Kiros Berhane, Eastern Africa GEOHealth Hub co-principal investigator, joined a National Institutes of Health sponsored seminar in September to give his take on data science efforts around environmental health hazards in Africa.
Using advanced data science tools to support environmental health research in Africa was the focus of a Sept. 23 seminar, part of a series on the state of data science. The series is sponsored by Harnessing Data Science for Health Discovery and Innovation in Africa (DS-I Africa), a program of the National Institutes of Health (NIH) Common Fund (see sidebar).
Three panelists shared their experiences.
– NIEHS grantee Kiros Berhane, Ph.D., from Columbia University.
– Engineer Bainomugisha, Ph.D., from Makerere University, Uganda.
– Caradee Wright, Ph.D., from the South African Medical Research Council and the University of Pretoria.
Overcoming human limitations
Exposome data are collected in Africa but gaps remain in the content and access to it. Computational methods and tools are needed to make complex data useful to health professionals and policymakers.
Berhane discussed machine learning, particularly predictive models. Because more data are not necessarily better data, researchers can use human-supervised machine learning to weed out messy or incomplete information. For example, hospital data, available in electronic form in much of the developed world, is manually collected in African hospitals.
“Africa is already facing multiple challenges, such as a wide range of exposures combined with rapid urbanization and industrialization,” said Berhane. “In the face of all this, there’s a lack of high-quality data and limited human capacity in these areas.”
