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Objective To assess the level of compliance with COVID-19 preventive measures and compliance-associated factors in the Rwanda community.Design Cross-sectional study.Settings Country-wide community survey in Rwanda.Participants 4763 participants were randomly sampled following the sampling frame used for the recent Rwanda Demographic Health Survey. Participants were aged between 22 years and 94 years.Outcomes The participants’ compliance with three preventive measures (wearing a face mask, washing hands and social distancing) was the main outcome.Methods From 14 February 2022 to 27 February 2022, a cross-sectional survey using telephone calls was conducted. Study questionnaires included different questions such as participants’ demographics and compliance with COVID-19 preventives measures. Verbal consent was obtained from each participant. The compliance on three main preventive measures (wearing a mask, washing hands and social distancing) were the main outcomes. Univariate and multivariable logistic regression analyses were performed to evaluate factors associated with compliance (age, gender, level of education, socioeconomic status).Results Compliance with the three primary preventive measures (washing hands 98%, wearing a mask 97% and observing social distance 98%) was at a rate of 95%. The respondents’ mean age was 46±11 SD (range 22–98) years. In addition, 69% were female and 86% had attended primary education. Bivariate and regression analyses indicated a significant association among the three primary preventive measures (p

Objective A vital component of a prehospital emergency care system is getting an injured patient to the right hospital at the right time. Process and information flow mapping are recognised methods to show where efficiencies can be made. We aimed to understand the process and information flows used by the prehospital emergency service in transporting community emergencies in Rwanda in order to identify areas for improvement.Design Two facilitated process/information mapping workshops were conducted. Process maps were produced in real time during discussions and shared with participants for their agreement. They were further validated by field observations.Setting The study took place in two prehospital care settings serving predominantly rural and predominantly urban patients.Participants 24 healthcare professionals from various cadres. Field observations were done on 49 emergencies across both sites.Results Two maps were produced, and four main process stages were described: (1) call triage by the dispatch/call centre team, (2) scene triage by the ambulance team, (3) patient monitoring by the ambulance team on the way to the health facility and (4) handover process at the health facility. The first key finding was that the rural site had multiple points of entry into the system for emergency patients, whereas the urban system had one point of entry (the national emergency number); processes were otherwise similar between sites. The second was that although large amounts of information were collected to inform decision-making about which health facility to transfer patients to, participants found it challenging to articulate the intellectual process by which they used this to make decisions; guidelines were not used for decision-making.Discussion We have identified several areas of the prehospital care processes where there can be efficiencies. To make efficiencies in the decision-making process and produce a standard approach for all patients will require protocolising care pathways.

Rationale: The COVID-19 pandemic along with its devastating impact on human lives has disrupted the socioeconomic situation worldwide. Rwanda has adopted lockdowns and other measures to prevent the spread of the COVID-19 pandemic. Recent studies documented the macro-level socio-economic pandemic impact but the impact on a household’s daily life has been scarcely documented especially in low-and-middle-income countries. Objective: This work describes the interplay between multiple factors to assess the socio-economic impact of COVID-19 on the Rwandan population at the micro-level (household). Methods: Data from a country-wide community survey conducted in Rwanda between December 2021 and March 2022 were used. A total of 26,412 response forms were received from around 4400 participants surveyed in 6 recurrent bi-weekly phases where participants were randomly selected. The Multivariable Logistic regression model was fitted to data with a backward stepwise elimination algorithm to assess the socioeconomic impact of COVID-19 on households’ income. Factors considered in this study are gender, age group, residence, level of education, occupation, change in employment status, socioeconomic status, and marital status. Results: The multivariable logistic regression model provided the factors associated with the decline in income due to COVID-19. The results show that people living without a partner are more likely to experience income decline due to COVID-19 than people living with their partner. It is seen that the higher the number of children in a household, the higher the risk of experiencing a decrease in income. Taking into consideration the education level and comparing people with post-secondary and university level vis-a-vis people who did not attend school, the latter are 27 times more likely to experience a decrease in their income, those who attended primary school are 5 times more likely to experience a decrease in income, and those who attended secondary school are almost 2 times more likely to experience a decrease in income. Conclusions: The findings from this research will be used by policymakers and other stakeholders to design and implement preventive and responsive measures for future pandemics that should be multifactorial and tailored to transversal parameters like gender and residence.

Abstract Background Since the outbreak of COVID-19 pandemic in Rwanda, a vast amount of SARS-COV-2/COVID-19-related data have been collected including COVID-19 testing and hospital routine care data. Unfortunately, those data are fragmented in silos with different data structures or formats and cannot be used to improve understanding of the disease, monitor its progress, and generate evidence to guide prevention measures. The objective of this project is to leverage the artificial intelligence (AI) and data science techniques in harmonizing datasets to support Rwandan government needs in monitoring and predicting the COVID-19 burden, including the hospital admissions and overall infection rates. Methods The project will gather the existing data including hospital electronic health records (EHRs), the COVID-19 testing data and will link with longitudinal data from community surveys. The open-source tools from Observational Health Data Sciences and Informatics (OHDSI) will be used to harmonize hospital EHRs through the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The project will also leverage other OHDSI tools for data analytics and network integration, as well as R Studio and Python. The network will include up to 15 health facilities in Rwanda, whose EHR data will be harmonized to OMOP CDM. Expected results This study will yield a technical infrastructure where the 15 participating hospitals and health centres will have EHR data in OMOP CDM format on a local Mac Mini (“data node”), together with a set of OHDSI open-source tools. A central server, or portal, will contain a data catalogue of participating sites, as well as the OHDSI tools that are used to define and manage distributed studies. The central server will also integrate the information from the national Covid-19 registry, as well as the results of the community surveys. The ultimate project outcome is the dynamic prediction modelling for COVID-19 pandemic in Rwanda. Discussion The project is the first on the African continent leveraging AI and implementation of an OMOP CDM based federated data network for data harmonization. Such infrastructure is scalable for other pandemics monitoring, outcomes predictions, and tailored response planning.

Abstract Background Innovative use of mobile health (mHealth) technology in timely management of childbirth complications is a promising strategy, but its evidence base is limited. The Safe Delivery mHealth Application (SDA) is one of the recent mhealth applications (loaded in smartphones) which is a clinical decision support and training tool for basic emergency obstetric and newborn care (BEmONC). This paper describes, the health providers’ experiences, perceptions, and acceptability of using the SDA, as well as the perceptions of key stakeholders. Methods A mixed-methods approach was utilized. Quantitative methods consisted of a self-reported acceptability survey, administered to 54 nurses and midwives, including questions on their usage and perceptions of the SDA. Descriptive statistics were employed to analyze the survey data. Qualitative methods included two focus group discussions with 24 nurses and midwives, and six key informant interviews with stakeholders (maternity matrons, responsible for maternal and child health, and district hospital managers). Thematic analysis was performed and selected quotations used to illustrate themes. The study took place in two district hospitals in Rwanda. Results Quantitative results found that 31 (57.4%) participants used the SDA four to six times per week. Many participants felt more confident (53.7%) and better at their job (40.7%) since having the SDA. Likert scale survey responses (1–5, 1 = Strongly Disagree, 5 = Strongly Agree) indicated general agreement that SDA is easy to use (Mean = 4.46), is an effective decision support tool (4.63), and training tool (4.65). Qualitative results included themes on perceived usefulness; professional growth acquired through the use of the SDA; SDA, an empowering, intuitive, and user-friendly technology; desired SDA features and functions; benefits of SDA as perceived by key informants, and future use of the SDA. Conclusions The nurses and midwives perceive the SDA as having improved their ability to manage childbirth complications. Key stakeholders also perceive the SDA as a useful tool with a reasonable cost and recommend its implementation in routine practices. This study deepens the understanding of the potential benefits of mHealth such as the SDA in low-income settings, like Rwanda. It also provides more evidence on the impact of mHealth in assuring quality BEmONC.

Abstract Background Hypertension remains the major risk factor for cardiovascular diseases (CVDs) worldwide with a prevalence and mortality in low- and middle-income countries (LMICs) among the highest. The early detection of hypertension risk factors is a crucial pillar for CVD prevention. Design and method This cross-sectional study included 4284 subjects, mean age 46 ± 16SD, 56.4% females and mean BMI 26.6 ± 3.7 SD. Data were collected through a screening campaign in rural area of Kirehe District, Eastern of Rwanda, with the objective to characterize and examine the prevalence of elevated blood pressure (BP) and other CVD risk factors. An adapted tool from the World Health Organization STEPwise Approach was used for data collection. Elevated BP was defined as ≥ 140/90 mm/Hg and elevated blood glucose as blood glucose ≥ 100 mg/dL after a 6-h fast. Results Of the sampled population, 21.2% (n = 910) had an elevated BP at screening; BP was elevated among individuals not previously known to have HTN in 18.7% (n = 752). Among individuals with a prior diagnosis of HTN, 62.2% (n = 158 of 254) BP was uncontrolled. Age, weight, smoking, alcohol history and waist circumference were associated with BP in both univariate analyses and multivariate analysis. Conclusion High rates of elevated BP identified through a health screening campaign in this Rwandan district were surprising given the rural characteristics of the district and relatively low population age. These data highlight the need to implement an adequate strategy for the prevention, diagnosis, and control of HTN that includes rural areas of Rwanda as part of a multicomponent strategy for CVD prevention.

Abstract Background In low and middle-income countries, nurses and midwives are the frontline healthcare workers in obstetric care. Insights into experiences of these healthcare workers in managing obstetric emergencies are critical for improving the quality of care. This article presents such insights, from the nurses and midwives working in Rwandan district hospitals, who reflected on their experiences of managing the most common birth-related complications; postpartum hemorrhage (PPH) and newborn asphyxia. Rwanda has made remarkable progress in obstetric care. However, challenges remain in the provision of high-quality basic emergency obstetric and newborn care (BEmONC). This study is a qualitative part of a broader research project about implementation of an mLearning and mHealth decision support tool in BEmONC services in Rwanda. Methods In this exploratory qualitative aspect of the research, four focus group discussions (FGDs) with 26 nurses and midwives from two district hospitals in Rwanda were conducted. Each FGD was made up of two parts. The first part focused on the participants’ reflections on the research results (from the previous study), while the second part explored their experiences of delivering obstetric care services. The research results included: survey results reflecting their knowledge and skills of PPH management and of neonatal resuscitation (NR); and findings from a six-month record review of PPH management and NR outcomes, from the district hospitals under study. Data were analyzed using hybrid thematic analysis. Results The analysis revealed three main themes: (1) reflections to the baseline research results, (2) self-reflection on the current practices, and (3) contextual factors influencing the delivery of BEmONC services. Nurses and midwives felt that the presented findings were a true reflection of the reality and offered diverse explanations for the results. The participants’ narratives of lived experiences of providing BEmONC services are also presented. Conclusion The insights of nurses and midwives regarding the management of birth-related complications revealed multi-faceted factors that influence the quality of their obstetric care. Even though the study was focused on PPH management and NR, the resulting recommendations to improve quality of care could benefit the broader field of maternal and child health, particularly in low and middle-income countries.

Abstract Background Globally, mobile health (mHealth) applications are known for their potential to improve healthcare providers’ access to relevant and reliable health information. Besides, electronic decision support tools, such as the Safe Delivery mHealth Application (SDA), may help to reduce clinical errors and to ensure quality care at the point of service delivery. The current study investigated the use of the SDA and its relationship to basic emergency obstetric and newborn care (BEmONC) outcomes for the most frequent complications in Rwanda; post-partum haemorrhage (PPH) and newborn asphyxia. Methods The study adopted a pre–post intervention design. A pre-intervention record review of BEmONC outcomes: Apgar score and PPH progressions, was conducted for 6 months’ period (February 2019 - July 2019). The intervention took place in two district hospitals in Rwanda and entails the implementation of the SDA for 6 months (October 2019- March 2020), and included 54 nurses and midwives using the SDA to manage PPH and neonatal resuscitation. Six months’ post-SDA intervention, the effect of the SDA on BEmONC outcomes was evaluated. The study included 327 participants (114 cases of PPH and 213 cases of neonatal complications). The analysis compared the outcome variables between the baseline and the endline data. Fisher’s exact test was used to compare the proportions and test between-group differences and significance level set at p