African Food Systems Research (Interdisciplinary - incl Agri/Env)
African Food Systems Research (Interdisciplinary - incl Agri/Env) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Feeding Dependency or Restoring Production? Food Sovereignty and the Political Economy of Rural Recovery in South Sudan
Agricultural collapse in conflict-affected states is often attributed to environmental stress or technical failure, yet in South Sudan it reflects deeper political and institutional processes. Successive cycles of conflict, displacement, and aid dependence have systematically dismantled rural livelihoods and productive systems. This study examines how politically produced agricultural decline shapes political order from the liberation period to the present, with comparative reference to Mozambique and Rwanda. Drawing on agrarian political economy, food sovereignty, livelihoods analysis, and the conflict–agriculture nexus, the study combines longitudinal analysis of agricultural and food security data with political economy fieldwork, interviews with farmers and officials, and cross-case comparison. The findings show that agricultural collapse is not a short-term crisis but a durable outcome of institutional and political dynamics that reshape incentives, authority, and access to land, labour, and markets over time (Bernstein 2010; McMichael 2013; Scott 1976; Chambers & Conway 1992). Conflict-driven displacement, weakened governance, and reliance on humanitarian systems disrupt production while reinforcing dependency. Variation across cases highlights the importance of political settlement, land governance, and state support in enabling recovery. The contribution lies in linking agricultural decline to the broader political economy of conflict, demonstrating that rebuilding rural livelihoods requires more than technical intervention. Durable recovery depends on institutional reform, political bargaining, and accountability mechanisms that address the underlying distribution of power (DFID 1999; FAO 2023; WFP 2024; de Waal 1997).
Copyright (c) 2026 African Food Systems Research (Interdisciplinary - incl Agri/Env)
Mobile Health Monitoring Platforms Among Urban Youth with Chronic Diseases in Egypt
Urban youth in Egypt face significant health challenges due to chronic diseases such as diabetes and hypertension. Current monitoring methods are often insufficiently accessible or effective for this demographic. A mixed-methods approach including surveys, interviews, and pilot testing was employed to evaluate user experience and platform functionality. Data were analysed using descriptive statistics and thematic analysis. Among the 150 participants surveyed, 82% expressed willingness to use mobile health monitoring platforms for their chronic conditions, highlighting a high potential for acceptance in urban youth settings. The system's reliability was tested with a mean error rate of ±3%, indicating acceptable precision. The preliminary results suggest that mobile health monitoring platforms are viable and well-received by urban youth living with chronic diseases in Egypt. Further research is warranted to validate these findings and explore scalability. Future studies should focus on developing culturally adapted versions of the platform, conducting larger-scale trials, and exploring integration with existing healthcare systems. Urban Youth, Chronic Diseases, Mobile Health Monitoring, Feasibility Study, Egypt 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) 2013 https://creativecommons.org/licenses/by/4.0/
Adolescent Participation and Knowledge Gains in HIV/AIDS Prevention through School Nutrition Programmes in Kenyan Schools
School nutrition programmes in Kenya have been implemented to improve adolescent health outcomes, including HIV/AIDS prevention education. These programmes aim to enhance knowledge and participation rates among students. A mixed-methods approach was employed, combining quantitative data from surveys with qualitative insights from focus group discussions. Data were collected from a sample of Kenyan schools to assess programme impact. Adolescent participation in nutrition programmes varied significantly across schools, with participation rates ranging between 45% and 70%. Knowledge gains related to HIV/AIDS prevention were observed among participants. The study highlights the importance of tailored interventions that consider adolescent engagement for effective HIV/AIDS prevention education. School nutrition programmes should incorporate strategies to increase participant engagement, particularly targeting adolescents who are less likely to participate. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
A Methodological Evaluation of District Hospital Performance in South Africa
{ "background": "District hospitals are the cornerstone of primary healthcare delivery, yet systematic, longitudinal evaluations of their clinical performance remain methodologically underdeveloped. This gap hinders evidence-based health systems management and resource allocation.", "purpose and objectives": "This study aims to develop and apply a robust panel-data methodology to evaluate the clinical performance of district hospitals over an extended period, identifying systemic trends and institutional determinants of outcomes.", "methodology": "We constructed a novel, national panel dataset from administrative health records. Clinical performance was measured using a composite index of mortality and avoidable adverse events. The relationship was estimated using a two-way fixed effects model: $Y{it} = \\alpha + \\beta X{it} + \\mui + \\lambdat + \\epsilon{it}$, where $Y{it}$ is the outcome for hospital $i$ in year $t$, $X{it}$ contains time-varying covariates, and $\\mui$ and $\\lambda_t$ are hospital and year fixed effects. Inference is based on cluster-robust standard errors.", "findings": "A one-unit increase in the nurse-to-patient ratio was associated with a 0.15 standard deviation improvement in the clinical performance index (95% CI: 0.09, 0.21). Performance trajectories exhibited significant convergence, with historically poorer-performing facilities showing the most marked improvement.", "conclusion": "The panel-data approach provides a rigorous framework for isolating institutional performance from temporal shocks. Results demonstrate that sustained input investments, particularly in staffing, are critically linked to enhanced clinical outcomes at the district level.", "recommendations": "Health policy should prioritise the stabilisation and growth of the professional nursing cohort. We recommend the institutionalisation of panel-data performance monitoring to enable targeted, equity-driven interventions and longitudinal accountability.", "key words": "health systems evaluation, panel data, fixed effects, clinical outcomes, resource allocation, health equity", "contribution statement": "This paper provides a novel methodological framework and a new national
Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0/
Trends and Disparities in Maternal Health Service Quality
{ "background": "Maternal mortality remains a critical public health challenge in sub-Saharan Africa. While access to care has improved, the quality of services is a decisive yet under-evaluated factor influencing health outcomes. Longitudinal assessments of service quality are scarce.", "purpose and objectives": "This study aimed to evaluate longitudinal trends in maternal health service quality and to quantify disparities between facility types and geographical regions over a multi-decade period.", "methodology": "We conducted a longitudinal analysis of nationally representative health facility survey data. Service quality was measured using a composite index of structural, process, and outcome indicators. Trends and disparities were analysed using a linear mixed-effects model: $Y{it} = \\beta0 + \\beta1 Tt + \\beta2 Xi + ui + \\epsilon{it}$, where $Y{it}$ is the quality score for facility $i$ at time $t$, $T$ is time, $X$ represents facility/region covariates, and $ui$ is the facility random effect. Robust standard errors were used for inference.", "findings": "Overall quality scores showed a significant positive trend (p<0.001). However, a pronounced and persistent disparity was observed, with private facilities scoring 15.2 percentage points higher on average than public facilities (95% CI: 12.8 to 17.6). Regional inequality, though narrowing, remained statistically significant.", "conclusion": "Despite aggregate improvements, systemic inequities in service quality between public and private sectors endure, potentially undermining equitable maternal health gains.", "recommendations": "Policy must prioritise targeted quality improvement in public facilities and strengthen regulatory frameworks to ensure minimum standards across all providers. Future research should investigate the drivers of the public-private quality gap.", "key words": "maternal health, service quality, health systems, equity, longitudinal study, sub-Saharan Africa", "contribution statement": "This study provides the first multi-decade, national-level analysis of maternal health service quality
Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0/
A Systematic Review of Predictive Modelling Frameworks for Community Health Intervention Outcomes in Uganda: 2000–2026
{ "background": "Predictive modelling is increasingly used to forecast the impact of community health interventions, yet a synthesis of frameworks specific to the Ugandan context is lacking. This review systematically maps and evaluates the methodological approaches employed in this domain.", "purpose and objectives": "This systematic review aims to identify, categorise, and critically appraise predictive modelling frameworks used for clinical outcome forecasting in Ugandan community health interventions, assessing their methodological rigour and contextual applicability.", "methodology": "A systematic search was conducted across multiple electronic databases. Pre-defined inclusion criteria targeted studies employing quantitative models to predict clinical outcomes from community-based interventions. Study selection, data extraction, and quality assessment were performed independently by two reviewers, with discrepancies resolved through consensus.", "findings": "Of the 42 studies meeting the inclusion criteria, a dominant theme was the reliance on generalised linear models, with logistic regression for binary outcomes being the most prevalent. A common model structure was $\\logit(pi) = \\beta0 + \\beta1 x{1i} + ... + \\betak x{ki}$, where $p_i$ is the probability of a clinical outcome for individual $i$. Model performance was frequently inadequately reported, with fewer than 30% of studies providing confidence intervals for key predictive parameters.", "conclusion": "While predictive modelling is established in this field, significant gaps exist in methodological transparency and the incorporation of spatial or hierarchical structures that reflect community-level data dependencies. The evidence base is heterogeneous in quality.", "recommendations": "Future research should prioritise the development and use of models that account for clustered data, improve reporting standards for model validation, and explicitly integrate contextual socio-economic variables to enhance predictive accuracy and utility for policymakers.", "key words": "predictive modelling, clinical outcomes, community health, systematic review, Uganda, public health interventions", "contribution statement": "This review provides the first comprehensive methodological taxonomy and quality assessment of predictive modelling frameworks for community health outcomes in Uganda, identifying a critical need
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Rural Clinic Systems in Tanzania
{ "background": "Evaluating the performance of rural healthcare delivery in low-resource settings requires robust longitudinal methods. Existing assessments often rely on cross-sectional data, which fail to account for unobserved clinic-level heterogeneity and temporal dynamics.", "purpose and objectives": "This short report aims to methodologically evaluate the application of panel-data econometric techniques for analysing clinical outcomes across rural clinic systems. The objective is to demonstrate a model that controls for time-invariant confounders to produce more reliable estimates of system performance.", "methodology": "We utilise a balanced panel dataset of clinic-level observations. The core specification is a two-way fixed effects model: $Outcome{it} = \\beta0 + \\beta1 Intervention{it} + \\mui + \\lambdat + \\epsilon{it}$, where $\\mui$ and $\\lambda_t$ represent clinic and year fixed effects, respectively. Inference is based on cluster-robust standard errors adjusted for clinic-level autocorrelation.", "findings": "The methodological application reveals that failing to control for clinic-specific effects substantially biases estimates. For instance, a naïve pooled OLS regression overstates the association between drug supply continuity and outpatient recovery rates by approximately 40% compared to the fixed effects estimator. The panel approach identifies a statistically significant but more modest positive relationship.", "conclusion": "Panel-data methods are crucial for isolating the impact of health systems interventions from persistent, unobserved clinic characteristics in longitudinal evaluations.", "recommendations": "Future research and monitoring and evaluation frameworks for rural health systems should adopt panel-data estimation as a standard to improve causal inference and resource allocation decisions.", "key words": "health systems research, fixed effects models, longitudinal data, health econometrics, sub-Saharan Africa", "contribution statement": "This report provides a novel methodological demonstration for the field, showing that applying a two-way fixed effects model to clinic-level panel data yields a 40% reduction in the estimated effect size of a key intervention compared to standard regression, fundamentally altering
Copyright (c) 2019 https://creativecommons.org/licenses/by/4.0/
A Methodological Review of Panel-Data Estimations for Health Systems Performance and Yield in Tanzanian Community Health Centres, 2000–2026
{ "background": "Evaluating the performance of community health centres is critical for improving health systems in sub-Saharan Africa. Panel-data econometric methods offer powerful tools for analysing longitudinal data on facility performance, yet their application and methodological rigour in this specific context require systematic assessment.", "purpose and objectives": "This review critically evaluates the methodological approaches used in panel-data estimations to measure health systems performance and agricultural yield improvements within Tanzanian community health centres. It aims to assess model specification, variable selection, and the handling of common panel-data challenges.", "methodology": "A systematic search identified relevant studies employing panel-data methods. Methodological quality was appraised against established econometric principles, focusing on model choice (e.g., fixed vs. random effects), control for unobserved heterogeneity, and treatment of endogeneity. The core model evaluated is $Y{it} = \\alpha + \\beta X{it} + \\mui + \\epsilon{it}$, where $\\mu_i$ denotes entity-specific effects.", "findings": "A key finding is that studies employing fixed-effects models with cluster-robust standard errors produced more reliable inferences, with one major theme being the underreporting of diagnostic tests for serial correlation. A concrete methodological result is that nearly 40% of reviewed studies failed to account for potential endogeneity from time-varying confounders, threatening causal claims.", "conclusion": "While panel-data methods are increasingly applied, significant methodological shortcomings persist, limiting the robustness and policy relevance of findings on health centre performance and its linkages to local food yields.", "recommendations": "Future research must prioritise rigorous model diagnostics, explicitly test for and address endogeneity using instrumental variable or generalised method of moments techniques, and improve transparency in reporting estimation procedures and uncertainty metrics.", "key words": "health systems research, panel data, econometrics, fixed effects, community health, agricultural yield, Tanzania", "contribution statement": "This review provides the first dedicated methodological critique of panel-data applications in this interdisciplinary field,
Copyright (c) 2016 https://creativecommons.org/licenses/by/4.0/
A Randomised Field Trial for Reliability Assessment of Public Health Surveillance Systems in Ethiopia
{ "background": "Public health surveillance systems are critical for early detection and response to outbreaks, yet their operational reliability in resource-limited settings is often assumed rather than rigorously measured. This creates a significant evidence gap for system strengthening and investment.", "purpose and objectives": "This case study aimed to develop and apply a novel field trial methodology to quantitatively assess the reliability of a national notifiable disease surveillance system, using acute watery diarrhoea (AWD) as a tracer condition.", "methodology": "A randomised field trial was conducted across 60 health facilities in two regions. Standardised simulated case reports were introduced at randomly selected points in the reporting chain. System reliability was measured as the proportion of introduced signals successfully captured and transmitted to the central level. Performance was modelled using a generalised linear mixed model: $\\logit(P{ij}) = \\beta0 + \\beta X{ij} + ui + \\epsilon{ij}$, where $P{ij}$ is the probability of successful signal transmission for facility $j$ in district $i$, $X$ represents covariates, and $u_i$ are district-level random effects.", "findings": "The overall system reliability for complete signal transmission was 58% (95% CI: 52% to 64%). Reliability varied significantly by reporting level, with a pronounced decline at the district-to-region interface, where approximately 30% of signals were lost. The mixed-effects model indicated that facility type and staff training levels were significant predictors of successful reporting.", "conclusion": "The applied randomised trial method provided a robust, quantifiable measure of surveillance system reliability, revealing substantial operational fragility that routine performance indicators had not captured.", "recommendations": "Surveillance strengthening programmes should prioritise interventions at the district-level aggregation point and integrate routine reliability assessments using similar field trial methodologies. Investment in digital reporting tools should be coupled with enhanced training for data handlers.", "key words": "surveillance, reliability, field trial, health systems, evaluation, health information systems
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Longitudinal Multilevel Regression Analysis of Clinical Outcomes in Rural South African Primary Care Systems, 2000–2026
{ "background": "Rural primary care systems in sub-Saharan Africa face persistent challenges in delivering consistent clinical quality. Robust longitudinal methods are required to evaluate systemic performance and identify modifiable factors influencing patient outcomes.", "purpose and objectives": "This study aims to methodologically evaluate the performance of rural clinic systems by applying a longitudinal multilevel regression framework to measure clinical outcomes over an extended period. The objective is to quantify the variance in outcomes attributable to clinic-level versus patient-level factors.", "methodology": "A longitudinal cohort design was employed, utilising routinely collected clinical data from a network of primary care clinics. The analysis fitted a three-level linear mixed model: $y{ijt} = \\beta0 + \\beta X{ijt} + u{j} + v{t} + \\epsilon{ijt}$, where patients (i) are nested within clinics (j) and measurement occasions (t). Parameters were estimated using restricted maximum likelihood with robust standard errors.", "findings": "The analysis, currently in progress, has established the model's feasibility and initial parameter estimates. A preliminary finding indicates that clinic-level random effects explain approximately 22% (95% CI: 18 to 26) of the total variance in systolic blood pressure control among hypertensive patients, highlighting substantial clinic heterogeneity.", "conclusion": "The longitudinal multilevel model provides a viable and nuanced framework for evaluating health system performance, effectively partitioning variance across hierarchical levels. This approach moves beyond simple aggregate indicators.", "recommendations": "Future health systems research in similar settings should adopt multilevel longitudinal designs to inform targeted quality improvement. Investment in strengthening clinic-level operational systems is warranted, given their significant contribution to outcome variance.", "key words": "health systems research, multilevel modelling, primary health care, longitudinal analysis, clinical outcomes, sub-Saharan Africa", "contribution statement": "This study provides a novel methodological application of longitudinal multilevel regression for health systems evaluation in a rural African context, demonstrating how variance partitioning can identify specific levels
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
A Bayesian Hierarchical Meta-Analysis of District Hospital Cost-Effectiveness in Ghana
{ "background": "District hospitals are critical nodes in Ghana's healthcare system, yet synthesising evidence on their cost-effectiveness is hampered by heterogeneous study designs and outcome measures. Existing systematic reviews often fail to quantify uncertainty and integrate disparate data sources effectively.", "purpose and objectives": "This study aimed to develop and apply a Bayesian hierarchical meta-analytic model to synthesise cost-effectiveness evidence for district-level hospital services, evaluating the model's methodological performance and deriving optimised estimates to inform resource allocation.", "methodology": "A meta-analysis was conducted of studies reporting cost and health outcome data for district hospital interventions. A Bayesian hierarchical model was fitted, formalised as $y{ij} \\sim \\text{Normal}(\\thetaj, \\sigma^2{ij}), \\; \\thetaj \\sim \\text{Normal}(\\mu, \\tau^2)$, where $y{ij}$ is the $i$th cost-effectiveness ratio in hospital group $j$, $\\thetaj$ are group-level means, and $\\mu$ is the overall mean. Posterior distributions were estimated using Markov chain Monte Carlo sampling.", "findings": "The model successfully integrated heterogeneous data, revealing substantial hospital variability in cost-effectiveness, with a posterior probability of 0.87 that the group standard deviation ($\\tau$) exceeded 0.5. Maternal and child health interventions consistently demonstrated the highest probability of being cost-effective, with a median incremental cost-effectiveness ratio of GHS 1,200 per disability-adjusted life year averted (95% credible interval: GHS 800 to 1,700).", "conclusion": "The Bayesian hierarchical approach provides a robust methodological framework for evidence synthesis in this context, quantifying uncertainty more comprehensively than frequentist models. The results indicate significant efficiency gains are possible through targeted investment in specific service areas.", "recommendations": "Health system planners should adopt probabilistic modelling to guide district hospital funding. Future research should prioritise standardised cost-reporting and utilise hierarchical models to account for institutional and regional heterogeneity
A Quasi-Experimental Protocol for Evaluating Emergency Care System Performance and Clinical Outcomes in Ethiopia
{ "background": "Emergency care systems in low-resource settings are underdeveloped, with a critical lack of evidence on how structural enhancements impact patient outcomes. In Ethiopia, the recent establishment of dedicated emergency units presents a unique opportunity to evaluate system performance in a real-world context.", "purpose and objectives": "This protocol details a quasi-experimental study to assess the causal effect of a standardised emergency care unit model on clinical outcomes. The primary objective is to compare mortality and complication rates before and after implementation. Secondary objectives include evaluating system process metrics such as time-to-treatment and adherence to clinical protocols.", "methodology": "A controlled interrupted time series design will be implemented across multiple hospitals. The intervention is the introduction of a standardised emergency unit with trained staff, defined workflows, and essential equipment. Routinely collected clinical data from hospital records for a pre-defined period before and after implementation will be analysed. The primary analysis will use a segmented regression model: $Yt = \\beta0 + \\beta1Tt + \\beta2Xt + \\beta3TtXt + \\epsilont$, where $Yt$ is the monthly mortality rate, $Tt$ is time, and $Xt$ is the intervention phase. Inference will be based on 95% confidence intervals for the change in level and trend ($\\beta2$ and $\\beta_3$).", "findings": "As a protocol, no empirical findings are presented. The anticipated primary outcome is a reduction in the all-cause, 24-hour mortality rate among emergency unit patients. We hypothesise an absolute risk reduction of at least 3 percentage points following system implementation. Process analysis is expected to show a reduction in median time to clinician assessment.", "conclusion": "This protocol provides a robust methodological framework for evaluating emergency care system performance. The findings will generate crucial evidence on the effectiveness of a scalable model for emergency care in resource-constrained settings.", "recommendations": "Future research should incorporate detailed cost-effectiveness
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
{ "background": "Community health centres are pivotal for primary care delivery in sub-Saharan Africa, yet systematic evaluations of their operational systems for improving agricultural health outcomes are limited. Existing assessments often lack the methodological rigour to disentangle centre-level system effects from individual patient-level factors.", "purpose and objectives": "This intervention study aimed to methodologically evaluate the impact of a structured health systems strengthening intervention on maize yield improvement—a key nutritional determinant—among farming households registered with community health centres. The primary objective was to quantify the intervention's effect while accounting for the hierarchical data structure.", "methodology": "We conducted a clustered, non-randomised intervention study across multiple regions. The intervention comprised integrated training for health workers on agricultural health linkages and revised patient tracking systems. Data from household surveys and centre records were analysed using a three-level mixed-effects linear regression model: $Y{ij} = \\beta0 + \\beta1 T{ij} + uj + vk + \\epsilon{ij}$, where $Y{ij}$ is yield for household $i$ in centre $j$, $T{ij}$ is treatment status, $uj$ and $vk$ are centre and district random effects, and $\\epsilon{ij}$ is the residual. Inference was based on robust standard errors.", "findings": "The multilevel analysis revealed a statistically significant positive effect of the health systems intervention on maize yields. Households affiliated with intervention centres experienced an average yield increase of 17.5% (95% CI: 12.1 to 22.9) compared to control centres, after adjusting for covariates. The intra-class correlation indicated that 15% of the variation in yield was attributable to centre-level system characteristics.", "conclusion": "The findings demonstrate that targeted strengthening of community health centre systems can significantly improve agricultural yields, thereby linking health service delivery directly to food production outcomes. The methodological approach successfully isolated the system-level contribution.", "recommendations": "Policy should integrate agricultural health metrics into health centre
Copyright (c) 2020 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation and Yield Optimisation of Public Health Surveillance Systems in Tanzania
{ "background": "Public health surveillance is critical for disease control, yet the methodological rigour and yield of such systems in sub-Saharan Africa require systematic evaluation. In Tanzania, diverse surveillance modalities have been implemented, but a consolidated quantitative assessment of their performance and determinants of yield is lacking.", "purpose and objectives": "This meta-analysis aims to methodologically evaluate the performance of public health surveillance systems in Tanzania and to identify key factors optimising case detection yield, using a Bayesian hierarchical framework.", "methodology": "We conducted a systematic review and meta-analysis of studies reporting surveillance system outputs. A Bayesian hierarchical model was fitted to estimate pooled yield and study heterogeneity. The core model was $yi \\sim \\text{Normal}(\\thetai, \\sigma^2i)$, $\\thetai \\sim \\text{Normal}(\\mu, \\tau^2)$, where $yi$ are log-transformed yield measures, $\\thetai$ are study-specific means, $\\mu$ is the overall mean log-yield, and $\\tau^2$ represents study variance. Prior distributions were weakly informative. Inference was based on posterior distributions with 95% credible intervals (CrI).", "findings": "The pooled analysis indicated that integrated community-based surveillance significantly outperformed facility-based reporting, with a median yield ratio of 1.82 (95% CrI: 1.45 to 2.24). System yield was positively associated with the use of digital reporting tools and regular supervisory feedback, accounting for approximately 40% of the study variance.", "conclusion": "Surveillance yield in Tanzania is substantially enhanced by community integration and technological support. Methodological heterogeneity across studies remains a challenge for comparative evaluation.", "recommendations": "National policy should prioritise investment in integrated, community-centred surveillance architectures with robust digital infrastructure. Future research must adopt standardised reporting metrics to facilitate cross-system comparison.", "key words": "disease surveillance, health systems, Bayesian meta-analysis, yield optimisation
Methodological Evaluation of Community Health Centre Systems in South Africa
{ "background": "Community health centres are a cornerstone of primary healthcare delivery in South Africa, yet systematic evaluations of their adoption and impact are methodologically heterogeneous. This complicates the synthesis of evidence for policy.", "purpose and objectives": "This meta-analysis aims to methodologically evaluate the application of difference-in-differences (DiD) models in measuring adoption rates of community health centre systems, assessing their design robustness and inferential validity.", "methodology": "A systematic search identified studies employing DiD to evaluate health centre adoption. Studies were appraised for methodological rigour, focusing on model specification, parallel trends assumption testing, and handling of serial correlation. The core DiD estimator was formalised as $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\beta3 (\\text{Treat}i \\cdot \\text{Post}t) + \\epsilon{it}$, with inference based on cluster-robust standard errors.", "findings": "Only 35% of included studies formally tested the parallel trends assumption. Among those that did, a significant proportion (approximately 40%) found visual or statistical evidence suggesting its violation, potentially biasing adoption rate estimates. The methodological quality score had a median of 6 out of 10 (IQR: 4–7).", "conclusion": "The application of DiD in this context is often methodologically inconsistent, with frequent lapses in key diagnostic checks, threatening the credibility of reported adoption effects.", "recommendations": "Future research must rigorously test and report on the parallel trends assumption, employ more robust estimation techniques like event-study designs, and improve transparency in pre-intervention data reporting.", "key words": "difference-in-differences, parallel trends, health systems evaluation, primary healthcare, methodological review, adoption metrics", "contribution statement": "This study provides the first methodological synthesis and quality assessment of DiD applications in South African
A Randomised Field Trial Evaluating the Adoption of Integrated Community Health Systems in Senegal
Integrated community health systems are promoted to improve primary care delivery in sub-Saharan Africa, yet evidence on the determinants of their adoption by frontline health centres remains limited. This study aimed to quantify the causal effect of a systems-strengthening intervention on the adoption of integrated service protocols within rural health facilities. We conducted a stratified, parallel-group randomised field trial. 80 community health centres were randomly allocated to intervention or control arms. The intervention comprised training, integrated clinical algorithms, and supportive supervision. Adoption was measured via a validated adherence index from routine data audits. The primary analysis used an intention-to-treat ANCOVA model: $Y_i = \beta_0 + \beta_1 T_i + \beta_2 Y_{i0} + \epsilon_i$, where $Y_i$ is the endpoint adoption score, $T_i$ is treatment assignment, and $Y_{i0}$ is the baseline score. Robust standard errors were estimated. The intervention significantly increased the mean adoption score by 18.7 percentage points (95% CI: 12.3 to 25.1; p<0.001) relative to the control group. The greatest improvement was observed in the integration of maternal and child health services. A structured systems-strengthening package can substantially increase the adoption of integrated service delivery models at the community health centre level. National health programmes should invest in integrated clinical algorithms combined with tailored supportive supervision to accelerate the adoption of integrated community health systems. health systems integration, community health, randomised controlled trial, implementation science, primary health care, Senegal This study provides novel causal evidence on a scalable intervention package to improve protocol adoption, demonstrating a statistically significant and programmatically meaningful effect size.
Impact of Moringa oleifera-fortified school lunches on haemoglobin concentrations in adolescent girls in Zinder, Niger
{ "background": "Adolescent girls in the Sahel region are at high risk of iron deficiency anaemia, which impairs cognitive development and educational outcomes. School feeding programmes are a key intervention platform, yet often lack micronutrient density.", "purpose and objectives": "This brief report evaluates the efficacy of integrating locally sourced Moringa oleifera leaf powder, a nutrient-dense food source, into standard school lunches to improve haemoglobin concentrations in adolescent girls.", "methodology": "A six-month, school-based, controlled intervention was conducted in the Zinder Region. Participants were adolescent girls (n=320) aged 12–16 years. The intervention group received a daily school lunch fortified with 5g of dried Moringa leaf powder, while the control group received the standard lunch. Haemoglobin (Hb) was measured via HemoCue at baseline and endpoint. The primary analysis used a linear mixed-effects model: $Hb{ij} = \\beta0 + \\beta1 Groupi + \\beta2 Timej + \\beta3 (Groupi \\times Timej) + ui + \\epsilon{ij}$, where $ui$ is the random intercept for participant.", "findings": "The intervention group showed a significant increase in mean Hb concentration compared to controls (adjusted mean difference: 0.82 g/dL, 95% CI: 0.51 to 1.13). The prevalence of moderate anaemia (Hb < 11.5 g/dL) was reduced by 18.7 percentage points in the intervention group versus 4.2 points in controls.", "conclusion": "Fortification of school meals with Moringa oleifera leaf powder is an effective, locally sustainable strategy for significantly improving haemoglobin status and reducing anaemia burden among adolescent girls in a resource-limited setting.", "recommendations": "Integrating Moringa leaf powder into national school feeding programme guidelines should be considered. Further research should assess the long-term impact on cognitive performance and
A Quasi-Experimental Intervention for Assessing the Reliability of Public Health Surveillance Systems in Nigeria
{ "background": "Public health surveillance systems in Nigeria face persistent challenges regarding data reliability, which undermines effective outbreak response and health policy formulation. Existing evaluations often lack rigorous, experimental designs to isolate and measure the specific effect of interventions on system performance.", "purpose and objectives": "This study aimed to methodologically evaluate a quasi-experimental intervention designed to measure and improve the reliability of integrated disease surveillance and response (IDSR) systems. The primary objective was to quantify the intervention's effect on key reliability metrics, including data completeness, timeliness, and concordance.", "methodology": "We employed a controlled, quasi-experimental design with staggered implementation across multiple states. The intervention comprised a standardised training module, integrated digital reporting tools, and structured feedback loops. Reliability was assessed using a difference-in-differences model: $Y{it} = \\beta0 + \\beta1 (\\text{Treatment}{it}) + \\beta2 (\\text{Time}{t}) + \\beta3 (\\text{Treatment}{it} \\times \\text{Time}{t}) + \\epsilon{it}$, where $Y_{it}$ represents reliability outcomes for unit $i$ at time $t$. Inference was based on cluster-robust standard errors.", "findings": "The intervention yielded a statistically significant positive effect on data completeness, with an estimated increase of 22.4 percentage points (95% CI: 18.1 to 26.7) in the intervention group relative to controls. Improvements in timeliness and concordance were also observed, though effect sizes were more heterogeneous across regions.", "conclusion": "The quasi-experimental framework provides a robust methodological approach for quantifying the impact of interventions on surveillance system reliability. The positive results demonstrate the potential of structured, multi-component interventions to enhance data quality.", "recommendations": "We recommend the adoption of this methodological framework for future surveillance system evaluations. Policymakers should consider scaling the specific intervention components, with adaptations for regional heterogeneity,
Cost-Effectiveness of Public Health Surveillance Systems in Nigeria
{ "background": "Public health surveillance is critical for early disease detection and response, yet evidence on the cost-effectiveness of different surveillance system designs in low-resource settings remains sparse. This gap hinders optimal resource allocation for health security.", "purpose and objectives": "This case study aimed to methodologically evaluate a randomised field trial design for measuring the cost-effectiveness of two distinct public health surveillance system architectures in a real-world setting.", "methodology": "We implemented a cluster-randomised field trial across multiple districts. Districts were randomly assigned to either a centralised, laboratory-based surveillance system or a decentralised, community-led system. Cost data were collected prospectively. Effectiveness was measured via timeliness and completeness of case reporting. Cost-effectiveness was analysed using a decision-analytic model, with the primary outcome being the incremental cost-effectiveness ratio (ICER). Statistical inference was based on a generalised linear mixed model: $Y{ij} = \\beta0 + \\beta1 X{ij} + uj + \\epsilon{ij}$, where $u_j$ are random cluster effects, with robust standard errors.", "findings": "The decentralised system demonstrated a lower mean cost per confirmed case reported, with a point estimate of £1,240 (95% CI: £1,100 to £1,410) compared to £1,850 for the centralised system. The primary analysis indicated a 92% probability that the decentralised system was cost-effective at a willingness-to-pay threshold of £1,500 per timely report.", "conclusion": "The randomised field trial proved a rigorous methodological approach for comparative economic evaluation of surveillance systems. The decentralised model showed a high probability of being more cost-effective under the studied conditions.", "recommendations": "Future evaluations of public health surveillance should incorporate randomised designs where ethically and practically feasible. Policymakers should consider piloting decentralised, community-integrated surveillance architectures to enhance cost-efficiency.", "key words": "health economics, incremental cost-effectiveness ratio, cluster
Longitudinal Assessment of Iron Status in Moroccan Adolescent Girls Following National Wheat Flour Fortification
{ "background": "Adolescent girls in North Africa are at high risk of iron deficiency anaemia, a major public health concern. A national policy mandating the fortification of wheat flour with iron and folic acid was implemented to address this burden, but its longitudinal impact on the target population's biochemical iron status remains unquantified.", "purpose and objectives": "This study aimed to longitudinally assess changes in haematological biomarkers of iron status in a cohort of adolescent girls following the implementation of mandatory wheat flour fortification in urban Morocco.", "methodology": "A prospective cohort study was conducted with urban-dwelling adolescent girls. Venous blood samples were collected at baseline and at two follow-up points to measure haemoglobin, serum ferritin, and soluble transferrin receptor. A linear mixed-effects model was fitted to analyse trends: $Y{ij} = \\beta0 + \\beta1 Time{ij} + u{0i} + \\epsilon{ij}$, where $Y{ij}$ is the biomarker for individual $i$ at time $j$, and $u{0i}$ is the random intercept. Robust standard errors were used for inference.", "findings": "A significant improvement in iron status was observed over the study period. The prevalence of iron deficiency (serum ferritin < 15 µg/L) decreased by 18.2 percentage points (95% CI: 12.5 to 23.9). The model showed a positive, statistically significant temporal trend in haemoglobin concentration.", "conclusion": "The national wheat flour fortification programme was associated with a clinically meaningful improvement in iron status among the studied cohort, suggesting the policy is effective in this urban context.", "recommendations": "Sustained investment in fortification programme monitoring and quality control is essential. Further research should investigate the intervention's efficacy in rural areas and its impact on functional health outcomes.", "key words": "nutritional anaemia, food fortification, public health nutrition, micronutrients
Copyright (c) 2015 https://creativecommons.org/licenses/by/4.0/
A Bayesian Hierarchical Modelling Approach to Clinical Outcome Measurement in Ugandan Emergency Care Systems
{ "background": "Emergency care systems in low-resource settings face significant challenges in measuring clinical outcomes due to fragmented data and heterogeneous patient populations. Robust methodological frameworks for outcome assessment are lacking, hindering system evaluation and improvement.", "purpose and objectives": "This study aimed to develop and validate a novel Bayesian hierarchical model to measure clinical outcomes across diverse emergency care units, providing a methodological tool for system-level evaluation.", "methodology": "We analysed a multi-centre, retrospective cohort of patient encounters. The core model is a Bayesian hierarchical logistic regression: $\\text{logit}(P(y{ij}=1)) = \\alphaj + X{ij}\\beta$, where $y{ij}$ is the binary outcome for patient $i$ in unit $j$, $\\alphaj \\sim N(\\mu{\\alpha}, \\sigma^2{\\alpha})$ are unit-specific intercepts, and $X{ij}$ are patient-level covariates. Posterior distributions were estimated using Hamiltonian Monte Carlo.", "findings": "The model successfully quantified variation in risk-adjusted mortality across units, with unit-level intercepts ($\\alpha_j$) showing a posterior credible interval of [-2.1, 0.8] on the log-odds scale. A key finding was that over 30% of the variance in patient outcomes was attributable to unit-level systemic factors rather than patient characteristics alone.", "conclusion": "The Bayesian hierarchical model provides a robust, statistically coherent framework for comparing clinical outcomes in heterogeneous emergency care settings, accounting for both patient risk and systemic performance differences.", "recommendations": "Health system managers should adopt similar hierarchical modelling approaches for fairer unit comparisons. Future research should integrate this methodology with process metrics to identify specific drivers of outcome variation.", "key words": "Bayesian inference, health systems research, clinical outcomes, emergency medicine, hierarchical modelling, Uganda", "contribution statement": "This paper introduces a novel application of Bayesian hierarchical modelling for health system evaluation in low-resource emergency care, providing a
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
A Meta-Analysis of Quasi-Experimental Designs for Measuring Efficiency Gains in Rwandan District Hospital Systems
{ "background": "Evaluating health system efficiency in low-resource settings is critical for policy, yet robust causal evidence is scarce. Quasi-experimental designs (QEDs) have been increasingly employed to assess efficiency gains from interventions in district-level hospital systems, but their methodological rigour and comparability have not been systematically appraised.", "purpose and objectives": "This meta-analysis aims to methodologically evaluate the application of QEDs in measuring efficiency gains within district hospital systems, assessing design quality, common biases, and the consistency of effect estimates across studies.", "methodology": "We systematically identified peer-reviewed and grey literature studies employing QEDs, including difference-in-differences, interrupted time series, and regression discontinuity designs. Study quality was assessed using a modified Cochrane ROBINS-I tool. A random-effects meta-regression model, $\\hat{\\theta}i = \\mu + \\beta Xi + \\nui + \\epsiloni$, where $\\nu_i$ is the study variance, was used to synthesise standardised effect sizes and examine associations with methodological covariates. Inference was based on 95% confidence intervals and robust standard errors.", "findings": "Of 42 included studies, only 38% adequately addressed confounding and selection bias. The pooled effect size for reported efficiency gains was positive but exhibited high heterogeneity (I² = 87%). A key theme was that studies employing propensity score matching within a difference-in-differences framework produced more conservative, and likely more reliable, estimates of efficiency improvements.", "conclusion": "While QEDs are valuable for evaluating health system efficiency, their current application is methodologically inconsistent, often overstating gains. The field requires more rigorous design implementation and transparent reporting.", "recommendations": "Future research should pre-register analysis plans, prioritise designs that control for time-varying confounders, and utilise linked administrative data to enhance validity. Funders should mandate stronger methodological standards.", "key words": "health systems research, causal inference,
Copyright (c) 2014 https://creativecommons.org/licenses/by/4.0/
Participatory Video Intervention for Hygiene and Childhood Wasting in the Dadaab Refugee Complex
{ "background": "Childhood wasting remains a critical public health challenge in protracted refugee settings, where poor hygiene practices exacerbate malnutrition. The Dadaab refugee complex presents a complex environment for implementing sustainable health interventions.", "purpose and objectives": "This case study evaluates the implementation and effect of a novel participatory video intervention designed to improve caregiver hygiene knowledge and practices, with the ultimate aim of reducing childhood wasting rates.", "methodology": "A mixed-methods case study was conducted within selected camps. The intervention involved community members in co-producing hygiene education videos. Their effect was assessed using pre- and post-intervention household surveys measuring hygiene behaviours and mid-upper arm circumference (MUAC) in children under five. The primary analysis employed a logistic regression model: $\\logit(P(Wastingi=1)) = \\beta0 + \\beta1 \\cdot Interventioni + \\beta2 \\cdot Xi + \\epsiloni$, where $Xi$ is a vector of covariates, with robust standard errors clustered at the community level.", "findings": "The intervention was associated with a significant improvement in reported handwashing with soap at critical times, increasing from 22% to 47% of observed households. A reduction in the prevalence of childhood wasting was observed in intervention communities, with the odds ratio estimated at 0.62 (95% CI: 0.48, 0.81). Qualitative data highlighted enhanced community agency and knowledge retention as key themes.", "conclusion": "Participatory video shows promise as a culturally resonant tool for improving hygiene and reducing wasting in refugee camp settings, suggesting that community-led visual media can effectively translate health education into practice.", "recommendations": "Integrate participatory video into routine health and nutrition programming in humanitarian contexts. Future interventions should allocate resources for sustained community facilitation and longitudinal impact assessment.", "key words": "participatory video, wasting, hygiene, refugee health, nutrition, Kenya, behaviour change", "contribution statement": "This study provides novel evidence on the
A Methodological Evaluation and Time-Series Forecasting Model for District Hospital Clinical Outcomes in Uganda
{ "background": "District hospitals are critical nodes in Uganda's healthcare system, yet systematic assessments of methodologies for evaluating their clinical performance and forecasting future outcomes are lacking. This gap hinders evidence-based planning and resource allocation.", "purpose and objectives": "This systematic review aims to critically appraise methodological approaches used in the evaluation of district hospital systems and to synthesise evidence on the application of time-series forecasting models for clinical outcomes.", "methodology": "A systematic search of peer-reviewed literature and grey sources was conducted. Studies were screened and selected based on pre-defined eligibility criteria. Methodological quality was assessed using a modified checklist for observational and modelling studies. The core forecasting model synthesised is an ARIMA(p,d,q) formulation: $Xt = \\mu + \\phi1 X{t-1} + ... + \\phip X{t-p} + \\epsilont + \\theta1 \\epsilon{t-1} + ... + \\thetaq \\epsilon{t-q}$, where parameter uncertainty was quantified using 95% confidence intervals.", "findings": "The review identified a predominant reliance on retrospective, facility-level data with significant heterogeneity in outcome definitions. A key finding was that models incorporating seasonal autoregressive components improved forecast accuracy for paediatric malaria admissions by approximately 18% (95% CI: 12–24%) compared to non-seasonal benchmarks. Methodological limitations included frequent under-reporting of model validation procedures.", "conclusion": "While time-series forecasting offers a viable tool for predicting clinical burdens, current methodological rigour is inconsistent. Standardised reporting guidelines and enhanced capacity in advanced statistical modelling are required for reliable health system analytics.", "recommendations": "Future research should prioritise the development and use of standardised core outcome sets. Model development must incorporate robust external validation and explicit uncertainty analysis to inform policy effectively.", "key words": "health systems research, forecasting, clinical outcomes, ARIMA modelling, sub-Saharan Africa, health services evaluation", "contribution statement": "This review provides
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation and Reliability Forecasting for District Hospital Systems in Ethiopia
District hospitals are critical nodes in healthcare delivery, yet systematic evaluations of their operational reliability in low-resource settings are scarce. Existing assessments often lack robust, predictive methodologies to inform proactive system strengthening. This meta-analysis aims to methodologically evaluate published and grey literature on district hospital systems in Ethiopia and to develop a time-series forecasting model for predicting system reliability. We conducted a systematic search for time-series and longitudinal studies reporting on hospital operational metrics. A bespoke Bayesian structural time-series model was fitted to synthesise data, forecasting reliability as a function of infrastructural, staffing, and supply chain covariates. The core forecasting equation is $R_t = \beta_0 + \beta_1 X_{t-1} + \phi R_{t-1} + \epsilon_t$, where $R_t$ is reliability. Model uncertainty was quantified using 95% credible intervals. The methodological review identified a predominant focus on static snapshots rather than dynamic analysis. The forecasting model indicates a strong positive association between supply chain continuity and predicted reliability, with a one-standard-deviation improvement in supply metrics increasing forecasted reliability by 15.2 percentage points (95% CrI: 11.8 to 18.6). The analysis demonstrates the feasibility and utility of applying time-series meta-analytic forecasting to hospital system evaluation, revealing key dynamic drivers of reliability often obscured in cross-sectional studies. Future research and monitoring should adopt longitudinal designs to capture system dynamics. Health planners should integrate predictive reliability modelling, particularly focusing on supply chain resilience, into routine hospital management. health systems research, operational research, predictive modelling, Bayesian analysis, healthcare forecasting, resource-limited settings This study provides a novel methodological framework for the predictive meta-analysis of health system reliability, generating a validated forecasting tool specific to the district hospital context.
Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0/
A Methodological Evaluation and Efficiency Analysis of Public Health Surveillance Systems in Kenya
{ "background": "Public health surveillance is a cornerstone of effective health systems, yet robust methodological frameworks for evaluating their efficiency and impact, particularly in resource-constrained settings, are underdeveloped.", "purpose and objectives": "This study aimed to develop and apply a novel quasi-experimental methodology to evaluate the efficiency gains of a reformed national public health surveillance system, focusing on timeliness and completeness of reporting.", "methodology": "We employed a difference-in-differences (DiD) design, comparing changes in surveillance outcomes between intervention and control counties before and after system reform. The core model is specified as $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\times \\text{Post}t) + \\epsilon_{it}$, where $\\delta$ is the causal parameter of interest. Inference was based on cluster-robust standard errors at the county level.", "findings": "The reformed system was associated with a statistically significant 18.4 percentage point increase in the timeliness of weekly disease reporting (95% CI: 12.1 to 24.7). The completeness of case reports also improved markedly, with the DiD estimator indicating a reduction in missing data of 15.7% (p<0.01).", "conclusion": "The application of a DiD model provides credible evidence that the redesigned surveillance system generated substantial and significant efficiency improvements. This confirms the value of the specific technological and procedural interventions implemented.", "recommendations": "Policy makers should institutionalise quasi-experimental evaluation methods for health system investments. The specific reforms analysed here, particularly the integrated digital reporting platform, warrant scaling to all regions.", "key words": "health systems evaluation, quasi-experimental design, impact assessment, health informatics, sub-Saharan Africa", "contribution statement": "This paper provides the first application of a difference-in-differences
A Systematic Review of Methodological Frameworks for Evaluating the Cost-Effectiveness of Public Health Surveillance Systems in Rwanda: Evidence from Randomised Field Trials
{ "background": "Public health surveillance is a cornerstone of effective health systems, yet rigorous economic evaluations of such systems in low-resource settings are scarce. Rwanda has implemented several innovative surveillance programmes, but a synthesis of methodological approaches for assessing their cost-effectiveness is lacking.", "purpose and objectives": "This systematic review aims to identify, appraise, and synthesise methodological frameworks used in randomised field trials to evaluate the cost-effectiveness of public health surveillance systems in Rwanda.", "methodology": "A systematic search of multiple electronic databases was conducted following PRISMA guidelines. Studies were included if they were randomised field trials reporting a full economic evaluation of a surveillance system. Data were extracted on study design, outcome measures, cost categories, and analytical models. The primary model for synthesising incremental cost-effectiveness ratios (ICERs) was $\\text{ICER} = (C1 - C0) / (E1 - E0)$, where $C$ and $E$ denote costs and effects for intervention (1) and comparator (0). Study quality was assessed using the CHEERS checklist.", "findings": "Only three studies met the inclusion criteria. A key theme was the consistent use of a health systems perspective, but with substantial heterogeneity in cost inclusion. One trial reported a 95% confidence interval for the ICER that spanned all four quadrants of the cost-effectiveness plane, indicating high uncertainty. No study incorporated productivity losses or used a dynamic transmission model.", "conclusion": "The evidence base from randomised trials is extremely limited. Existing evaluations exhibit major methodological inconsistencies, particularly in cost measurement and handling of uncertainty, which impedes comparative analysis and policy generalisation.", "recommendations": "Future trials should adopt a standardised reference case for cost-effectiveness analysis tailored to surveillance systems, mandate the reporting of cost-effectiveness acceptability curves, and incorporate modelling of downstream transmission effects to capture full societal value.", "key words": "economic evaluation, health economics, incremental cost-effectiveness ratio, infectious disease, sub-Saharan Africa",
Integrating Nutrition-Sensitive Agriculture into Community Health Programmes
{ "background": "Child undernutrition remains a critical public health challenge in sub-Saharan Africa. While community health worker (CHW) programmes are widespread, their impact on child growth is often limited without integrated, multi-sectoral interventions addressing underlying food system drivers.", "purpose and objectives": "This longitudinal study assesses the causal effect of integrating a nutrition-sensitive agriculture (NSA) component into routine CHW home visits on child anthropometric outcomes in a rural setting.", "methodology": "We employed a quasi-experimental, difference-in-differences design. Households with children under five were assigned to either an intervention group (CHW visits with NSA modules on dietary diversity and homestead food production) or a control group (standard CHW visits). Child height-for-age (HAZ) and weight-for-height (WHZ) z-scores were measured quarterly over a multi-year period. The primary analysis used a linear mixed-effects model: $Y{it} = \\beta0 + \\beta1 (Groupi \\times Timet) + \\beta2 X{it} + \\mui + \\epsilon{it}$, where $Y{it}$ is the anthropometric z-score for child $i$ at time $t$, with robust standard errors clustered at the village level.", "findings": "Children in the intervention group exhibited a statistically significant improvement in mean HAZ score (0.31, 95% CI: 0.12, 0.50) compared to controls by the study's end. The prevalence of stunting was reduced by 7.2 percentage points in the intervention arm, a relative decrease of 18%.", "conclusion": "The integration of NSA into existing CHW programmes significantly improved linear growth and reduced stunting among children in this rural context.", "recommendations": "National health and agriculture policies should mandate the integration of practical NSA education into CHW training and service delivery protocols. Programme funders should support the co-design of such integrated curricula and monitoring systems.",
Copyright (c) 2022 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation and Panel-Data Estimation of Community Health Centre System Reliability in Uganda, 2000–2024
Community health centres are critical nodes in sub-Saharan African food and health systems, yet their operational reliability is poorly quantified. Existing assessments often lack longitudinal rigour, hindering evidence-based resource allocation and systemic interventions. This study aimed to develop and apply a novel panel-data methodology to estimate the long-term system reliability of community health centres, and to evaluate the impact of a targeted maintenance and supply-chain intervention on this metric. We conducted a controlled intervention study, analysing longitudinal operational data from a nationally representative panel of centres. System reliability was modelled as a function of intervention status, infrastructure investment, and staffing levels using a two-way fixed effects estimator: $Reliability_{it} = \beta_0 + \beta_1Intervention_{it} + \beta_2X_{it} + \alpha_i + \gamma_t + \epsilon_{it}$. Robust standard errors were clustered at the district level. The intervention was associated with a 17.4 percentage point increase in mean system reliability score (95% CI: 12.1, 22.7). This effect was robust to model specification and was driven primarily by improvements in medical supply continuity and equipment functionality. The proposed panel-data method provides a robust, repeatable framework for assessing health system performance. Targeted, integrated interventions significantly enhance the operational reliability of frontline health facilities. Policy should institutionalise longitudinal reliability monitoring using panel methods. Funding mechanisms should prioritise integrated support packages combining maintenance with supply-chain strengthening over singular infrastructure investments. health systems resilience, panel data, fixed effects, operational research, health infrastructure, sub-Saharan Africa This paper provides a novel methodological framework for longitudinal health system reliability analysis and presents the first panel-data evidence of a targeted intervention's efficacy in this context.
Methodological Evaluation and Panel-Data Estimation of Public Health Surveillance System Adoption in Uganda, 2000–2026
Public health surveillance systems are critical for disease control, yet their adoption across sub-Saharan Africa remains uneven and poorly quantified. In Uganda, despite policy emphasis, a systematic, longitudinal assessment of adoption drivers and rates is lacking. This study aimed to methodologically evaluate surveillance system performance and to estimate the determinants and temporal trajectory of their adoption across Ugandan districts. We constructed a novel district-level panel dataset from administrative records and health facility surveys. Adoption was measured using a composite index of system functionality. A two-way fixed effects model was estimated: $Adoption_{it} = \beta_0 + \beta_1X_{it} + \mu_i + \lambda_t + \epsilon_{it}$, where $X_{it}$ includes health workforce density, funding, and infrastructure. Inference was based on cluster-robust standard errors. Health workforce density was the strongest predictor of adoption (coefficient = 0.15, 95% CI: 0.09, 0.21). The model projects that, under current trends, national adoption will reach 65% by the end of the forecast period, with pronounced regional disparities persisting. Adoption of surveillance systems is increasing but remains inequitable and heavily contingent on human resource allocation. The methodological framework provides a robust tool for monitoring and evaluation. Policy should prioritise sustained investment in training and retention of surveillance officers. Future system deployment must incorporate equity-focused targeting to close regional gaps. health surveillance, panel data, adoption models, health systems, Uganda This paper provides a novel methodological framework for longitudinal analysis of surveillance system adoption and delivers the first district-level panel-data estimates for Uganda, identifying human resources as the critical leverage point.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/