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Tuberculosis (TB) is responsible for a high mortality rate (2.5%) worldwide, mainly in developing countries with a high prevalence of human immunodeficiency virus (HIV). The emergence of multiresistant strains of TB poses an extreme risk for TB outbreaks and highlights the need for global TB control strategies. Among Western African countries, Côte d'Ivoire (CI) represents a specific example of a country with great potential to prevent TB. Specifically, CI has a promising healthcare system for monitoring diseases, including vaccination programs. However, military and political conflict in CI favors the spread of infectious diseases, TB being among the most devastating. Compilation of the studies identifying common causes of TB would be extremely beneficial for the development of treatment and prevention strategies. Therefore, the purpose of this comprehensive review is to evaluate the epidemiology of TB in CI, describe the factors involved in pathogenesis, and suggest simple and applicable prevention strategies. [ABSTRACT FROM AUTHOR]

Background: Genotyping methods are useful tools to provide information on tuberculosis epidemic. They can allow a better response from health authorities and the implementation of measures for tuberculosis control. This study aimed to identify the main lineages and clades of Mycobacterium tuberculosis complex strains circulating in Côte d'Ivoire. Methods/Main Findings: Strains isolated from sputum samples of patients ongoing retreatment from all the country were characterized by spoligotyping and by MIRU-VNTR. Profiles obtained by spoligotyping were first compared to the SITVIT/ SpolDB4 database for family assignment. Of 194 strains analysed, 146 (75.3%) belonged to the T lineage. The most predominant spoligotype was the shared international type 53 with 135 strains (69.6%). In contrast with neighbouring countries, LAM (11 strains, 5.7%) and H (9 strains 4.6%) lineages were slightly represented. Only 3 Beijing strains (1.5%) and 4 strains of Mycobacterium africanum (2%) were found. Analysis of the results obtained with MIRU-VNTR revealed also a high level of clustering. [ABSTRACT FROM AUTHOR]