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Childhood stunting in its moderate and severe forms is a major global problem and an important indicator of child health. Rwanda has made progress in reducing the prevalence of stunting. However, the burden of stunting and its geographical disparities have precipitated the need to investigate its spatial clusters and attributable factors. Here, we assessed the determinants of under‐5 stunting and mapped its prevalence to identify areas where interventions can be directed. Using three combined rounds of the nationally representative Rwanda Demographic and Health Surveys of 2010, 2015 and 2020, we employed the Blinder‐Oaxaca decomposition analysis and the hotspot and cluster analyses to quantify the contributions of key determinants of stunting. Overall, there was a 7.9% and 10.3% points reduction in moderate stunting among urban and rural areas, respectively, and a 2.8% and 8.3% points reduction in severe stunting in urban and rural areas, respectively. Child age, wealth index, maternal education and the number of antenatal care visits were key determinants for the reduction of moderate and severe stunting. Over time, persistent statistically significant hotspots for moderate and severe stunting were observed in Northern and Western parts of the country. There is a need for an adaptive scaling approach when implementing national nutritional interventions by targeting high‐burden regions. Stunting hotspots in Western and Northern provinces underscore the need for coordinated subnational initiatives and strategies such as empowering the rural poor, enhancing antenatal health care, and improving maternal health and education levels to sustain the gains made in reducing childhood stunting. Key messages: Stunting among children under 5 is a major problem in Rwanda, increasing the need for more tailored interventions and increased investments in child health.The prevalence of moderate and severe stunting among children aged 0–5 years in Rwanda has reduced over the last decade.High hotspots indicating childhood moderate and severe stunting clustered in the Northern and Western provinces of the country remain persistent.There is a need for multisectoral collaboration in addressing the key determinants of stunting and sustaining the reduction that has been achieved in the last decade. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic resulted in drops in access to and availability of a number of evidence-based interventions (EBIs) known to reduce under-5 mortality (U5M) across a wide range of countries, including Rwanda. We aimed to understand the strategies and contextual factors associated with preventing or mitigating drops nationally and subnationally, and the extent to which previous efforts to reduce U5M supported the maintenance of healthcare delivery. Methods: We used a convergent mixed methods implementation science approach, guided by hybrid implementation research and resiliency frameworks. We triangulated data from three sources: desk review of available documents, existing routine data from the health management information system, and key informant interviews (KIIs). We analyzed quantitative data through scatter plots using interrupted time series analysis to describe changes in EBI access, uptake, and delivery. We used a Poisson regression model to estimate the impact of COVID-19 on health management information system indicators, adjusting for seasonality. We used thematic analysis of coded interviews to identify emerging patterns and themes. Results: We found moderate 4% (IRR = 0.96; 95%CI: 0.93, 1.00) and 5% (IRR = 0.95; 95%CI: 0.92, 0.99) drops in pentavalent and rotavirus 2 doses vaccines administered, respectively. Nationally, there was a 5% drop in facility-based delivery (IRR = 0.95; 95%CI: 0.92, 0.99). Lockdown and movement restrictions and community and health-worker fear of COVID-19 were barriers to service delivery early in the pandemic. Key implementation strategies to prevent or respond to EBI drops included leveraging community-based healthcare delivery, data use for decision-making, mentorship and supervision, and use of digital platform. Conclusions: While Rwanda had drops in some EBIs early in the pandemic, especially during the initial lockdown, this was rapidly identified, and response implemented. The resiliency of the health system was associated with the Rwandan health system's ability to learn and adapt, encouraging a flexible response to fit the situation., Competing Interests: The authors have no competing interests to declare., (Copyright: © 2024 The Author(s).)

Background: The coronavirus disease 2019 (COVID-19) pandemic led to disruptions of health service delivery in many countries; some were more resilient in either limiting or rapidly responding to the disruption than others. We used mixed methods implementation research to understand factors and strategies associated with resiliency in Rwanda and Bangladesh, focussing on how evidence-based interventions targeting amenable under-five mortality that had been used during the Millennium Development Goal (MDG) period (2000-15) were maintained during the early period of COVID-19., Methods: We triangulated data from three sources - a desk review of available documents, existing quantitative data on evidence-based intervention coverage, and key informant interviews - to perform a comparative analysis using multiple case studies methodology, comparing contextual factors (barriers or facilitators), implementation strategies (existing from 2000-15, new, or adapted), and implementation outcomes across the two countries. We also analysed which health system resiliency capabilities were present in the two countries., Results: Both countries experienced many of the same facilitators for resiliency of evidence-based interventions for children under five, as well as new, pandemic-specific barriers during the early COVID-19 period (March to December 2020) that required targeted implementation strategies in response. Common facilitators included leadership and governance and a culture of accountability, while common barriers included movement restrictions, workload, and staff shortages. We saw a continuity of implementation strategies that had been associated with success in care delivery during the MDG period, including data use for monitoring and decision-making, as well as building on community health worker programmes for community-based health care delivery. New or adapted strategies used in responding to new barriers included the expanded use of digital platforms. We found implementation outcomes and strong resilience capabilities, including awareness and adaptiveness, which were related to pre-existing facilitators and implementation strategies (continued and new)., Conclusions: The strategies and contextual factors Rwanda and Bangladesh leveraged to build 'everyday resilience' before COVID-19, i.e. during the MDG period, likely supported the maintained delivery of the evidence-based interventions targeting under-five mortality during the early stages of the pandemic. Expanding our understanding of pre-existing factors and strategies that contributed to resilience before and during the pandemic is important to support other countries' efforts to incorporate 'everyday resilience' into their health systems., Competing Interests: Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and disclose no relevant interests., (Copyright © 2024 by the Journal of Global Health. All rights reserved.)

Background: Mathematical modeling of infectious diseases is an important decision-making tool for outbreak control. However, in Africa, limited expertise reduces the use and impact of these tools on policy. Therefore, there is a need to build capacity in Africa for the use of mathematical modeling to inform policy. Here we describe our experience implementing a mathematical modeling training program for public health professionals in East Africa., Methods: We used a deliverable-driven and learning-by-doing model to introduce trainees to the mathematical modeling of infectious diseases. The training comprised two two-week in-person sessions and a practicum where trainees received intensive mentorship. Trainees evaluated the content and structure of the course at the end of each week, and this feedback informed the strategy for subsequent weeks., Findings: Out of 875 applications from 38 countries, we selected ten trainees from three countries - Rwanda (6), Kenya (2), and Uganda (2) - with guidance from an advisory committee. Nine trainees were based at government institutions and one at an academic organization. Participants gained skills in developing models to answer questions of interest and critically appraising modeling studies. At the end of the training, trainees prepared policy briefs summarizing their modeling study findings. These were presented at a dissemination event to policymakers, researchers, and program managers. All trainees indicated they would recommend the course to colleagues and rated the quality of the training with a median score of 9/10., Conclusions: Mathematical modeling training programs for public health professionals in Africa can be an effective tool for research capacity building and policy support to mitigate infectious disease burden and forecast resources. Overall, the course was successful, owing to a combination of factors, including institutional support, trainees' commitment, intensive mentorship, a diverse trainee pool, and regular evaluations., Competing Interests: The authors have no competing interests to declare., (Copyright: © 2024 The Author(s).)

Background: Between 2000-2015, many low- and middle-income countries (LMICs) implemented evidence-based interventions (EBIs) known to reduce under-5 mortality (U5M). Even among LMICs successful in reducing U5M, this drop was unequal subnationally, with varying success in EBI implementation. Building on mixed methods multi-case studies of six LMICs (Bangladesh, Ethiopia, Nepal, Peru, Rwanda, and Senegal) leading in U5M reduction, we describe geographic and wealth-based equity in facility-based delivery (FBD), a critical EBI to reduce neonatal mortality which requires a trusted and functional health system, and compare the implementation strategies and contextual factors which influenced success or challenges within and across the countries., Methods: To obtain equity gaps in FBD coverage and changes in absolute geographic and wealth-based equity between 2000-2015, we calculated the difference between the highest and lowest FBD coverage across subnational regions and in the FBD coverage between the richest and poorest wealth quintiles. We extracted and compared contextual factors and implementation strategies associated with reduced or remaining inequities from the country case studies., Results: The absolute geographic and wealth-based equity gaps decreased in three countries, with greatest drops in Rwanda - decreasing from 50 to 5% across subnational regions and from 43 to 13% across wealth quintiles. The largest increases were seen in Bangladesh - from 10 to 32% across geography - and in Ethiopia - from 22 to 58% across wealth quintiles. Facilitators to reducing equity gaps across the six countries included leadership commitment and culture of data use; in some countries, community or maternal and child health insurance was also an important factor (Rwanda and Peru). Barriers across all the countries included geography, while country-specific barriers included low female empowerment subnationally (Bangladesh) and cultural beliefs (Ethiopia). Successful strategies included building on community health worker (CHW) programs, with country-specific adaptation of pre-existing CHW programs (Rwanda, Ethiopia, and Senegal) and cultural adaptation of delivery protocols (Peru). Reducing delivery costs was successful in Senegal, and partially successful in Nepal and Ethiopia., Conclusion: Variable success in reducing inequity in FBD coverage among countries successful in reducing U5M underscores the importance of measuring not just coverage but also equity. Learning from FBD interventions shows the need to prioritize equity in access and uptake of EBIs for the poor and in remote areas by adapting the strategies to local context., (© 2024. The Author(s).)