Combining cluster surveys to estimate vaccination coverage: Experiences from Nigeria's multiple indicator cluster survey / national immunization coverage survey (MICS/NICS), 2016-17.
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SUBMITTER: Rhoda DA
PROVIDER: S-EPMC7450266 | biostudies-literature | 2020 Sep
REPOSITORIES: biostudies-literature
Publications
Combining cluster surveys to estimate vaccination coverage: Experiences from Nigeria's multiple indicator cluster survey / national immunization coverage survey (MICS/NICS), 2016-17.
Rhoda Dale A DA Wagai John Ndegwa JN Beshanski-Pedersen Bo Robert BR Yusafari Yusuf Y Sequeira Jenny J Hayford Kyla K Brown David W DW Danovaro-Holliday M Carolina MC Braka Fiona F Ali Daniel D Shuaib Faisal F Okposen Bassey B Nwaze Eric E Olarewaju Isiaka I Adeniran Adeyemi A Kassogue Modibo M Jobin Denis D Ryman Tove K TK
Vaccine 20200711 39
In 2015 immunization stakeholders in Nigeria were proceeding with plans that would have fielded two nationally representative surveys to estimate vaccination coverage at the same time. Rather than duplicate efforts and generate either conflicting or redundant results, the stakeholders collaborated to conduct a combined Multiple Indicator Cluster Survey (MICS) / National Immunization Coverage Survey (NICS) with MICS focusing on core sampling clusters and NICS adding supplementary clusters in 20 s ...[more]
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Project description:BackgroundInfant immunization coverage worldwide has plateaued at about 85%. Using existing survey data to conduct analyses beyond estimating coverage may help immunization programmes better tailor strategies to reach un- and under-immunized children. The Demographic and Health Survey (DHS) and the Multiple Indicators Cluster Survey (MICS), routinely conducted in low and middle-income countries (LMICs), collect immunization data, yet vaccination coverage is often the only indicator reported and used. We conducted a review of published immunization-related analyses to characterize and quantify immunization secondary analyses done using DHS and MICS databases.MethodsWe conducted a systematic search of the literature, of immunization-related secondary analyses from DHS or MICS published between 2006 and August 2018. We searched 15 electronic databases without language restrictions. For the articles included, relevant information was extracted and analyzed to summarize the characteristics of immunization-related secondary analyses. Results are presented following the PRISMA guidelines.ResultsAmong 1411 papers identified, 115 met our eligibility criteria; additionally, one article was supplemented by the Pan American Health Organization. The majority were published since 2012 (77.6%), and most (68.9%) had a first or corresponding author affiliated with institutions in high-income countries (as opposed to LMICs where these surveys are conducted). The median delay between survey implementation and publication of the secondary analysis was 5.4 years, with papers with authors affiliated to institutions in LMIC having a longer median publication delay (p < 0.001). Over 80% of the published analyses looked at factors associated with a specific vaccine or with full immunization. Quality proxies, such as reporting percent of immunization data from cards vs recall; occurrence and handling of missing data; whether survey analyses were weighted; and listing of potential biases or limitations of the original survey or analyses, were infrequently mentioned.ConclusionOur review suggests that more needs to be done to increase the increase the utilization of existing DHS and MICS datasets and improve the quality of the analyses to inform immunization programmes. This would include increasing the proportion of analyses done in LMICs, reducing the time lag between survey implementation and publication of additional analyses, and including more qualitative information about the survey in the publications to better interpret the results.
| S-EPMC7880859 | biostudies-literature
Project description:ObjectivesWe analysed predictors of health insurance enrolment in Nepal, measured wealth-related inequality and decomposed inequality into its contributing factors.DesignCross-sectional study.SettingWe used nationally representative data based on Nepal Multiple Indicator Cluster Survey 2019. Out of 10 958 households included in this study, 6.95% households were enroled in at least one health insurance scheme.Primary outcomemeasures health insurance (of any type) enrolment.ResultsHouseholds were more likely to have health insurance membership when household head have higher secondary education or above compared with households without formal education (adjusted OR 1.87; 95% CI: 1.32 to 2.64)). Households with mass media exposure were nearly three times more likely to get enroled into the schemes compared with their counterparts (adjusted OR 2.96; 95% CI 2.03 to 4.31). Hindus had greater odds of being enroled (adjusted OR 1.82; 95% CI 1.20 to 2.77) compared with non-Hindus. Dalits were less likely to get enroled compared with Brahmin, Chhetri and Madhesi (adjusted OR 0.66; 95% CI 0.47 to 0.94). Households from province 2, Bagmati and Sudurpaschim were less likely to have membership compared with households from province 1. Households from Richer and Richest wealth quintiles were more than two times more likely to have health insurance membership compared with households from the poorest wealth quintile. A positive concentration index 0.25 (95% CI 0.21 to 0.30; p<0.001) indicated disproportionately higher health insurance enrolment among wealthy households.ConclusionsEducation of household head, exposure to mass media, religious and ethnic background, geographical location (province) and wealth status were key predictors of health insurance enrolment in Nepal. There was a significant wealth-related inequality in health insurance affiliation. The study recommends regular monitoring of inequality in health insurance enrolment across demographic and socioeconomic groups to ensure progress towards Universal Health Coverage.
| S-EPMC8628343 | biostudies-literature
Project description:BackgroundInequality in maternal healthcare use is a major concern for low-and middle-income countries (LMICs). Maternal health indicators at the national level have markedly improved in the last couple of decades in Nepal. However, the progress is not uniform across different population sub-groups. This study aims to identify the determinants of institutional delivery, measure wealth-related inequality, and examine the key components that explain the inequality.MethodsMost recent nationally representative Multiple Indicator Cluster Survey (MICS) 2019 was used to extract data about married women (15-49 years) with a live birth within two years preceding the survey. Logistic regression models were employed to assess the association of independent variables with the institutional delivery. The concentration curve (CC) and concentration index (CIX) were used to analyze the inequality in institutional delivery. Wealth index scores were used as a socio-economic variable to rank households. Decomposition was performed to identify the determinants that explain socio-economic inequality.ResultsThe socio-economic status of households to which women belong was a significant predictor of institutional delivery, along with age, parity, four or more ANC visits, education status of women, area of residence, sex of household head, religious belief, and province. The concentration curve was below the line of equality and the relative concentration index (CIX) was 0.097 (p < 0.001), meaning the institutional delivery was disproportionately higher among women from wealthy groups. The decomposition analysis showed the following variables as the most significant contributor to the inequality: wealth status of women (53.20%), education of women (17.02%), residence (8.64%) and ANC visit (6.84%).ConclusionsTo reduce the existing socio-economic inequality in institutional delivery, health policies and strategies should focus more on poorest and poor quintiles of the population. The strategies should also focus on raising the education level of women especially from the rural and relatively backward province (Province 2). Increasing antenatal care (ANC) coverage through outreach campaigns is likely to increase facility-based delivery and decrease inequality. Monitoring of healthcare indicators at different sub-population levels (for example wealth, residence, province) is key to ensure equitable improvement in health status and achieve universal health coverage (UHC).
| S-EPMC8665495 | biostudies-literature
Project description:UNLABELLED: BACKGROUND: Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required. METHODS: We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. RESULTS: VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. CONCLUSIONS: Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.
| S-EPMC3502089 | biostudies-other
Project description:OBJECTIVE:Demographic and health surveys, immunization coverage surveys and administrative data often divergently estimate vaccination coverage, which hinders pinpointing districts where immunization services require strengthening. We assayed vaccination coverage in three regions in Ethiopia by coverage surveys and linked serosurveys. METHODS:Households with children aged 12-23 (N = 300) or 6-8 months (N = 100) in each of three districts (woredas) were randomly selected for immunization coverage surveys (inspection of vaccination cards and immunization clinic records and maternal recall) and linked serosurveys. IgG-ELISA serologic biomarkers included tetanus antitoxin ? 0.15 IU/ml in toddlers (receipt of tetanus toxoid) and Haemophilus influenzae type b (Hib) anti-capsular titers ? 1.0 mcg/ml in infants (timely receipt of Hib vaccine). FINDINGS:Coverage surveys enrolled 1,181 children across three woredas; 1,023 (87%) also enrolled in linked serosurveys. Administrative data over-estimated coverage compared to surveys, while maternal recall was unreliable. Serologic biomarkers documented a hierarchy among the districts. Biomarker measurement in infants provided insight on timeliness of vaccination not deducible from toddler results. CONCLUSION:Neither administrative projections, vaccination card or EPI register inspections, nor parental recall, substitute for objective serological biomarker measurement. Including infants in serosurveys informs on vaccination timeliness.
| S-EPMC4774907 | biostudies-literature
Project description:Vaccination coverage in Zhejiang province, east China, is evaluated through repeated coverage surveys. The Zhejiang provincial immunization information system (ZJIIS) was established in 2004 with links to all immunization clinics. ZJIIS has become an alternative to quickly assess the vaccination coverage. To assess the current completeness and accuracy on the vaccination coverage derived from ZJIIS, we compared the estimates from ZJIIS with the estimates from the most recent provincial coverage survey in 2014, which combined interview data with verified data from ZJIIS. Of the enrolled 2772 children in the 2014 provincial survey, the proportions of children with vaccination cards and registered in ZJIIS were 94.0% and 87.4%, respectively. Coverage estimates from ZJIIS were systematically higher than the corresponding estimates obtained through the survey, with a mean difference of 4.5%. Of the vaccination doses registered in ZJIIS, 16.7% differed from the date recorded in the corresponding vaccination cards. Under-registration in ZJIIS significantly influenced the coverage estimates derived from ZJIIS. Therefore, periodic coverage surveys currently provide more complete and reliable results than the estimates based on ZJIIS alone. However, further improvement of completeness and accuracy of ZJIIS will likely allow more reliable and timely estimates in future.
| S-EPMC5551196 | biostudies-other
Project description:BackgroundChildhood pneumonia is the single largest infectious cause of death in children under five worldwide. Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) provide health information on care sought for sick children in resource poor settings. Despite not being primarily designed to identify childhood pneumonia, there are concerns that reported episodes of "symptoms of acute respiratory infection" in DHS and MICS are often interpreted by other groups as a "proxy" for childhood pneumonia. Using DHS5 and MICS5 survey tools, this study aimed to assess how accurately caregivers report of "symptoms of acute respiratory infection" reflect pneumonia episodes and antibiotic use in children under five.MethodsChildren aged 0 to 59 months presenting with cough and/or difficult breathing were recruited from four study hospitals in Ibadan, Nigeria from August 2015 to March 2017. Children were assessed using World Health Organization (WHO) standard criteria by study physicians to identify whether they had pneumonia. Three hundred and two matched children in each category of 'pneumonia' and "no pneumonia" were followed up at home, either two or eight weeks later, using questions from DHS5 and MICS5 surveys to assess the accuracy of caregiver recall of pneumonia.ResultsThe specificity of DHS5 and MICS5 questions for identifying childhood pneumonia were 87.4 (95% confidence interval (CI)?=?83.1-91.0) and 86.1 (95% CI?=?81.7-89.8) respectively and the sensitivity of questions were 37.1 (95% CI?=?31.6-42.8) and 37.1 (95% CI?=?31.6-42.8). Correct recall of antibiotic treatment was poor (kappa statistic?=?0.064) but improved with the use of medicine pill boards (kappa statistic?=?0.235).ConclusionsDHS5 and MICS5 survey questions are not designed to identify childhood pneumonia and this study confirms that they do not accurately discern episodes of childhood pneumonia from cough/cold in children under five. The proportion of pneumonia episodes appropriately treated with antibiotics cannot be accurately assessed using current DHS and MICS surveys. If these results are used to guide programmatic decisions, it is likely to encourage overuse and inappropriate prescribing of antibiotics for episodes of cough/cold. International agencies who continue to use these household data to monitor the proportion of children with pneumonia who receive antibiotic treatment should be discouraged from doing this as these data are likely to mislead national and global programmes. Medicine pill boards are used in a number of DHS surveys and should be promoted for wider use in national population surveys to improve the accuracy of antibiotic recall.
| S-EPMC6150611 | biostudies-other
Project description:Calls have been made for improved measurement of coverage for maternal, newborn and child health interventions. Recently, methods linking household and health facility surveys have been used to improve estimation of intervention coverage. However, linking methods rely the availability of household and health facility surveys which are temporally matched. Because nationally representative health facility assessments are not yet routinely conducted in many low and middle income countries, estimates of intervention coverage based on linking methods can be produced for only a subset of countries. Estimates of intervention coverage are a critical input for modelling the health impact of intervention scale-up in the Lives Saved Tool (LiST). The purpose of this study was to develop a data-driven approach to estimate coverage for a subset of antenatal care interventions modeled in LiST.Using a five-step process, estimates of population level coverage for syphilis detection and treatment, case management of diabetes, malaria infection, hypertensive disorders, and pre-eclampsia, were computed by linking household and health facility surveys. Based on data characterizing antenatal care and estimates of coverage derived from the linking approach, predictive models for intervention coverage were developed. Updated estimates of coverage based on the predictive models were compared, first with current default proxies, then with estimates based on the linking approach. Model fit and accuracy were assessed using three measures: the coefficient of determination, Pearson's correlation coefficient, and the root mean square error (RMSE).The ability to predict intervention coverage was fairly accurate across all interventions considered. Predictive models accounted for 20-63% of the variance in intervention coverages, and correlation coefficients ranged from 0.5 to 0.83. The predictive model used to estimate coverage of management of pre-eclampsia performed relatively better (RMSE = 0.11) than the model estimating coverage of diabetes case management (RMSE = 0.19).The new approach to estimate coverage represents an improvement over current default proxies in LiST. As the availability of reliable coverage data improves, impact estimates generated by LiST will improve. This study underscores the need for continued efforts to improve coverage measurement, while bringing to the fore the importance of health facility assessments as complementary data sources.
| S-EPMC5688485 | biostudies-other
Project description:BackgroundIn 1986, the Government of Mali launched its Expanded Program on Immunization (EPI) with the goal of vaccinating, within five years, 80% of all children under the age of five against six target diseases: diphtheria, tetanus, pertussis, poliomyelitis, tuberculosis, and measles. The Demographic and Health Survey carried out in 2001 revealed that, in Kita Circle, in the Kayes region, only 13% of children aged 12 to 23 months had received all the EPI vaccinations. A priority program was implemented in 2003 by the Regional Health Department in Kayes to improve EPI immunization coverage in this area.MethodsA cross-sectional survey using Henderson's method (following the method used by the Demographic and Health Surveys) was carried out in July 2006 to determine the level of vaccination coverage among children aged 12 to 23 months in Kita Circle, after implementation of the priority program. Both vaccination cards and mothers' declarations (in cases where the mother cannot make the declaration, it is made by the person responsible for the child) were used to determine coverage.ResultsAccording to the vaccination cards, 59.9% [CI 95% (54.7-64.8)] of the children were fully vaccinated, while according to the mothers' declarations the rate was 74.1% [CI 95% (69.3-78.4)]. The drop-out rate between DTCP1 and DTCP3 was 5.5%, according to the vaccination cards. The rate of immunization coverage was higher among children whose mothers had received the anti-tetanus vaccine [OR = 2.1, CI 95% (1.44-3.28)]. However, our study found no difference associated with parents' knowledge about EPI diseases, distance from the health centre, or socio-economic status. Lack of information was one reason given for children not being vaccinated against the six EPI diseases.ConclusionThree years after the implementation of the priority program (which included decentralization, the active search for missing children, and deployment of health personnel, material and financial resources), our evaluation of the vaccination coverage rates shows that there is improvement in the EPI immunization coverage rate in Kita Circle. The design of our study did not, however, enable us to determine the extent to which different aspects of the program contributed to this increase in coverage. Efforts should nevertheless be continued, in order to reach the goal of 80% immunization coverage. ABSTRACT IN FRENCH: See the full article online for a translation of this abstract in French.
| S-EPMC3226232 | biostudies-literature
Project description:BackgroundPopulation-based measures of intervention coverage are used in low- and middle-income countries for program planning, prioritization, and evaluation. There is increased interest in effective coverage, which integrates information about service quality or health outcomes. Approaches proposed for quality-adjusted effective coverage include linking data on need and service contact from population-based surveys with data on service quality from health facility surveys. However, there is limited evidence about the validity of different linking methods for effective coverage estimation.MethodsWe collaborated with the 2016 Côte d'Ivoire Multiple Indicator Cluster Survey (MICS) to link data from a health provider assessment to care-seeking data collected by the MICS in the Savanes region of Côte d'Ivoire. The provider assessment was conducted in a census of public and non-public health facilities and pharmacies in Savanes in May-June 2016. We also included community health workers managing sick children who served the clusters sampled for the MICS. The provider assessment collected information on structural and process quality for antenatal care, delivery and immediate newborn care, postnatal care, and sick child care. We linked the MICS and provider data using exact-match and ecological linking methods, including aggregate linking and geolinking methods. We compared the results obtained from exact-match and ecological methods.ResultsWe linked 731 of 786 care-seeking episodes (93%) from the MICS to a structural quality score for the provider named by the respondent. Effective coverage estimates computed using exact-match methods were 13%-63% lower than the care-seeking estimates from the MICS. Absolute differences between exact match and ecological linking methods were ±7 percentage points for all ecological methods. Incorporating adjustments for provider category and weighting by service-specific utilization into the ecological methods generally resulted in better agreement between ecological and exact match estimates.ConclusionsEcological linking may be a feasible and valid approach for estimating quality-adjusted effective coverage when a census of providers is used. Adjusting for provider type and caseload may improve agreement with exact match results. There remain methodological questions to be addressed to develop guidance on using linking methods for estimating quality-adjusted effective coverage, including the effect of facility sampling and time displacement.
| S-EPMC6211616 | biostudies-literature