Leveraging artificial intelligence and data science techniques in harmonizing, sharing, accessing and analyzing SARS-COV-2/COVID-19 data in Rwanda (LAISDAR Project): study design and rationale.

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.

High rates of undiagnosed and uncontrolled hypertension upon a screening campaign in rural Rwanda: a cross-sectional study.

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.

Stress Measured by Allostatic Load Score Varies by Reason for Immigration: The Africans in America Study.

OBJECTIVE: Reason for immigration as a biological stress has not been studied in Africans. Our goal was to determine in African immigrants, if biological stress measured by allostatic load score (ALS) varies by reason for immigration. METHODS: Using an ALS which had been previously developed with the National Health and Nutrition Examination Survey (NHANES) data to assess stress due to racism and nativity, ALS was calculated in 85 African immigrants (67% male, age 42 ± 10 years). For confirmation, we tested five additional ALS also built from NHANES. RESULTS: The two reasons for immigration which consistently had the lowest ALS were family reunification and lottery winner for self and immediate family. The other reasons for immigration such as study, asylum/refugee, and work had higher ALS. As reasons for immigration with the lowest ALS promoted family unity, they were combined (group 1) and the Africans who came for other reasons were combined (group 2). ALS in group 1 vs. group 2 was 1.96 ± 1.40 vs. 2.94 ± 1.87, P = 0.03. CONCLUSIONS: Biological stress varies by reason for immigration and appears to be mitigated by maintaining family unity. Overall, reason for immigration is an important biographical data likely to influence health.

Reversing the tide - diagnosis and prevention of T2DM in populations of African descent.

Populations of African descent are at the forefront of the worldwide epidemic of type 2 diabetes mellitus (T2DM). The burden of T2DM is amplified by diagnosis after preventable complications of the disease have occurred. Earlier detection would result in a reduction in undiagnosed T2DM, more accurate statistics, more informed resource allocation and better health. An underappreciated factor contributing to undiagnosed T2DM in populations of African descent is that screening tests for hyperglycaemia, specifically, fasting plasma glucose and HbA1c, perform sub-optimally in these populations. To offset this problem, combining tests or adding glycated albumin (a nonfasting marker of glycaemia), might be the way forward. However, differences in diet, exercise, BMI, environment, gene-environment interactions and the prevalence of sickle cell trait mean that neither diagnostic tests nor interventions will be uniformly effective in individuals of African, Caribbean or African-American descent. Among these three populations of African descent, intensive lifestyle interventions have been reported in only the African-American population, in which they have been found to provide effective primary prevention of T2DM but not secondary prevention. Owing to a lack of health literacy and poor glycaemic control in Africa and the Caribbean, customized lifestyle interventions might achieve both secondary and primary prevention. Overall, diagnosis and prevention of T2DM requires innovative strategies that are sensitive to the diversity that exists within populations of African descent.

Time to glucose peak during an oral glucose tolerance test identifies prediabetes risk.

CONTEXT: Morphological characteristics of the glucose curve during an oral glucose tolerance test (OGTT) (time to peak and shape) may reflect different phenotypes of insulin secretion and action, but their ability to predict diabetes risk is uncertain. OBJECTIVE: To compare the ability of time to glucose peak and curve shape to detect prediabetes and ß-cell function. DESIGN AND PARTICIPANTS: In a cross-sectional evaluation using an OGTT, 145 adults without diabetes (age 42±9 years (mean±SD), range 24-62 years, BMI 29.2±5.3 kg/m2 , range 19.9-45.2 kg/m2 ) were characterized by peak (30 minutes vs >30 minutes) and shape (biphasic vs monophasic). MAIN OUTCOME MEASURES: Prediabetes and disposition index (DI)-a marker of ß-cell function. RESULTS: Prediabetes was diagnosed in 36% (52/145) of participants. Peak>30 minutes, not monophasic curve, was associated with increased odds of prediabetes (OR: 4.0 vs 1.1; P<.001). Both monophasic curve and peak>30 minutes were associated with lower DI (P≤.01). Time to glucose peak and glucose area under the curves (AUC) were independent predictors of DI (adjR2 =0.45, P<.001). CONCLUSION: Glucose peak >30 minutes was a stronger independent indicator of prediabetes and ß-cell function than the monophasic curve. Time to glucose peak may be an important tool that could enhance prediabetes risk stratification.

The Association between Stress Measured by Allostatic Load Score and Physiologic Dysregulation in African Immigrants: The Africans in America Study.

INTRODUCTION: Allostatic load score (ALS) summarizes the physiological effect of stress on cardiovascular, metabolic and immune systems. As immigration is stressful, ALS could be affected. OBJECTIVE: Associations between age of immigration, reason for immigration, and unhealthy assimilation behavior and ALS were determined in 238 African immigrants to the United States (age 40 ± 10, mean ± SD, range 21-64 years). METHODS: ALS was calculated using 10 variables from three domains; cardiovascular (SBP, DBP, cholesterol, triglyceride, homocysteine), metabolic [BMI, A1C, albumin, estimated glomerular filtration rate (eGFR)], and immunological [high-sensitivity C-reactive protein (hsCRP)]. Variables were divided into sex-specific quartiles with high-risk defined by the highest quartile for each variable except for albumin and eGFR, which used the lowest quartile. One point was assigned if the variable was in the high-risk range and 0 if not. Unhealthy assimilation behavior was defined by a higher prevalence of smoking, alcohol consumption, or sedentary activity in immigrants who lived in the US for ≥10 years compare to <10 years. RESULTS: Sixteen percent of the immigrants arrived in the US as children (age < 18 years); 84% arrived as adults (age ≥ 18 years). Compared to adulthood immigrants, childhood immigrants were younger (30 ± 7 vs. 42 ± 9, P < 0.01) but had lived in the US longer (20 ± 8 vs. 12 ± 9 years, P < 0.01). Age-adjusted ALS was similar in childhood and adulthood immigrants (2.78 ± 1.83 vs. 2.73 ± 1.69, P = 0.87). For adulthood immigrants, multiple regression analysis (adj R2 = 0.20) revealed older age at immigration and more years in the US were associated with higher ALS (both P < 0.05); whereas, current age, education, income, and gender had no significant influence (all P ≥ 0.4). The prevalence of smoking, alcohol intake, and physical activity did not differ in adulthood immigrants living in the US for ≥10 years vs. <10 years (all P ≥ 0.2). Reason for immigration was available for 77 participants. The reasons included: family reunification, lottery, marriage, work, education, and asylum. Compared to all other reasons combined, immigration for family reunification was associated with the lowest ALS (1.94 ± 1.51 vs. 3.03 ± 1.86, P = 0.03). CONCLUSION: African immigrants do not appear to respond to the stress of immigration by developing unhealthy assimilation behaviors. However, older age at immigration and increased duration of stay in the US are associated with higher ALS; whereas, family reunification is associated with lower ALS. CLINICAL TRIALSGOV IDENTIFIER: NCT00001853.