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

Abstract

Background: Tuberculosis (TB) cases 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 with 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 the 2020-2035 study period, we estimate an additional 2,784 (95% uncertainty interval: 2,164-3,461) TB cases and 1,138 (1,076-1,201) TB deaths in the United States associated with changes occurring during the COVID-19 pandemic. The four mechanisms had offsetting effects - decreases in TB diagnosis rates and increases in TB mortality rates led to more TB deaths, while reductions in contact rates reduced TB deaths. Immigration changes initially reduced TB deaths, but increased deaths over time.

Discussion: While the direct impacts of the COVID-19 pandemic occurred between 2020-2023, these changes may continue to influence TB incidence and mortality in future years.