Systematic Assessment of Multiple Routine and Near Real-Time Indicators to Classify the Severity of Influenza Seasons and Pandemics in the United States, 2003-2004 Through 2015-2016.

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Abstract

Assessments of influenza season severity can guide public health action. We used the moving epidemic method to develop intensity thresholds (ITs) for 3 US surveillance indicators from the 2003-2004 through 2014-2015 influenza seasons (excluding the 2009 pandemic). The indicators were: 1) outpatient visits for influenza-like illness; 2) influenza-related hospitalizations; and 3) influenza- and pneumonia-related deaths. ITs were developed for the population overall and separately for children, adults, and older adults, and they were set at the upper limit of the 50% (IT50), 90% (IT90), and 98% (IT98) 1-sided confidence intervals of the geometric mean of each season's 3 highest values. Severity was classified as low if ≥2 systems peaked below IT50, moderate if ≥2 peaked between IT50 and IT90, high if ≥2 peaked between IT90 and IT98, and very high if ≥2 peaked above IT98. We pilot-tested this method with the 2015-2016 season and the 2009 pandemic. Overall, 4 seasons were classified as low severity, 7 as moderate, 2 as high, and none as very high. Among the age groups, older adults had the most seasons (n = 3) classified as high, and children were the only group to have seasons (n = 2) classified as very high. We will apply this method to classify the severity of future seasons and inform pandemic response.

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Influenza surveillance in Europe: establishing epidemic thresholds by the Moving Epidemic Method

Tomás Vega, José Lozano, Tamara J Meerhoff … (2012)

Please cite this paper as: Vega et al. (2012) Influenza surveillance in Europe: establishing epidemic thresholds by the moving epidemic method. Influenza and Other Respiratory Viruses 7(4), 546–558. Background Timely influenza surveillance is important to monitor influenza epidemics. Objectives (i) To calculate the epidemic threshold for influenza‐like illness (ILI) and acute respiratory infections (ARI) in 19 countries, as well as the thresholds for different levels of intensity. (ii) To evaluate the performance of these thresholds. Methods The moving epidemic method (MEM) has been developed to determine the baseline influenza activity and an epidemic threshold. False alerts, detection lags and timeliness of the detection of epidemics were calculated. The performance was evaluated using a cross‐validation procedure. Results The overall sensitivity of the MEM threshold was 71·8% and the specificity was 95·5%. The median of the timeliness was 1 week (range: 0–4·5). Conclusions The method produced a robust and specific signal to detect influenza epidemics. The good balance between the sensitivity and specificity of the epidemic threshold to detect seasonal epidemics and avoid false alerts has advantages for public health purposes. This method may serve as standard to define the start of the annual influenza epidemic in countries in Europe.

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Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge

Matthew Biggerstaff, David Alper, Mark Dredze … (2016)

Background Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013–14 Unites States influenza season. Methods Challenge contestants were asked to forecast the start, peak, and intensity of the 2013–2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013–March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. Electronic supplementary material The online version of this article (doi:10.1186/s12879-016-1669-x) contains supplementary material, which is available to authorized users.

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Influenza Illness and Hospitalizations Averted by Influenza Vaccination in the United States, 2005–2011

Deliana Kostova, Carrie Reed, Lyn Finelli … (2013)

Context The goal of influenza vaccination programs is to reduce influenza-associated disease outcomes. Therefore, estimating the reduced burden of influenza as a result of vaccination over time and by age group would allow for a clear understanding of the value of influenza vaccines in the US, and of areas where improvements could lead to greatest benefits. Objective To estimate the direct effect of influenza vaccination in the US in terms of averted number of cases, medically-attended cases, and hospitalizations over six recent influenza seasons. Design Using existing surveillance data, we present a method for assessing the impact of influenza vaccination where impact is defined as either the number of averted outcomes or as the prevented disease fraction (the number of cases estimated to have been averted relative to the number of cases that would have occurred in the absence of vaccination). Results We estimated that during our 6-year study period, the number of influenza illnesses averted by vaccination ranged from a low of approximately 1.1 million (95% confidence interval (CI) 0.6–1.7 million) during the 2006–2007 season to a high of 5 million (CI 2.9–8.6 million) during the 2010–2011 season while the number of averted hospitalizations ranged from a low of 7,700 (CI 3,700–14,100) in 2009–2010 to a high of 40,400 (CI 20,800–73,000) in 2010–2011. Prevented fractions varied across age groups and over time. The highest prevented fraction in the study period was observed in 2010–2011, reflecting the post-pandemic expansion of vaccination coverage. Conclusions Influenza vaccination programs in the US produce a substantial health benefit in terms of averted cases, clinic visits and hospitalizations. Our results underscore the potential for additional disease prevention through increased vaccination coverage, particularly among nonelderly adults, and increased vaccine effectiveness, particularly among the elderly.

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PubMed ID:: 29053783

PMC ID:: 5908755

DOI:: 10.1093/aje/kwx334

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Systematic Assessment of Multiple Routine and Near Real-Time Indicators to Classify the Severity of Influenza Seasons and Pandemics in the United States, 2003-2004 Through 2015-2016.

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Influenza surveillance in Europe: establishing epidemic thresholds by the Moving Epidemic Method

Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge

Influenza Illness and Hospitalizations Averted by Influenza Vaccination in the United States, 2005–2011

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