Socio-economic disparities in mortality due to pandemic influenza in England

Objectives

This study examines variations in mortality between socio-economic groups due to the pandemic Influenza (H1N1) 2009 virus in England.

Methods

We established a system to identify all deaths related to pandemic (H1N1) 2009 influenza. We collected the postcode of every individual who died, and through this determined the socio-economic deprivation, urban–rural characteristics and region of their residence. Across England, we were therefore able to examine how mortality rates varied by socio-economic group, between urban and rural areas, and between regions.

Results

People in the most deprived quintile of England’s population had an age and sex-standardised mortality rate three times that experienced by the least deprived quintile (RR?=?3.1, 95% CI 2.2–4.4). Mortality was also higher in urban areas than in rural areas (RR?=?1.7, 95% CI 1.2–2.3). Mortality rates were similar between regions of the country.

Conclusion

Tackling socio-economic health inequalities is a central concept within public health, but has not always been a part of emergency preparedness plans. These data demonstrate the opportunity to reduce the overall impact and narrow inequalities by considering socio-economic disparities in future pandemic planning.     

All-Cause Mortality during First Wave of Pandemic (H1N1) 2009, New South Wales, Australia, 2009

In temperate countries, death rates increase in winter, but influenza epidemics often cause greater increases. The death rate time series that occurs without epidemic influenza can be called a seasonal baseline. Differentiating observed death rates from the seasonally oscillating baseline provides estimated influenza-associated death rates. During 2003–2009 in New South Wales, Australia, we used a Serfling approach with robust regression to estimate age-specific weekly baseline all-cause death rates. Total differences between weekly observed and baseline rates during May–September provided annual estimates of influenza-associated death rates. In 2009, which included our first wave of pandemic (H1N1) 2009, the all-age death rate was 6.0 (95% confidence interval 3.1–8.9) per 100,000 persons lower than baseline. In persons >80 years of age, it was 131.6 (95% confidence interval 126.2–137.1) per 100,000 lower. This estimate is consistent with a pandemic virus causing mild illness in most persons infected and sparing older persons.     

Trends in parameterization,economics and host behaviour in influenza pandemic modelling: a review and reporting protocol

Background

The volume of influenza pandemic modelling studies has increased dramatically in the last decade. Many models incorporate now sophisticated parameterization and validation techniques, economic analyses and the behaviour of individuals.

Methods

We reviewed trends in these aspects in models for influenza pandemic preparedness that aimed to generate policy insights for epidemic management and were published from 2000 to September 2011, i.e. before and after the 2009 pandemic.

Results

We find that many influenza pandemics models rely on parameters from previous modelling studies, models are rarely validated using observed data and are seldom applied to low-income countries. Mechanisms for international data sharing would be necessary to facilitate a wider adoption of model validation. The variety of modelling decisions makes it difficult to compare and evaluate models systematically.

Conclusions

We propose a model Characteristics, Construction, Parameterization and Validation aspects protocol (CCPV protocol) to contribute to the systematisation of the reporting of models with an emphasis on the incorporation of economic aspects and host behaviour. Model reporting, as already exists in many other fields of modelling, would increase confidence in model results, and transparency in their assessment and comparison.

     

Knowledge about the pandemic influenza A (H1N1) and willingness to accept vaccination: a cross-sectional survey

Aims

(1) To determine undergraduate medical students' knowledge about and perceptions of influenza A (H1N1) infection, (2) to explore their willingness to be vaccinated, and (3) to identify variables that could predict the likelihood of taking the vaccination.

Subject and methods

A cross-sectional survey with a convenience sample of 264 medical students was performed. Data were collected using a structured questionnaire. Summary statistics, Pearson chi-square test and logistic regression were used for data analysis.

Results

A total of 264 undergraduate medical students were interviewed. All of them had heard of the influenza vaccine, but none had ever been vaccinated at the time of survey. Regarding mode of transmission, 38.3% had at least two misconceptions. Of them, 43% had willingness to be vaccinated. In the binary logistic model, willingness to be vaccinated was statistically significant with those who feared the resurgence of a pandemic influenza (p = 0.01), those who trusted that vaccination would be effective for prevention of a pandemic influenza (p = 0.045), and those who were worried for family (p = 0.03) and if the vaccination would be freely provided (p = 0.04).

Conclusion

The findings may be helpful for decision makers and health care planners as baseline information for designing wider coverage of newly implemented vaccination programs.     

The determinants of 2009 pandemic A/H1N1 influenza vaccination: a systematic review

Background

Pandemic A/H1N1 influenza vaccine coverage varied widely across countries. To understand the factors influencing pandemic influenza vaccination and to guide the development of successful vaccination programs for future influenza pandemics, we identified and summarized studies examining the determinants of vaccination during the 2009 influenza pandemic.

Methods

We performed a systematic literature review using the PubMED electronic database from June 2009 to February 2011. We included studies examining an association between a possible predictive variable and actual receipt of the pandemic A/H1N1 influenza vaccine. We excluded studies examining intention or willingness to receive the vaccine.

Results

Twenty-seven studies were identified from twelve countries. Pandemic influenza vaccine coverage varied from 4.8% to 92%. Coverage varied by population sub-group, country, and assessment method used. Most studies used questionnaires to estimate vaccine coverage, however seven (26%) used a vaccination registry. Factors that positively influenced pandemic influenza vaccination were: male sex, younger age, higher education, being a doctor, being in a priority group for which vaccination was recommended, receiving a prior seasonal influenza vaccination, believing the vaccine to be safe and/or effective, and obtaining information from official medical sources.

Conclusions

Vaccine coverage during the pandemic varied widely across countries and population sub-groups. We identified some consistent determinants of this variation that can be targeted to increase vaccination during future influenza pandemics.     

High effectiveness of pandemic influenza A (H1N1) vaccination in healthcare workers from a Portuguese hospital

Objectives

Vaccination of healthcare workers (HCWs) was made a high priority during the phase six pandemic of the novel influenza A H1N1 (pH1N1) virus. We surveyed adherence to pH1N1 vaccination and the incidence of pH1N1 infection between vaccinated and unvaccinated HCWs.

Methods

Employees at the S. Jo?o Hospital in Porto, Portugal, were offered pH1N1 vaccinations free of charge. Pandemrix^? was the vaccine administered. As part of the pandemic plan, employees with influenza-like symptoms (ILS) were called upon to take an RT-PCR H1N1 test. If the test results were positive, they had to stay off work for at least 7?days. Sociodemographic data, vaccination status, contact with infectious patients, ILS and pH1N1 test results were documented in a standardised manner.

Results

The survey population comprised 5,592 employees. The vaccination rate was 30.8% (n?=?1,720) for pH1N1 and 50.4% (n?=?2,819) for the 2009/2010 seasonal trivalent inactivated influenza vaccine (TIV). One mild anaphylactic reaction occurred after pH1N1 vaccination. Minor local side effects occurred more often after pH1N1 vaccination than after 2009/2010 seasonal TIV (38.0% vs. 12.3%). Pandemic H1N1 infection was diagnosed in 97 HCWs (1.7%). Compared to employees with no regular patient contact, nurses (2.8%) had the highest risk of pH1N1 infection (adjusted OR 3.8; 95% CI 1.2–6.8). Vaccination reduced the pH1N1 infection risk (OR 0.12; 95% CI 0.05–0.29). Vaccine effectiveness was 90.4% (95% CI 73.5–97.3%).

Conclusion

Vaccination reduced the pH1N1 infection risk considerably. The pandemic plan to contain the pH1N1 infection was successful. Nurses had the highest risk of pH1N1 infection and are therefore a target group for vaccination measures.     

Influenza pandemic (H1N1) 2009 activity during summer 2009. Effectiveness of the 2008-9 trivalent vaccine against pandemic influenza in Spain

Introduction

The Spanish influenza surveillance system (SISS) maintained its activity during the summer of 2009 to monitor the influenza pandemic.

Objectives

To describe pandemic influenza activity from May to September 2009 and to estimate the effectiveness of the 2008-9 seasonal influenza vaccine against laboratory-confirmed pandemic (H1N1) 2009 influenza.

Methods

Data from the SISS were used to identify the trend of pandemic (H1N1) 2009 influenza outside the influenza season. For the effectiveness study, we compared the vaccination status of notified cases [influenza-like illnesses (ILI) laboratory confirmed as pandemic influenza] with that of the test-negative controls.

Results

The first laboratory-confirmed case of the pandemic virus was notified in the system in week 20/2009. The ILI rate increased gradually in the study period, exceeding basic activity in week 38. The proportion of pandemic (H1N1) 2009 influenza viruses detected by the system represented 14% in week 20/2009 and rapidly increased to 90% in week 34. The adjusted vaccine effectiveness of the 2008-9 seasonal vaccine against laboratory-confirmed pandemic influenza was 12% (-30; 41).

Conclusions

The SISS became an essential tool for pandemic monitoring in Spain. The improved SISS will provide more accurate information on influenza activity in future seasonal or pandemic waves. Using surveillance data, we could not demonstrate the effectiveness of the seasonal 2008-9 vaccine against laboratory-confirmed pandemic influenza.     

Effectiveness of Seasonal Influenza Vaccine against Pandemic (H1N1) 2009 Virus, Australia, 2010

To estimate effectiveness of seasonal trivalent and monovalent influenza vaccines against pandemic influenza A (H1N1) 2009 virus, we conducted a test-negative case–control study in Victoria, Australia, in 2010. Patients seen for influenza-like illness by general practitioners in a sentinel surveillance network during 2010 were tested for influenza; vaccination status was recorded. Case-patients had positive PCRs for pandemic (H1N1) 2009 virus, and controls had negative influenza test results. Of 319 eligible patients, test results for 139 (44%) were pandemic (H1N1) 2009 virus positive. Adjusted effectiveness of seasonal vaccine against pandemic (H1N1) 2009 virus was 79% (95% confidence interval 33%–93%); effectiveness of monovalent vaccine was 47% and not statistically significant. Vaccine effectiveness was higher among adults. Despite some limitations, this study indicates that the first seasonal trivalent influenza vaccine to include the pandemic (H1N1) 2009 virus strain provided significant protection against laboratory-confirmed pandemic (H1N1) 2009 infection.After the emergence and rapid global spread of pandemic influenza A (H1N1) 2009 virus, development of a pandemic (H1N1) 2009–specific vaccine began (1). A candidate reassortant vaccine virus, derived from the A/California/7/2009 (H1N1)v virus as recommended by the World Health Organization, was used to produce a monovalent, unadjuvanted, inactivated, split-virus vaccine for Australia (2,3). The national monovalent pandemic (H1N1) 2009 vaccination program in Australia ran from September 30, 2009, through December 31, 2010, and vaccination was publicly funded for all persons in Australia >6 months of age (4,5).In September 2009, the World Health Organization recommended that trivalent influenza vaccines for use in the 2010 influenza season (Southern Hemisphere winter) contain A/California/7/2009 (H1N1)–like virus, A/Perth/16/2009 (H3N2)–like virus, and B/Brisbane/60/2008 (of the B/Victoria/2/87 lineage) virus (6). Since March 2010, the Australian Government has provided free seasonal influenza vaccination to all Australia residents >65 years of age, all Aboriginal and Torres Strait Islander persons >50 years, all Aboriginal and Torres Strait Islander persons 15–49 years with medical risk factors, persons >6 months with conditions that predispose them to severe influenza, and pregnant women (7). Influenza vaccination is also recommended, but not funded, for persons who might transmit influenza to those at high risk for complications from influenza, persons who provide essential services, travelers, and anyone >6 months of age for whom reducing the likelihood of becoming ill with influenza is desired. Individual industries are also advised to consider the benefits of offering influenza vaccine in the workplace (8). Because pandemic (H1N1) 2009 was expected to be the dominant strain in 2010, the monovalent vaccine continued to be used despite the availability of the seasonal vaccine, particularly by persons who were not eligible for funded vaccine (M. Batchelor, pers. comm.). However, in 2010, there were no published data on the relative use of monovalent and seasonal vaccines at that time.The need for rapid implementation of programs results in initial studies using immunogenicity, rather than efficacy, to assess performance of influenza vaccines. After 1 dose of monovalent pandemic (H1N1) 2009 vaccine containing 15 µg hemagglutinin without adjuvant, seroprotection was estimated to be 94%–97% in working-age adults (3,9,10) and 75% in children (10). Observational studies provide a practical way to calculate vaccine effectiveness under field conditions (11,12). Effectiveness of monovalent pandemic (H1N1) 2009 was estimated to be 72%–97% by 3 studies in general practice and community-based settings in Europe (13–15), 90% in a hospital-based study in Spain (16), and 100% in a community-based study of children in Canada (17). These studies were conducted in populations for which the respective local or national pandemic vaccination program primarily used vaccine without adjuvant.We assessed effectiveness of the 2010 seasonal influenza vaccine against laboratory-confirmed pandemic (H1N1) 2009 influenza infection in Victoria, Australia. Data came from an established test-negative case–control study in a general practitioner sentinel surveillance network (18,19).     

H1N1 Influenza Vaccination During Pregnancy and Fetal and Neonatal Outcomes

Objectives. We evaluated the relationship between maternal H1N1 vaccination and fetal and neonatal outcomes among singleton births during the 2009–2010 H1N1 pandemic.Methods. We used a population-based perinatal database in Ontario, Canada, to examine preterm birth (PTB), small-for-gestational-age (SGA) births, 5-minute Apgar score below 7, and fetal death via multivariable regression. We compared outcomes between women who did and did not receive an H1N1 vaccination during pregnancy.Results. Of the 55 570 mothers with a singleton birth, 23 340 (42.0%) received an H1N1 vaccination during pregnancy. Vaccinated mothers were less likely to have an SGA infant based on the 10th (adjusted risk ratio [RR] = 0.90; 95% confidence interval [CI] = 0.85, 0.96) and 3rd (adjusted RR = 0.81; 95% CI = 0.72, 0.92) growth percentiles; PTB at less than 32 weeks’ gestation (adjusted RR = 0.73; 95% CI = 0.58, 0.91) and fetal death (adjusted RR = 0.66; 95% CI = 0.47, 0.91) were also less likely among these women.Conclusions. Our results suggest that second- or third-trimester H1N1 vaccination was associated with improved fetal and neonatal outcomes during the recent pandemic. Our findings need to be confirmed in future studies with designs that can better overcome concerns regarding biased estimates of vaccine efficacy.During the 2009–2010 H1N1 influenza pandemic, early case reports documented more severe illness among pregnant women than among the general population, as well as higher rates of hospitalization and intensive care unit admissions.1,2 Later reports confirmed the disproportionately severe clinical course among pregnant women infected with H1N1 influenza.3–6 Public health organizations7–9 and professional associations10,11 strongly encouraged pregnant women to receive an H1N1 vaccination, and recent evidence suggests that the intensive vaccination campaign resulted in higher maternal vaccination rates during the pandemic than had been documented in previous influenza seasons.12–14Recommendations for routine vaccination of all pregnant women with inactivated influenza vaccine have been in place in Canada and the United States for a number of years.15–18 Nevertheless, seasonal vaccination rates prior to the 2009–2010 pandemic year were low in the United States,19–22 ranging from 0.7% to 20% (estimates were not available for Canada). In both countries, misconceptions about the risk of complications from influenza infection during pregnancy23 and concerns about safety12,23 are commonly cited reasons for not receiving an influenza vaccination, whereas care provider recommendations have been shown to increase vaccination rates.12,14,24Despite ongoing maternal concerns about vaccine safety, no evidence of serious harmful effects following influenza vaccination during pregnancy has been reported in the available studies on this topic19–21,25–32; thus, vaccination is promoted as the best way of preventing maternal morbidity from influenza infection.31 Theoretically, maternal influenza vaccination should also benefit the fetus by averting maternal illness and associated hyperthermia and other morbidity.28,31 Recent studies have reported a lower risk of preterm birth (PTB)33 and small-for-gestational-age (SGA) infants33,34 among women receiving an influenza vaccination during their pregnancy. However, the impact of maternal influenza vaccination on fetal and neonatal outcomes has not been extensively evaluated, possibly as a result of low immunization rates and limited sample sizes that preclude assessment of rare outcomes.In Ontario, Canada, the 2009 pandemic H1N1 vaccination campaign started on October 26, 2009; high-priority groups, including pregnant women, were targeted. During the pandemic, Better Outcomes Registry & Network (BORN) Ontario collected influenza immunization information from all pregnant women who gave birth in the province. Using this large, population-based birth cohort, we examined the association between maternal H1N1 influenza vaccination and fetal and neonatal outcomes.     

Comparison of Pandemic (H1N1) 2009 and Seasonal Influenza, Western Australia, 2009

We compared confirmed pandemic (H1N1) 2009 influenza and seasonal influenza diagnosed in Western Australia during the 2009 influenza season. From 3,178 eligible reports, 984 pandemic and 356 seasonal influenza patients were selected; 871 (88.5%) and 288 (80.9%) were interviewed, respectively. Patients in both groups reported a median of 6 of 11 symptoms; the difference between groups in the proportion reporting any given symptom was <10%. Fewer than half the patients in both groups had >1 underlying condition, and only diabetes was associated with pandemic (H1N1) 2009 influenza (odds ratio [OR] 1.9, 95% confidence interval [CI] 1.1–3.5). A total of 129 (14.8%) persons with pandemic (H1N1) 2009 and 36 (12.5%) persons with seasonal influenza were hospitalized (p = 0.22). After controlling for age, we found that patient hospitalization was associated with pandemic (H1N1) 2009 influenza (OR 1.5; 95% CI 1.1–2.1). Contemporaneous pandemic and seasonal influenza infections were substantially similar in terms of patients’ symptoms, risk factors, and proportion hospitalized.     

Pandemic and seasonal vaccine coverage and effectiveness during the 2009–2010 pandemic influenza in an Italian adult population

Objectives

To evaluate the response to pandemic vaccination and seasonal and pandemic vaccine effectiveness (VE) in an Italian adult population, during the 2009?C2010 influenza season.

Methods

Data were recorded by interviewing 19,275 subjects (??35?years), randomly recruited from the general population of the Moli-sani project. Events [influenza-like illness (ILI), hospitalization and death], which had occurred between 1 November 2009 and 31 January 2010 were considered. VE was analyzed by multivariable Poisson regression analysis.

Results

Pandemic vaccine coverage was very low (2.4%) in subjects at high-flu risk, aged 35?C65?years (N?=?8,048); there was no significant preventive effect of vaccine against ILI. Seasonal vaccine coverage was 26.6% in the whole population (63% in elderly and 21.9% in middle-aged subjects at high-flu risk). There was a higher risk to develop ILI in middle-age [VE: ?17% (95% CI: ?35,?1)] or at high flu-risk [VE: ?17% (95% CI: ?39, 2)] vaccinated groups.

Conclusions

Coverage of pandemic vaccine was very low in a Southern Italy population, with no protective effect against ILI.     

Selection for resistance to oseltamivir in seasonal and pandemic H1N1 influenza and widespread co-circulation of the lineages

Background

In Spring 2009, a novel reassortant strain of H1N1 influenza A emerged as a lineage distinct from seasonal H1N1. On June 11, the World Heath Organization declared a pandemic - the first since 1968. There are currently two main branches of H1N1 circulating in humans, a seasonal branch and a pandemic branch. The primary treatment method for pandemic and seasonal H1N1 is the antiviral drug Tamiflu^® (oseltamivir). Although many seasonal H1N1 strains around the world are resistant to oseltamivir, initially, pandemic H1N1 strains have been susceptible to oseltamivir. As of February 3, 2010, there have been reports of resistance to oseltamivir in 225 cases of H1N1 pandemic influenza. The evolution of resistance to oseltamivir in pandemic H1N1 could be due to point mutations in the neuraminidase or a reassortment event between seasonal H1N1 and pandemic H1N1 viruses that provide a neuraminidase carrying an oseltamivir-resistant genotype to pandemic H1N1.

Results

Using phylogenetic analysis of neuraminidase sequences, we show that both seasonal and pandemic lineages of H1N1 are evolving to direct selective pressure for resistance to oseltamivir. Moreover, seasonal lineages of H1N1 that are resistant to oseltamivir co-circulate with pandemic H1N1 throughout the globe. By combining phylogenetic and geographic data we have thus far identified 53 areas of co-circulation where reassortment can occur. At our website POINTMAP, http://pointmap.osu.edu we make available a visualization and an application for updating these results as more data are released.

Conclusions

As oseltamivir is a keystone of preparedness and treatment for pandemic H1N1, the potential for resistance to oseltamivir is an ongoing concern. Reassortment and, more likely, point mutation have the potential to create a strain of pandemic H1N1 against which we have a reduced number of treatment options.

     

Präsentismus vermeiden – Arbeitsbereitschaft fördern. Ein Zielkonflikt der Pandemieplanung?

Introduction

Employees are recommended to stay at home when they show symptoms of an acute respiratory infection. Yet, in case of an influenza pandemic another challenge is to promote the employees’ high willingness to report to work. For pandemic planning this raises the question, whether there is a conflict between these two goals.

Method

Employee survey at the urban administration of Dortmund, Germany, about presenteeism with symptoms of an acute respiratory infection and the willingness to report to work during an influenza pandemic.

Results

Results of multivariate linear regression indicated: There is only little association between propensity for presenteeism with symptoms of an acute respiratory infection and willingness to report to work during an influenza pandemic (R²?=?0,024).

Conclusion

Results did not support the aforementioned conflict of goals between reducing presenteeism with symptoms of an acute respiratory infection and promoting willingness to report to work during an influenza pandemic. Further research should investigate interventions, which will support both goals alike, in order to support pandemic planning.     

Serologic survey of pandemic influenza A (H1N1 2009) in Beijing, China

Objective

To examine the frequency and distribution of antibodies against pandemic influenza A (H1N1 2009) [H1N1] in populations in Beijing and elucidate influencing factors.

Methods

In January 2010, a randomized serologic survey of pandemic influenza A (H1N1 2009) was carried out. Six districts that were randomly selected with a total of 4601 participants involved in the survey have their antibody level tested by hemagglutination inhibition assay.

Results

Among the 4601 participants, the overall seropositive rate for pandemic influenza A (H1N1 2009) antibodies was 31.7%. The seropositivity prevalence in participants who received the pandemic H1N1 vaccination was 60.9%. Only 53.1% of the pandemic influenza A (H1N1 2009) seropositive individuals who had not received the vaccination experienced respiratory tract infection symptoms. Multivariate logistic regression revealed that factors such as age, occupation, dwelling type, whether the participant's family included students in school, and the vaccination history with pandemic influenza A (H1N1 2009) were associated with antibody titers (p < 0.05).

Conclusions

Our data indicated that almost 30.0% of the residents had appropriate antibody titers against pandemic influenza A (H1N1 2009) in Beijing, and these titers may provide an immune barrier.     

Using Surveillance Data to Identify Risk Factors for Severe H1N1 in First Nations

Objective

We sought to measure from surveillance data the effect of proximity to an urban centre (rurality) and other risk factors, (e.g., age, residency on a FN reservation, and pandemic wave) on hospitalization and intensive care unit admission for severe influenza.

Introduction

Research has shown that Canadian First Nation (FN) populations were disproportionately affected by the 2009 H1N1 influenza pandemic. However, the mechanisms for the disproportionate outcomes are not well understood. Possibilities such as healthcare access, infrastructure and housing issues, and pre-existing comorbidities have been suggested. We estimated the odds of hospitalization and intensive care unit admission for cases of H1N1 influenza among FN living in Manitoba, Canada, to determine the effect of location of residency and other factors on disease outcomes during the 2009 H1N1 pandemic.

Methods

We obtained surveillance data on laboratory confirmed cases of pandemic H1N1 influenza from the province of Manitoba. These data described demographic characteristics, residence location, and dates of hospital and ICU admission. We measured the rurality of each case using a pre-exiting scale (Rambeau & Todd, 2000). We tabulated the number of hospitalizations (and ICU admissions) stratified first by reservation residency and second by rurality and calculated unadjusted odds ratios. We then used logistic regression to calculate the odds of hospitalization given infection (and the odds of ICU admission given hospitalization), adjusting for age, reservation residency, rurality, and pandemic wave. We also investigated the effect of rurality and reserve residency on time to hospitalization from infection.

Results

FN individuals diagnosed with influenza and living on-reserve were more likely to be hospitalized than those living off-reserve, even after controlling for the effects of rurality (OR: 2.16, 95% CI: 1.15, 4.05). FN living in rural areas were hospitalized more frequently and experienced longer delays between infection and hospitalization than FN residing in more urban areas. Rurality and reserve residency had less effect on ICU admissions once an individual was hospitalized.

Conclusions

While it is established that FN individuals had disproportionately high rates of severe outcomes from H1N1, the causal mechanisms at work are not well understood. Reasonable possibilities include barriers to healthcare access, lack of proper housing and infrastructure, and pre-existing comorbidities. This research using surveillance data suggests that geographic location has an effect on healthcare access, including both on vs. off reserve residency as well as rurality.     

The Social Determinants of Health and Pandemic H1N1 2009 Influenza Severity

Objectives. We explored the effects of social determinants of health on pandemic H1N1 2009 influenza severity and the role of clinical risk factors in mediating such associations.Methods. We used multivariate logistic regression with generalized estimating equations to examine the associations between individual- and ecological-level social determinants of health and hospitalization for pandemic H1N1 2009 illness in a case-control study in Ontario, Canada.Results. During the first pandemic phase (April 23–July 20, 2009), hospitalization was associated with having a high school education or less and living in a neighborhood with high material or total deprivation. We also observed the association with education in the second phase (August 1–November 6, 2009). Clinical risk factors for severe pandemic H1N1 2009 illness mediated approximately 39% of the observed association.Conclusions. The main clinical risk factors for severe pandemic H1N1 2009 illness explain only a portion of the associations observed between social determinants of health and hospitalization, suggesting that the means by which the social determinants of health affect pandemic H1N1 2009 outcomes extend beyond clinically recognized risk factors.Similar to seasonal influenza, most cases of pandemic H1N1 2009 influenza were relatively mild; however, certain groups of individuals were at a higher risk of complication and severe disease than were others. Information from early pandemic H1N1 2009 case series indicated that risk factors typically associated with severe seasonal influenza, including underlying conditions such as pulmonary or cardiac disease, diabetes, and pregnancy, were observed among individuals very ill with pandemic H1N1 2009; however, unlike seasonal influenza, severe pandemic H1N1 2009 affected children of all ages and young adults, many of whom were previously healthy.1–6 Obesity and morbid obesity were also recognized as risk factors.2,7,8In Ontario, Canada, a case-control study was conducted as part of a pan-Canadian approach to pandemic H1N1 2009 research. The purpose of this study was to identify risk factors for pandemic H1N1 2009 infection requiring hospitalization (L. C. R. and N. C., unpublished data, 2010).9 Many of the risk factors identified in our study and others, notably the presence of chronic conditions such as diabetes10–12and obesity13,14 and health behaviors such as smoking15,16 and accessing health care,17 are known to be influenced by the social determinants of health. The social determinants of health are social and economic conditions, such as income, education, employment, and social support, that influence the health of individuals and communities. Disparities in these conditions are reflected in a gradient of socioeconomic status (SES), which, in turn, is associated with inequalities in health. It is widely recognized that individuals at the lower end of the SES gradient experience poorer health and a reduced life expectancy compared with more advantaged groups.18–20 We were therefore interested in exploring the effects of the social determinants of health on pandemic H1N1 2009 severity in Ontario and the role of clinical risk factors in mediating any such associations.In addition to individual characteristics, contextual socioeconomic factors, such as neighborhood conditions, influence health outcomes. A majority of studies investigating neighborhood effects on health have found significant associations between measures of area SES and health outcomes, such as self-reported health and mortality, that are independent of the effects of individual socioeconomic characteristics.21,22 The mechanisms by which neighborhood characteristics affect the health of individuals are not fully understood, but there are several potential pathways through which ecological exposures may affect the severity of influenza infection. For example, neighborhood problems such as vandalism, illegal drug use, noise, and litter are sources of psychological stress for residents,23–25 and psychological stress is known to influence immune function.26,27 Neighborhood-associated psychological stress could therefore place individuals at increased risk of severe influenza illness. Indeed, Cohen et al. demonstrated that among individuals experimentally infected with influenza, those reporting high psychological stress before inoculation experienced more severe illness than did individuals with low stress.28 Another possibility is that environmental exposures, such as air pollution, contribute to an individual’s risk for severe infection. Traffic-related air pollution is associated with incident asthma,29–32 and asthma was identified as an important risk factor for severe pandemic H1N1 2009 outcomes, including hospitalization.33 This evidence demonstrates that the social determinants of health exert influence on health at the ecological level as well as at the individual level.We examined the effects of individual- and ecological-level social determinants of health on pandemic H1N1 2009 severity, as indicated by hospitalization, in Ontario, Canada. Furthermore, we explored the role of known clinical risk factors for severe pandemic H1N1 2009 infection in mediating any such associations.A few studies have investigated the associations between the social determinants of health and respiratory infection outcomes, such as healthcare utilization34 and hospitalization.35–37 The outcomes measured in these studies are not specific to influenza and include outcomes from all or acute respiratory infections35 and influenza and pneumonia diagnoses combined.37 Measuring influenza-specific outcomes is challenging because of the nonspecific presentation of illness and the limited use of laboratory diagnostic testing for medical management. The prevalent use of diagnostic testing for influenza during the H1N1 2009 pandemic, therefore, provided a unique opportunity to examine the effect of the social determinants of health on influencing hospitalization specifically because of this novel strain of influenza.     

Value for Money in H1N1 Influenza: A Systematic Review of the Cost-Effectiveness of Pandemic Interventions

Background

The 2009 A/H1N1 influenza pandemic generated additional data and triggered new studies that opened debate over the optimal strategy for handling a pandemic. The lessons-learned documents from the World Health Organization show the need for a cost estimation of the pandemic response during the risk-assessment phase. Several years after the crisis, what conclusions can we draw from this field of research?