Vaccine effectiveness of recombinant and standard dose influenza vaccines against influenza related hospitalization using a retrospective test-negative design.

BACKGROUND: Relative effectiveness of various vaccine formulations provide important input for vaccine policy decisions and provider purchasing decisions. We used electronic databases to conduct a test-negative case control study to determine relative vaccine effectiveness (rVE) of recombinant influenza vaccine (RIV4) compared with standard dose vaccines (SD-IIV4) against influenza hospitalization. METHODS: Adults 18-64 and ≥65 years of age hospitalized in a large U.S. health system (19 hospitals) in 2018-2019 and 2019-2020 who were clinically tested for influenza using reverse transcription polymerase chain reaction (RT-PCR) assays were included. The hospital system electronic medical record (EMR) and the state immunization registry were used to confirm influenza vaccination. Propensity scores with inverse probability weighting were used to adjust for potential confounders and determine rVE. RESULTS: Of the 14,590 individuals included in the primary analysis, 3,338 were vaccinated with RIV4 and 976 were vaccinated with SD-IIV4, with the balance of 10,276 being unvaccinated. Most participants were white (80 %), most (70 %) had a high-risk condition, just over half were female (54 %) and age 65 years or older (53 %). Overall RIV4 rVE was significant when adjusted for propensity scores with inverse probability weights (rVE = 31; 95 % CI = 11 %, 46 %). Among younger adults (18-64 years-old), overall rVE of RIV4 was significant (rVE = 29; 95 % CI = 4 %, 47 %). CONCLUSIONS: Over all adults, both RIV4 and SD-IIV4 were effective against influenza hospitalization, with RIV4 providing better protection compared with SD-IIV4 overall, for females, younger adults, and those with no high-risk conditions.

Blood Inflammatory Biomarkers Differentiate Inpatient and Outpatient Coronavirus Disease 2019 From Influenza.

Background: The ongoing circulation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a diagnostic challenge because symptoms of coronavirus disease 2019 (COVID-19) are difficult to distinguish from other respiratory diseases. Our goal was to use statistical analyses and machine learning to identify biomarkers that distinguish patients with COVID-19 from patients with influenza. Methods: Cytokine levels were analyzed in plasma and serum samples from patients with influenza and COVID-19, which were collected as part of the Centers for Disease Control and Prevention's Hospitalized Adult Influenza Vaccine Effectiveness Network (inpatient network) and the US Flu Vaccine Effectiveness (outpatient network). Results: We determined that interleukin (IL)-10 family cytokines are significantly different between COVID-19 and influenza patients. The results suggest that the IL-10 family cytokines are a potential diagnostic biomarker to distinguish COVID-19 and influenza infection, especially for inpatients. We also demonstrate that cytokine combinations, consisting of up to 3 cytokines, can distinguish SARS-CoV-2 and influenza infection with high accuracy in both inpatient (area under the receiver operating characteristics curve [AUC] = 0.84) and outpatient (AUC = 0.81) groups, revealing another potential screening tool for SARS-CoV-2 infection. Conclusions: This study not only reveals prospective screening tools for COVID-19 infections that are independent of polymerase chain reaction testing or clinical condition, but it also emphasizes potential pathways involved in disease pathogenesis that act as potential targets for future mechanistic studies.

Vaccine effectiveness of recombinant and standard dose influenza vaccines against outpatient illness during 2018-2019 and 2019-2020 calculated using a retrospective test-negative design.

Newer influenza vaccine formulations have entered the market, but real-world effectiveness studies are not widely conducted until there is sufficient uptake. We conducted a retrospective test-negative case-control study to determine relative vaccine effectiveness (rVE) of recombinant influenza vaccine or RIV4, compared with standard dose vaccines (SD) in a health system with significant RIV4 uptake. Using the electronic medical record (EMR) and the Pennsylvania state immunization registry to confirm influenza vaccination, VE against outpatient medically attended visits was calculated. Immunocompetent outpatients ages 18-64 years seen in hospital-based clinics or emergency departments who were tested for influenza using reverse transcription polymerase chain reaction (RT-PCR) assays during the 2018-2019 and 2019-2020 influenza seasons were included. Propensity scores with inverse probability weighting were used to adjust for potential confounders and determine rVE. Among this mostly white and female cohort of 5,515 individuals, 510 were vaccinated with RIV4 and 557 were vaccinated with SD, with the balance of 4,448 (81%) being unvaccinated. Adjusted influenza VE estimates were 37% overall (95% CI = 27, 46), 40% (95% CI = 25, 51) for RIV4 and 35% (95% CI = 20, 47) for standard dose vaccines. Overall, rVE of RIV4 compared to SD was not significantly higher (11%; 95% CI = -20, 33). Influenza vaccines were moderately protective against medically attended outpatient influenza during the 2018-2019 and 2019-2020 seasons. Although the point estimates are higher for RIV4, the large confidence intervals around VE estimates suggest this study was underpowered to detect significant rVE of individual vaccine formulations.

Effect of mild COVID-19 on health-related quality of life.

Background: Little is known about the effects of a mild SARS-CoV-2 infection on health-related quality of life. Methods: This prospective observational study of symptomatic adults (18-87 years) who sought outpatient care for an acute respiratory illness, was conducted from 3/30/2020 to 4/30/2021. Participants completed the Short Form Health Survey (SF-12) at enrollment and 6-8 weeks later, to report their physical and mental health function levels as measured by the physical health and mental health composite scores (PHC and MHC, respectively). PHC and MHC scores for COVID-19 cases and non-COVID cases were compared using t-tests. Multivariable regression modeling was used to determine predictors of physical and mental health function at follow-up. Results: Of 2301 enrollees, 426 COVID-19 cases and 547 non-COVID cases completed both surveys. PHC improved significantly from enrollment to follow-up for both COVID-19 cases (5.4 ± 0.41; P < 0.001) and non-COVID cases (3.3 ± 0.32; P < 0.001); whereas MHC improved significantly for COVID-19 cases (1.4 ± 0.51; P < 0.001) and decreased significantly for non-COVID cases (-0.8 ± 0.37; P < 0.05). Adjusting for enrollment PHC, the most important predictors of PHC at follow-up included male sex (ß = 1.17; SE = 0.5; P = 0.021), having COVID-19 (ß = 1.99; SE = 0.54; P < 0.001); and non-white race (ß = -2.01; SE = 0.70; P = 0.004). Adjusting for enrollment MHC, the most important predictors of MHC at follow-up included male sex (ß = 1.92; SE = 0.63; P = 0.002) and having COVID-19 (ß = 2.42; SE = 0.67; P < 0.001). Conclusion: Both COVID-19 cases and non-COVID cases reported improved physical health function at 6-8 weeks' convalescence; whereas mental health function improved among COVID-19 cases but declined among non-COVID cases. Both physical and mental health functioning were significantly better among males with COVID-19 than females.

Estimating the burden of adult hospitalized RSV infection including special populations.

BACKGROUND: Numerous studies in the U.S. have made estimates of the RSV burden among adults that vary widely due to differences in methodology, reliance on influenza surveillance, which does not adequately capture all RSV clinical symptoms, and lack of diagnostic methods to identify RSV when viral loads are low. Nevertheless, accurate burden estimates can inform healthcare planning, resource allocation and potentially, RSV vaccine policy. METHODS: A simple method combined with statewide and local hospitalization, medical record and U.S. Census data were used to estimate population-based RSV hospitalization burden among adults ages 18-64 years, ≥65 years, and including immunocompetent, immunocompromised and pregnant individuals during 2015-2018 for Allegheny County, Pennsylvania. Economic burden of hospitalization was estimated using state-provided average hospitalization charges for comparisons across patient groups. RESULTS: The largest burden was borne by adults ≥ 65 years of age whose rates per 100,000 population of that age group (939/100,000) were 7.0-9.0 times those of adults 18-64 years of age (118/100,000). Immunosuppressed patients bore the greatest relative burden of RSV hospitalizations (1,288-1,562/100,000 immunosuppressed individuals). RSV burden ranged from 0 to 808/100,000 pregnant women. Average total charges for RSV hospitalization in Allegheny County across all adults increased from $39 million in 2015-2016 to $57 million in 2016-2017 to $89 million in 2017-2018, due to both increased average charges for an acute respiratory hospitalization and increased numbers of RSV cases. CONCLUSIONS: These RSV burden estimates add to the body of knowledge to guide public health policy makers and offer a method for simply and easily producing population-based burden estimates.

Using capture-recapture methods to estimate influenza hospitalization incidence rates.

BACKGROUND: Accurate population estimates of disease incidence and burden are needed to set appropriate public health policy. The capture-recapture (C-R) method combines data from multiple sources to provide better estimates than is possible using single sources. METHODS: Data were derived from clinical virology test results and from an influenza vaccine effectiveness study from seasons 2016-2017 to 2018-2019. The Petersen C-R method was used to estimate the population size of influenza cases; these estimates were then used to calculate adult influenza hospitalization burden using a Centers for Disease Control and Prevention (CDC) multiplier method. RESULTS: Over all seasons, 343 influenza cases were reported in the clinical database, and 313 in the research database. Fifty-nine cases (17%) reported in the clinical database were not captured in the research database, and 29 (9%) cases in the research database were not captured in the clinical database. Influenza hospitalizations were higher among vaccinated (58%) than the unvaccinated (35%) in the current season and were similar among unvaccinated (51%) and vaccinated (49%) in the previous year. Completeness of the influenza hospitalization capture was estimated to be 76%. The incidence rates for influenza hospitalizations varied by age and season and averaged 307-309 cases/100,000 adult population annually. CONCLUSION: Using C-R methods with more than one database, along with a multiplier method with adjustments improves the population estimates of influenza disease burden compared with relying on a single-data source.

Using Capture-Recapture Methods to Estimate Influenza Hospitalization Incidence Rates.

BACKGROUND: Accurate population estimates of disease incidence and burden are needed to set appropriate public health policy. The capture-recapture (C-R) method combines data from multiple sources to provide better estimates than is possible using single sources. METHODS: Data were derived from clinical virology test results and from an influenza vaccine effectiveness study from seasons 2016-2017 to 2018-2019. The Petersen C-R method was used to estimate the population size of influenza cases; these estimates were then used to calculate adult influenza hospitalization burden using a Centers for Disease Control and Prevention (CDC) multiplier method. RESULTS: Over all seasons, 343 influenza cases were reported in the clinical database and 313 in the research database. Fifty-nine cases (17%) reported in the clinical database were not captured in the research database, and 29 (9%) cases in the research database were not captured in the clinical database. Influenza hospitalizations were higher among vaccinated (58%) than the unvaccinated (35%) in the current season and were similar among unvaccinated (51%) and vaccinated (49%) in the previous year. Completeness of the influenza hospitalization capture was estimated to be 76%. The incidence rates for influenza hospitalizations varied by age and season and averaged 307-309 cases/100,000 adult population annually. CONCLUSION: Using Capture-Recapture methods with more than one database, along with a multiplier method with adjustments improves the population estimates of influenza disease burden compared with relying on a single data source.