Strategies for halting the rise of multidrug resistant TB epidemics: assessing the effect of early case detection and isolation.
The increasing rates of multidrug resistant TB (MDR-TB) have posed the question of whether control programs under enhanced directly observed treatment, short-course (DOTS-Plus) are sufficient or implemented optimally. Despite enhanced efforts on early case detection and improved treatment regimens, direct transmission of MDR-TB remains a major hurdle for global TB control.



We developed an agent-based simulation model of TB dynamics to evaluate the effect of transmission reduction measures on the incidence of MDR-TB. We implemented a 15-day isolation period following the start of treatment in active TB cases. The model was parameterized with the latest estimates derived from the published literature.



We found that if high rates (over 90%) of TB case identification are achieved within 4 weeks of developing active TB, then a 15-day patient isolation strategy with 50% effectiveness in interrupting disease transmission leads to 10% reduction in the incidence of MDR-TB over 10 years. If transmission is fully prevented, the rise of MDR-TB can be halted within 10 years, but the temporal reduction of MDR-TB incidence remains below 20% in this period.



The impact of transmission reduction measures on the TB incidence depends critically on the rates and timelines of case identification. The high costs and adverse effects associated with MDR-TB treatment warrant increased efforts and investments on measures that can interrupt direct transmission through early case detection.
Departamento de Física, Instituto de Ciéncias Exatas-ICEx, Universidade Federal Fluminense, Volta Redonda, RJ, 27.213-145Brazil.
Aquino L
AL
Espindola
Department of Mathematical and Statistical Sciences and Department of Public Health Sciences, University of Alberta, Edmonton, Alberta, Canada.
Marie
M
Varughese
Agent-Based Modelling Laboratory, York University, 4700 Keele St., Toronto, Ontario, M3J 1P3, Canada.
Marek
M
Laskowski
Agent-Based Modelling Laboratory, York University, 4700 Keele St., Toronto, Ontario, M3J 1P3, Canada.
Affan
A
Shoukat
Centre for Disease Modelling, Department of Mathematics and Statistics, York University, Toronto, ON, M3J 1P3, Canada.
Jane M
JM
Heffernan
Agent-Based Modelling Laboratory, York University, 4700 Keele St., Toronto, Ontario, M3J 1P3, Canada.
Seyed M
SM
Moghadas
D000995:Antitubercular Agents / Q000627:therapeutic use*; D003140:Communicable Disease Control / Q000379:methods*; D003906:Developing Countries; D018562:Disease Transmission, Infectious / Q000517:prevention & control*; D042241:Early Diagnosis; D058872:Epidemics; D006801:Humans; D015994:Incidence; D008962:Models, Theoretical; D009169:Mycobacterium tuberculosis / Q000302:isolation & purification; D011157:Population Dynamics; D018088:Tuberculosis, Multidrug-Resistant / Q000175:diagnosis* / Q000517:prevention & control* / Q000635:transmission
D000995:Antitubercular Agents
Agent-based modelling; Case isolation; Exogenous re-infection; Multidrug resistant TB; Relapse; Transmission dynamics