Facial analysis technology for the detection of Down syndrome in the Democratic Republic of the Congo.

Down syndrome is one of the most common chromosomal anomalies affecting the world's population, with an estimated frequency of 1 in 700 live births. Despite its relatively high prevalence, diagnostic rates based on clinical features have remained under 70% for most of the developed world and even lower in countries with limited resources. While genetic and cytogenetic confirmation greatly increases the diagnostic rate, such resources are often non-existent in many low- and middle-income countries, particularly in Sub-Saharan Africa. To address the needs of countries with limited resources, the implementation of mobile, user-friendly and affordable technologies that aid in diagnosis would greatly increase the odds of success for a child born with a genetic condition. Given that the Democratic Republic of the Congo is estimated to have one of the highest rates of birth defects in the world, our team sought to determine if smartphone-based facial analysis technology could accurately detect Down syndrome in individuals of Congolese descent. Prior to technology training, we confirmed the presence of trisomy 21 using low-cost genomic applications that do not need advanced expertise to utilize and are available in many low-resourced countries. Our software technology trained on 132 Congolese subjects had a significantly improved performance (91.67% accuracy, 95.45% sensitivity, 87.88% specificity) when compared to previous technology trained on individuals who are not of Congolese origin (p < 5%). In addition, we provide the list of most discriminative facial features of Down syndrome and their ranges in the Congolese population. Collectively, our technology provides low-cost and accurate diagnosis of Down syndrome in the local population.

Comparisons of social and demographic determinants of tobacco use in the Democratic Republic of the Congo.

BACKGROUND: Worldwide, tobacco use has caused over 100 million deaths in the twentieth century and is projected to cause death in up to one billion people in the twenty-first century. It is a leading cause of early death and disability in over 100 countries and accounts for over 11% of global deaths, disproportionately affecting low- and middle-income countries. The purpose of the study was to examine a variety of social determinants of tobacco use in the Democratic Republic of the Congo, including region, sex, ethnicity, education, literacy, wealth index and place of residence, to gain insights with regard to tobacco use among sub-national groups. METHODS: This project was a secondary data analysis of the 2013-2014 Demographics and Health Survey (DHS) for the Democratic Republic of the Congo. Logistic regressions predicting smoking, use of snuff and smoking cigars or natural tobacco as dichotomous variables were conducted. Independent variables included age, educational level, religion, rurality, literacy, wealth index, occupation and ethnicity. RESULTS: Tobacco use is highest among those with less education and low literacy. It was also highest among the working poor. Older age and living in larger cities were predictive of smoking, although the relationship between age and smoking was not linear. There was a strong linear effect for wealth. Being in a professional, technical or managerial position was highly protective against smoking while being engaged in services, skilled and unskilled manual labor, and the army had significantly greater odds of smoking. CONCLUSIONS: Data indicate that tobacco use in the DRC, as is common in the developing world, is heavily concentrated in the working poor with lower educational status. Higher educational status is consistently predictive of avoiding tobacco use. Additionally, examining only national-level data to ascertain tobacco use levels and patterns may lead to mistaken conclusions that can lead to inefficient and ineffective allocation of resources aimed at controlling tobacco use.