The objective of this study was to develop a model to estimate the hospitalization burden attributable to influenza, respiratory syncytial virus (RSV), enterovirus (EV), human metapneumovirus (HMPV), human parainfluenza virus (HPIV), and other respiratory viruses (OV) in Canada. A Poisson regression model was developed using respiratory hospitalization administrative data for the seasons 2010/2011 to 2018/2019. The estimated average seasonal number of respiratory hospitalizations attributable to influenza was 15,000 in Canada (rate 43.4 hospitalizations per 100,000 population [95

The literature on best practices for evidence-informed decision-making has seen considerable growth from both knowledge users tasked with assessing the quality of the evidence and knowledge creators wishing to make a stronger contribution to evidence-based decisions. The knowledge translation process is highly dependent on the quality of the original research study, the completeness of the reporting, and the cross-discipline accessibility. The aim of this chapter is to introduce scientists interested in using their statistical, analytical, mathematical, or modelling skills to contribute evidence for evidence-informed decisions in public health to the various guideline systems used in the knowledge translation process. As these guideline systems are extensive, we have provided only an overview, highlighting recommendations of potential interest to researchers reporting statistical estimates, analytical results, or modelled output. We have also included a few references to published reporting recommendations by these analytical groups. Knowledge translation does not end with a policy decision. Public health messaging is needed to inform and often persuade the general public to take the appropriate action. We have included a discussion on public communication, as media coverage of research studies can often be traced to the abstracts of the original study.

Importance Achievement of the World Health Organization (WHO) target of eliminating hepatitis C virus (HCV) by 2030 will require an increase in key services, including harm reduction, HCV screening, and HCV treatment initiatives in member countries. These data are not available for Canada but are important for informing a national HCV elimination strategy. Objective To use a decision analytical model to explore the association of different treatment strategies with HCV epidemiology and HCV-associated mortality in Canada and to assess the levels of service increase needed to meet the WHO elimination targets by 2030. Design, Setting, and Participants Study participants in this decision analytical model included individuals with hepatitis C virus infection in Canada. Five HCV treatment scenarios (optimistic, very aggressive, aggressive, gradual decrease, and rapid decrease) were applied using a previously validated Markov-type mathematical model. The optimistic and very aggressive treatment scenarios modeled a sustained annual treatment of 10 200 persons and 14 000 persons, respectively, from 2018 to 2030. The aggressive, gradual decrease, and rapid decrease scenarios assessed decreases in treatment uptake from 14 000 persons to 10 000 persons per year, 12 000 persons to 8500 persons per year, and 12 000 persons to 4500 persons per year, respectively, between 2018 and 2030. Main Outcomes and Measures Hepatitis C virus prevalence and HCV-associated health outcomes were assessed for each of the 5 treatment scenarios with the goal of identifying strategies to achieve HCV elimination by 2030. Results An estimated mean 180 142 persons (95% CI, 122 786-196 862 persons) in Canada had chronic HCV infection at the end of 2017. The optimistic and gradual decrease scenarios estimated a decrease in HCV prevalence from 180 142 persons to 37 246 persons and 37 721 persons, respectively, by 2030. Relative to 2015, this decrease in HCV prevalence was associated with 74%, 69%, and 69% reductions in the prevalence of decompensated cirrhosis, hepatocellular carcinoma, and liver-associated mortality, respectively, leading to HCV elimination by 2030. More aggressive treatment uptake (very aggressive scenario) could result in goal achievement up to 3 years earlier than 2030, although a rapid decrease in the initiation of treatment (rapid decrease scenario) would preclude Canada from reaching the HCV elimination goal by 2030. Conclusions and Relevance The study findings suggest that Canada could meet the WHO goals for HCV elimination by 2030 by sustaining the current national HCV treatment rate during the next decade. This target will not be achieved if treatment uptake is allowed to decrease rapidly.

Background A regression‐based study design has commonly been used to estimate the influenza burden; however, these estimates are not timely and many countries lack sufficient virological data. Alternative approaches that would permit a timelier assessment of the burden, including a sentinel surveillance approach recommended by the World Health Organization (WHO), have been proposed. We aimed to estimate the hospitalization burden attributable to influenza, respiratory syncytial virus (RSV), and other respiratory viruses (ORV) and to assess both the completeness of viral identification among respiratory inpatients in Canada and the implications of adopting other approaches. Methods Respiratory inpatient records were extracted from the Canadian Discharge Abstract Database from 2003 to 2014. A regression model was used to estimate excess respiratory hospitalizations attributable to influenza, RSV, and ORV by age group and diagnostic category and compare these estimates with the number with a respiratory viral identification. Results An estimated 33 (95% CI: 29, 38), 27 (95% CI: 22, 33), and 27 (95% CI: 18, 36) hospitalizations per 100 000 population per year were attributed to influenza, RSV, and ORV, respectively. An influenza virus was identified in an estimated 78% (95% CI: 75, 81) and 17% (95% CI: 15, 21) of respiratory hospitalizations attributed to influenza for children and adults, respectively, and 75% of influenza‐attributed hospitalizations had an ARI diagnosis. Conclusions Hospitalization rates with respiratory viral identification still underestimate the burden. Approaches based on acute respiratory case definitions will likely underestimate the burden as well, although each proposed method should be compared with regression‐based estimates of influenza‐attributed burden as a way of assessing their validity.

Background While combination antiretroviral therapy (cART) has significantly improved survival times for persons diagnosed with HIV, estimation of life expectancy (LE) for this cohort remains a challenge, as mortality rates are a function of both time since diagnosis and age, and mortality rates for the oldest age groups may not be available. Methods A validated case-finding algorithm for HIV was used to update the cohort of HIV-positive adults who had entered care in Ontario, Canada as of 2012. The Chiang II abridged life table algorithm was modified to use mortality rates stratified by time since entering the cohort and to include various methods for extrapolation of the excess HIV mortality rates to older age groups. Results As of 2012, there were approximately 15,000 adults in care for HIV in Ontario. The crude all-cause mortality rate declined from 2.6% (95%CI 2.3, 2.9) per year in 2000 to 1.3% (1.2, 1.5) in 2012. Mortality rates were elevated for the first year of care compared to subsequent years (rate ratio of 2.6 (95% CI 2.3, 3.1)). LE for a 20-year old living in Ontario was 62 years (expected age at death is 82), while LE for a 20-year old with HIV was estimated to be reduced to 47 years, for a loss of 15 years of life. Ignoring the higher mortality rates among new cases introduced a modest bias of 1.5 additional years of life lost. In comparison, using 55+ as the open-ended age group was a major source of bias, adding 11 years to the calculated LE. Conclusions Use of age limits less than the expected age at death for the open-ended age group significantly overstates the estimated LE and is not recommended. The Chiang II method easily accommodated input of stratified mortality rates and extrapolation of excess mortality rates.

OBJECTIVE:The acellular pertussis vaccine was introduced into the routine childhood immunization schedule across Canada in 1997-98 and adolescent booster doses were added between 1999 and 2005. We sought to assess the impact of these changes on infant pertussis hospitalizations and admissions to intensive care units (ICU) in Canada. METHODS:Hospitalizations with a primary diagnosis of pertussis were extracted from the Canadian Discharge Abstract Database (DAD) for cases with hospital discharge dates between 1981 and 2016 using relevant ICD-9 and ICD-10 codes. Only cases with age less than one year at time of admission were included. Disease severity was assessed by admission to ICU. Cases were categorized into two periods: pre-program implementation period (1981-1995) and the post-program implementation period (2006-2016). Incidence rates, risk ratios, and rate differences were calculated for each period and comparisons for the two periods were done using chi-squared and t-tests. Quasi Poisson analysis was used to investigate trends. RESULTS:When comparing the pre- and post-implementation periods, the average annual hospitalization rates for infants less than 1 year declined from 165.1 (95% CI 161.3, 168.9) to 33.6 (95% CI 31.6, 35.6) pertussis-related admissions per 100,000 population, with a corresponding reduction in the risk ratio of 4.9 (95% CI 4.6, 5.2). The risk of admission into an ICU was 1.58 times higher in the pre- versus post-implementation period while the highest reduction in average annual hospitalizations was 263.3 admissions per 100,000 population in infants 2 months of age. In the post-implementation period, infants less than 1 month of age had the highest average annual hospitalization rate at 126.6 (95% CI 113.1, 140.1) hospitalizations per 100,000 infants. CONCLUSION:Infant pertussis hospitalizations have reduced greatly over time. Infants under 2 months of age remain the most at-risk age group for hospitalization and admission to ICU.

BACKGROUNDS:Hospitalizations associated with hepatitis C virus (HCV) infection and liver disease increased on average by 6.0% per year from 2004 to 2010 in Canada and were projected (in 2010) to increase by another 4% by 2016. The first generation of direct-acting antivirals (DAAs) became available in 2012. In 2014, a second generation of effective and well-tolerated DAA therapy was authorized in Canada. The impact of DAA therapy on the HCV-associated disease burden in Canada has not been documented.OBJECTIVES:To assess the potential impact of DAA therapy on the disease burden by a) comparing the actual hospitalization rates associated with HCV infection and liver disease following the introduction of DAAs in Canada with the 2010 baseline projection and b) documenting the associated uptake of anti-HCV therapy.METHODS:The hospital records of inpatients diagnosed with chronic HCV and chronic liver disease were extracted from the Canadian Discharge Abstract Database (DAD) by fiscal year for 2004-2016. We compared the actual number of hospitalizations to the baseline projection by year and for selected 5-year birth cohorts (1925-1989). The monthly number of new prescriptions for anti-HCV regimens was extracted from the IQVIA CDH CompuScript database (formerly IMS Health), aggregated to annual levels by age group and compared with hospitalization trends.RESULTS:Compared to the baseline projection, there was a slight reduction in hospitalizations in 2014/15 and 2015/16. This slight reduction was followed by a more significant decline in 2016/17 (32% below expected; 95% confidence interval [CI]: 27%-37%). The largest declines were observed for patients born before 1960 (age 55 or older) at 40% below expected in 2016/17. The number of new anti-HCV prescriptions increased from 5,484 in fiscal year 2012/13 to a peak of 17,775 in 2015/2016. The number of new prescriptions corresponds to approximately 1.3 and five times the number of hospitalizations in 2012/13 and 2015/16, respectively.CONCLUSIONS:In Canada there has been a modest decrease in HCV and liver-related hospitalizations following a significant increase in uptake of second-generation DAAs in 2015. However, the burden is still high. Linked health administrative databases created to monitor the disease burden in the new treatment era should provide additional insight with the linkage of treatment history and disease stage to individual outcomes.

Disease modeling is increasingly being used to evaluate the effect of health intervention strategies, particularly for infectious diseases. However, the utility and application of such models are hampered by the inconsistent use of infectious disease modeling terms between and within disciplines. We sought to standardize the lexicon of infectious disease modeling terms and develop a glossary of terms commonly used in describing models' assumptions, parameters, variables, and outcomes. We combined a comprehensive literature review of relevant terms with an online forum discussion in a virtual community of practice, mod4PH (Modeling for Public Health). Using a convergent discussion process and consensus amongst the members of mod4PH, a glossary of terms was developed as an online resource. We anticipate that the glossary will improve inter- and intradisciplinary communication and will result in a greater uptake and understanding of disease modeling outcomes in heath policy decision-making. We highlight the role of the mod4PH community of practice and the methodologies used in this endeavor to link theory, policy, and practice in the public health domain.

Background Most evaluations of epidemic thresholds for influenza have been limited to internal criteria of the indicator variable. We aimed to initiate discussion on appropriate methods for evaluation and the value of cross-validation in assessing the performance of a candidate indicator for influenza activity. Methods Hospital records of in-patients with a diagnosis of confirmed influenza were extracted from the Canadian Discharge Abstract Database from 2003 to 2011 and aggregated to weekly and regional levels, yielding 7 seasons and 4 regions for evaluation (excluding the 2009 pandemic period). An alert created from the weekly time-series of influenza positive laboratory tests (FluWatch, Public Health Agency of Canada) was evaluated against influenza-confirmed hospitalizations on 5 criteria: lead/lag timing; proportion of influenza hospitalizations covered by the alert period; average length of the influenza alert period; continuity of the alert period and length of the pre-peak alert period. Results Influenza hospitalizations led laboratory positive tests an average of only 1.6 (95% CI: -1.5, 4.7) days. However, the difference in timing exceeded 1 week and was statistically significant at the significance level of 0.01 in 5 out of 28 regional seasons. An alert based primarily on 5% positivity and 15 positive tests produced an average alert period of 16.6 weeks. After allowing for a reporting delay of 2 weeks, the alert period included 80% of all influenza-confirmed hospitalizations. For 20 out of the 28 (71%) seasons, the first alert would have been signalled at least 3 weeks (in real time) prior to the week with maximum number of influenza hospitalizations. Conclusions Virological data collected from laboratories was a good indicator of influenza activity with the resulting alert covering most influenza hospitalizations and providing a reasonable pre-peak warning at the regional level. Though differences in timing were statistically significant, neither time-series consistently led the other.

BACKGROUND:Much of the recent increase in hospital admission rates and mortality associated with hepatitis C in Canada is believed to be because of a higher prevalence of hepatitis C virus infection among those born between 1945 and 1965 (the baby boomer generation). We explored the effects of birth cohort on the rates of and projected trends in hospital admissions associated with hepatitis C.METHODS:The hospital records of 17 344 inpatients with a diagnosis of chronic hepatitis C and liver disease, including liver cancer, were extracted from the Canadian Discharge Abstract Database for April 2004 to March 2011. For each 5-year birth cohort from 1915 to 1984, regression analysis was used to estimate the temporal trends associated with the average age of the cohort during the study period. Future hospital admissions were predicted based on the assumption that past trends would continue.RESULTS:Hospital admissions associated with hepatitis C and liver disease increased an average of 6.0% (95% confidence interval [CI] 4.4%-7.7%) a year over the study period. As of 2010, hospital admission rates were highest for the 1950-1954 and 1955-1959 birth cohorts, at 17.6 (95% CI 13.2-23.5) and 13.7 (95% CI 10.3-18.2) times the rate for the 1970-1974 birth cohort. The corresponding same-age rate ratios predicted under a status quo scenario were 3.6 (95% CI 2.3-4.9) and 3.4 (95% CI 2.1-4.7). Same-age rate ratios were significantly higher for the four 5-year birth cohorts between 1950 and 1969 compared with other birth cohorts.INTERPRETATION:Hospital admissions associated with chronic hepatitis C and liver disease were significantly higher for the 1950-1954 and 1955-1959 birth cohorts than for most other birth cohorts. Without further interventions, the disease burden associated with hepatitis C will continue to increase for most birth cohorts, likely peaking after age 70 years. The substantial disease burden emerging in younger birth cohorts should be monitored.

OBJECTIVES:Weekly influenza-like illness (ILI) consultation rates are an integral part of influenza surveillance. However, in most health care settings, only a small proportion of true influenza cases are clinically diagnosed as influenza or ILI. The primary objective of this study was to estimate the number and rate of visits to the emergency department (ED) that are attributable to seasonal and pandemic influenza and to describe the effect of influenza on the ED by age, diagnostic categories, and visit disposition. A secondary objective was to assess the weekly "real-time" time series of ILI ED visits as an indicator of the full burden due to influenza.METHODS:The authors performed an ecologic analysis of ED records extracted from the National Ambulatory Care Reporting System (NARCS) database for the province of Ontario, Canada, from September 2003 to March 2010 and stratified by diagnostic characteristics (International Classification of Diseases, 10th Revision [ICD-10]), age, and visit disposition. A regression model was used to estimate the seasonal baseline. The weekly number of influenza-attributable ED visits was calculated as the difference between the weekly number of visits predicted by the statistical model and the estimated baseline.RESULTS:The estimated rate of ED visits attributable to influenza was elevated during the H1N1/2009 pandemic period at 1,000 per 100,000 (95% confidence interval [CI] = 920 to 1,100) population compared to an average annual rate of 500 per 100,000 (95% CI = 450 to 550) for seasonal influenza. ILI or influenza was clinically diagnosed in one of 2.6 (38%) and one of 14 (7%) of these visits, respectively. While the ILI or clinical influenza diagnosis was the diagnosis most specific to influenza, only 87% and 58% of the clinically diagnosed ILI or influenza visits for pandemic and seasonal influenza, respectively, were likely directly due to an influenza infection. Rates for ILI ED visits were highest for younger age groups, while the likelihood of admission to hospital was highest in older persons. During periods of seasonal influenza activity, there was a significant increase in the number of persons who registered with nonrespiratory complaints, but left without being seen. This effect was more pronounced during the 2009 pandemic. The ratio of influenza-attributed respiratory visits to influenza-attributed ILI visits varied from 2.4:1 for the fall H1N1/2009 wave to 9:1 for the 2003/04 influenza A(H3N2) season and 28:1 for the 2007/08 H1N1 season.CONCLUSIONS:Influenza appears to have had a much larger effect on ED visits than was captured by clinical diagnoses of influenza or ILI. Throughout the study period, ILI ED visits were strongly associated with excess respiratory complaints. However, the relationship between ILI ED visits and the estimated effect of influenza on ED visits was not consistent enough from year to year to predict the effect of influenza on the ED or downstream in-hospital resource requirements.

BACKGROUND:Poisson regression modelling has been widely used to estimate the disease burden attributable to influenza, though not without concerns that some of the excess burden could be due to other causes. This study aims to provide annual estimates of the mortality and hospitalization burden attributable to both seasonal influenza and the 2009 A/H1N1 pandemic influenza for Canada, and to discuss issues related to the reliability of these estimates.METHODS:Weekly time-series for all-cause mortality and regression models were used to estimate the number of deaths in Canada attributable to influenza from September 1992 to December 2009. To assess their robustness, the annual estimates derived from different parameterizations of the regression model for all-cause mortality were compared. In addition, the association between the annual estimates for mortality and hospitalization by age group, underlying cause of death or primary reason for admission and discharge status is discussed.RESULTS:The crude influenza-attributed mortality rate based on all-cause mortality and averaged over 17 influenza seasons prior to the 2009 A/H1N1 pandemic was 11.3 (95%CI, 10.5 - 12.1) deaths per 100 000 population per year, or an average of 3,500 (95%CI, 3,200 - 3,700) deaths per year attributable to seasonal influenza. The estimated annual rates ranged from undetectable at the ecological level to more than 6000 deaths per year over the three A/Sydney seasons. In comparison, we attributed an estimated 740 deaths (95%CI, 350-1500) to A(H1N1)pdm09. Annual estimates from different model parameterizations were strongly correlated, as were estimates for mortality and morbidity; the higher A(H1N1)pdm09 burden in younger age groups was the most notable exception.INTERPRETATION:With the exception of some of the Serfling models, differences in the ecological estimates of the disease burden attributable to influenza were small in comparison to the variation in disease burden from one season to another.

BACKGROUND:The Canadian National Antiviral Stockpile (NAS) contains treatment for 17.5% of Canadians. This assumes no concurrent intervention strategies and no wastage due to non-influenza respiratory infections. A dynamic model can provide a mechanism to consider complex scenarios to support decisions regarding the optimal NAS size under uncertainty.METHODS:We developed a dynamic model for pandemic influenza in Canada that is structured by age and risk to calculate the demand for antivirals to treat persons with pandemic influenza under a wide-range of scenarios that incorporated transmission dynamics, disease severity, and intervention strategies. The anticipated per capita number of acute respiratory infections due to viruses other than influenza was estimated for the full pandemic period from surveys based on criteria to identify potential respiratory infections.RESULTS:Our results demonstrate that up to two thirds of the population could develop respiratory symptoms as a result of infection with a pandemic strain. In the case of perfect antiviral allocation, up to 39.8% of the population could request antiviral treatment. As transmission dynamics, severity and timing of the emergence of a novel influenza strain are unknown, the sensitivity analysis produced considerable variation in potential demand (median: 11%, IQR: 2-21%). If the next pandemic strain emerges in late spring or summer and a vaccine is available before the anticipated fall wave, the median prediction was reduced to 6% and IQR to 0.7-14%. Under the strategy of offering empirical treatment to all patients with influenza like symptoms who present for care, demand could increase to between 65 and 144%.CONCLUSIONS:The demand for antivirals during a pandemic is uncertain. Unless an accurate, timely and cost-effective test is available to identify influenza cases, demand for antivirals from persons infected with other respiratory viruses will be substantial and have a significant impact on the NAS.

OBJECTIVE:We aimed to assess the potential prevention benefits of HIV treatment as prevention (TasP) in resource-rich countries and examine the potential interactions between TasP and other prevention strategies by reviewing mathematical models of TasP. METHOD:Multiple databases were searched for mathematical models published in the previous 5 years (from July 2007 to July 2012). The nine models located were set in Canada, Australia and the United States. RESULTS:These models' predictions suggested that the impact of expanding treatment rates on expected new infections could range widely, from no decrease to a decrease of 76%, depending on the time horizon, assumptions and the form of TasP modeled. Increased testing, reducing sexually transmitted infections and reducing risky practices were also predicted to be important strategies for decreasing expected new infections. Sensitivity analysis suggests that current uncertainties such as the effectiveness of highly active antiretroviral therapy outside of heterosexual transmission, less than ideal adherence, and risk compensation, could impact on the success of TasP at the population level. CONCLUSION:The results from large scale pilots and community randomized controlled trials will be useful in demonstrating how well this prevention approach works in real world settings, and in identifying the factors that are needed to support its effectiveness.

Please cite this paper as: Schanzer et al. (2012) Statistical estimates of respiratory admissions attributable to seasonal and pandemic influenza for Canada. Influenza and Other Respiratory Viruses DOI: 10.1111/irv.12011.Background The number of admissions to hospital for which influenza is laboratory confirmed is considered to be a substantial underestimate of the true number of admissions due to an influenza infection. During the 2009 pandemic, testing for influenza in hospitalized patients was a priority, but the ascertainment rate remains uncertain.Methods The discharge abstracts of persons admitted with any respiratory condition were extracted from the Canadian Discharge Abstract Database, for April 2003–March 2010. Stratified, weekly admissions were modeled as a function of viral activity, seasonality, and trend using Poisson regression models.Results An estimated 1 out of every 6·4 admissions attributable to seasonal influenza (2003–April 2009) were coded to J10 (influenza virus identified). During the 2009 pandemic (May–March 2010), the influenza virus was identified in 1 of 1·6 admissions (95% CI, 1·5–1·7) attributed to the pandemic strain. Compared with previous H1N1 seasons (2007/08, 2008/09), the influenza‐attributed hospitalization rate for persons <65 years was approximately six times higher during the 2009 H1N1 pandemic, whereas for persons 75 years or older, the pandemic rate was approximately fivefold lower.Conclusions Case ascertainment was much improved during the pandemic period, with under ascertainment of admissions due to H1N1/2009 limited primarily to patients with a diagnosis of pneumonia.

BACKGROUND: As observed during the 2009 pandemic, a novel influenza virus can spread globally before the epidemic peaks locally. As consistencies in the relative timing and direction of spread could form the basis for an early alert system, the objectives of this study were to use the case-based reporting system for laboratory confirmed influenza from the Canadian FluWatch surveillance program to identify the geographic scale at which spatial synchrony exists and then to describe the geographic patterns of influenza A virus across Canada and in relationship to activity in the United States (US). METHODOLOGY/PRINCIPAL FINDINGS: Weekly laboratory confirmations for influenza A were obtained from the Canadian FluWatch and the US FluView surveillance programs from 1997/98 to 2006/07. For the six seasons where at least 80% of the specimens were antigenically similar, we identified the epidemic midpoint of the local/regional/provincial epidemics and analyzed trends in the direction of spread. In three out of the six seasons, the epidemic appeared first in Canada. Regional epidemics were more closely synchronized across the US (3-5 weeks) compared to Canada (5-13 weeks), with a slight gradient in timing from the southwest regions in the US to northeast regions of Canada and the US. Cities, as well as rural areas within provinces, usually peaked within a couple of weeks of each other. The anticipated delay in peak activity between large cities and rural areas was not observed. In some mixed influenza A seasons, lack of synchronization sub-provincially was evident. CONCLUSIONS/SIGNIFICANCE: As mixing between regions appears to be too weak to force a consistency in the direction and timing of spread, local laboratory-based surveillance is needed to accurately assess the level of influenza activity in the community. In comparison, mixing between urban communities and adjacent rural areas, and between some communities, may be sufficient to force synchronization.

There is accumulating evidence suggesting that children may drive the spread of influenza epidemics. The objective of this study was to quantify the lead time by age using laboratory-confirmed cases of influenza A for the 1995/1996–2005/2006 seasons from Canadian communities and laboratory-confirmed hospital admissions for the H1N1/2009 pandemic strain. With alignment of the epidemic curves locally before aggregation of cases, slight age-specific differences in the timing of infection became apparent. For seasonal influenza, both the 10–19- and 20–29-year age groups peaked 1 week earlier than other age groups, while during the fall wave of the 2009 pandemic, infections peaked earlier among only the 10–19-year age group. In the H3N2 seasons, infections occurred an average of 3.9 (95% confidence interval: 1.7, 6.1) days earlier in the 20–29-year age group than for youth aged 10–19 years, while during the fall pandemic wave, the 10–19-year age group had a statistically significant lead of 3 days compared with both younger children aged 4–9 years and adults aged 20–29 years (P < 0.0001). This analysis casts doubt on the hypothesis that younger school-age children actually lead influenza epidemic waves.

Background: As many respiratory viruses are responsible for influenza like symptoms, accurate measures of the disease burden are not available and estimates are generally based on statistical methods. The objective of this study was to estimate absenteeism rates and hours lost due to seasonal influenza and compare these estimates with estimates of absenteeism attributable to the two H1N1 pandemic waves that occurred in 2009.Methods: Key absenteeism variables were extracted from Statistics Canada's monthly labour force survey (LFS). Absenteeism and the proportion of hours lost due to own illness or disability were modelled as a function of trend, seasonality and proxy variables for influenza activity from 1998 to 2009.Results: Hours lost due to the H1N1/09 pandemic strain were elevated compared to seasonal influenza, accounting for a loss of 0.2% of potential hours worked annually. In comparison, an estimated 0.08% of hours worked annually were lost due to seasonal influenza illnesses. Absenteeism rates due to influenza were estimated at 12% per year for seasonal influenza over the 1997/98 to 2008/09 seasons, and 13% for the two H1N1/09 pandemic waves. Employees who took time off due to a seasonal influenza infection took an average of 14 hours off. For the pandemic strain, the average absence was 25 hours.Conclusions: This study confirms that absenteeism due to seasonal influenza has typically ranged from 5% to 20%, with higher rates associated with multiple circulating strains. Absenteeism rates for the 2009 pandemic were similar to those occurring for seasonal influenza. Employees took more time off due to the pandemic strain than was typical for seasonal influenza.