Mobile data as public health decision enabler: a case study of cardiac and neurological emergencies
Published in Data for Development (D4D) Challenge at Net Mob 2015, Boston, USA, 7-10 April 2015, 2015
The establishment of hospitals in an area depends on numerous parameters considered by health authorities. This study aims to investigate whether mobile phone usage data could contribute to this decision-making process, focusing on two diseases requiring rapid hospitalization: myocardial infarction and stroke. The objective is to identify areas where the absence of a nearby hospital could result in death or serious sequelae. The proposed approach utilizes Voronoi diagrams to estimate antenna coverage and mobile population density to estimate real population density in each antenna area. The study considered 40 hospitals across Senegal’s 14 regions, estimating maximum distances reachable within 90 minutes or three hours, corresponding to the time limits for the two diseases. Expected case numbers were calculated using incidence rates and population figures in each antenna area. Results show that out of an estimated 13,508 annual stroke cases, only 462 (3.42%) occur too far from a hospital for timely trombolysis treatment, as 96% of the population can reach a hospital within 3 hours. However, for myocardial infarctions, out of 24,315 expected cases, 4,241 (17.4%) occur too far from a hospital to receive balloon treatment within the critical 90-minute window.
Recommended citation: Mutafungwa, Edward; Thiessard, Frantz; Diallo, Pathé; Gore, Ross; Jouhet, Vianney; Karray, Chiheb; Kheder, Nouha; Rym, Saddem; Hämäläinen, Jyri; Diallo, Gayo. (2015). "Mobile data as public health decision enabler: a case study of cardiac and neurological emergencies". Data for Development (D4D) Challenge at Net Mob 2015, Boston, USA, 7-10 April 2015.
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