highlighting that addressing gender barriers is imperative to achieve universal coverage in immunization and to ensure that no child is left behind in routine vaccination.

Exploring the potential for a new measure of socioeconomic deprivation status to monitor health inequality.

BACKGROUND: Monitoring health inequalities is an important task for health research and policy, to uncover who is being left behind - and where - and to inform effective and equitable policies and programmes to tackle existing inequities. The choice of which measure to use to monitor and analyse health inequalities is thereby not trivial. This article explores a new measure of socioeconomic deprivation status (SDS) to monitor health inequalities. METHODS: The SDS measure was constructed using the Alkire-Foster method. It includes eight indicators across two equally weighted dimensions (education and living standards) and specifies a four-level gradient of socioeconomic deprivation at the household-level. We conducted four exercises to examine the value-added of the proposed SDS measure, using Demographic and Health Surveys data. First, we examined the discriminatory power of the new measure when applied to outcomes in four select reproductive, maternal, neonatal, and child health (RMNCH) indicators across six countries: skilled birth attendance, stunting, U5MR, and DTP3 immunisation. Then, we analysed the behaviour and association of the new SDS measure vis-à-vis the DHS Wealth Index, including chi-squared test and Pearson correlation coefficient. Third, we analysed the robustness of the SDS measure results to changes in its structure, using pairwise comparisons and Kendal Tau-b rank correlation. Finally, we illustrated some of the advantageous properties of the new measure, disaggregation and decomposition, on Haitian data. RESULTS: 1) Higher levels of socioeconomic deprivation are generally consistently associated with lower levels of achievements in the RMNCH indicators across countries. 2) 87% of all pairwise rank comparisons across a range of SDS measure structures were robust. 3) SDS and DHS Wealth Index are associated, but with considerable cross-country variation, highlighting their complementarity. 4) Haitian households in rural areas experienced, on average, more severe socioeconomic deprivation as well as lower levels of RMNCH achievement than urban households. CONCLUSIONS: The proposed SDS measure adds analytical possibilities to the health inequality monitoring literature, in line with ethically and conceptually well-founded notions of absolute, multidimensional disadvantage. In addition, it allows for breakdown by its dimensions and components, which may facilitate nuanced analyses of health inequality, its correlates, and determinants.

Improving child survival through environmental and nutritional interventions: the importance of targeting interventions toward the poor.

CONTEXT: The United Nations Millennium Development Goals (MDGs) set targets related to important global poverty, health, and sustainability issues. A critical but underinvestigated question for planning and allocating resources toward the MDGs is how interventions related to one MDG might affect progress toward other goals. OBJECTIVES: To estimate the reduction in child mortality as a result of interventions related to the environmental and nutritional MDGs (improving child nutrition and providing clean water, sanitation, and fuels) and to estimate how the magnitude and distribution of the effects of interventions vary based on the economic status of intervention recipients. DESIGN, SETTING, AND POPULATION: Population-level comparative risk assessment modeling the mortality effects of interventions on child nutrition and environmental risk factors, stratified by economic status. Data on economic status, child underweight, water and sanitation, and household fuels were from the nationally representative Demographic and Health Surveys for 42 countries in Latin America and the Caribbean, South Asia, and sub-Saharan Africa. Data on disease-specific child mortality were from the World Health Organization. Data on the hazardous effects of each MDG-related risk factor were from systematic reviews and meta-analyses of epidemiological studies. MAIN OUTCOME MEASURE: Child mortality, stratified by comparable international quintiles of economic status. RESULTS: Implementing interventions that improve child nutrition and provide clean water and sanitation and clean household fuels to all children younger than 5 years would result in an estimated annual reduction in child deaths of 49,700 (14%) in Latin America and the Caribbean, 0.80 million (24%) in South Asia, and 1.47 million (31%) in sub-Saharan Africa. These benefits are equivalent to 30% to 48% of the current regional gaps toward the MDG target on reducing child mortality. Fifty percent coverage of the same environmental and nutritional interventions, as envisioned by the MDGs, would reduce child mortality by 26,900, 0.51 million, and 1.02 million in the 3 regions, respectively, if the interventions are implemented among the poor first. These reductions are 30% to 75% larger than those expected if the same 50% coverage first reached the wealthier households, who nonetheless are in need of similar interventions. CONCLUSIONS: Interventions related to nutritional and environmental MDGs can also provide substantial gains toward the MDG of reducing child mortality. To maximize the reduction in childhood mortality, such integrated management of interventions should prioritize the poor.

Tendencias en las coberturas de parto institucional, EDAs e IRAs y la reforma de salud de Bolivia: un análisis de diferencias en diferencias / Trends in the coverage of institutional delivery, EDAs and IRAs and the reform of the health of Bolivia: a difference analisys in differences

El estudio examina el impacto del Seguro Básico de salud (SBS) sobre la cobertura de atención institucional del parto en mujeres entre 13 y 50 años, y de EDAs e IRAs en niños menores de cinco años. la estrategia de identificación del impacto del SBS se basa en la comparación del cambio en las coberturas de salud en municipios de baja utilización del SBS. Los resultados indican que en municipios de alta utilización del SBS, las coberturas de parto institucional se incrementaron más rápidamente. Este incremento fue más acentuado entre mujeres de bajos ingresos y bajos niveles de educación. No se observan diferencias significativas en las tendencias de cobertura de EDAs e IRAs.