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

Abstract

Abstract 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.

Keywords

• Pulmonary TB
• Extrapulmonary TB
• Interrupted time series
• COVID-19
• Quasi-poisson regression
• Relative risk