Bordetella pertussis in sporadic and outbreak settings in Alberta, Canada, July 2004-December 2012.

BACKGROUND: ProvLab Alberta provides all laboratory testing for Bordetella pertussis including sporadic cases and outbreak investigations through collaborations with provincial public health partners. We describe B. pertussis activity in Alberta from July 2004 to December 2012. METHODS: Laboratory testing for pertussis was analyzed using interpreted laboratory data that was generated by DIAL, a secure web-based platform. Duplicate specimens from the same individual ≤90 days were excluded to generate a case-based dataset. Immunization status of confirmed pertussis cases from the provincial immunization repository was reviewed. RESULTS: Overall, 7.1% of suspected pertussis cases tested positive with a higher positivity rate in outbreak as compared to sporadic setting. Annual variations in sporadic pertussis cases were observed across the province with higher positivity rates in 2005, 2008, 2009 and 2012. A significantly higher positivity rate was observed in a northern region of Alberta. While the positivity rate in sporadic setting was highest in adolescents aged 10 to <15 years old (14.8%), population-based disease burden was highest in young children <5 years old. Of the 81.6% (n = 1,348) pertussis cases with immunization records, 48.3% were up-to-date with immunization. The pertussis cases that were up-to-date with their immunization were older (median age 12.9 years) as compared to those with incomplete (median age 9.7 years) or no pertussis immunization (median age 3.8 years). CONCLUSIONS: Cyclic pattern of annual pertussis activity with geographic variation was observed in Alberta with no obvious case finding effect from outbreak investigations. The high positivity rates in adolescents suggested an underestimation of disease burden in this age group.

Impact of routine real-time PCR testing of imported malaria over 4 years of implementation in a clinical laboratory.

In clinical laboratories, diagnosis of imported malaria is commonly performed by microscopy. However, the volume of specimens is generally low and maintaining proficiency in reading blood smears, particularly at the species level, is challenging in this setting. To address this problem, the Provincial Laboratory for Public Health (ProvLab) in Alberta, Canada, implemented real-time PCR for routine confirmation of all smear-positive samples in the province. Here we report our experience over a 4-year period (2008 to 2012) with this new diagnostic algorithm. While detection of Plasmodium falciparum by microscopy alone was accurate, real-time PCR served as an important adjunct to microscopy for the identification of non-falciparum species. In 18% of cases, the result was reported as non-falciparum or the species could not be identified by microscopy alone, and in all cases, the species was resolved by real-time PCR. In another 4% of cases, the species was misidentified by microscopy. To enhance surveillance for malaria, we integrated our demographic, clinical, and laboratory data into a new system developed by the Canadian Network for Public Health Intelligence, called the Malaria System for Online Surveillance (SOS). Using this application, we characterized our patient populations and travel history to identify risk factors associated with malaria infection abroad.

Swine influenza test results from animal health laboratories in Canada.

Due to its infrastructure and partnerships the Canadian Animal Health Surveillance Network was able to rapidly collect test results from 9 Canadian laboratories that were conducting primary testing for influenza on swine-origin samples, in response to the threat posed by the pandemic H1N1 influenza virus in 2009.

Résultats des tests de la grippe porcine provenant des laboratoires de santé animale au Canada. En raison de son infrastructure et de partenariats, le Réseau canadien de surveillance zoosanitaire a été capable de recueillir rapidement les résultats de tests de 9 laboratoires canadiens qui réalisaient des tests primaires pour la grippe sur des échantillons d'origine porcine, en réponse à la menace présentée par le virus de l'influenza H1N1 pandémique en 2009.(Traduit par Isabelle Vallières).

Innovative technology and established partnerships-a recipe for rapid adaptability under emerging pandemic conditions.

Background: Aided by a collaborative partnership dating back to 2011, the Canadian Network for Public Health Intelligence (CNPHI) and the Canadian Paediatric Surveillance Program (CPSP) quickly undertook substantial enhancements to the CPSP's data collection instruments on the CNPHI platform to characterize the impacts of the coronavirus disease 2019 (COVID-19) on children and youth in Canada. Faced with an emerging public health threat with impacts yet unknown, the objective of the intervention was to rapidly complete enhancements to existing data collection and analytical tools to enable the CPSP's ability to characterize the impacts of COVID-19 in Canadian children and youth. Intervention: Reporting frequency from CPSP's network of paediatric practitioners was increased from monthly to weekly, and the flexibility of detailed case data collection was substantially enhanced using complex survey instruments, interactively designed using CNPHI's Web Data technology. To ensure their data collection proceeded along all required lines of surveillance, CPSP's data collection tools were enhanced to collect demographic, epidemiological, microbiological and clinical data including comorbidities of cases identified. Outcomes: Less than a month after the World Health Organization declared the COVID-19 pandemic, CPSP was able to start collecting detailed weekly case data on emerging cases of COVID-19 among Canadian children and youth. By May 2020, CPSP was able to launch a detailed study, supporting research into potential risk factors for severe COVID-19-related illness in children and youth. Conclusion: In response to a novel public health threat, CNPHI and CPSP were able to implement rapid adaptations and enhancements to existing data collection instruments while fortifying their preparedness to do the same in the future, when needed. With innovative and agile technologies at the ready, this experience helps to emphasize the importance of established collaborative partnerships across public health disciplines as a factor contributing to preparedness and agility to respond to the unforeseen. Canadian Network for Public Health Intelligence's Web Data technology showed agile adaptability and a capacity for complex and detailed data collection, supporting timely surveillance and response.

Syndromic surveillance performance in Canada throughout the COVID-19 pandemic, March 1, 2020 to March 4, 2023.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for robust surveillance of respiratory viruses. Syndromic surveillance continues to be an important surveillance component recommended by the World Health Organization (WHO). While FluWatchers, Canada's syndromic surveillance system, has been in place since 2015, the COVID-19 pandemic provided a valuable opportunity to expand the program's scope and underlying technology infrastructure. Following some structural changes to FluWatchers syndromic questionnaire, participants are now able to contribute valuable data to the non-specific surveillance of respiratory virus activity across Canada. This article examines the performance of FluWatchers' syndromic surveillance over the three years of the COVID-19 pandemic in Canada. More specifically, this article examines FluWatchers' performance with respect to the correlation between the FluWatchers influenza-like illness (ILI) and acute respiratory infection (ARI) indicators and total respiratory virus detections (RVDs) in Canada, including influenza, respiratory syncytial virus (RSV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and other respiratory viruses.

Overview of Canada's Antimicrobial Resistance Network (AMRNet): A data-driven One Health approach to antimicrobial resistance surveillance.

The Antimicrobial Resistance Network (AMRNet) is a laboratory-based antimicrobial resistance (AMR) surveillance system under development at the Public Health Agency of Canada's (PHAC's) National Microbiology Laboratory. The AMRNet surveillance system captures information on antimicrobial susceptibility testing from clinical and veterinary laboratories including both public and private facilities. In the future, the AMRNet system will also capture relevant data from existing PHAC surveillance systems for AMR including the Canadian Integrated Program for Antimicrobial Resistance Surveillance, the Canadian Nosocomial Infection Surveillance Program and the Enhanced Surveillance of Antimicrobial-Resistant Gonorrhea program, and contribute to the Canadian Antimicrobial Resistance Surveillance System. AMRNet's integrated "One Health" approach will allow health professionals and researchers to take a multi-dimensional perspective of AMR in both human and animal health in Canada and will make Canada a leader in AMR surveillance. AMRNet is a collaboration between PHAC, provincial and territorial public health organizations as well as clinical and veterinary laboratories across the country. As part of a phased rollout, AMRNet is now collecting human clinical data from three provinces, from both inpatients and outpatients. Ultimately, AMRNet aims to capture all antimicrobial susceptibility testing results from all bacterial and fungal pathogens across Canada. This article describes the AMRNet surveillance system, including program objectives, system structure and the data collected. The integration of human and animal data in AMRNet will inform One Health responses to AMR issues. The capacity to collect and to disseminate data to stakeholders in real time is a critical step to addressing emerging AMR issues in Canada.

Determination of the relative economic impact of different molecular-based laboratory algorithms for respiratory viral pathogen detection, including Pandemic (H1N1), using a secure web based platform.

BACKGROUND: During period of crisis, laboratory planners may be faced with a need to make operational and clinical decisions in the face of limited information. To avoid this dilemma, our laboratory utilizes a secure web based platform, Data Integration for Alberta Laboratories (DIAL) to make near real-time decisions.This manuscript utilizes the data collected by DIAL as well as laboratory test cost modeling to identify the relative economic impact of four proposed scenarios of testing for Pandemic H1N1 (2009) and other respiratory viral pathogens. METHODS: Historical data was collected from the two waves of the pandemic using DIAL. Four proposed molecular testing scenarios were generated: A) Luminex respiratory virus panel (RVP) first with/without US centers for Disease Control Influenza A Matrix gene assay (CDC-M), B) CDC-M first with/without RVP, C) RVP only, and D) CDC-M only. Relative cost estimates of different testing algorithm were generated from a review of historical costs in the lab and were based on 2009 Canadian dollars. RESULTS: Scenarios A and B had similar costs when the rate of influenza A was low (< 10%) with higher relative cost in Scenario A with increasing incidence. Scenario A provided more information about mixed respiratory virus infection as compared with Scenario B. CONCLUSIONS: No one approach is applicable to all conditions. Testing costs will vary depending on the test volume, prevalence of influenza A strains, as well as other circulating viruses and a more costly algorithm involving a combination of different tests may be chosen to ensure that tests results are returned to the clinician in a quicker manner. Costing should not be the only consideration for determination of laboratory algorithms.

FluWatchers: Evaluation of a crowdsourced influenza-like illness surveillance application for Canadian influenza seasons 2015-2016 to 2018-2019.

BACKGROUND: Sentinel influenza-like illness (ILI) surveillance is an essential component of a comprehensive influenza surveillance program. Community-based ILI surveillance systems that rely solely on sentinel healthcare practices omit important segments of the population, including those who do not seek medical care. Participatory surveillance, which relies on community participation in surveillance, may address some limitations of traditional ILI systems. OBJECTIVE: We aimed to evaluate FluWatchers, a crowdsourced ILI application developed to complement and complete ILI surveillance in Canada. METHODS: Using established frameworks for surveillance evaluations, we assessed the acceptability, reliability, accuracy and usefulness of the FluWatchers system 2015-2016, through 2018-2019. Evaluation indicators were compared against national surveillance indicators of ILI and of laboratory confirmed respiratory virus infections. RESULTS: The acceptability of FluWatchers was demonstrated by growth of 50%-100% in season-over-season participation, and a consistent season-over-season retention of 80%. Reliability was greater for FluWatchers than for our traditional ILI system, although both systems had week-over-week fluctuations in the number of participants responding. FluWatchers' ILI rates had moderate correlation with weekly influenza laboratory detection rates and other winter seasonal respiratory virus detections including respiratory syncytial virus and seasonal coronaviruses. Finally, FluWatchers has demonstrated its usefulness as a source of core FluWatch surveillance information and has the potential to fill data gaps in current programs for influenza surveillance and control. CONCLUSION: FluWatchers is an example of an innovative digital participatory surveillance program that was created to address limitations of traditional ILI surveillance in Canada. It fulfills the surveillance system evaluation criteria of acceptability, reliability, accuracy and usefulness.

Representativeness of the FluWatchers Participatory Disease Surveillance Program 2015-2016 to 2018-2019: How do participants compare with the Canadian population?

BACKGROUND: FluWatch is Canada's national surveillance system that monitors the spread of influenza. Its syndromic surveillance component monitors the spread of influenza-like illness (ILI) in near-real time for signals of unusual or increased activity. Syndromic surveillance data are collected from two main sources: the Sentinel Practitioner ILI Reporting System and FluWatchers.We evaluated the representativeness of the most recent participant population to understand changes in representativeness since 2015, to identify demographic and geographic gaps and correlates/determinants of participation to characterize a typical participant. METHODS: In this serial cross-sectional study, characteristics of participants during four consecutive influenza seasons (2015-2016, 2016-2017, 2017-2018 and 2018-2019) were compared with the 2016 Canadian Census and the 2015-2016, 2016-2017, 2017-2018 and 2018-2019 National Seasonal Influenza Vaccination Coverage Surveys. Associations between demographic factors and the level of user participation were also analyzed among the 2018-2019 FluWatchers population. RESULTS: Infants (0-4 years) and older adults (65 years and older) were under-represented in FluWatchers across all four influenza seasons. Female and urban participants were significantly over-represented. Vaccination coverage remained significantly higher among the FluWatchers populations from the past four influenza seasons across all age groups. Level of participation among FluWatchers was associated with age and vaccination status, but not with sex or geography. Over its four years of implementation, the FluWatchers participant population became more representative of the Canadian population with respect to age and geography (urban/rural and provincial/territorial). CONCLUSION: FluWatchers participants under-represent the tails of Canada's age distribution and over-represent those who engage in health promoting behaviours as indicated by high influenza vaccine coverage, consistent with typical volunteer-based survey response biases. Representativeness would likely improve with targeted recruitment of under-represented groups, such as males, older adults and Canadians living in rural areas.

Seasonality of Respiratory Viruses at Northern Latitudes.

Importance: Every year, respiratory viruses exact a heavy burden on Canadian hospitals during winter months. Generalizable seasonal patterns of respiratory virus transmission may estimate the evolution of SARS-CoV-2 or other emerging pathogens. Objective: To describe the annual and biennial variation in respiratory virus seasonality in a northern climate. Design, Setting, and Participants: This cohort study is an epidemiological assessment using population-based surveillance of patients with medically attended respiratory tract infection from 2005 through 2017 in Alberta, Canada. Incident cases of respiratory virus infection and infant respiratory syncytial virus (RSV) hospitalizations in Alberta were extracted from the Data Integration for Alberta Laboratories platform and Alberta Health Services Discharge Abstract Database, respectively. A deterministic susceptible-infected-recovered-susceptible mathematical model with seasonal forcing function was fitted to the data for each virus. The possible future seasonal course of SARS-CoV-2 in northern latitudes was modeled on the basis of these observations. The analysis was conducted between December 15, 2020, and February 10, 2021. Exposures: Seasonal respiratory pathogens. Main Outcomes and Measures: Incidence (temporal pattern) of respiratory virus infections and RSV hospitalizations. Results: A total of 37 719 incident infections with RSV, human metapneumovirus, or human coronaviruses 229E, NL63, OC43, or HKU1 among 35 375 patients (18 069 [51.1%] male; median [interquartile range], 1.29 [0.42-12.2] years) were documented. A susceptible-infected-recovered-susceptible model mirrored the epidemiological data, including a striking biennial variation with alternating severe and mild winter peaks. Qualitative description of the model and numerical simulations showed that strong seasonal contact rate and temporary immunity lasting 6 to 12 months were sufficient to explain biennial seasonality in these various respiratory viruses. The seasonality of 10 212 hospitalizations among children younger than 5 years with RSV was also explored. The median (interquartile range) rate of hospitalizations per 1000 live births was 18.6 (17.6-19.9) and 11.0 (10.4-11.7) in alternating even (severe) and odd (less-severe) seasons, respectively (P = .001). The hazard of admission was higher for children born in severe (even) seasons compared with those born in less-severe (odd) seasons (hazard ratio, 1.68; 95% CI, 1.61-1.75; P < .001). Conclusions and Relevance: In this modeling study of respiratory viruses in Alberta, Canada, the seasonality followed a pattern estimated by simple mathematical models, which may be informative for anticipating future waves of pandemic SARS-CoV-2.

Bioaerosol and surface sampling for the surveillance of influenza A virus in swine.

Influenza A virus in swine is of significant importance to human and veterinary public health. Environmental sampling techniques that prove practical would enhance surveillance for influenza viruses in swine. The primary objective of this study was to demonstrate the feasibility of bioaerosol and surface sampling for the detection of influenza virus in swine barns with a secondary objective of piloting a mobile application for data collection. Sampling was conducted at a large swine operation between July 2016 and August 2017. Swine oral fluids and surface swabs were collected from multiple rooms. Room-level air samples were collected using four bioaerosol samplers: a low volume polytetrafluoroethylene (PTFE) filter sampler, the National Institute for Occupational Safety and Health's low volume cyclone sampler, a 2-stage Andersen impactor and/or one high volume cyclonic sampler. Samples were analysed using quantitative RT-PCR. Data and results were reported using a mobile data application. Eighty-nine composite oral fluid samples, 70 surface swabs and 122 bioaerosol samples were analysed. Detection rates for influenza virus RNA in swine barn samples were 71.1% for oral fluids, 70.8% for surface swabs and 71.1% for the PTFE sampler. Analysis revealed a statistically significant relationship between the results of the PTFE sampler and the surface swabs with oral fluid results (p < 0.001 and p < 0.01 respectively). In addition, both the PTFE sampler (p < 0.01) and surface swabs (p = 0.03) significantly correlated with, and predicted oral fluid results. Bioaerosol sampling using PTFE samplers is an effective hands-off approach for detecting influenza virus activity among swine. Further study is required for the implementation of this approach for surveillance and risk assessment of circulating influenza viruses of swine origin. In addition, mobile data collection stands to be an invaluable tool in the field by allowing secure, real-time reporting of sample collection and results.

Can coders abstract child maltreatment variables from child welfare administrative data and case narratives for public health surveillance in Canada?

BACKGROUND: Public health surveillance is essential to inform programs that aim to eradicate child maltreatment (CM) and to provide services to children and families. However, collection of CM data imposes a burden on child welfare workers (CWWs). This study assesses the feasibility of hiring coders to abstract the required information from administrative records and case narratives. METHODS: Based on a convenience sample of child welfare data from Manitoba, Canada, two coders abstracted information on 181 alleged CM cases. The coders completed a short web-based questionnaire for each case to identify which of five types of CM had been investigated, level of substantiation for each type, and risk of future CM. The CWWs responsible for each case completed the same questionnaire. Percentages of the occurrence of CM by the three sources were compared. The validity of the coders' classifications was assessed by calculating sensitivity, specificity, and positive and negative predictive values, against the CWWs' classifications as the "gold standard." Cohen's kappa was also calculated. RESULTS: The coders' classifications of physical abuse, sexual abuse and neglect generally matched those of CWWs; for exposure to intimate partner violence, agreement was weak for one coder. Coding of emotional maltreatment and risk investigations could not be evaluated. CONCLUSION: Results were promising. Abstraction was not time-consuming. Differences between coders and CWWs can be largely explained by the administrative data system, child welfare practice, and legislation. Further investigation is required to determine if additional training could improve coders' classifications of CM.

User rating activity within KIWI: A technology for public health event monitoring and early warning signal detection.

OBJECTIVES: To review user signal rating activity within the Canadian Network for Public Health Intelligence's (CNPHI's) Knowledge Integration using Web-based Intelligence (KIWI) technology by answering the following questions: (1) who is rating, (2) how are users rating, and (3) how well are users rating? METHODS: KIWI rating data was extracted from the CNPHI platform. Zoonotic & Emerging program signals with first rating occurring between January 1, 2016 and December 31, 2017 were included. Krippendorff's alpha was used to estimate inter-rater reliability between users. A z-test was used to identify whether users tended to rate within 95% confidence interval (versus outside) the average community rating. RESULTS: The 37 users who rated signals represented 20 organizations. 27.0% (n = 10) of users rated ≥10% of all rated signals, and their inter-rater reliability estimate was 72.4% (95% CI: 66.5-77.9%). Five users tended to rate significantly outside of the average community rating. An average user rated 58.4% of the time within the signal's 95% CI. All users who significantly rated within the average community rating rated outside the 95% CI at least once. DISCUSSION: A diverse community of raters participated in rating the signals. Krippendorff's Alpha estimate revealed moderate reliability for users who rated ≥10% of signals. It was observed that inter-rater reliability increased for users with more experience rating signals. CONCLUSIONS: Diversity was observed between user ratings. It is hypothesized that rating diversity is influenced by differences in user expertise and experience, and that the number of times a user rates within and outside of a signal's 95% CI can be used as a proxy for user expertise. The introduction of a weighted rating algorithm within KIWI that takes this into consideration could be beneficial.

An innovative mobile data collection technology for public health in a field setting.

OBJECTIVES: The Canadian Network for Public Health Intelligence (CNPHI) is a secure, web-based scientific informatics and biosurveillance platform that leverages disparate public health information resources and expertise for the direct benefit of local, regional and national decision makers. CNPHI fosters collaboration and consultation through innovation in disease surveillance, intelligence exchange, research and response to protect, promote and support public health. The objective of this article is to present the CNPHI 'on the go' mobile application, and to discuss preliminary evaluation of the technology. The mobile application is intended to enable rapid mobile data collection using both online and offline modes supporting various stages of surveillance and response through the extension of data collection and analysis to the mobile environment. METHODS: Two needs assessment meetings were held with stakeholders representing individuals from government, academia and research institutions, to inform the development of the CNPHI "on the go" mobile application. An initial version of the mobile technology (an "app") was developed and piloted by end-users with expertise in the field. Two focused pilots were conducted to test the technology: Pilot 1: 17-7-2017 to 21-11-2017 (6 participants); Pilot 2: 25-7-2017 to 15-9-2017 (2 participants). An initial consultation was held with the project leads to identify data elements for mobile data collection. A custom data collection form was designed using CNPHI's Web Data technology for each pilot, which was then made available through the mobile app. The technology was assessed using feedback received during each pilot as well as through a survey that was conducted at the conclusion of pilots. RESULTS: Pilot participants reported that the mobile technology allowed seamless data collection, data management and rapid information sharing. Participants also reported that the entire process was seamless, simple, efficient, and that fewer steps were required for data collection and management. Further, significant efficiencies were gained by directly entering information using the mobile app without having to transfer handwritten information into an electronic database. An overall positive experience was reported by participants from both pilots. DISCUSSION: Literature suggests that traditional methods of surveillance and data collection using a paper based methodology pose many challenges such as data loss and duplication, difficulty in managing the database, and lack of timely access to the data. Accurate and rapid access is critical for public health professionals in order to effectively make decisions and respond to public health emergencies. Results show that the CNPHI "on the go" app is well poised to address some of the suggested challenges. A limitation of this study was that sample size for pilot participation was small for capturing overall feedback on the readiness of the technology for integration into regular surveillance activities and response procedures. CONCLUSIONS: CNPHI "on the go" is a customizable technology developed within an already thriving collaborative CNPHI platform used by public health professionals, and performs well as a tool for rapid data collection and secure information sharing.

Contributing to communicable diseases intelligence management in Canada: CACMID meeting, March 2007, Halifax, Nova Scotia.

In the spring of 2003, the Public Health Agency of Canada (then, Health Canada) partnered with several provincial/territorial and regional public health stakeholders to improve pan-Canadian public health surveillance, communications and response through the application of new technologies. This resulted in the creation of the Canadian Network for Public Health Intelligence (CNPHI), a comprehensive framework of applications and resources designed to fill critical gaps in Canada's national public health infostructure. Over the past four years, the CNPHI has evolved into Canada's only pan-Canadian public health information management system. With over 2000 registered users, the current CNPHI environment consists of more than 30 integrated applications and systems that can be loosely categorized into four functional groups: data exchange; data analysis and integration; communication, collaboration and coordination; and knowledge management. Despite poor data repositories, legacy information management systems, and the lack of standards and agreements, the CNPHI has demonstrated that much can be accomplished in these areas. Over the next decade, significant barriers impeding additional advances will be bridged through the implementation of the Electronic Health Record, and through ongoing efforts to address gaps in standards, and data- and information-sharing agreements. Together with new technologies coming on-line, opportunities to further enhance public health surveillance and response will be limited only by one's imagination.

Influenza-like illness-related emergency department visits: Christmas and New Year holiday peaks and relationships with laboratory-confirmed respiratory virus detections, Edmonton, Alberta, 2004-2014.

BACKGROUND: Emergency department (ED) visit volumes can be especially high during the Christmas-New Year holidays, a period occurring during the influenza season in Canada. METHODS: Using daily data, we examined the relationship between ED visits for the chief complaint "cough" (for Edmonton, Alberta residents) and laboratory detections for influenza A and respiratory syncytial virus (RSV) (for Edmonton and surrounding areas), lagged 0-5 days ahead, for non-pandemic years (2004-2008 and 2010-2014) using multivariable linear regression adjusting for temporal variables. We defined these cough-related visits as influenza-like illness (ILI)-related ED visits and, for 2004-2014, compared Christmas-New Year holiday (December 24-January 3) and non-holiday volumes during the influenza season (October-April). RESULTS: Adjusting for temporal variables, ILI-related ED visits were significantly associated with laboratory detections for influenza A and RSV. During non-pandemic years, the highest peak in ILI-related visit volumes always occurred during the holidays. The median number of holiday ILI-related visits/day (42.5) was almost twice the non-holiday median (24) and was even higher in 2012-2013 (80) and 2013-2014 (86). Holiday ILI-related ED visit volumes/100 000 population ranged from 56.0 (2010-2011) to 117.4 (2012-2013). In contrast, lower visit volumes occurred during the holidays of pandemic-affected years (2008-2010). CONCLUSIONS: During non-pandemic years, ILI-related ED visit volumes were associated with variations in detections for influenza A and RSV and always peaked during the Christmas-New Year holidays. This predictability should be used to prepare for, and possibly prevent, this increase in healthcare use; however, interventions beyond disease prevention strategies are likely needed.

KIWI: A technology for public health event monitoring and early warning signal detection.

OBJECTIVES: To introduce the Canadian Network for Public Health Intelligence's new Knowledge Integration using Web-based Intelligence (KIWI) technology, and to pefrom preliminary evaluation of the KIWI technology using a case study. The purpose of this new technology is to support surveillance activities by monitoring unstructured data sources for the early detection and awareness of potential public health threats. METHODS: A prototype of the KIWI technology, adapted for zoonotic and emerging diseases, was piloted by end-users with expertise in the field of public health and zoonotic/emerging disease surveillance. The technology was assessed using variables such as geographic coverage, user participation, and others; categorized by high-level attributes from evaluation guidelines for internet based surveillance systems. Special attention was given to the evaluation of the system's automated sense-making algorithm, which used variables such as sensitivity, specificity, and predictive values. Event-based surveillance evaluation was not applied to its full capacity as such an evaluation is beyond the scope of this paper. RESULTS: KIWI was piloted with user participation = 85.0% and geographic coverage within monitored sources = 83.9% of countries. The pilots, which focused on zoonotic and emerging diseases, lasted a combined total of 65 days and resulted in the collection of 3243 individual information pieces (IIP) and 2 community reported events (CRE) for processing. Ten sources were monitored during the second phase of the pilot, which resulted in 545 anticipatory intelligence signals (AIS). KIWI's automated sense-making algorithm (SMA) had sensitivity = 63.9% (95% CI: 60.2-67.5%), specificity = 88.6% (95% CI: 87.3-89.8%), positive predictive value = 59.8% (95% CI: 56.1-63.4%), and negative predictive value = 90.3% (95% CI: 89.0-91.4%). DISCUSSION: Literature suggests the need for internet based monitoring and surveillance systems that are customizable, integrated into collaborative networks of public health professionals, and incorporated into national surveillance activities. Results show that the KIWI technology is well posied to address some of the suggested challenges. A limitation of this study is that sample size for pilot participation was small for capturing overall readiness of integrating KIWI into regular surveillance activities. CONCLUSIONS: KIWI is a customizable technology developed within an already thriving collaborative platform used by public health professionals, and performs well as a tool for discipline-specific event monitoring and early warning signal detection.

Development and Validation of a Standardized Tool for Prioritization of Information Sources.

PURPOSE: To validate the utility and effectiveness of a standardized tool for prioritization of information sources for early detection of diseases. METHODS: The tool was developed with input from diverse public health experts garnered through survey. Ten raters used the tool to evaluate ten information sources and reliability among raters was computed. The Proc mixed procedure with random effect statement and SAS Macros were used to compute multiple raters' Fleiss Kappa agreement and Kendall's Coefficient of Concordance. RESULTS: Ten disparate information sources evaluated obtained the following composite scores: ProMed 91%; WAHID 90%; Eurosurv 87%; MediSys 85%; SciDaily 84%; EurekAl 83%; CSHB 78%; GermTrax 75%; Google 74%; and CBC 70%. A Fleiss Kappa agreement of 50.7% was obtained for ten information sources and 72.5% for a sub-set of five sources rated, which is substantial agreement validating the utility and effectiveness of the tool. CONCLUSION: This study validated the utility and effectiveness of a standardized criteria tool developed to prioritize information sources. The new tool was used to identify five information sources suited for use by the KIWI system in the CEZD-IIR project to improve surveillance of infectious diseases. The tool can be generalized to situations when prioritization of numerous information sources is necessary.

An innovative web based system for reporting rare diseases in paediatrics.

BACKGROUND: Surveillance of rare diseases in children is an important aspect of public health. Rare diseases affect thousands of children worldwide. The Canadian Paediatric Surveillance Program (CPSP) has been in existence since 1996, and provides an innovative means to undertake paediatric surveillance and increase awareness of childhood disorders that are high in disability, morbidity, mortality, and economic costs to society, despite their low frequency. Traditionally, CPSP used manual paper-based reporting on a monthly basis, which although had an impressive response rate, it had inherent longer processing times and costs associated with it. OBJECTIVES: To provide an overview and evaluate an innovative web-based system that enables seamless reporting from participants across the country providing a quick, reliable and simple mechanism for the participants to submit data while yielding better data quality, timeliness and increased efficiencies. METHODS: In 2011, a proprietary electronic CPSP (eCPSP) system was developed to provide a simple, quick and reliable reporting environment for participants. It supports both the electronic and hardcopy reporting. The analysis presented in this paper was conducted based on usage data of this system. RESULTS: The response rates of the new eCPSP were found to be very favorable with adjusted rate of 80%, which equals the baseline. Approximately 50% of online participants report the first day they receive the notification e-mail. The response time was also reduced considerably. Furthermore, there has been significant reduction in data handling related activities (by almost 70%) from estimated 690 hours per year. Finally, the number of cases reported that do not fit the study case criteria has fallen, likely because participants can now immediately access the case definition and protocol via the online system. This has reduced both staff and investigator time for case processing. CONCLUSION: The eCPSP has modernized the CPSP program from paper-based reporting to efficient online technology while maintaining the core principles of the program. This simple and intuitive approach has proven to be an efficient approach cutting response times significantly while maintaining the desired response rates.