Trends of inequalities in childhood immunization coverage among children aged 12-23 months in Kenya, Ghana, and Côte d’Ivoire

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Study Justification:
– Immunization is a cost-effective health intervention that can prevent childhood diseases and improve child health.
– There is a significant disparity in childhood immunization coverage.
– The study aims to investigate the trends of within-country inequalities in childhood immunization coverage in Kenya, Ghana, and Côte d’Ivoire.
– These countries are on the verge of entering the accelerated phase of the Gavi, the Vaccine Alliance’s co-sharing of costs of vaccine and eventually assuming full costs of vaccines.
Highlights:
– The study uses data from the Demographic Health Surveys and Multiple Indicator Cluster Surveys.
– Measures of inequality such as rate difference, rate ratio, and relative concentration index are used to analyze the trends in immunization coverage.
– Results suggest that inequality in immunization coverage persists over time in most years, favoring the most-advantaged households.
– However, there is a sharp decrease in inequalities in childhood immunization coverage in Ghana over time.
– Policymakers could address pro-rich inequality in immunization coverage by designing health interventions through an equity lens.
Recommendations:
– Policymakers should use inequality data and prioritize disadvantaged households in health intervention designs to increase the efficiency of the primary health care system and reduce vaccine-preventable diseases.
– Strategies should be developed to address the persistent inequalities in immunization coverage in Kenya and Côte d’Ivoire.
Key Role Players:
– Policymakers and government officials responsible for health and immunization programs.
– Health professionals and practitioners involved in immunization campaigns.
– Non-governmental organizations (NGOs) working on healthcare and child welfare.
– Community leaders and volunteers who can help raise awareness and promote immunization.
Cost Items for Planning Recommendations:
– Funding for immunization campaigns, including vaccine procurement, distribution, and administration.
– Training and capacity building for healthcare workers and volunteers.
– Communication and awareness campaigns targeting disadvantaged communities.
– Monitoring and evaluation systems to track immunization coverage and inequality indicators.
– Research and data analysis to inform evidence-based decision-making.

Background: Immunization is one of the most cost-effective health intervention to halt the spread of childhood diseases, and improve child health. Yet, there is a substantial disparity in childhood immunization coverage. The overall objective of the study is to investigate the trends of within-country inequalities in childhood immunization coverage among children aged 12-23 months in Kenya, Ghana, and Côte d’Ivoire. The three countries included in this study are countries that are on the verge of entering the accelerated phase of the Gavi, the Vaccine Alliance’s co-sharing of costs of vaccine and eventually assuming full costs of vaccines. Côte d’Ivoire is in the Gavi preparatory transition phase, entering the accelerated transition phase in 2020, with an expected transition to full self-financing in 2025. Ghana is expected to enter the accelerated transition phase in 2021 and to full self-financing in 2026 while Kenya will enter in 2022 and fully self-finance in 2027. We examine the pattern of inequality in childhood immunization coverage over time through an equity lens by mainly exploring the direction of inequality in coverage. Methods: We use data from the Demographic Health Surveys and Multiple Indicator Cluster Surveys. The rate difference, rate ratio, and relative concentration index are used as measures of inequality. Results: Results of the study suggest that in most years inequality in immunization coverage in the three countries persist over time, and it favors the most-advantaged households. However, there is a sharp decrease pattern in inequalities in childhood immunization coverage in Ghana over time. Conclusion: Policymakers could be more strategic in addressing pro-rich inequality in immunization coverage by designing health interventions through an equity lens. Using inequality data and putting disadvantaged households at the center of health intervention designs could increase the efficiency of the primary health care system and reduce the incidence of mortality and morbidity as a result of vaccine-preventable disease.

Data used in this study were obtained from the DHS covering the 1993–2014 period (Kenya and Ghana), DHS and Multiple Indicator Cluster Surveys (MICS) covering the 1994–2011 period (Côte d’Ivoire) and analyzed using the Health Equity Assessment Toolkit (HEAT). The periods differ by country due to data availability. The HEAT [16] is a software developed by the World Health Organization (WHO) used to monitor health inequalities on 30 reproductive, maternal, newborn and child health indicators, disaggregated by five dimensions of inequality (economic status, education, place of residence, subnational region and child’s sex). It covers most of the low-and-middle-income countries. The DHS and MICS are uploaded in the HEAT. The DHS are nationally representative household survey conducted in low-and-middle-income countries for the purpose of monitoring and evaluating population, health and nutrition programs. It is a face-to-face survey on women aged 15–49 administered by highly trained enumerators. In DHS, specific questions were asked to women about children’s health. Questions related to immunization coverage are of particular interest. The enumerators either record the dates of different vaccines from the child health book/vaccination card or ask questions about whether or not the child has ever had some vaccines. We focus on routine vaccines among children aged 12–23 months. The DHS are implemented by ICF International and funded by the United States Agency for International Development. The MICS are household surveys that collect information on children under the age of five and women aged 15–49 in several countries. MICS are comparable to DHS and contain similar questions related to immunization coverage. MICS are managed by the United Nations Children’s Fund. In the study, we use four immunization coverage indicators: Bacille Calmette-Guérin (BCG) coverage, diphtheria, tetanus toxoid and pertussis (DTP) coverage, measles coverage, poliomyelitis coverage, and full immunization coverage. BCG coverage is defined as the percentage of children aged 12–23 months who have received one dose of BCG vaccine given at birth, in a given year. DTP coverage is the percentage of children who have received three doses of the combined DTP vaccine given at age six, ten, and fourteen weeks respectively, in a given year. Measles coverage is defined as the percentage of children aged 12–23 months who have received at least one dose of measles-containing vaccine given in some countries at the age of nine months, in a given year. Poliomyelitis coverage is the percentage of children aged 12–23 months who have received three doses of polio vaccine given at age six, ten, and fourteen weeks respectively, in a given year. Full immunization coverage is the percentage of children aged 12–23 months who have received one dose of BCG vaccine, three doses of the polio vaccine, three doses of the combined DTP vaccine, and one dose of measles vaccine. Table ​Table11 presents the definition of the indicators of immunization coverage. Immunization coverage indicators among children aged 12–23 months Notes: Data sources are from DHS, MICS and analyzed using the HEAT software Different statistics are used to measure inequality depending on whether the inequality dimensions are ordered or non-ordered [17]. Ordered dimensions such as economic status and education have an inherent ordering of subgroups, implying that households in the poorest quintile (with less education) have less of something compared to those with more wealth (more education). Non-ordered dimensions, by contrast, have subgroups that have no intrinsic ordering of subgroups such as gender, place of residence (urban vs. rural), subnational region. In this study, inequalities measures of ordered dimensions are used. The economic status of households was determined using a wealth index, which captures the households’ ownership of assets and access to some services. For each country selected, the wealth index was constructed using principal component analysis and households are classified into quintiles, ranging from the poorest quintile to the richest quintile. Additionally, we use mother’s education as another dimension of inequality. Education was an ordinal variable taking three categories: no education, primary education level, and secondary or higher. In assessing the inequality in immunization coverage indicators, three inequality measures are used: rate difference (absolute inequality), rate ratio (relative inequality), and the relative concentration index. These measures are commonly used in the literature. The rate difference and rate ratio are simple measures of inequality which do not account for the population share and only looks at the extreme categories. Simply stated, the rate difference is the difference of immunization outcomes between the most-advantaged (richest quintile, secondary school or higher) and most-disadvantaged subgroups (poorest quintile, no education), whereas the rate ratio is the immunization outcomes in the most-advantaged (richest quintile, secondary school or higher) divided by the immunization outcomes in the most-disadvantaged subgroups (poorest quintile, no education). A positive value of the rate difference indicates that immunization coverage tends to favor the most-advantaged households. Similarly, a rate ratio greater than one means that immunization coverage tends to favor the most-advantaged households. The relative concentration index is a complex and sophisticated measure of inequality [18]. It accounts for the population share in different subgroups and is defined as twice the area between the line of equality and the concentration curve. It provides information on the extent to which immunization coverage is concentrated among the disadvantaged or the advantaged households. In the HEAT, the relative concentration index is bounded between − 100 and + 100 since it is multiplied by 100. Positive values indicate a concentration of the immunization coverage among the advantaged, while negative values indicate a concentration of the immunization coverage among the disadvantaged. We explore the significance of the relative concentration index using a t-test at the 5% level of significance. We also report the 95% confidence intervals in each figure for every country. The confidence intervals are estimated via bootstrap methods. The survey sampling design was taken into account for estimating all inequality measures. Because our data cover several time points, we examine the pattern of inequality in immunization coverage over time through an equity lens by mainly exploring the variation of inequality in immunization coverage over time. Table ​Table22 summarizes these inequality measures. Inequality measures of ordered dimensions Notes: Ymax, Ymin are the immunization outcomes of the most-advantaged subgroup, most-disadvantaged subgroup, respectively. Xj, Pj, Yj are the relative rank, population share, and immunization outcomes of subgroup j, respectively. μ is the national average

Based on the provided information, here are some potential innovations that could improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide information and reminders about maternal health, including immunization schedules, prenatal care, and postnatal care. These apps can be easily accessible to pregnant women and new mothers, helping them stay informed and connected to healthcare services.

2. Community Health Workers: Train and deploy community health workers to provide education, counseling, and support to pregnant women and new mothers in remote or underserved areas. These workers can help bridge the gap between healthcare facilities and the community, ensuring that women receive the necessary care and information.

3. Telemedicine: Implement telemedicine services to enable remote consultations between healthcare providers and pregnant women or new mothers. This can be particularly beneficial for women in rural areas who may have limited access to healthcare facilities. Telemedicine can provide timely advice, guidance, and support, reducing the need for unnecessary travel.

4. Maternal Health Vouchers: Introduce voucher programs that provide financial assistance to pregnant women for accessing maternal health services, including immunizations. These vouchers can help reduce financial barriers and ensure that women receive the necessary care without facing financial hardship.

5. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve leveraging private sector resources, such as clinics, pharmacies, and transportation services, to enhance the availability and affordability of maternal health services.

6. Health Education Campaigns: Launch targeted health education campaigns to raise awareness about the importance of maternal health and immunizations. These campaigns can use various channels, such as radio, television, social media, and community events, to reach a wide audience and promote behavior change.

7. Strengthening Health Systems: Invest in strengthening healthcare infrastructure, including facilities, equipment, and trained healthcare professionals, to ensure that maternal health services are readily available and of high quality. This can involve improving the capacity of healthcare facilities to provide immunizations and other essential maternal health services.

It is important to note that the specific context and needs of each country should be considered when implementing these innovations. Additionally, ongoing monitoring and evaluation should be conducted to assess the effectiveness and impact of these interventions on improving access to maternal health.
AI Innovations Description
Based on the description provided, the recommendation to improve access to maternal health is to design health interventions through an equity lens. Policymakers should use inequality data and prioritize disadvantaged households in the development of health interventions. This approach can increase the efficiency of the primary healthcare system and reduce mortality and morbidity from vaccine-preventable diseases. By addressing pro-rich inequality in immunization coverage, policymakers can work towards improving access to maternal health for all individuals, regardless of their socioeconomic status.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Strengthening Primary Health Care: Enhance the capacity and resources of primary health care facilities to provide comprehensive maternal health services, including antenatal care, skilled birth attendance, and postnatal care.

2. Community-Based Interventions: Implement community-based interventions to increase awareness and knowledge about maternal health, promote early and regular antenatal care visits, and encourage facility-based deliveries.

3. Mobile Health (mHealth) Solutions: Utilize mobile technology to provide maternal health information, reminders for antenatal care visits, and access to teleconsultations with healthcare providers.

4. Transportation Support: Establish transportation systems or programs to ensure that pregnant women can easily access healthcare facilities, especially in remote or underserved areas.

5. Financial Incentives: Provide financial incentives, such as conditional cash transfers or maternity vouchers, to encourage pregnant women to seek and utilize maternal health services.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the indicators: Identify specific indicators to measure access to maternal health, such as the number of antenatal care visits, facility-based deliveries, postnatal care utilization, and maternal mortality rates.

2. Data collection: Gather data on the selected indicators from various sources, including health facilities, surveys, and administrative records. Ensure that the data is representative and covers the target population.

3. Baseline assessment: Analyze the current status of access to maternal health services using the collected data. Calculate the baseline values for the selected indicators and assess any existing disparities or inequalities.

4. Intervention implementation: Implement the recommended interventions in selected areas or communities. Ensure proper monitoring and evaluation mechanisms are in place to track the implementation process.

5. Data analysis: Collect post-intervention data on the selected indicators. Compare the post-intervention values with the baseline values to assess the impact of the interventions on improving access to maternal health.

6. Statistical analysis: Use appropriate statistical methods, such as regression analysis or difference-in-differences analysis, to quantify the impact of the interventions. Analyze any changes in the selected indicators and assess the significance of the results.

7. Interpretation and reporting: Interpret the findings of the analysis and report the results in a clear and concise manner. Highlight the impact of the interventions on improving access to maternal health and identify any remaining gaps or challenges.

8. Policy recommendations: Based on the findings, provide policy recommendations to further enhance access to maternal health services. Consider scaling up successful interventions, addressing remaining disparities, and ensuring sustainability of the improvements achieved.

It is important to note that the specific methodology may vary depending on the context, available data, and resources. It is recommended to consult with experts and stakeholders in the field of maternal health to tailor the methodology to the specific situation.

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