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ObjectiveTo assess the level of compliance with COVID-19 preventive measures and compliance-associated factors in the Rwanda community.DesignCross-sectional study.SettingsCountry-wide community survey in Rwanda.Participants4763 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.OutcomesThe participants’ compliance with three preventive measures (wearing a face mask, washing hands and social distancing) was the main outcome.MethodsFrom 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).ResultsCompliance 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<0.05). The results showed factors associated significantly between the different models (p<0.05): proper mask use and social distancing in the hand washing model; hand washing, social distancing, avoiding handshakes and not attending gatherings in the proper mask use model; hand washing and avoiding handshakes in the social distancing model.ConclusionCompliance with the three key preventive measures against COVID-19 was high in the Rwandan community and these measures were interdependent. Therefore, the importance of all three measures should be emphasised for effective disease control.

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.

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.

Effective blood pressure (BP) monitoring is vital for the management of hypertension, allowing timely adjustments in treatment. This study focuses on the development and implementation of an innovative, locally designed eHealth technology, the HeartCare@Home system, to enhance the control and management of hypertension in outpatient noncommunicable disease (NCD) clinics in Rwanda. The HeartCare@Home system comprises a mobile health app that incorporates rapid SMS technology, an integrated dashboard for signal reception at the clinic office level, and a clinical decision support algorithm. This study aims to assess the clinical efficacy, feasibility, and acceptability of a novel eHealth technology, the HeartCare@Home system, that uses home and clinic-based automated BP monitoring with real-time management of elevated BP in an outpatient NCD clinic in Rwanda. This pilot study will use an interventional design with a crossover approach to test the clinical efficacy of the HeartCare@Home system at the NCD clinic of Kibagabaga District Hospital. A total of 140 patients with hypertension will take part in the study. All enrolled patients will be allocated to either the interventional group or the standard of care group. The follow-up for each group will be 6 months (3 months in each group follow-up). The data for the intervention group will be generated by our mobile health app, while data for the control group (standard care) will be retrieved from usual patient files at the NCD clinic. Data extraction sheets will be used for standard care data retrieval. The Feasibility of Intervention Measure and Acceptability of Intervention Measure tools will be used to cross-sectionally evaluate the feasibility and acceptability of the HeartCare@Home system. Data will be summarized with descriptive statistics. A paired sample 2-tailed t test will be used to test for differences between the pre- and postintervention records for hypertension control. This study will yield a technical infrastructure, the HeartCare@Home system, to support the control and management of hypertension in outpatient NCD clinics. It will introduce a new model of health care delivery through innovative technology that enables home-based BP monitoring. This will offer a unique technology to enable elevated BP control and timely hypertension management and will also ensure a real-time communication linkage between patients and the appropriate level of care. Furthermore, the findings from the assessment of the clinical efficacy, feasibility, and acceptability of the HeartCare@Home system will inform possible scalability of the system to more NCD clinics. The study is currently in the implementation stage. The HeartCare@Home project will address the important gap of low BP control rates in patients with hypertension, which has contributed to delayed consultations and increased cardiovascular mortality. Such eHealth technology infrastructure may also be scalable to other settings. DERR1-10.2196/66211.

ObjectivesTo determine the prevalence of proximal deep vein thrombosis (DVT) by ultrasound scanning, as well as associated clinical features and known risk factors, among medical and obstetrics–gynaecology inpatients in two Rwandan tertiary hospitals.DesignCross-sectional study.SettingsRwanda teaching hospitals: Kigali and Butare University Teaching Hospitals.Participants901 adult patients admitted to the Departments of Internal Medicine and Obstetrics–Gynecology (O&G) who were at least 21 years of age and willing to provide a consent.OutcomesPrevalence of proximal DVT, clinical features and known risk factors associated with DVT.MethodsBetween August 2015 and August 2016, participants were screened for DVT by compressive ultrasound of femoral and popliteal veins, conducted as a monthly cross-sectional survey of all consenting eligible inpatients. Patients completed a self-report survey on DVT risk factors. Prevalence of proximal DVT by compression ultrasonography was the primary endpoint, with univariate and multivariate regression analyses performed to assess associated clinical features and risk factors.ResultsProximal DVT was found in 5.5% of the study population, with similar rates in medical and O&G inpatients. The mean age was 41±16 SD (range, 21–91), 70% were female and 7% were pregnant. Univariate analysis showed active malignancy, immobilisation, prolonged recent travel and history of DVT to be significant risk factors for proximal DVT (all p values <0.05); while only active malignancy was an independent risk factor on multivariate regression (OR 5.2; 95% CI 2.0 to 13). Leg pain or tenderness, increased calf circumference, unilateral limb swelling or pitting oedema were predictive clinical features of DVT on both univariate analysis and multivariate regression (all p values <0.05).ConclusionProximal DVT prevalence is high among hospitalised medical and O&G patients in two tertiary hospitals in Rwanda. For reducing morbidity and mortality, research to develop Africa-specific clinical prediction tools for DVT and interventions to increase thromboprophylaxis use in the region are urgently needed.