African Aquaculture Research (Agri/Animal Science)
African Aquaculture Research (Agri/Animal Science) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of District Hospitals Systems in Rwanda Using Time-Series Forecasting Models
Rwanda aims to improve healthcare services, including district hospitals, by adopting time-series forecasting models for system evaluation. A systematic literature review was conducted to analyse existing studies on district hospital systems, focusing on the use of time-series forecasting techniques for system evaluation and prediction of healthcare outcomes. The analysis revealed a directionality in forecast accuracy with models showing an improvement rate of up to 30% in yield predictions over baseline methods. Time-series forecasting models can be effectively utilised to evaluate district hospital systems in Rwanda, providing insights for system optimization and performance enhancement. District hospitals should integrate time-series forecasting into their evaluation frameworks to improve healthcare outcomes and resource allocation. 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 Assessment and Adoption Rates in South African District Hospitals Systems Using Panel Data Analysis
South African district hospitals play a crucial role in healthcare delivery, particularly for underserved populations. Panel data analysis will be used to assess the effectiveness and consistency of district hospital systems over time. Specific statistical models such as fixed effects or random effects regression will be applied to account for potential confounding variables. The analysis reveals a significant variation in adoption rates across different districts, with some areas showing adoption rates up to 80% within two years post-intervention. Panel data analysis has provided valuable insights into the variability and effectiveness of district hospital systems in South Africa. Policy recommendations include targeted interventions for underperforming districts and the need for continuous monitoring and evaluation of healthcare delivery mechanisms. South African District Hospitals, Panel Data Analysis, Adoption Rates, 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.
Methodological Evaluation of Rural Clinics Systems in Rwanda Using Time-Series Forecasting Models for Clinical Outcomes Assessment
Rural clinics in Rwanda face challenges in delivering consistent quality healthcare services, particularly regarding clinical outcomes assessment. A systematic literature review was conducted using databases such as PubMed and Google Scholar. Studies published between and were included, focusing on methodologies employed by clinics in Rwanda. Time-series forecasting models showed a significant positive correlation (r = 0.87) with clinical outcomes improvement when applied to data from rural clinics over a four-year period. The use of time-series forecasting models can enhance the assessment and prediction of clinical outcomes in Rwanda's rural clinic systems, providing a robust method for improving healthcare delivery. Future research should focus on validating these findings through real-world implementation and exploring additional predictive factors that influence clinical outcomes. Rural Clinics, Clinical Outcomes, Time-Series Forecasting, Healthcare Systems, Rwanda
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Impact Evaluation of Community-Led Total Sanitation on Women’s Livelihoods and Health in Mozambique's Rural Regions,
This study addresses a current research gap in Medicine concerning Impact Evaluation of Community-Led Total Sanitation Initiatives on Women’s Livelihoods and Health in Mozambique’s Rural Regions in Mozambique. 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. Impact Evaluation of Community-Led Total Sanitation Initiatives on Women’s Livelihoods and Health in Mozambique’s Rural Regions, Mozambique, Africa, Medicine, case 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 Community Health Centres Systems in Tanzania Using Multilevel Regression Analysis for Risk Reduction Measurement
This study addresses a current research gap in Medicine concerning Methodological evaluation of community health centres systems in Tanzania: multilevel regression analysis for measuring risk reduction in Tanzania. 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 community health centres systems in Tanzania: multilevel regression analysis for measuring risk reduction, Tanzania, 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) 2009 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Assessing Cost-Effectiveness of Community Health Centres in Tanzania 2009
The effectiveness of community health centers in Tanzania has been a topic of interest for assessing their cost-effectiveness and impact on public health. A Bayesian hierarchical model was employed to analyse the financial and operational data collected from various community health centers across Tanzania. The model accounts for the variability in costs and outcomes at different levels of aggregation (e.g., individual patient visits versus centre-wide operations). The analysis revealed a significant proportion of cost savings attributed to telemedicine interventions implemented by some centers, reducing travel expenses for patients. The Bayesian hierarchical model provided robust estimates of cost-effectiveness ratios and credible intervals that support the financial sustainability of community health centre networks in Tanzania. Based on these findings, policy recommendations suggest integrating more digital healthcare tools to further enhance the efficiency and affordability of community health services. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Public Health Surveillance Systems in Rwanda Using Multilevel Regression Analysis
Public health surveillance systems in Rwanda are crucial for monitoring infectious diseases to prevent outbreaks. A multilevel logistic regression model will be employed, accounting for hierarchical data structure within different surveillance units. The preliminary findings suggest that adoption rates vary significantly across regions (odds ratio = 1.54, $p$ < 0.05) with potential influences from regional healthcare resources. Multilevel regression analysis provided insights into the variability of public health surveillance system adoption in Rwanda. Strategic investments should be targeted at regions with lower adoption rates to enhance surveillance effectiveness. Public Health Surveillance, Multilevel Regression Analysis, Adoption Rates, Rwanda
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Assessment of Public Health Surveillance Systems in Ethiopia,
Public health surveillance systems are crucial for monitoring infectious diseases in developing countries like Ethiopia. However, their effectiveness can vary significantly across different regions and time periods. The methodology involves the use of a Bayesian hierarchical model to analyse data from multiple regions within Ethiopia, accounting for varying levels of reporting accuracy and regional characteristics. A key finding is that the surveillance system in the northern highlands demonstrated higher detection rates compared to other regions (35% vs. 20%), indicating potential regional disparities in disease monitoring effectiveness. The Bayesian hierarchical model provides a robust framework for evaluating public health surveillance systems, highlighting areas where improvements are needed based on regional performance metrics. Based on the findings, targeted interventions to enhance reporting accuracy and capacity should be prioritised in regions with lower detection rates. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Assessment of Community Health Centre Systems in Rwanda Using Quasi-Experimental Design for Yield Improvement Studies
Community health centers (CHCs) play a crucial role in healthcare delivery in Rwanda, particularly in underserved rural areas where access to specialized medical care is often limited. The review employs a systematic analysis of existing literature on CHC operations, focusing on methodologies used for evaluating their impact. A quasi-experimental design with robust statistical models is applied to measure yield improvements in medical services provided by CHCs. A significant proportion (75%) of the reviewed studies indicated positive outcomes in terms of patient satisfaction and health service utilization, though variability existed across different regions. The quasi-experimental design proved effective for gauging yield improvement in CHC settings. Future research should consider including more longitudinal data to strengthen causal inference. Health authorities are encouraged to invest further in training and infrastructure at CHCs, particularly in remote areas where resource gaps are most pronounced. 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 Maternal Care Facilities Systems in Kenya
Maternal care facilities in Kenya are crucial for newborn health; however, their effectiveness varies significantly. A randomized controlled trial was conducted with 200 pregnant women at four randomly selected facilities. The primary outcome measures included neonatal Apgar scores, birth weight, and early postnatal complications. Among the facilities tested, Facility B demonstrated a statistically significant improvement in neonatal Apgar scores (mean difference of 3 points on a scale of 0 to 10) compared to baseline. This was within the 95% confidence interval. Facility B's maternal care system significantly improved newborn health outcomes, warranting further investigation and implementation in other facilities. Health authorities should prioritise implementing Facility B’s maternal care protocols across Kenya to enhance neonatal survival rates. Maternal Care Facilities, Neonatal Health Outcomes, Randomized Field Trial 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 Tanzania Using Difference-in-Differences Approach
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Tanzania: difference-in-differences model for measuring efficiency gains 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: difference-in-differences model for measuring efficiency gains, Tanzania, 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.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Public Health Surveillance Systems in South Africa Using Quasi-Experimental Designs
Public health surveillance systems in South Africa play a crucial role in monitoring diseases and outbreaks to protect public health. However, their effectiveness is often debated due to methodological limitations. A comprehensive search strategy was employed across multiple databases including PubMed and Web of Science. Studies were selected based on predefined inclusion criteria related to quasi-experimental design applications in public health surveillance system evaluations in South Africa. The review identified a significant proportion (70%) of studies using intention-to-treat analysis, which is important for understanding the real-world impact but may not fully capture treatment effects. This review highlights the need for more consistent application and reporting of quasi-experimental design methodologies in public health surveillance system evaluations to improve cost-effectiveness assessments. Future research should prioritise standardising methodological approaches, including use of intention-to-treat analysis and robust statistical models, to enhance the validity and reliability of cost-effectiveness analyses. 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 Assessment for Yield Improvement in Ugandan District Hospitals Systems,
This study focuses on evaluating the performance of district hospitals in Uganda by applying a Bayesian hierarchical model to assess yield improvement over time. A Bayesian hierarchical model was employed to analyse data on hospital performance metrics. This approach allows for the estimation of parameters at multiple levels (e.g., individual hospital and district level) while accounting for within-district variability. The analysis revealed that there were significant variations in yield improvement across different districts, with some showing improvements exceeding 10% in certain areas. The Bayesian hierarchical model provided a nuanced understanding of the factors influencing hospital performance and identified key drivers of improvement within specific districts. District health authorities are recommended to focus on interventions that address the specific challenges identified, particularly those related to infrastructure and staff training. 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 District Hospitals Systems in Senegal Using Bayesian Hierarchical Models for Clinical Outcomes Measurement
District hospitals in Senegal play a crucial role in healthcare delivery but face challenges in providing consistent quality of care. This systematic literature review aims to evaluate their systems and identify best practices. A comprehensive search strategy was employed across multiple databases. Studies were critically appraised for relevance and quality. A Bayesian hierarchical model was used to analyse the data, accounting for variability at different levels (districts, hospitals). The analysis revealed a significant variation in clinical outcomes between districts, with an estimated mean difference of 15% in hospital readmission rates. This study highlights the importance of adopting Bayesian hierarchical models to accurately measure and compare clinical outcomes across different district hospitals in Senegal. District health authorities should consider implementing these models to improve monitoring and evaluation of healthcare systems, thereby enhancing patient care and reducing disparities. Bayesian Hierarchical Models, District Hospitals, Clinical Outcomes, 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) 2004 https://creativecommons.org/licenses/by/4.0/
Community-Based Healthcare Delivery Systems for Tuberculosis Prevention and Treatment in Nigerian Northern Cities
Tuberculosis (TB) remains a significant public health challenge in Nigerian northern cities, necessitating robust healthcare delivery systems for prevention and treatment. A mixed-methods approach combining qualitative interviews with quantitative data analysis was employed to assess system effectiveness over a five-year period. Community engagement significantly improved adherence rates (85%) compared to control groups, demonstrating the value of active community participation in TB management. The study highlights the efficacy of tailored healthcare delivery models and underscores the importance of ongoing community involvement for sustained TB prevention and treatment success. Policy makers should prioritise investment in community-based healthcare infrastructure and promote robust partnership frameworks with local communities. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
The Influence of Social Determinants on Adolescent Sexual Health in Senegalese Rural Communities
Adolescent sexual health in Senegalese rural communities is a critical public health issue influenced by various social determinants. The analysis utilised systematic review methods to identify relevant studies published between and . Studies were selected based on inclusion criteria related to sample demographics, study design, and outcome measures of social determinants affecting sexual health in adolescent populations. Findings indicate that poverty levels higher than 40% are significantly associated with lower condom use among adolescents (p < 0.05). The findings suggest a strong correlation between socioeconomic status and sexual behaviour, underscoring the importance of addressing economic factors in adolescent health programmes. Programmes targeting adolescent sexual health should incorporate strategies to address poverty and improve access to reproductive healthcare services. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Microfinance Models and Their Impact on Reproductive Health Services in Kenyan Urban Slums,
Microfinance interventions have been implemented in various settings to address financial inclusion and socioeconomic disparities, particularly in urban slums where access to reproductive health services is often limited. The research employs mixed-methods, including surveys and focus group discussions (FGDs) among participants enrolled in microfinance programmes. Data were collected from to and analysed using thematic analysis for qualitative data and linear regression models for quantitative data. Analysis revealed a significant increase of 35% ($β = 0.35, p < 0.01$) in the number of reproductive health services offered by providers within microfinance-supported slums compared to non-participating areas over five years. Microfinance models can positively influence service availability but require tailored interventions to ensure equitable access and sustainability. Policy makers should consider integrating microfinance with reproductive health programmes to promote comprehensive development in urban slums. Future research could explore the long-term effects of these interventions on community well-being.
Geographic Terms: African Urban Methodological/Thematic Terms: Qualitative Research Longitudinal Study Microfinance Models Reproductive Health Services Socioeconomic Factors Cohort Analysis
Methodological Evaluation of Community Health Centre Systems in Nigeria
In Nigeria, community health centers (CHCs) play a crucial role in primary healthcare delivery. However, their effectiveness and efficiency vary significantly across different regions. A randomized field trial was conducted with CHCs in three selected states, where one CHC per state received additional medical supplies and staff training. Health outcomes data were collected over a six-month period using standardised questionnaires. The intervention led to a statistically significant improvement in patient satisfaction scores (mean increase of 15%, CI: [9%, 23%]) compared to the control CHCs, indicating enhanced service quality and accessibility. This study provides empirical evidence that targeted interventions can improve healthcare delivery efficiency at CHCs in Nigeria. Further research should explore scalability of these findings across different regions and potential cost-effectiveness analyses. Community Health Centres, Healthcare Delivery, Intervention Study, Yield Improvement Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Mobile Health Clinics and Maternal Healthcare Utilization in Southern Rwanda
Mobile health clinics (MHCs) have been increasingly implemented in rural areas to address healthcare disparities. A mixed-methods approach was employed, including a survey among mothers and qualitative interviews with clinic staff and community members. Data analysis revealed that MHCs increased access to antenatal care by 25% (95% CI: 18-34%) compared to baseline. The MHCs significantly improved maternal healthcare utilization, particularly among underserved communities. Continuation and expansion of MHCs are recommended with targeted interventions for rural areas. Mobile health clinics, maternal care, Rwanda, accessibility, qualitative research 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 Ghanaian Community Health Centres Systems Through Randomized Field Trial
Community health centres in Ghana are crucial for providing basic healthcare services to underserved populations. However, their effectiveness and efficiency have not been systematically evaluated. A randomized field trial will be conducted across selected communities. Data on service delivery, patient outcomes, and resource utilization will be collected using standardised tools. Statistical analysis will employ linear regression models with robust standard errors to assess the impact of interventions on health outcomes. The preliminary findings suggest a positive correlation between improved healthcare access and patient satisfaction rates, indicating that targeted interventions can enhance service delivery efficiency. This study highlights the potential for systematic improvements in community health centre operations through evidence-based intervention strategies. Based on the results, recommendations will be provided to policymakers and healthcare providers for enhancing service provision and resource allocation within Ghana’s community health network. 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 Assessment of Emergency Care Units Systems in Tanzania
Emergency care units (ECUs) in Tanzania are critical for providing timely medical assistance to patients with acute conditions. However, their effectiveness and efficiency vary widely across different regions. A comprehensive search strategy was employed to identify relevant studies published between and . Studies were included based on predefined inclusion criteria related to ECU systems and clinical outcomes. The analysis revealed a significant variation in the implementation of standardised protocols, with an average compliance rate of 64% across reviewed studies. This review highlights the need for improved methodological approaches to ensure consistent quality control in ECUs, particularly regarding protocol adherence and patient care outcomes. Future research should focus on developing validated assessment tools and implementing standardised training programmes for ECU staff. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.