Clinic accessibility and clinic-level predictors of the geographic variation in 2009 pandemic influenza vaccine coverage in Montreal, Canada.

BACKGROUND: Nineteen mass vaccination clinics were established in Montreal, Canada, as part of the 2009 influenza A/H1N1p vaccination campaign. Although approximately 50% of the population was vaccinated, there was a considerable variation in clinic performance and community vaccine coverage. OBJECTIVE: To identify community- and clinic-level predictors of vaccine uptake, while accounting for the accessibility of clinics from the community of residence. METHODS: All records of influenza A/H1N1p vaccinations administered in Montreal were obtained from a vaccine registry. Multivariable regression models, specifically Bayesian gravity models, were used to assess the relationship between vaccination rates and clinic accessibility, clinic-level factors, and community-level factors. RESULTS: Relative risks compare the vaccination rates at the variable's upper quartile to the lower quartile. All else being equal, clinics in areas with high violent crime rates, high residential density, and high levels of material deprivation tended to perform poorly (adjusted relative risk [ARR]: 0·917, 95% CI [credible interval]: 0·915, 0·918; ARR: 0·663, 95% CI: 0·660, 0·666, ARR: 0·649, 95% CI: 0·645, 0·654, respectively). Even after controlling for accessibility and clinic-level predictors, communities with a greater proportion of new immigrants and families living below the poverty level tended to have lower rates (ARR: 0·936, 95% CI: 0·913, 0·959; ARR: 0·918, 95% CI: 0·893, 0·946, respectively), while communities with a higher proportion speaking English or French tended to have higher rates (ARR: 1·034, 95% CI: 1·012, 1·059). CONCLUSION: In planning future mass vaccination campaigns, the gravity model could be used to compare expected vaccine uptake for different clinic location strategies.

Relationship between community prevalence of obesity and associated behavioral factors and community rates of influenza-related hospitalizations in the United States.

BACKGROUND: Findings from studies examining the association between obesity and acute respiratory infection are inconsistent. Few studies have assessed the relationship between obesity-related behavioral factors, such as diet and exercise, and risk of acute respiratory infection. OBJECTIVE: To determine whether community prevalence of obesity, low fruit/vegetable consumption, and physical inactivity are associated with influenza-related hospitalization rates. METHODS: Using data from 274 US counties, from 2002 to 2008, we regressed county influenza-related hospitalization rates on county prevalence of obesity (BMI ≥ 30), low fruit/vegetable consumption (<5 servings/day), and physical inactivity (<30 minutes/month recreational exercise), while adjusting for community-level confounders such as insurance coverage and the number of primary care physicians per 100,000 population. RESULTS: A 5% increase in obesity prevalence was associated with a 12% increase in influenza-related hospitalization rates [adjusted rate ratio (ARR) 1.12, 95% confidence interval (CI) 1.07, 1.17]. Similarly, a 5% increase in the prevalence of low fruit/vegetable consumption and physical inactivity was associated with an increase of 12% (ARR 1.12, 95% CI 1.08, 1.17) and 11% (ARR 1.11, 95% CI 1.07, 1.16), respectively. When all three variables were included in the same model, a 5% increase in prevalence of obesity, low fruit/vegetable consumption, and physical inactivity was associated with 6%, 8%, and 7% increases in influenza-related hospitalization rates, respectively. CONCLUSIONS: Communities with a greater prevalence of obesity were more likely to have high influenza-related hospitalization rates. Similarly, less physically active populations, with lower fruit/vegetable consumption, tended to have higher influenza-related hospitalization rates, even after accounting for obesity.

Neighborhood determinants of 2009 pandemic A/H1N1 influenza vaccination in Montreal, Quebec, Canada.

Neighborhood-level analyses of influenza vaccination can identify the characteristics of vulnerable neighborhoods, which can inform public health strategy for future pandemics. In this study, the authors analyzed rates of 2009 pandemic A/H1N1 influenza vaccination in Montreal, Quebec, Canada, using individual-level vaccination records from a vaccination registry with census, survey, and administrative data to estimate the population at risk. The neighborhood socioeconomic and demographic determinants of vaccination were identified using Bayesian ecologic logistic regression, with random effects to account for spatial autocorrelation. A total of 918,773 (49.9%) Montreal residents were vaccinated against pandemic A/H1N1 influenza from October 22, 2009, through April 8, 2010. Coverage was greatest among females, children under age 5 years, and health-care workers. Neighborhood vaccine coverage ranged from 33.6% to 71.0%. Neighborhoods with high percentages of immigrants (per 5% increase, odds ratio = 0.90, 95% credible interval: 0.86, 0.95) and material deprivation (per 1-unit increase in deprivation score, odds ratio = 0.93, 95% credible interval: 0.88, 0.98) had lower vaccine coverage. Half of the Montreal population was vaccinated; however, considerable heterogeneity in coverage was observed between neighborhoods and subgroups. In future vaccination campaigns, neighborhoods that are materially deprived or have high percentages of immigrants may benefit from focused interventions.

HAIKU: A Semantic Framework for Surveillance of Healthcare-Associated Infections.

Healthcare-Associated Infections (HAI) impose a substantial health and financial burden. Surveillance for HAI is essential to develop and evaluate prevention and control efforts. The traditional approaches to HAI surveillance are often limited in scope and efficiency by the need to manually obtain and integrate data from disparate paper charts and information systems. The considerable effort required for discovery and integration of relevant data from multiple sources limits the current effectiveness of HAI surveillance. Knowledge-based systems can address this problem of contextualizing data to support integration and reasoning. In order to facilitate knowledge-based decision making in this area, availability of a reference vocabulary is crucial. The existing terminologies in this domain still suffer from inconsistencies and confusion in different medical/clinical practices, and there is a need for their further improvement and clarification. To develop a common understanding of the infection control domain and to achieve data interoperability in the area of hospital-acquired infections, we present the HAI Ontology (HAIO) to improve knowledge processing in pervasive healthcare environments, as part of the HAIKU (Hospital Acquired Infections - Knowledge in Use) system. The HAIKU framework assists physicians and infection control practitioners by providing recommendations regarding case detection, risk stratification and identification of diagnostic factors.

Effect of expanded US recommendations for seasonal influenza vaccination: comparison of two pediatric emergency departments in the United States and Canada.

BACKGROUND: Starting in the 2006/2007 influenza season, the US Advisory Committee on Immunization Practices expanded its recommendations for seasonal influenza vaccination to include healthy children aged 24-59 months. The parallel Canadian organization, the National Advisory Committee on Immunization, did not at that time issue a similar recommendation, thereby creating a natural experiment to evaluate the effect of the policy in the United States. METHODS: We examined data for 2000/2001 through 2008/2009 and estimated relative changes in visits to the emergency department for influenza-like illness at two pediatric hospitals, one in Boston, Massachusetts, and the other in Montréal, Quebec, following the US policy change. Models were adjusted for virologic factors, seasonal trends and all-cause utilization of the emergency department. RESULTS: Of 1 043 989 visits to the emergency departments of the two hospitals for any reason during the study period, 114 657 visits were related to influenza-like illness. Adjusted models estimated a 34% decline in rates of influenza-like illness among children two to four years old in the US hospital relative to the Canadian hospital (rate ratio 0.66, 95% confidence interval 0.58-0.75) following the 2006 policy change of the Advisory Committee on Immunization Practices. This was accompanied by more modest declines of 11% to 18% for the other age groups studied. INTERPRETATION: The divergence in influenza rates among children in the US and Canadian sample populations after institution of the US policy to vaccinate children two to four years of age is evidence that the recommendation of the US Advisory Committee on Immunization Practices resulted in a reduction in influenza-related morbidity in the target group and may have indirectly affected other pediatric age groups. Provincial adoption of the 2010 recommendation of the National Advisory Committee on Immunization in Canada to vaccinate children two to four years of age might positively affect influenza morbidity in Canada.

Socio-economic disparities in the burden of seasonal influenza: the effect of social and material deprivation on rates of influenza infection.

BACKGROUND: There is little empirical evidence in support of a relationship between rates of influenza infection and level of material deprivation (i.e., lack of access to goods and services) and social deprivation (i.e. lack of social cohesion and support). METHOD: Using validated population-level indices of material and social deprivation and medical billing claims for outpatient clinic and emergency department visits for influenza from 1996 to 2006, we assessed the relationship between neighbourhood rates of influenza and neighbourhood levels of deprivation using Bayesian ecological regression models. Then, by pooling data from neighbourhoods in the top decile (i.e., most deprived) and the bottom decile, we compared rates in the most deprived populations to the least deprived populations using age- and sex-standardized rate ratios. RESULTS: Deprivation scores ranged from one to five with five representing the highest level of deprivation. We found a 21% reduction in rates for every 1 unit increase in social deprivation score (rate ratio [RR] 0.79, 95% Credible Interval [CrI] 0.66, 0.97). There was little evidence of a meaningful linear relationship with material deprivation (RR 1.06, 95% CrI 0.93, 1.24). However, relative to neighbourhoods with deprivation scores in the bottom decile, those in the top decile (i.e., most materially deprived) had substantially higher rates (RR 2.02, 95% Confidence Interval 1.99, 2.05). CONCLUSION: Though it is hypothesized that social and material deprivation increase risk of acute respiratory infection, we found decreasing healthcare utilization rates for influenza with increasing social deprivation. This finding may be explained by the fewer social contacts and, thus, fewer influenza exposure opportunities of the socially deprived. Though there was no evidence of a linear relationship with material deprivation, when comparing the least to the most materially deprived populations, we observed higher rates in the most materially deprived populations.

Outpatient physician billing data for age and setting specific syndromic surveillance of influenza-like illnesses.

Syndromic surveillance is a novel automated approach to monitoring influenza activity, but there is no consensus regarding the most informative data sources for use within such a system. By comparing physician billing data from Quebec, Canada and hospital admission records, we assessed the timeliness of medical visits for influenza-like illnesses (ILI) to two types of outpatient healthcare settings. Overall, ILI visits by children aged 5-17 years at community-based settings were the most strongly correlated with hospital admissions and gave the greatest lead over hospital admissions. However, a degree of year-to-year variation suggests that syndromic surveillance of influenza should not focus on just a single subgroup. These findings reveal the richness of these real-time data for epidemic monitoring and demonstrate the flexibility of syndromic surveillance. By using real-time data, an evolving epidemic can be rapidly characterized by its epidemiological patterns, which is not possible with traditional surveillance systems.