Effects of the COVID-19 pandemic on TB outcomes in the United States: a Bayesian analysis

Abstract

Background Tuberculosis (TB) notifications and deaths in the United States fluctuated substantially during the COVID-19 pandemic. We analyzed multiple data sources to understand the factors contributing to these changes and estimated future TB trends. Methods We identified four mechanisms potentially contributing to observed TB trends during 2020–2023: immigration, respiratory contact rates, rates of accurate diagnosis and treatment initiation, and mortality rates for persons experiencing TB disease. We employed a Bayesian approach to synthesize evidence on how these mechanisms changed during the pandemic and how they might have combined to produce observed 2020–2023 TB data, using a transmission-dynamic model to link mechanisms to TB outcomes. We also simulated a no-pandemic-counterfactual scenario that assumed mechanisms followed pre-pandemic trends. We estimated TB outcomes associated with the pandemic until 2035 to capture lagged effects. We evaluated additional scenarios to estimate the individual effect of each mechanism. Results Over 2020–2035, we estimate an additional 2,784 (95% uncertainty interval: 2,164–3,461) TB notifications and 1,138 (1,076–1,201) TB deaths in the United States associated with changes occurring during the COVID-19 pandemic. Mechanisms had offsetting effects – decreases in TB diagnosis rates led to more TB deaths and notifications, while reductions in contact rates reduced TB deaths and notifications. Immigration changes initially reduced TB deaths, but increased deaths and notifications over time. Higher TB mortality rates increased TB deaths, but decreased TB notifications. Conclusions While direct impacts of the COVID-19 pandemic occurred between 2020–2023, these changes may continue to influence TB incidence and mortality in future years.