Universal Immunization Coverage Research Articles

Presidents and vaccines: head of state inoculation as a tool for vaccine promotion.

Vaccine hesitancy, an important threat to global health, has increased since the onset of the COVID-19 pandemic. The public vaccination of high-profile figures, such as heads of state, has been touted as a potential tool for increasing vaccine acceptance among the general population. However, systematic information on such role modelling is lacking and existing studies focus on a small number of high-income countries. We take advantage of the COVID-19 pandemic to fill this gap. Through a systematic search of internet sources, we first document that most global leaders supported the vaccination campaign and actively communicated their vaccination status to the public. We then turn to a case study to provide experimental evidence on vaccine role modelling for a country in Africa - the region that is most lagging behind in achieving universal immunization coverage. We rely on a randomized survey experiment with 600 citizens in the Democratic Republic of Congo and take advantage of the fact that the Congolese President publicly received a COVID-19 vaccine during the survey period. Our findings demonstrate that the impact of political leader's role modelling is moderated by trust and depends on media outreach and access. When trust in leaders is lacking, or news on their actions is inaccessible, alternative ambassadors and effective communication methods become crucial in motivating and informing the public. This may be especially relevant in fragile states and remote regions.

Leveraging machine learning for vaccine distribution in resource-limited settings: A synthesis of approaches

Vaccine distribution in resource-limited settings remains a crucial global health challenge, exacerbated by factors such as inadequate infrastructure, limited resources, and complex supply chains. Leveraging machine learning (ML) holds promise for optimizing distribution efficiency and ensuring equitable access to life-saving vaccines. This paper synthesizes various ML approaches aimed at addressing vaccine distribution challenges in resource-constrained environments. The literature review examines existing research on ML applications in healthcare and vaccine distribution, highlighting key findings and methodologies. Methodologically, criteria were established for selecting relevant studies, with a focus on ML techniques and their effectiveness in resource-limited contexts. Key ML approaches identified include predictive analytics for demand forecasting, route optimization algorithms for efficient vaccine delivery, and decision support systems for prioritizing distribution efforts. Case studies illustrate successful ML implementations in real-world settings, showcasing improved vaccine coverage and reduced wastage. Despite promising results, challenges persist, including data scarcity, model generalization, and ethical considerations. Future research directions include enhancing data collection methods, refining ML algorithms for specific contexts, and integrating ML solutions into existing healthcare systems. In conclusion, this synthesis underscores the transformative potential of ML in revolutionizing vaccine distribution in resource-limited settings. By addressing logistical barriers and optimizing resource allocation, ML-driven approaches offer a pathway towards achieving universal immunization coverage and mitigating the impact of infectious diseases on vulnerable populations. Keywords: Machine Learning, Vaccine Distribution, Resource-Limited Settings, Synthesis of Approaches.

Leveraging Resource Centers for Strengthening Immunization Supply Chain.

The efficacy of immunization programs is critically dependent on robust supply chain management, a complex challenge exacerbated by expanding program scopes and evolving vaccine technologies. This comprehensive review underscores the pivotal role of Resource Centers in fortifying the immunization supply chain, presenting a paradigm shift toward enhanced national and global health outcomes. Through a detailed examination of their key activities, the article elucidates how these centers catalyze improvements across various facets of supply chain management - from the integration of suitable technology technologies and specialized training programs to the development of sustainable models and advocacy for policy prioritization. This further explores the multifaceted challenges these centers confront, including funding constraints, capacity building, and infrastructural gaps, alongside the burgeoning opportunities presented by new vaccine introductions, donor interest in health system strengthening, and the potential for broadened scope beyond immunization. By weaving together examples of existing centers worldwide, the review highlights their contributions towards optimizing vaccine logistics, enhancing data management, and ultimately achieving Sustainable Development Goal 3. The insights provided offer valuable guidance for planning and sustaining resource centers, positioning them as indispensable allies in the global pursuit of universal immunization coverage.

Assessment of immunization data management practices in Cameroon: unveiling potential barriers to immunization data quality

BackgroundOne crucial obstacle to attaining universal immunization coverage in Sub-Saharan Africa is the paucity of timely and high-quality data. This challenge, in part, stems from the fact that many frontline immunization staff in this part of the world are commonly overburdened with multiple data-related responsibilities that often compete with their clinical tasks, which in turn could affect their data collection practices. This study assessed the data management practices of immunization staff and unveiled potential barriers impacting immunization data quality in Cameroon.MethodsA descriptive cross-sectional study was conducted, involving health districts and health facilities in all 10 regions in Cameroon selected by a multi-stage sampling scheme. Structured questionnaires and observation checklists were used to collect data from Expanded Program of Immunization (EPI) staff, and data were analyzed using STATA VERSION 13.0 (StataCorp LP. 2015. College Station, TX).ResultsA total of 265 facilities in 68 health districts were assessed. There was limited availability of some data recording tools like vaccination cards (43%), maintenance registers (8%), and stock cards (57%) in most health facilities. Core data collection tools were incompletely filled in a significant proportion of facilities (37% for registers and 81% for tally sheets). Almost every health facility (89%) did not adhere to the recommendation of filling tally sheets during vaccination; the filling was instead done either before (51% of facilities) or after (25% of facilities) vaccinating several children. Moreso, about 8% of facilities did not collect data on vaccine administration. About a third of facilities did not collect data on stock levels (35%), vaccine storage temperatures (21%), and vaccine wastage (39%).ConclusionOur findings unveil important gaps in data collection practices at the facility level that could adversely affect Cameroon’s immunization data quality. It highlights the urgent need for systematic capacity building of frontline immunization staff on data management capacity, standardizing data management processes, and building systems that ensure constant availability of data recording tools at the facility level.

Evaluation of a Mobile-Based Immunization Decision Support System for Scheduling Age-Appropriate Vaccine Schedules for Children Younger Than 2 Years in Pakistan and Bangladesh: Lessons From a Multisite, Mixed Methods Study.

Missed opportunities for vaccination (MOVs), that is, when children interact with the health system but fail to receive age-eligible vaccines, pose a crucial challenge for equitable and universal immunization coverage. Inaccurate interpretations of complex catch-up schedules by health workers contribute to MOVs. We assessed the feasibility of a mobile-based immunization decision support system (iDSS) to automatically construct age-appropriate vaccination schedules for children and to prevent MOVs. A sequential exploratory mixed methods study was conducted at 6 immunization centers in Pakistan and Bangladesh. An android-based iDSS that is packaged in the form of an application programming interface constructed age-appropriate immunization schedules for eligible children. The diagnostic accuracy of the iDSS was measured by comparing the schedules constructed by the iDSS with the gold standard of evaluation (World Health Organization-recommended Expanded Programme on Immunization schedule constructed by a vaccines expert). Preliminary estimates were collected on the number of MOVs among visiting children (caused by inaccurate vaccination scheduling by vaccinators) that could be reduced through iDSS by comparing the manual schedules constructed by vaccinators with the gold standard. Finally, the vaccinators' understanding, perceived usability, and acceptability of the iDSS were determined through interviews with key informants. From July 5, 2019, to April 11, 2020, a total of 6241 immunization visits were recorded from 4613 eligible children. Data were collected for 17,961 immunization doses for all antigens. The iDSS correctly scheduled 99.8% (17,932/17,961) of all age-appropriate immunization doses compared with the gold standard. In comparison, vaccinators correctly scheduled 96.8% (17,378/17,961) of all immunization doses. A total of 3.2% (583/17,961) of all due doses (across antigens) were missed in age-eligible children by the vaccinators across both countries. Vaccinators reported positively on the usefulness of iDSS, as well as the understanding and benefits of the technology. This study demonstrated the feasibility of a mobile-based iDSS to accurately construct age-appropriate vaccination schedules for children aged 0 to 23 months across multicountry and low- and middle-income country settings, and underscores its potential to increase immunization coverage and timeliness by eliminating MOVs.

Using a mobile application ("PrimaKu") to promote childhood immunization in Indonesia: A cross-sectional study.

Universal immunization coverage among children in Indonesia is low compared to the global target. Many children in Indonesia are not fully immunized as recommended by the government, which results in a high mortality rate. The government has developed a mobile application (PrimaKu) to provide information on vaccinations and reminder features. However, the successful use of the immunization features of the app has not been widely studied. This study aimed to evaluate the use of PrimaKu on maternal attitudes toward immunization and complete basic immunizations status among Indonesian children aged 12 to 24 months. A cross-sectional research was conducted at a public health center in West Java Province, Indonesia, from August to December 2020. Convenience sampling was used to select the respondents. Data were collected using validated questionnaires and analyzed using binomial logistic regression. A total of 119 mothers were included. About 44.5% of children had a complete basic immunization status. Mothers who had a supportive attitude toward immunization were 3.58 times (95% CI 1.49-8.57, p 0.003) more likely to complete the basic immunization, and those who used the mobile app were 3.23 times (95% CI 1.18-8.87, p 0.034) more likely to complete the immunization. Using the PrimaKu mobile application could increase maternal attitudes toward immunization and complete basic immunization status. Therefore, public health nurses should provide comprehensive education and improve mothers' literacy to use the application.

Pro-equity immunization and health systems strengthening strategies in select Gavi-supported countries

BackgroundAchieving universal immunization coverage and reaching every child with life-saving vaccines will require the implementation of pro-equity immunization strategies, especially in poorer countries. Gavi-supported countries continue to implement and report strategies that aim to address implementation challenges and improve equity. This paper summarizes the first mapping of these strategies from country reports. MethodsThirteen Gavi-supported countries were purposively selected with emphasis on Gavi’s priority countries. Following a scoping of different documents submitted to Gavi by countries, 47 Gavi Joint Appraisals (JAs) for the period 2016–2019 from the 13 selected countries were included in the mapping. We used a consolidated framework synthesized from 16 different equity and health systems frameworks, which incorporated UNICEF’s coverage and equity assessment approach – an adaptation of the Tanahashi model. Using search terms, the mapping was conducted using a combination of manual search and the MAXQDA qualitative analysis tool. Pro-equity strategies meeting the inclusion criteria were identified and compiled in an Excel database, and then populated on a tableau visualization dashboard. ResultsIn total, 258 pro-equity strategies were implemented by the 13 sampled Gavi-supported countries between 2016 and 2019. The framework determinants of social norms, utilization, and management and coordination accounted for more than three-quarters of all pro-equity strategies implemented in these countries. The median number of strategies reported per country was 17. Afghanistan, Nigeria, and Uganda reported the highest number of strategies that we considered as pro-equity. ConclusionFindings from this mapping can be useful in addressing equity gaps, reaching partially immunized, and ‘zero-dose’ vaccinated children, and valuable resource for countries planning to implement pro-equity strategies, especially as immunization stakeholders reimagine immunization delivery in light of COVID-19, and as Gavi finalizes its fifth organizational strategy. Future efforts should seek to identify pro-equity strategies being implemented across additional countries, and to assess the extent to which these strategies have improved immunization coverage and equity.

Rethinking Strategies to Address Inequity in Immunization Services towards Achieving Universal Immunization Coverage (UIC) in Karachi, Pakistan

Karachi, the largest city in Pakistan, having high population growth and a complex health care environment, has highest density of unimmunized (zero dose) and under-immunized children. The main reasons of low immunization coverage in Karachi were lack of governance and accountability in a duplicative and fragmented health management structure, weak and inequitable immunization services, and lack of demand and trust among people for immunization services. The Expanded Programme on Immunization (EPI), Ministry of Health (MOH) in Sindh Province spearheaded a structured and collaborative process to develop strategies for addressing inequity in immunization services towards achieving Universal Immunization Coverage (UIC) in Karachi. The process included a situation analysis with gathering quantitative and qualitative information on the root causes of zero-dose and inequity of the immunization services. The strategies and interventions were developed with multi-layer input and feedback of the stakeholders and partners, and focusing primarily to address gaps in three program areas: governance, leadership and accountability; immunization service delivery; and building demand and trust among the people. The interventions were further prioritized for high-risk areas; identified based on maximum number zero-dose children, presence of large slum areas, measles outbreak and on-going circulation of wild poliovirus. Finally, costing for the Roadmap activities was done through consultation with partners and aligning domestic and external (donor) resources. In this paper, we have highlighted the unique process the Sindh Government undertook in collaboration with the stakeholders and partners to develop strategies and interventions for addressing inequity in urban immunization services in Karachi towards achieving Universal Immunization Coverage (UIC). Similar processes can be adapted, as a potential model, for developing strategies to achieve universal health coverage in the cities of Pakistan and in other countries.

The evaluation of immunization coverage under mission Indradhanush: a review

The government of India introduced mission Indradhanush (MI) to strengthen the routine immunization planning and delivery mechanism. It was launched on 25th December 2014 with an objective to achieve more than 90% full immunization (FI) coverage in the country. To evaluate universal immunization coverage, barriers encountered for not achieving the target and problem solving in removing the barriers. PubMed and google scholar were used to search the relevant articles. PRISMA tool was used for the review process and for in­clusion of potential articles. The studies conducted in Manipur, Madhya Pradesh, Bihar and south Kerala reported successful achievement of MI goal. The minimum FI percentage was 57% and the maximum was 96.4%. The most common reason for not achievement of the goal was lack of awareness, illiteracy, child illness, fear of adverse effects.

Using mobile immunization vans to cover under-served populations in hard-to-reach areas

Abstract Background In Pakistan, only 66% of children receive their basic vaccinations. However, the figure masks significant inequalities in vaccine coverage between urban and rural residences, slums and areas distantly located from EPI centers. Frequent outbreaks of vaccine-preventable diseases such as polio and measles, in urban cities like Karachi, signal the need for expanding vaccine services to underserved areas. In Apr'19, we introduced the Mobile Immunization Van initiative in Karachi in collaboration with EPI Sindh. Currently, two vans are deployed in hard-to-reach areas and slums to immunize under-2 children for routine vaccines. Methods Before the van visit, mobilization efforts are conducted in targeted areas to encourage caretakers to bring their child for vaccination. On the day of visit, the van is parked at a central location, and announcements are played on a loudspeaker to attract caregivers. All vaccinations are administered in the van, and entries are recorded in Government's Digital Immunization Registry along with GIS coordinates of immunized children. The data is then automatically transferred on to a web-dashboard for analysis and tracking. Results From Apr'19 to Jan'20, the vans have vaccinated 2,867 children, out of which 50% had never been immunized prior to the van visit. Of those who received their follow-up vaccines from the van, 80% were at least 4 weeks beyond from their vaccine due date. GIS analysis of van data confirmed that immunizations were conducted in slums, and areas distantly located from EPI centers. Moreover, compared to government outreach activity, proportion of BCG, Penta3 and Measles1 administrations in slums was higher through the vans by 5%, 6%, and 4% respectively. Conclusions The vans provide an opportunity for immunizing never-vaccinated children and children defaulting on their vaccine schedule, from the most vulnerable geographies, while simultaneously enrolling them in the Government's EPI Program for effective tracking. Key messages The mobile vans help achieve universal immunization coverage through provision of vaccine services in slum and rural hard-to-reach areas with limited access to government-provided services. The mobile vans help vaccinate and capture never-immunized children into the Government’s EPI records, reducing the number of children missed through routine services.

Understanding the full-immunization gap in districts of India: A geospatial approach

ObjectiveDespite the continuous global and national effort, India is far away from achieving universal immunization coverage. The primary objective of this paper is to find the spatial pattern and correlates of the full immunization coverage gap in the districts of India. Data and methodsWe used data from the fourth round of the National Family Health Survey (NFHS-4) conducted in 2015–16. Moran's I, univariate and bivariate Local Indicator of Spatial Association (LISA) analysis had been used to assess the spatial autocorrelation, clustering, and risk factors of the full immunization coverage gap in the districts of India. ResultsThe full immunization coverage gap among children has reduced by 33% over 2005–15. Around half of the children in 163 districts of India were deprived of full immunization. The spatial pattern of immunization coverage identified 99 districts as hot spots, whereas 111 as cold spots. Results from the bivariate LISA map signifies that the districts with higher coverage gap in full immunization also had higher deficit in pre-natal and post-natal care and skilled birth attendant. The spatial regression model revealed that female literacy, female-headed households, antenatal, and post-natal care have a significant association with full immunization coverage in India. ConclusionThe existence of clusters indicates the presence of unevenness in immunization coverage and has several implications that should be addressed for better health of the population. Efforts are to be made to ensure the universalization of education, along with accessible and affordable healthcare for all ensuring universal health coverage in India.

Effect of donor funding for immunization from Gavi and other development assistance channels on vaccine coverage: Evidence from 120 low and middle income recipient countries

Donor assistance for immunization has remained resilient with increased resource mobilization efforts in recent years to achieve current global coverage targets. As a result, more countries continue to introduce new vaccines while optimizing coverage for traditional vaccines. Gavi the Vaccine Alliance has been at the forefront of immunization support specifically among low and middle income countries, alongside other channels of development assistance which continue to play a vital role in immunization.Using available recipient country level data from 1996 to 2016, we estimate the impact of Gavi support for vaccines and health systems strengthening on vaccine coverage for 3 dose DPT, 3 dose pneumococcal conjugate vaccine, 3 dose pentavalent, 2 dose measles and 2 dose rotavirus vaccines. We investigate the same effects of total aid for immunization from other channels of development assistance. Standard time series cross sectional analysis methods are applied to investigate the effects of vaccine support controlling for country income, governance and population, with robustness tests implemented using different model specifications. Double counting was eliminated and results are presented in real 2017 US dollars.We found significant positive effects of aid particularly among the newer vaccines. Using 2016 country specific disbursements and coverage levels as baseline, we estimated that among recipient countries below the universal target, additional DAH per capita required to reach 90%, ranged from 0.01USD to 4.33USD for PCV, 0.03USD to 9.06USD for pentavalent vaccine and 0.01USD to 2.57USD for rotavirus vaccine. The estimated number of children vaccinated through 2016, attributable to Gavi support totaled 46.6million, 75.2million and 12.3million for PCV, pentavalent and rotavirus vaccines respectively.Our analysis suggests substantial success both from a historical and prospective perspective in the implementation of global immunization initiatives thus far. As more vaccines are rolled out and countries transition from donor aid, strategies for fiscal sustainability and efficiency need to be strengthened in order to achieve universal immunization coverage.

FACTORS AFFECTING CHILD IMMUNIZATION IN INDONESIA BASED ON IDHS 2012

Immunization programs have contributed to prevent the spread of infectious diseases and mortality among children. Although Indonesia has experienced remarkable progress in reducing child mortality, universal immunization coverage has not been achieved. This paper aims to identify important factors affecting the incidence of child immunization in Indonesia using the Indonesia Demographic and Health Survey (IDHS) of 2012. By probit regression, I estimated the child immunization acceptance and analyzed the impact of location of households at the provincial level which divide the location of respondents both inside and outside of Java. I found that mother’s level of education, household assets, and urbanity are important factors affecting the uptake of vaccinations. In addition, significant regional differences in vaccination incidence indicated that local resources serve as bottlenecks in vaccination. By encouraging government policies that improve women’s schooling, household assets, and regional support for health, immunization coverage could increase and even become more universal

Zindagi Mehfooz (Safe Life) Digital Immunization Registry: Leveraging Low-Cost Technology to Improve Immunization Coverage and Timeliness in Pakistan

Background: Despite free access to vaccines through the Expanded Program on Immunization (EPI) in Pakistan, only 54% of children receive all basic vaccinations. The global success of mobile health (mHealth) technologies, particularly, Digital immunization registries (DIRs), offers immense potential for comprehensive improvement in immunization programs. In 2012, we developed and piloted Zindagi Mehfooz (Safe Life; ZM) Digital Immunization Registry, an Android phone-based platform that enables vaccinators to digitally enroll and track the immunization status of their catchment population while allowing real-time access to data and easy generation of monitoring reports. Leveraging cutting edge mHealth technology, ZM includes features such as identification through quick response barcodes, interactive SMS reminders, decision support systems for routine/catch-up immunizations, real-time workforce tracking, predictive analytics for identifying high-risk children and customized report generation for monitoring. In 2017, ZM was scaled up, in collaboration with EPI, across the entire Sindh province and is currently being used by 1589 government vaccinators in 1296 basic health facilities. Objective: We evaluated the ZM Registry in terms of improvement in immunization coverage and timeliness. The primary outcome of interest was fully immunized child (FIC) coverage in children under 2 years of age, ie, a child who has received one dose of Bacillus-Calmette-Guerin (BCG), three doses each of OPV and Pentavalent immunizations, and one dose of Measles vaccine. The secondary outcomes of interest included the Pentavalent-3 coverage rate and dropout rate between BCG and Measles-1 vaccine. Methods: The provincial scale-up commenced in October 2017, and as of July 2018, over 700,000 children between 0-2 years have been enrolled in the Registry. At enrollment, the caretaker’s information, child’s bio-data, and immunization history are recorded and a unique Quick Response (QR)-code sticker is provided for identification. For the follow-up immunization visits, 3 SMS reminders are sent to parents for each vaccination. At the follow-up immunization, the child’s history is retrieved on the phone by scanning the QR-code, and the vaccination record is updated accordingly. Data exported from the ZM DIR records was used to calculate the coverage rate for children enrolled in the Registry and the outcomes were compared with the coverage estimates from the most recent demographic survey (MICS 2014) to determine the impact of the Registry. Results: Full immunization coverage of children (12-23 months) increased significantly from 35% as reported in MICS 2014 to 45% for children enrolled in ZM. Pentavalent-3 coverage of children enrolled in the Registry showed a 7% increase (from 53% reported in MICS 2014 data to 60% for children enrolled in the Registry). The dropout rate from BCG to Measles 1 vaccine was 24% as per the MICS 2014 figures and only 4% for children enrolled in the Registry. Conclusions: ZM demonstrates the potential of DIRs to improve immunization outcomes within low-resource settings by enabling better child tracking, efficient data monitoring and most importantly a higher retention rate for completing all the recommended immunizations. The evidence base generated through the evolution of ZM over the years has also facilitated global replication and can be leveraged to achieve universal immunization coverage in underserved regions.

Using Predictive Analytics to Identify Children at High Risk of Defaulting From a Routine Immunization Program: Feasibility Study.

BackgroundDespite the availability of free routine immunizations in low- and middle-income countries, many children are not completely vaccinated, vaccinated late for age, or drop out from the course of the immunization schedule. Without the technology to model and visualize risk of large datasets, vaccinators and policy makers are unable to identify target groups and individuals at high risk of dropping out; thus default rates remain high, preventing universal immunization coverage. Predictive analytics algorithm leverages artificial intelligence and uses statistical modeling, machine learning, and multidimensional data mining to accurately identify children who are most likely to delay or miss their follow-up immunization visits.ObjectiveThis study aimed to conduct feasibility testing and validation of a predictive analytics algorithm to identify the children who are likely to default on subsequent immunization visits for any vaccine included in the routine immunization schedule.MethodsThe algorithm was developed using 47,554 longitudinal immunization records, which were classified into the training and validation cohorts. Four machine learning models (random forest; recursive partitioning; support vector machines, SVMs; and C-forest) were used to generate the algorithm that predicts the likelihood of each child defaulting from the follow-up immunization visit. The following variables were used in the models as predictors of defaulting: gender of the child, language spoken at the child’s house, place of residence of the child (town or city), enrollment vaccine, timeliness of vaccination, enrolling staff (vaccinator or others), date of birth (accurate or estimated), and age group of the child. The models were encapsulated in the predictive engine, which identified the most appropriate method to use in a given case. Each of the models was assessed in terms of accuracy, precision (positive predictive value), sensitivity, specificity and negative predictive value, and area under the curve (AUC).ResultsOut of 11,889 cases in the validation dataset, the random forest model correctly predicted 8994 cases, yielding 94.9% sensitivity and 54.9% specificity. The C-forest model, SVMs, and recursive partitioning models improved prediction by achieving 352, 376, and 389 correctly predicted cases, respectively, above the predictions made by the random forest model. All models had a C-statistic of 0.750 or above, whereas the highest statistic (AUC 0.791, 95% CI 0.784-0.798) was observed in the recursive partitioning algorithm.ConclusionsThis feasibility study demonstrates that predictive analytics can accurately identify children who are at a higher risk for defaulting on follow-up immunization visits. Correct identification of potential defaulters opens a window for evidence-based targeted interventions in resource limited settings to achieve optimal immunization coverage and timeliness.

Five-year Experience of African Vaccination Week Implemented by the WHO Regional Office

The 5th edition of the African Vaccination Week (AVW) kicked off in Lusaka, Zambia, on 23 April 2016, the same day as did the 4th World Immunization Week (WIW), and vaccination week in other WHO regions. The theme was "Save lives, prevent disabilities, vaccinate!". The aim was to draw attention to the need to attain universal immunization coverage in the African Region by closing the immunization gap, while also celebrating the important polio eradication milestone reached in the African Region. Twenty-eight (59.6%) of the 47 countries in the African Region celebrated the AVW within the regionally set dates of 24th to 30th April 2015. However, given its flexibility, the celebration continued until September in 15 other countries in the Region. Three countries, namely Comoros, Gabon, and Cape Verde did not join the celebration for the 2015 edition of the AVW. Countries used the opportunity to introduce new vaccines into their routine immunization. Populations, hitherto unreached with basic health services were reached with needed services, such as vitamin A supplementation, deworming, and catch up immunization services. The programmes promoted awareness of the benefits of vaccines and the rights of communities to demand vaccines and immunization services to save lives and prevent disabilities. The number of participating countries rose steadily from 40 in 2011 to 43 and 46 countries in 2013 and 2014 respectively. The number ranged from one intervention integrated with AVW in 17 countries to 5 interventions integrated with the AVW in three countries. In 2015, 67.4% of the participating countries integrated other interventions with AVW activities.

Bottlenecks to universal immunization coverage in Africa

Bottlenecks to universal immunization coverage in Africa

Immunization coverage in an urban resettlement colony of district Gautam-Budh Nagar, Uttar Pradesh, India using WHO 30×7 cluster sampling technique

Background: Immunization is one of the most cost-effective interventions to prevent the suffering that comes from avoidable sickness, disability and death. In India, though immunization coverage has improved over the past few years, the country still accounts for the largest number of children who are not immunized i.e. 7.4 million. So, this study was taken up to assess the immunization coverage among children in District Gautam-Budh Nagar of Uttar Pradesh and to decipher the causes behind the partial immunization/non- immunization. Methods: A cross-sectional study was conducted during June-August 2015 in an urban resettlement colony of District Gautam-Budh Nagar in Uttar Pradesh among 210 children aged 12-23 months selected using WHO 30X7 cluster sampling technique. Results: A total of 210 children were covered, of which 72.9% children were fully immunized, 19.0% children were partially immunized, whereas, 8.1% children did not receive even a single dose of any vaccine, thus constituting a total of 27.1% children with partial/no immunization. On bi-variate analysis, significant associ­ation was observed between immunization status among children and caste (p=0.047), mother’s education (p=0.01), father’s education (p=0.000) and socio-economic status (p=0.003). On multi-variate analysis, however, only father’s educational status was found to be significantly associated. The major reasons for partial/non-immunization among children were Ignorance (80.7%) followed by unavailability of vaccines (7.0%). Conclusions: Immunization coverage found in the present study is still way short of the target of universal coverage. Therefore, health planners and policy makers in our country should develop a comprehensive strategy to achieve universal immunization coverage.

Using Predictive Analytics to Prevent Missed Opportunities and Achieve Higher Immunization Coverage and Timeliness

Background: Despite the availability of free routine immunizations in low- and middle-income countries (LMICs), many children are incompletely vaccinated, vaccinated late for age, or drop out over the course of the immunization schedule. According to WHO & UNICEF estimates, average BCG coverage in LMICs is 84% (range: 39-99%) while only 63% (range: 8-97%) children receive the last dose of measles. Without the technology to model and visualize risk on large datasets, vaccinators and policy-makers are unable to identify and target groups and individuals at high risk of dropping out. Thus, default rates remain high, preventing full universal immunization coverage. Predictive analytics algorithm leverages Artificial Intelligence (AI), and uses statistical modeling, machine learning, and multi-dimensional data mining to accurately identify children who are most likely to delay or miss their follow-up immunization visits. Objective: We conducted feasibility testing of a predictive analytics algorithm to identify which children are likely to delay or miss the follow-up vaccines through risk profiling of clients into high-, medium- and low-risk groups. We will validate the functionality and accuracy of the algorithm though verifying what percentage of clients classified as “high-risk” actually delay or miss the follow-up immunization visit. Methods: The algorithm was developed using existing immunization data from across Pakistan. There were 44,493 immunization records, collected from 21 immunization centers in over seven cities, used to train the system, which was then successfully piloted on 8,898 longitudinal patient records. After development, the predictive analytics module was incorporated in our existing digital immunization registry (DIR) and is currently deployed in 5 immunization centers in Karachi, Pakistan. Once the child is enrolled in the DIR, his immunization information is captured along with the salient socioeconomic and demographic characteristics. The predictive analytic technology uses data mining, statistical modeling, and pattern identification techniques to accurately forecast future immunization outcomes based on existing immunization and demographic data which are correlated to the child’s likelihood to miss or not show up on time for a vaccination visit. Results: At the time of development, the predictive power of the system was validated through training the system on 44,493 records collected from 21 immunization centers, and was then piloted on 8,898 records. Out of a total of 8,898, the Recursive Partition Model predicted that 3,352 (38%) children would default out of which 2,500 children did default (75%). Similarly, it predicted that 5,546 (62%) children would return for next vaccine, out of which 3,751 (67%) children did return. This indicates a 70% overall accuracy rate. Over time, through artificial intelligence, as more data is captured, the system will continue to self-learn from accumulated records, recognizing influential variables, self-selecting statistical models, and continually upgrading itself to achieve highest predictive accuracy. Results from feasibility testing in 5 immunization centers are currently pending. Conclusions: Predictive analytics is an unconventional approach to improving the timeliness of routine immunization and reducing missed opportunities; results of the pilot will provide strong evidence of the potential of predictive analytics to revolutionize immunization service delivery.

Investing in life saving vaccines to guarantee life of future generations in Africa

The World Health Organization’s Regional Offices for Africa and for the Eastern Mediterranean in conjunction with the African Union and the Government of Ethiopia hosted a ministerial conference on immunization in Africa from 24 to 25 February 2016 in Addis Ababa, Ethiopia under the theme “towards universal immunization coverage as a cornerstone for health and development in Africa”. The conference brought together African leaders – including health and finance ministers, and parliamentarians thus creating a powerful platform for governments to demonstrate their commitment to advancing universal access to immunization on the continent in line with the Global Vaccine Action Plan. The event also brought together advocates, technical experts, policymakers, partner agencies, donors and journalists to examine how best to drive forward immunization across Africa, ensuring every child has access to the vaccines they need. Key points highlighted throughout conference were: universal access to immunization is at the forefront of enabling Africa to reach its full potential – by improving health, driving economic growth and empowering future generations; it is one of the most cost-effective solutions in global health, with clear benefits for health and development; and immunization brings economic benefits too, reducing health care costs and increasing productivity. At the close of the conference, 46 African countries signed a historic ministerial declaration on “Universal Access to Immunization as a Cornerstone for Health and Development in Africa” signaling fierce determination among African leaders to secure the health and prosperity of their societies through immunization.