Bui Viet Long, Ragonnet Romain, Hughes Angus E, Shipman David S, McBryde Emma S, Nguyen Binh Hoa, Do Hoang Nam, Ha Thai Son, Fox Greg J, Trauer James M
School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Centre for Clinical Research, The University of Queensland, Brisbane, Queensland, Australia.
J Infect Dis. 2025 Aug 7. doi: 10.1093/infdis/jiaf406.
Vietnam, a high-burden tuberculosis (TB) country, experienced marked declines in TB notifications during the COVID-19 pandemic. We assessed the impact of pandemic-related disruptions on TB case detection and transmission using a dynamic transmission model calibrated to local demographic and epidemiological observations.
We developed an age-structured compartmental TB transmission model to estimate COVID-19's impact on TB in Vietnam. Four model assumptions reflecting reductions in detection and/or transmission were calibrated to notification data, with the best-fitting assumption used for future projections and to evaluate the effects of enhanced case detection scenarios.
COVID-19 significantly disrupted TB services in Viet Nam, resulting in an estimated 2,000 additional TB episodes (95% credible interval [CrI]: 200-5,100) and 1,100 TB-related deaths (95%CrI: 100-2,700) in 2021.By 2035, the cumulative impact of these disruptions could reach 22,000 additional TB episodes (95%CrI: 2,200-63,000) and 5,900 deaths (95%CrI: 600-16,600) by 2035. We predicted two hypothetical scenarios of enhancing TB case detection. Under the ambitious scenario, enhancing TB case detection could mitigate these potential impacts by preventing 17.8% of new TB episodes (95%CrI: 13.1%-21.9%) and 34.2% (95%CrI: 31.5%-37.0%) of TB-related deaths by 2035, compared to no enhancement.
COVID-19-related disruptions have hindered TB detection in Vietnam, likely causing long-term increases in new TB episodes and deaths. However, the uncertainty around these effects is considerable. Sustained investment in diagnostics, system resilience, and patient-centric policies have the potential to achieve benefits that are substantially larger than these pandemic-related setbacks.
越南是结核病高负担国家，在新冠疫情期间结核病报告病例数显著下降。我们使用根据当地人口统计学和流行病学观察结果校准的动态传播模型，评估了疫情相关干扰对结核病病例发现和传播的影响。
我们开发了一个按年龄分层的结核病传播模型，以估计新冠疫情对越南结核病的影响。根据报告数据校准了反映发现和/或传播减少的四个模型假设，使用拟合最佳的假设进行未来预测，并评估加强病例发现方案的效果。
新冠疫情严重扰乱了越南的结核病服务，预计2021年将新增约2000例结核病病例（95%可信区间[CrI]：200 - 5100）和1100例与结核病相关的死亡（95%CrI：100 - 2700）。到2035年，这些干扰的累积影响可能导致新增22000例结核病病例（95%CrI：2200 - 63000）和5900例死亡（95%CrI：600 - 16600）。我们预测了两种加强结核病病例发现的假设情景。在雄心勃勃的情景下，与不加强相比，到2035年加强结核病病例发现可通过预防17.8%的新增结核病病例（95%CrI：13.1% - 21.9%）和34.2%（95%CrI：31.5% - 37.0%）的结核病相关死亡来减轻这些潜在影响。
与新冠疫情相关的干扰阻碍了越南的结核病发现，可能导致新的结核病病例和死亡人数长期增加。然而，这些影响的不确定性相当大。对诊断、系统弹性和以患者为中心的政策进行持续投资有可能带来远大于这些与疫情相关挫折的益处。
