Can Interactions between Timing of Vaccine-Altered Influenza Pandemic Waves and Seasonality in Influenza Complications Lead to More Severe Outcomes?

Vaccination can delay the peak of a pandemic influenza wave by reducing the number of individuals initially susceptible to influenza infection. Emerging evidence indicates that susceptibility to severe secondary bacterial infections following a primary influenza infection may vary seasonally, with peak susceptibility occurring in winter. Taken together, these two observations suggest that vaccinating to prevent a fall pandemic wave might delay it long enough to inadvertently increase influenza infections in winter, when primary influenza infection is more likely to cause severe outcomes. This could potentially cause a net increase in severe outcomes. Most pandemic models implicitly assume that the probability of severe outcomes does not vary seasonally and hence cannot capture this effect. Here we show that the probability of intensive care unit (ICU) admission per influenza infection in the 2009 H1N1 pandemic followed a seasonal pattern. We combine this with an influenza transmission model to investigate conditions under which a vaccination program could inadvertently shift influenza susceptibility to months where the risk of ICU admission due to influenza is higher. We find that vaccination in advance of a fall pandemic wave can actually increase the number of ICU admissions in situations where antigenic drift is sufficiently rapid or where importation of a cross-reactive strain is possible. Moreover, this effect is stronger for vaccination programs that prevent more primary influenza infections. Sensitivity analysis indicates several mechanisms that may cause this effect. We also find that the predicted number of ICU admissions changes dramatically depending on whether the probability of ICU admission varies seasonally, or whether it is held constant. These results suggest that pandemic planning should explore the potential interactions between seasonally varying susceptibility to severe influenza outcomes and the timing of vaccine-altered pandemic influenza waves.     

Responding to Vaccine Safety Signals during Pandemic Influenza: A Modeling Study

Background

Managing emerging vaccine safety signals during an influenza pandemic is challenging. Federal regulators must balance vaccine risks against benefits while maintaining public confidence in the public health system.

Methods

We developed a multi-criteria decision analysis model to explore regulatory decision-making in the context of emerging vaccine safety signals during a pandemic. We simulated vaccine safety surveillance system capabilities and used an age-structured compartmental model to develop potential pandemic scenarios. We used an expert-derived multi-attribute utility function to evaluate potential regulatory responses by combining four outcome measures into a single measure of interest: 1) expected vaccination benefit from averted influenza; 2) expected vaccination risk from vaccine-associated febrile seizures; 3) expected vaccination risk from vaccine-associated Guillain-Barre Syndrome; and 4) expected change in vaccine-seeking behavior in future influenza seasons.

Results

Over multiple scenarios, risk communication, with or without suspension of vaccination of high-risk persons, were the consistently preferred regulatory responses over no action or general suspension when safety signals were detected during a pandemic influenza. On average, the expert panel valued near-term vaccine-related outcomes relative to long-term projected outcomes by 3∶1. However, when decision-makers had minimal ability to influence near-term outcomes, the response was selected primarily by projected impacts on future vaccine-seeking behavior.

Conclusions

The selected regulatory response depends on how quickly a vaccine safety signal is identified relative to the peak of the pandemic and the initiation of vaccination. Our analysis suggested two areas for future investment: efforts to improve the size and timeliness of the surveillance system and behavioral research to understand changes in vaccine-seeking behavior.     

Multi-Dimensional Measurement of Antibody-Mediated Heterosubtypic Immunity to Influenza

The human immune response to influenza vaccination depends in part on preexisting cross-reactive (heterosubtypic) immunity from previous infection by, and/or vaccination with, influenza strains that share antigenic determinants with the vaccine strains. However, current methods for assessing heterosubtypic antibody responses against influenza, including the hemagglutination-inhibition (HAI) assay and ELISA, are time and labor intensive, and require moderate amounts of serum and reagents. To address these issues we have developed a fluorescent multiplex assay, mPlex-Flu, that rapidly and simultaneously measures strain specific IgG, IgA, and IgM antibodies against influenza hemagglutinin (HA) from multiple viral strains. We cloned, expressed and purified HA proteins from 12 influenza strains, and coupled them to multiplex beads. Assay validation showed that minimal sample volumes (<5 μl of serum) were needed, and the assay had a linear response over a four Log₁₀ range. The assay detected nanogram levels of anti-influenza specific antibodies, had high accuracy and reproducibility, with an average percentage coefficient of variation (%CV) of 9.06 for intra-assay and 12.94 for inter-assay variability. Pre- and post-intramuscular trivalent influenza vaccination levels of virus specific Ig were consistent with HAI titer and ELISA measurements. A significant advantage of the mPLEX-Flu assay over the HAI assay is the ability to perform antigenic cartography, determining the antigenic distances between influenza HA’s, without mathematical correction for HAI data issues. For validation we performed antigenic cartography on 14 different post-influenza infection ferret sera assayed against 12 different influenza HA’s. Results were in good agreement with a phylogenetic tree generated from hierarchical clustering of the genomic HA sequences. This is the first report of the use of a multiplex method for antigenic cartography using ferret sera. Overall, the mPlex-Flu assay provides a powerful tool to rapidly assess the influenza antibody repertoire in large populations and to study heterosubtypic immunity induced by influenza vaccination.     

Seasonal Influenza Vaccination amongst Medical Students: A Social Network Analysis Based on a Cross-Sectional Study

Introduction

The Chief Medical Officer for England recommends that healthcare workers have a seasonal influenza vaccination in an attempt to protect both patients and NHS staff. Despite this, many healthcare workers do not have a seasonal influenza vaccination. Social network analysis is a well-established research approach that looks at individuals in the context of their social connections. We examine the effects of social networks on influenza vaccination decision and disease dynamics.

Methods

We used a social network analysis approach to look at vaccination distribution within the network of the Lancaster Medical School students and combined these data with the students’ beliefs about vaccination behaviours. We then developed a model which simulated influenza outbreaks to study the effects of preferentially vaccinating individuals within this network.

Results

Of the 253 eligible students, 217 (86%) provided relational data, and 65% of responders had received a seasonal influenza vaccination. Students who were vaccinated were more likely to think other medical students were vaccinated. However, there was no clustering of vaccinated individuals within the medical student social network. The influenza simulation model demonstrated that vaccination of well-connected individuals may have a disproportional effect on disease dynamics.

Conclusions

This medical student population exhibited vaccination coverage levels similar to those seen in other healthcare groups but below recommendations. However, in this population, a lack of vaccination clustering might provide natural protection from influenza outbreaks. An individual student’s perception of the vaccination coverage amongst their peers appears to correlate with their own decision to vaccinate, but the directionality of this relationship is not clear. When looking at the spread of disease within a population it is important to include social structures alongside vaccination data. Social networks influence disease epidemiology and vaccination campaigns designed with information from social networks could be a future target for policy makers.     

Universal influenza vaccination: the time to act is now

Annual influenza epidemics create a significant public health burden each year in the United States. That influenza continues to pose a public health threat despite being largely preventable through vaccination is indicative of continuing weaknesses in the U.S.'s public health system. Moreover, the burden of annual influenza epidemics and the fragility and instability of the capacity to respond to them underscore the U.S.'s ongoing vulnerability to pandemic influenza and highlights gaps in bioterrorism preparedness and response efforts. This article examines the burden of annual influenza epidemics in the U.S., efforts to combat that burden with vaccination, shortcomings of influenza vaccination efforts, and how those shortcomings exemplify weaknesses in pandemic influenza and bioterrorism preparedness efforts. We make the case for establishing an annual universal influenza vaccination program to assure access to influenza vaccination to anyone who can safely receive vaccination and desires it. Such a program could greatly reduce the annual burden of influenza while advancing and maintaining U.S. pandemic influenza and bioterrorism preparedness and response efforts.     

Knowledge of and Attitudes to Influenza Vaccination in Healthy Primary Healthcare Workers in Spain, 2011-2012

Annual influenza vaccination is recommended for healthcare workers, but many do not follow the recommendation. The objective of this study was to investigate the factors associated with seasonal influenza vaccination in the 2011–2012 season. We carried out an anonymous web survey of Spanish primary healthcare workers in 2012. Information on vaccination, and knowledge and attitudes about the influenza vaccine was collected. Workers with medical conditions that contraindicated vaccination and those with high risk conditions were excluded. Multivariate analysis was performed using unconditional logistic regression. We included 1,749 workers. The overall vaccination coverage was 50.7% and was higher in workers aged ≥ 55 years (55.7%), males (57.4%) and paediatricians (63.1%). Factors associated with vaccination were concern about infection at work (aOR 4.93; 95% CI 3.72–6.53), considering that vaccination of heathcare workers is important (aOR 2.62; 95%CI 1.83–3.75) and that vaccination is effective in preventing influenza and its complications (aOR 2.40; 95% CI 1.56–3.67). No association was found between vaccination and knowledge of influenza or the vaccine characteristics. Educational programs should aim to remove the misconceptions and attitudes that limit compliance with recommendations about influenza vaccination in primary healthcare workers rather than only increasing knowledge about influenza and the characteristics of the vaccine.     

Perspectives of immunization program managers on 2009-10 H1N1 vaccination in the United States: a national survey

In June and July 2010, we conducted a national internet-based survey of 64 city, state, and territorial immunization program managers (IPMs) to assess their experiences in managing the 2009-10 H1N1 influenza vaccination campaign. Fifty-four (84%) of the managers or individuals responsible for an immunization program responded to the survey. To manage the campaign, 76% indicated their health department activated an incident command system (ICS) and 49% used an emergency operations center (EOC). Forty percent indicated they shared the leadership of the campaign with their state-level emergency preparedness program. The managers' perceptions of the helpfulness of the emergency preparedness staff was higher when they had collaborated with the emergency preparedness program on actual or simulated mass vaccination events within the previous 2 years. Fifty-seven percent found their pandemic influenza plan helpful, and those programs that mandated that vaccine providers enter data into their jurisdiction's immunization information system (IIS) were more likely than those who did not mandate data entry to rate their IIS as valuable for facilitating registration of nontraditional providers (42% vs. 25%, p<0.05) and tracking recalled influenza vaccine (50% vs. 38%, p<0.05). Results suggest that ICS and EOC structures, pandemic influenza plans, collaborations with emergency preparedness partners during nonemergencies, and expanded use of IIS can enhance immunization programs' ability to successfully manage a large-scale vaccination campaign. Maintaining the close working relationships developed between state-level immunization and emergency preparedness programs during the H1N1 influenza vaccination campaign will be especially important as states prepare for budget cuts in the coming years.     

Personal Decision-Making Criteria Related to Seasonal and Pandemic A(H1N1) Influenza-Vaccination Acceptance among French Healthcare Workers

BACKGROUND: Influenza-vaccination rates among healthcare workers (HCW) remain low worldwide, even during the 2009 A(H1N1) pandemic. In France, this vaccination is free but administered on a voluntary basis. We investigated the factors influencing HCW influenza vaccination. METHODS: In June-July 2010, HCW from wards of five French hospitals completed a cross-sectional survey. A multifaceted campaign aimed at improving vaccination coverage in this hospital group was conducted before and during the 2009 pandemic. Using an anonymous self-administered questionnaire, we assessed the relationships between seasonal (SIV) and pandemic (PIV) influenza vaccinations, and sociodemographic and professional characteristics, previous and current vaccination statuses, and 33 statements investigating 10 sociocognitive domains. The sociocognitive domains describing HCWs' SIV and PIV profiles were analyzed using the classification-and-regression-tree method. RESULTS: Of the HCWs responding to our survey, 1480 were paramedical and 401 were medical with 2009 vaccination rates of 30% and 58% for SIV and 21% and 71% for PIV, respectively (p<0.0001 for both SIV and PIV vaccinations). Older age, prior SIV, working in emergency departments or intensive care units, being a medical HCW and the hospital they worked in were associated with both vaccinations; while work shift was associated only with PIV. Sociocognitive domains associated with both vaccinations were self-perception of benefits and health motivation for all HCW. For medical HCW, being a role model was an additional domain associated with SIV and PIV. CONCLUSIONS: Both vaccination rates remained low. Vaccination mainly depended on self-determined factors and for medical HCW, being a role model.     

Active Learning to Understand Infectious Disease Models and Improve Policy Making

Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings.     

Influenza Seasonality in the Tropics and Subtropics – When to Vaccinate?

BackgroundThe timing of the biannual WHO influenza vaccine composition selection and production cycle has been historically directed to the influenza seasonality patterns in the temperate regions of the northern and southern hemispheres. Influenza activity, however, is poorly understood in the tropics with multiple peaks and identifiable year-round activity. The evidence-base needed to take informed decisions on vaccination timing and vaccine formulation is often lacking for the tropics and subtropics. This paper aims to assess influenza seasonality in the tropics and subtropics. It explores geographical grouping of countries into vaccination zones based on optimal timing of influenza vaccination.MethodsInfluenza seasonality was assessed by different analytic approaches (weekly proportion of positive cases, time series analysis, etc.) using FluNet and national surveillance data. In case of discordance in the seasonality assessment, consensus was built through discussions with in-country experts. Countries with similar onset periods of their primary influenza season were grouped into geographical zones.ResultsThe number and period of peak activity was ascertained for 70 of the 138 countries in the tropics and subtropics. Thirty-seven countries had one and seventeen countries had two distinct peaks. Countries near the equator had secondary peaks or even identifiable year-round activity. The main influenza season in most of South America and Asia started between April and June. The start of the main season varied widely in Africa (October and December in northern Africa, April and June in Southern Africa and a mixed pattern in tropical Africa). Eight “influenza vaccination zones” (two each in America and Asia, and four in Africa and Middle East) were defined with recommendations for vaccination timing and vaccine formulation. The main limitation of our study is that FluNet and national surveillance data may lack the granularity to detect sub-national variability in seasonality patterns.ConclusionDistinct influenza seasonality patterns, though complex, could be ascertained for most countries in the tropics and subtropics using national surveillance data. It may be possible to group countries into zones based on similar recommendations for vaccine timing and formulation.     

Stereoselectivity and affinity in molecular pharmacology. IV. A search for eudismic-affinity correlations among angiotension II analogues

In order to establish the applicability of eudismic analysis (correlation between potency and the ratio of isomer potencies), the extensive data reported on the biological activities of angiotensin II analogues were examined. For a series of 13 heptapeptides epimeric at the N-terminal residue, apparent correlations were found for pressor activity in vivo, but not for 10 of them on the basis of their myotropic activity under in vitro conditions. The analogues belongning to sub-groups displaying correlations have side chains of sufficiently different nature so that their grouping is questionable. 3 octapeptides epimeric at the second residue displayed an excellent correlation for their pressor activity. The demonstrated differential metabolic susceptibility of these epimers, however, casts further doubt on the usefulness of the data as a measure of their potency. The lack of a correlation under in vitro conditions would indicate that eudismic-affinity correlations (EAC) may be limited to epimers which differ less in their properties than these angiotensin analogues. Nevertheless, until better receptor affinity estimates become available, the observed correlations may be useful in advancing our knowledge of the angiotensin II receptor in particular, and of stereoselective molecular recognition in general.     

Effectiveness of Inactivated Influenza Vaccines in Preventing Influenza-Associated Deaths and Hospitalizations among Ontario Residents Aged ≥65 Years: Estimates with Generalized Linear Models Accounting for Healthy Vaccinee Effects

Background

Estimates of the effectiveness of influenza vaccines in older adults may be biased because of difficulties identifying and adjusting for confounders of the vaccine-outcome association. We estimated vaccine effectiveness for prevention of serious influenza complications among older persons by using methods to account for underlying differences in risk for these complications.

Methods

We conducted a retrospective cohort study among Ontario residents aged ≥65 years from September 1993 through September 2008. We linked weekly vaccination, hospitalization, and death records for 1.4 million community-dwelling persons aged ≥65 years. Vaccine effectiveness was estimated by comparing ratios of outcome rates during weeks of high versus low influenza activity (defined by viral surveillance data) among vaccinated and unvaccinated subjects by using log-linear regression models that accounted for temperature and time trends with natural spline functions. Effectiveness was estimated for three influenza-associated outcomes: all-cause deaths, deaths occurring within 30 days of pneumonia/influenza hospitalizations, and pneumonia/influenza hospitalizations.

Results

During weeks when 5% of respiratory specimens tested positive for influenza A, vaccine effectiveness among persons aged ≥65 years was 22% (95% confidence interval [CI], −6%–42%) for all influenza-associated deaths, 25% (95% CI, 13%–37%) for deaths occurring within 30 days after an influenza-associated pneumonia/influenza hospitalization, and 19% (95% CI, 4%–31%) for influenza-associated pneumonia/influenza hospitalizations. Because small proportions of deaths, deaths after pneumonia/influenza hospitalizations, and pneumonia/influenza hospitalizations were associated with influenza virus circulation, we estimated that vaccination prevented 1.6%, 4.8%, and 4.1% of these outcomes, respectively.

Conclusions

By using confounding-reducing techniques with 15 years of provincial-level data including vaccination and health outcomes, we estimated that influenza vaccination prevented ∼4% of influenza-associated hospitalizations and deaths occurring after hospitalizations among older adults in Ontario.     

Seasonal Influenza Vaccination for Children in Thailand: A Cost-Effectiveness Analysis

Background

Seasonal influenza is a major cause of mortality worldwide. Routine immunization of children has the potential to reduce this mortality through both direct and indirect protection, but has not been adopted by any low- or middle-income countries. We developed a framework to evaluate the cost-effectiveness of influenza vaccination policies in developing countries and used it to consider annual vaccination of school- and preschool-aged children with either trivalent inactivated influenza vaccine (TIV) or trivalent live-attenuated influenza vaccine (LAIV) in Thailand. We also compared these approaches with a policy of expanding TIV coverage in the elderly.

Methods and Findings

We developed an age-structured model to evaluate the cost-effectiveness of eight vaccination policies parameterized using country-level data from Thailand. For policies using LAIV, we considered five different age groups of children to vaccinate. We adopted a Bayesian evidence-synthesis framework, expressing uncertainty in parameters through probability distributions derived by fitting the model to prospectively collected laboratory-confirmed influenza data from 2005-2009, by meta-analysis of clinical trial data, and by using prior probability distributions derived from literature review and elicitation of expert opinion. We performed sensitivity analyses using alternative assumptions about prior immunity, contact patterns between age groups, the proportion of infections that are symptomatic, cost per unit vaccine, and vaccine effectiveness. Vaccination of children with LAIV was found to be highly cost-effective, with incremental cost-effectiveness ratios between about 2,000 and 5,000 international dollars per disability-adjusted life year averted, and was consistently preferred to TIV-based policies. These findings were robust to extensive sensitivity analyses. The optimal age group to vaccinate with LAIV, however, was sensitive both to the willingness to pay for health benefits and to assumptions about contact patterns between age groups.

Conclusions

Vaccinating school-aged children with LAIV is likely to be cost-effective in Thailand in the short term, though the long-term consequences of such a policy cannot be reliably predicted given current knowledge of influenza epidemiology and immunology. Our work provides a coherent framework that can be used for similar analyses in other low- and middle-income countries.     

Machine Learning Methods Enable Predictive Modeling of Antibody Feature:Function Relationships in RV144 Vaccinees

The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.     

The social network around influenza vaccination in health care workers: a cross-sectional study

Background

Influenza vaccination coverage remains low among health care workers (HCWs) in many health facilities. This study describes the social network defined by HCWs’ conversations around an influenza vaccination campaign in order to describe the role played by vaccination behavior and other HCW characteristics in the configuration of the links among subjects.

Methods

This study used cross-sectional data from 235 HCWs interviewed after the 2010/2011 influenza vaccination campaign at the Hospital Clinic of Barcelona (HCB), Spain. The study asked: “Who did you talk to or share some activity with respect to the seasonal vaccination campaign?” Variables studied included sociodemographic characteristics and reported conversations among HCWs during the influenza campaign. Exponential random graph models (ERGM) were used to assess the role of shared characteristics (homophily) and individual characteristics in the social network around the influenza vaccination campaign.

Results

Links were more likely between HCWs who shared the same professional category (OR 3.13, 95% CI?=?2.61–3.75), sex (OR 1.34, 95% CI?=?1.09–1.62), age (OR 0.7, 95% CI?=?0.63–0.78 per decade of difference), and department (OR 11.35, 95% CI?=?8.17–15.64), but not between HCWs who shared the same vaccination behavior (OR 1.02, 95% CI?=?0.86–1.22). Older (OR 1.26, 95% CI?=?1.14–1.39 per extra decade of HCW) and vaccinated (OR 1.32, 95% CI?=?1.09–1.62) HCWs were more likely to be named.

Conclusions

This study finds that there is no homophily by vaccination status in whom HCWs speak to or interact with about a workplace vaccination promotion campaign. This result highlights the relevance of social network analysis in the planning of health promotion interventions.

     

The effect of universal influenza immunization on mortality and health care use

Background

In 2000, Ontario, Canada, initiated a universal influenza immunization program (UIIP) to provide free influenza vaccines for the entire population aged 6 mo or older. Influenza immunization increased more rapidly in younger age groups in Ontario compared to other Canadian provinces, which all maintained targeted immunization programs. We evaluated the effect of Ontario''s UIIP on influenza-associated mortality, hospitalizations, emergency department (ED) use, and visits to doctors'' offices.

Methods and Findings

Mortality and hospitalization data from 1997 to 2004 for all ten Canadian provinces were obtained from national datasets. Physician billing claims for visits to EDs and doctors'' offices were obtained from provincial administrative datasets for four provinces with comprehensive data. Since outcomes coded as influenza are known to underestimate the true burden of influenza, we studied more broadly defined conditions. Hospitalizations, ED use, doctors'' office visits for pneumonia and influenza, and all-cause mortality from 1997 to 2004 were modelled using Poisson regression, controlling for age, sex, province, influenza surveillance data, and temporal trends, and used to estimate the expected baseline outcome rates in the absence of influenza activity. The primary outcome was then defined as influenza-associated events, or the difference between the observed events and the expected baseline events. Changes in influenza-associated outcome rates before and after UIIP introduction in Ontario were compared to the corresponding changes in other provinces. After UIIP introduction, influenza-associated mortality decreased more in Ontario (relative rate [RR] = 0.26) than in other provinces (RR = 0.43) (ratio of RRs = 0.61, p = 0.002). Similar differences between Ontario and other provinces were observed for influenza-associated hospitalizations (RR = 0.25 versus 0.44, ratio of RRs = 0.58, p < 0.001), ED use (RR = 0.31 versus 0.69, ratio of RRs = 0.45, p < 0.001), and doctors'' office visits (RR = 0.21 versus 0.52, ratio of RRs = 0.41, p < 0.001). Sensitivity analyses were carried out to assess consistency, specificity, and the presence of a dose-response relationship. Limitations of this study include the ecological study design, the nonspecific outcomes, difficulty in modeling baseline events, data quality and availability, and the inability to control for potentially important confounders.

Conclusions

Compared to targeted programs in other provinces, introduction of universal vaccination in Ontario in 2000 was associated with relative reductions in influenza-associated mortality and health care use. The results of this large-scale natural experiment suggest that universal vaccination may be an effective public health measure for reducing the annual burden of influenza.     

Quantitative Outcomes of a One Health approach to Study Global Health Challenges

Having gained momentum in the last decade, the One Health initiative promotes a holistic approach to address complex global health issues. Before recommending its adoption to stakeholders, however, it is paramount to first compile quantitative evidence of the benefit of such an approach. The aim of this scoping review was to identify and summarize primary research that describes monetary and non-monetary outcomes following adoption of a One Health approach. An extensive literature search yielded a total of 42,167 references, of which 85 were included in the final analysis. The top two biotic health issues addressed in these studies were rabies and malaria; the top abiotic health issue was air pollution. Most studies described collaborations between human and animal (n = 42), or human and environmental disciplines (n = 41); commonly reported interventions included vector control and animal vaccination. Monetary outcomes were commonly expressed as cost–benefit or cost–utility ratios; non-monetary outcomes were described using disease frequency or disease burden measurements. The majority of the studies reported positive or partially positive outcomes. This paper illustrates the variety of health challenges that can be addressed using a One Health approach, and provides tangible quantitative measures that can be used to evaluate future implementations of the One Health approach.     

Monitoring influenza activity in the United States: a comparison of traditional surveillance systems with Google Flu Trends

Background

Google Flu Trends was developed to estimate US influenza-like illness (ILI) rates from internet searches; however ILI does not necessarily correlate with actual influenza virus infections.

Methods and Findings

Influenza activity data from 2003–04 through 2007–08 were obtained from three US surveillance systems: Google Flu Trends, CDC Outpatient ILI Surveillance Network (CDC ILI Surveillance), and US Influenza Virologic Surveillance System (CDC Virus Surveillance). Pearson''s correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data. An analysis was performed to investigate outlier observations and determine the extent to which they affected the correlations between surveillance data. Pearson''s correlation coefficient describing Google Flu Trends and CDC Virus Surveillance over the study period was 0.72 (95% CI: 0.64, 0.79). The correlation between CDC ILI Surveillance and CDC Virus Surveillance over the same period was 0.85 (95% CI: 0.81, 0.89). Most of the outlier observations in both comparisons were from the 2003–04 influenza season. Exclusion of the outlier observations did not substantially improve the correlation between Google Flu Trends and CDC Virus Surveillance (0.82; 95% CI: 0.76, 0.87) or CDC ILI Surveillance and CDC Virus Surveillance (0.86; 95%CI: 0.82, 0.90).

Conclusions

This analysis demonstrates that while Google Flu Trends is highly correlated with rates of ILI, it has a lower correlation with surveillance for laboratory-confirmed influenza. Most of the outlier observations occurred during the 2003–04 influenza season that was characterized by early and intense influenza activity, which potentially altered health care seeking behavior, physician testing practices, and internet search behavior.     

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

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.