Predictive Validation of an Influenza Spread Model

Background

Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread.

Methods and Findings

We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic.

Conclusions

Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive ability.     

The geographic synchrony of seasonal influenza: a waves across Canada and the United States

Background

As observed during the 2009 pandemic, a novel influenza virus can spread globally before the epidemic peaks locally. As consistencies in the relative timing and direction of spread could form the basis for an early alert system, the objectives of this study were to use the case-based reporting system for laboratory confirmed influenza from the Canadian FluWatch surveillance program to identify the geographic scale at which spatial synchrony exists and then to describe the geographic patterns of influenza A virus across Canada and in relationship to activity in the United States (US).

Methodology/Principal Findings

Weekly laboratory confirmations for influenza A were obtained from the Canadian FluWatch and the US FluView surveillance programs from 1997/98 to 2006/07. For the six seasons where at least 80% of the specimens were antigenically similar, we identified the epidemic midpoint of the local/regional/provincial epidemics and analyzed trends in the direction of spread. In three out of the six seasons, the epidemic appeared first in Canada. Regional epidemics were more closely synchronized across the US (3–5 weeks) compared to Canada (5–13 weeks), with a slight gradient in timing from the southwest regions in the US to northeast regions of Canada and the US. Cities, as well as rural areas within provinces, usually peaked within a couple of weeks of each other. The anticipated delay in peak activity between large cities and rural areas was not observed. In some mixed influenza A seasons, lack of synchronization sub-provincially was evident.

Conclusions/Significance

As mixing between regions appears to be too weak to force a consistency in the direction and timing of spread, local laboratory-based surveillance is needed to accurately assess the level of influenza activity in the community. In comparison, mixing between urban communities and adjacent rural areas, and between some communities, may be sufficient to force synchronization.     

Local spatial and temporal processes of influenza in Pennsylvania, USA: 2003-2009

Background

Influenza is a contagious respiratory disease responsible for annual seasonal epidemics in temperate climates. An understanding of how influenza spreads geographically and temporally within regions could result in improved public health prevention programs. The purpose of this study was to summarize the spatial and temporal spread of influenza using data obtained from the Pennsylvania Department of Health''s influenza surveillance system.

Methodology and Findings

We evaluated the spatial and temporal patterns of laboratory-confirmed influenza cases in Pennsylvania, United States from six influenza seasons (2003–2009). Using a test of spatial autocorrelation, local clusters of elevated risk were identified in the South Central region of the state. Multivariable logistic regression indicated that lower monthly precipitation levels during the influenza season (OR = 0.52, 95% CI: 0.28, 0.94), fewer residents over age 64 (OR = 0.27, 95% CI: 0.10, 0.73) and fewer residents with more than a high school education (OR = 0.76, 95% CI: 0.61, 0.95) were significantly associated with membership in this cluster. In addition, time series analysis revealed a temporal lag in the peak timing of the influenza B epidemic compared to the influenza A epidemic.

Conclusions

These findings illustrate a distinct spatial cluster of cases in the South Central region of Pennsylvania. Further examination of the regional transmission dynamics within these clusters may be useful in planning public health influenza prevention programs.     

Comparison of Different Risk Perception Measures in Predicting Seasonal Influenza Vaccination among Healthy Chinese Adults in Hong Kong: A Prospective Longitudinal Study

Background

Risk perception is a reported predictor of vaccination uptake, but which measures of risk perception best predict influenza vaccination uptake remain unclear.

Methodology

During the main influenza seasons (between January and March) of 2009 (Wave 1) and 2010 (Wave 2),505 Chinese students and employees from a Hong Kong university completed an online survey. Multivariate logistic regression models were conducted to assess how well different risk perceptions measures in Wave 1 predicted vaccination uptake against seasonal influenza in Wave 2.

Principal Findings

The results of the multivariate logistic regression models showed that feeling at risk (β = 0.25, p = 0.021) was the better predictor compared with probability judgment while probability judgment (β = 0.25, p = 0.029 ) was better than beliefs about risk in predicting subsequent influenza vaccination uptake. Beliefs about risk and feeling at risk seemed to predict the same aspect of subsequent vaccination uptake because their associations with vaccination uptake became insignificant when paired into the logistic regression model. Similarly, to compare the four scales for assessing probability judgment in predicting vaccination uptake, the 7-point verbal scale remained a significant and stronger predictor for vaccination uptake when paired with other three scales; the 6-point verbal scale was a significant and stronger predictor when paired with the percentage scale or the 2-point verbal scale; and the percentage scale was a significant and stronger predictor only when paired with the 2-point verbal scale.

Conclusions/Significance

Beliefs about risk and feeling at risk are not well differentiated by Hong Kong Chinese people. Feeling at risk, an affective-cognitive dimension of risk perception predicts subsequent vaccination uptake better than do probability judgments. Among the four scales for assessing risk probability judgment, the 7-point verbal scale offered the best predictive power for subsequent vaccination uptake.     

Demonstrating the Use of High-Volume Electronic Medical Claims Data to Monitor Local and Regional Influenza Activity in the US

Introduction

Fine-grained influenza surveillance data are lacking in the US, hampering our ability to monitor disease spread at a local scale. Here we evaluate the performances of high-volume electronic medical claims data to assess local and regional influenza activity.

Material and Methods

We used electronic medical claims data compiled by IMS Health in 480 US locations to create weekly regional influenza-like-illness (ILI) time series during 2003–2010. IMS Health captured 62% of US outpatient visits in 2009. We studied the performances of IMS-ILI indicators against reference influenza surveillance datasets, including CDC-ILI outpatient and laboratory-confirmed influenza data. We estimated correlation in weekly incidences, peak timing and seasonal intensity across datasets, stratified by 10 regions and four age groups (<5, 5–29, 30–59, and 60+ years). To test IMS-Health performances at the city level, we compared IMS-ILI indicators to syndromic surveillance data for New York City. We also used control data on laboratory-confirmed Respiratory Syncytial Virus (RSV) activity to test the specificity of IMS-ILI for influenza surveillance.

Results

Regional IMS-ILI indicators were highly synchronous with CDC''s reference influenza surveillance data (Pearson correlation coefficients rho≥0.89; range across regions, 0.80–0.97, P<0.001). Seasonal intensity estimates were weakly correlated across datasets in all age data (rho≤0.52), moderately correlated among adults (rho≥0.64) and uncorrelated among school-age children. IMS-ILI indicators were more correlated with reference influenza data than control RSV indicators (rho = 0.93 with influenza v. rho = 0.33 with RSV, P<0.05). City-level IMS-ILI indicators were highly consistent with reference syndromic data (rho≥0.86).

Conclusion

Medical claims-based ILI indicators accurately capture weekly fluctuations in influenza activity in all US regions during inter-pandemic and pandemic seasons, and can be broken down by age groups and fine geographical areas. Medical claims data provide more reliable and fine-grained indicators of influenza activity than other high-volume electronic algorithms and should be used to augment existing influenza surveillance systems.     

Seasonal Patterns in Human A (H5N1) Virus Infection: Analysis of Global Cases

Background

Human cases of highly pathogenic avian influenza (HPAI) A (H5N1) have high mortality. Despite abundant data on seasonal patterns in influenza epidemics, it is unknown whether similar patterns exist for human HPAI H5N1 cases worldwide. Such knowledge could help decrease avian-to-human transmission through increased prevention and control activities during peak periods.

Methods

We performed a systematic search of published human HPAI H5N1 cases to date, collecting month, year, country, season, hemisphere, and climate data. We used negative binomial regression to predict changes in case incidence as a function of season. To investigate hemisphere as a potential moderator, we used AIC and the likelihood-ratio test to compare the season-only model to nested models including a main effect or interaction with hemisphere. Finally, we visually assessed replication of seasonal patterns across climate groups based on the Köppen-Geiger climate classification.

Findings

We identified 617 human cases (611 with complete seasonal data) occurring in 15 countries in Southeast Asia, Africa, and the Middle East. Case occurrence was much higher in winter (n = 285, p = 0.03) than summer (n = 64), and the winter peak occurred across diverse climate groups. There was no significant interaction between hemisphere and season.

Interpretation

Across diverse climates, HPAI H5N1 virus infection in humans increases significantly in winter. This is consistent with increased poultry outbreaks and HPAI H5N1 virus transmission during cold and dry conditions. Prioritizing prevention and control activities among poultry and focusing public health messaging to reduce poultry exposures during winter months may help to reduce zoonotic transmission of HPAI H5N1 virus in resource-limited settings.     

Latitudinal Variations in Seasonal Activity of Influenza and Respiratory Syncytial Virus (RSV): A Global Comparative Review

Background

There is limited information on influenza and respiratory syncytial virus (RSV) seasonal patterns in tropical areas, although there is renewed interest in understanding the seasonal drivers of respiratory viruses.

Methods

We review geographic variations in seasonality of laboratory-confirmed influenza and RSV epidemics in 137 global locations based on literature review and electronic sources. We assessed peak timing and epidemic duration and explored their association with geography and study settings. We fitted time series model to weekly national data available from the WHO influenza surveillance system (FluNet) to further characterize seasonal parameters.

Results

Influenza and RSV activity consistently peaked during winter months in temperate locales, while there was greater diversity in the tropics. Several temperate locations experienced semi-annual influenza activity with peaks occurring in winter and summer. Semi-annual activity was relatively common in tropical areas of Southeast Asia for both viruses. Biennial cycles of RSV activity were identified in Northern Europe. Both viruses exhibited weak latitudinal gradients in the timing of epidemics by hemisphere, with peak timing occurring later in the calendar year with increasing latitude (P<0.03). Time series model applied to influenza data from 85 countries confirmed the presence of latitudinal gradients in timing, duration, seasonal amplitude, and between-year variability of epidemics. Overall, 80% of tropical locations experienced distinct RSV seasons lasting 6 months or less, while the percentage was 50% for influenza.

Conclusion

Our review combining literature and electronic data sources suggests that a large fraction of tropical locations experience focused seasons of respiratory virus activity in individual years. Information on seasonal patterns remains limited in large undersampled regions, included Africa and Central America. Future studies should attempt to link the observed latitudinal gradients in seasonality of viral epidemics with climatic and population factors, and explore regional differences in disease transmission dynamics and attack rates.     

A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002

Background

Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns.

Methods

A spatial statistical analysis using Kulldorff''s spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns.

Results

The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55) and 10 counties in eastern Kentucky (RR = 1.97). Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002) and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001).

Conclusions

This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions) with the intention of reducing tractor overturns in the highest risk counties in Kentucky.     

Supply of Neuraminidase Inhibitors Related to Reduced Influenza A (H1N1) Mortality during the 2009–2010 H1N1 Pandemic: An Ecological Study

Background

The influenza A (H1N1) pandemic swept across the globe from April 2009 to August 2010 affecting millions. Many WHO Member States relied on antiviral drugs, specifically neuraminidase inhibitors (NAIs) oseltamivir and zanamivir, to treat influenza patients in critical condition. Such drugs have been found to be effective in reducing severity and duration of influenza illness, and likely reduced morbidity during the pandemic. However, it is less clear whether NAIs used during the pandemic reduced H1N1 mortality.

Methods

Country-level data on supply of oseltamivir and zanamivir were used to predict H1N1 mortality (per 100,000 people) from July 2009 to August 2010 in forty-two WHO Member States. Poisson regression was used to model the association between NAI supply and H1N1 mortality, with adjustment for economic, demographic, and health-related confounders.

Results

After adjustment for potential confounders, each 10% increase in kilograms of oseltamivir, per 100,000 people, was associated with a 1.6% reduction in H1N1 mortality over the pandemic period (relative rate (RR) = 0.84 per log increase in oseltamivir supply). While the supply of zanamivir was considerably less than that of oseltamivir in each Member State, each 10% increase in kilogram of active zanamivir, per 100,000, was associated with a 0.3% reduction in H1N1 mortality (RR = 0.97 per log increase).

Conclusion

While there are limitations to the ecologic nature of these data, this analysis offers evidence of a protective relationship between antiviral drug supply and influenza mortality and supports a role for influenza antiviral use in future pandemics.     

Do Intensive Care Data on Respiratory Infections Reflect Influenza Epidemics?

Objectives

Severe influenza can lead to Intensive Care Unit (ICU) admission. We explored whether ICU data reflect influenza like illness (ILI) activity in the general population, and whether ICU respiratory infections can predict influenza epidemics.

Methods

We calculated the time lag and correlation between ILI incidence (from ILI sentinel surveillance, based on general practitioners (GP) consultations) and percentages of ICU admissions with a respiratory infection (from the Dutch National Intensive Care Registry) over the years 2003–2011. In addition, ICU data of the first three years was used to build three regression models to predict the start and end of influenza epidemics in the years thereafter, one to three weeks ahead. The predicted start and end of influenza epidemics were compared with observed start and end of such epidemics according to the incidence of ILI.

Results

Peaks in respiratory ICU admissions lasted longer than peaks in ILI incidence rates. Increases in ICU admissions occurred on average two days earlier compared to ILI. Predicting influenza epidemics one, two, or three weeks ahead yielded positive predictive values ranging from 0.52 to 0.78, and sensitivities from 0.34 to 0.51.

Conclusions

ICU data was associated with ILI activity, with increases in ICU data often occurring earlier and for a longer time period. However, in the Netherlands, predicting influenza epidemics in the general population using ICU data was imprecise, with low positive predictive values and sensitivities.     

Health-Related Behaviors and Effectiveness of Trivalent Inactivated versus Live Attenuated Influenza Vaccine in Preventing Influenza-Like Illness among Young Adults

Background

Vaccination is the preferred preventive strategy against influenza. Though health behaviors are known to affect immunity and vaccine delivery modes utilize different immune processes, data regarding the preferred influenza vaccine type among adults endorsing specific health-related behaviors (alcohol use, tobacco use, and exercise level) are limited.

Methods

The relative effectiveness of two currently available influenza vaccines were compared for prevention of influenza-like illness during 2 well-matched influenza seasons (2006/2007, 2008/2009) among US military personnel aged 18–49 years. Relative vaccine effectiveness was compared between those self-reporting and not reporting recent smoking history and potential alcohol problem, and by exercise level using Cox proportional hazard modeling adjusted for sociodemographic and military factors, geographic area, and other health behaviors.

Results

28,929 vaccination events and 3936 influenza-like illness events over both influenza seasons were studied. Of subjects, 27.5% were smokers, 7.7% had a potential alcohol-related problem, 10.5% reported minimal exercise, and 4.4% reported high exercise levels. Overall, the risk of influenza-like illness did not significantly differ between live attenuated and trivalent inactivated influenza vaccine recipients (hazard ratio, 0.98; 95% confidence interval, 0.90–1.06). In the final adjusted model, the relative effectiveness of the 2 vaccine types did not differ by smoking status (p = 0.10), alcohol status (p = 0.21), or activity level (p = 0.11).

Conclusions

Live attenuated and trivalent inactivated influenza vaccines were similarly effective in preventing influenza-like illness among young adults and did not differ by health-related behavior status. Influenza vaccine efforts should continue to focus simply on delivering vaccine.     

Influenza Excess Mortality from 1950–2000 in Tropical Singapore

Introduction

Tropical regions have been shown to exhibit different influenza seasonal patterns compared to their temperate counterparts. However, there is little information about the burden of annual tropical influenza epidemics across time, and the relationship between tropical influenza epidemics compared with other regions.

Methods

Data on monthly national mortality and population was obtained from 1947 to 2003 in Singapore. To determine excess mortality for each month, we used a moving average analysis for each month from 1950 to 2000. From 1972, influenza viral surveillance data was available. Before 1972, information was obtained from serial annual government reports, peer-reviewed journal articles and press articles.

Results

The influenza pandemics of 1957 and 1968 resulted in substantial mortality. In addition, there were 20 other time points with significant excess mortality. Of the 12 periods with significant excess mortality post-1972, only one point (1988) did not correspond to a recorded influenza activity. For the 8 periods with significant excess mortality periods before 1972 excluding the pandemic years, 2 years (1951 and 1953) had newspaper reports of increased pneumonia deaths. Excess mortality could be observed in almost all periods with recorded influenza outbreaks but did not always exceed the 95% confidence limits of the baseline mortality rate.

Conclusion

Influenza epidemics were the likely cause of most excess mortality periods in post-war tropical Singapore, although not every epidemic resulted in high mortality. It is therefore important to have good influenza surveillance systems in place to detect influenza activity.     

Situational awareness and health protective responses to pandemic influenza A (H1N1) in Hong Kong: a cross-sectional study

Background

Whether information sources influence health protective behaviours during influenza pandemics or other emerging infectious disease epidemics is uncertain.

Methodology

Data from cross-sectional telephone interviews of 1,001 Hong Kong adults in June, 2009 were tested against theory and data-derived hypothesized associations between trust in (formal/informal) information, understanding, self-efficacy, perceived susceptibility and worry, and hand hygiene and social distancing using Structural Equation Modelling with multigroup comparisons.

Principal Findings

Trust in formal (government/media) information about influenza was associated with greater reported understanding of A/H1N1 cause (β = 0.36) and A/H1N1 prevention self-efficacy (β = 0.25), which in turn were associated with more hand hygiene (β = 0.19 and β = 0.23, respectively). Trust in informal (interpersonal) information was negatively associated with perceived personal A/H1N1 susceptibility (β = −0.21), which was negatively associated with perceived self-efficacy (β = −0.42) but positively associated with influenza worry (β = 0.44). Trust in informal information was positively associated with influenza worry (β = 0.16) which was in turn associated with greater social distancing (β = 0.36). Multigroup comparisons showed gender differences regarding paths from trust in formal information to understanding of A/H1N1 cause, trust in informal information to understanding of A/H1N1 cause, and understanding of A/H1N1 cause to perceived self-efficacy.

Conclusions/Significance

Trust in government/media information was more strongly associated with greater self-efficacy and handwashing, whereas trust in informal information was strongly associated with perceived health threat and avoidance behaviour. Risk communication should consider the effect of gender differences.     

2009 Swine-Origin Influenza A (H1N1) Resembles Previous Influenza Isolates

Background

In April 2009, novel swine-origin influenza viruses (S-OIV) were identified in patients from Mexico and the United States. The viruses were genetically characterized as a novel influenza A (H1N1) strain originating in swine, and within a very short time the S-OIV strain spread across the globe via human-to-human contact.

Methodology

We conducted a comprehensive computational search of all available sequences of the surface proteins of H1N1 swine influenza isolates and found that a similar strain to S-OIV appeared in Thailand in 2000. The earlier isolates caused infections in pigs but only one sequenced human case, A/Thailand/271/2005 (H1N1).

Significance

Differences between the Thai cases and S-OIV may help shed light on the ability of the current outbreak strain to spread rapidly among humans.     

Who Takes Precautionary Action in the Face of the New H1N1 Influenza? Prediction of Who Collects a Free Hand Sanitizer Using a Health Behavior Model

Background

In order to fight the spread of the novel H1N1 influenza, health authorities worldwide called for a change in hygiene behavior. Within a longitudinal study, we examined who collected a free bottle of hand sanitizer towards the end of the first swine flu pandemic wave in December 2009.

Methods

629 participants took part in a longitudinal study assessing perceived likelihood and severity of an H1N1 infection, and H1N1 influenza related negative affect (i.e., feelings of threat, concern, and worry) at T1 (October 2009, week 43–44) and T2 (December 2009, week 51–52). Importantly, all participants received a voucher for a bottle of hand sanitizer at T2 which could be redeemed in a university office newly established for this occasion at T3 (ranging between 1–4 days after T2).

Results

Both a sequential longitudinal model (M2) as well as a change score model (M3) showed that greater perceived likelihood and severity at T1 (M2) or changes in perceived likelihood and severity between T1 and T2 (M3) did not directly drive protective behavior (T3), but showed a significant indirect impact on behavior through H1N1 influenza related negative affect. Specifically, increases in perceived likelihood (β = .12), severity (β = .24) and their interaction (β = .13) were associated with a more pronounced change in negative affect (M3). The more threatened, concerned and worried people felt (T2), the more likely they were to redeem the voucher at T3 (OR = 1.20).

Conclusions

Affective components need to be considered in health behavior models. Perceived likelihood and severity of an influenza infection represent necessary but not sufficient self-referential knowledge for paving the way for preventive behaviors.     

I-MOVE multi-centre case control study 2010-11: overall and stratified estimates of influenza vaccine effectiveness in Europe

Background

In the third season of I-MOVE (Influenza Monitoring Vaccine Effectiveness in Europe), we undertook a multicentre case-control study based on sentinel practitioner surveillance networks in eight European Union (EU) member states to estimate 2010/11 influenza vaccine effectiveness (VE) against medically-attended influenza-like illness (ILI) laboratory-confirmed as influenza.

Methods

Using systematic sampling, practitioners swabbed ILI/ARI patients within seven days of symptom onset. We compared influenza-positive to influenza laboratory-negative patients among those meeting the EU ILI case definition. A valid vaccination corresponded to > 14 days between receiving a dose of vaccine and symptom onset. We used multiple imputation with chained equations to estimate missing values. Using logistic regression with study as fixed effect we calculated influenza VE adjusting for potential confounders. We estimated influenza VE overall, by influenza type, age group and among the target group for vaccination.

Results

We included 2019 cases and 2391 controls in the analysis. Adjusted VE was 52% (95% CI 30-67) overall (N = 4410), 55% (95% CI 29-72) against A(H1N1) and 50% (95% CI 14-71) against influenza B. Adjusted VE against all influenza subtypes was 66% (95% CI 15-86), 41% (95% CI -3-66) and 60% (95% CI 17-81) among those aged 0-14, 15-59 and ≥60 respectively. Among target groups for vaccination (N = 1004), VE was 56% (95% CI 34-71) overall, 59% (95% CI 32-75) against A(H1N1) and 63% (95% CI 31-81) against influenza B.

Conclusions

Results suggest moderate protection from 2010-11 trivalent influenza vaccines against medically-attended ILI laboratory-confirmed as influenza across Europe. Adjusted and stratified influenza VE estimates are possible with the large sample size of this multi-centre case-control. I-MOVE shows how a network can provide precise summary VE measures across Europe.     

Effects of Green Tea Gargling on the Prevention of Influenza Infection in High School Students: A Randomized Controlled Study

Background

The anti-influenza virus activity of green tea catechins has been demonstrated in experimental studies, but clinical evidence has been inconclusive. School-aged children play an important role in the infection and spread of influenza in the form of school-based outbreaks. Preventing influenza infection among students is essential for reducing the frequency of epidemics and pandemics. As a non-pharmaceutical intervention against infection, gargling is also commonly performed in Asian countries but has not yet been extensively studied.

Methods and Findings

A randomized, open label, 2-group parallel study of 757 high school students (15 to 17 years of age) was conducted for 90 days during the influenza epidemic season from December 1st, 2011 to February 28th, 2012, in 6 high schools in Shizuoka Prefecture, Japan. The green tea gargling group gargled 3 times a day with bottled green tea, and the water gargling group did the same with tap water. The water group was restricted from gargling with green tea. The primary outcome measure was the incidence of laboratory-confirmed influenza using immunochromatographic assay for antigen detection. 757 participants were enrolled and 747 participants completed the study (384 in the green tea group and 363 in the water group). Multivariate logistic regression indicated no significant difference in the incidence of laboratory-confirmed influenza between the green tea group (19 participants; 4.9%) and the water group (25 participants; 6.9%) (adjusted OR, 0.69; 95%CI, 0.37 to 1.28; P = 0.24). The main limitation of the study is the adherence rate among high school students was lower than expected.

Conclusions

Among high school students, gargling with green tea three times a day was not significantly more efficacious than gargling with water for the prevention of influenza infection. In order to adequately assess the effectiveness of such gargling, additional large-scale randomized studies are needed.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01225770","term_id":"NCT01225770"}}NCT01225770     

The population impact of a large school-based influenza vaccination campaign

Background

The optimal vaccination strategy to mitigate the impact of influenza epidemics is unclear. In 2005, a countywide school-based influenza vaccination campaign was launched in Knox County, Tennessee (population 385,899). Approximately 41% and 48% of eligible county children aged 5–17 years were immunized with live attenuated influenza vaccine before the 2005–2006 and 2006–2007 influenza seasons, respectively. We sought to determine the population impact of this campaign.

Methods

Laboratory-confirmed influenza data defined influenza seasons. We calculated the incidence of medically attended acute respiratory illness attributable to influenza in Knox and Knox-surrounding counties (concurrent controls) during consecutive seasons (5 precampaign and 2 campaign seasons) using negative binomial regression and rate difference methods. Age-stratified analyses compared the incidence of emergency department (ED) visits and hospitalizations attributable to influenza.

Results

During precampaign seasons, estimated ED visit rates attributable to influenza were 12.39 (95% CI: 10.34–14.44) per 1000 Knox children aged 5–17 years and similar in Knox-surrounding counties. During the campaign seasons, annual Knox influenza-associated ED visit rates declined relative to rates in Knox-surrounding counties: rate ratios 0.55 (95% CI: 0.27–0.83) and 0.70 (95% CI: 0.56–0.84) for the first and second campaign seasons, respectively. Overall, there were about 35% or 4.86 per 1000 fewer influenza-associated ED visits among Knox County children aged 5–17 years attributable to the campaign. No significant declines in Knox compared to surrounding counties were detected for influenza associated ED visits in children aged <5 years, all adults combined or selected adult age subgroups, although power for these analyses was limited. Alternate rate-difference analyses yielded consistent results.

Conclusion

Vaccination of approximately 45% of Knox school-aged children with influenza vaccine was associated with a 35% annual reduction (4.86 per 1000) in ED visit rates attributable to influenza. Higher vaccination coverage and/or larger studies would be needed to determine whether similar interventions have indirect benefits in other age groups.