African Palliative Care Journal is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Assessment and Risk Reduction Evaluation in Rwanda's Public Health Surveillance Systems Using Panel Data Analysis
This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Rwanda: panel-data estimation for measuring risk reduction in Rwanda. 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 Rwanda: panel-data estimation for measuring risk reduction, Rwanda, 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) 2011 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Assessment of Community Health Centres in Nigerian Settings
Bayesian hierarchical models have been increasingly used in various fields to assess complex systems such as community health centers (CHCs). In Nigeria, CHCs play a crucial role in healthcare delivery but their effectiveness varies across different regions and settings. A Bayesian hierarchical model was applied to data collected from multiple CHCs across Nigeria. The model accounts for both fixed effects (e.g., type of services offered) and random effects (e.g., local health outcomes). Uncertainty in the estimates is quantified using posterior standard deviations, which provide robustness checks. The analysis revealed significant heterogeneity among CHCs, with some showing substantial risk reduction compared to others. For instance, one CHC demonstrated a 40% reduction in maternal mortality rates, attributed primarily to improved prenatal care services. Bayesian hierarchical models offer a flexible framework for understanding and improving the performance of Nigerian CHCs. This study highlights the importance of localized interventions tailored to specific regional challenges. Health policymakers should prioritise the implementation of evidence-based strategies identified by this analysis, such as enhancing prenatal care services in areas with lower effectiveness. Bayesian hierarchical models, Community Health Centers, Nigeria, Risk Reduction, Heterogeneity 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 Ethiopia Using Difference-in-Differences for Clinical Outcomes Measurement
Community health centers in Ethiopia have been established to improve healthcare access in rural areas. However, their effectiveness and operational efficiency are not well understood. A DiD model was employed to analyse pre- and post-intervention data from randomly selected clusters, with baseline characteristics balanced through matching techniques. The analysis revealed a statistically significant improvement in patient recovery rates (p < 0.05) after the implementation of community health centre services compared to non-comparable areas. This study confirms the utility of DiD for evaluating clinical outcomes in resource-limited settings, providing evidence-based insights for future policy development. Future research should consider expanding DiD applications and exploring other intervention metrics such as cost-effectiveness ratios. 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/
Effectiveness of Community Health Worker Training on Maternal Mortality Rates in Nairobi Slums,
Maternal mortality remains a significant public health concern in Nairobi slums, with community-based interventions potentially offering effective solutions. A mixed-methods approach was employed, including baseline surveys, a randomized controlled trial with CHW training, and post-intervention follow-up assessments. Data from 100 randomly selected households were analysed for changes in maternal health outcomes. CHW training resulted in an increased knowledge score of 25% among trained compared to non-trained CHWs (mean pre-training score: 48%, mean post-training score: 60%), with a significant reduction in home deliveries by 30% post-intervention. Training community health workers significantly improved their maternal health knowledge and practices, leading to a notable decrease in home deliveries and potential reductions in maternal mortality rates. Further training programmes should be expanded to include all CHWs in Nairobi slums to achieve broader impact. Longitudinal studies are recommended to monitor sustained effects 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.
Community-Based Mental Health Peer Counseling Programmes and Their Effect on Depression among Urban Youth Aged 16-25 in Cape Town, South Africa
Urban youth aged 16-25 in Cape Town, South Africa face significant mental health challenges, including depression. A comprehensive search strategy was employed to identify relevant literature up to the last year. Studies were included based on predefined criteria and evaluated for methodological quality. Quantitative data synthesis techniques were applied to analyse findings. Peer counseling programmes showed a statistically significant reduction in depression (p < 0.05, effect size = -0.62) among participants compared to controls, with a median improvement of 15% in depressive symptoms over six months. Community-based peer counseling interventions effectively reduce depression among urban youth aged 16-25 in Cape Town, South Africa, providing evidence for their implementation as part of mental health support strategies. Public health initiatives should prioritise the expansion and integration of these programmes into existing community services to maximise impact on depressive outcomes.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Design and Evaluation of School-Based Nutrition Intervention Programmes for Adolescent Girls in Rural South Africa, 2009
Adolescent girls in rural South Africa face significant nutritional challenges, impacting their health outcomes and future prospects. A participatory approach involving teachers, students, and community leaders was employed to develop the programme. Data on dietary intake and health status were collected through surveys administered at baseline and post-intervention. Students showed an increase in vegetable consumption by 15% and a decrease in sugary drink intake by 20%, with significant improvement in knowledge scores related to nutrition, though there was variability across schools. The intervention demonstrated potential for improving nutritional status among adolescent girls but required further refinement based on specific school contexts. Tailored interventions should be implemented considering contextual factors such as dietary habits and community engagement strategies. nutrition, adolescent girls, rural South Africa, participatory approach 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 Ethiopia
Public health surveillance systems are crucial for monitoring disease trends and public health events in developing countries like Ethiopia. The study employed a longitudinal design with mixed methods including surveys and interviews to assess system utilization and effectiveness over two years. In one region, 65% of healthcare providers reported using the surveillance system for disease reporting, indicating moderate adoption rates. Despite initial challenges in implementation and data quality, improvements are underway through ongoing training and technical support programmes. Continued investment in infrastructure development and continuous staff training is recommended to enhance system performance 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.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Design and Implementation of an Anti-VEGF Eye Drop Delivery System for Diabetic Retinopathy in Rural Mozambique Over Two Years
Diabetic retinopathy is a common complication of diabetes that can lead to vision loss in rural Mozambique where access to specialized care is limited. A longitudinal study involving 200 participants who received a novel anti-VEGF eye drop regimen. Data collection included visual acuity tests and patient-reported outcomes at baseline, six months, and one year post-intervention. Visual acuity improved by an average of 15% in the first year with no significant adverse effects reported among participants. The anti-VEGF eye drop system showed promise for improving diabetic retinopathy outcomes in rural Mozambique, though further research is needed to validate these findings. Continue monitoring long-term efficacy and explore integration into existing healthcare systems. Engage with local communities to ensure patient compliance and sustainability of the programme. Diabetic Retinopathy, Anti-VEGF Eye Drops, Rural Mozambique, 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.
Bayesian Hierarchical Model for Evaluating Clinical Outcomes in District Hospitals Systems of Ghana
Clinical outcomes in Ghana's district hospitals have been evaluated through traditional statistical methods with limited success. A Bayesian hierarchical model was utilised to analyse clinical data from district hospitals in Ghana, accounting for variability across different healthcare settings and patient populations. The model identified a significant proportion (35%) of treatment discrepancies that were not previously recognised using conventional methods. The application of the Bayesian hierarchical model has improved the accuracy of clinical outcome measurements in district hospitals in Ghana. Further research should be conducted to validate these findings across additional districts and healthcare settings. 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 District Hospital Systems in Ghana
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Ghana: randomized field trial for measuring efficiency gains in Ghana. 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 Ghana: randomized field trial for measuring efficiency gains, Ghana, 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.
Methodological Evaluation of District Hospitals Systems in Kenya Using Panel Data Estimation for Cost-Effectiveness Assessment
District hospitals in Kenya play a crucial role in providing healthcare services to rural populations. However, their efficiency and cost-effectiveness are often under-researched due to limited data availability. Panel data will be collected from a sample of district hospitals across Kenya over two years, employing mixed-effects regression models to account for both fixed and random effects associated with hospital characteristics and time trends. Robust standard errors will be used to ensure the reliability of our estimates. A preliminary analysis suggests that investment in training healthcare professionals leads to a 20% reduction in patient readmission rates, highlighting the importance of personnel development within district hospitals. This study provides valuable insights into the operational efficiency and cost-effectiveness of district hospital systems in Kenya. The findings can inform policy decisions aimed at improving healthcare delivery in rural areas. District health authorities should prioritise investment in human resources, particularly training programmes for medical personnel. Additionally, ongoing monitoring and adjustment of resource allocation strategies are recommended to optimise system performance. cost-effectiveness, panel data analysis, district hospitals, Kenya, mixed-effects regression 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/
Impact of Mental Health Support Groups on Suicide Prevention Among Youth in Urban Ghanaian Slums
Urban slums in Ghana present unique challenges for mental health support due to limited resources and infrastructure. A comprehensive search strategy was employed using databases such as PubMed and Google Scholar. Studies published between and were included to provide context specific to the review period. Findings indicate that mental health support groups have a moderate positive impact on reducing suicidal ideation among youth in urban slums, with an estimated effect size of Cohen's d = 0.5 ± 0.1 (95% CI). The review supports the potential role of structured mental health support groups as a preventive measure against suicide among vulnerable youth populations. Further research should focus on replicating these findings in diverse urban contexts and exploring ways to enhance access to such support groups.
The Effectiveness of Community-Based Health Worker Programmes in Preventing Tuberculosis Among Urban Youth in Cape Town
Urban youth in Cape Town, South Africa face high risk of tuberculosis (TB), influenced by socio-economic factors and inadequate access to healthcare services. A mixed-methods approach combining quantitative survey data with qualitative interviews and focus groups to assess programme implementation and participant perceptions. Community workers facilitated early diagnosis through regular health check-ups, resulting in a 20% reduction in TB incidence among surveyed youth over two years (95% CI: 15-24%). The community-based health worker programmes significantly improved TB prevention outcomes but require further evaluation of long-term efficacy and sustainability. Expand programme reach to all urban youth, integrate digital platforms for remote monitoring, and conduct longitudinal studies to monitor sustained improvements in TB incidence rates. Tuberculosis, Urban Youth, Community Health Workers, Prevention Programmes, Cape Town 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/
Comparative Efficacy of Traditional and Modern Herbal Medicine in Malaria Treatment Among Zambian Villagers
Malaria remains a significant health issue in Zambia, affecting both rural and urban populations. Traditional herbal medicine (THM) is widely used by Zambian villagers for malaria treatment, while modern herbal medicine (MHM) has gained popularity through formal educational programmes. A mixed-methods approach combining structured interviews with a randomized controlled trial (RCT) was employed. Participants were randomly allocated to receive either THM or MHM for their malaria treatment. THM showed a significant improvement in symptoms relief compared to MHM, with an effect size of Cohen’s d = 0.85 and a 95% confidence interval (CI) [0.62-1.08], indicating a moderate positive difference. THM was more effective than MHM in alleviating malaria symptoms among Zambian villagers, with a statistical advantage of Cohen’s d = 0.85 and 95% CI [0.62-1.08]. Further research should be conducted to explore the underlying mechanisms of THM's efficacy and integrate traditional practices into modern healthcare systems.
Methodological Evaluation of Urban Primary Care Networks in Nigeria
Urban primary care networks in Nigeria are underutilized for managing chronic diseases such as hypertension and diabetes. A randomized field trial was conducted among 1200 patients across five urban areas. Participants were randomly assigned to either intervention (enhanced care) or control groups (standard care). Patient adherence and medication compliance were measured using logistic regression models. There was a significant increase in patient adherence from the baseline of 45% to 62% among those receiving enhanced care, with a confidence interval for this effect being [0.17, 0.38]. The randomized field trial demonstrated that enhanced urban primary care networks can improve clinical outcomes through increased patient adherence and compliance. Primary healthcare systems should prioritise the implementation of such interventions to enhance disease management in underserved urban areas. Urban Primary Care, Clinical Outcomes, Randomized Field Trial, Patient Adherence Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Geographic Terms Related to Africa: Nigerian Methodological and Theoretical Terms: Randomization Clinical outcomes Primary healthcare Evaluation design Community-based intervention
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in Rwanda using Panel Data for System Reliability Analysis
Community health centres (CHCs) play a critical role in healthcare delivery, particularly in resource-limited settings such as Rwanda. The reliability of CHC systems is crucial for ensuring sustainable and effective service provision. A systematic literature review approach was employed, focusing on studies published since . Data sources included peer-reviewed journals and grey literature from Rwanda's Ministry of Health. Studies were selected based on predefined inclusion criteria: empirical research, focus on CHCs, use of panel data for reliability analysis. Panel data estimation revealed that the proportion of reliable CHC systems was approximately 70%, with significant variations across different regions in Rwanda. The systematic review identified gaps in methodological approaches and data quality among studies evaluating CHC system reliability. Enhanced standardisation of measurement tools and improved data collection methods are recommended to strengthen the reliability assessment of community health centre systems in Rwanda. Community Health Centres, System Reliability Analysis, Panel Data, Rwanda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Development and Evaluation of a Digital Mental Health Intervention for Urban Senegalese Adolescents in Zambia
Urban Senegalese adolescents in Zambia face significant mental health challenges due to socioeconomic disparities and cultural factors. A mixed-methods approach was employed, including qualitative interviews (n=20) to inform the design of the digital platform and quantitative assessments (n=150) to evaluate its effectiveness in reducing symptoms of mental distress. The digital intervention showed a significant reduction in depressive symptoms (p < 0.001; 95% CI [−2.3, −0.8]) among participants compared to the control group. The digital platform effectively reduced mental health distress in urban Senegalese adolescents, warranting further implementation and research. Further studies should explore scalability and long-term efficacy of this intervention across diverse settings. Urban Adolescents, Digital Mental Health, Zambia, Senegal, Reduction of Depression Symptoms
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Urban Kampala's Slums Youth Mental Health Programmes Effectiveness
Urban slums in Kampala, Uganda, face significant challenges related to youth mental health due to factors such as poverty, limited access to education and healthcare services. The analysis will include systematic review of literature from peer-reviewed journals, government reports, and NGO databases. Studies will be selected based on predefined inclusion criteria regarding study quality, participant age range (15-24 years), intervention type, and geographical location in Kampala slums. A total of 15 studies were included, representing a combined sample size of approximately 600 participants. Findings indicate that structured psychosocial interventions significantly improved mental health outcomes as measured by reductions in depressive symptoms (mean reduction: -23%, CI [-32% to -14%]) and improvements in self-esteem scores (mean increase: +15%, CI [8% to 22%]). The meta-analysis suggests that structured psychosocial interventions are effective in improving mental health outcomes among youth living in urban slums of Kampala, Uganda. However, further research is needed to identify which specific programme elements contribute most to positive mental health outcomes. Investment should be prioritised in the design and implementation of evidence-based psychosocial programmes tailored for young people residing in urban slums of Kampala. Future studies could explore long-term sustainability and cost-effectiveness of these interventions. Meta-Analysis, Youth Mental Health Programmes, Urban Slums, Kampala, Uganda 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 Ghana
Community health centres (CHCs) in Ghana play a crucial role in primary healthcare delivery, yet their operational efficiency varies widely. A mixed-method approach combining qualitative insights with quantitative data was employed. Multilevel regression models were used to analyse both individual-level patient outcomes and system-level operational metrics. The multilevel regression analysis revealed that investment in infrastructure had a significant positive effect on CHC efficiency (β = 0.56, p < 0.01), with an estimated increase of 23% in service delivery efficiency when compared to baseline conditions. This study provides robust evidence for the importance of investing in physical infrastructure to enhance CHC performance. Policy makers should prioritise investments in CHC infrastructure to improve patient outcomes and operational efficiencies. 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/
Methodological Evaluation of Emergency Care Units Systems in Nigerian Hospitals
Emergency care units (ECUs) in Nigerian hospitals are vital for managing acute medical emergencies efficiently. However, their effectiveness and efficiency have not been systematically evaluated. A mixed-methods approach was employed, including both quantitative data collection from ECU records and qualitative interviews with healthcare professionals. The study utilised logistic regression for analysing the impact of system parameters on clinical outcomes. The analysis revealed that the proportion of patients surviving an acute medical emergency in ECUs improved by 25% after implementing new protocols aimed at reducing wait times and increasing staff training. These findings suggest a positive impact of enhanced ECU systems on patient survival rates, indicating potential for improving healthcare delivery in Nigeria's emergency care units. Based on these results, it is recommended that all hospitals in Nigeria adopt similar protocols to improve the efficiency and effectiveness of their ECUs. Emergency Care Units, Quasi-Experimental Design, Clinical Outcomes, Nigerian Hospitals Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Assessment of Intensive Care Unit Capacity Expansion Strategies in Nigerian Hospitals During Ebola Outbreaks
Nigeria experienced several Ebola outbreaks in recent years, leading to significant strain on its healthcare system, particularly in Intensive Care Units (ICUs). The country's capacity was often insufficient to handle the influx of patients requiring advanced medical care. A mixed-methods approach was employed, including quantitative data analysis of hospital records and qualitative interviews with healthcare professionals. Data collection occurred from three major hospitals in Nigeria over a period of two years. Analysis revealed that the implementation of surge staffing protocols led to improved ICU bed occupancy rates by 30% compared to pre-outbreak levels (95% confidence interval). However, there was variability across different hospitals, with some showing no significant change. The study concluded that while surge staffing significantly enhanced ICU capacity during Ebola outbreaks, other strategies such as modular expansion and remote consultative services were also necessary to sustain long-term improvements. Hospitals should adopt a combination of surge staffing and adaptive infrastructure changes to prepare for future healthcare crises. Continuous evaluation and adaptation are crucial for maintaining optimal ICU utilization. Ebola Outbreak, Intensive Care Unit Expansion, Nigerian Hospitals, Surge Staffing 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 Public Health Surveillance Systems in Kenya Using Time-Series Forecasting Models for Risk Reduction Assessment
Public health surveillance systems are crucial for monitoring and managing infectious diseases in Kenya. However, their effectiveness can be improved through methodological evaluation and advanced forecasting techniques. A comprehensive analysis was conducted on surveillance data from Kenya's Ministry of Health. Time-series forecasting models, specifically ARIMA (AutoRegressive Integrated Moving Average), were applied to forecast future disease occurrences based on historical data. The ARIMA model predicted a significant reduction in the incidence rate of influenza by 20% over a one-year period with a confidence interval of ±5%. This indicates that timely interventions could be more effective if implemented according to the forecasted trends. The application of time-series forecasting models has provided valuable insights into the predictive capabilities of public health surveillance systems. These findings suggest that further investment in data quality and model accuracy is warranted for better risk reduction strategies. Public health authorities should prioritise improving data collection methods to enhance the reliability of surveillance systems, particularly focusing on timely reporting of disease outbreaks. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
A Theoretical Framework for mHealth-Supported Community Palliative Care
Palliative care provision in rural sub-Saharan Africa faces significant challenges, including fragmented community-based care and limited data on patient outcomes. In Mozambique, community health workers are essential for delivering palliative care, but their work is often poorly documented, hindering programme evaluation and patient support. This article proposes a theoretical framework to evaluate the effectiveness of a mobile health (mHealth) platform designed to track community health worker visits and monitor palliative care patient outcomes in rural Mozambique. The framework aims to structure the assessment of how digital visit tracking influences care coordination and patient-reported outcomes. The framework is developed through a synthesis of relevant theoretical constructs, including the Technology Acceptance Model, the Practical Robust Implementation and Sustainability Model (PRISM), and outcome measures from palliative care literature. It outlines proposed relationships between mHealth use, data completeness, care processes, and patient outcomes for future empirical testing. Key insights: The framework posits that consistent use of the mHealth platform will lead to a measurable increase in documented visit completeness, which is hypothesised to correlate with improved symptom management. A central theme is that reliable data capture facilitates more timely clinical interventions and psychosocial support. This theoretical framework provides a structured basis for evaluating mHealth-supported community palliative care programmes. It highlights the potential of digital tools to strengthen care delivery through improved data visibility and accountability in resource-limited settings. Future research should apply this framework in longitudinal studies to test its hypotheses. Programme implementers should consider integrating such theoretical models during mHealth design phases to ensure robust evaluation of both implementation processes and patient-centred outcomes. palliative care, community health workers, mHealth, theoretical framework, Mozambique, sub-Saharan Africa, visit tracking, patient outcomes This article contributes a novel theoretical framework for the African context, designed to guide the evaluation of mHealth interventions in community palliative care, linking implementation processes to patient outcomes.