Assessment of Treatment Strategies to Achieve Hepatitis C Elimination in Canada Using a Validated Model.

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.

Trends in Canadian infant pertussis hospitalizations in the pre- and post-acellular vaccine era, 1981-2016.

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.

Empirical estimation of life expectancy from a linked health database of adults who entered care for HIV.

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.

Estimates of global seasonal influenza-associated respiratory mortality: a modelling study.

BACKGROUND: Estimates of influenza-associated mortality are important for national and international decision making on public health priorities. Previous estimates of 250 000-500 000 annual influenza deaths are outdated. We updated the estimated number of global annual influenza-associated respiratory deaths using country-specific influenza-associated excess respiratory mortality estimates from 1999-2015. METHODS: We estimated country-specific influenza-associated respiratory excess mortality rates (EMR) for 33 countries using time series log-linear regression models with vital death records and influenza surveillance data. To extrapolate estimates to countries without data, we divided countries into three analytic divisions for three age groups (<65 years, 65-74 years, and ≥75 years) using WHO Global Health Estimate (GHE) respiratory infection mortality rates. We calculated mortality rate ratios (MRR) to account for differences in risk of influenza death across countries by comparing GHE respiratory infection mortality rates from countries without EMR estimates with those with estimates. To calculate death estimates for individual countries within each age-specific analytic division, we multiplied randomly selected mean annual EMRs by the country's MRR and population. Global 95% credible interval (CrI) estimates were obtained from the posterior distribution of the sum of country-specific estimates to represent the range of possible influenza-associated deaths in a season or year. We calculated influenza-associated deaths for children younger than 5 years for 92 countries with high rates of mortality due to respiratory infection using the same methods. FINDINGS: EMR-contributing countries represented 57% of the global population. The estimated mean annual influenza-associated respiratory EMR ranged from 0·1 to 6·4 per 100 000 individuals for people younger than 65 years, 2·9 to 44·0 per 100 000 individuals for people aged between 65 and 74 years, and 17·9 to 223·5 per 100 000 for people older than 75 years. We estimated that 291 243-645 832 seasonal influenza-associated respiratory deaths (4·0-8·8 per 100 000 individuals) occur annually. The highest mortality rates were estimated in sub-Saharan Africa (2·8-16·5 per 100 000 individuals), southeast Asia (3·5-9·2 per 100 000 individuals), and among people aged 75 years or older (51·3-99·4 per 100 000 individuals). For 92 countries, we estimated that among children younger than 5 years, 9243-105 690 influenza-associated respiratory deaths occur annually. INTERPRETATION: These global influenza-associated respiratory mortality estimates are higher than previously reported, suggesting that previous estimates might have underestimated disease burden. The contribution of non-respiratory causes of death to global influenza-associated mortality should be investigated. FUNDING: None.

Burden of influenza, respiratory syncytial virus, and other respiratory viruses and the completeness of respiratory viral identification among respiratory inpatients, Canada, 2003-2014.

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.

Toward Standardizing a Lexicon of Infectious Disease Modeling Terms.

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.

Leading Indicators and the Evaluation of the Performance of Alerts for Influenza Epidemics.

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.

Historical trends and projected hospital admissions for chronic hepatitis C infection in Canada: a birth cohort analysis.

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.

The impact of HIV treatment as prevention in the presence of other prevention strategies: lessons learned from a review of mathematical models set in resource-rich countries.

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.

Estimating influenza deaths in Canada, 1992-2009.

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.

Using a Dynamic Model to Consider Optimal Antiviral Stockpile Size in the Face of Pandemic Influenza Uncertainty.

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.

Impact of seasonal and pandemic influenza on emergency department visits, 2003-2010, Ontario, Canada.

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.

Statistical estimates of respiratory admissions attributable to seasonal and pandemic influenza for Canada.

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.

The geographic synchrony of seasonal influenza: a waves across Canada and the United States.

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.

Age-specific differences in influenza A epidemic curves: do children drive the spread of influenza epidemics?

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.

Statistical estimates of absenteeism attributable to seasonal and pandemic influenza from the Canadian Labour Force Survey.

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.

A composite epidemic curve for seasonal influenza in Canada with an international comparison.

BACKGROUND: Empirical data on laboratory-confirmed seasonal influenza is limited by very low and possibly non-systematic case ascertainment as well as geographical variation. OBJECTIVE: To provide a visual representation of an influenza epidemic at the community and regional level using empirical data and to describe the epidemic characteristics. METHODS: Weekly influenza A confirmations were obtained from the Canadian FluWatch program and American FluView program for the 1997/1998-2006/2007 seasons; 1- year data were also available for Europe (FluNet, WHO). For seasons where at least 80% of the influenza A strains were antigenically similar, a composite epidemic curve was created by centring the local epidemics relative to their epidemic midpoint. RESULTS: The range in timing of the regional peaks varied from 5 to 13 weeks. Once the epidemic curves were centred relative to their peak, the composite epidemic curves were similar for Canada, the United States and Europe, and the epidemic growth rates were similar for most subgroups (city size; regions; H1N1 versus H3N2 seasons). During the exponential growth period, the number of cases increased by a factor of 1.5-2.0 per week, averaging 1.8. Exponential growth was evident approximately 10 weeks before the peak. Evidence of sustained transmission occurred from mid-September to early June. DISCUSSION: The shape of the composite curve created in this study clearly demonstrates a consistency in the epidemic pattern across geographically disparate locales. Laboratory confirmation will likely play an increasing role in the development of better methods for early detection and summary measures of influenza activity.

Estimates of the number of prevalent and incident human immunodeficiency virus (HIV) infections in Canada, 2008.

OBJECTIVE: To estimate the number of prevalent and incident HIV infections in Canada in 2008. METHODS: We applied multiple methods to estimate national HIV prevalence and incidence in Canada, including the workbook method, two statistical modelling methods, and an iterative spreadsheet model. RESULTS: The estimated number of people living with diagnosed or undiagnosed HIV infection (including AIDS) continues to rise, from an estimated 57,000 in 2005 to 65,000 in 2008. Nearly half (48%) of these HIV-infected persons were men who have sex with men (MSM) and 22% were women. An estimated 16,900 persons with prevalent infection (26% of total prevalent infections) were unaware of their HIV-infected status and this proportion varied from an estimated 19% of HIV-infected MSM, to 25% of HIV-infected people who inject drugs, and 35% of HIV-infected heterosexuals. An estimated 3,300 new infections occurred in Canada in 2008, which was about the same as the estimate of 3200 in 2005. Of those new infections, 26% were among women and 12.5% were of Aboriginal descent; in terms of exposure category, MSM continued to comprise the greatest proportion of new infections (44%) and heterosexuals who originated in countries where HIV is endemic comprised 16%. CONCLUSION: HIV incidence in Canada is not decreasing. Aboriginal people and people from HIV-endemic countries continue to be over-represented in Canada's HIV epidemic. People unaware of their HIV infection are a priority for being tested and diagnosed to enable them to take advantage of care services and receive counselling to prevent further spread of HIV.

Estimating sensitivity of laboratory testing for influenza in Canada through modelling.

BACKGROUND: The weekly proportion of laboratory tests that are positive for influenza is used in public health surveillance systems to identify periods of influenza activity. We aimed to estimate the sensitivity of influenza testing in Canada based on results of a national respiratory virus surveillance system. METHODS AND FINDINGS: The weekly number of influenza-negative tests from 1999 to 2006 was modelled as a function of laboratory-confirmed positive tests for influenza, respiratory syncytial virus (RSV), adenovirus and parainfluenza viruses, seasonality, and trend using Poisson regression. Sensitivity was calculated as the number of influenza positive tests divided by the number of influenza positive tests plus the model-estimated number of false negative tests. The sensitivity of influenza testing was estimated to be 33% (95%CI 32-34%), varying from 30-40% depending on the season and region. CONCLUSIONS: The estimated sensitivity of influenza tests reported to this national laboratory surveillance system is considerably less than reported test characteristics for most laboratory tests. A number of factors may explain this difference, including sample quality and specimen procurement issues as well as test characteristics. Improved diagnosis would permit better estimation of the burden of influenza.