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Background Influenza hospitalizations result in substantial morbidity and mortality each year. Little is known about the association between influenza hospitalization and census tract-based socioeconomic determinants beyond the effect of individual factors. Objective To evaluate whether census tract-based determinants such as poverty and household crowding would contribute significantly to the risk of influenza hospitalization above and beyond individual-level determinants. Methods We analyzed 33 515 laboratory-confirmed influenza-associated hospitalizations that occurred during the 2009-2010 through 2013-2014 influenza seasons using a population-based surveillance system at 14 sites across the United States. Results Using a multilevel regression model, we found that individual factors were associated with influenza hospitalization with the highest adjusted odds ratio ( AOR) of 9.20 (95% CI 8.72-9.70) for those ≥65 vs 5-17 years old. African Americans had an AOR of 1.67 (95% CI 1.60-1.73) compared to Whites, and Hispanics had an AOR of 1.21 (95% CI 1.16-1.26) compared to non-Hispanics. Among census tract-based determinants, those living in a tract with ≥20% vs <5% of persons living below poverty had an AOR of 1.31 (95% CI 1.16-1.47), those living in a tract with ≥5% vs <5% of persons living in crowded conditions had an AOR of 1.17 (95% CI 1.11-1.23), and those living in a tract with ≥40% vs <5% female heads of household had an AOR of 1.32 (95% CI 1.25-1.40). Conclusion Census tract-based determinants account for 11% of the variability in influenza hospitalization. [ABSTRACT FROM AUTHOR]

Introduction Previous FluSurv- NET studies found that adult females had a higher incidence of influenza-associated hospitalizations than males. To identify groups of women at higher risk than men, we analyzed data from 14 FluSurv- NET sites that conducted population-based surveillance for laboratory-confirmed influenza-associated hospitalizations among residents of 78 US counties. Methods We analyzed 6292 laboratory-confirmed, geocodable (96%) adult cases collected by FluSurv- NET during the 2010-12 influenza seasons. We used 2010 US Census and 2008-2012 American Community Survey data to calculate overall age-adjusted and age group-specific female:male incidence rate ratios ( IRR) by race/ethnicity and census tract-level poverty. We used national 2010 pregnancy rates to estimate denominators for pregnant women aged 18-49. We calculated male:female IRRs excluding them and IRRs for pregnant:non-pregnant women. Results Overall, 55% of laboratory-confirmed influenza cases were female. Female:male IRRs were highest for females aged 18-49 of high neighborhood poverty ( IRR 1.50, 95% CI 1.30-1.74) and of Hispanic ethnicity ( IRR 1.70, 95% CI 1.34-2.17). These differences disappeared after excluding pregnant women. Overall, 26% of 1083 hospitalized females aged 18-49 were pregnant. Pregnant adult females were more likely to have influenza-associated hospitalizations than their non-pregnant counterparts (relative risk [ RR] 5.86, 95% CI 5.12-6.71), but vaccination levels were similar (25.5% vs 27.8%). Conclusions Overall rates of influenza-associated hospitalization were not significantly different for men and women after excluding pregnant women. Among women aged 18-49, pregnancy increased the risk of influenza-associated hospitalization sixfold but did not increase the likelihood of vaccination. Improving vaccination rates in pregnant women should be an influenza vaccination priority. [ABSTRACT FROM AUTHOR]

Background The 2018–19 influenza season was characterized by prolonged co-circulation of Influenza A H3N2 (H3) and H1N1pdm09 (H1) viruses. We used data from the Influenza Hospitalization Surveillance Network (FluSurv-NET) to describe age-related differences in the distribution of influenza A subtypes. Methods We included all cases residing within a FluSurv-NET catchment area and hospitalized with laboratory-confirmed influenza during October 1, 2018–April 30, 2019. We multiply imputed influenza A subtype for 63% of cases with unknown subtype and based imputation on factors that could be associated with missing subtype including surveillance site, 10-year age groups and month of hospital admission. We calculated influenza hospitalization rates and 95% confidence intervals (95% CI) by type and subtype per 100,000 population. We compared the proportion of cases with H1 by year of age in FluSurv-NET to the distribution obtained from US public health laboratories participating in virologic surveillance and providing specimen-level influenza Results. Results Based on available data, 18,669 hospitalizations were reported; 41% received influenza vaccination ≥2 weeks prior to hospitalization and 90% received antivirals. Cumulative hospitalization rates per 100,000 population were as follows: H1 32.5 (95% CI 31.7–33.3), H3 29.3 (95% CI 28.5–30.1) and B 2.5 (95% CI 2.3–2.7). Based on weekly rates, H1 hospitalizations peaked during February (week 8) and H3 hospitalizations during March (week 11) (Figure A). FluSurv-NET data showed distinct patterns of subtype distribution by age, with H1 predominating among cases 0–9 and 24–70 years, and H3 predominating among cases 10–23 and ≥71 years. Data on the proportion of H1 results by age correlated well between FluSurv-NET and US virologic surveillance (Figure B). Conclusion Influenza A H1 and H3 virus circulation patterns varied by age group during the 2018–2019 season. The proportion of cases with H1 relative to H3 was low among those born between 1996 and 2009 and those born before 1948. These findings may indicate protection against H1 viruses in age groups with exposure to H1N1pdm09 during the 2009 pandemic or to older antigenically similar H1N1 viruses as young children. Disclosures Evan J. Anderson, MD, AbbVie (Consultant), GSK (Grant/Research Support), Merck (Grant/Research Support), Micron (Grant/Research Support), PaxVax (Grant/Research Support), Pfizer (Consultant, Grant/Research Support), sanofi pasteur (Grant/Research Support), Keipp Talbot, MD, MPH, Sequirus (Other Financial or Material Support, On Data Safety Monitoring Board). [ABSTRACT FROM AUTHOR]