Publications by authors named "B M Flannery"
Background: The 2023-2024 influenza season had predominant influenza A(H1N1)pdm09 virus activity, but A(H3N2) and B viruses co-circulated. Seasonal influenza vaccine strains were well-matched to these viruses.
Methods: Using health care encounters data from health systems in 8 states, we evaluated influenza vaccine effectiveness (VE) against influenza-associated medical encounters from October 2023-April 2024.
Article Synopsis
- Machine learning, particularly deep learning with convolutional neural networks (CNNs), is being used to detect prostate cancer in tissue slides, but sample type differences affect model accuracy.
- Research tested whether CNNs trained on one type of sample (biopsy or radical prostatectomy) could effectively analyze the other type, revealing a significant drop in performance across sample types.
- Results indicated that models performed well on their own sample but poorly on the alternative type, highlighting the need to consider morphological differences in training to improve cancer detection accuracy in clinical settings.*
Background: The 2023-24 U.S. influenza season was characterized by a predominance of A(H1N1)pdm09 virus circulation with co-circulation of A(H3N2) and B/Victoria viruses.
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- Test-negative design (TND) studies are essential for monitoring the effectiveness of influenza vaccines, but the emergence of vaccines for SARS-CoV-2 and RSV complicates the analysis due to the need for appropriate control selection.
- A simulation study and secondary analysis of TND estimates from Southeast Michigan showed that RSV prevalence among control groups could potentially bias influenza vaccine effectiveness results, especially when RSV is vaccine-preventable.
- However, the actual analysis indicated that including RSV cases in the control group did not significantly affect the effectiveness estimates for influenza vaccines, suggesting that current biases are minimal when RSV is not vaccine-preventable.
Background: Previous estimates of vaccine effectiveness (VE) against asymptomatic influenza virus infection based on seroconversion have varied widely and may be biased. We estimated 2022-2023 influenza VE against illness and asymptomatic infection in a prospective cohort.
Methods: In the HEROES-RECOVER cohort, adults at increased occupational risk of influenza exposure across 7 US sites provided weekly symptom reports and nasal swabs for reverse transcription-polymerase chain reaction (RT-PCR) influenza testing.