Janet Ogundepo A new study published in the Journal of Tropical Medicine and Infectious Disease has revealed that artificial intelligence could be used to identify and map areas with a high prevalence of tuberculosis. The research, conducted in Lagos, Ogun, Oyo and Osun States, used the EPCON AI-powered Epi-control platform’s hot spot mapping model and demonstrated a 75 per cent accuracy in predicting TB hotspots in Nigeria, than traditional approaches. EPCON is a healthcare impact organisation specialising in the use of AI to estimate disease burden, predict its evolution and the effect of interventions.
In a statement sent to PUNCH Healthwise and signed by Candice Burgess-Look, the intervention of AI in finding people with TB would hasten the progress of fighting the treatable TB disease. According to the World Health Organisation, TB is an infectious disease caused by a bacterium that affects the lungs of infected persons. It spreads through the air when infected persons sneeze, cough or spit.
The WHO further states that TB is the second leading infectious killer after COVID-19. According to the National Tuberculosis, Leprosy and Buruli Ulcer Control Programme, Nigeria ranks sixth among 30 high-burden TB countries globally. It further noted that the TB burden in Nigeria was 21,000 annually with only 2,384 cases diagnosed.
Continuing, the statement emphasised that about 590,000 new TB cases were reported, of this figure, 140,000 are persons positive for the Human immunode.