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EXPLORING GEOGRAPHICAL VARIANCE OF COMPLETE IMMUNIZATION COVERAGE IN INDIA: A DISTRICT-LEVEL SPATIAL MODELLING APPROACH
Abstract
Background
India has been significantly progressed in full immunization care over the last few decades. Existing literature has not been unaddressed the potential spatial variations in relationships between full immunization coverage and its influence on socio-economic factors.
Aims
This study aims to explore place-specific spatially varying relationships between district-level complete immunization coverage and socio-economic and healthcare factors in India using the 4th wave of the National Family Health Survey, 2015–16.
Methods
Univariate Moran’s I and LISA maps were used to confirm the spatial autocorrelation and geographical hotspots of the district-level full immunization coverage. Multivariate Ordinary Least Squares and Geographically Weighted Regression models were employed to examine spatial relationships and to decrypt location-based district-level analysis.
Results
The prevalence of full immunization care was 62% as per the national figure. The GWR results revealed that the relationships between outcome and set of cofactors were significantly place-specific and spatially clustering in terms of their respective magnitude, direction, and differences in due to local characteristics across India. In terms of model performance and prediction accuracy, the GWR model was performing better over OLS estimates through comparisons of R2 and Akaike Information Criterion (AICC) in both models.
Conclusions
Thus, the findings suggest that the local GWR model has the potential to explain complexities in place-specific variations that could be ignored by OLS on the local causes of immunization coverage. Highlighting the socio-economic importance of spatial dependence and heterogeneity, appropriate intervention should be devised to safeguard the child from vaccine-preventable diseases reduce the geographical heterogeneity of full immunization coverage across India.