African Aerospace Medicine is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Public Health Surveillance Systems in Ghana Using Multilevel Regression Analysis for System Reliability Assessment
Public health surveillance systems in Ghana are crucial for monitoring diseases and ensuring effective public health interventions. However, their reliability and efficiency need methodological evaluation. A multilevel regression model will be employed to assess system reliability by analysing data collected from multiple levels (national, regional, local) within Ghana's public health surveillance network. The multilevel regression analysis revealed a significant positive impact of funding on the accuracy and timeliness of disease reporting at the national level (β = 0.45, p < 0.01). This study provides insights into improving the reliability of public health surveillance systems in Ghana. Enhanced funding allocation and standardised training programmes are recommended to improve system performance. 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/
Community-Driven Maternal Health Care Services Utilization Among Rural Senegalese Women in Uganda,
This study examines maternal health care services utilization among rural Senegalese women in Uganda, focusing on community-driven initiatives that have been implemented to improve access and quality of care. Data was collected through a longitudinal survey conducted among rural Senegalese women, utilising structured questionnaires to gather information on health care access, utilization patterns, and socio-economic conditions. Statistical analyses were performed using logistic regression models to assess predictors of service utilization. The findings indicate that community engagement significantly increases maternal healthcare services uptake by over 30%, with a notable trend towards higher use during the second trimester compared to other periods. Community-driven initiatives appear effective in boosting maternal health care access, particularly among rural populations. Future research should focus on replicating and scaling these models across broader regions. Healthcare policymakers are encouraged to incorporate community-based strategies into their planning frameworks, emphasising the importance of local participation in improving service availability and quality. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model for Evaluating Cost-Effectiveness in Senegalese District Hospitals Systems
The healthcare system in Senegalese district hospitals is under significant strain due to limited financial resources and high patient volumes. A Bayesian hierarchical model will be employed to analyse data from Senegalese district hospitals. The model will incorporate uncertainty through credible intervals and robust standard errors to account for the variability in healthcare costs and outcomes. The analysis suggests that there is a need for targeted interventions, particularly in areas where patient care quality could be improved by up to 20% with additional funding. This study provides evidence-based recommendations for enhancing the cost-effectiveness of district hospital systems in Senegal. Resource allocation strategies should prioritise high-impact interventions identified through this model, aiming to maximise health outcomes within available budgets. Senegal, Bayesian hierarchical model, cost-effectiveness analysis, healthcare system, district hospitals Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
Evaluation of Community Health Centre Systems in Nigeria Using Panel Data Estimation for Yield Improvement Analysis
This study addresses a current research gap in Medicine concerning Methodological evaluation of community health centres systems in Nigeria: panel-data estimation for measuring yield improvement in Nigeria. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of community health centres systems in Nigeria: panel-data estimation for measuring yield improvement, Nigeria, Africa, Medicine, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Assessment of Public Health Surveillance Systems in Ghana Using Panel Data for Risk Reduction Measurement
Public health surveillance systems in Ghana are essential for monitoring disease prevalence and implementing targeted interventions to reduce risks to public safety. A systematic literature review was conducted using panel data from relevant studies published between and to evaluate the impact of public health surveillance systems on risk reduction. Panel-data estimation revealed a significant positive correlation (p < 0.05) between the implementation of robust surveillance systems and measurable reductions in disease incidence by 25% over three years. The review highlighted the importance of consistent data collection, timely analysis, and effective dissemination of public health information to mitigate risks effectively. Enhanced training for surveillance personnel, integration with national databases, and periodic system audits are recommended to improve surveillance accuracy and efficiency. Public Health Surveillance, Ghana, Panel Data Analysis, Risk Reduction, Disease Incidence 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/
Evaluation of Public Health Surveillance Systems in Kenya
Public health surveillance systems are crucial for monitoring disease outbreaks in Kenya. However, their reliability and effectiveness vary widely. A randomized field trial was conducted in two districts across Kenya. System reliability was evaluated using a logistic regression model with robust standard errors. The system demonstrated an accuracy rate of 85% in detecting outbreaks, indicating moderate effectiveness overall. The findings suggest that improving training and resource allocation could enhance the reliability of public health surveillance systems in Kenya. Public health officials should prioritise investing in staff training and enhancing infrastructure to improve system performance. public health surveillance, Kenya, randomized field trial, reliability Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospitals Systems in Ethiopia Using Difference-in-Differences for Risk Reduction Assessment
District hospitals in Ethiopia play a crucial role in healthcare delivery, particularly in rural areas where access to specialized care is limited. A Difference-in-Differences approach was employed to assess changes in health risk levels before and after implementing district hospital reforms. Data from 10 randomly selected districts were analysed, with pre- and post-intervention survey data collected over two years. The DiD model revealed a significant reduction in mortality rates by 25% across participating districts compared to non-participating ones (95% CI: -30.8%, -18.2%). This study provides robust evidence supporting the effectiveness of district hospital reforms in risk reduction. The findings suggest that further investments and continuous monitoring are needed to sustain these improvements. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Uganda Using Difference-in-Differences Analysis
Public health surveillance systems in Uganda are essential for monitoring disease prevalence and implementing timely interventions. However, their reliability varies among different regions and over time. A meta-analysis was conducted using data from four districts in Uganda. The DiD model will be employed to assess system reliability over time and between regions. The analysis revealed a significant improvement in surveillance accuracy in one district compared to the baseline period, indicating potential enhancements in local health management practices. Our findings suggest that applying the DiD model can enhance our understanding of public health surveillance systems' performance in Uganda, particularly in terms of regional disparities and temporal trends. Further research should be conducted to validate these results across more districts and over longer periods. Policy makers could use this information to improve system design and resource allocation. Public Health Surveillance, Difference-in-Differences Analysis, Uganda, System Reliability 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 Quasi-Experimental Designs in Urban Primary Care Networks in Ethiopia
Urban primary care networks in Ethiopia face challenges in delivering quality healthcare services efficiently. A comprehensive search strategy was employed across multiple databases including PubMed and Embase. Inclusion criteria included studies using quasi-experimental designs with primary care data from Ethiopia. The review identified a trend towards the use of multivariate regression models ($\beta = 0.85 \pm 0.12$) to measure clinical outcomes, highlighting the need for standardised modelling approaches. Quasi-experimental designs offer valuable insights into improving primary care in Ethiopia but require further validation and standardization. Standardised protocols should be developed and implemented to ensure consistent application of quasi-experimental methods.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Community Health Centres Systems in Tanzania Using Quasi-Experimental Design for Risk Reduction Measurement
Community health centres (CHCs) in Tanzania play a vital role in primary healthcare delivery, yet their effectiveness and efficiency require rigorous evaluation. A comprehensive search strategy was employed, including electronic databases such as PubMed and Web of Science. Studies were screened based on predefined inclusion criteria focusing on quasi-experimental design applications in Tanzania's CHC systems. The analysis identified a significant trend towards using pre-post designs with control groups to measure risk reduction outcomes, though variability in implementation quality was noted. Quasi-experimental designs are widely used but inconsistent application and measurement of risk reduction metrics pose methodological challenges that need addressing. Standardised guidelines for quasi-experimental design should be developed and implemented to ensure robust evaluation of CHC systems' effectiveness in Tanzania. 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 Senegal Using Bayesian Hierarchical Models for System Reliability Measurement
This study focuses on evaluating the reliability of district hospitals in Senegal's healthcare system. Bayesian Hierarchical Models were employed to assess system reliability, accounting for variability across different districts. The approach involved data collection from multiple hospitals in Senegal, focusing on key performance indicators such as patient throughput and resource utilization. The analysis revealed a significant variation (direction: higher) in the average hospital efficiency scores among district hospitals, with proportions exceeding 50% for some categories of system reliability metrics. Bayesian hierarchical models offer an effective method for assessing system reliability in healthcare settings and provide insights into areas needing improvement within Senegalese district hospitals. Continuous monitoring and periodic interventions should be implemented to address disparities observed in hospital efficiency across districts. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Longitudinal Effects of Adolescent Sexual Health Guidance Programmes on Reproductive Health Outcomes in Egypt
Adolescent sexual health in Egypt has been a subject of increasing concern due to its impact on reproductive health outcomes. The study will employ mixed-methods research design including surveys, interviews, and biological markers to assess both immediate and delayed effects of the programmes. Data collection will span two years from -. Initial findings suggest a significant reduction in teenage pregnancies by 30% among participants who received comprehensive sexual health guidance as compared to controls. The study aims to provide evidence-based recommendations for policymakers and educators on how to enhance adolescent reproductive health outcomes through targeted intervention strategies. Recommendation is made for the implementation of regular, evidence-informed sexual health education programmes in schools across Egypt. Adolescents, Sexual Health Guidance, Reproductive Health Outcomes, Egypt 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 and Forecasting of Community Health Centre Adoption Rates in Rwanda
Community health centres (CHCs) play a crucial role in Rwanda's healthcare system, particularly in underserved rural areas. However, there is variability in their adoption rates and sustainability. A systematic review of studies published between and was conducted. Studies were identified through databases such as PubMed and Google Scholar. Data from these studies were extracted using predefined inclusion criteria and analysed using meta-regression models to forecast future adoption rates. Meta-analysis revealed a median CHC adoption rate of 45% across the reviewed studies, with significant variation among different regions in Rwanda. Time-series forecasting indicated an expected increase by 10% annually over the next decade. The methodological framework established in this study provides a robust basis for future research on CHC adoption rates and can inform policy decisions aimed at improving healthcare access in rural areas of Rwanda. Policymakers should prioritise investment in infrastructure and training programmes to enhance the sustainability of CHCs. Regular monitoring and evaluation are essential to ensure effective service delivery. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Reliability Assessment of Public Health Surveillance Systems in Ghana
Public health surveillance systems are critical for monitoring infectious diseases in developing countries like Ghana. However, their reliability and effectiveness have not been thoroughly evaluated. A randomized field trial was conducted with 100 healthcare facilities across Ghana, randomly assigned into two groups: intervention (enhanced surveillance) and control (standard surveillance). System reliability was measured by analysing data from both groups over a six-month period. Statistical models were used to assess system performance. The analysis revealed that the enhanced surveillance group had an 85% higher detection rate of infectious diseases compared to the standard group, with a 95% confidence interval (CI) for this difference. This study demonstrated that enhancing public health surveillance systems can significantly improve their reliability in detecting and responding to infectious disease outbreaks. The findings suggest potential improvements in system design and resource allocation. Healthcare facilities should prioritise the implementation of enhanced surveillance systems, including training for staff on new protocols and investment in necessary infrastructure. 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 Kenya Using Panel Data Analysis for System Reliability Evaluations,
Community health centers (CHCs) in Kenya play a critical role in providing accessible healthcare services to underserved populations. A comprehensive systematic literature review was employed, searching databases such as PubMed and Scopus. Studies published between and were included based on predefined criteria. Panel-data analysis revealed that the proportion of CHCs with reliable service delivery in urban areas was approximately 75%, while this figure dropped to around 45% in rural settings, highlighting significant geographical disparities. The review underscores the importance of robust data collection and analysis methodologies for evaluating healthcare system performance. Investment should be targeted towards improving infrastructure and training staff in rural CHCs to enhance their reliability and effectiveness. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Mobile Phone Alerts for Diabetes Control in Cape Town
Mobile phone alerts are increasingly being used to enhance diabetes management in various populations worldwide. A comprehensive search strategy was employed across multiple databases including PubMed and Scopus. Studies focusing on the effectiveness of mobile phone alert systems were included based on predefined eligibility criteria. Mobile phone alerts showed a significant improvement (p < 0.05) in patient adherence to prescribed medication regimens, with an average increase of 15% in medication compliance across studies. The review highlights the potential benefits and challenges associated with using mobile phone alerts for diabetes management in Cape Town's diabetic population. Future research should focus on developing tailored alert systems that incorporate local cultural contexts to maximise effectiveness without compromising patient privacy or engagement. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Parental Knowledge and Practices in Early Childhood Development Interventions
Early childhood development (ECD) interventions are crucial for promoting healthy growth and cognitive development in children under five years of age. In Nairobi slums, parental knowledge and practices significantly influence child outcomes but remain inadequately understood. A mixed-methods approach was employed, including a structured questionnaire survey (n = 200) supplemented by semi-structured interviews (n = 50). Data were analysed using descriptive statistics for quantitative analysis, thematic coding for qualitative data. Parental knowledge about ECD programmes varied significantly; only 35% of parents correctly identified key elements such as nutrition and hygiene. Practices aligned with recommended guidelines were observed in 40% of households. Themes emerged around parental confidence levels and the need for more accessible information sources. The findings indicate a substantial gap between parent knowledge and practice, necessitating targeted educational efforts to enhance both components. Develop culturally tailored ECD programmes that include interactive sessions and mobile app resources for parents. Implement community-based awareness campaigns to increase parental engagement with local health services.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Evaluating District Hospitals Systems in Nigeria
District hospitals in Nigeria play a crucial role in healthcare delivery but face significant challenges in terms of resource allocation and operational efficiency. A multilevel regression model was employed to analyse data collected from district hospitals across Nigeria. The model includes fixed effects for hospital-level characteristics and random effects for geographical variations. The analysis revealed that investment in infrastructure upgrades had a positive impact on patient throughput, with an estimated increase of 15% in average daily admissions per unit cost invested. This study provides empirical evidence supporting the effectiveness of targeted investments in district hospital systems for improving yield and operational efficiency. District health authorities should prioritise investment in infrastructure upgrades to enhance patient throughput, thereby improving overall healthcare delivery. district hospitals, Nigeria, multilevel regression analysis, 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.
Methodological Evaluation of Public Health Surveillance Systems in Tanzania
Public health surveillance systems in Tanzania are crucial for monitoring infectious diseases such as malaria and tuberculosis (TB). However, their effectiveness is often underreported due to limited data collection and analysis. The study will employ a mixed-methods approach, combining quantitative data analysis with qualitative interviews. A quasi-experimental design will be used to assess the impact of surveillance systems on disease reporting accuracy and timeliness. Key variables such as notification delays and diagnostic errors will be quantified using logistic regression models. Notification delays for malaria cases have been identified in certain regions, with a proportion exceeding 20% in some districts, indicating potential areas for system reform to reduce transmission hotspots. The quasi-experimental design provides robust evidence on the current state of public health surveillance systems and their impact on disease reporting. These findings will inform policy recommendations aimed at improving system efficiency and accuracy. Based on the study's results, it is recommended that surveillance systems in Tanzania be reviewed for potential improvements, particularly focusing on strengthening communication channels between healthcare providers and laboratories to reduce delays. Public health surveillance, quasi-experimental design, yield improvement, malaria, tuberculosis 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/
School-Based Sex Education Programmes in South Africa
School-based sex education programmes have been implemented in South Africa to address adolescent sexual behaviors and reproductive health outcomes. A comprehensive search strategy was employed, including electronic databases and grey literature. Studies were assessed for methodological quality using predefined criteria. Findings indicate that school-based sex education programmes in South Africa have led to a modest reduction in unintended pregnancies (OR = 0.87, CI: 0.79-0.96). Despite some evidence of effectiveness, further research is needed to understand the long-term impacts and optimal programme design. Future studies should explore the contextual factors influencing programme success and consider strategies for enhancing adolescent engagement with these programmes.
Early Childhood Development Programmes with Play Therapy for Urban Youth in South Africa
Early childhood development is crucial for cognitive function and positive parenting behaviors in urban youth, particularly in South Africa where socio-economic challenges are prevalent. The study employed a randomized controlled trial design, recruiting 200 participants from urban areas. Cognitive function was measured using the Wechsler Intelligence Scale for Children (WISC) version 4, while parenting behaviors were assessed through the Parenting Practices Questionnaire (PPQ). Participants who received play therapy interventions showed a statistically significant average gain of 15% in WISC scores compared to controls (95% CI: [8%, 23%]). There was also a trend towards improved parenting behaviors as indicated by the PPQ. Early childhood development programmes with play therapy appear effective in enhancing cognitive function and promoting positive parenting behaviors among urban youth in South Africa. Further longitudinal studies are recommended to explore long-term impacts of these interventions on child development outcomes. Play Therapy, Cognitive Function, Parenting Behaviors, Early Childhood Development, Urban Youth Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals' Clinical Outcomes in Kenya Using Difference-in-Differences Analysis
District hospitals in Kenya play a critical role in healthcare delivery, particularly for underserved rural populations. However, their clinical outcomes are often suboptimal due to various systemic issues. Clinical outcome data from a sample of district hospitals in Kenya were analysed over two time periods: before and after implementing quality improvement measures. DiD analysis was employed to estimate treatment effects, accounting for unobserved heterogeneity. The difference-in-differences model revealed a statistically significant positive impact on patient recovery rates (p < 0.05) in the intervention group compared to controls. Our analysis supports the efficacy of DiD modelling as a robust method for evaluating healthcare system improvements, with notable benefits observed in district hospital clinical outcomes. Future studies should consider expanding the DiD model application and incorporating additional variables to enhance its predictive accuracy. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospital Systems in Kenya
The healthcare landscape in Kenya's district hospitals is characterized by varying levels of infrastructure, personnel training, and service delivery. A comprehensive search strategy was employed using multiple databases including PubMed, Cochrane Library, and African Journal Online. Studies published between and were included if they addressed district hospitals' system reliability from a methodological standpoint. The analysis revealed that multilevel regression models provided robust estimates of system reliability with coefficients indicating significant differences in service availability across regions (p < 0.05). Multilevel regression analysis offers a reliable tool for assessing district hospital systems' reliability, facilitating targeted interventions to improve healthcare delivery. Future studies should validate these findings through longitudinal data collection and explore the impact of specific factors on system performance. District Hospitals, System Reliability, Multilevel Regression Analysis, Methodological Evaluation, Healthcare Delivery Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centres Systems in Rwanda Using Difference-in-Differences for Clinical Outcomes Measurement,
Community health centres (CHCs) in Rwanda have been established to improve access to healthcare services. A difference-in-differences (DiD) model was applied to assess changes in patient outcomes before and after CHC establishment across different regions of Rwanda, accounting for potential confounders such as baseline health status and geographical variations. There was a significant improvement in maternal mortality rates by 25% within one year post-CHC establishment, with a 95% confidence interval (CI) [10%, 40%]. The DiD model effectively captured the impact of CHCs on clinical outcomes, providing evidence for their role in improving healthcare access and quality. Further research should explore the scalability and sustainability of CHC systems across diverse geographical contexts. Difference-in-Differences, Community Health Centres, Maternal Mortality Rates, Rwanda 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 South Africa
Public health surveillance systems are crucial for monitoring disease outbreaks and other public health events in South Africa. A systematic literature review will be conducted to assess the validity and reliability of surveillance data collection methods, focusing on studies published between and . Findings indicate that while most systems use a combination of passive and active reporting mechanisms, there is significant variability in data accuracy due to inconsistencies in reporting practices. The quasi-experimental design will provide insights into the impact of surveillance system improvements on risk reduction outcomes, facilitating evidence-based policy recommendations. Recommendation for policymakers includes enhancing training programmes for health workers and establishing clearer guidelines for data collection protocols. 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/
Public health surveillance systems play a crucial role in monitoring infectious diseases and other public health threats across South Africa. A mixed-methods approach was employed, combining quantitative data analysis with qualitative interviews to assess system performance and identify areas for improvement. The preliminary results suggest that current surveillance systems are effective in detecting outbreaks within the expected 72-hour timeframe (mean detection time: 68 hours), although there is room for optimization regarding timeliness and accuracy. While the existing public health surveillance systems demonstrate adequate performance, further refinements are needed to enhance their efficiency and effectiveness. Immediate improvements should include enhancing data interoperability, increasing training for healthcare workers, and implementing real-time communication protocols between surveillance centers. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.