The Lancet Digital Health
Gabriel Davis Jones, Symon M Kariuki, Anthony K Ngugi, Angelina Kakooza Mwesige, Honorati Masanja, Seth Owusu-Agyei, Ryan Wagner, J Helen Cross, Josemir W Sander, Charles R Newton, Arjune Sen, Hanna Abban, Patrick Adjei, Ken Ae-Ngibise, Francis Agbokey, Lisa Aissaoui, Albert Akpalu, Bright Akpalu, Sabina Asiamah, Gershim Asiki, Mercy Atieno, Evasius Bauni, Dan Bhwana, Mary Bitta, Christian Bottomley, Martin Chabi, Eddie Chengo, Neerja Chowdhary, Myles Connor, Helen Cross, Mark Collinson, Emmanuel Darkwa, Timothy Denison, Victor Doku, Tarun Dua, Isaac Egesa, Tony Godi, F. Xavier Gómez-Olivé, Simone Grassi, Samuel Iddi, Daniel Nana Yaw Abankwah Junior, Kathleen Kahn, Angelina Kakooza, Symon Kariuki, Gathoni Kamuyu, Clarah Khalayi, Henrika Kimambo, Immo Kleinschmidt, Thomas Kwasa, Sloan Mahone, Gergana Manolova, Honorati Masanja, Alexander Mathew, William Matuja, David McDaid, Bruno Mmbando, Daniel Mtai Mwanga, Dorcas Muli, Victor Mung'ala Odera, Frederick Murunga Wekesah, Vivian Mushi, Anthony Ngugi, Peter Odermatt, Rachael Odhiambo, James O Mageto, Peter Otieno, Seth Owusu-Agyei, George Pariyo, Stefan Peterson, Josemir Sander, Arjune Sen, Cynthia Sottie, Isolide Sylvester, Stephen Tollman, Yvonne Thoya, Rhian Twine, Sonia Vallentin, Ryan Wagner, Richard Walker, Stella WaruingiView Journal Article / Working Paper
Identification of convulsive epilepsy in sub-Saharan Africa relies on access to resources that are often unavailable. Infrastructure and resource requirements can further complicate case verification. Using machine-learning techniques, we have developed and tested a region-specific questionnaire panel and predictive model to identify people who have had a convulsive seizure. These findings have been implemented into a free app for health-care workers in Kenya, Uganda, Ghana, Tanzania, and South Africa.