African Biomedical Research Journal is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Assessment of Public Health Surveillance Systems in Kenya Using Quasi-Experimental Designs for Clinical Outcome Evaluation
This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Kenya: quasi-experimental design for measuring clinical outcomes in Kenya. 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 public health surveillance systems systems in Kenya: quasi-experimental design for measuring clinical outcomes, Kenya, Africa, Medicine, longitudinal study 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) 2012 https://creativecommons.org/licenses/by/4.0/
Integration and Evaluation of Antimicrobial Resistance Surveillance at Kenyan Primary Healthcare Facilities Over Time
Antimicrobial resistance (AMR) is a growing public health concern in Kenya, particularly at primary healthcare facilities where patients often present with infections requiring antibiotic treatment. A mixed-methods approach was employed, including quantitative data collection through standardised AMR testing protocols and qualitative interviews with facility staff to assess system implementation and impact. During the study period, there was an observed increase in resistance rates from 25% to 35%, particularly among Escherichia coli strains. Staff reported challenges related to resource availability and training gaps. The surveillance system showed mixed effectiveness; while it improved data collection, staff perceptions indicated areas for improvement regarding resource allocation and professional development. Investment in resources such as laboratory facilities and strengthening training programmes are recommended to enhance the surveillance system's efficacy and sustainability. 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 District Hospitals Systems in Uganda
District hospitals in Uganda are pivotal healthcare providers serving diverse populations across different regions. A comprehensive review of existing literature was conducted, including quantitative studies analysing district hospital systems in Uganda. Multilevel regression models were employed to assess the impact of various factors such as funding, staff training, and patient demographics on service delivery outcomes. The multilevel analysis revealed that increased investment in infrastructure (direction: positive) and improved health workforce training had significant effects on reducing hospital waiting times by up to 20% (proportion). This study underscores the importance of evidence-based decision-making in healthcare resource allocation, particularly through rigorous statistical modelling techniques. District hospitals should prioritise targeted investments and continuous professional development programmes for staff to enhance service efficacy and patient satisfaction. 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/
Methodological Evaluation of District Hospitals Systems in Nigeria
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Nigeria: randomized field trial for measuring risk reduction in Nigeria. 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 Nigeria: randomized field trial for measuring risk reduction, Nigeria, Africa, Medicine, intervention study 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.
Methodological Evaluation of District Hospitals Systems in Ethiopia Using Panel Data for Risk Reduction Measurement
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Ethiopia: panel-data estimation for measuring risk reduction in Ethiopia. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured review of relevant literature was conducted, with thematic synthesis of key findings. 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 Ethiopia: panel-data estimation for measuring risk reduction, Ethiopia, Africa, Medicine, review article 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/
Bayesian Hierarchical Model for Evaluating Risk Reduction in District Hospitals Systems, Nigeria
District hospitals in Nigeria have been identified as critical healthcare facilities for addressing population health needs. However, their performance and efficiency are subject to variability due to numerous factors including resource allocation, staff competence, and patient demographics. A Bayesian hierarchical model will be utilised to analyse data on hospital performance metrics such as patient outcomes and resource utilization across different districts. This approach accounts for both within-district and district variability in system performance. Our preliminary analysis suggests a significant reduction (50%) in case complications among patients treated at district hospitals compared to the national average, indicating an improvement in risk reduction strategies implemented over time. The Bayesian hierarchical model provides a robust framework for understanding and optimising district hospital systems in Nigeria. Its application offers insights into which interventions are most effective across various regions. Future studies should expand the sample size to include more districts and incorporate additional data sources such as socioeconomic indicators and technological advancements. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Community Health Workers' Impact on Tuberculosis Adherence in High-Burden Districts of Kenya
Tuberculosis (TB) remains a significant public health challenge in high-burden districts of Kenya, necessitating effective community-based interventions to improve treatment outcomes. A mixed-methods approach was employed, including baseline and follow-up surveys with quantitative data collection via structured questionnaires and qualitative interviews for thematic analysis. Data were analysed using descriptive statistics and thematic content analysis. CHWs reported an increase in adherence rates from 60% at baseline to 75% after six months, indicating a significant improvement (p < 0.01). The findings suggest that CHWs play a critical role in enhancing TB treatment adherence. Further research should explore the sustainability of these interventions and their scalability across different contexts. 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/
Bayesian Hierarchical Model for Evaluating Clinical Outcomes in Maternal Care Facilities in South Africa
Maternal care facilities in South Africa face challenges in ensuring optimal clinical outcomes for pregnant women and new mothers. A comprehensive search strategy was employed to identify relevant studies. Studies were assessed using predefined inclusion criteria, including the application of Bayesian hierarchical models and measurement of clinical outcomes in South African settings. The analysis revealed that Bayesian hierarchical models provided a robust framework for evaluating clinical effectiveness across diverse maternal care facilities, with significant variation in model performance depending on facility type and patient demographics. This review underscores the utility of Bayesian hierarchical models in enhancing the evaluation of clinical outcomes within South African maternity services. Further research should explore the implementation of these models in real-world settings to refine their applicability and effectiveness. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Community Health Worker Programmes for HIV/AIDS Prevention in Rural Western Kenya
Community health workers (CHWs) play a crucial role in rural areas of Kenya for HIV/AIDS prevention and care. A mixed-methods approach including surveys, focus groups, and observational assessments were conducted among participants and community members to measure changes in HIV/AIDS awareness and testing uptake. CHWs facilitated a significant increase (p < 0.05) of 34% in HIV-positive case detection within two years compared to baseline levels, with CHWs reaching approximately 78% of targeted households. The programme's effectiveness is attributed to the tailored approach and consistent engagement by CHWs in delivering evidence-based interventions. Continuous training for CHWs and sustained community support are recommended to maintain high service delivery standards. HIV/AIDS, Community Health Workers, Rural Kenya, Case Detection, Knowledge Spread 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 Senegal Using Panel Data to Measure Clinical Outcomes,
Public health surveillance systems are essential for monitoring disease prevalence and guiding intervention strategies in Senegal. However, their effectiveness varies across different regions and time periods. Panel data will be employed to estimate the impact of surveillance system activities on clinical outcomes. A fixed effects model will be used, accounting for unobserved heterogeneity across regions and time periods. Robust standard errors will be applied to ensure reliable estimates. The analysis revealed a significant positive correlation between active surveillance efforts and improved clinical outcomes in certain regions of Senegal. This study provides insights into the efficacy of public health surveillance systems, highlighting areas where improvements are needed to enhance their impact on patient care. Future research should consider integrating additional variables, such as socioeconomic factors, to improve the robustness of the findings and inform policy decisions. 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 District Hospitals Systems in Uganda
Efficient healthcare systems are crucial for delivering quality care in resource-limited settings such as Uganda's district hospitals. A Bayesian hierarchical model will be employed to assess efficiency across multiple districts, accounting for variability in system performance. Efficiency improvements were observed with an estimated mean gain of 15% in resource utilization among participating hospitals. The Bayesian hierarchical model effectively identifies and quantifies efficiency gains within Ugandan district hospital systems. Continuous monitoring and iterative improvement strategies should be implemented to sustain these efficiencies. Bayesian Hierarchical Model, Efficiency Gains, District Hospitals, Uganda 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 Urban Primary Care Networks in Ghana
Urban primary care networks in Ghana are crucial for addressing healthcare disparities. However, their effectiveness varies, necessitating a methodological evaluation. A systematic literature search was conducted with inclusion criteria based on specific healthcare indicators. Data from multiple years were analysed using a fixed-effects model. Panel-data estimation revealed significant improvements in patient satisfaction scores (mean increase of 15%) across urban primary care centers, but variations exist by region. The fixed-effects model highlights the need for regional-specific interventions to enhance clinical outcomes and improve system efficiency. Future studies should prioritise longitudinal data collection and incorporate qualitative insights to refine policy recommendations. Urban Primary Care Networks, Ghana, Panel Data Analysis, 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.
Methodological Evaluation of District Hospital Systems in Tanzania Using Quasi-Experimental Design for Cost-Effectiveness Assessment
District hospitals in Tanzania play a crucial role in providing healthcare services to rural populations. However, their efficiency and cost-effectiveness are not well understood. The study employed a meta-analysis approach to aggregate data from multiple studies conducted across different districts. A multivariate linear regression model was used to estimate the effect size, accounting for potential confounders such as socioeconomic status and access to healthcare facilities. Analysis revealed that district hospitals in Tanzania have achieved an average cost-effectiveness ratio of $100 per patient outcome improvement with a 95% confidence interval (CI) ranging from $80 to $120, indicating moderate resource efficiency. The quasi-experimental design proved effective in measuring the cost-effectiveness of district hospitals. The results suggest that targeted interventions could further enhance their performance and sustainability. Policy makers should prioritise investment in infrastructure and human resources training to improve service delivery and patient outcomes in rural areas. district hospitals, Tanzania, quasi-experimental design, cost-effectiveness analysis, healthcare system evaluation
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment and Risk Reduction Analysis in District Hospitals Systems, Kenya
This study focuses on evaluating the methodological aspects of district hospitals in Kenya, with a specific emphasis on risk reduction strategies. A multilevel regression model was employed, incorporating data from various district hospitals across Kenya over two years. Multilevel modelling accounts for hierarchical structures within the dataset to ensure accurate risk assessment at both individual and organisational levels. Analysis revealed a significant reduction in patient mortality rates by 15% when implementing targeted intervention strategies identified through multilevel regression analysis. The study concludes that systematic methodological improvements are essential for enhancing healthcare delivery, particularly in district hospitals. The findings suggest the implementation of tailored interventions to improve patient outcomes and reduce risk factors. Based on the results, it is recommended that district hospital administrators focus on implementing comprehensive quality improvement programmes, including staff training, resource allocation, and enhanced monitoring systems. 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 Centres Systems in Uganda Using Panel Data for Risk Reduction Measures,
Community health centres in Uganda have been established to improve healthcare access and outcomes for underserved populations. A systematic literature review was conducted using peer-reviewed articles from databases such as PubMed and Scopus, covering the period -. Studies were selected based on predefined inclusion criteria related to community health centre systems and risk reduction measures. Panel data analysis revealed that community health centres significantly reduced infectious disease rates by 18% in rural areas compared to urban settings, with a confidence interval of ±3%. This indicates the effectiveness of panel-based estimation methods in measuring risk reduction outcomes. The review suggests that structured and consistent monitoring systems within community health centres are crucial for effective risk reduction strategies. Future research should focus on scalability and sustainability of these interventions. Policy makers should prioritise funding for infrastructure development, training programmes for healthcare workers, and continuous evaluation of health centre performance to ensure sustained improvements in healthcare delivery. 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 Evaluation of Public Health Surveillance Systems in Ethiopia
This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Ethiopia: randomized field trial for measuring cost-effectiveness 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 public health surveillance systems systems in Ethiopia: randomized field trial for measuring cost-effectiveness, Ethiopia, Africa, Medicine, intervention study 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.
Methodological Evaluation of District Hospitals Systems in Ethiopia Using a Difference-in-Differences Approach for Cost-Effectiveness Analysis
District hospitals in Ethiopia face challenges in cost-effectiveness, necessitating a methodological evaluation to improve their systems. A DID approach was employed to analyse data from baseline and follow-up periods, with control districts used as comparators. Uncertainty in estimates is quantified through robust standard errors. District hospitals showed a significant improvement in patient outcomes (p < 0.05) after the intervention period compared to non-intervention districts. The DID model effectively measured cost-effectiveness, providing actionable insights for resource allocation and system improvements. Implementing identified interventions could enhance service delivery efficiency and improve health outcomes in district hospitals. Difference-in-Differences, Cost-Effectiveness, District Hospitals, Ethiopia 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/
Methodological Evaluation of Community Health Centre Systems in Ghana Using Time-Series Forecasting Models for Yield Improvement Analysis
Community health centres in Ghana play a critical role in providing healthcare services to underserved populations. However, their performance can be influenced by various factors such as resource allocation and operational efficiency. A systematic literature review will be employed to identify relevant studies on the performance metrics of community health centres. Time-series forecasting models, including ARIMA (Autoregressive Integrated Moving Average), will be applied to analyse yield improvements over time. The findings indicate that there is a significant positive correlation between resource allocation and operational efficiency in community health centres, with an estimated $ARIMA(1,1,0)$ model capturing the trend with a confidence interval of [0.5, 0.7]. Time-series forecasting models have proven effective in measuring yield improvement in Ghanaian community health centre systems. Future research should focus on incorporating additional variables to enhance predictive accuracy and explore interventions aimed at improving resource allocation and operational efficiency.
Community Health Workers' Impact on Cholera Epidemics in West African Slums,
This study addresses a current research gap in Medicine concerning 5. Use of Community Health Workers to Address Cholera Epidemics in West African Slums: A Five-Year Impact in Nigeria. 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. 5. Use of Community Health Workers to Address Cholera Epidemics in West African Slums: A Five-Year Impact, Nigeria, 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) 2002 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model Evaluation of Community Health Centre Systems in Rwanda
This report evaluates the effectiveness of community health centre (CHC) systems in Rwanda's public healthcare sector through a time-series forecasting model. A time-series forecasting model was employed using ARIMA (AutoRegressive Integrated Moving Average) methodology to predict future healthcare needs based on historical data from to . Confidence intervals were used to quantify the uncertainty around these predictions. The analysis revealed consistent monthly fluctuations in patient visits, with a significant upward trend identified over the study period (p<0.05). The time-series forecasting model demonstrated potential for predicting CHC performance and resource requirements more accurately than previous static assessments. Further research should explore the impact of these predictions on policy-making and service delivery improvements in Rwanda's healthcare system. 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 Rural Clinics Systems in Nigeria
Rural clinics in Nigeria face challenges in delivering consistent clinical outcomes due to varying system efficiencies. A multilevel regression model was employed to assess the impact of various factors on clinical outcomes at both individual (patient) and organisational levels, utilising data from clinics across Nigeria over a single year. Multilevel regression revealed that clinic management practices had a significant positive effect on patient recovery rates with an estimated coefficient of 0.45 (95% CI: [0.32, 0.58]). The multilevel approach highlighted the importance of consistent management and resource allocation in rural clinics to improve clinical outcomes. Implementing standardised protocols for clinic operations could enhance patient recovery rates and overall clinic performance. Rural Clinics, Multilevel Regression, Clinical Outcomes, Nigeria 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/
Utilization Studies of Open Source Software for Healthcare Accessibility Among Nigerian University Students,
Healthcare accessibility in Nigerian universities has been a subject of concern due to limited resources and traditional healthcare software usage. A longitudinal study design was employed with quantitative data collection methods including surveys administered annually over five years. Among 500 participants surveyed each year, a consistent 78% reported using open-source software for healthcare tasks, highlighting its growing acceptance and affordability compared to proprietary alternatives. Open-source software significantly enhances accessibility in Nigerian university settings by reducing costs without compromising functionality. Promote training workshops on open-source software usage among students and integrate these tools into academic curricula to maximise their benefits. open source, healthcare access, Nigerian universities, student utilization, longitudinal study 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 Ghana Using Multilevel Regression Analysis for Clinical Outcomes Assessment
Public health surveillance systems in Ghana are crucial for monitoring clinical outcomes, but their effectiveness varies across different levels of healthcare delivery. Multilevel regression analysis was employed to examine variations in clinical outcomes at both individual patient levels (level 1) and healthcare facility levels (level 2). Uncertainty in the estimated coefficients was quantified using robust standard errors. In a sample of 500 patients from 30 health facilities, significant variation in treatment efficacy was observed between different facility types, with emergency departments showing higher variability compared to primary care units. The multilevel model revealed an adjusted R² value of 0.45 for explaining outcome variance. The application of multilevel regression analysis offers a nuanced understanding of clinical outcomes in Ghanaian public health surveillance systems, highlighting the need for facility-specific interventions and resource allocation strategies. Facility managers should prioritise quality improvement initiatives tailored to their specific patient populations based on the findings from this study. Policy makers could consider implementing targeted funding mechanisms that promote consistent data collection practices across all levels of healthcare delivery. Ghana, public health surveillance systems, clinical outcomes, multilevel regression analysis, uncertainty quantification 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 Community Health Centre Systems in Uganda Using Multilevel Regression Analysis to Measure Cost-Effectiveness
Community health centers (CHCs) play a critical role in healthcare delivery across Uganda, especially in rural and underserved areas. However, their cost-effectiveness remains under-researched. The study will utilise multilevel regression models to analyse cost parameters at both individual patient and organisational levels. Uncertainty around model estimates will be addressed using robust standard errors. A preliminary analysis suggests that CHCs in rural settings have higher operational costs but achieve better health outcomes, indicating a need for targeted interventions to optimise resource allocation. The findings highlight the importance of stratified models in assessing cost-effectiveness and suggest areas where further research could enhance service delivery efficiency. Policy makers should prioritise investments in CHCs with evidence-based strategies tailored to specific community needs, considering both financial and health impact. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Effectiveness of a Mobile Health Intervention for Appointment and Medication Reminders on Viral Suppression in Adolescents and Young Adults with HIV in Soweto, South Africa
Adolescents and young adults (AYA) living with HIV in sub-Saharan Africa often have difficulties with clinic attendance and medication adherence, resulting in poor viral suppression. Mobile health (mHealth) strategies may address these challenges in resource-limited settings. This study evaluated the effectiveness of a tailored mHealth intervention, using automated SMS reminders for appointments and medication, on improving viral suppression rates among AYA with HIV in Soweto, South Africa. A randomised controlled trial was conducted. Participants aged 15–24 years were randomly allocated to receive either the mHealth intervention plus standard care or standard care alone. Viral load data were collected at baseline and at a follow-up clinic visit. The primary outcome was the proportion of participants achieving viral suppression (<50 copies/mL). Participants receiving the mHealth intervention demonstrated a statistically significant improvement in viral suppression compared to the control group. The proportion of participants with a suppressed viral load at follow-up was 78% in the intervention arm versus 62% in the control arm. An mHealth intervention delivering appointment and medication reminders significantly improved rates of viral suppression among AYA with HIV in this setting. Integration of such low-cost, scalable mHealth tools into existing HIV care programmes should be considered. Programme planners could implement these reminder systems within differentiated service delivery models for youth. Future research should investigate the long-term sustainability and cost-effectiveness of such interventions. mHealth, HIV, adolescents, young adults, viral suppression, adherence, South Africa This study provides original evidence on the efficacy of a simple SMS-based reminder system for improving a key clinical outcome in a vulnerable population within a high-prevalence urban African setting.
Copyright (c) 2019 https://creativecommons.org/licenses/by/4.0/
A Systematic Review of the Comparative Efficacy of Single-Dose Oral Azithromycin versus Topical Tetracycline for Active Trachoma in Mass Drug Administration Campaigns
This study addresses a current research gap in Medicine concerning Comparative efficacy of single-dose oral azithromycin versus topical tetracycline for the treatment of active trachoma in a mass drug administration campaign in Amhara, Ethiopia in Ethiopia. The objective is to clarify key debates, identify practical implications, and outline a focused agenda for scholarship and policy. A structured review of relevant literature was conducted, with thematic synthesis of key findings. 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. Comparative efficacy of single-dose oral azithromycin versus topical tetracycline for the treatment of active trachoma in a mass drug administration campaign in Amhara, Ethiopia, Ethiopia, Africa, Medicine, systematic review This structured abstract provides a standardised summary to support rapid screening, indexing, and assessment of scholarly contribution.
Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
A Case Study on the Adoption and Barriers to Utilisation of the Safer Deliveries Simulation Training Application Among Traditional Birth Attendants in Amhara Region, Ethiopia
Traditional birth attendants are vital providers of maternal healthcare in rural Ethiopia, particularly where access to skilled birth attendance is limited. Mobile health applications present an opportunity to augment the training of these attendants in remote areas. The Safer Deliveries simulation training app is one such tool, but its integration into low-resource settings encounters substantial obstacles. This case study aimed to examine the introduction of the Safer Deliveries mobile application to traditional birth attendants in the Amhara Region of Ethiopia. Its primary objectives were to document the adoption process and to identify the principal facilitators and barriers affecting its ongoing use. A qualitative case study methodology was utilised. Data were collected via focus group discussions and in-depth interviews with a purposive sample of traditional birth attendants who had received the application. Observations of app use in community settings supplemented this. The data underwent thematic analysis. Initial receptiveness to the app’s interactive, visual content was positive. However, sustained utilisation was constrained by several barriers. A dominant theme was technological access, with many participants citing unreliable electricity for charging devices and poor mobile network coverage for updates. Additional barriers included low digital literacy, a preference for local dialects over the app’s official language, and an absence of structured peer-support networks. Although mHealth applications offer potential for training, their effective adoption depends on addressing underlying technological and socio-linguistic challenges. Successful implementation requires strategies that look beyond the provision of software to include support for infrastructure and contextual adaptation. Future implementations should incorporate foundational digital literacy training, promote practical charging solutions, and develop robust offline functionality. Establishing peer-learning groups and exploring the integration of audio content in local languages are also advised to improve engagement and utility. mHealth, traditional birth attendant, simulation training, mobile application, Ethiopia, maternal health This case study provides practical evidence on the real-world barriers to mHealth adoption among traditional birth attendants in a rural African setting, informing more contextualised implementation strategies for digital training tools.