Is This an Outbreak? A retrospective evaluation of syndromic surveillance for emerging infectious disease Is This an Outbreak? A retrospective evaluation of syndromic surveillance for emerging infectious disease Is dit een uitbraak? Een retrospectieve evaluatie van syndroomsurveillance voor nieuw opduikende infectieziekten Proefschrift ter verkrijging van de graad van doctor aan de Erasmus Universiteit Rotterdam op gezag van de rector magnificus Prof.dr. H.G. Schmidt en volgens besluit van het College voor Promoties. De openbare verdediging zal plaatsvinden op donderdag 9 december 2010 om 13.30 uur door © 2010 Kees van den Wijngaard, Zeist Cornelis Carolus van den Wijngaard ISBN 978 90 6464 426 9 Layout: GVO drukkers & vormgevers B.V. | Ponsen & Looijen geboren te Sittard Printed by: GVO drukkers & vormgevers B.V. | Ponsen & Looijen Reprints were made with permission of The American Public Health Association and Cambridge University Press. Publication of this thesis was financially supported by the National Institute for Public Health and the Environment (RIVM) and Erasmus University Rotterdam (EUR). Promotiecommissie Promotoren: Prof.dr. M.P.G. Koopmans Prof.dr. N.J.D. Nagelkerke Overige leden: Prof.dr. A. Osterhaus Prof.dr. J.H. Richardus Prof.dr. M.C.J.M. Sturkenboom Copromotor: Dr. W. van Pelt Contents Chapter 1 General Introduction 9 Chapter 2 Validation of Syndromic Surveillance for Respiratory Pathogen Activity Emerg Infect Dis 2008;14:917-25 19 Chapter 3 Detection of Excess Influenza Severity: Associating Respiratory Hospitalization and Mortality Data With Reports of Influenza-Like Illness by Primary Care Physicians 31 Am J Public Health [Epub ahead of print] Chapter 4 Syndromic Surveillance for Local Outbreaks of Lower Respiratory Infections: Would It Work? 41 PLoS ONE 2010;5:e10406 Chapter 5 In Search of Hidden Q-fever Outbreaks: Linking Syndromic Hospital Clusters to Infected Goat Farms 51 Epidemiolog Infect 2010 [Epub ahead of print] Chapter 6 Evaluation of Syndromic Surveillance: Perspective on Its Added Value and Recommendations for Implementation 61 Submitted for publication Chapter 7 General Discussion 73 Appendices/Supplementary material 85 Summary 130 Samenvatting 134 Dankwoord/Acknowledgements 138 Curriculum vitae 140 PhD Portfolio 142 Chapter 1 General Introduction 10 Chapter 1 General Introduction 11 General Introduction pathogens [9,21-24]. Figure 1 shows that in all disease phases, data can be generated for syndromic surveillance. This ranges from data reflecting mild morbidity not even requiring medical treatment, to data reflecting more severe morbidity (requiring hospitalization) or even death. In the prodromal phase, elevations of absenteeism Background and over-the-counter sales of medications could indicate early disease elevations. In the clinical phase, work- In the last decade, worldwide several major infectious disease events occurred — like the anthrax attacks in the diagnoses, (acute) chief complaints, prescription medications or emergency-department diagnoses can be USA in 2001, the SARS epidemic in 2003 and the 2009 influenza pandemic. As a result, public-health authorities used for syndromic surveillance. Trends in the number of specimens submitted to diagnostic laboratories worldwide have acknowledged the need for improved surveillance for emerging infectious diseases, as early — before the test results become available — could indicate disease elevations as well. Even in the final phase detection and control may well mitigate the impact of emerging outbreaks. For instance, the SARS epidemic of disease, cause-of-death or crude (overall) mortality data can be used for syndromic surveillance purposes. could have caused a major pandemic with millions of deaths if it had not been contained by public health Traditional surveillance, on the other hand, is mainly limited to diagnoses based on laboratory detection of measures. Still, the SARS epidemic was only recognized several months after its emergence, and in the end it pathogens (Figure 1), followed by notification. infected 8096 patients in 27 countries and caused 774 deaths before it could be controlled [1,2]. SARS, and most other pathogens that are considered a high threat for public health, cause symptoms that are common in clinical Analyses and Response practice, like pneumonia (e.g. B. anthracis, SARS or pandemic influenza), gastro-enteritis (e.g. Vibrio cholerae) A syndromic surveillance system that is used for early warning, is supposed to generate a signal if a certain or neurological disease (e.g. West Nile virus) [3,4]. That is why traditional outbreak detection based on astute syndrome shows an unexpected elevation [5,25]. For signaling such elevations in time and/or space-time, clinicians and laboratory diagnoses can have blind spots for such emerging diseases, because patients reporting statistical algorithms can be used to compare the difference between the number of observed and expected with such common symptoms might not alarm clinicians — especially since individual clinicians may only see cases, often derived from historical data [5,6]. Obviously, in order to have added value for public health, one or a few of these “new” cases — and uncommon pathogens can remain undetected by the laboratory. syndromic surveillance signals have to be translated in public-health responses such as active case finding, To reveal such blind spots, many countries have implemented so called syndromic surveillance systems that treatment and/or quarantine. aim to capture infectious disease events earlier and more completely than traditional surveillance; they do this by monitoring new health indicators, such as basic symptom information or clinical diagnoses, rather than positive Performance evaluation laboratory results for specific pathogens [5-14]. Surveillance of symptom based data has been used since decades To evaluate the added value of syndromic surveillance, it would make sense to assess its performance for for surveillance of polio (acute flaccid paralysis) and influenza (influenza-like illness) [15,16], but the increasing different systems and disease events in a standardized way. However, one should keep in mind that quantitative availability of electronic health-care data with information on specific morbidity in time, has made large-scale performance measures like the sensitivity, specificity and timeliness of outbreak detection are difficult to real-time monitoring of syndromes possible. Syndromic surveillance was initially developed for early-warning standardize, because detection of disease events depends on many sometimes unpredictable factors; these detection of bioterrorism attacks, but is also used for early detection of naturally occurring (local) outbreaks, include data types and sources, syndrome definitions, detection algorithms, response actions, surveillance following the size and spread of ongoing outbreaks, monitoring disease trends in the general population, and populations and types of disease event [25-27]. In addition, there is a lack of data on real (major) disease events providing reassurance that an outbreak has not occurred [5,6]. At the same time, in light of limited resources for to use as “gold standard”, whereas simulated test outbreaks may not reflect the diversity and unpredictability public health, there has been an ongoing debate about the actual added value of syndromic surveillance, with of real-life disease events [25,28]. An additional problem is that many existing syndromic surveillance systems particular concerns about its specificity [17-20]. have limitations like low data quality or coverage, making these systems unfit for evaluating the potential Because little validation had been done to address these concerns[18,20], we chose to evaluate the potential performance and thus added value of syndromic surveillance. value of syndromic surveillance for infectious disease surveillance and control, before starting any implementation. This thesis is the result of that evaluation project. Objective, approach, specific research questions and outline of the PhD-thesis The objective of this PhD-thesis is to evaluate the added value of syndromic surveillance for infectious disease The concept of syndromic surveillance surveillance and control, and to make recommendations for its possible implementation in the Netherlands. We chose to evaluate a range of syndromic data types from existing Dutch medical registries — all retrospective but Syndromic data with high-quality data and preferably high coverage. Table 1 lists the six registries included in the study, with data There is no official definition of syndromic surveillance, but systems designated as such monitor all kinds of on work-absenteeism, General Practitioner (GP) consultations, pharmacy prescriptions, laboratory submissions, pre- or non-diagnostic data in order to capture (infectious) disease dynamics. In this context, a syndrome can be hospital diagnoses and mortality. Data was available from 1999-2009 or parts of this period. defined as a combination of complaints and symptoms of a patient which could indicate an infection with certain Rather than estimating performance parameters like sensitivity and specificity for detecting fictitious major 12 Chapter 1 General Introduction 13 disease events, we first assessed whether known infectious disease dynamics and outbreaks during the study First Symptoms Symptoms Infection period were reflected in these data sources, assuming that good reflection of known dynamics and outbreaks symptoms increase