Estimating the impact of the first 2 years of the COVID-19 pandemic on tuberculosis diagnosis and treatment outcomes in Southeastern City in Iran: an interrupted time series analysis of the preceding 10 years of ecological data.

Background: With shared modes of transmission and clinical symptoms the convergence of COVID-19 and tuberculosis (TB) might lead to reduced diagnosis and detection of TB, which is challenging for healthcare systems already strained by the pandemic's reach.

Methods: This ecological study investigated the impact of the COVID-19 pandemic on TB surveillance over the first 2 years of the pandemic (March 2020 to February 2022) in southeastern Iran. Interrupted Time Series (ITS) analysis with the quasi-Poisson regression models was used to estimate the relative risk (RR) of TB diagnosis and treatment outcome counts, stratified by gender, case definition, involvement type, and treatment outcomes.

Results: The ITS analyses showed a significant decrease in TB total cases (RR: 0.622 [95% CI: 0.487, 0.793], P < 0.001), new cases (RR: 0.632 [95% CI: 0.493, 0.810], P < 0.001) and recurrent cases (RR: 0.491 [95% CI: 0.247, 0.974], P < 0.001). In addition, recovery and treatment failure counts also showed significant decreases (RR: 0.751 [95% CI: 0.566, 0.996], P = 0.05; RR: 0.201 [95% CI: 0.054, 0.738], P = 0.02). Moreover, significant decreases are observed in both genders and involvement types (pulmonary and extrapulmonary TB). No significant change was observed for absent to treatment and death counts.

Conclusion: The COVID-19 pandemic has negatively impacted TB diagnosis and treatments. Concerns are risen about the progress achieved in TB control.