The study’s methodology is grounded in the idea that educational development is inherently multidimensional. Rather than relying on enrolment counts or literacy rates alone, the researchers treated infrastructure as an input, participation as a process, and institutional efficiency as an output, echoing the input–process–performance framework common in educational assessment. Every indicator was standardized using Z-score transformation so that variables measured in different units could be compared, and all indicators received equal weights, a choice the authors acknowledge may influence rankings. Districts were then classified into five categories, from Very Low to Very High, using standard deviation thresholds.

The headline finding is a pronounced spatial pattern. Imphal West topped the composite index with a score of 0.902, followed closely by Kakching at 0.888, with Imphal East, Thoubal, and Bishnupur rounding out the high performers. Every one of these districts lies in the central Imphal Valley, a compact alluvial plain that occupies barely a tenth of the state’s 22,327 square kilometres yet concentrates most of its population, roads, and institutions. At the other extreme, Pherzawl, a remote hill district, recorded a composite score of −1.126, the only district in the Very Low category, with hill districts Ukhrul, Kamjong, Noney, Tengnoupal, and Kangpokpi close behind.

Infrastructure emerged as the most unequal dimension of all. The Infrastructure Index showed a standard deviation of 0.698 and a range of 2.535, the widest spread among the indices examined, suggesting that uneven resource allocation is the single largest driver of educational inequality in the state. The details are striking. Nearly every school in Manipur has drinking water, and most have toilets and playgrounds, but only 35.19 percent have computer facilities, 36.63 percent have internet connectivity, and a mere 12.90 percent have functional smart classrooms. In Kakching, 88.30 percent of schools enjoy internet access, while in Kamjong the figure is just 6.79 percent. Pherzawl’s schools report library facilities in only 4.62 percent of cases, and electricity coverage there stands at 23.08 percent.

Participation patterns mirror this divide. Imphal West and Kakching posted the highest Participation Index values at 0.887 and 0.968 respectively, while Pherzawl, Kamjong, Kangpokpi, Tengnoupal, Senapati, and Ukhrul all recorded negative scores indicating weaker participation. Transition rates, which track whether students actually progress from one schooling stage to the next, reveal where continuity breaks down. Kamjong managed only a 51.5 percent transition from preparatory to middle level, and Pherzawl just 54.8 percent from middle to secondary, compared with perfect transitions in several valley districts. Children with Special Needs accounted for only 0.63 percent of total enrolment statewide, a figure the authors flag as a signal that inclusive education outreach remains limited across all districts.

Institutional efficiency data tell an equally sobering story. Pherzawl recorded dropout rates of 25.8 percent at the preparatory level and a startling 49.5 percent at the secondary level, meaning roughly half its students leave school before completing secondary education. Kamjong’s secondary dropout rate reached 20.2 percent. By contrast, Churachandpur, Imphal West, and Thoubal reported zero dropout at preparatory and middle levels. Performance Grading Index scores, a government assessment of institutional quality, ranged from 307.4 in Imphal West down to 191.1 in Noney. Notably, teacher availability is not the problem: pupil–teacher ratios ranged only from 10 to 20 students per teacher across districts, indicating that Manipur’s inefficiencies lie elsewhere, in retention, facilities, and institutional capacity.

The statistical heart of the paper lies in its correlation and regression analyses, which probe how the three dimensions interact. Participation, infrastructure, and institutional efficiency were strongly intercorrelated, with infrastructure and efficiency showing a coefficient of 0.83. Secondary dropout rates correlated negatively with every index, most strongly with institutional efficiency at −0.76, while middle-to-secondary transition rates and PGI scores correlated positively with all three dimensions. In a multiple regression model explaining about 70.4 percent of the variation in institutional efficiency, infrastructure was the only statistically significant predictor, with a coefficient of 0.515 and a p-value of 0.019. Participation, though positive in direction, did not reach significance. The authors are careful to stress that these are associations, not causal proof, since the cross-sectional design cannot rule out confounding influences such as broader regional development.

That caveat matters, because the study’s conceptual framing draws on Amartya Sen’s Capability Approach, which views infrastructure as an enabling condition that expands opportunities rather than a mechanical determinant of outcomes. The authors note that districts with better infrastructure may simply enjoy wider advantages, including greater public investment, stronger administrative capacity, and improved connectivity. They also acknowledge limitations: the analysis uses a single year of administrative data, which may contain reporting inconsistencies, and district-level aggregation risks ecological fallacy, meaning patterns observed across districts may not hold for individual students or schools. Factors such as teacher quality, household poverty, and governance quality were not directly measured.

Even so, the policy implications are pointed. The authors argue that uniform state-wide strategies will not close a gap this structurally embedded, and they call for geographically differentiated interventions. In hill districts such as Pherzawl, Kamjong, and Noney, they recommend prioritizing reliable electricity, internet connectivity, digital learning facilities, libraries, and transport access, with resource allocation formulas that weight remoteness and infrastructural deprivation alongside population size. Teacher deployment policies, including hardship allowances and location-specific recruitment, feature in their recommendations, as does stronger engagement of School Management Committees and parent groups. As India pushes toward the inclusive education goals of SDG-4 and implements the National Education Policy 2020, the study offers a template for diagnosing exactly where, and in what dimension, the system is failing, and a reminder that enrolment drives alone cannot substitute for the classrooms, connections, and institutional muscle that keep children learning.

Subject of Research: Spatial disparities in educational development across the districts of Manipur, India

Article Title: Spatial disparities in educational development across districts of Manipur based on participation infrastructure and institutional efficiency

Article References: Meitei, K. M., & Das, B. (2026). Spatial disparities in educational development across districts of Manipur based on participation infrastructure and institutional efficiency. Discover Global Society, 4(1), Article 262. https://doi.org/10.1007/s44282-026-00621-1

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00621-1

Keywords: educational development, Manipur, spatial disparity, composite index, school infrastructure, institutional efficiency, UDISE+, regional inequality, dropout rates, hill districts, valley districts, education policy

The study’s design gives its findings unusual weight for a subnational survey. Rather than relying on maternal recall alone, the team used interviewer-administered questionnaires combined with physical inspection of immunization cards, the gold-standard documentary evidence of each dose a child has received. Children were enrolled through multistage sampling, a technique that first selects larger administrative units and then narrows down to households, giving every eligible child in the district a known chance of inclusion. Slightly more than half of the recruited children were aged twelve to twenty-three months, the age window in which the routine schedule demands the densest series of visits, and 51.3 percent were female. Because the sampling frame was anchored in communities rather than clinics, the survey captured children who never reach health facilities, a population that facility-based studies systematically miss.

Timeliness, the second pillar of the analysis, proved as troubling as coverage itself. A vaccine administered late leaves a child exposed during the interval when protection should already be in place, so immunization programs track not only whether doses are given but whether they arrive on schedule. In this district, timeliness varied sharply by vaccine type, ranging from 40.8 percent for the birth dose of hepatitis B vaccine, known as HBV0, to 65.2 percent for the first dose of oral polio vaccine, OPV1. The pattern is telling: OPV1 is often delivered through mass campaigns and at the first postnatal contact, while the hepatitis B birth dose depends on a facility delivery and a functioning cold chain on the very day of birth. Where the schedule depends on early, facility-linked contact, the system faltered most.

Dropout rates, the third metric, quantify the attrition between a child’s first and last scheduled doses, and they expose where families disengage from the program. The dropout from BCG, given at birth, to the measles vaccine, given near nine months, was 16.1 percent. For the pentavalent vaccine series, which protects against diphtheria, pertussis, tetanus, hepatitis B, and Haemophilus influenzae type b, dropout from the first to the third dose was 10.3 percent, while dropout from pentavalent dose one to measles reached 16.5 percent. These figures indicate that roughly one child in six who starts the schedule in Akpabuyo does not finish it, a leak in the pipeline that no amount of initial mobilization alone can fix.

To understand which children were most likely to be fully immunized, the researchers employed a two-level mixed-effects logistic regression model, a statistical approach that accounts for the fact that children living in the same community share facilities, vaccine supplies, and social norms, and therefore do not behave as independent observations. The model treated children as nested within communities and reported adjusted odds ratios with 95 percent confidence intervals. As sensitivity analyses, the team compared the results against simpler ordinary binary logistic regression and against models adjusting for ward-level clustering, a robustness check that guards against conclusions driven by the choice of statistical technique alone.

The predictors that emerged paint a coherent picture of advantage and access. Children from upper socioeconomic status households had 1.81 times the odds of full immunization compared with their less advantaged peers, and each increment in family income raised the odds by 6 percent. Delivery attended by a healthcare professional increased the odds by 1.7 times, and maternal attendance at postnatal care raised them 1.72-fold, both reflecting the fact that the health system’s first contact with a newborn is also its best chance to launch the vaccination schedule. Caregivers who reported that the timing of immunization sessions was convenient for them had 1.82 times the odds of completing their child’s schedule, suggesting that service hours themselves are a modifiable determinant, not a fixed constraint.

On the other side of the ledger, several factors significantly reduced the likelihood of full immunization. Each additional month of child age was associated with slightly lower odds, an effect consistent with the accumulating risk of falling behind as the schedule stretches across months. Living more than two kilometers from a health facility cut the odds to 0.66, a distance penalty that in rural terrain with poor roads can translate into hours of travel. Most striking were the supply-side failures: children whose caregivers reported ever missing a vaccination because no vaccine was available had only 0.31 times the odds of full immunization, and those who had missed a session because no vaccinator was present had just 0.20 times the odds. These are not failures of parental motivation but failures of the delivery system itself.

The authors conclude that full immunization coverage and timeliness in the district were low, with high dropout rates recorded, and they identify a set of concrete remedies: strengthening the vaccine supply chain, ensuring health worker availability in facilities, encouraging delivery by skilled professionals, and reinforcing caregiver counselling after delivery. Each recommendation maps directly onto a predictor in the regression model. Stock-outs and absent vaccinators are logistical problems with logistical solutions, while the strong effect of facility delivery and postnatal care suggests that linking immunization to the perinatal cascade of services could capture children at the moment families are already in contact with the health system.

The broader significance of the study lies in its demonstration that rural immunization gaps are not monolithic. Coverage, timeliness, and dropout are distinct failure modes that require distinct interventions, and a district can perform adequately on one while failing on another. By measuring all three simultaneously in a large, card-verified, community-representative sample, and by modeling community-level clustering explicitly, the researchers have produced a template for the kind of granular diagnosis that national averages conceal. For the children of Akpabuyo, the message is sobering: more than half remain incompletely protected. But for program planners across Nigeria and similar settings, the study offers a precise map of where the pipeline leaks, from the cold chain at birth to the long walk to the nearest clinic, and a reminder that every dose delivered on time is a child shielded from diseases that vaccines have long since made preventable.

Subject of Research: Full immunization coverage, timeliness, and dropout rates among children aged 12–59 months in a rural Nigerian district

Article Title: Full immunization coverage, timeliness and dropout rates among children aged 12–59 months: a community-based cross-sectional study in a rural subnational district in Nigeria

Article References: Otu, V. M., Fajola, A. O., Ikobah, J. M., Ita-Lincoln, F., Bassey, G. E., & Ekanem, E. E. (2026). Full immunization coverage, timeliness and dropout rates among children aged 12–59 months: a community-based cross-sectional study in a rural subnational district in Nigeria. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14556-0

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14556-0

Keywords: immunization, vaccination coverage, Nigeria, child health, dropout rates, vaccine timeliness, rural health, public health, cross-sectional study, vaccine-preventable diseases, supply chain, maternal and child health