Evaluation of TB elimination strategies in Canadian Inuit populations: Nunavut as a case study

• Published in: Infectious Disease Modelling
• Main Authors: Elaheh Abdollahi, Yoav Keynan, Patrick Foucault, Jason Brophy, Holden Sheffield, Seyed M. Moghadas
• Format: Article in Journal/Newspaper
• Language: English
• Published: KeAi Communications Co., Ltd. 2022
• Subjects: Tuberculosis; Inuit populations; Treatment; Agent-based simulation 2000 MSC; 92B05; Infectious and parasitic diseases; RC109-216; inuit; Nunavut
• Online Access: https://doi.org/10.1016/j.idm.2022.07.005; https://doaj.org/article/01c58387aaf1438a89ec04e979146333

Tuberculosis (TB) continues to disproportionately affect Inuit populations in Canada with some communities having over 300 times higher rate of active TB than Canadian-born, non-Indigenous people. Inuit Tuberculosis Elimination Framework has set the goal of reducing active TB incidence by at least 50% by 2025, aiming to eliminate it by 2030. Whether these goals are achievable with available resources and treatment regimens currently in practice has not been evaluated. We developed an agent-based model of TB transmission to evaluate timelines and milestones attainable in Nunavut, Canada by including case findings, contact-tracing and testing, treatment of latent TB infection (LTBI), and the government investment on housing infrastructure to reduce the average household size. The model was calibrated to ten years of TB incidence data, and simulated for 20 years to project program outcomes. We found that, under a range of plausible scenarios with tracing and testing of 25%–100% of frequent contacts of detected active cases, the goal of 50% reduction in annual incidence by 2025 is not achievable. If active TB cases are identified rapidly within one week of becoming symptomatic, then the annual incidence would reduce below 100 per 100,000 population, with 50% reduction being met between 2025 and 2030. Eliminating TB from Inuit populations would require high rates of contact-tracing and would extend beyond 2030. The findings indicate that time-to-identification of active TB is a critical factor determining program effectiveness, suggesting that investment in resources for rapid case detection is fundamental to controlling TB.