Background Sepsis in the first 3 days of life is a leading cause of morbidity and mortality among infants. Group B Streptococcus (GBS), historically the primary cause of early-onset sepsis, has declined through widespread use of intrapartum chemoprophylaxis. We estimated the national burden of invasive early-onset sepsis (EOS) cases and deaths in the era of GBS prevention. Methods Population-based surveillance for invasive EOS was conducted in 4 of CDC’s Active Bacterial Core surveillance (ABCs) sites from 2005–2008. We calculated incidence using state and national live birth files. Estimates of the national number of cases and deaths were calculated, standardizing by race and gestational age. Results ABCs identified 658 cases of EOS; 72 (10.9%) were fatal. Overall incidence remained stable during the three years (2005:0.77 cases/1,000 live births; 2008:0.76 cases/1,000 live births). GBS (~38%) was the most commonly reported pathogen followed by Escherichia coli (~24%). Black preterm infants had the highest incidence (5.14 cases/1,000 live births) and case fatality (24.4%). Non-black term infants had the lowest incidence (0.40 cases/1,000 live births) and case fatality (1.6%). The estimated national annual burden of EOS was approximately 3,320 cases (95% CI: 3,060–3,580) including 390 deaths (95% CI: 300–490). Among preterm infants, 1,570 cases (95% CI: 1,400–1,770; 47.3% of the overall) and 360 deaths (95% CI: 280–460; 92.3% of the overall) occurred annually. Conclusions The burden of invasive early-onset sepsis remains substantial in the era of GBS prevention and disproportionately affects preterm and black infants. Identification of strategies to prevent preterm births is needed to reduce the neonatal sepsis burden.

Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Here, we use a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy. We estimate 6,454,951 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) in the United States as of April 18, 2020. Accounting for uncertainty, the number of infections during this period was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64–99%) of this difference is due to incomplete testing, while 14% (0.3–36%) is due to imperfect test accuracy. The approach can readily be applied in future studies in other locations or at finer spatial scale to correct for biased testing and imperfect diagnostic accuracy to provide a more realistic assessment of COVID-19 burden.

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