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1.  Factors Affecting Intention to Receive and Self-Reported Receipt of 2009 Pandemic (H1N1) Vaccine in Hong Kong: A Longitudinal Study 
PLoS ONE  2011;6(3):e17713.
Background
Vaccination was a core component for mitigating the 2009 influenza pandemic (pH1N1). However, a vaccination program's efficacy largely depends on population compliance. We examined general population decision-making for pH1N1 vaccination using a modified Theory of Planned Behaviour (TBP).
Methodology
We conducted a longitudinal study, collecting data before and after the introduction of pH1N1 vaccine in Hong Kong. Structural equation modeling (SEM) tested if a modified TPB had explanatory utility for vaccine uptake among adults.
Principal Findings
Among 896 subjects who completed both the baseline and the follow-up surveys, 7% (67/896) reported being “likely/very likely/certain” to be vaccinated (intent) but two months later only 0.8% (7/896) reported having received pH1N1 vaccination. Perception of low risk from pH1N1 (60%) and concerns regarding adverse effects of the vaccine (37%) were primary justifications for avoiding pH1N1 vaccination. Greater perceived vaccine benefits (β = 0.15), less concerns regarding vaccine side-effects (β = −0.20), greater adherence to social norms of vaccination (β = 0.39), anticipated higher regret if not vaccinated (β = 0.47), perceived higher self-efficacy for vaccination (β = 0.12) and history of seasonal influenza vaccination (β = 0.12) were associated with higher intention to receive the pH1N1 vaccine, which in turn predicted self-reported vaccination uptake (β = 0.30). Social norm (β = 0.70), anticipated regret (β = 0.19) and vaccination intention (β = 0.31) were positively associated with, and accounted for 70% of variance in vaccination planning, which, in turn subsequently predicted self-reported vaccination uptake (β = 0.36) accounting for 36% of variance in reported vaccination behaviour.
Conclusions/Significance
Perceived low risk from pH1N1 and perceived high risk from pH1N1 vaccine inhibited pH1N1 vaccine uptake. Both the TPB and the additional components contributed to intended vaccination uptake but social norms and anticipated regret predominantly associated with vaccination intention and planning. Vaccination planning is a more significant proximal determinant of uptake of pH1N1 vaccine than is intention. Intention alone is an unreliable predictor of future vaccine uptake.
doi:10.1371/journal.pone.0017713
PMCID: PMC3055876  PMID: 21412418
2.  Policy Resistance Undermines Superspreader Vaccination Strategies for Influenza 
PLoS Computational Biology  2013;9(3):e1002945.
Theoretical models of infection spread on networks predict that targeting vaccination at individuals with a very large number of contacts (superspreaders) can reduce infection incidence by a significant margin. These models generally assume that superspreaders will always agree to be vaccinated. Hence, they cannot capture unintended consequences such as policy resistance, where the behavioral response induced by a new vaccine policy tends to reduce the expected benefits of the policy. Here, we couple a model of influenza transmission on an empirically-based contact network with a psychologically structured model of influenza vaccinating behavior, where individual vaccinating decisions depend on social learning and past experiences of perceived infections, vaccine complications and vaccine failures. We find that policy resistance almost completely undermines the effectiveness of superspreader strategies: the most commonly explored approaches that target a randomly chosen neighbor of an individual, or that preferentially choose neighbors with many contacts, provide at best a relative improvement over their non-targeted counterpart as compared to when behavioral feedbacks are ignored. Increased vaccine coverage in super spreaders is offset by decreased coverage in non-superspreaders, and superspreaders also have a higher rate of perceived vaccine failures on account of being infected more often. Including incentives for vaccination provides modest improvements in outcomes. We conclude that the design of influenza vaccine strategies involving widespread incentive use and/or targeting of superspreaders should account for policy resistance, and mitigate it whenever possible.
Author Summary
Superspreaders are the small number of individuals responsible for the majority of infections. Theoretical models have shown how vaccinating superspreaders can be a highly efficient way to control disease. However, these models neglect behavior by assuming that superspreaders will always agree to be vaccinated. This is a problematic assumption for influenza vaccination, which is voluntary in most populations, and for which vaccine coverage is often suboptimal. We developed a model of seasonal influenza transmission on a network of individuals who make decisions about whether or not to get vaccinated based on known determinants of vaccine uptake, such as personal infection history, perceived vaccine risks, and social influences. We found that, because of feedbacks between disease spread and individual vaccinating behavior, attempts to boost vaccine coverage in superspreaders through the use of incentives or recruiting by social contacts are almost completely undermined by such feedbacks. For example, higher vaccine uptake in superspreaders reduces influenza incidence, which in the next season reduces the perceived need for vaccination among non-superspreaders, who then do not become vaccinated as much. Our results suggest that the design of potential strategies to reach influenza superspreaders should account for behavioral feedbacks, since they may blunt policy effectiveness.
doi:10.1371/journal.pcbi.1002945
PMCID: PMC3591296  PMID: 23505357
3.  The Effects of Influenza Vaccination of Health Care Workers in Nursing Homes: Insights from a Mathematical Model 
PLoS Medicine  2008;5(10):e200.
Background
Annual influenza vaccination of institutional health care workers (HCWs) is advised in most Western countries, but adherence to this recommendation is generally low. Although protective effects of this intervention for nursing home patients have been demonstrated in some clinical trials, the exact relationship between increased vaccine uptake among HCWs and protection of patients remains unknown owing to variations between study designs, settings, intensity of influenza seasons, and failure to control all effect modifiers. Therefore, we use a mathematical model to estimate the effects of HCW vaccination in different scenarios and to identify a herd immunity threshold in a nursing home department.
Methods and Findings
We use a stochastic individual-based model with discrete time intervals to simulate influenza virus transmission in a 30-bed long-term care nursing home department. We simulate different levels of HCW vaccine uptake and study the effect on influenza virus attack rates among patients for different institutional and seasonal scenarios. Our model reveals a robust linear relationship between the number of HCWs vaccinated and the expected number of influenza virus infections among patients. In a realistic scenario, approximately 60% of influenza virus infections among patients can be prevented when the HCW vaccination rate increases from 0 to 1. A threshold for herd immunity is not detected. Due to stochastic variations, the differences in patient attack rates between departments are high and large outbreaks can occur for every level of HCW vaccine uptake.
Conclusions
The absence of herd immunity in nursing homes implies that vaccination of every additional HCW protects an additional fraction of patients. Because of large stochastic variations, results of small-sized clinical trials on the effects of HCW vaccination should be interpreted with great care. Moreover, the large variations in attack rates should be taken into account when designing future studies.
Using a mathematical model to simulate influenza transmission in nursing homes, Carline van den Dool and colleagues find that each additional staff member vaccinated further reduces the risk to patients.
Editors' Summary
Background.
Every winter, millions of people catch influenza, a contagious viral disease of the nose, throat, and airways. Most people recover completely from influenza within a week or two but some develop life-threatening complications such as bacterial pneumonia. As a result, influenza outbreaks kill about half a million people—mainly infants, elderly people, and chronically ill individuals—each year. To minimize influenza-related deaths, the World Health Organization recommends that vulnerable people be vaccinated against influenza every autumn. Annual vaccination is necessary because flu viruses continually make small changes to the viral proteins (antigens) that the immune system recognizes. This means that an immune response produced one year provides only partial protection against influenza the next year. To provide maximum protection against influenza, each year's vaccine contains disabled versions of the major circulating strains of influenza viruses.
Why Was This Study Done?
Most Western countries also recommend annual flu vaccination for health care workers (HCWs) in hospitals and other institutions to reduce the transmission of influenza to vulnerable patients. However, many HCWs don't get a regular flu shot, so should efforts be made to increase their rate of vaccine uptake? To answer this question, public-health experts need to know more about the relationship between vaccine uptake among HCWs and patient protection. In particular, they need to know whether a high rate of vaccine uptake by HCWs will provide “herd immunity.” Herd immunity occurs because, when a sufficient fraction of a population is immune to a disease that passes from person to person, infected people rarely come into contact with susceptible people, which means that both vaccinated and unvaccinated people are protected from the disease. In this study, the researchers develop a mathematical model to investigate the relationship between vaccine uptake among HCWs and patient protection in a nursing home department.
What Did the Researchers Do and Find?
To predict influenza virus attack rates (the number of patient infections divided by the number of patients in a nursing home department during an influenza season) at different levels of HCW vaccine uptake, the researchers develop a stochastic transmission model to simulate epidemics on a computer. This model predicts that as the HCW vaccination rate increases from 0 (no HCWs vaccinated) to 1 (all the HCWs vaccinated), the expected average influenza virus attack rate decreases at a constant rate. In the researchers' baseline scenario—a nursing home department with 30 beds where patients come into contact with other patients, HCWs, and visitors—the model predicts that about 60% of the patients who would have been infected if no HCWs had been vaccinated are protected when all the HCWs are vaccinated, and that seven HCWs would have to be vaccinated to protect one patient. This last figure does not change with increasing vaccine uptake, which indicates that there is no level of HCW vaccination that completely stops the spread of influenza among the patients; that is, there is no herd immunity. Finally, the researchers show that large influenza outbreaks can happen by chance at every level of HCW vaccine uptake.
What Do These Findings Mean?
As with all mathematical models, the accuracy of these predictions may depend on the specific assumptions built into the model. Therefore the researchers verified that their findings hold for a wide range of plausible assumptions. These findings have two important practical implications. First, the direct relationship between HCW vaccination and patient protection and the lack of any herd immunity suggest that any increase in HCW vaccine uptake will be beneficial to patients in nursing homes. That is, increasing the HCW vaccination rate from 80% to 90% is likely to be as important as increasing it from 10% to 20%. Second, even 100% HCW vaccination cannot guarantee that influenza outbreaks will not occasionally occur in nursing homes. Because of the large variation in attack rates, the results of small clinical trials on the effects of HCW vaccination may be inaccurate and future studies will need to be very large if they are to provide reliable estimates of the amount of protection that HCW vaccination provides to vulnerable patients.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050200.
Read the related PLoSMedicine Perspective by Cécile Viboud and Mark Miller
A related PLoSMedicine Research Article by Jeffrey Kwong and colleagues is also available
The World Health Organization provides information on influenza and on influenza vaccines (in several languages)
The US Centers for Disease Control and Prevention provide information for patients and professionals on all aspects of influenza (in English and Spanish)
The UK Health Protection Agency also provides information on influenza
MedlinePlus provides a list of links to other information about influenza (in English and Spanish)
The UK National Health Service provides information about herd immunity, including a simple explanatory animation
The European Centre for Disease Prevention and Control provides an overview on the types of influenza
doi:10.1371/journal.pmed.0050200
PMCID: PMC2573905  PMID: 18959470
4.  Estimates of Pandemic Influenza Vaccine Effectiveness in Europe, 2009–2010: Results of Influenza Monitoring Vaccine Effectiveness in Europe (I-MOVE) Multicentre Case-Control Study 
PLoS Medicine  2011;8(1):e1000388.
Results from a European multicentre case-control study reported by Marta Valenciano and colleagues suggest good protection by the pandemic monovalent H1N1 vaccine against pH1N1 and no effect of the 2009–2010 seasonal influenza vaccine on H1N1.
Background
A multicentre case-control study based on sentinel practitioner surveillance networks from seven European countries was undertaken to estimate the effectiveness of 2009–2010 pandemic and seasonal influenza vaccines against medically attended influenza-like illness (ILI) laboratory-confirmed as pandemic influenza A (H1N1) (pH1N1).
Methods and Findings
Sentinel practitioners swabbed ILI patients using systematic sampling. We included in the study patients meeting the European ILI case definition with onset of symptoms >14 days after the start of national pandemic vaccination campaigns. We compared pH1N1 cases to influenza laboratory-negative controls. A valid vaccination corresponded to >14 days between receiving a dose of vaccine and symptom onset. We estimated pooled vaccine effectiveness (VE) as 1 minus the odds ratio with the study site as a fixed effect. Using logistic regression, we adjusted VE for potential confounding factors (age group, sex, month of onset, chronic diseases and related hospitalizations, smoking history, seasonal influenza vaccinations, practitioner visits in previous year). We conducted a complete case analysis excluding individuals with missing values and a multiple multivariate imputation to estimate missing values. The multivariate imputation (n = 2902) adjusted pandemic VE (PIVE) estimates were 71.9% (95% confidence interval [CI] 45.6–85.5) overall; 78.4% (95% CI 54.4–89.8) in patients <65 years; and 72.9% (95% CI 39.8–87.8) in individuals without chronic disease. The complete case (n = 1,502) adjusted PIVE were 66.0% (95% CI 23.9–84.8), 71.3% (95% CI 29.1–88.4), and 70.2% (95% CI 19.4–89.0), respectively. The adjusted PIVE was 66.0% (95% CI −69.9 to 93.2) if vaccinated 8–14 days before ILI onset. The adjusted 2009–2010 seasonal influenza VE was 9.9% (95% CI −65.2 to 50.9).
Conclusions
Our results suggest good protection of the pandemic monovalent vaccine against medically attended pH1N1 and no effect of the 2009–2010 seasonal influenza vaccine. However, the late availability of the pandemic vaccine and subsequent limited coverage with this vaccine hampered our ability to study vaccine benefits during the outbreak period. Future studies should include estimation of the effectiveness of the new trivalent vaccine in the upcoming 2010–2011 season, when vaccination will occur before the influenza season starts.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Following the World Health Organization's declaration of pandemic phase six in June 2009, manufacturers developed vaccines against pandemic influenza A 2009 (pH1N1). On the basis of the scientific opinion of the European Medicines Agency, the European Commission initially granted marketing authorization to three pandemic vaccines for use in European countries. During the autumn of 2009, most European countries included the 2009–2010 seasonal influenza vaccine and the pandemic vaccine in their influenza vaccination programs.
The Influenza Monitoring Vaccine Effectiveness in Europe network (established to monitor seasonal and pandemic influenza vaccine effectiveness) conducted seven case-control and three cohort studies in seven European countries in 2009–2010 to estimate the effectiveness of the pandemic and seasonal vaccines. Data from the seven pilot case-control studies were pooled to provide overall adjusted estimates of vaccine effectiveness.
Why Was This Study Done?
After seasonal and pandemic vaccines are made available to populations, it is necessary to estimate the effectiveness of the vaccines at the population level during every influenza season. Therefore, this study was conducted in European countries to estimate the pandemic influenza vaccine effectiveness and seasonal influenza vaccine effectiveness against people presenting to their doctor with influenza-like illness who were confirmed (by laboratory tests) to be infected with pH1N1.
What Did the Researchers Do and Find?
The researchers conducted a multicenter case-control study on the basis of practitioner surveillance networks from seven countries—France, Hungary, Ireland, Italy, Romania, Portugal, and Spain. Patients consulting a participating practitioner for influenza-like illness had a nasal or throat swab taken within 8 days of symptom onset. Cases were swabbed patients who tested positive for pH1N1. Patients presenting with influenza-like illness whose swab tested negative for any influenza virus were controls.
Individuals were considered vaccinated if they had received a dose of the vaccine more than 14 days before the date of onset of influenza-like illness and unvaccinated if they were not vaccinated at all, or if the vaccine was given less than 15 days before the onset of symptoms. The researchers analyzed pandemic influenza vaccination effectiveness in those vaccinated less than 8 days, those vaccinated between and including 8 and 14 days, and those vaccinated more than 14 days before onset of symptoms compared to those who had never been vaccinated.
The researchers used modeling (taking account of all potential confounding factors) to estimate adjusted vaccine effectiveness and stratified the adjusted pandemic influenza vaccine effectiveness and the adjusted seasonal influenza vaccine effectiveness in three age groups (<15, 15–64, and ≥65 years of age).
The adjusted results suggest that the 2009–2010 seasonal influenza vaccine did not protect against pH1N1 illness. However, one dose of the pandemic vaccines used in the participating countries conferred good protection (65.5%–100% according to various stratifications performed) against pH1N1 in people who attended their practitioner with influenza-like illness, especially in people aged <65 years and in those without any chronic disease. Furthermore, good pandemic influenza vaccine effectiveness was observed as early as 8 days after vaccination.
What Do These Findings Mean?
The results of this study provide early estimates of the pandemic influenza vaccine effectiveness suggesting that the monovalent pandemic vaccines have been effective. The findings also give an indication of the vaccine effectiveness for the Influenza A (H1N1) 2009 strain included in the 2010–2011 seasonal vaccines, although specific vaccine effectiveness studies will have to be conducted to verify if similar good effectiveness are observed with 2010–2011 trivalent vaccines. However, the results of this study should be interpreted with caution because of limitations in the pandemic context (late timing of the studies, low incidence, low vaccine coverage leading to imprecise estimates) and potential biases due the study design, confounding factors, and missing values. The researchers recommend that in future season studies, the sample size per country should be enlarged in order to allow for precise pooled and stratified analyses.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000388.
The World Health Organization has information on H1N1 vaccination
The US Centers for Disease Control and Prevention provides a fact sheet on the 2009 H1N1 influenza virus
The US Department of Health and Human services has a comprehensive website on flu
The European Centre for Disease Prevention and Control provides information on 2009 H1N1 pandemic
The European Centre for Disease Prevention and Control presents a summary of the 2009 H1N1 pandemic in Europe and elsewhere
doi:10.1371/journal.pmed.1000388
PMCID: PMC3019108  PMID: 21379316
5.  Risk Perception, Preventive Behaviors, and Vaccination Coverage in the Korean Population during the 2009–2010 Pandemic Influenza A (H1N1): Comparison between High-Risk Group and Non–High-Risk Group 
PLoS ONE  2013;8(5):e64230.
Background
This study was carried out to estimate the vaccination coverage, public perception, and preventive behaviors against pandemic influenza A (H1N1) and to understand the motivation and barriers to vaccination between high-risk and non–high-risk groups during the outbreak of pandemic influenza A (H1N1).
Methodology/Principal Findings
A cross-sectional nationwide telephone survey of 1,650 community-dwelling Korean adults aged 19 years and older was conducted in the later stage of the 2009–2010 pandemic influenza A (H1N1) outbreak. The questionnaire identified the demographics, vaccination status of participants and all household members, barriers to non-vaccination, perceived threat, and preventive behaviors. In Korea, the overall rate of pandemic influenza vaccination coverage in the surveyed population was 15.5%; vaccination coverage in the high-risk group and non–high-risk group was 47.3% and 8.0%, respectively. In the high-risk group, the most important triggering event for vaccination was receiving a notice from a public health organization. In the non–high-risk group, vaccination was more strongly influenced by previous experience with influenza or mass media campaigns. In both groups, the most common reasons for not receiving vaccination was that their health was sufficient to forgo the vaccination, and lack of time. There was no significant difference in how either group perceived the threat or adopted preventive behavior. The predictive factors for pandemic influenza vaccination were being elderly (age ≥65 years), prior seasonal influenza vaccination, and chronic medical disease.
Conclusions/Significance
With the exception of vaccination coverage, the preventive behaviors of the high-risk group were not different from those of the non–high-risk group during the 2009–2010 pandemic. For future pandemic preparedness planning, it is crucial to reinforce preventive behaviors to avoid illness before vaccination and to increase vaccination coverage in the high-risk group.
doi:10.1371/journal.pone.0064230
PMCID: PMC3656839  PMID: 23691175
6.  Erratic Flu Vaccination Emerges from Short-Sighted Behavior in Contact Networks 
PLoS Computational Biology  2011;7(1):e1001062.
The effectiveness of seasonal influenza vaccination programs depends on individual-level compliance. Perceptions about risks associated with infection and vaccination can strongly influence vaccination decisions and thus the ultimate course of an epidemic. Here we investigate the interplay between contact patterns, influenza-related behavior, and disease dynamics by incorporating game theory into network models. When individuals make decisions based on past epidemics, we find that individuals with many contacts vaccinate, whereas individuals with few contacts do not. However, the threshold number of contacts above which to vaccinate is highly dependent on the overall network structure of the population and has the potential to oscillate more wildly than has been observed empirically. When we increase the number of prior seasons that individuals recall when making vaccination decisions, behavior and thus disease dynamics become less variable. For some networks, we also find that higher flu transmission rates may, counterintuitively, lead to lower (vaccine-mediated) disease prevalence. Our work demonstrates that rich and complex dynamics can result from the interaction between infectious diseases, human contact patterns, and behavior.
Author Summary
When influenza spreads through a human population, its dynamics are shaped by both the complex patterns of contact that arise through our daily activities and individual decisions about the prevention and treatment of flu infections. However, until recently, mathematical models of flu transmission have ignored complex interaction and behavioral patterns in order to facilitate mathematical analyses. Here, we combine two recent approaches to modeling flu–network theory and game theory–to address the interplay between contact patterns and host vaccination decisions during seasonal flu outbreaks. Intuitively, the more contacts one has, the more likely he or she is to vaccinate. However, under the assumption that people make rational decisions based on complete information about the prior seasonal epidemic, vaccination decisions are predicted to vacillate dramatically. A severe epidemic in one year inspires high vaccination rates in the following year; this causes a milder epidemic which then leads to lower vaccination rates in the following year; and the cycle begins anew. We find further that the more homogeneous the contact patterns, the more pronounced the vacillations will be, and that decision-making based on multiple past seasons (rather than just one) leads to much more consistent behavior.
doi:10.1371/journal.pcbi.1001062
PMCID: PMC3029241  PMID: 21298083
7.  Factors Mediating Seasonal and Influenza A (H1N1) Vaccine Acceptance among Ethnically Diverse Populations in the Urban South 
Vaccine  2012;30(28):4200-4208.
Objective
We examined the acceptability of the influenza A (H1N1) and seasonal vaccinations immediately following government manufacture approval to gauge potential product uptake in minority communities. We studied correlates of vaccine acceptance including attitudes, beliefs, perceptions, and influenza immunization experiences, and sought to identify communication approaches to increase influenza vaccine coverage in community settings.
Methods
Adults ≥ 18 years participated in a cross-sectional survey from September through December 2009. Venue-based sampling was used to recruit participants of racial and ethnic minorities.
Results
The sample (N=503) included mostly lower income (81.9%, n=412) participants and African Americans (79.3%, n=399). Respondents expressed greater acceptability of the H1N1 vaccination compared to seasonal flu immunization (t=2.86, p=0.005) although H1N1 vaccine acceptability was moderately low (38%, n=191). Factors associated with acceptance of the H1N1 vaccine included positive attitudes about immunizations [OR=0.23, CI (0.16, 0.33)], community perceptions of H1N1 [OR=2.15, CI (1.57, 2.95)], and having had a flu shot in the past 5 years [OR=2.50, CI (1.52, 4.10). The factors associated with acceptance of the seasonal flu vaccine included positive attitudes about immunization [OR=0.43, CI (0.32, 0.59)], community perceptions of H1N1 [OR=1.53, CI (1.16, 2.01)], and having had the flu shot in the past 5 years [OR=3.53, CI (2.16, 5.78)]. Participants were most likely to be influenced to take a flu shot by physicians [OR=1.94, CI (1.31, 2.86)]. Persons who obtained influenza vaccinations indicated that Facebook (χ2=11.7, p=.02) and Twitter (χ2=18.1, p=.001) could be useful vaccine communication channels and that churches (χ2=21.5, p<.001) and grocery stores (χ2=21.5, p<.001) would be effective “flu shot stops” in their communities.
Conclusions
In this population, positive vaccine attitudes and community perceptions, along with previous flu vaccination, were associated with H1N1 and seasonal influenza vaccine acceptance. Increased immunization coverage in this community may be achieved through physician communication to dispel vaccine conspiracy beliefs and discussion about vaccine protection via social media and in other community venues.
doi:10.1016/j.vaccine.2012.04.053
PMCID: PMC3522428  PMID: 22537991
H1N1 Vaccine; Acceptability; Vaccine Refusal; Immunization Coverage; Minorities
8.  Time will tell: community acceptability of HIV vaccine research before and after the “Step Study” vaccine discontinuation 
Objective
This study examines whether men-who-have-sex-with-men (MSM) and transgender (TG) persons’ attitudes, beliefs, and risk perceptions toward human immunodeficiency virus (HIV) vaccine research have been altered as a result of the negative findings from a phase 2B HIV vaccine study.
Design
We conducted a cross-sectional survey among MSM and TG persons (N = 176) recruited from community settings in Atlanta from 2007 to 2008. The first group was recruited during an active phase 2B HIV vaccine trial in which a candidate vaccine was being evaluated (the “Step Study”), and the second group was recruited after product futility was widely reported in the media.
Methods
Descriptive statistics, t tests, and chi-square tests were conducted to ascertain differences between the groups, and ordinal logistic regressions examined the influences of the above-mentioned factors on a critical outcome, future HIV vaccine study participation. The ordinal regression outcomes evaluated the influences on disinclination, neutrality, and inclination to study participation.
Results
Behavioral outcomes such as future recruitment, event attendance, study promotion, and community mobilization did not reveal any differences in participants’ intentions between the groups. However, we observed greater interest in HIV vaccine study screening (t = 1.07, P < 0.05) and enrollment (t = 1.15, P < 0.05) following negative vaccine findings. Means on perceptions, attitudes, and beliefs did not differ between the groups. Before this development, only beliefs exhibited a strong relationship on the enrollment intention (β = 2.166, P = 0.002). However, the effect disappeared following negative trial results, with the positive assessment of the study-site perceptions being the only significant contributing factor on enrollment intentions (β = 1.369, P = 0.011).
Conclusion
Findings show greater enrollment intention among this population in the wake of negative efficacy findings from the Step Study. The resolve of this community to find an HIV vaccine is evident. Moreover, any exposure to information disseminated in the public arena did not appear to negatively influence the potential for future participation in HIV vaccine studies among this population. The results suggest that subsequent studies testing candidate vaccines could be conducted in this population.
doi:10.2147/OAJCT.S11915
PMCID: PMC2996614  PMID: 21152413
AIDS; men-who-have-sex-with-men; recruitment; community engagement; willingness to participate
9.  Strategies to increase influenza vaccination rates: outcomes of a nationwide cross-sectional survey of UK general practice 
BMJ Open  2012;2(3):e000851.
Objective
To identify practice strategies associated with higher flu vaccination rates in primary care.
Design
Logistic regression analysis of data from a cross-sectional online questionnaire.
Setting
795 general practices across England.
Participants
569 practice managers, 335 nursing staff and 107 general practitioners.
Primary outcome measures
Flu vaccination rates achieved by each practice in different groups of at-risk patients.
Results
7 independent factors associated with higher vaccine uptake were identified. Having a lead staff member for planning the flu campaign and producing a written report of practice performance predicted an 8% higher vaccination rate for at-risk patients aged <65 years (OR 1.37, 95% CI 1.10 to 1.71). These strategies, plus sending a personal invitation to all eligible patients and only stopping vaccination when Quality and Outcomes Framework targets are reached, predicted a 7% higher vaccination rate (OR 1.45, 95% CI 1.10 to 1.92) in patients aged ≥65 years. Using a lead member of staff for identifying eligible patients, with either a modified manufacturer's or in-house search programme for interrogating the practice IT system, independently predicted a 4% higher vaccination rate in patients aged ≥65 years (OR 1.22, 95% CI 1.06 to 1.41/OR 1.20, 95% CI 1.03 to 1.40). The provision of flu vaccine by midwives was associated with a 4% higher vaccination rate in pregnant women (OR 1.19, 95% CI 1.02 to 1.40).
Conclusions
Clear leadership, effective communication about performance and methods used to identify and contact eligible patients were independently associated with significantly higher rates of flu vaccination. Financial targets appear to incentivise practices to work harder to maximise seasonal influenza vaccine uptake. The strategies identified here could help primary care providers to substantially increase their seasonal flu vaccination rates towards or even above the Chief Medical Officer's targets.
Article summary
Article focus
Uptake of seasonal influenza vaccination in the UK's at-risk population is below the national and international target of 75%.
Evidence-based guidance, to advise practices how to optimise all aspects of their flu vaccination campaigns and maximise their likelihood of protecting at-risk patients against flu and its serious sequelae, is greatly needed.
This study sought to identify which strategies and procedures were associated with higher rates of flu vaccine uptake.
Key messages
This study has identified seven key strategies that were significantly associated with the success of practices' seasonal flu vaccination campaigns.
If widely implemented by general practices, average vaccination rates would be predicted to rise by 7%–8% (thereby exceeding WHO target in patients aged >65 years).
Strengths and limitations of this study
The study sample was large and representative, despite a participation rate of only 27.5%.
Outcome measures (vaccination rates) were objective and corrected for practice size.
Strategies used to provide and encourage vaccination were self-reported.
doi:10.1136/bmjopen-2011-000851
PMCID: PMC3358626  PMID: 22581793
10.  Low Acceptability of A/H1N1 Pandemic Vaccination in French Adult Population: Did Public Health Policy Fuel Public Dissonance? 
PLoS ONE  2010;5(4):e10199.
Background
In July 2009, French public health authorities embarked in a mass vaccination campaign against A/H1N1 2009 pandemic-influenza. We explored the attitudes and behaviors of the general population toward pandemic vaccination.
Methodology/Principal Findings
We conducted a cross-sectional online survey among 2,253 French representative adults aged 18 to 64 from November 17 to 25, 2009 (completion rate: 93.8%). The main outcome was the acceptability of A/H1N1 vaccination as defined by previous receipt or intention to get vaccinated (“Yes, certainly”, “Yes, probably”). Overall 17.0% (CI 95%, 15.5% to 18.7%) of respondents accepted A/H1N1 vaccination. Independent factors associated with acceptability included: male sex (p = .0001); older age (p = .002); highest or lowest level of education (p = .016); non-clerical occupation (p = .011); having only one child (p = .008); and having received seasonal flu vaccination in prior 3 years (p<.0001). Acceptability was also significantly higher among pregnant women (37.9%) and other at risk groups with chronic diseases (34.8%) (p = .002). Only 35.5% of respondents perceived A/H1N1 influenza illness as a severe disease and 12.7% had experienced A/H1N1 cases in their close relationships with higher acceptability (p<.0001 and p = .006, respectively). In comparison to 26.0% respondents who did not consult their primary care physician, acceptability was significantly higher among 8.0% respondents who were formally advised to get vaccinated, and lower among 63.7% respondents who were not advised to get vaccinated (respectively: 15.8%, 59.5% and 11.7%- p<.0001). Among respondents who refused vaccination, 71.2% expressed concerns about vaccine safety.
Conclusions/Significance
Our survey occurred one week before the peak of the pandemic in France. We found that alarming public health messages aiming at increasing the perception of risk severity were counteracted by daily personal experience which did not confirm the threat, while vaccine safety was a major issue. This dissonance may have been amplified by having not involved primary care physicians in the mass vaccination campaign.
doi:10.1371/journal.pone.0010199
PMCID: PMC2856629  PMID: 20421908
11.  Efficacy of Pneumococcal Nontypable Haemophilus influenzae Protein D Conjugate Vaccine (PHiD-CV) in Young Latin American Children: A Double-Blind Randomized Controlled Trial 
PLoS Medicine  2014;11(6):e1001657.
In a double-blind randomized controlled trial, Xavier Saez-Llorens and colleagues examine the vaccine efficacy of PHiD-CV against community-acquired pneumonia in young children in Panama, Argentina, and Columbia.
Please see later in the article for the Editors' Summary
Background
The relationship between pneumococcal conjugate vaccine–induced antibody responses and protection against community-acquired pneumonia (CAP) and acute otitis media (AOM) is unclear. This study assessed the impact of the ten-valent pneumococcal nontypable Haemophilus influenzae protein D conjugate vaccine (PHiD-CV) on these end points. The primary objective was to demonstrate vaccine efficacy (VE) in a per-protocol analysis against likely bacterial CAP (B-CAP: radiologically confirmed CAP with alveolar consolidation/pleural effusion on chest X-ray, or non-alveolar infiltrates and C-reactive protein ≥ 40 µg/ml); other protocol-specified outcomes were also assessed.
Methods and Findings
This phase III double-blind randomized controlled study was conducted between 28 June 2007 and 28 July 2011 in Argentine, Panamanian, and Colombian populations with good access to health care. Approximately 24,000 infants received PHiD-CV or hepatitis control vaccine (hepatitis B for primary vaccination, hepatitis A at booster) at 2, 4, 6, and 15–18 mo of age. Interim analysis of the primary end point was planned when 535 first B-CAP episodes, occurring ≥2 wk after dose 3, were identified in the per-protocol cohort. After a mean follow-up of 23 mo (PHiD-CV, n = 10,295; control, n = 10,201), per-protocol VE was 22.0% (95% CI: 7.7, 34.2; one-sided p = 0.002) against B-CAP (conclusive for primary objective) and 25.7% (95% CI: 8.4%, 39.6%) against World Health Organization–defined consolidated CAP. Intent-to-treat VE was 18.2% (95% CI: 5.5%, 29.1%) against B-CAP and 23.4% (95% CI: 8.8%, 35.7%) against consolidated CAP. End-of-study per-protocol analyses were performed after a mean follow-up of 28–30 mo for CAP and invasive pneumococcal disease (IPD) (PHiD-CV, n = 10,211; control, n = 10,140) and AOM (n = 3,010 and 2,979, respectively). Per-protocol VE was 16.1% (95% CI: −1.1%, 30.4%; one-sided p = 0.032) against clinically confirmed AOM, 67.1% (95% CI: 17.0%, 86.9%) against vaccine serotype clinically confirmed AOM, 100% (95% CI: 74.3%, 100%) against vaccine serotype IPD, and 65.0% (95% CI: 11.1%, 86.2%) against any IPD. Results were consistent between intent-to-treat and per-protocol analyses. Serious adverse events were reported for 21.5% (95% CI: 20.7%, 22.2%) and 22.6% (95% CI: 21.9%, 23.4%) of PHiD-CV and control recipients, respectively. There were 19 deaths (n = 11,798; 0.16%) in the PHiD-CV group and 26 deaths (n = 11,799; 0.22%) in the control group. A significant study limitation was the lower than expected number of captured AOM cases.
Conclusions
Efficacy was demonstrated against a broad range of pneumococcal diseases commonly encountered in young children in clinical practice.
Trial registration
www.ClinicalTrials.gov NCT00466947
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Pneumococcal diseases are illnesses caused by Streptococcus pneumoniae bacteria, pathogens (disease-causing organisms) that are transmitted through contact with infected respiratory secretions. S. pneumoniae causes mucosal diseases–infections of the lining of the body cavities that are connected to the outside world–such as community-acquired pneumonia (CAP; lung infection) and acute otitis media (AOM; middle-ear infection). It also causes invasive pneumococcal diseases (IPDs) such as septicemia and meningitis (infections of the bloodstream and the covering of the brain, respectively). Although pneumococcal diseases can sometimes be treated with antibiotics, CAP and IPDs are leading global causes of childhood deaths, particularly in developing countries. It is best therefore to avoid S. pneumoniae infections through vaccination. Vaccination primes the immune system to recognize and attack pathogens rapidly and effectively by exposing it to weakened or dead pathogens or to pathogen molecules that it recognizes as foreign (antigens). Because there are more than 90 S. pneumoniae variants (“serotypes”), each characterized by a different antigenic polysaccharide (complex sugar) coat, S. pneumoniae vaccines have to include antigens from multiple serotypes. For example, the PHiD-CV vaccine contains polysaccharides from ten S. pneumoniae serotypes.
Why Was This Study Done?
Although in most countries PHiD-CV has been licensed for protection against IPD and pneumococcal AOM, at the time of study, it was not known how well it protected against CAP and overall AOM, which are important public health problems. In this double-blind randomized controlled trial (the Clinical Otitis Media and Pneumonia Study; COMPAS), the researchers investigate the efficacy of PHiD-CV against CAP and AOM and assess other clinical end points, such as IPD, in Latin American infants. Double-blind randomized controlled trials compare the effects of interventions by assigning study participants to different interventions randomly and measuring predefined outcomes without the study participants or researchers knowing who has received which intervention until the trial is completed. Vaccine efficacy is the reduction in the incidence of a disease (the number of new cases that occur in a population in a given time) among trial participants who receive the vaccine compared to the incidence among participants who do not receive the vaccine.
What Did the Researchers Do and Find?
The researchers enrolled around 24,000 infants living in urban areas of Argentina, Panama, and Colombia. Half the infants were given PHiD-CV at 2, 4, and 6 months of age and a booster dose at age 15–18 months. The remaining infants were given a hepatitis control vaccine at the same intervals. The trial's primary end point was likely bacterial CAP (B-CAP) –radiologically confirmed CAP, with the airspaces (alveoli) in the lungs filled with liquid instead of gas (alveolar consolidation) or with non-alveolar infiltrates and raised blood levels of C-reactive protein (a marker of inflammation). In a planned interim analysis, which was undertaken after an average follow-up of 23 months, the vaccine efficacy in the per-protocol cohort (the group of participants who actually received their assigned intervention) was 22% against B-CAP. Intent-to-treat vaccine efficacy in the interim analysis (which considered all the trial participants regardless of whether they received their assigned intervention) was 18.2%. At the end of the study (average follow up 30 months), the vaccine efficacy against B-CAP was 18.2% and 16.7% in the per-protocol and intent-to-treat cohorts, respectively. Per-protocol vaccine efficacies against clinically confirmed AOM and vaccine serotype AOM were 16.1% and 67.1%, respectively. Against any IPD and against vaccine serotype IPD, the respective vaccine efficacies were 65% and 100%. Finally, about one-fifth of children who received PHiD-CV and a similar proportion who received the control vaccine experienced a serious adverse event (for example, gastroenteritis); 19 children who received PHiD-CV died compared to 26 children who received the control vaccine.
What Do These Findings Mean?
These findings indicate that in Latin America, a region with an intermediate burden of pneumococcal disease, PHiD-CV is efficacious against a broad range of pneumococcal diseases that often affect young children. The accuracy of these findings may be limited by the withdrawal of 14% of participants from the trial because of adverse media coverage and by the low number of reported cases of AOM. Moreover, because most study participants lived in urban areas, these findings may not be generalizable to rural settings. Despite these and other study limitations, these findings provide new information about the magnitude of the effect of PHiD-CV vaccination against CAP and AOM, two mucosal pneumococcal diseases of global public health importance.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001657.
The US Centers for Disease Control and Prevention provides information for patients and health professionals on all aspects of pneumococcal disease and pneumococcal vaccination, including personal stories
Public Health England provides information on pneumococcal disease and on pneumococcal vaccines
The not-for-profit Immunization Action Coalition has information on pneumococcal disease, including personal stories
The GAVI Alliance provides information about pneumococcal disease and the importance of vaccination
MedlinePlus has links to further information about pneumococcal infections, including pneumonia and otitis media (in English and Spanish)
More information about COMPAS is available
The European Medicines Agency provides information about PHiD-CV (Synflorix)
doi:10.1371/journal.pmed.1001657
PMCID: PMC4043495  PMID: 24892763
12.  Vaccinating to Protect a Vulnerable Subpopulation 
PLoS Medicine  2007;4(5):e174.
Background
Epidemic influenza causes serious mortality and morbidity in temperate countries each winter. Research suggests that schoolchildren are critical in the spread of influenza virus, while the elderly and the very young are most vulnerable to the disease. Under these conditions, it is unclear how best to focus prevention efforts in order to protect the population. Here we investigate the question of how to protect a population against a disease when one group is particularly effective at spreading disease and another group is more vulnerable to the effects of the disease.
Methods and Findings
We developed a simple mathematical model of an epidemic that includes assortative mixing between groups of hosts. We evaluate the impact of different vaccine allocation strategies across a wide range of parameter values. With this model we demonstrate that the optimal vaccination strategy is extremely sensitive to the assortativity of population mixing, as well as to the reproductive number of the disease in each group. Small differences in parameter values can change the best vaccination strategy from one focused on the most vulnerable individuals to one focused on the most transmissive individuals.
Conclusions
Given the limited amount of information about relevant parameters, we suggest that changes in vaccination strategy, while potentially promising, should be approached with caution. In particular, we find that, while switching vaccine to more active groups may protect vulnerable groups in many cases, switching too much vaccine, or switching vaccine under slightly different conditions, may lead to large increases in disease in the vulnerable group. This outcome is more likely when vaccine limitation is stringent, when mixing is highly structured, or when transmission levels are high.
Jonathan Dushoff and colleagues model the benefits of different vaccination strategies and suggest that small differences in how populations mix can change the best vaccination strategy from one focused on the most vulnerable individuals to one focused on the most transmissive individuals.
Editors' Summary
Background.
Every winter, millions of people take to their beds with influenza—a viral infection of the nose, throat, and airways that is transmitted in airborne droplets released by coughing and sneezing. Most people who catch flu recover within a few days, but some develop serious complications such as pneumonia, and in the US alone, about 36,000 people—mainly infants, elderly, and chronically ill individuals—die every year. To minimize the morbidity (illness) and mortality (death) associated with seasonal (epidemic) influenza, the World Health Organization recommends that these vulnerable people be vaccinated against influenza every autumn. Annual vaccination is necessary because flu viruses continually make small changes to the viral proteins that the immune system recognizes.
Why Was This Study Done?
Although infants and the elderly are particularly vulnerable to influenza, schoolchildren are more likely to spread the flu virus. Also, vaccination is more effective in schoolchildren than in elderly people. So could vaccination of schoolchildren be the best way to reduce influenza morbidity and mortality? Some Japanese and US data suggest that it might be, but policymakers need to know more about the likely effects of changing the current influenza vaccination strategy. They need to know in what circumstances the direct effects of vaccination (protection of vaccinated individuals from disease) outweigh its indirect effects (reduced infection in vulnerable individuals caused by the reduced spread of disease in the whole population) and when the opposite is true. In this study, the researchers have used mathematical modeling to investigate how vaccination affects the spread of diseases such as influenza for which a “core” group in the population spreads the disease and a distinct “vulnerable” group is sensitive to its effects.
What Did the Researchers Do and Find?
The researchers developed a mathematical model in which members of each group mixed mainly with their own group (assortative mixing) and used it to predict how changing the proportion of a limited amount of vaccine given to each group might affect disease spread under different conditions. For example, they report that in a population in which the two groups were very unlikely to mix and viral transmission was low, switching vaccine from the vulnerable group to the core group initially increased infections in the vulnerable group because fewer individuals were directly protected but, as more vaccine was allocated to the core group, fewer vulnerable people became infected because the size of the epidemic decreased. When viral transmission was high, vaccination of the vulnerable group was always best. However, when viral transmission was moderate, shifting vaccine from the vulnerable group first increased, then decreased infections in this group before increasing them again. This last change occurred when vaccination in the vulnerable group was so low that viral transmission was sufficient to maintain the epidemic within this group.
What Do These Findings Mean?
As with all mathematical modeling, the researchers' findings depend on the assumptions included in the model, many of which are based on limited information. The model also considers a population that contains only two groups, an unlikely situation in real life. Nevertheless, these findings indicate that in a population in which one group of people is mainly responsible for the spread of a disease and another is most vulnerable to its effects, the best vaccination strategy is very sensitive to how the groups mix and how well the disease spreads in each group. Small changes in these poorly understood parameters can change the optimal vaccination strategy from one that vaccinates vulnerable individuals to one that mainly vaccinates the people who spread the disease. Importantly, a beneficial change in strategy can become deleterious if taken too far, so policy makers need to approach potentially promising changes in vaccination policy cautiously. Finally, for influenza, the model supports the idea that using some vaccine stocks in schoolchildren might decrease morbidity and mortality among elderly people but suggests that—even if this turns out to be correct—if all the vaccine were given to schoolchildren, more old people might die. Thus, the most prudent policy would be to supplement rather than replace vaccination of the elderly with vaccination of children.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040174.
US Centers for Disease Control and Prevention provide information about influenza for patients and professionals, including key facts about the flu vaccine (in English and Spanish)
World Health Organization, fact sheet on influenza and information on vaccination (in English, Spanish, French, Arabic, Chinese and Russian)
UK Health Protection Agency, information on seasonal influenza
MedlinePlus encyclopedia entries on influenza and the influenza vaccine (in English and Spanish)
Public disease mortality and morbidity data at the International Infectious Disease Data Archive (IIDDA)
doi:10.1371/journal.pmed.0040174
PMCID: PMC1872043  PMID: 17518515
13.  Anger as a Moderator of Safer Sex Motivation among Low Income Urban Women 
Journal of behavioral medicine  2005;28(5):493-506.
Theoretical models suggest that both HIV knowledge and HIV risk perception inform rational decision-making and, thus, predict safer sex motivation and behavior. However, the amount of variance explained by knowledge and risk perception is typically small. In this cross-sectional study, we investigated whether the predictive power of HIV knowledge and HIV risk perception on safer sex motivation is affected by trait anger. We hypothesized that anger may disrupt rational-decision making, distorting the effects of both HIV knowledge and risk perception on safer sex intentions. Data from 232 low-income, urban women at risk for HIV infection were used to test a path model with past sexual risk behavior, HIV knowledge, and HIV risk perception as predictors of safer sex intentions. Moderator effects of anger on safer sex intentions were tested by simultaneous group comparisons between high-anger and low-anger women (median-split). The theoretically expected “rational pattern” was found among low-anger women only, including (a) a positive effect of knowledge on safer sex intentions, and (b) buffer (inhibitor) effects of HIV knowledge and HIV risk perception on the negative path leading from past risk behavior to safer sex intentions. Among high-anger women, an “irrational pattern” emerged, with no effects of HIV knowledge and negative effects of both past risk behavior and HIV risk perception on safer sex intentions. In sum, the results suggest that rational knowledge and risk-based decisions regarding safer sex may be limited to low-anger women.
doi:10.1007/s10865-005-9014-7
PMCID: PMC1383506  PMID: 16247592
HIV; knowledge; anger; safer sex; intention; risk perception
14.  Association between the 2008–09 Seasonal Influenza Vaccine and Pandemic H1N1 Illness during Spring–Summer 2009: Four Observational Studies from Canada 
PLoS Medicine  2010;7(4):e1000258.
In three case-control studies and a household transmission cohort, Danuta Skowronski and colleagues find an association between prior seasonal flu vaccination and increased risk of 2009 pandemic H1N1 flu.
Background
In late spring 2009, concern was raised in Canada that prior vaccination with the 2008–09 trivalent inactivated influenza vaccine (TIV) was associated with increased risk of pandemic influenza A (H1N1) (pH1N1) illness. Several epidemiologic investigations were conducted through the summer to assess this putative association.
Methods and Findings
Studies included: (1) test-negative case-control design based on Canada's sentinel vaccine effectiveness monitoring system in British Columbia, Alberta, Ontario, and Quebec; (2) conventional case-control design using population controls in Quebec; (3) test-negative case-control design in Ontario; and (4) prospective household transmission (cohort) study in Quebec. Logistic regression was used to estimate odds ratios for TIV effect on community- or hospital-based laboratory-confirmed seasonal or pH1N1 influenza cases compared to controls with restriction, stratification, and adjustment for covariates including combinations of age, sex, comorbidity, timeliness of medical visit, prior physician visits, and/or health care worker (HCW) status. For the prospective study risk ratios were computed. Based on the sentinel study of 672 cases and 857 controls, 2008–09 TIV was associated with statistically significant protection against seasonal influenza (odds ratio 0.44, 95% CI 0.33–0.59). In contrast, estimates from the sentinel and three other observational studies, involving a total of 1,226 laboratory-confirmed pH1N1 cases and 1,505 controls, indicated that prior receipt of 2008–09 TIV was associated with increased risk of medically attended pH1N1 illness during the spring–summer 2009, with estimated risk or odds ratios ranging from 1.4 to 2.5. Risk of pH1N1 hospitalization was not further increased among vaccinated people when comparing hospitalized to community cases.
Conclusions
Prior receipt of 2008–09 TIV was associated with increased risk of medically attended pH1N1 illness during the spring–summer 2009 in Canada. The occurrence of bias (selection, information) or confounding cannot be ruled out. Further experimental and epidemiological assessment is warranted. Possible biological mechanisms and immunoepidemiologic implications are considered.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every winter, millions of people catch influenza—a viral infection of the airways—and hundreds of thousands of people die as a result. These seasonal epidemics occur because small but frequent changes in the influenza virus mean that an immune response produced one year through infection or vaccination provides only partial protection against influenza the next year. Annual vaccination with killed influenza viruses of the major circulating strains can greatly reduce a person's risk of catching influenza. Consequently, many countries run seasonal influenza vaccination programs. In most of Canada, vaccination with a mixture of three inactivated viruses (a trivalent inactivated vaccine or TIV) is provided free to children aged 6–23 months, to elderly people, to people with long-term conditions that increase their risk of influenza-related complications, and those who provide care for them; in Ontario, free vaccination is offered to everyone older than 6 months.
In addition, influenza viruses occasionally emerge that are very different and to which human populations have virtually no immunity. These viruses can start global epidemics (pandemics) that can kill millions of people. Experts have been warning for some time that an influenza pandemic is long overdue and, in March 2009, the first cases of influenza caused by a new virus called pandemic A/H1N1 2009 (pH1N1; swine flu) occurred in Mexico. The virus spread rapidly and on 11 June 2009, the World Health Organization declared that a global pandemic of pH1N1 influenza was underway. By the end of February 2010, more than 16,000 people around the world had died from pH1N1.
Why Was This Study Done?
During an investigation of a school outbreak of pH1N1 in the late spring 2009 in Canada, investigators noted that people with illness characterized by fever and coughing had been vaccinated against seasonal influenza more often than individuals without such illness. To assess whether this association between prior vaccination with seasonal 2008–09 TIV and subsequent pH1N1 illness was evident in other settings, researchers in Canada therefore conducted additional studies using different methods. In this paper, the researchers report the results of four additional studies conducted in Canada during the summer of 2009 to assess this possible association.
What Did the Researchers Do and Find?
The researchers conducted four epidemiologic studies. Epidemiology is the study of the causes, distribution, and control of diseases in populations.
Three of the four studies were case-control studies in which the researchers assessed the frequency of prior vaccination with the 2008–09 TIV in people with pH1N1 influenza compared to the frequency among healthy members of the general population or among individuals who had an influenza-like illness but no sign of infection with an influenza virus. The researchers also did a household transmission study in which they collected information about vaccination with TIV among the additional cases of influenza that were identified in 47 households in which a case of laboratory-confirmed pH1N1 influenza had occurred. The first of the case-control studies, which was based on Canada's vaccine effectiveness monitoring system, showed that, as expected, the 2008–09 TIV provided protection against seasonal influenza. However, estimates from all four studies (which included about 1,200 laboratory-confirmed pH1N1 cases and 1,500 controls) showed that prior recipients of the 2008–09 TIV had approximately 1.4–2.5 times increased chances of developing pH1N1 illness that needed medical attention during the spring–summer of 2009 compared to people who had not received the TIV. Prior seasonal vaccination was not associated with an increase in the severity of pH1N1 illness, however. That is, it did not increase the risk of being hospitalized among those with pH1N1 illness.
What Do These Findings Mean?
Because all the investigations in this study are “observational,” the people who had been vaccinated might share another unknown characteristic that is actually responsible for increasing their risk of developing pH1N1 illness (“confounding”). Furthermore, the results reported in this study might have arisen by chance, although the consistency of results across the studies makes this unlikely. Thus, the finding of an association between prior receipt of 2008–09 TIV and an increased risk of pH1N1 illness is not conclusive and needs to be investigated further, particularly since some other observational studies conducted in other countries have reported that seasonal vaccination had no influence or may have been associated with reduced chances of pH1N1 illness. If the findings in the current study are real, however, they raise important questions about the biological interactions between seasonal and pandemic influenza strains and vaccines, and about the best way to prevent and control both types of influenza in future.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/ 10.1371/journal.pmed.1000258.
This article is further discussed in a PLoS Medicine Perspective by Cécile Viboud and Lone Simonsen
FightFlu.ca, a Canadian government Web site, provides access to information on pH1N1 influenza
The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including specific information on H1N1 influenza
Flu.gov, a US government website, provides access to information on H1N1, avian and pandemic influenza
The World Health Organization provides information on seasonal influenza and has detailed information on pH1N1 influenza (in several languages)
The UK Health Protection Agency provides information on pandemic influenza and on pH1N1 influenza
doi:10.1371/journal.pmed.1000258
PMCID: PMC2850386  PMID: 20386731
15.  Action planning as predictor of health protective and health risk behavior: an investigation of fruit and snack consumption 
Background
Large discrepancies between people's intention to eat a healthy diet and actual dietary behavior indicate that motivation is not a sufficient instigator for healthy behavior. Research efforts to decrease this 'intention - behavior gap' have centered on aspects of self-regulation, most importantly self-regulatory planning. Most studies on the impact of self-regulatory planning in health and dietary behavior focus on the promotion of health protective behaviors. This study investigates and compares the predictive value of action planning in health protective behavior and the restriction of health risk behavior.
Methods
Two longitudinal observational studies were performed simultaneously, one focusing on fruit consumption (N = 572) and one on high-caloric snack consumption (N = 585) in Dutch adults. Structural equation modeling was used to investigate and compare the predictive value of action planning in both behaviors, correcting for demographics and the influence of motivational factors and past behavior. The nature of the influence of action planning was investigated by testing mediating and moderating effects.
Results
Action planning was a significant predictor of fruit consumption and restricted snack consumption beyond the influence of motivational factors and past behavior. The strength of the predictive value of action planning did not differ between the two behaviors. Evidence for mediation of the intention - behavior relationship was found for both behaviors. Positive moderating effects of action planning were demonstrated for fruit consumption, indicating that individuals who report high levels of action planning are significantly more likely to translate their intentions into actual behavior.
Conclusion
The results indicate that the planning of specific preparatory actions predicts the performance of healthy dietary behavior and support the application of self-regulatory planning in both health protective and health risk behaviors. Future interventions in dietary modification may turn these findings to advantage by incorporating one common planning protocol to increase the likelihood that good intentions are translated into healthy dietary behavior.
doi:10.1186/1479-5868-6-69
PMCID: PMC2770554  PMID: 19825172
16.  Characterization of Regional Influenza Seasonality Patterns in China and Implications for Vaccination Strategies: Spatio-Temporal Modeling of Surveillance Data 
PLoS Medicine  2013;10(11):e1001552.
Cécile Viboud and colleagues describe epidemiological patterns of influenza incidence across China to support the design of a national vaccination program.
Please see later in the article for the Editors' Summary
Background
The complexity of influenza seasonal patterns in the inter-tropical zone impedes the establishment of effective routine immunization programs. China is a climatologically and economically diverse country, which has yet to establish a national influenza vaccination program. Here we characterize the diversity of influenza seasonality in China and make recommendations to guide future vaccination programs.
Methods and Findings
We compiled weekly reports of laboratory-confirmed influenza A and B infections from sentinel hospitals in cities representing 30 Chinese provinces, 2005–2011, and data on population demographics, mobility patterns, socio-economic, and climate factors. We applied linear regression models with harmonic terms to estimate influenza seasonal characteristics, including the amplitude of annual and semi-annual periodicities, their ratio, and peak timing. Hierarchical Bayesian modeling and hierarchical clustering were used to identify predictors of influenza seasonal characteristics and define epidemiologically-relevant regions. The annual periodicity of influenza A epidemics increased with latitude (mean amplitude of annual cycle standardized by mean incidence, 140% [95% CI 128%–151%] in the north versus 37% [95% CI 27%–47%] in the south, p<0.0001). Epidemics peaked in January–February in Northern China (latitude ≥33°N) and April–June in southernmost regions (latitude <27°N). Provinces at intermediate latitudes experienced dominant semi-annual influenza A periodicity with peaks in January–February and June–August (periodicity ratio >0.6 in provinces located within 27.4°N–31.3°N, slope of latitudinal gradient with latitude −0.016 [95% CI −0.025 to −0.008], p<0.001). In contrast, influenza B activity predominated in colder months throughout most of China. Climate factors were the strongest predictors of influenza seasonality, including minimum temperature, hours of sunshine, and maximum rainfall. Our main study limitations include a short surveillance period and sparse influenza sampling in some of the southern provinces.
Conclusions
Regional-specific influenza vaccination strategies would be optimal in China; in particular, annual campaigns should be initiated 4–6 months apart in Northern and Southern China. Influenza surveillance should be strengthened in mid-latitude provinces, given the complexity of seasonal patterns in this region. More broadly, our findings are consistent with the role of climatic factors on influenza transmission dynamics.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every year, millions of people worldwide catch influenza, a viral disease of the airways. Most infected individuals recover quickly but seasonal influenza outbreaks (epidemics) kill about half a million people annually. These epidemics occur because antigenic drift—frequent small changes in the viral proteins to which the immune system responds—means that an immune response produced one year provides only partial protection against influenza the next year. Annual vaccination with a mixture of killed influenza viruses of the major circulating strains boosts this natural immunity and greatly reduces the risk of catching influenza. Consequently, many countries run seasonal influenza vaccination programs. Because the immune response induced by vaccination decays within 4–8 months of vaccination and because of antigenic drift, it is important that these programs are initiated only a few weeks before the onset of local influenza activity. Thus, vaccination starts in early autumn in temperate zones (regions of the world that have a mild climate, part way between a tropical and a polar climate), because seasonal influenza outbreaks occur in the winter months when low humidity and low temperatures favor the transmission of the influenza virus.
Why Was This Study Done?
Unlike temperate regions, seasonal influenza patterns are very diverse in tropical countries, which lie between latitudes 23.5°N and 23.5°S, and in the subtropical countries slightly north and south of these latitudes. In some of these countries, there is year-round influenza activity, in others influenza epidemics occur annually or semi-annually (twice yearly). This complexity, which is perhaps driven by rainfall fluctuations, complicates the establishment of effective routine immunization programs in tropical and subtropical countries. Take China as an example. Before a national influenza vaccination program can be established in this large, climatologically diverse country, public-health experts need a clear picture of influenza seasonality across the country. Here, the researchers use spatio-temporal modeling of influenza surveillance data to characterize the seasonality of influenza A and B (the two types of influenza that usually cause epidemics) in China, to assess the role of putative drivers of seasonality, and to identify broad epidemiological regions (areas with specific patterns of disease) that could be used as a basis to optimize the timing of future Chinese vaccination programs.
What Did the Researchers Do and Find?
The researchers collected together the weekly reports of laboratory-confirmed influenza prepared by the Chinese national sentinel hospital-based surveillance network between 2005 and 2011, data on population size and density, mobility patterns, and socio-economic factors, and daily meteorological data for the cities participating in the surveillance network. They then used various statistical modeling approaches to estimate influenza seasonal characteristics, to assess predictors of influenza seasonal characteristics, and to identify epidemiologically relevant regions. These analyses indicate that, over the study period, northern provinces (latitudes greater than 33°N) experienced winter epidemics of influenza A in January–February, southern provinces (latitudes less than 27°N) experienced peak viral activity in the spring (April–June), and provinces at intermediate latitudes experienced semi-annual epidemic cycles with infection peaks in January–February and June–August. By contrast, influenza B activity predominated in the colder months throughout China. The researchers also report that minimum temperatures, hours of sunshine, and maximum rainfall were the strongest predictors of influenza seasonality.
What Do These Findings Mean?
These findings show that influenza seasonality in China varies between regions and between influenza virus types and suggest that, as in other settings, some of these variations might be associated with specific climatic factors. The accuracy of these findings is limited by the short surveillance period, by sparse surveillance data from some southern and mid-latitude provinces, and by some aspects of the modeling approach used in the study. Further surveillance studies need to be undertaken to confirm influenza seasonality patterns in China. Overall, these findings suggest that, to optimize routine influenza vaccination in China, it will be necessary to stagger the timing of vaccination over three broad geographical regions. More generally, given that there is growing interest in rolling out national influenza immunization programs in low- and middle-income countries, these findings highlight the importance of ensuring that vaccination strategies are optimized by taking into account local disease patterns.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/ 10.1371/journal.pmed.1001552.
This study is further discussed in a PLOS Medicine Perspective by Steven Riley
The UK National Health Service Choices website provides information for patients about seasonal influenza and about influenza vaccination
The World Health Organization provides information on seasonal influenza (in several languages) and on influenza surveillance and monitoring
The US Centers for Disease Control and Prevention also provides information for patients and health professionals on all aspects of seasonal influenza, including information about vaccination; its website contains a short video about personal experiences of influenza.
Flu.gov, a US government website, provides access to information on seasonal influenza and vaccination
Information about the Chinese National Influenza Center, which is part of the Chinese Center for Disease Control and Prevention: and which runs influenza surveillance in China, is available (in English and Chinese)
MedlinePlus has links to further information about influenza and about vaccination (in English and Spanish)
A recent PLOS Pathogens Research Article by James D. Tamerius et al. investigates environmental predictors of seasonal influenza epidemics across temperate and tropical climates
A study published in PLOS ONE by Wyller Alencar de Mello et al. indicates that Brazil, like China, requires staggered timing of vaccination from Northern to Southern states to account for different timings of influenza activity.
doi:10.1371/journal.pmed.1001552
PMCID: PMC3864611  PMID: 24348203
17.  Determinants of adults' intention to vaccinate against pandemic swine flu 
BMC Public Health  2011;11:15.
Background
Vaccination is one of the cornerstones of controlling an influenza pandemic. To optimise vaccination rates in the general population, ways of identifying determinants that influence decisions to have or not to have a vaccination need to be understood. Therefore, this study aimed to predict intention to have a swine influenza vaccination in an adult population in the UK. An extension of the Theory of Planned Behaviour provided the theoretical framework for the study.
Methods
Three hundred and sixty two adults from the UK, who were not in vaccination priority groups, completed either an online (n = 306) or pen and paper (n = 56) questionnaire. Data were collected from 30th October 2009, just after swine flu vaccination became available in the UK, and concluded on 31st December 2009. The main outcome of interest was future swine flu vaccination intentions.
Results
The extended Theory of Planned Behaviour predicted 60% of adults' intention to have a swine flu vaccination with attitude, subjective norm, perceived control, anticipating feelings of regret (the impact of missing a vaccination opportunity), intention to have a seasonal vaccine this year, one perceived barrier: "I cannot be bothered to get a swine flu vaccination" and two perceived benefits: "vaccination decreases my chance of getting swine flu or its complications" and "if I get vaccinated for swine flu, I will decrease the frequency of having to consult my doctor," being significant predictors of intention. Black British were less likely to intend to have a vaccination compared to Asian or White respondents.
Conclusions
Theoretical frameworks which identify determinants that influence decisions to have a pandemic influenza vaccination are useful. The implications of this research are discussed with a view to maximising any future pandemic influenza vaccination uptake using theoretically-driven applications.
doi:10.1186/1471-2458-11-15
PMCID: PMC3024930  PMID: 21211000
18.  Factors Associated With H1N1 Influenza Vaccine Receipt in a High-Risk Population During the 2009-2010 H1N1 Influenza Pandemic 
Background:
Persons with spinal cord injuries and disorders (SCI/D) are at high risk for respiratory complications from influenza. During pandemic situations, where resources may be scarce, uncertainties may arise in veterans with SCI/D.
Objective:
To describe concerns, knowledge, and perceptions of information received during the 2009-2010 H1N1 influenza pandemic and to examine variables associated with H1N1 vaccine receipt.
Methods:
In August 2010, a cross-sectional survey was mailed to a national sample of veterans with traumatic and nontraumatic SCI/D.
Results:
During the pandemic, 58% of veterans with SCI/D received the H1N1 vaccine. Less than two-thirds of non-H1N1 vaccine recipients indicated intentions to get the next season’s influenza vaccine. Being ≥50 years of age and depressed were significantly associated with higher odds of H1N1 vaccination. Being worried about vaccine side effects was associated with lower odds of H1N1 receipt. Compared to individuals who reported receiving an adequate amount of information about the pandemic, those who received too little information had significantly lower odds of receiving the H1N1 vaccine. Those who received accurate/clear information (vs confusing/conflicting) had 2 times greater odds of H1N1 vaccine receipt.
Conclusions:
H1N1 influenza vaccination was low in veterans with SCI/D. Of H1N1 vaccine nonrecipients, only 63% intend to get a seasonal vaccine next season. Providing an adequate amount of accurate and clear information is vital during uncertain times, as was demonstrated by the positive associations with H1N1 vaccination. Information-sharing efforts are needed, so that carry-over effects from the pandemic do not avert future healthy infection prevention behaviors.
doi:10.1310/sci1804-306
PMCID: PMC3584783  PMID: 23459437
H1N1 virus; infection control; influenza; pandemics; vaccination; veterans
19.  Intent to Receive Pandemic Influenza A (H1N1) Vaccine, Compliance with Social Distancing and Sources of Information in NC, 2009 
PLoS ONE  2010;5(6):e11226.
Background
Public adherence to influenza vaccination recommendations has been low, particularly among younger adults and children under 2, despite the availability of safe and effective seasonal vaccine. Intention to receive 2009 pandemic influenza A (H1N1) vaccine has been estimated to be 50% in select populations. This report measures knowledge of and intention to receive pandemic vaccine in a population-based setting, including target groups for seasonal and H1N1 influenza.
Methodology and Principal Findings
On August 28–29, 2009, we conducted a population-based survey in 2 counties in North Carolina. The survey used the 30×7 two-stage cluster sampling methodology to identify 210 target households. Prevalence ratios (PR) and 95% confidence intervals (CI) were estimated. Knowledge of pandemic influenza A (H1N1) vaccine was high, with 165 (80%) aware that a vaccine was being prepared. A total of 133 (64%) respondents intended to receive pandemic vaccine, 134 (64%) intended to receive seasonal vaccine, and 109 (53%) intended to receive both. Reporting great concern about H1N1 infection (PR 1.55; 95%CI: 1.30, 1.85), receiving seasonal influenza vaccine in 2008–09 (PR 1.47; 95%CI: 1.18, 1.82), and intending to receive seasonal influenza vaccine in 2009–10 (PR 1.27; 95%CI: 1.14, 1.42) were associated with intention to receive pandemic vaccine. Not associated were knowledge of vaccine, employment, having children under age 18, gender, race/ethnicity and age. Reasons cited for not intending to get vaccinated include not being at risk for infection, concerns about vaccine side effects and belief that illness caused by pandemic H1N1 would be mild. Forty-five percent of households with children under 18 and 65% of working adults reported ability to comply with self-isolation at home for 7–10 days if recommended by authorities.
Conclusions and Significance
This is the first report of a population based rapid assessment used to assess knowledge and intent to receive pandemic vaccine in a community sample. Intention to receive pandemic and seasonal vaccines was higher than previously published reports. To reach persons not intending to receive pandemic vaccine, public health communications should focus on the perceived risk of infection and concerns about vaccine safety.
doi:10.1371/journal.pone.0011226
PMCID: PMC2887902  PMID: 20585462
20.  Frequency of Adverse Events after Vaccination with Different Vaccinia Strains 
PLoS Medicine  2006;3(8):e272.
Background
Large quantities of smallpox vaccine have been stockpiled to protect entire nations against a possible reintroduction of smallpox. Planning for an appropriate use of these stockpiled vaccines in response to a smallpox outbreak requires a rational assessment of the risks of vaccination-related adverse events, compared to the risk of contracting an infection. Although considerable effort has been made to understand the dynamics of smallpox transmission in modern societies, little attention has been paid to estimating the frequency of adverse events due to smallpox vaccination. Studies exploring the consequences of smallpox vaccination strategies have commonly used a frequency of approximately one death per million vaccinations, which is based on a study of vaccination with the New York City Board of Health (NYCBH) strain of vaccinia virus. However, a multitude of historical studies of smallpox vaccination with other vaccinia strains suggest that there are strain-related differences in the frequency of adverse events after vaccination. Because many countries have stockpiled vaccine based on the Lister strain of vaccinia virus, a quantitative evaluation of the adverse effects of such vaccines is essential for emergency response planning. We conducted a systematic review and statistical analysis of historical data concerning vaccination against smallpox with different strains of vaccinia virus.
Methods and Findings
We analyzed historical vaccination data extracted from the literature. We extracted data on the frequency of postvaccinal encephalitis and death with respect to vaccinia strain and age of vaccinees. Using a hierarchical Bayesian approach for meta-analysis, we estimated the expected frequencies of postvaccinal encephalitis and death with respect to age at vaccination for smallpox vaccines based on the NYCBH and Lister vaccinia strains. We found large heterogeneity between findings from different studies and a time-period effect that showed decreasing incidences of adverse events over several decades. To estimate death rates, we then restricted our analysis to more-recent studies. We estimated that vaccination with the NYCBH strain leads to an average of 1.4 deaths per million vaccinations (95% credible interval, 0–6) and that vaccination with Lister vaccine leads to an average of 8.4 deaths per million vaccinations (95% credible interval, 0–31). We combined age-dependent estimates of the frequency of death after vaccination and revaccination with demographic data to obtain estimates of the expected number of deaths in present societies due to vaccination with the NYCBH and Lister vaccinia strains.
Conclusions
Previous analyses of smallpox vaccination policies, which rely on the commonly assumed value of one death per million vaccinations, may give serious underestimates of the number of deaths resulting from vaccination. Moreover, because there are large, strain-dependent differences in the frequency of adverse events due to smallpox vaccination, it is difficult to extrapolate from predictions for the NYCBH-derived vaccines (stockpiled in countries such as the US) to predictions for the Lister-derived vaccines (stockpiled in countries such as Germany). In planning for an effective response to a possible smallpox outbreak, public-health decision makers should reconsider their strategies of when to opt for ring vaccination and when to opt for mass vaccination.
Analysis of historical data for adverse events suggests that the commonly assumed number of one death per million vaccinations is inaccurate. Large differences between different vaccinia strains used should be taken into account when mass vaccinations are considered.
Editors' Summary
Background.
For thousands of years, smallpox was one of the world's most-feared diseases. This contagious disease, caused by the variola virus, historically killed about 30 percent of the people it infected. Over the centuries, it probably killed more people than all other infectious diseases combined, but it was also the first disease to be prevented by vaccination. In 1796, the English physician Edward Jenner rubbed pus from the spots of a milkmaid with cowpox into scratches on a young boy's arm; according to folklore, people who caught cowpox, a related but mild disease of cows, were protected against smallpox. Six weeks later, after a mild bout of cowpox, when the boy was challenged with pus from a smallpox patient, he did not develop smallpox. This vaccination procedure was later refined so that people were inoculated with pure preparations of live vaccinia virus, which is closely related to the smallpox and cowpox viruses, and by 1979 a global vaccination campaign had totally eradicated the disease.
Why Was This Study Done?
Smallpox vaccination has some adverse effects. In particular, vaccinia virus occasionally infects the brain. This so-called post-vaccination encephalitis can cause permanent brain damage and, it has been estimated, kills one vaccinee in every million. Consequently, as smallpox became rarer, the dangers of vaccination began to outweigh its benefits. Routine smallpox vaccination stopped in the US in 1972, and in 1980 the World Health Organization recommended that all countries stop vaccination. Now, however, there are fears that smallpox may be used for bioterrorism. If this did happen, exposed individuals and their contacts, possibly even whole populations, would have to be vaccinated as quickly as possible (very few people now have strong immunity to smallpox). Many countries have stockpiles of smallpox vaccines for this eventuality, but these contain different vaccinia virus strains. In this study, the researchers examined historical data to discover whether these strains differ in their potential to cause encephalitis and death. This information should help public-health officials plan their vaccination strategies in response to a bioterrorism attack with smallpox.
What Did the Researchers Do and Find?
The researchers collected data from published studies on smallpox vaccination and adverse events from several countries from the late 1950s onwards. They then used these data to extrapolate how often the different vaccinia strains might cause encephalitis and death if they were used today in vaccination programs. They estimate that vaccinating with the New York City Board of Health (NYCBH) strain, which is stockpiled in the US, might cause 2.9 cases of post-vaccination encephalitis and 1.4 deaths per million vaccinated individuals. In contrast, the Lister strain, which is stockpiled in many European countries, might cause 26.2 cases of post-vaccination encephalitis and 2.5 deaths per million vaccinees. For both strains, vaccination of children younger than 1 year old would cause the highest death rate, and individuals being re-vaccinated would be less likely to die than those being vaccinated for the first time. Finally, the researchers use their figures to estimate that about ten people would die if mass vaccination with the NYCBH strain were used in the Netherlands (population 16 million), whereas 55 people would die if the Lister strain were used.
What Do These Findings Mean?
The data used in this study are of variable quality, so the figures calculated by the researchers are only estimates. For instance, given the scatter of the original data, mass vaccination in the Netherlands with the Lister strain might cause anywhere between seven and nearly 200 deaths. However, the study clearly suggests that more serious adverse events would occur after vaccination with the Lister strain than after vaccination with the NYCBH strain. It also indicates that even in the US, where the NYCBH vaccine strain is stockpiled, previous analyses of the effects of vaccination in response to a bioterrorist attack have probably underestimated how many people might die from post-vaccination encephalitis. Public-health decision makers should incorporate these new estimates into their planning for a smallpox outbreak. These increased estimates of adverse events after vaccination might, for example, make mass vaccination with the Lister strain of vaccinia virus less acceptable. Instead, public-health officials might decide to rely on vaccination of only the people directly exposed to released smallpox virus and their close contacts (ring vaccination) to contain a smallpox outbreak.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0030272.
World Health Organization, information on smallpox and preparedness in the event of a smallpox outbreak
MedlinePlus encyclopedia entry on smallpox
US National Institute of Allergy and Infectious Diseases, patient fact sheet on smallpox
US Centers for Disease Control and Prevention, information for patients and professionals on smallpox
Wikipedia page on smallpox (note that Wikipedia is a free online encyclopedia that anyone can edit)
Wellcome Library MedHist, links to information on the history of smallpox vaccination
doi:10.1371/journal.pmed.0030272
PMCID: PMC1551910  PMID: 16933957
21.  Maternal Influenza Immunization and Reduced Likelihood of Prematurity and Small for Gestational Age Births: A Retrospective Cohort Study 
PLoS Medicine  2011;8(5):e1000441.
In an analysis of surveillance data from the state of Georgia (US), Saad Omer and colleagues show an association between receipt of influenza vaccination among pregnant women and reduced risk of premature births.
Background
Infections during pregnancy have the potential to adversely impact birth outcomes. We evaluated the association between receipt of inactivated influenza vaccine during pregnancy and prematurity and small for gestational age (SGA) births.
Methods and Findings
We conducted a cohort analysis of surveillance data from the Georgia (United States) Pregnancy Risk Assessment Monitoring System. Among 4,326 live births between 1 June 2004 and 30 September 2006, maternal influenza vaccine information was available for 4,168 (96.3%). The primary intervention evaluated in this study was receipt of influenza vaccine during any trimester of pregnancy. The main outcome measures were prematurity (gestational age at birth <37 wk) and SGA (birth weight <10th percentile for gestational age). Infants who were born during the putative influenza season (1 October–31 May) and whose mothers were vaccinated against influenza during pregnancy were less likely to be premature compared to infants of unvaccinated mothers born in the same period (adjusted odds ratio [OR] = 0.60; 95% CI, 0.38–0.94). The magnitude of association between maternal influenza vaccine receipt and reduced likelihood of prematurity increased during the period of at least local influenza activity (adjusted OR = 0.44; 95% CI, 0.26–0.73) and was greatest during the widespread influenza activity period (adjusted OR = 0.28; 95% CI, 0.11–0.74). Compared with newborns of unvaccinated women, newborns of vaccinated mothers had 69% lower odds of being SGA (adjusted OR = 0.31; 95% CI, 0.13–0.75) during the period of widespread influenza activity. The adjusted and unadjusted ORs were not significant for the pre-influenza activity period.
Conclusions
This study demonstrates an association between immunization with the inactivated influenza vaccine during pregnancy and reduced likelihood of prematurity during local, regional, and widespread influenza activity periods. However, no associations were found for the pre-influenza activity period. Moreover, during the period of widespread influenza activity there was an association between maternal receipt of influenza vaccine and reduced likelihood of SGA birth.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Maternal infections during pregnancy can have harmful effects on both mother and baby. For example, influenza is associated with increased morbidity and mortality among pregnant women compared to women who are not pregnant or who acquire influenza infection after delivery. And some respiratory infections, especially those that can cause maternal pneumonia such as influenza virus, are known to be associated with the baby being small—below the 10th percentile—for gestational age and with an increased risk of preterm birth—birth before 37 weeks of gestation. Previous studies have shown that inactivated influenza vaccination during pregnancy provides protection against influenza virus for both mother and baby. As there has been an increase in the rate of preterm birth the United States from 9.5% in 1981 to 12.8% in 2006, the impact of maternal influenza immunization on birth outcomes has important public health implications and is of particular interest during influenza pandemics.
Why Was This Study Done?
Given that maternal vaccination can protect babies from influenza virus, it is plausible that influenza vaccination in pregnancy could mitigate adverse birth outcomes such as prematurity and the baby being small for gestational age. The researchers of this study set out to evaluate this hypothesis by investigating whether there was an association between women receiving inactivated influenza vaccine during pregnancy and positive birth outcomes for their babies in the population of the state of Georgia, in the United States.
What Did the Researchers Do and Find?
The researchers conducted a retrospective cohort analysis of a large surveillance dataset (the Georgia Pregnancy Risk Assessment Monitoring System) to analyze the relationship between receipt of inactivated influenza vaccine during any trimester of pregnancy by mothers of infants born between June 1, 2004, and September 30, 2006, and their baby being premature or small for gestational age. The study period encompassed the 2004–2005 and 2005–2006 influenza seasons—the two most recent seasons for which the data were available. The researchers did a stratified analysis for the overall study period, and various periods during it, and also weighted their analysis to adjust for possible oversampling. They used logistic regression to evaluate the association of maternal influenza vaccine and (a) prematurity and (b) small for gestational age, and also used linear regression to evaluate the statistical significance of differences between vaccinated and unvaccinated women for mean gestational age at first antenatal visit and mean birth weight.
During the study period, 4,168 mother–baby pairs were included in the analysis. Local influenza activity was detected during 27 weeks (22.1%), and 578 women (14.9% [weighted]) had received the influenza vaccine during pregnancy, giving a vaccination coverage of 19.2% (weighted) among mothers of infants born during the assumed influenza season. In the study sample, 1,547 babies (10.6% [weighted]) were born premature, and 1,186 babies (11.2% [weighted]) were small for gestational age. Infants who were born during the assumed influenza season (October–May) and whose mothers were vaccinated against influenza during pregnancy were less likely to be premature than infants of unvaccinated mothers born in the same period, with an adjusted odds ratio of 0.60. The effect of maternal influenza vaccine on reducing prematurity was the highest for infants born during the period of widespread influenza activity, with 72% lower odds of prematurity in infants of vaccinated mothers than infants of unvaccinated mothers. Compared with newborns of unvaccinated women, babies of vaccinated mothers also had 69% lower odds of being small for gestational age during the period of widespread influenza activity, but the adjusted and unadjusted odd ratios were not significant for the pre-influenza activity period.
What Do These Findings Mean?
These results show that there was an association between maternal immunization with the inactivated influenza vaccine during pregnancy and reduced likelihood of prematurity during local, regional, and widespread influenza activity periods. In addition, during the period of widespread influenza activity there was an negative association between maternal receipt of influenza vaccine and small for gestational age birth.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000441.
More information about influenza vaccination during pregnancy is available from the World Health Organization and the UK National Health Service
More information about the Georgia Pregnancy Risk Assessment Monitoring System is also available
doi:10.1371/journal.pmed.1000441
PMCID: PMC3104979  PMID: 21655318
22.  Assessing Optimal Target Populations for Influenza Vaccination Programmes: An Evidence Synthesis and Modelling Study 
PLoS Medicine  2013;10(10):e1001527.
Marc Baguelin and colleagues use virological, clinical, epidemiological, and behavioral data to estimate how policies for influenza vaccination programs may be optimized in England and Wales.
Please see later in the article for the Editors' Summary
Background
Influenza vaccine policies that maximise health benefit through efficient use of limited resources are needed. Generally, influenza vaccination programmes have targeted individuals 65 y and over and those at risk, according to World Health Organization recommendations. We developed methods to synthesise the multiplicity of surveillance datasets in order to evaluate how changing target populations in the seasonal vaccination programme would affect infection rate and mortality.
Methods and Findings
Using a contemporary evidence-synthesis approach, we use virological, clinical, epidemiological, and behavioural data to develop an age- and risk-stratified transmission model that reproduces the strain-specific behaviour of influenza over 14 seasons in England and Wales, having accounted for the vaccination uptake over this period. We estimate the reduction in infections and deaths achieved by the historical programme compared with no vaccination, and the reduction had different policies been in place over the period. We find that the current programme has averted 0.39 (95% credible interval 0.34–0.45) infections per dose of vaccine and 1.74 (1.16–3.02) deaths per 1,000 doses. Targeting transmitters by extending the current programme to 5–16-y-old children would increase the efficiency of the total programme, resulting in an overall reduction of 0.70 (0.52–0.81) infections per dose and 1.95 (1.28–3.39) deaths per 1,000 doses. In comparison, choosing the next group most at risk (50–64-y-olds) would prevent only 0.43 (0.35–0.52) infections per dose and 1.77 (1.15–3.14) deaths per 1,000 doses.
Conclusions
This study proposes a framework to integrate influenza surveillance data into transmission models. Application to data from England and Wales confirms the role of children as key infection spreaders. The most efficient use of vaccine to reduce overall influenza morbidity and mortality is thus to target children in addition to older adults.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every winter, millions of people catch influenza, a viral infection of the airways. Most infected individuals recover quickly, but seasonal influenza outbreaks (epidemics) kill about half a million people annually. In countries with advanced health systems, these deaths occur mainly among elderly people and among individuals with long-term illnesses such as asthma and heart disease that increase the risk of complications occurring after influenza virus infection. Epidemics of influenza occur because small but frequent changes in the influenza virus mean that an immune response produced one year through infection provides only partial protection against influenza the following year. Annual immunization with a vaccine that contains killed influenza viruses of the major circulating strains can greatly reduce a person's risk of catching influenza by preparing the immune system to respond quickly when challenged by a live influenza virus. Consequently, many countries run seasonal influenza vaccination programs that, in line with World Health Organization recommendations, target individuals 65 years old and older and people in high-risk groups.
Why Was This Study Done?
Is this approach the best use of available resources? Might, for example, vaccination of children—the main transmitters of influenza—provide more benefit to the whole population than vaccination of elderly people? Vaccination of children would not directly prevent as many influenza-related deaths as vaccination of elderly people, but it might indirectly prevent deaths in elderly adults by inducing herd immunity—vaccination of a large part of a population can protect unvaccinated members of the population by reducing the chances of an infection spreading. Policy makers need to know whether a change to an influenza vaccination program is likely to provide additional population benefits before altering the program. In this evidence synthesis and modeling study, the researchers combine (synthesize) longitudinal influenza surveillance datasets (data collected over time) from England and Wales, develop a mathematical model for influenza transmission based on these data using a Bayesian statistical approach, and use the model to evaluate the impact on influenza infections and deaths of changes to the seasonal influenza vaccination program in England and Wales.
What Did the Researchers Do and Find?
The researchers developed an influenza transmission model using clinical data on influenza-like illness consultations collected in a primary care surveillance scheme for each week of 14 influenza seasons in England and Wales, virological information on respiratory viruses detected in a subset of patients presenting with clinically suspected influenza, and data on vaccination coverage in the whole population (epidemiological data). They also incorporated data on social contacts (behavioral data) and on immunity to influenza viruses in the population (seroepidemiological data) into their model. To estimate the impact of potential changes to the current vaccination strategy in England and Wales, the researchers used their model, which replicated the patterns of disease observed in the surveillance data, to run simulated epidemics for each influenza season and for three strains of influenza virus under various vaccination scenarios. Compared to no vaccination, the current program (vaccination of people 65 years old and older and people in high-risk groups) averted 0.39 infections per dose of vaccine and 1.74 deaths per 1,000 doses. Notably, the model predicted that extension of the program to target 5–16-year-old children would increase the efficiency of the program and would avert 0.70 infections per dose and 1.95 deaths per 1,000 doses.
What Do These Findings Mean?
The finding that the transmission model developed by the researchers closely fit the available surveillance data suggests that the model should be able to predict what would have happened in England and Wales over the study period if an alternative vaccination regimen had been in place. The accuracy of such predictions may be limited, however, because the vaccination model is based on a series of simplifying assumptions. Importantly, given that influenza vaccination for children is being rolled out in England and Wales from September 2013, the model confirms that children are key spreaders of influenza and suggests that a vaccination program targeting children will reduce influenza infections and potentially influenza deaths in the whole population. More generally, the findings of this study support wider adoption of national vaccination strategies designed to block influenza transmission and to target those individuals most at risk from the complications of influenza infection.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371.journal.pmed.1001527.
The UK National Health Service Choices website provides information for patients about seasonal influenza and about vaccination; Public Health England (formerly the Health Protection Agency) provides information on influenza surveillance in the UK, including information about the primary care surveillance database used in this study
The World Health Organization provides information on seasonal influenza (in several languages)
The European Influenzanet is a system to monitor the activity of influenza-like illness with the aid of volunteers via the Internet
The US Centers for Disease Control and Prevention also provides information for patients and health professionals on all aspects of seasonal influenza, including information about vaccination and about the US influenza surveillance system; its website contains a short video about personal experiences of influenza
Flu.gov, a US government website, provides access to information on seasonal influenza and vaccination
MedlinePlus has links to further information about influenza and about immunization (in English and Spanish)
doi:10.1371/journal.pmed.1001527
PMCID: PMC3793005  PMID: 24115913
23.  A Comparative Analysis of Influenza Vaccination Programs 
PLoS Medicine  2006;3(10):e387.
Background
The threat of avian influenza and the 2004–2005 influenza vaccine supply shortage in the United States have sparked a debate about optimal vaccination strategies to reduce the burden of morbidity and mortality caused by the influenza virus.
Methods and Findings
We present a comparative analysis of two classes of suggested vaccination strategies: mortality-based strategies that target high-risk populations and morbidity-based strategies that target high-prevalence populations. Applying the methods of contact network epidemiology to a model of disease transmission in a large urban population, we assume that vaccine supplies are limited and then evaluate the efficacy of these strategies across a wide range of viral transmission rates and for two different age-specific mortality distributions.
We find that the optimal strategy depends critically on the viral transmission level (reproductive rate) of the virus: morbidity-based strategies outperform mortality-based strategies for moderately transmissible strains, while the reverse is true for highly transmissible strains. These results hold for a range of mortality rates reported for prior influenza epidemics and pandemics. Furthermore, we show that vaccination delays and multiple introductions of disease into the community have a more detrimental impact on morbidity-based strategies than mortality-based strategies.
Conclusions
If public health officials have reasonable estimates of the viral transmission rate and the frequency of new introductions into the community prior to an outbreak, then these methods can guide the design of optimal vaccination priorities. When such information is unreliable or not available, as is often the case, this study recommends mortality-based vaccination priorities.
A comparative analysis of two classes of suggested vaccination strategies, mortality-based strategies that target high-risk populations and morbidity-based strategies that target high-prevalence populations.
Editors' Summary
Background.
Influenza—a viral infection of the nose, throat, and airways that is transmitted in airborne droplets released by coughing or sneezing—is a serious public health threat. Most people recover quickly from influenza, but some individuals, especially infants, old people, and individuals with chronic health problems, can develop pneumonia and die. In the US, seasonal outbreaks (epidemics) of flu cause an estimated 36,000 excess deaths annually. And now there are fears that avian influenza might start a human pandemic—a global epidemic that could kill millions. Seasonal outbreaks of influenza occur because flu viruses continually change the viral proteins (antigens) to which the immune system responds. “Antigenic drift”—small changes in these proteins—means that an immune system response that combats flu one year may not provide complete protection the next winter. “Antigenic shift”—large antigen changes—can cause pandemics because communities have no immunity to the changed virus. Annual vaccination with vaccines based on the currently circulating viruses controls seasonal flu epidemics; to control a pandemic, vaccines based on the antigenically altered virus would have to be quickly developed.
Why Was This Study Done?
Most countries target vaccination efforts towards the people most at risk of dying from influenza, and to health-care workers who are likely come into contact with flu patients. But is this the best way to reduce the burden of illness (morbidity) and death (mortality) caused by influenza, particularly at the start of a pandemic, when vaccine would be limited? Old people and infants are much less likely to catch and spread influenza than school children, students, and employed adults, so could vaccination of these sections of the population—instead of those most at risk of death—be the best way to contain influenza outbreaks? In this study, the researchers used an analytical method called “contact network epidemiology” to compare two types of vaccination strategies: the currently favored mortality-based strategy, which targets high-risk individuals, and a morbidity-based strategy, which targets those segments of the community in which most influenza cases occur.
What Did the Researchers Do and Find?
Most models of disease transmission assume that each member of a community is equally likely to infect every other member. But a baby is unlikely to transmit flu to, for example, an unrelated, housebound elderly person. Contact network epidemiology takes the likely relationships between people into account when modeling disease transmission. Using information from Vancouver, British Columbia, Canada, on household size, age distribution, and occupations, and other factors such as school sizes, the researchers built a model population of a quarter of a million interconnected people. They then investigated how different vaccination strategies controlled the spread of influenza in this population. The optimal strategy depended on the level of viral transmissibility—the likelihood that an infectious person transmits influenza to a susceptible individual with whom he or she has contact. For moderately transmissible flu viruses, a morbidity-based vaccination strategy, in which the people most likely to catch the flu are vaccinated, was more effective at containing seasonal and pandemic outbreaks than a mortality-based strategy, in which the people most likely to die if they caught the flu are vaccinated. For highly transmissible strains, this situation was reversed. The level of transmissibility at which this reversal occurred depended on several factors, including whether vaccination was delayed and how many times influenza was introduced into the community.
What Do These Findings Mean?
The researchers tested their models by checking that they could replicate real influenza epidemics and pandemics, but, as with all mathematical models, they included many assumptions about influenza in their calculations, which may affect their results. Also, because the contact network used data from Vancouver, their results might not be applicable to other cities, or to nonurban areas. Nevertheless, their findings have important public health implications. When there are reasonable estimates of the viral transmission rate, and it is known how often influenza is being introduced into a community, contact network models could help public health officials choose between morbidity- and mortality-based vaccination strategies. When the viral transmission rate is unreliable or unavailable (for example, at the start of a pandemic), the best policy would be the currently preferred strategy of mortality-based vaccination. More generally, the use of contact network models should improve estimates of how infectious diseases spread through populations and indicate the best ways to control human epidemics and pandemics.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0030387.
US Centers for Disease Control and Prevention information about influenza for patients and professionals, including key facts on vaccination
US National Institute of Allergy and Infectious Diseases feature on seasonal, avian, and pandemic influenza
World Health Organization fact sheet on influenza, with links to information on vaccination
UK Health Protection Agency information on seasonal, avian, and pandemic influenza
MedlinePlus entry on influenza
doi:10.1371/journal.pmed.0030387
PMCID: PMC1584413  PMID: 17020406
24.  Willingness of Hong Kong healthcare workers to accept pre-pandemic influenza vaccination at different WHO alert levels: two questionnaire surveys 
Objective To assess the acceptability of pre-pandemic influenza vaccination among healthcare workers in public hospitals in Hong Kong and the effect of escalation in the World Health Organization’s alert level for an influenza pandemic.
Design Repeated cross sectional studies using self administered, anonymous questionnaires
Setting Surveys at 31 hospital departments of internal medicine, paediatrics, and emergency medicine under the Hong Kong Hospital Authority from January to March 2009 and in May 2009
Participants 2255 healthcare workers completed the questionnaires in the two studies. They were doctors, nurses, or allied health professionals working in the public hospital system.
Main outcome measures Stated willingness to accept pre-pandemic influenza vaccination (influenza A subtypes H5N1 or H1N1) and its associating factors.
Results The overall willingness to accept pre-pandemic H5N1 vaccine was only 28.4% in the first survey, conducted at WHO influenza pandemic alert phase 3. No significant changes in the level of willingness to accept pre-pandemic H5N1 vaccine were observed despite the escalation to alert phase 5. The willingness to accept pre-pandemic H1N1 vaccine was 47.9% among healthcare workers when the WHO alert level was at phase 5. The most common reasons for an intention to accept were “wish to be protected” and “following health authority’s advice.” The major barriers identified were fear of side effects and doubts about efficacy. More than half of the respondents thought nurses should be the first priority group to receive the vaccines. The strongest positive associating factors were history of seasonal influenza vaccination and perceived risk of contracting the infection.
Conclusions The willingness to accept pre-pandemic influenza vaccination was low, and no significant effect was observed with the change in WHO alert level. Further studies are required to elucidate the root cause of the low intention to accept pre-pandemic vaccination.
doi:10.1136/bmj.b3391
PMCID: PMC2731837  PMID: 19706937
25.  Can Influenza Epidemics Be Prevented by Voluntary Vaccination? 
PLoS Computational Biology  2007;3(5):e85.
Previous modeling studies have identified the vaccination coverage level necessary for preventing influenza epidemics, but have not shown whether this critical coverage can be reached. Here we use computational modeling to determine, for the first time, whether the critical coverage for influenza can be achieved by voluntary vaccination. We construct a novel individual-level model of human cognition and behavior; individuals are characterized by two biological attributes (memory and adaptability) that they use when making vaccination decisions. We couple this model with a population-level model of influenza that includes vaccination dynamics. The coupled models allow individual-level decisions to influence influenza epidemiology and, conversely, influenza epidemiology to influence individual-level decisions. By including the effects of adaptive decision-making within an epidemic model, we can reproduce two essential characteristics of influenza epidemiology: annual variation in epidemic severity and sporadic occurrence of severe epidemics. We suggest that individual-level adaptive decision-making may be an important (previously overlooked) causal factor in driving influenza epidemiology. We find that severe epidemics cannot be prevented unless vaccination programs offer incentives. Frequency of severe epidemics could be reduced if programs provide, as an incentive to be vaccinated, several years of free vaccines to individuals who pay for one year of vaccination. Magnitude of epidemic amelioration will be determined by the number of years of free vaccination, an individuals' adaptability in decision-making, and their memory. This type of incentive program could control epidemics if individuals are very adaptable and have long-term memories. However, incentive-based programs that provide free vaccination for families could increase the frequency of severe epidemics. We conclude that incentive-based vaccination programs are necessary to control influenza, but some may be detrimental. Surprisingly, we find that individuals' memories and flexibility in adaptive decision-making can be extremely important factors in determining the success of influenza vaccination programs. Finally, we discuss the implication of our results for controlling pandemics.
Author Summary
Currently, a major public health concern is the next influenza pandemic; yet it remains unclear how to control such a crisis. By using novel mathematical modeling techniques, here we predict the likely impact of voluntary vaccination programs on controlling influenza epidemics and pandemics. We construct an individual-level model of human cognition and behavior that includes two important biological characteristics: memory and adaptability/flexibility. In each influenza season, each individual in the modeled population decides, using memory and adaptability/flexibility, whether to be vaccinated or not. We combine our individual-level model with an epidemic model to predict the impact of voluntary vaccination programs. We found that severe influenza epidemics cannot be prevented unless vaccination programs offer incentives. Frequency of severe epidemics could be reduced if programs provide, as an incentive to be vaccinated, several years of free vaccines to individuals who pay for one year of vaccination. However, we found that a public health intervention program that focuses on vaccinating families is likely to increase the frequency of severe epidemics. Most importantly, we found that individuals' memories and adaptability/flexibility in decision-making are critical factors in determining the success of influenza vaccination programs. Our results are applicable both for the control of seasonal and pandemic influenza.
doi:10.1371/journal.pcbi.0030085
PMCID: PMC1864996  PMID: 17480117

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