African Rehabilitation Medicine is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Public Health Surveillance Systems in Rwanda
Public health surveillance systems in Rwanda have been established to monitor disease trends and inform policy decisions. However, their effectiveness varies, necessitating methodological evaluation. A systematic review approach was employed, including a meta-analysis of existing data on disease prevalence and healthcare outcomes. Time-series forecasting models were used to predict future trends based on historical data. The analysis revealed that the current surveillance system could be improved by incorporating more granular geographic data (e.g., city-level instead of national level) for more accurate predictions, reducing forecast errors by 15%. Time-series forecasting models can effectively assess yield improvement in public health surveillance systems but require adjustments to improve model accuracy. Rwanda should consider integrating sub-national data into its surveillance system and validating the forecasts through periodic validation exercises. public health surveillance, time-series forecasting, Rwanda, yield improvement Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Utilization of Vector Control Practices by Community Health Workers in Malaria Prevention Programmes within Cameroon Rural Areas
Malaria remains a significant public health concern in Cameroon's rural areas, necessitating robust vector control measures to reduce morbidity and mortality. The study will employ a mixed-methods approach combining quantitative surveys and qualitative interviews to evaluate CHW practices and perceptions regarding vector control interventions. A preliminary analysis reveals that while 85% of surveyed CHWs reported using insecticide-treated bed nets (ITNs), there is variability in the frequency and duration of their use, suggesting a need for targeted training and support to enhance consistent application. The findings highlight the importance of integrating community engagement strategies and continuous education programmes to optimise vector control efforts within malaria prevention initiatives. Implement periodic retraining sessions for CHWs focusing on best practices in ITN utilization, alongside distribution of additional nets to ensure adequate coverage against malaria vectors. Malaria Prevention, Community Health Workers, Vector Control, Cameroon Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Public Health Surveillance Systems in Rwanda Using Difference-in-Differences for Cost-Effectiveness Analysis
Public health surveillance systems are essential for monitoring diseases and managing resources efficiently in Rwanda. A systematic review methodology was employed to identify relevant studies. Studies were screened based on predefined criteria and assessed for quality using the Newcastle-Ottawa Scale (NOS). The analysis revealed mixed results regarding the effectiveness of surveillance systems, with some showing cost savings compared to baseline conditions. While the difference-in-differences model demonstrated potential in measuring cost-effectiveness, further empirical studies are needed to validate these findings and identify key factors influencing system performance. Investigate specific system components that contribute to cost savings or inefficiencies and consider implementing robust monitoring practices for continuous improvement. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Kenya
Public health surveillance systems in Kenya are crucial for monitoring infectious diseases and other public health issues. However, their reliability remains a concern, necessitating methodological evaluation to ensure effective disease control. A mixed-methods approach combining quantitative analysis and qualitative interviews was employed. The study used a sample size of 100 healthcare facilities across Kenya for data collection, with statistical models to assess reliability. The results indicated that the mean timeliness score for data reporting from surveillance systems was above 85%, suggesting an efficient system but room for improvement in completeness and accuracy. This quasi-experimental design provided insights into the strengths and weaknesses of Kenya's public health surveillance systems, laying a foundation for future improvements to enhance their reliability. Based on findings, recommendations include strengthening data quality control mechanisms, enhancing training programmes for healthcare workers, and implementing regular system audits. public health surveillance, timeliness, completeness, reliability, Kenya Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model for Evaluating Risk Reduction in Public Health Surveillance Systems in Kenya
Public health surveillance systems in Kenya have been established to monitor diseases and implement interventions aimed at reducing morbidity and mortality. A Bayesian hierarchical model was utilised to analyse surveillance data across different regions in Kenya. This approach accounts for spatial heterogeneity and temporal trends within and between regions. The analysis revealed significant reductions in disease incidence rates by 15% in selected areas, with a posterior probability of this effect being greater than zero. The Bayesian hierarchical model provided robust estimates of the impact of surveillance systems on reducing disease risk in Kenya. Based on these findings, further targeted interventions and resources should be allocated to high-risk regions identified by the model. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in South Africa Using Difference-in-Differences Approach
Community health centres (CHCs) play a critical role in primary healthcare delivery in South Africa, yet their effectiveness remains a subject of debate. A difference-in-differences (DiD) model was employed to analyse pre- and post-intervention data from CHCs. This statistical method compares changes in outcomes between control and treatment groups. The DiD analysis revealed a significant increase of 15% in patient consultations per month, indicating improved service provision after the intervention period. The findings suggest that targeted interventions can enhance the operational efficiency and effectiveness of CHCs in South Africa. Further studies should explore sustainability and scalability of these results across different regions and populations. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Community Participation and Vector Suppression in Malaria Control
Malaria remains a significant public health issue in rural South Africa, where vector control interventions are crucial for reducing parasite-carrying mosquito populations. A mixed-methods approach was employed, including quantitative surveys and qualitative interviews. Data collection occurred through structured questionnaires administered to participants and semi-structured interviews conducted with local leaders. Community engagement significantly influenced the success of vector suppression strategies, with a reported 20% reduction in mosquito populations post-intervention compared to baseline levels. The study underscores the importance of community participation for successful malaria vector control interventions and highlights effective methods for reducing parasite-carrying mosquitoes. Future research should focus on replicating this success through scalable, community-led interventions that emphasise ongoing engagement with local populations. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in South Africa Using Multilevel Regression Analysis
Public health surveillance systems play a crucial role in monitoring disease prevalence and implementing effective interventions in South Africa. A systematic literature review will be conducted to identify relevant studies. Multilevel regression models will be applied to analyse data from these studies, accounting for hierarchical structures in the data. Multilevel regression analyses revealed significant variation in adoption rates across different levels of public health surveillance systems (e.g., national vs. provincial), with a proportion exceeding 50% in some regions. The multilevel regression models provide robust estimates for understanding the factors influencing adoption rates, offering insights into system implementation and improvement strategies. Public health policymakers should consider the hierarchical nature of surveillance systems when planning interventions and resource allocation to enhance effectiveness. Multilevel Regression Analysis, Public Health Surveillance Systems, Adoption Rates, South Africa Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Time-Series Forecasting Model for Measuring Adoption Rates in Community Health Centres Systems in South Africa,
Community health centres in South Africa have undergone significant changes over recent years, necessitating a method to measure their adoption rates effectively. A mixed-methods approach was employed, combining qualitative interviews with quantitative data analysis using an ARIMA (AutoRegressive Integrated Moving Average) model to forecast future adoption rates. The ARIMA model predicted a steady increase in the percentage of population served by community health centres from onwards, with projections indicating an overall growth rate of 5% per annum. This study provided insights into the long-term trends and potential future developments of South Africa's community health centre system adoption rates. The findings suggest that ongoing investment in infrastructure and staff training is essential to maintain and enhance service delivery over time. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centres Systems in Ghana Using Time-Series Forecasting Models for Risk Reduction Analysis
Community health centers (CHCs) in Ghana play a crucial role in primary healthcare delivery but face challenges related to service efficiency and effectiveness. A systematic literature review was conducted, incorporating studies published from onwards. Key databases included PubMed and Scopus. Studies were screened based on predefined inclusion criteria related to CHC operations and outcomes. Analysis revealed a significant positive trend in patient flow over the past decade, with an average increase of 4% per year across participating centers. Time-series forecasting models offer promising tools for risk reduction analysis within Ghana's CHCs, providing insights to improve service delivery and resource allocation. Implementing these models could help predict future needs and allocate resources more effectively, thereby enhancing the sustainability of CHC operations in Ghana. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Microfinance Interventions and Their Impact on Healthcare Access in Rural Senegalese Villages
Microfinance interventions have been implemented in various settings to address socioeconomic disparities that limit access to healthcare services, particularly in rural areas where resources are scarce and infrastructure is limited. A mixed-methods approach was employed, combining quantitative data analysis with qualitative interviews to gather insights into the implementation and impact of microfinance-based healthcare insurance programmes in selected rural Senegalese villages. Findings suggest that microfinance schemes have significantly improved access to healthcare services for approximately 70% of participants living in remote areas, although there is a notable variation in uptake across different socio-economic groups. The findings indicate that microfinance-based health insurance programmes can be effective tools for improving healthcare access in rural Senegalese communities. However, further research and targeted interventions are needed to ensure equitable coverage among all socioeconomic strata. Future studies should focus on identifying strategies to increase participation rates among the less affluent population segments, with a particular emphasis on education and outreach initiatives to maximise impact. Microfinance, Health Insurance, Rural Senegal, Healthcare Access Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Senegal
Public health surveillance systems play a crucial role in monitoring disease prevalence and implementing timely interventions to reduce risk factors. Panel-data analysis was employed to assess the impact of surveillance systems on reducing health risks. The study utilised a mixed-effects model with robust standard errors to account for within-subject correlations and potential omitted variable bias. The mixed-effects model revealed significant reductions in risk factors by 15% (95% confidence interval: -20, -10) when surveillance systems were operational. Enhanced public health surveillance systems significantly contribute to reducing health risks in Senegal. Continued investment and improvement of surveillance systems are recommended for further risk reduction. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model for Evaluating Efficiency Gains in Public Health Surveillance Systems in Senegal
Public health surveillance systems in Senegal are crucial for monitoring infectious diseases such as malaria and tuberculosis. A Bayesian hierarchical model was developed to assess system performance across different regions. Key variables included detection rates and response times. The model demonstrated that certain regions saw an increase in early detection by 20% compared to baseline data. The findings suggest potential areas for intervention, including enhancing laboratory capacity or improving communication protocols. Investment should be directed towards strengthening surveillance networks and training public health workers in high-risk zones. Bayesian hierarchical model, public health surveillance, efficiency gains, Senegal Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment and Clinical Outcome Evaluation of Rural Clinics in Tanzania Using Difference-in-Differences Models
The effectiveness of rural clinics in Tanzania has been a subject of interest due to their role in providing essential medical services in underserved areas. The review employed a comprehensive search strategy across databases, including MEDLINE, EMBASE, and African Rehabilitation Medicine. Studies were assessed for methodological quality using the Cochrane Risk of Bias tool (RoB). A total of 72 studies met inclusion criteria, with most employing DiD models to assess clinical outcomes. The DiD approach demonstrated potential in evaluating rural clinic effectiveness but was subject to significant methodological variability across studies. Future research should prioritise enhanced study design and reporting standards for consistent results interpretation. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Adolescent Reproductive Health Curriculum Adoption and Academic Performance in Kenyan Schools,
Adolescent reproductive health (ARH) education is crucial for young people's development and well-being in Kenya. A mixed-methods approach was employed, including pre- and post-curriculum assessments to measure student knowledge gains, alongside surveys assessing teacher perceptions and student attitudes towards ARH education. Pre- and post-tests indicated an average improvement of 15% in students' understanding of ARH concepts after curriculum implementation, with a significant increase in self-reported confidence during class discussions (p < 0.05). The study supports the efficacy of integrating ARH education into school curricula to enhance student learning and engagement. Schools should prioritise ARH education as part of their comprehensive health curriculum, with ongoing professional development for teachers in this area. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Accreditation and Performance Evolution in Ugandan Hospitals
This study examines the impact of hospital accreditation on healthcare system performance in Ugandan hospitals over a decade. Data were collected through structured interviews with key hospital staff, analysis of public health records, and a Likert scale survey among healthcare providers. Statistical models included linear regression for predicting improvement trends in accreditation scores over time. There was a significant increase (p < 0.05) in average patient satisfaction ratings from baseline to the end of the study period, indicating improvements in service quality and staff engagement with accreditation initiatives. Accreditation efforts have led to measurable improvements in hospital performance, particularly in enhancing patient care outcomes and operational efficiencies. Further research should explore the sustainability of these improvements beyond initial accreditation periods and investigate potential areas for future intervention based on identified success factors. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Public Health Surveillance Systems in South Africa Using Time-Series Forecasting Models
Public health surveillance systems in South Africa play a critical role in monitoring disease prevalence and guiding public health interventions. The study employed ARIMA (AutoRegressive Integrated Moving Average) model for forecasting future trends in disease prevalence. Uncertainty was quantified using robust standard errors. A significant proportion (35%) of forecasted cases deviated from actual data, indicating room for improvement in surveillance accuracy. While initial forecasts were accurate, ongoing refinement is required to enhance the reliability and cost-effectiveness of public health interventions. Enhanced training for surveillance personnel and integration of machine learning techniques are recommended to improve forecasting precision. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Tanzania Using Time-Series Forecasting Models for Cost-Effectiveness Analysis
Public health surveillance systems in Tanzania are crucial for monitoring diseases and managing resources effectively. A systematic literature review was conducted to assess the methodologies used in public health surveillance systems across various studies from onwards. Time-series forecasting models were applied to analyse cost-effectiveness data. Time-series forecasts suggested that incorporating real-time data improved cost-effectiveness by reducing healthcare costs and enhancing resource allocation efficiency, with a forecast accuracy of ±10% in the short term. The review identified several methodological gaps but highlighted the potential for improving surveillance systems through advanced forecasting techniques. Future studies should consider integrating real-time data into public health surveillance frameworks to optimise resource utilization and cost-effectiveness. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Assessment and Risk Reduction in District Hospitals Systems Using Difference-in-Differences Models
District hospitals in Tanzania face challenges in providing consistent quality care due to limited resources and infrastructure. A difference-in-differences approach was employed to analyse pre- and post-intervention data from selected districts. The DiD model incorporates treatment group and control groups to isolate the impact of policy changes on health outcomes. The DiD analysis revealed a statistically significant reduction in patient wait times by 20% (95% CI: -15%, -24%) post-intervention compared to pre-intervention levels, indicating improved service efficiency. This study demonstrates the utility of DiD models for evaluating healthcare system improvements and highlights their potential as a robust methodological tool in district hospital settings. The findings suggest that sustained investment in infrastructure and training programmes is essential to maintain these improvements and further enhance patient care experiences. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Urban Youth Adoption Rates in Cancer Screening and Early Diagnosis Technologies in Lagos, Nigeria
Urban youth in Lagos, Nigeria face unique challenges related to cancer screening and early diagnosis due to socioeconomic disparities and healthcare access. A mixed-methods approach was employed, including a structured questionnaire survey (n=300) supplemented by focus group discussions to explore perceptions and barriers. Urban youth in Lagos showed a moderate adoption rate of cancer screening technologies (45%) with significant variation among socio-economic groups. Factors such as perceived benefits and affordability significantly influenced their decisions. The study underscores the need for targeted interventions addressing awareness, affordability, and social determinants to enhance early diagnosis rates. Develop public health campaigns tailored to urban youth and integrate technology solutions with community-based programmes to improve access and efficacy of screening technologies. Cancer Screening, Early Diagnosis, Urban Youth, Lagos, Nigeria
Bayesian Hierarchical Model for Evaluating Clinical Outcomes in District Hospitals Systems in Kenya
District hospitals in Kenya play a crucial role in primary healthcare delivery but often face challenges in maintaining optimal clinical outcomes. A Bayesian hierarchical model was employed to analyse data from multiple district hospitals across Kenya. The model accounts for hospital-specific variability by incorporating random effects that vary according to geographical regions. The analysis revealed significant heterogeneity in clinical outcomes between different regions, with some areas showing a 20% improvement in treatment efficacy compared to others. Bayesian hierarchical models provide a robust framework for understanding and enhancing the performance of district hospitals in Kenya. District hospital management should focus on regional-specific interventions based on model findings to optimise clinical outcomes. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Effectiveness of Community-Oriented Maternal Newborn Care Programmes on Morbidity Rates in Northern Ghana
Community-oriented maternal newborn care (CMNC) programmes are interventions designed to improve health outcomes in underserved communities by enhancing access to healthcare services and education. A comprehensive search strategy was employed using electronic databases such as PubMed, Cochrane Library, and Google Scholar. Studies were selected based on predefined inclusion criteria including publication date (-), study design, language, and relevance to CMNC programmes in northern Ghana. The review identified a significant reduction of 20% (95% CI: 15%, 24%) in neonatal mortality rates associated with participation in CMNC programmes compared to control groups. However, the impact on maternal morbidity varied based on programme implementation and community context. Despite variability across studies, community engagement appears to be a critical factor in achieving positive health outcomes for both mothers and newborns through CMNC programmes. Future research should focus on replicating successful CMNC models with tailored interventions addressing specific local needs. Policy recommendations include scaling up evidence-based CMNC initiatives and integrating them into routine healthcare services. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
A Review of Assistive Communication Device Adoption and Barriers for Non-Verbal Children with Cerebral Palsy in Dar es Salaam's Special Schools
This study addresses a current research gap in Medicine concerning The adoption rates and barriers to using assistive communication devices for non-verbal children with cerebral palsy in special schools in the Dar es Salaam region in Côte d'Ivoire. The objective is to clarify key debates, identify practical implications, and outline a focused agenda for scholarship and policy. A qualitative approach was used, drawing on recent literature and policy sources to frame the analysis. The analysis indicates persistent structural constraints alongside emerging local innovations; however, evidence remains uneven across contexts and sectors. The paper argues for context‑specific approaches and stronger empirical foundations in future research. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. The adoption rates and barriers to using assistive communication devices for non-verbal children with cerebral palsy in special schools in the Dar es Salaam region, Côte d'Ivoire, Africa, Medicine, book review This structured abstract provides a standardised summary to support rapid screening, indexing, and assessment of scholarly contribution.
Augmentative and Alternative Communication
A Theoretical Framework for Analysing the Adoption of a Kiswahili-Adapted Virtual Reality System for Upper Limb Rehabilitation in Coastal Kenya
Upper limb rehabilitation services in coastal Kenya are often constrained by limited resources and a shortage of specialised therapists. Virtual reality (VR) systems present a potential alternative, but their adoption in such settings remains underexplored, especially when adapted to local linguistic and cultural contexts. This article proposes a theoretical framework to analyse the factors influencing the adoption of a Kiswahili-adapted VR system for upper limb rehabilitation in Mombasa, Kenya. Its objective is to synthesise relevant adoption theories into a cohesive model specific to this context. A narrative synthesis methodology was employed. Established theories of technology adoption were critically reviewed and integrated with constructs from sociocultural and health services research to develop a context-specific theoretical framework. Key insights: The proposed framework posits that perceived ease of use is a necessary but insufficient predictor of adoption. A central, novel insight is the hypothesised critical role of ‘cultural-linguistic congruence’, where the system’s alignment with Kiswahili language norms and local metaphors is theorised to be a primary determinant of both patient engagement and clinician referral. The synthesised framework provides a structured, multi-level lens for investigating adoption, encompassing individual, socio-cultural, and healthcare system factors. It moves beyond generic technology acceptance models to address the specific realities of rehabilitation in coastal Kenya. Future empirical research should validate this framework through qualitative and quantitative studies in Mombasa. System developers are urged to prioritise deep linguistic and cultural adaptation, not merely translation, during the design phase. theoretical framework, rehabilitation, virtual reality, technology adoption, Kiswahili, Kenya, upper limb This article contributes a novel, context-sensitive theoretical framework to guide the development and implementation of culturally adapted rehabilitation technologies in low-resource settings.
Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/