Collateral effects of COVID-19 pandemic control on the US infectious disease landscape

Using data from the United States Centers for Disease Control and Prevention (CDC) disease surveillance systems, we sought to quantify the indirect effects of the COVID-19 pandemic, and the possibility of lack of exposure to common pathogens resulting in immune deficits. Clustering analysis on pandemic-era time-series data identified pathogen groupings according to transmission mechanism. Counterfactual analysis, using Bayesian structural time-series (BSTS) modeling, confirmed that infectious diseases that are directly transmitted via airborne droplets (aerosols) experienced the greatest disruption to transmission. By contrast, sexually transmitted infections (STIs) experienced a smaller transient disruption, and increasing trends in incidence prepandemic appear to have been curtailed. Using epidemiological theory, we demonstrate that the observed magnitudes and durations of notifications deficits were determined by fundamental disease system properties, namely, the serial interval, basic reproductive number, and susceptible recruitment.