Russell Kabir
Anglia Ruskin University

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

Effectiveness and Implementation Challenges of Malaria Control Interventions Among Children Under Five in Malawi: A Systematic Review Eneles Chisonga; Russell Kabir
Asian Journal of Public Health and Nursing Vol. 3 No. 2 (2026)
Publisher : Queeva Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62377/g8v67q86

Abstract

Background: Malaria remains a major cause of morbidity and mortality among children under five years of age in Malawi despite the widespread implementation of insecticide-treated nets (ITNs), indoor residual spraying (IRS), and the RTS,S/AS01 malaria vaccine. However, evidence regarding the effectiveness of these interventions remains fragmented. Methods: A systematic review was conducted following the PRISMA 2020 guidelines. PubMed, Scopus, Web of Science, and Embase were searched for studies published between 2015 and 2025 evaluating malaria control interventions among children under five years of age in Malawi. Eight studies met the inclusion criteria and were synthesised narratively due to heterogeneity in study designs and outcome measures. Methodological quality was assessed using study-design-appropriate appraisal tools, including CASP checklists for empirical studies. Five studies were assessed as high quality and three as moderate quality. Results: Across the included studies, ITN use was generally associated with lower malaria risk or prevalence, although the magnitude of effect varied due to differences in study design, outcome measures, and study settings. IRS reduced prevalence by up to 20% in sprayed households. Evidence on RTS,S/AS01 indicated protection against clinical malaria that varied with environmental context, while modelling estimated the greatest reductions (65–71%) when vaccination was combined with ITN use. Post-introduction evidence identified no new vaccine safety concerns. Intervention effectiveness was influenced by utilisation, coverage, insecticide resistance, environmental conditions, and socioeconomic factors. Key implementation challenges included inconsistent ITN use, logistical constraints, and inequities in access and uptake. Conclusions: Malaria control interventions were generally associated with reductions in the malaria burden among children under five years of age in Malawi, with modelling evidence suggesting additional benefits from combining RTS,S/AS01 vaccination with ITN use. However, evidence on combined interventions was limited and heterogeneous, with the largest estimated benefits derived from modelling. Strengthening integrated delivery strategies, improving adherence, and addressing implementation challenges are essential for achieving sustained reductions in malaria transmission.
Application of Logistic Regression in Health and Allied Research: Part I – Basic Concepts, Purpose, Methods, Variable Requirements, and Assumptions Mohammad Tajul Islam; Russell Kabir; Sufia Nasrin Rita; Ali Davod Parsa; SM Anwar Sadat
Asian Journal of Public Health and Nursing Vol. 3 No. 2 (2026)
Publisher : Queeva Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62377/jsgzqy90

Abstract

Background: Logistic regression is a widely used multivariable statistical method in health and allied research for examining associations and predicting categorical outcomes. However, its appropriate application requires an understanding of the type of outcome variable, model specification, variable coding, and underlying assumptions. This article provides an accessible introduction to logistic regression for non-statisticians, clinical professionals, and early-career researchers. Methods: This methodological article reviews the purpose, methods, mathematical concepts, variable requirements, sample size considerations, and assumptions of logistic regression. It distinguishes binary, multinomial, and ordinal logistic regression and explains odds, logit transformation, regression coefficients, odds ratios, predicted probabilities, reference category selection, and dummy variable coding. Results: Binary logistic regression is appropriate for dichotomous outcomes, multinomial logistic regression for nominal outcomes with more than two categories, and ordinal logistic regression for ordered categorical outcomes. Appropriate coding and selection of reference categories are essential for interpretation. Although a minimum of 10 outcome events per estimated model parameter has traditionally been used as a rule of thumb, sample size requirements depend on the characteristics and purpose of the model. Logistic regression does not require normally distributed predictors but requires attention to model assumptions and diagnostics. Conclusions: This article provides an accessible foundation for understanding and applying logistic regression in health and allied research and prepares readers for Part II, which focuses on binary logistic regression.