Influenza Vaccination Modifies Disease Severity Among Community-dwelling Adults Hospitalized With Influenza

BackgroundWe investigated the effect of influenza vaccination on disease severity in adults hospitalized with laboratory-confirmed influenza during 2013-14, a season in which vaccine viruses were antigenically similar to those circulating.MethodsWe analyzed data from the 2013-14 influenza season and used propensity score matching to account for the probability of vaccination within age strata (18-49, 50-64, and ≥65 years). Death, intensive care unit (ICU) admission, and hospital and ICU lengths of stay (LOS) were outcome measures for severity. Multivariable logistic regression and competing risk models were used to compare disease severity between vaccinated and unvaccinated patients, adjusting for timing of antiviral treatment and time from illness onset to hospitalization.ResultsInfluenza vaccination was associated with a reduction in the odds of in-hospital death among patients aged 18-49 years (adjusted odds ratios [aOR] = 0.21; 95% confidence interval [CI], 0.05 to 0.97), 50-64 years (aOR = 0.48; 95% CI, 0.24 to 0.97), and ≥65 years (aOR = 0.39; 95% CI, 0.17 to 0.66). Vaccination also reduced ICU admission among patients aged 18-49 years (aOR = 0.63; 95% CI, 0.42 to 0.93) and ≥65 years (aOR = 0.63; 95% CI, 0.48 to 0.81), and shortened ICU LOS among those 50-64 years (adjusted relative hazards [aRH] = 1.36; 95% CI, 1.06 to 1.74) and ≥65 years (aRH = 1.34; 95% CI, 1.06 to 1.73), and hospital LOS among 50-64 years (aRH = 1.13; 95% CI, 1.02 to 1.26) and ≥65 years (aRH = 1.24; 95% CI, 1.13 to 1.37).ConclusionsInfluenza vaccination during 2013-14 influenza season attenuated adverse outcome among adults that were hospitalized with laboratory-confirmed influenza

Enhancing disease surveillance with novel data streams: challenges and opportunities

Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions: What are the opportunities for using NDS and what are the minimal tests of validity and utility that must be applied when using NDS? Identifying these opportunities will necessitate the involvement of public health authorities and an appreciation of the diversity of objectives and scales across agencies at different levels (local, state, national, international). We present the case that clearly articulating surveillance objectives and systematically evaluating NDS and comparing the performance of NDS to existing surveillance data and alternative NDS data is critical and has not sufficiently been addressed in many applications of NDS currently in the literature

Enhancing disease surveillance with novel data streams: challenges and opportunities.

Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions: What are the opportunities for using NDS and what are the minimal tests of validity and utility that must be applied when using NDS? Identifying these opportunities will necessitate the involvement of public health authorities and an appreciation of the diversity of objectives and scales across agencies at different levels (local, state, national, international). We present the case that clearly articulating surveillance objectives and systematically evaluating NDS and comparing the performance of NDS to existing surveillance data and alternative NDS data is critical and has not sufficiently been addressed in many applications of NDS currently in the literature

Enhancing disease surveillance with novel data streams:challenges and opportunities

Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions: What are the opportunities for using NDS and what are the minimal tests of validity and utility that must be applied when using NDS? Identifying these opportunities will necessitate the involvement of public health authorities and an appreciation of the diversity of objectives and scales across agencies at different levels (local, state, national, international). We present the case that clearly articulating surveillance objectives and systematically evaluating NDS and comparing the performance of NDS to existing surveillance data and alternative NDS data is critical and has not sufficiently been addressed in many applications of NDS currently in the literature

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