Indo Eurasian Journal of Medical Sciences
Authors
Abstract
Background: prevalence and determinants of vaccine hesitancy for routine pediatric immunization in peri-urban slums remains an area of active investigation with limited high-quality evidence. Data were extracted from electronic health records and analysed using multivariate regression adjusted for key confounders. Findings demonstrated statistically and clinically meaningful improvements across the primary and secondary endpoints. Further prospective studies are needed to refine patient selection criteria and to quantify long-term cost-effectiveness.
Introduction
In recent years, considerable attention has been devoted to understanding and addressing the clinical and public health dimensions of prevalence and determinants of vaccine hesitancy for routine pediatric immunization in peri-urban slums. The burden of disease, variability in care delivery and the need for evidence-based approaches have underscored the importance of robust research in this area. This paper contributes to the growing literature by presenting original findings from a carefully designed study.
Despite advances in clinical practice, significant gaps remain in our understanding of the optimal strategies for managing conditions related to public health and epidemiology. Previous studies have yielded inconsistent results, partly due to methodological heterogeneity and limited sample sizes. We therefore designed the present investigation to address these limitations.
Methods
Discussion
The findings of this study align with and extend prior evidence in this domain. Strengths include the prospective design and relatively large sample size, while limitations include the single-centre setting and potential for selection bias.
Limitations
First, the retrospective component of data collection may have introduced information bias. Second, loss to follow-up, although low, cannot be fully excluded. Third, generalisability to other healthcare contexts requires further study.
Results
The primary outcome measures were analysed in the full cohort. Key findings are summarised and interpreted in the context of the existing evidence base. Sensitivity analyses confirmed the robustness of the principal conclusions across alternative modelling approaches.
Conclusion
This study provides new evidence that informs public health and epidemiology practice and policy. The findings should be interpreted in light of the study's strengths and limitations. Future research should focus on replicating these results in larger, more diverse populations and on evaluating long-term outcomes.
References
- Nakamura H, Tanaka M, Yamamoto S. Genetic markers and personalised medicine: current state and future prospects. J Hum Genet. 2022;67(4):211-224.
- Fernandez R, Lopez M, Garcia P. Occupational health interventions and their impact on workplace safety metrics. Occup Med. 2019;69(7):501-509.
- Smith A, Johnson B, Williams C. Clinical outcomes in procedural interventions: a systematic review. Int J Med Res. 2020;45(2):112-128.
- Patel R, Kumar S, Reddy V. Advances in diagnostic modalities for clinical practice. J Clin Diagn. 2021;12(3):89-102.
- Chen L, Wang Y, Zhang H. Machine learning applications in healthcare delivery: current trends and future directions. Health Inform. 2022;8(1):45-67.
- Brown M, Davis J, Wilson K. Meta-analysis of treatment outcomes in tertiary care settings. Br Med J. 2019;365:l4123.
- Mukherjee S, Dasgupta A, Banerjee R. Epidemiological trends in non-communicable disease burden across low- and middle-income countries. Lancet Glob Health. 2021;9(8):e1123-e1135.
- Thompson R, Garcia M, Lee S. Cost-effectiveness analysis of novel therapeutic interventions: a decision-tree approach. Pharmacoeconomics. 2020;38(6):637-651.