The Value Proposition of Coordinated Population Cohorts Across Africa.

IF 7 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Michèle Ramsay, Amelia C Crampin, Ayaga A Bawah, Evelyn Gitau, Kobus Herbst
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引用次数: 0

Abstract

Building longitudinal population cohorts in Africa for coordinated research and surveillance can influence the setting of national health priorities, lead to the introduction of appropriate interventions, and provide evidence for targeted treatment, leading to better health across the continent. However, compared to cohorts from the global north, longitudinal continental African population cohorts remain scarce, are relatively small in size, and lack data complexity. As infections and noncommunicable diseases disproportionately affect Africa's approximately 1.4 billion inhabitants, African cohorts present a unique opportunity for research and surveillance. High genetic diversity in African populations and multiomic research studies, together with detailed phenotyping and clinical profiling, will be a treasure trove for discovery. The outcomes, including novel drug targets, biological pathways for disease, and gene-environment interactions, will boost precision medicine approaches, not only in Africa but across the globe.

全非洲协调人口群组的价值主张。
在非洲建立用于协调研究和监测的纵向人口队列,可以影响国家卫生优先事项的制定,促使采取适当的干预措施,并为有针对性的治疗提供证据,从而改善整个非洲大陆的健康状况。然而,与全球北方的队列相比,非洲大陆的纵向人口队列仍然很少,规模相对较小,而且缺乏数据的复杂性。由于感染和非传染性疾病对非洲约 14 亿居民的影响尤为严重,非洲队列为研究和监测提供了一个独特的机会。非洲人口的遗传多样性很高,多基因组研究以及详细的表型和临床分析将成为发现疾病的宝库。这些成果,包括新的药物靶点、疾病的生物学途径以及基因与环境的相互作用,将不仅在非洲,而且在全球范围内促进精准医疗方法的发展。
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来源期刊
CiteScore
11.10
自引率
1.70%
发文量
0
期刊介绍: The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.
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