Epidemiological Analysis of Tuberculosis Relapses in Morocco: Leveraging Artificial Intelligence for Predictive Modeling

Abstract

Tuberculosis remains a major public health problem. In most cases, appropriate and correctly administered anti-tuberculosis treatment leads to recovery. However, the presence of certain factors increases the risk of relapses. This study aims to analyze the epidemiological profile of tuberculosis relapses and discuss the results of treatments at the tuberculosis diagnostic center in Khémisset, Morocco. A total of 274 cases of tuberculosis relapse were reported during the study period. The average age of patients was 44.7 years ±18.1. Of these patients, 65.3% were male, giving a male-to-female ratio of 1.9. Of the relapses, 21.9% were extrapulmonary and 78.1% were pulmonary, of these, 71.5% were confirmed bacteriologically. The treatment success rate was 74.3%, the death rate, 7.8%, 9% of patients were lost to follow-up, the failure rate, 4.1% and 3.4% of patients became drug-resistant. Integrating artificial intelligence into the diagnosis and monitoring of tuberculosis treatment could significantly enhance public health initiatives in the fight against the disease.