Socioeconomic and residence-based related inequality in childhood vaccination in Sub-Saharan Africa: Evidence from Benin

Understanding Socioeconomic Inequalities in Zero-Dose Children for Vaccination in Underserved Settings of Ethiopia: Decomposition Analysis Approach

Despite considerable global efforts to enhance vaccine distribution in low-income countries, a significant number of children remain unvaccinated, particularly in Ethiopia. The underlying socioeconomic challenges in these regions are recognized as primary contributors to the low vaccination rates. However, the reasons for this persistent disparity in Ethiopia's remote and underserved regions need further analysis. The study employed a cross-sectional design and was conducted as part of the Project HOPE Zero-Dose Evaluation from 1 February to 31 July 2022. Concentration indices were utilized to quantify the extent of inequality, with further decomposition aimed at identifying contributing factors to this disparity. The findings underscored that populations with lower socioeconomic status encounter high numbers of children receiving no vaccinations. Key factors influencing the number of zero-dose children included distance from healthcare facilities (61.03%), economic status of the household (38.93%), absence of skilled birth assistance (20.36%), underutilization of antenatal care services ( Collapse

Key Words

• Ethiopia
• concentration index
• decomposition analysis
• immunization
• zero-dose

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MESH Headings

• Ethiopia
• Humans
• Cross-Sectional Studies
• Socioeconomic Factors
• Vaccination/statistics & numerical data
• Female
• Infant
• Child, Preschool
• Male
• Healthcare Disparities/statistics & numerical data

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Grants

• NV 018567 Bill & Melinda Gates Foundation

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Affiliation(s)

Gashaw Andargie Biks Project HOPE, Ethiopia Country Office, Addis Ababa P.O. Box 45, Ethiopia; (F.S.); (D.A.T.)
Fisseha Shiferie Project HOPE, Ethiopia Country Office, Addis Ababa P.O. Box 45, Ethiopia; (F.S.); (D.A.T.)
Dawit Abraham Tsegaye Project HOPE, Ethiopia Country Office, Addis Ababa P.O. Box 45, Ethiopia; (F.S.); (D.A.T.)
Wondwossen Asefa Project HOPE Headquarter, 1220 19th St NW #800, Washington, DC 20036, USA;
Frank DelPizzo Bill & Melinda Gates Foundation, 500 5th Ave N, Seattle, WA 98109, USA;
Samson Gebremedhin School of Public Health, Addis Ababa University, Addis Ababa P.O. Box 1176, Ethiopia;

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Inequality in Childhood Immunization Coverage: A Scoping Review of Data Sources, Analyses, and Reporting Methods

Immunization through vaccines among children has contributed to improved childhood survival and health outcomes globally. However, vaccine coverage among children is unevenly distributed across settings and populations. The measurement of inequalities is essential for understanding gaps in vaccine coverage affecting certain sub-populations and monitoring progress towards achieving equity. Our study aimed to characterize the methods of reporting inequalities in childhood vaccine coverage, inclusive of the settings, data source types, analytical methods, and reporting modalities used to quantify and communicate inequality. We conducted a scoping review of publications in academic journals which included analyses of inequalities in vaccination among children. Literature searches were conducted in PubMed and Web of Science and included relevant articles published between 8 December 2013 and 7 December 2023. Overall, 242 publications were identified, including 204 assessing inequalities in a single country and 38 assessing inequalities across more than one country. We observed that analyses on inequalities in childhood vaccine coverage rely heavily on Demographic Health Survey (DHS) or Multiple Indicator Cluster Surveys (MICS) data (39.3%), and papers leveraging these data had increased in the last decade. Additionally, about half of the single-country studies were conducted in low- and middle-income countries. We found that few studies analyzed and reported inequalities using summary measures of health inequality and largely used the odds ratio resulting from logistic regression models for analyses. The most analyzed dimensions of inequality were economic status and maternal education, and the most common vaccine outcome indicator was full vaccination with the recommended vaccine schedule. However, the definition and construction of both dimensions of inequality and vaccine coverage measures varied across studies, and a variety of approaches were used to study inequalities in vaccine coverage across contexts. Overall, harmonizing methods for selecting and categorizing dimensions of inequalities as well as methods for analyzing and reporting inequalities can improve our ability to assess the magnitude and patterns of inequality in vaccine coverage and compare those inequalities across settings and time.

Spatial distribution and determinants of measles vaccination dropout among under-five children in Ethiopia: A spatial and multilevel analysis of 2019 Ethiopian demographic and health survey

BACKGROUND

Each year, vaccine-preventable diseases cost the lives of 8.8 million under-five children. Although vaccination prevents 1-2 million childhood deaths worldwide, measles vaccination dropouts are not well studied in developing countries, particularly in Ethiopia. Therefore, this study aims to assess the spatial distribution of the measles vaccination dropout and its determinants among under-five children in Ethiopia.

METHODS

Data from Ethiopian Demographic and Health Survey 2019 was used for data analysis. The study used a total of 5,753 children. Spatial autocorrelations was used to determine the spatial dependency of measles vaccination dropout. Ordinary interpolation was employed to forecast measles vaccination dropout. Factors associated with measles vaccination dropout were declared significant at p-values <0.05. The data were interpreted using the confidence interval and adjusted odds ratio. A model with the lowest deviance and highest logliklihood ratio was selected as the best-fit model.

RESULTS

In Ethiopia, one in three under-five children had measles vaccination dropouts. Factors such as birth interval (AOR = 1.87, 95% CI: 1.30, 2.70), unmarried marital status women (AOR = 3.98, 95% CI: 1.08, 8.45), ≤1 number of under-five children (AOR = 3.86, 95% CI: 2.56, 5.81), rural place of residence (AOR = 2.43, 95% CI: 2.29, 3.11), low community-level ANC utilization (AOR = 3.20, 95% CI: 2.53, 3.56), and residing in Benishangul Gumuz (AOR = 1.80, 95% CI: 1.061, 3.06) had higher odds of measles vaccination dropout.

CONCLUSIONS

Measles vaccination dropout rates in Ethiopia among under-five children were high compared to the maximum tolerable vaccination dropout level of 10% by the WHO. Both individual and community-level variables were determinants of measles vaccination dropout. The ministry of health in Ethiopia should give attention to those mothers of under-five children who reported underutilization of ANC services and rural residences while designing policies and strategies in areas of high spatial clustering of vaccine dropout in Ethiopia.

Decomposition Analysis of Socioeconomic Inequalities in Vaccination Dropout in Remote and Underserved Settings in Ethiopia

Despite increments in immunization coverage over the past decades, substantial inequality due to wealth status has persisted in Ethiopia. This study aimed to decompose the concentration index into the contributions of individual factors to socioeconomic inequalities of childhood vaccination dropout in remote and underserved settings in Ethiopia by using a decomposition approach. A wealth index was developed by reducing 41 variables related to women's household living standards into nine factors by using principal component analysis. The components were further totaled into a composite score and divided into five quintiles (poorest, poorer, middle, richer, and richest). Vaccination dropout was calculated as the proportion of children who did not get the pentavalent-3 vaccine among those who received the pentavalent-1 vaccine. The concentration index was used to estimate socioeconomic inequalities in childhood vaccination dropout, which was then decomposed to examine the factors contributing to socioeconomic inequalities in vaccination dropout. The overall concentration index was -0.179 (P <0.01), confirming the concentration of vaccination dropout among the lowest wealth strata. The decomposition analyses showed that wealth index significantly contributed to inequalities in vaccination dropout (49.7%). Place of residence also explained -16.2% of the inequality. Skilled birth attendance and availability of a health facility in the kebele (the lowest administrative government structure) also significantly contributed (33.6% and 12.6%, respectively) to inequalities in vaccination dropout. Wealth index, place of residence, skilled birth attendance, and availability of a health facility in the kebele largely contributed to the concentration of vaccination dropout among the lowest wealth strata. Policymakers should address vaccination inequality by designing more effective strategies.

Socioeconomic Determinants of Health: Remoteness From Care

Remoteness from care remains a major challenge to equitable provision of health services worldwide. Beyond the difficulties associated with geographically and climatically rugged terrain, there are also socioeconomic, cultural, and technological challenges associated with remote residence. The objective of this review is to examine the factors whereby remoteness can be associated with sociodemographic disadvantage in health care and describe some of the methodologies for measurement and analysis of remoteness, with examples from the literature, particularly focusing on Canada. As surrogates for remoteness, simple measurements of direct distance or travel time may correlate well with more complex measures and can be performed relative to specific health care services of interest (for example, tertiary obstetric service). These metrics may also be measured, as general proxies for service availability, to various sizes of population centres. More complex measures of remoteness may also incorporate modes of available transport and availability of specific services into an index such as the Canadian Index of Remoteness. As an important independent predictor of health, remoteness requires careful predictive modelling because of potential complex nonlinear relationships, edge effects created by health system zone boundaries, and covariance with other sociodemographic factors and Indigenous population proportions. To combat disadvantage caused by remoteness, innovation in health service delivery, policy, and technology is required. Health-resource allocation must be adequate, and innovative technological advances-such as remote monitoring, expert clinical support, and artificial intelligence algorithms-must be supported by development of appropriate technological infrastructure, targeting remote regions. With these, the barriers to equitable health imposed by remoteness can be overcome.

Obscured inequity: How focusing on rates of disparities can conceal inequities in the reasons why adolescents are unvaccinated

Traditional sociodemographic disparities in adolescent vaccination initiation for the HPV, Tdap, and MenACWY vaccines have declined in the United States of America. This decline raises the question of whether inequities in access have been successfully addressed. This paper synthesizes research on the resource barriers that inhibit vaccination alongside research on vaccine hesitancy where parents actively refuse vaccination. To do so, I classify the primary reason why teens are unvaccinated in the National Immunization Survey-Teen 2012-2022 into three categories: resource failure, agentic refusal, and other reasons. I use three non-exclusive subsamples of teens who are unvaccinated against the HPV (N = 87,163), MenACWY (N = 54,726), and Tdap (N = 10,947) vaccines to examine the relative importance of resource failure reasons and agentic refusal reasons for non-vaccination across time and teens' sociodemographic characteristics. Results indicate that resource failure reasons continue to explain a substantial portion of the reasons why teens are unvaccinated and disproportionately affect racially/ethnically and economically marginalized teens. Thus, even as sociodemographic inequalities in rates of vaccination have declined, inequities in access remain consequential.

Vaccination dropout and wealth related inequality among children aged 12-35 months in remote and underserved settings of Ethiopia: a cross-sectional evaluation survey

Background

Vaccination is one of the most cost-effective public health interventions that prevents millions of deaths. Although immunization coverage is increasing globally, many children in low- and middle-income countries drop out of the vaccination continuum. This study aimed at determining vaccination dropout rates and predictors in children aged 12-35 months in remote and underserved areas of Ethiopia.

Methods

This study was part of a cross-sectional evaluation survey that was conducted in 2022 in Ethiopia. The study settings include pastoralist, developing & newly established regions, conflict affected areas, urban slums, internally displaced populations and refugees. A sample of 3,646 children aged 12-35 months were selected using a cluster sampling approach. Vaccination dropout was estimated as the proportion of children who did not get the subsequent vaccine among those who received the first vaccine. A generalized estimating equation was used to assess determinants of the dropout rate and findings were presented using an adjusted odds ratio with 95% confidence interval. Concentration curve and index were used to estimate wealth related inequality of vaccination dropout.

Results

A total of 3,646 caregivers of children participated in the study with a response rate of 97.7%. The BCG to Penta-3 (52.5%), BCG to MCV-2 (57.4%), and Penta-1 to Penta-3 (43.9%) dropouts were all high. The highest Penta-1 to Penta-3 dropout rate was found in developing regions (60.1%) and the lowest was in urban slums (11.2%). Caregivers who were working outside their homes [AOR (95% CI) = 3.67 (1.24-10.86)], who had no postnatal care follow-up visits [AOR (95%CI) = 1.66 (1.15-2.39)], who did not receive a service from a skilled birth attendant [AOR (95%CI) = 1.64 (1.21-2.27)], who were older than 45 years [AOR (95% CI) = 12.49 (3.87-40.33)], and who were less gender empowered [AOR (95%CI) = 1.63 (1.24-2.15)] had increased odds of Penta-1 to Penta-3 dropout. The odds of dropout for children from poor caregivers was nearly two times higher compared to their wealthy counterparts [AOR (95%CI) = 1.87 (1.38-2.52)].

Conclusion

Vaccination dropout estimates were high among children residing in remote and underserved settings. Poor wealth quintile, advanced maternal age, low women empowerment, and limited utilization of maternity care services contributed to vaccination dropout.

COVID-19 Impact on DTP Vaccination Trends in Africa: A Joinpoint Regression Analysis

BACKGROUND

Deaths due to vaccine-preventable diseases are one of the leading causes of death among African children. Vaccine coverage is an essential measure to decrease infant mortality. The COVID-19 pandemic has affected the healthcare system and may have disrupted vaccine coverage.

METHODS

DTP third doses (DTP3) Vaccine Coverage was extracted from UNICEF databases from 2012 to 2021 (the last available date). Joinpoint regression was performed to detect the point where the trend changed. The annual percentage change (APC) with 95% confidence intervals (95% CI) was calculated for Africa and the regions. We compared DTP3 vaccination coverage in 2019-2021 in each country using the Chi-square test.

RESULT

During the whole period, the vaccine coverage in Africa increased with an Annual Percent change of 1.2% (IC 95% 0.9-1.5): We detected one joinpoint in 2019. In 2019-2021, there was a decrease in DTP3 coverage with an APC of -3.5 (95% -6.0; -0,9). (p < 0.001). Vaccination rates decreased in many regions of Sub-Saharan Africa, especially in Eastern and Southern Africa. There were 26 countries (Angola, Cabo Verde, Comoros, Congo, Côte d'Ivoire, Democratic Republic of the Congo, Djibouti, Ethiopia, Eswatini, The Gambia, Guinea-Bissau, Liberia, Madagascar, Malawi, Mauritania, Mauritius, Mozambique, Rwanda, Senegal, Seychelles, Sierra Leone, Sudan, Tanzania, Togo, Tunisia, Uganda, and Zimbabwe) where the vaccine coverage during the two years decreased. There were 10 countries (Angola, Cabo Verde, Comoros, Democratic Republic of the Congo, Eswatini, The Gambia, Mozambique, Rwanda, Senegal, and Sudan) where the joinpoint regression detected a change in the trend.

CONCLUSIONS

COVID-19 has disrupted vaccine coverage, decreasing it all over Africa.