title: Within-host population dynamics of antibiotic-resistant M. tuberculosis.
abstract: Mathematical models for the population dynamics of de novo resistant Mycobacterium tuberculosis within individuals are studied. The models address the use of one or two antimicrobial drugs for treating latent tuberculosis (TB). They consider the effect of varying individual immune response strength on the dynamics for the appearance of resistant bacteria. From the analysis of the models, equilibria and local stabilities are determined. For assessing temporal dynamics and global stability for sensitive and drug-resistant bacteria, numerical simulations are used. Results indicate that for a low bacteria load that is characteristic of latent TB and for small reduction in an immune response, the use of a single drug is capable of curing the infection before the appearance of drug resistance. However, for severe immune deficiency, the use of two drugs will provide a larger time period before the emergence of resistance. Therefore, in this case, two-drugs treatment will be more efficient in controlling the infection.
authors.affiliation: División Académica de Ciencias Básicas, Universidad Juárez Autónoma de Tabasco, Cunduacán 86690, Tabasco, México.
authors.forename: Justino
authors.initials: J
authors.lastname: Alavez-Ramírez
authors.forename: J Rogelio Avendano
authors.initials: JR
authors.lastname: Castellanos
authors.forename: Lourdes
authors.initials: L
authors.lastname: Esteva
authors.forename: José Antonio
authors.initials: JA
authors.lastname: Flores
authors.forename: José Luis
authors.initials: JL
authors.lastname: Fuentes-Allen
authors.forename: Gisela
authors.initials: G
authors.lastname: García-Ramos
authors.forename: Guillermo
authors.initials: G
authors.lastname: Gómez
authors.forename: Jesús
authors.initials: J
authors.lastname: López-Estrada
mesh_terms: D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000494:pharmacology* / Q000627:therapeutic use; D003198:Computer Simulation; D004352:Drug Resistance, Microbial; D004359:Drug Therapy, Combination; D006099:Granuloma / Q000188:drug therapy / Q000382:microbiology; D006801:Humans; D007538:Isoniazid / Q000494:pharmacology / Q000627:therapeutic use; D008954:Models, Biological; D009169:Mycobacterium tuberculosis / Q000187:drug effects* / Q000254:growth & development; D012293:Rifampin / Q000494:pharmacology / Q000627:therapeutic use; D014397:Tuberculosis, Pulmonary / Q000188:drug therapy / Q000382:microbiology*
chemical_list: D000900:Anti-Bacterial Agents; D007538:Isoniazid; D012293:Rifampin