Spatial patterns and multilevel analysis of factors associated with paediatric tuberculosis in India

Abstract

BackgroundTuberculosis (TB) is a serious global health problem that remains as leading cause of high mortality and morbidity in children. Despite India with a high global tuberculosis burden, very few studies have specifically addressed the problem of TB among children, a vulnerable group where delayed diagnosis aggravates the morbidity. MethodsIdentifying the hotspots with high risk of Paediatric TB by employing a localized clustering method can help in developing regional policies for eliminating TB. Factors specified at various levels must be taken into account in studies of health aetiology and their practical applications for disease control. Multilevel analysis is a viable analytic technique for including components identified at many levels in an epidemiologic study and the interindividual variances can be inferred using multilevel analysis. ResultsIn this study, the incidence of tuberculosis pertaining to individual-level attributes are elucidated at district and state level through a multilevel model using the information from National Family Health Survey-5, carried out in 2019–20 comprising 636,699 households over 28 states and 8 union territories of India and the spatial method has detected 62 hotspots. ConclusionThe model expresses a nested structure with districts and states having significant contribution in the variation of paediatric TB and the autocorrelation pattern exhibited by the hotspots emphasises the need for targeted TB elimination programs.