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Spatial patterns and multilevel analysis of factors associated with paediatric tuberculosis in India
Mohan Balakrishnan1, Varadharajan R1
1Department of Mathematics, SRM Institute of Science and Technology, Kattankulathur-603203, Tamil Nadu, India.
Insights
This study identified 62 high-risk pediatric tuberculosis hotspots in India using a multilevel model. Targeted regional elimination programs are crucial for this vulnerable population.
Area of Science:
- Public Health
- Epidemiology
- Spatial Analysis
Background:
- Pediatric tuberculosis (TB) is a significant cause of child mortality and morbidity globally, particularly in India.
- Delayed diagnosis in children exacerbates TB-related health issues.
- Limited research specifically addresses pediatric TB in high-burden countries like India.
Purpose of the Study:
- To identify high-risk areas for pediatric TB in India.
- To inform the development of targeted regional policies for TB elimination.
- To analyze individual-level factors contributing to pediatric TB incidence.
Main Methods:
- Utilized a localized clustering method to detect pediatric TB hotspots.
- Employed multilevel analysis to account for factors at various levels (individual, district, state).
- Analyzed data from the National Family Health Survey-5 (2019-20) covering 636,699 households across India.
Main Results:
- Identified 62 distinct hotspots for pediatric TB.
- The multilevel model elucidated individual-level attributes associated with TB incidence at district and state levels.
- Spatial analysis confirmed the presence of significant autocorrelation in identified hotspots.
Conclusions:
- District and state levels significantly contribute to the variation in pediatric TB incidence.
- The identified hotspots and their spatial patterns underscore the necessity for focused TB elimination strategies.
- Findings support the implementation of data-driven, geographically targeted interventions for pediatric TB control.
Background:
Tuberculosis (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.
Methods:
Identifying 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.
Results:
In 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.
Conclusion:
The 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.
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