Impact of Case Detection and Covid-19-Related Disruptions on Tuberculosis In Vietnam: A Modelling Analysis.

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.