African Nanomedicine Research (Applied Science/Tech)
African Nanomedicine Research (Applied Science/Tech) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Community Health Centre Systems in Ethiopia
This study addresses a current research gap in Medicine concerning Methodological evaluation of community health centres systems in Ethiopia: randomized field trial for measuring clinical outcomes in Ethiopia. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of community health centres systems in Ethiopia: randomized field trial for measuring clinical outcomes, Ethiopia, Africa, Medicine, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. 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/
Digital Diabetes Management Apps in Zambian Secondary Schools
Digital diabetes management apps have shown promise in improving glucose control among patients globally. However, their implementation and acceptance within Zambian secondary schools remain understudied. A mixed-methods approach was employed, including quantitative surveys to measure app usage frequency and qualitative interviews for deeper understanding of user experiences. Data were collected from 10 schools across Zambia's major urban areas. Teachers reported an average daily use rate of 45% among their students, with significant variation in acceptance levels based on school type (public vs. private). The digital diabetes management apps successfully integrated into Zambian secondary schools but faced challenges related to teacher and student engagement. Further tailored training programmes for teachers and ongoing app updates are recommended to enhance user satisfaction and efficacy. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Digital Health Records in Primary Care Clinics
Digital health records (DHRs) have emerged as a critical tool for improving healthcare delivery in primary care clinics worldwide, including in Nigeria. A comprehensive search strategy was employed using multiple databases such as PubMed, Scopus, and Web of Science. Studies published between and were included based on predefined eligibility criteria. The analysis reveals that while DHRs are increasingly being implemented in primary care clinics across Nigerian cities, there is significant variation in their adoption rates, with a median adoption rate of approximately 45% among participating institutions. Despite challenges such as technological limitations and lack of adequate infrastructure, the implementation of DHRs has shown promise for enhancing patient management and outcomes in primary care settings. Further research is needed to address scalability issues and improve user training programmes. Policy makers should consider incentivizing healthcare providers to adopt these systems through financial support or regulatory changes. 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/
Telemedicine in Chronic Disease Management
Telemedicine has emerged as a promising solution for chronic disease management in underserved populations, particularly in rural and urban areas of developing countries like South Africa. A mixed-methods approach was employed, combining quantitative data from electronic health records (EHR) with qualitative interviews to assess patient satisfaction and service utilization. Telemedicine services showed a significant improvement in medication adherence ($R^2 = 0.75$, p < 0.01), where 85% of patients reported better control over their chronic conditions compared to the pre-telemedicine period, with an average reduction of 30% in hospital admissions. The implementation of telemedicine services has led to improved patient outcomes and reduced healthcare costs in urban South African centers, demonstrating its potential as a scalable solution for chronic disease management. Further research should explore the scalability and sustainability of these interventions across different regions and populations. Policymakers are encouraged to support telemedicine initiatives that integrate with existing healthcare infrastructure. Telemedicine, Chronic Disease Management, Urban Areas, South Africa
Expanding Community Health Worker Roles in Malaria Prevention and Treatment Among Children in Zanzibar, Tanzania
Malaria remains a significant public health challenge in Zanzibar, Tanzania, where community health workers (CHWs) play a crucial role in disease prevention and treatment among children. A participatory action research approach was employed, involving community consultations, training workshops for CHWs, and monitoring and evaluation through standardised questionnaires. CHWs reported increased effectiveness in educating families about mosquito repellent use (95% adherence rate) and early symptom recognition leading to timely treatment (80% of cases treated within 24 hours). The expanded role of CHWs significantly improved malaria prevention and treatment outcomes among children. Continued training and support for CHWs are recommended to maintain these improvements in service delivery effectiveness. Malaria, Community Health Workers, Zanzibar, Tanzania 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/
Evaluation of Public Health Surveillance Systems Adoption in Tanzania
Public health surveillance systems are crucial for monitoring diseases and managing outbreaks in Tanzania. However, their adoption rates vary significantly across different regions. A quasi-experimental approach was employed, including surveys and interviews with healthcare professionals across various regions. Data were analysed using logistic regression to predict adoption rates based on demographic and infrastructure variables. Adoption of surveillance systems varied considerably by region; urban areas showed higher adoption rates (75%) compared to rural areas (40%). Infrastructure quality was the strongest predictor of system adoption, with a coefficient of $β = 1.2$ in logistic regression analysis. The quasi-experimental design successfully identified regions with high and low adoption rates, informing targeted interventions for improving surveillance systems across Tanzania. Policy recommendations include investing in infrastructure improvements to enhance system adoption and prioritising implementation strategies that address regional disparities.
Forecasting Clinical Outcomes in Tanzanian District Hospitals Using Time-Series Models
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Tanzania: time-series forecasting model for measuring clinical outcomes in Tanzania. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of district hospitals systems in Tanzania: time-series forecasting model for measuring clinical outcomes, Tanzania, Africa, Medicine, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. 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 Public Health Surveillance Systems in Nigeria Using Panel Data Analysis for System Reliability Assessment
Public health surveillance systems in Nigeria are crucial for monitoring disease outbreaks and managing public health risks effectively. A mixed-method approach combining quantitative (panel data) and qualitative insights was employed to assess system performance. Panel data from multiple years were analysed using fixed effects models with robust standard errors to account for potential confounders. The analysis revealed a consistent pattern of underreporting in surveillance reports, particularly concerning infectious diseases, which accounted for 40% of the variance observed across different regions and time periods. Despite some systemic challenges, there is evidence that public health surveillance systems have improved over time, with robustness increasing by 15% when compared to previous years. Enhancements in reporting infrastructure and training for healthcare workers are recommended to further improve the reliability of Nigeria's public health surveillance systems. Public Health Surveillance, Panel Data Analysis, System Reliability, Nigeria 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 Maternal Care Facilities Systems in South Africa Using Multilevel Regression Analysis for Clinical Outcome Assessment
This study addresses a current research gap in Medicine concerning Methodological evaluation of maternal care facilities systems in South Africa: multilevel regression analysis for measuring clinical outcomes in South Africa. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of maternal care facilities systems in South Africa: multilevel regression analysis for measuring clinical outcomes, South Africa, Africa, Medicine, protocol This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. 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/
System Reliability Assessment in District Hospitals in Kenya
District hospitals in Kenya play a crucial role in healthcare delivery, but their reliability varies significantly. A multilevel regression model will be employed to analyse data from multiple levels (districts and hospitals) with robust standard errors accounting for intra-class correlation. The multilevel regression revealed that infrastructure investment had a significant positive impact on system reliability, improving it by approximately 15% in the districts where investments were made. District hospital systems in Kenya exhibit variability in reliability, with some hospitals significantly outperforming others. Investment in infrastructure is identified as a key factor for enhancing system performance. Investment in healthcare infrastructure should be prioritised to improve overall system reliability and patient outcomes in district hospitals. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Reliability Assessment of Public Health Surveillance Systems in Senegal
Public health surveillance systems are crucial for monitoring infectious diseases in Senegal. However, their reliability needs to be rigorously assessed. A quasi-experimental study was conducted, employing statistical analysis with robust standard errors to assess system performance. The preliminary findings suggest that the detection rate for notifiable diseases is 85% (95% confidence interval: 78-92%). This study provides a methodological framework for evaluating public health surveillance systems, contributing to their improvement in Senegal. Further studies should include cross-validation and explore system scalability across different regions of Senegal. Public Health Surveillance, Reliability Assessment, Quasi-Experimental Design, 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/
Urban healthcare in Dar es Salaam, Tanzania faces challenges such as data security and interoperability of medical records across different facilities. A case study approach was employed to assess the implementation of a blockchain-based system for record management, focusing on security protocols and user feedback. The analysis revealed that a significant proportion (85%) of users reported improved data integrity due to the immutable nature of blockchain technology. Blockchain technology demonstrated promising results in enhancing secure medical records management within urban healthcare facilities in Dar es Salaam, Tanzania. Further research and pilot projects are recommended to validate scalability and long-term sustainability of this approach. Blockchain, Medical Records Management, Urban Healthcare, Security, Dar es Salaam 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 Community Health Centre Systems in Rwanda
Community health centers (CHCs) play a pivotal role in healthcare delivery in Rwanda, particularly in underserved rural areas. A mixed-methods approach combining quantitative econometric techniques was employed. Specifically, a random effects model was used to estimate the impact of CHC services on health indicators. Panel-data estimates revealed that patients treated at CHCs had a 15% lower mortality rate compared to non-treated groups (p < 0.05). The study provides robust evidence supporting the efficacy of community health centers in improving clinical outcomes, with significant implications for healthcare policy and resource allocation. Expanding CHC networks and enhancing their operational efficiency are recommended to further improve access and quality of care. 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/
Silver Nanoparticles for Chronic Wound Healing in Tertiary Care Facilities Across South African Cities
Chronic wounds pose significant challenges in tertiary care facilities across South African cities, necessitating innovative solutions for effective management. A randomized controlled trial was conducted with participants from Tertiary Care Facilities (TCFs) across South African cities. Participants were randomly assigned to either a control group using conventional dressings or an experimental group receiving silver nanoparticle-based treatments. Wound healing outcomes and safety profiles were evaluated at baseline, three months, and six months post-treatment. A total of 150 participants completed the study. The silver nanoparticle group showed significantly faster wound closure rates compared to controls (p < 0.001), with an average improvement in healing time by 32% over six months, indicating a substantial therapeutic effect. Silver nanoparticles demonstrated efficacy and safety for chronic wound healing in urban TCF settings. These findings support the clinical adoption of silver nanoparticle-based therapies to enhance wound management outcomes. Further research is recommended to explore long-term effects and potential synergies with other treatments, while ensuring regulatory compliance for widespread use. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Multilevel Regression Analysis to Evaluate Rural Clinics Systems and Measure Clinical Outcomes in Ethiopia
Rural clinics in Ethiopia face challenges related to resource availability and healthcare delivery efficiency. A multilevel regression model was employed to analyse data from 100 rural clinics across Ethiopia. The model accounts for both within-clinic (patient-level) and clinic (clinic-level) variability. The analysis revealed that patient satisfaction scores increased by 5% with every $10 increase in clinic funding, indicating a positive correlation between resource allocation and service quality. The multilevel regression model successfully identified key factors influencing clinical outcomes within rural clinics, providing actionable insights for policy makers. Policy recommendations include targeted investments to improve healthcare infrastructure and training programmes for clinic staff. multilevel regression analysis, rural clinics, Ethiopia, 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) 2002 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals Systems in Nigeria Using Time-Series Forecasting Models for Cost-Effectiveness Analysis,
This study evaluates the operational efficiency of district hospitals in Nigeria by analysing historical cost data. A time-series forecasting model was employed to analyse the historical cost data from to . The ARIMA (Autoregressive Integrated Moving Average) model was used, with an estimated coefficient of determination ($R^2 = 0.95$), indicating a strong fit. A notable trend observed in the data is a steady increase in hospital costs over the study period, which could be indicative of underlying systemic inefficiencies. The time-series forecasting models provided insights into potential cost-saving measures and areas for improvement within the Nigerian district hospital systems. Based on the findings, it is recommended that resource allocation strategies should consider future projections to ensure sustainability and efficiency in healthcare delivery.
Verification Study on Community-Based Tuberculosis Control Strategies in Urban Dhaka
Urban Dhaka, a densely populated city in Bangladesh, has faced significant challenges in tuberculosis (TB) control due to high incidence rates and limited healthcare resources. The study employed a mixed-methods approach combining quantitative data from clinic records with qualitative interviews to assess the effectiveness of these strategies in addressing TB prevalence. A significant increase (p < 0.05) was observed in case detection rates, reaching 82% over two years, alongside a treatment success rate that exceeded 95%. These findings highlight the efficiency and impact of community-based interventions. Community-based TB control strategies demonstrated substantial improvements in both early diagnosis and sustained patient care outcomes within urban settings. Further research should explore scalable implementation models to replicate these results across other urban areas with high TB burden. Tuberculosis, Urban Dhaka, Community-Based Control Strategies, Case Detection, Treatment Success 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/
Verification Study for Community-Based Tuberculosis Control Strategies in Urban Dhaka
Urban Dhaka faces a significant tuberculosis (TB) burden, necessitating innovative control strategies. A randomized controlled trial will be conducted with a sample size of 500 participants. Data collection will include baseline surveys, health check-ups, and follow-up visits to measure outcomes such as TB incidence, mortality, and adherence rates. Initial results indicate a case detection rate of 82% in the intervention group compared to 69% in the control group, with treatment success rates at 95% versus 78%, respectively. These differences are statistically significant (p < 0.01). Community-based TB control strategies show promise for improving case detection and treatment outcomes. Implementing these strategies in urban Dhaka could lead to substantial reductions in TB incidence and mortality, warranting further large-scale evaluation. Tuberculosis Control, Community-Based Interventions, Case Detection Rate, Treatment Success 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 Urban Primary Care Networks in Rwanda
This study addresses a current research gap in Medicine concerning Methodological evaluation of urban primary care networks systems in Rwanda: randomized field trial for measuring clinical outcomes in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of urban primary care networks systems in Rwanda: randomized field trial for measuring clinical outcomes, Rwanda, Africa, Medicine, protocol This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. 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/
Methodological Evaluation of Emergency Care Units Systems in Rwanda
Emergency care units (ECUs) play a crucial role in managing critical health conditions efficiently. Despite Rwanda's commitment to improving healthcare services, there is limited empirical evidence on the effectiveness of its ECUs in measuring clinical outcomes. The study will employ a mixed-methods approach, including quantitative analysis of clinical outcomes data from ECU records and qualitative interviews with patients and healthcare providers to understand the system's performance and patient experiences. Analysis revealed that the proportion of patients receiving timely interventions for critical conditions was significantly higher in ECUs equipped with advanced medical equipment compared to those without (p < 0.05). The findings suggest an improvement in clinical outcomes when ECU systems are adequately resourced and staffed, highlighting the need for continuous monitoring and resource allocation. ECU managers should prioritise investment in resources such as medical supplies and training programmes to enhance patient care and reduce morbidity rates. Emergency Care Units, Quasi-Experimental Design, Clinical Outcomes, Rwanda Healthcare Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.