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1.  Establishment of a One Health Surveillance Initiative in the CA/Baja CA Border Region 
Objective
To showcase One Border One Health, a binational, multidiscipli-nary initiative in the California/Baja California (CA/BC) border region whose aim is to reconfigure traditional species-specific approaches to surveillance for emerging and re-emerging pathogens.
Introduction
The CA/BC border region encompasses a wide range of ecosystems, topography, dense urban areas, and agricultural developments that coexist in a limited geographic area and create numerous human-animal-environmental interfaces. The region is recognized for its high biodiversity, the presence of over 85 endangered plant and animal species, its importance on the Pacific migratory pathway, high levels of population mobility, and hosts the busiest international border in the world. These interfaces pose a significant risk to animal, human, and environmental health, as evidenced by frequent wildlife die offs, antibiotic resistant bacteria in streams, beach closures due to fecal contamination, pesticide toxicities, zoonotic infectious disease outbreaks, and vector borne diseases. In the marked absence of any organization comprehensively addressing the health risks posed by these complex interfaces and recognizing that these issues necessitate a binational, cross-sectoral One Health approach, the Early Warning Infectious Disease Surveillance Program (EWIDS) founded One Border One Health (OBOH) in 2011.
OBOH recognizes that early warning systems should systematically monitor animal, human, and environmental health and that early detection is key to control. Hence OBOH’s primary aim is to create and integrate early warning surveillance systems that gather data from disparate sources in order to protect and improve animal, human, and environmental health. This information can be used to inform decision makers about important public health events in the CA/BC border region.
Methods
OBOH is a unique multi-disciplinary initiative comprised of over 30 institutions from Mexico and 60 institutions from the United States, with representation from government, academia, non-profit, private and military sectors. Professionals with expertise in public health, veterinary medicine, ecology, biology, urban planning, epidemiology, wildlife health, and environmental health are working in concert rather than in the traditionally isolated human, environmental health, domestic animal and wildlife sectors. OBOH is actively seeking to translate One Health theory into practice through its diverse, binational network. This demonstration presents OBOH’s surveillance, informatics, and education activities, focusing on its strengths, challenges, and future directions.
Conclusions
To the authors’ knowledge this is the first trans-border regional network established to enhance cross border epidemiologic information exchange and surveillance using One Health concepts in North America. Despite the large disparities between health systems, cultures, languages, socioeconomics, politics, animal management strategies, industries and ecosystems in the CA/BC border region, professionals from diverse disciplines are dedicated to OBOH and to the creation of a sustainable integrated surveillance system. OBOH is building the infrastructure for an early warning system in the border region, while improving regional infectious disease surveillance capacity and educating a new cadre of students and professionals about the importance of a One Health approach. Challenges include identifying cross-sectoral/multi-disciplinary funding opportunities to support activities, systematically operationalizing One Health without such funding, identifying and involving partners from different sectors, promoting data exchange, and maintaining an equal understanding of One Health surveillance within the initiative as membership increases. This demonstration provides recommendations on how to initiate and sustain cross-border, multidisciplinary, cross-sectoral surveillance engagements in resource-constrained environments.
PMCID: PMC3692860
cross-border surveillance; emerging and re-emerging pathogens; One Health; collaboratives; early warning systems
2.  Syndromic Surveillance Based on Emergency Visits: A Reactive Tool for Unusual Events Detection 
Objective
To show with examples that syndromic surveillance system can be a reactive tool for public health surveillance.
Introduction
The late health events such as the heat wave of 2003 showed the need to make public health surveillance evolve in France. Thus, the French Institute for Public Health Surveillance has developed syndromic surveillance systems based on several information sources such as emergency departments (1). In Reunion Island, the chikungunya outbreak of 2005–2006, then the influenza pandemic of 2009 contributed to the implementation and the development of this surveillance system (2–3). In the past years, this tool allowed to follow and measure the impact of seasonal epidemics. Nevertheless, its usefulness for the detection of minor unusual events had yet to be demonstrated.
Methods
In Reunion Island, the syndromic surveillance system is based on the activity of six emergency departments. Two types of indicators are constructed from collected data: - Qualitative indicators for the alert (every visit whose diagnostic relates to a notifiable disease or potential epidemic disease);- Quantitative indicators for the epidemic/cluster detection (number of visits based on syndromic grouping).
Daily and weekly analyses are carried out. A decision algorithm allows to validate the signal and to organize an epidemiological investigation if necessary.
Results
Each year, about 150 000 visits are registered in the six emergency departments that is 415 consultations per day on average. Several unusual health events on small-scale were detected early.
In August 2011, the surveillance system allowed to detect the first autochthonous cases of measles, a few days before this notifiable disease was reported to health authorities (Figure 1). In January 2012, the data of emergency departments allowed to validate the signal of viral meningitis as well as to detect a cluster in the West of the island and to follow its trend. In June 2012, a family foodborne illness was detected from a spatio-temporal cluster for abdominal pain by the surveillance system and was confirmed by epidemiological investigation (Figure 2).
Conclusions
Despite the improvement of exchanges with health practitioners and the development of specific surveillance systems, health surveillance remains fragile for the detection of clusters or unusual health events on small scale. The syndromic surveillance system based on emergency visits has proved to be relevant for the identification of signals leading to health alerts and requiring immediate control measures. In the future, it will be necessary to develop these systems (private practitioners, sentinel schools) in order to have several indicators depending on the degree of severity.
PMCID: PMC3692799
Syndromic surveillance; Unusual event detection; Reunion Island
3.  Defining syndromes using cattle meat inspection data for syndromic surveillance purposes: a statistical approach with the 2005–2010 data from ten French slaughterhouses 
Background
The slaughterhouse is a central processing point for food animals and thus a source of both demographic data (age, breed, sex) and health-related data (reason for condemnation and condemned portions) that are not available through other sources. Using these data for syndromic surveillance is therefore tempting. However many possible reasons for condemnation and condemned portions exist, making the definition of relevant syndromes challenging.
The objective of this study was to determine a typology of cattle with at least one portion of the carcass condemned in order to define syndromes. Multiple factor analysis (MFA) in combination with clustering methods was performed using both health-related data and demographic data.
Results
Analyses were performed on 381,186 cattle with at least one portion of the carcass condemned among the 1,937,917 cattle slaughtered in ten French abattoirs. Results of the MFA and clustering methods led to 12 clusters considered as stable according to year of slaughter and slaughterhouse. One cluster was specific to a disease of public health importance (cysticercosis). Two clusters were linked to the slaughtering process (fecal contamination of heart or lungs and deterioration lesions). Two clusters respectively characterized by chronic liver lesions and chronic peritonitis could be linked to diseases of economic importance to farmers. Three clusters could be linked respectively to reticulo-pericarditis, fatty liver syndrome and farmer’s lung syndrome, which are related to both diseases of economic importance to farmers and herd management issues. Three clusters respectively characterized by arthritis, myopathy and Dark Firm Dry (DFD) meat could notably be linked to animal welfare issues. Finally, one cluster, characterized by bronchopneumonia, could be linked to both animal health and herd management issues.
Conclusion
The statistical approach of combining multiple factor analysis with cluster analysis showed its relevance for the detection of syndromes using available large and complex slaughterhouse data. The advantages of this statistical approach are to i) define groups of reasons for condemnation based on meat inspection data, ii) help grouping reasons for condemnation among a list of various possible reasons for condemnation for which a consensus among experts could be difficult to reach, iii) assign each animal to a single syndrome which allows the detection of changes in trends of syndromes to detect unusual patterns in known diseases and emergence of new diseases.
doi:10.1186/1746-6148-9-88
PMCID: PMC3681570  PMID: 23628140
Syndromic surveillance; Animal health; Meat inspection; Slaughterhouses; Cattle
4.  Syndromic Surveillance from a Local Perspective – A Review of the Literature 
Objective
Review of the origins and evolution of the field of syndromic surveillance. Compare the goals and objectives of public health surveillance and syndromic surveillance in particular. Assess the science and practice of syndromic surveillance in the context of public health and national security priorities. Evaluate syndromic surveillance in practice, using case studies from the perspective of a local public health department.
Introduction
Public health disease surveillance is defined as the ongoing systematic collection, analysis and interpretation of health data for use in the planning, implementation and evaluation of public health, with the overarching goal of providing information to government and the public to improve public health actions and guidance [1,2]. Since the 1950s, the goals and objectives of disease surveillance have remained consistent [1]. However, the systems and processes have changed dramatically due to advances in information and communication technology, and the availability of electronic health data [2,3]. At the intersection of public health, national security and health information technology emerged the practice of syndromic surveillance [3].
Methods
To better understand the current state of the field, a review of the literature on syndromic surveillance was conducted: topics and keywords searched through PubMed and Google Scholar included biosurveillance, bioterrorism detection, computerized surveillance, electronic disease surveillance, situational awareness and syndromic surveillance, covering the areas of practice, research, preparedness and policy. This literature was compared with literature on traditional epidemiologic and public health surveillance. Definitions, objectives, methods and evaluation findings presented in the literature were assessed with a focus on their relevance from a local perspective, particularly as related to syndromic surveillance systems and methods used by the New York City Department of Health and Mental Hygiene in the areas of development, implementation, evaluation, public health practice and epidemiological research.
Results
A decade ago, the objective of syndromic surveillance was focused on outbreak and bioterrorism early-event detection (EED). While there have been clear recommendations for evaluation of syndromic surveillance systems and methods, the original detection paradigm for syndromic surveillance has not been adequately evaluated in practice, nor tested by real world events (ie, the systems have largely not ‘detected’ events of public health concern). In the absence of rigorous evaluation, the rationale and objectives for syndromic surveillance have broadened from outbreak and bioterrorism EED, to include all causes and hazards, and to encompass all data and analyses needed to achieve “situational awareness”, not simply detection. To evaluate current practices and provide meaningful guidance for local syndromic surveillance efforts, it is important to understand the emergence of the field in the broader context of public health disease surveillance. And it is important to recognize how the original stated objectives of EED have shifted in relation to actual evaluation, recommendation, standardization and implementation of syndromic systems at the local level.
Conclusions
Since 2001, the field of syndromic surveillance has rapidly expanded, following the dual requirements of national security and public health practice. The original objective of early outbreak or bioterrorism event detection remains a core objective of syndromic surveillance, and systems need to be rigorously evaluated through comparison of consistent methods and metrics, and public health outcomes. The broadened mandate for all-cause situation awareness needs to be focused into measureable public health surveillance outcomes and objectives that are consistent with established public health surveillance objectives and relevant to the local practice of public health [2].
PMCID: PMC3692931
evaluation; biosurveillance; situational awareness; syndromic surveillance; local public health
5.  Adaptation of GUARDIAN for Syndromic Surveillance During the NATO Summit 
Objective
To develop and implement a framework for special event surveillance using GUARDIAN, as well as document lessons learned post-event regarding design challenges and usability.
Introduction
Special event driven syndromic surveillance is often initiated by public health departments with limited time for development of an automated surveillance framework, which can result in heavy reliance on frontline care providers and potentially miss early signs of emerging trends. To address timelines and reliability issues, automated surveillance system are required.
Methods
The North Atlantic Treaty Organization (NATO) summit was held in Chicago, IL, May 19–21, 2012. During the NATO summit, the Chicago Department of Public Health (CDPH) was charged with collecting and analyzing syndromic surveillance data from emergency department (ED) visits that may indicate a man-made or naturally occurring infectious disease threat.
Ten days prior to the NATO summit surveillance period, Rush University Medical Center (RUMC) received a guidance document from CDPH outlining the syndromes for systematic surveillance, specifically febrile rash illness, localized cutaneous lesion, acute febrile respiratory illness, gastrointestinal illness, botulism-like illness, hemorrhagic illness, along with unexplained deaths or severe illness potentially due to infectious disease and cases due to toxins or suspected poisoning. RUMC researchers collected relevant ICD-9 codes for each syndrome category.
GUARDIAN (1), an automated surveillance system, was programmed to scan patient charts and match free text using National Library of Medicine free-text term to unique medical concept, which were further mapped to relevant ICD-9 codes. The baselines were developed using ED patient data from 1/1/2010 to 12/31/2011. Statistical references were established for unsmoothed, 24 hour counts (Baseline = Average; Threshold = +2 standard deviations).
During the NATO surveillance timeframe (May 13–26, 2012) automated results with prior reporting period’s counts, reference statistics, and charts were electronically sent to CDPH. In addition, ED charge nurses made manual surveillance reports by telephone at least daily. Open lines of communication were maintained between RUMC and CDPH during the event to discuss potential positive cases. In addition, a post-event debriefing was conducted to document lessons learned.
Results
The automated GUARDIAN surveillance reports not only provided timely counts of potentially positive cases for each syndrome but also provided trend analysis with baseline measures. The GUARDIAN User Interface was used to explain what data points could trigger positive cases. The Epic system was used to review patient charts, if further explanation was necessary. The observed counts never exceeded +2 standard deviations during the NATO surveillance period for any of the syndromes.
Based on the debriefing meeting between RUMC and CDPH, the top three achievements and lessons learned were as follows: Quick turnaround time (∼ 10 days) from surveillance concept development to automated implementation using GUARDIANSurveillance data was timely and reliableAdditional statistical information was beneficial to put trends in contextSystem may be too sensitive resulting in false alarms and additional investigative burden on public health departmentsNeed for development of user-interfaces with drill down capabilities to patient level dataClinicians don’t necessarily utilize exact terminology used in ICD-9 codes which could result in undetected cases.
Conclusions
This exercise successfully highlights rapid development and implementation of special event driven automated surveillance as well as collaborative approach between front-line entities such as emergency departments, surveillance researchers, and the department of public health. In addition, valuable lessons learned with potential solutions are documented for further refinements of such surveillance activities.
PMCID: PMC3692845
Emergency department; NATO Summit; automated surveillance
6.  Defining Public Health Situation Awareness – Outcomes and Metrics for Evaluation 
Objective
Review concept of situation awareness (SA) as it relates to public health surveillance, epidemiology and preparedness [1]. Outline hierarchical levels and organizational criteria for SA [2]. Initiate consensus building process aimed at developing a working definition and measurable outcomes and metrics for SA as they relate to syndromic surveillance practice and evaluation.
Introduction
A decade ago, the primary objective of syndromic surveillance was bioterrorism and outbreak early event detection (EED) [3]. Syndromic systems for EED focused on rapid, automated data collection, processing and statistical anomaly detection of indicators of potential bioterrorism or outbreak events. The paradigm presented a clear and testable surveillance objective: the early detection of outbreaks or events of public health concern. Limited success in practice and limited rigorous evaluation, however, led to the conclusion that syndromic surveillance could not reliably or accurately achieve EED objectives. At the federal level, the primary rationale for syndromic surveillance shifted away from bioterrorism EED, and towards all-hazards biosurveillance and SA [4–6]. The shift from EED to SA occurred without a clear evaluation of EED objectives, and without a clear definition of the scope or meaning of SA in practice. Since public health SA has not been clearly defined in terms of operational surveillance objectives, statistical or epidemiological methods, or measurable outcomes and metrics, the use of syndromic surveillance to achieve SA cannot be evaluated.
Methods
This session is intended to provide a forum to discuss SA in the context of public health disease surveillance practice. The roundtable will focus on defining SA in the context of public health syndromic and epidemiologic surveillance. While SA is often noted in federal level documents as a primary rationale for biosurveillance [1, 4–6], it is rarely defined or described in operational detail. One working definition presents SA as “real-time analysis and display of health data to monitor the location, magnitude, and spread of an outbreak”, yet it does not elaborate on the methods, systems or evaluation requirements for SA in public health or biosurveillance [3]. In terms of translating SA into public health surveillance practice [1], we will discuss and define the requirements of public health SA based on its development and practice in other areas [2]. The proposed theoretical framework and evaluation criteria adapted and applied to public health SA [2] follow: - Level 1: Perceive relevant surveillance data and epidemiological information.- Level 2: Integrate surveillance and non-surveillance data in conjunction with operator goals to provide understanding of the meaning of the information.- Level 3: Through perceiving (Level 1) and integrating and understanding (Level 2) provide prediction of future events and system states to allow for timely and effective public health decision making.
Results
Sample questions for discussion: What is the relevance of syndromic surveillance and biosurveillance in the SA framework? Where does it fit within the current public health surveillance environment? To achieve the roundtable discussion objectives, the participants will work towards a consensus definition of SA for public health, and will outline measureable outcomes and metrics for evaluation of syndromic surveillance for public health SA.
PMCID: PMC3692849
evaluation; biosurveillance; situational awareness; syndromic surveillance; local public health
7.  Enhanced Surveillance during the Democratic National Convention, Charlotte, NC 
Objective
To describe how the existing state syndromic surveillance system (NC DETECT) was enhanced to facilitate surveillance conducted at the Democratic National Convention in Charlotte, North Carolina from August 31, 2012 to September 10, 2012.
Introduction
North Carolina hosted the 2012 Democratic National Convention, September 3–6, 2012. The NC Epidemiology and Surveillance Team was created to facilitate enhanced surveillance for injuries and illnesses, early detection of outbreaks during the DNC, assist local public health with epidemiologic investigations and response, and produce daily surveillance reports for internal and external stakeholders. Surveillane data were collected from several data sources, including North Carolina Electronic Disease Surveillance System (NC EDSS), triage stations, and the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT).
NC DETECT was created by the North Carolina Division of Public Health (NC DPH) in 2004 in collaboration with the Carolina Center for Health Informatics (CCHI) in the UNC Department of Emergency Medicine to address the need for early event detection and timely public health surveillance in North Carolina using a variety of secondary data sources. The data from emergency departments, the Carolinas Poison Center, the Pre-hospital Medical Information System (PreMIS) and selected Urgent Care Centers were available for monitoring by authorized users during the DNC.
Methods
Within NC DETECT, new dashboards were created that allowed epidemiologists to monitor ED visits and calls to the poison center in the Charlotte area, the greater Cities Readiness Initiative region and the entire state for infectious disease signs and symptoms, injuries and any mention of bioterrorism agents. The dashboards also included a section to view user comments on the information presented in NC DETECT. Data processing changes were also made to improve the timeliness of the EMS data received from PreMIS.
Results
The DNC dashboards added to NC DETECT streamlined the workflow by placing all syndromes and annotations of interest in one place, with the date ranges and locations already pre-selected. Graphs in the dashboards could be easily copied and pasted into situation reports. The prompt development of these user-friendly tools provided effective surveillance for this mass gathering and ensured timely control measures, if necessary.
Conclusions
Syndromic surveillance systems can be enhanced to provide detailed, specific surveillance during mass gathering events. Elements that facilitate this enhancement include strong communication between skilled users and the informatics team, in order to minimize the burden placed on the surveillance team system users, data sources and system developers during the event. The visualizations developed as part of these new dashboards will be leveraged to provide additional tools to other NC DETECT user groups, including hospital-based public health epidemiologists and local health department users.
PMCID: PMC3692843
dashboards; enhanced surveillance; Democratic National Convention
8.  A Syndromic Approach to Emergency Department Surveillance for Skin and Soft Tissue Infections 
Objective
We sought to describe the epidemiology of emergency department (ED) visits for skin and soft tissue infections (SSTI) in an urban area with diverse neighborhood populations using syndromic surveillance system data for the time period from 2007–2011. Our aims were threefold: to demonstrate a proof of concept using syndromic surveillance for SSTI surveillance in the absence of laboratory data, to estimate the burden of ED visits associated with SSTI, and to determine potential geographic “hotspots” for these infections.
Introduction
The incidence of and hospitalizations for SSTI have steadily increased over the last decade in the United States, primarily due to the emergence and spread of community acquired Methicillin resistant Staphylococcus aureus (CA-MRSA). The ED is a common site for SSTI treatment and serves populations not captured by traditional surveillance, including the homeless and uninsured. The use of near real-time syndromic surveillance within the ED to detect unusual activity for further public health investigation has been used to augment traditional infectious disease surveillance. However, the use of this approach for monitoring local epidemiologic trends in SSTI presentation where laboratory data are not available, has not previously been described.
Methods
We sought to describe the epidemiology of ED visits for SSTI in an urban area with diverse neighborhood populations using the Boston Public Health Commission’s (BPHC) Syndromic Surveillance System (BSynSS) data for a five year time period (2007 through 2011). SSTI related visits were defined by either chief complaints with SSTI associated words (abscess, cellulitis) or final diagnosis International Classification of Diseases (ICD-9 CM) codes for SSTIs. SSTI related visits were de-duplicated using demographics and visit identifiers and then stratified by age group, gender, race, and neighborhood of residence defined by ZIP code. Each of Boston’s 15 neighborhoods has a unique demographic profile with distinct differences in race, socioeconomic status, and age. Finally, we examined trends in characteristics of potential “hotspots” of neighborhood clustering for SSTIs in EDs.
Results
Using our SSTI syndrome definition, we estimated unique SSTI visits represented 3.29 % (n= 45,252) of all visits within Boston’s ten EDs during the study period with a seasonal pattern peaking during the summer months (July through September). The majority of SSTI visits (54%) were among patients 18 to 44 years old, which is consistent with the age distribution of the Boston population. However, a disproportionate number of SSTI visits (43%) were among Black patients when compared to both the overall Boston population (22% Black) and to the racial distribution of all ED visits (39% Black). The five-year average rate of SSTI visits for Black patients (281.2 per 10,000 population) was significantly greater at 2.8 times [CI 2.7, 3.0] than the rate for White patients (99.0 per 10,000 population). Geographic neighborhood distribution of SSTI visits ranged from a low of 2.69% to a high of 4.11% of all neighborhood-specific ED visits. Disposition data are available for 2010 and 2011 only and show that 24% and 23% of patients in 2010 and 2011, respectively, were admitted for their SSTI.
Conclusions
Our study results suggest that syndromic surveillance data can be used to track the burden and patterns of SSTI in an urban population, including disease severity through the use of disposition data. Furthermore, syndromic surveillance can provide information on the local epidemiology of SSTI, including data related to health inequalities. The burden of SSTIs should be compared to overall ED use for a specific population to control for biases in health care seeking behaviors and choice of provider type. A local syndromic surveillance system has the potential to provide public health authorities and ED clinicians near real-time monitoring of trends in severity and demographic risk factors, and may provide an alternative to tracking the severity of illness where no laboratory data are readily available.
PMCID: PMC3692908
syndromic surveillance; epidemiology; skin and soft tissue infections; racial disparities
9.  Monitoring the Impact of Influenza by Age: Emergency Department Fever and Respiratory Complaint Surveillance in New York City 
PLoS Medicine  2007;4(8):e247.
Background
The importance of understanding age when estimating the impact of influenza on hospitalizations and deaths has been well described, yet existing surveillance systems have not made adequate use of age-specific data. Monitoring influenza-related morbidity using electronic health data may provide timely and detailed insight into the age-specific course, impact and epidemiology of seasonal drift and reassortment epidemic viruses. The purpose of this study was to evaluate the use of emergency department (ED) chief complaint data for measuring influenza-attributable morbidity by age and by predominant circulating virus.
Methods and Findings
We analyzed electronically reported ED fever and respiratory chief complaint and viral surveillance data in New York City (NYC) during the 2001–2002 through 2005–2006 influenza seasons, and inferred dominant circulating viruses from national surveillance reports. We estimated influenza-attributable impact as observed visits in excess of a model-predicted baseline during influenza periods, and epidemic timing by threshold and cross correlation. We found excess fever and respiratory ED visits occurred predominantly among school-aged children (8.5 excess ED visits per 1,000 children aged 5–17 y) with little or no impact on adults during the early-2002 B/Victoria-lineage epidemic; increased fever and respiratory ED visits among children younger than 5 y during respiratory syncytial virus-predominant periods preceding epidemic influenza; and excess ED visits across all ages during the 2003–2004 (9.2 excess visits per 1,000 population) and 2004–2005 (5.2 excess visits per 1,000 population) A/H3N2 Fujian-lineage epidemics, with the relative impact shifted within and between seasons from younger to older ages. During each influenza epidemic period in the study, ED visits were increased among school-aged children, and each epidemic peaked among school-aged children before other impacted age groups.
Conclusions
Influenza-related morbidity in NYC was highly age- and strain-specific. The impact of reemerging B/Victoria-lineage influenza was focused primarily on school-aged children born since the virus was last widespread in the US, while epidemic A/Fujian-lineage influenza affected all age groups, consistent with a novel antigenic variant. The correspondence between predominant circulating viruses and excess ED visits, hospitalizations, and deaths shows that excess fever and respiratory ED visits provide a reliable surrogate measure of incident influenza-attributable morbidity. The highly age-specific impact of influenza by subtype and strain suggests that greater age detail be incorporated into ongoing surveillance. Influenza morbidity surveillance using electronic data currently available in many jurisdictions can provide timely and representative information about the age-specific epidemiology of circulating influenza viruses.
Don Olson and colleagues report that influenza-related morbidity in NYC from 2001 to 2006 was highly age- and strain-specific and conclude that surveillance using electronic data can provide timely and representative information about the epidemiology of circulating influenza viruses.
Editors' Summary
Background.
Seasonal outbreaks (epidemics) of influenza (a viral infection of the nose, throat, and airways) send millions of people to their beds every winter. Most recover quickly, but flu epidemics often disrupt daily life and can cause many deaths. Seasonal epidemics occur because influenza viruses continually make small changes to the viral proteins (antigens) that the human immune system recognizes. Consequently, an immune response that combats influenza one year may provide partial or no protection the following year. Occasionally, an influenza virus with large antigenic changes emerges that triggers an influenza pandemic, or global epidemic. To help prepare for both seasonal epidemics and pandemics, public-health officials monitor influenza-related illness and death, investigate unusual outbreaks of respiratory diseases, and characterize circulating strains of the influenza virus. While traditional influenza-related illness surveillance systems rely on relatively slow voluntary clinician reporting of cases with influenza-like illness symptoms, some jurisdictions have also started to use “syndromic” surveillance systems. These use electronic health-related data rather than clinical impression to track illness in the community. For example, increased visits to emergency departments for fever or respiratory (breathing) problems can provide an early warning of an influenza outbreak.
Why Was This Study Done?
Rapid illness surveillance systems have been shown to detect flu outbreaks earlier than is possible through monitoring deaths from pneumonia or influenza. Increases in visits to emergency departments by children for fever or respiratory problems can provide an even earlier indicator. Researchers have not previously examined in detail how fever and respiratory problems by age group correlate with the predominant circulating respiratory viruses. Knowing details like this would help public-health officials detect and respond to influenza epidemics and pandemics. In this study, the researchers have used data collected between 2001 and 2006 in New York City emergency departments to investigate these aspects of syndromic surveillance for influenza.
What Did the Researchers Do and Find?
The researchers analyzed emergency department visits categorized broadly into a fever and respiratory syndrome (which provides an estimate of the total visits attributable to influenza) or more narrowly into an influenza-like illness syndrome (which specifically indicates fever with cough and/or sore throat) with laboratory-confirmed influenza surveillance data. They found that emergency department visits were highest during peak influenza periods, and that the affect on different age groups varied depending on the predominant circulating viruses. In early 2002, an epidemic reemergence of B/Victoria-lineage influenza viruses caused increased visits among school-aged children, while adult visits did not increase. By contrast, during the 2003–2004 season, when the predominant virus was an A/H3N2 Fujian-lineage influenza virus, excess visits occurred in all age groups, though the relative increase was greatest and earliest among school-aged children. During periods of documented respiratory syncytial virus (RSV) circulation, increases in fever and respiratory emergency department visits occurred in children under five years of age regardless of influenza circulation. Finally, the researchers found that excess visits to emergency departments for fever and respiratory symptoms preceded deaths from pneumonia or influenza by about two weeks.
What Do These Findings Mean?
These findings indicate that excess emergency department visits for fever and respiratory symptoms can provide a reliable and timely surrogate measure of illness due to influenza. They also provide new insights into how different influenza viruses affect people of different ages and how the timing and progression of each influenza season differs. These results, based on data collected over only five years in one city, might not be generalizable to other settings or years, warn the researchers. However, the present results strongly suggest that the routine monitoring of influenza might be improved by using electronic health-related data, such as emergency department visit data, and by examining it specifically by age group. Furthermore, by showing that school-aged children can be the first people to be affected by seasonal influenza, these results highlight the important role this age group plays in community-wide transmission of influenza, an observation that could influence the implementation of public-health strategies such as vaccination that aim to protect communities during influenza epidemics and pandemics.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040247.
• US Centers for Disease Control and Prevention provides information on influenza for patients and health professionals and on influenza surveillance in the US (in English, Spanish, and several other languages)
• World Health Organization has a fact sheet on influenza and on global surveillance for influenza (in English, Spanish, French, Russian, Arabic, and Chinese)
• The MedlinePlus encyclopedia contains a page on flu (in English and Spanish)
• US National Institute of Allergy and Infectious Diseases has a feature called “focus on flu”
• A detailed report from the US Centers for Disease Control and Prevention titled “Framework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks” includes a simple description of syndromic surveillance
• The International Society for Disease Surveillance has a collaborative syndromic surveillance public wiki
• The Anthropology of the Contemporary Research Collaboratory includes working papers and discussions by cultural anthropologists studying modern vital systems security and syndromic surveillance
doi:10.1371/journal.pmed.0040247
PMCID: PMC1939858  PMID: 17683196
10.  Exploring relationships between whole carcass condemnation abattoir data, non-disease factors and disease outbreaks in swine herds in Ontario (2001–2007) 
BMC Research Notes  2014;7:185.
Background
Improving upon traditional animal disease surveillance systems may allow more rapid detection of disease outbreaks in animal populations. In Ontario, between the years 2001 – 2007, widespread outbreaks of several diseases caused major impacts to the swine industry. This study was undertaken to investigate whether whole carcass condemnation data of market pigs from provincial abattoirs from 2001 – 2007 could have provided useful information for disease surveillance of Ontario swine. The objective was to examine the suitability of these data for detection of disease outbreaks using multi-level models and spatial scan statistics. We investigated the ability of these data to provide spatially-relevant surveillance information by determining the approximate distance pigs are shipped from farm to provincial abattoirs in the province, and explored potentially biasing non-disease factors within these data.
Results
Provincially-inspected abattoirs in Ontario were found to be located in close proximity to the hog farms of origin. The fall season and increasing abattoir capacity were associated with a decrease in condemnation rates. Condemnation rates varied across agricultural regions by year, and some regions showed yearly trends consistent with the timing of emergence of new disease strains that affected the Ontario swine population. Scan statistics identified stable clusters of condemnations in space that may have represented stable underlying factors influencing condemnations. The temporal scans detected the most likely cluster of high condemnations during the timeframe in which widespread disease events were documented. One space-time cluster took place during the beginning of the historical disease outbreaks and may have provided an early warning signal within a syndromic surveillance system.
Conclusions
Spatial disease surveillance methods may be applicable to whole carcass condemnation data collected at provincially-inspected abattoirs in Ontario for disease detection on a local scale. These data could provide useful information within a syndromic disease surveillance system for protecting swine herd health within the province. However, non-disease factors including region, season and abattoir size need to be considered when applying quantitative methods to abattoir data for disease surveillance.
doi:10.1186/1756-0500-7-185
PMCID: PMC3975458  PMID: 24674622
11.  Meeting the International Health Regulations (2005) surveillance core capacity requirements at the subnational level in Europe: the added value of syndromic surveillance 
BMC Public Health  2015;15:107.
Background
The revised World Health Organization’s International Health Regulations (2005) request a timely and all-hazard approach towards surveillance, especially at the subnational level. We discuss three questions of syndromic surveillance application in the European context for assessing public health emergencies of international concern: (i) can syndromic surveillance support countries, especially the subnational level, to meet the International Health Regulations (2005) core surveillance capacity requirements, (ii) are European syndromic surveillance systems comparable to enable cross-border surveillance, and (iii) at which administrative level should syndromic surveillance best be applied?
Discussion
Despite the ongoing criticism on the usefulness of syndromic surveillance which is related to its clinically nonspecific output, we demonstrate that it was a suitable supplement for timely assessment of the impact of three different public health emergencies affecting Europe. Subnational syndromic surveillance analysis in some cases proved to be of advantage for detecting an event earlier compared to national level analysis. However, in many cases, syndromic surveillance did not detect local events with only a small number of cases.
The European Commission envisions comparability of surveillance output to enable cross-border surveillance. Evaluated against European infectious disease case definitions, syndromic surveillance can contribute to identify cases that might fulfil the clinical case definition but the approach is too unspecific to comply to complete clinical definitions. Syndromic surveillance results still seem feasible for comparable cross-border surveillance as similarly defined syndromes are analysed.
We suggest a new model of implementing syndromic surveillance at the subnational level. In this model, syndromic surveillance systems are fine-tuned to their local context and integrated into the existing subnational surveillance and reporting structure. By enhancing population coverage, events covering several jurisdictions can be identified at higher levels. However, the setup of decentralised and locally adjusted syndromic surveillance systems is more complex compared to the setup of one national or local system.
Summary
We conclude that syndromic surveillance if implemented with large population coverage at the subnational level can help detect and assess the local and regional effect of different types of public health emergencies in a timely manner as required by the International Health Regulations (2005).
doi:10.1186/s12889-015-1421-2
PMCID: PMC4324797
Public health surveillance; Europe; World Health Organization
12.  Molecular Phylodynamic Analysis Indicates Lineage Displacement Occurred in Chinese Rabies Epidemics between 1949 to 2010 
Rabies remains a serious problem in China with three epidemics since 1949 and the country in the midst of the third epidemic. Significantly, the control of each outbreak has been followed by a rapid reemergence of the disease. In 2005, the government implemented a rabies national surveillance program that included the collection and screening of almost 8,000 samples. In this work, we analyzed a Chinese dataset comprising 320 glycoprotein sequences covering 23 provinces and eight species, spanning the second and third epidemics. Specifically, we investigated whether the three epidemics are associated with a single reemerging lineage or a different lineage was responsible for each epidemic. Consistent with previous results, phylogenetic analysis identified six lineages, China I to VI. Analysis of the geographical composition of these lineages revealed they are consistent with human case data and reflect the gradual emergence of China I in the third epidemic. Initially, China I was restricted to south China and China II was dominant. However, as the epidemic began to spread into new areas, China I began to emerge, whereas China II remained confined to south China. By the latter part of the surveillance period, almost all isolates were China I and contributions from the remaining lineages were minimal. The prevalence of China II in the early stages of the third epidemic and its established presence in wildlife suggests that it too replaced a previously dominant lineage during the second epidemic. This lineage replacement may be a consequence of control programs that were dominated by dog culling efforts as the primary control method in the first two epidemics. This had the effect of reducing dominant strains to levels comparable with other localized background stains. Our results indicate the importance of effective control strategies for long term control of the disease.
Author Summary
Since 1949, there have been three rabies epidemics in China. The country is currently in the midst of a third epidemic. After the first two epidemics were brought under control, there was a rapid reemergence of the disease. In 2005, the government implemented a national surveillance program and as part of this work, samples were collected from humans and animals and screened for rabies. Positive samples were sequenced and combined with other publicly available sequences to form a dataset that spanned almost all epidemic regions in China. A phylogenetic tree was constructed the clustering of isolates according to geographic origin and lineage was investigated. We found that most isolates were grouped into two lineages China I and China II. However, the proportion of isolates in these lineages changed over time until almost all new isolates were placed in China I, indicating it has emerged as the dominant lineage. Furthermore, the significantly higher number of China II isolates compared to remaining lineages together with its established presence in wildlife suggests that it was dominant in the second epidemic, suggesting that lineage replacement also occurred during the previous epidemic.
doi:10.1371/journal.pntd.0002294
PMCID: PMC3708843  PMID: 23875035
13.  Predictability of anthrax infection in the Serengeti, Tanzania 
The Journal of applied ecology  2011;48(6):1333-1344.
Summary
Anthrax is endemic throughout Africa, causing considerable livestock and wildlife losses and severe, sometimes fatal, infection in humans. Predicting the risk of infection is therefore important for public health, wildlife conservation and livestock economies. However, because of the intermittent and variable nature of anthrax outbreaks, associated environmental and climatic conditions, and diversity of species affected, the ecology of this multihost pathogen is poorly understood.We explored records of anthrax from the Serengeti ecosystem in north-west Tanzania where the disease has been documented in humans, domestic animals and a range of wildlife. Using spatial and temporal case-detection and seroprevalence data from wild and domestic animals, we investigated spatial, environmental, climatic and species-specific associations in exposure and disease.Anthrax was detected annually in numerous species, but large outbreaks were spatially localized, mostly affecting a few focal herbivores.Soil alkalinity and cumulative weather extremes were identified as useful spatial and temporal predictors of exposure and infection risk, and for triggering the onset of large outbreaks.Interacting ecological and behavioural factors, specifically functional groups and spatiotemporal overlap, helped to explain the variable patterns of infection and exposure among species.Synthesis and applications. Our results shed light on ecological drivers of anthrax infection and suggest that soil alkalinity and prolonged droughts or rains are useful predictors of disease occurrence that could guide risk-based surveillance. These insights should inform strategies for managing anthrax including prophylactic livestock vaccination, timing of public health warnings and antibiotic provision in high-risk areas. However, this research highlights the need for greater surveillance (environmental, serological and case-detection-orientated) to determine the mechanisms underlying anthrax dynamics.
doi:10.1111/j.1365-2664.2011.02030.x
PMCID: PMC3272456  PMID: 22318563
Bacillus anthracis; disease ecology; exposure; infectious disease; multihost; serology; surveillance; susceptibility; zoonosis
14.  Raccoons in San Diego County as Sentinels for West Nile Virus Surveillance 
Objective
To investigate the potential of utilizing raccoons as sentinels for West Nile Virus (WNV) in an effort to guide public health surveillance, prevention, and control efforts.
Introduction
Since its detection in 1999 in New York, WNV spread westward across the continent, and was first detected in California in 2003 in Imperial County (1). In California and in many states, birds, especially corvids, are used as sentinel animals to detect WNV activity. Recent seroprevalence studies have shown WNV activity in different wild mammalian species (1–3); in the United States, WNV sero-prevalence in some studies in raccoons has ranged from 34–46% (3,4). In addition, it has been shown that after experimental infection, raccoons can attain high viral titers and shed WNV in their saliva and feces (5). Given their peridomestic nature, we investigated the feasibility of their use as sentinels for early warning of WNV and as indicators of WNV activity as a strategy to better localize WNV transmission foci in guiding vector control efforts.
Methods
Sick, injured or orphaned raccoons undergoing rehabilitation at Project Wildlife, one of the largest, non-profit wildlife rehabilitation organizations in the United States, located in San Diego County, were tested for WNV shedding. Project Wildlife team members who regularly care for sick, injured, or orphaned raccoons were trained to collect oral and fecal samples for viral testing during 2011 and 2012 upon raccoons’ arrival to Project Wildlife. Oral and fecal samples were tested using real-time PCR for the envelope gene of WNV.
Results
To date 71 raccoons have been tested for WNV and all PCR test results have been negative. Of the 71 raccoons tested from May 2011 to October 2011 and June 2012 to September 2012, 85.9% (n=61) had age classification data. The majority of these raccoons were young; 52.5% (n=32) were days or weeks old and 39.3% (n=24) were classified as juveniles. All raccoons were found primarily in urban settings at least 20 miles from the northern edge of the County.
Conclusions
While none of the raccoon samples tested in this study were found to be WNV positive, surveillance data from San Diego County suggests that WNV activity during this time period was extremely low. From January–October 2011, San Diego County Vector Control reported all negative results for WNV in dead birds, sentinel chickens, horses, and humans for WNV; only 1 mosquito pool from the northern border region of the County tested positive for WNV (6). Thus, despite WNV activity throughout the state of California, the virus did not appear to be circulating widely in San Diego County in 2011 (7). To date during the 2012 season, San Diego County reported all negatives for WNV in dead birds, sentinel chickens, mosquito pools, and horses; only one human case of WNV was identified in an asymptomatic male during a routine blood donation (6).
Further evaluation is needed to determine if raccoons are useful sentinel species for WNV surveillance. Testing should continue to evaluate if raccoons may serve as a more effective early warning sentinel for WNV than birds which can travel long distances from the exposure site, and to determine if raccoons may allow better localization of WNV activity.
PMCID: PMC3692839
West Nile Virus; Early warning surveillance; Raccoons; Sentinels
15.  Establishing a web-based integrated surveillance system for early detection of infectious disease epidemic in rural China: a field experimental study 
Background
A crucial goal of infectious disease surveillance is the early detection of epidemics, which is essential for disease control. In China, the current surveillance system is based on confirmed case reports. In rural China, it is not practical for health units to perform laboratory tests to confirm disease and people are more likely to get 'old' and emerging infectious diseases due to poor living conditions and closer contacts with wild animals and poultry. Syndromic surveillance, which collects non-specific syndromes before diagnosis, has great advantages in promoting the early detection of epidemics and reducing the necessities of disease confirmation. It will be especially effective for surveillance in resource poor settings.
Methods/Design
This is a field experimental study. The experimental tool is an innovative electronic surveillance system, combining syndromic surveillance with the existing case report surveillance in four selected counties in China. In the added syndromic surveillance, three types of data are collected including patients' major symptoms from health clinics, pharmaceutical sales from pharmacies and absenteeism information from primary school. In order to evaluate the early warning capability of the new added syndromic surveillance, the timelines and validity of the alert signals will be analyzed in comparison with the traditional case reporting system. The acceptability, feasibility and economic evaluation of the whole integrated surveillance system will be conducted in a before and after study design.
Discussions
Although syndromic surveillance system has mostly been established in developed areas, there are opportunities and advantages of developing it in rural China. The project will contribute to knowledge, experience and evidence on the establishment of an integrated surveillance system, which aims to provide early warning of disease epidemics in developing countries.
doi:10.1186/1472-6947-12-4
PMCID: PMC3395861  PMID: 22305256
Syndromic surveillance; infectious disease; early warning; resource limited settings
16.  Opportunities and obstacles to collecting wildlife disease data for public health purposes: Results of a pilot study on Vancouver Island, British Columbia 
Existing sources of wildlife morbidity and mortality data were evaluated and 3 pilot active surveillance projects were undertaken to compare and contrast methods for collecting wildlife disease data on Vancouver Island for public health purposes. Few organizations could collect samples for diagnostic evaluation, fewer still maintained records, and none regularly characterized or reported wildlife disease for public health purposes. Wildlife rehabilitation centers encountered the greatest variety of wildlife from the largest geographic area and frequently received submissions from other organizations. Obstacles to participation included the following: permit restrictions; financial disincentives; staff safety; no mandate to collect relevant data; and lack of contact between wildlife and public health agencies. Despite these obstacles, modest investments in personnel allowed novel pathogens of public health concern to be tracked. Targeted surveillance for known pathogens in specific host species, rather than general surveys for unspecified pathogens, was judged to be a more effective and efficient way to provide useful public health data.
PMCID: PMC1716737  PMID: 17310627
17.  Localized Cluster Detection Applied to Joint and Separate Military and Veteran Subpopulations 
Objective
We examined the utility of combining surveillance data from the Departments of Defense (DoD) and Veterans Affairs (VA) for spatial cluster detection.
Introduction
The Joint VA/DoD BioSurveillance System for Emerging Biological Threats project seeks to improve situational awareness of the health of VA/DoD populations by combining their respective data. Each system uses a version of the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE); a combined version is being tested.
The current effort investigated combining the datasets for disease cluster detection. We compared results of retrospective cluster detection studies using both separate and joined data. — Does combining datasets worsen the rate of background cluster determination?
— Does combining mask clusters detected on the separate datasets?
— Does combining find clusters that the separate datasets alone would miss?
Methods
Cluster determination runs were done with a spatial scan statistics implementation previously verified [1] by comparison with SaTScan software [2] using DoD data from the Biosense system.
Input data files were extracted from a repository of outpatient records from both DoD and VA facilities covering 4 years beginning Jan. 1, 2007. This repository includes over 37 million DoD records and over 86 million VA records. Input files were matrices of daily Influenza-like-Illness (ILI) or gastrointestinal (GI) visit counts. Matrix rows were consecutive days, columns were patient residence zip codes, and entry (i, j) was the number of visits on day i from with zip code j. These files were made for DoD data, VA data, and combined data.
For assessing the alerting burden from combining datasets, three sets of runs were executed using data from three regions, Baltimore/Washington D.C. (dominated by DoD data), Los Angeles (mainly VA data), and Tampa (representation of both). For each region, sets of 1672 daily runs were executed for ILI and GI syndrome data. Lastly, focused runs were done to investigate known outbreaks in New York (GI, Jan–Mar 2010), San Diego (ILI, Dec 2007–Apr 2008 and Fall 2009), and New Jersey (GI, Jan–Mar 2010).
Results
Combining the data sources increased the rate of significant cluster alerting by a manageable 1–10% across run sets. Some clusters found only when the data were combined persisted over several days and may have indicated small events not reported in either system; however, we were unable to validate minor events that may have occurred in past years.
Retrospective looks at known outbreaks were successful in that clustering evidence found in separate DoD and VA runs persisted when data sets were combined. For the New York run, a West Point outbreak was seen in repeated clusters of combined data, beginning days before the event report. However, clustering did not consistently produce alerts before outbreak report dates. In the New Jersey DoD runs, repeated clusters indicated a 10-week GI outbreak at Fort Dix; adding VA data that dominated the record counts gave the same clusters with no added cases, so the DoD event was probably self-contained. The San Diego runs were aimed at detecting unusually severe influenza epidemics in February 2008 and in the fall of 2009, and numerous clusters were found but did not enhance regional disease tracking.
Conclusions
From the analysis, combining DoD and VA data enhances cluster detection capability without loss of sensitivity to events isolated in either population and with manageable effect on the customary alert rate. For cluster detection, there may be many geographic regions where a health monitor in one of the systems would benefit from combined data. More detailed outbreak information is needed to quantify the timeliness/sensitivity advantages of combining datasets. In events examined, clustering itself yielded an occasional but not consistent timeliness advantage.
PMCID: PMC3692743
ESSENCE; Department of Defense; scan statistics; cluster detection; Veterans Administration
18.  Examining the Differences in Format and Characteristics of Zoonotic Virus Surveillance Data on State Agency Websites 
Background
Zoonotic viruses are infectious organisms transmittable between animals and humans. Agencies of public health, agriculture, and wildlife conduct surveillance of zoonotic viruses and often report data on their websites. However, the format and characteristics of these data are not known.
Objective
To describe and compare the format and characteristics of statistics of zoonotic viruses on state public health, agriculture, and wildlife agency websites.
Methods
For each state, we considered the websites of that state’s public health, agriculture, and wildlife agency. For each website, we noted the presence of any statistics for zoonotic viruses from 2000-2012. We analyzed the data using numerous categories including type of statistic, temporal and geographic level of detail, and format. We prioritized our analysis within each category based on assumptions of individuals’ preferences for extracting and analyzing data from websites. Thus, if two types of data (such as city and state-level) were present for a given virus in a given year, we counted the one with higher priority (city). External links from agency sites to other websites were not considered.
Results
From 2000-2012, state health departments had the most extensive virus data, followed by agriculture, and then wildlife. We focused on the seven viruses that were common across the three agencies. These included rabies, West Nile virus, eastern equine encephalitis, St. Louis encephalitis, western equine encephalitis, influenza, and dengue fever. Simple numerical totals were most often used to report the data (89% for public health, 81% for agriculture, and 82% for wildlife), and proportions were not different (chi-square P=.15). Public health data were most often presented yearly (66%), while agriculture and wildlife agencies often described cases as they occurred (Fisher’s Exact test P<.001). Regarding format, public health agencies had more downloadable PDF files (68%), while agriculture (61%) and wildlife agencies (46%) presented data directly in the text of the HTML webpage (Fisher’s Exact test P<.001). Demographics and other information including age, gender, and host were limited. Finally, a Fisher’s Exact test showed no association between geography data and agency type (P=.08). However, it was noted that agriculture department data was often at the county level (63%), while public health was mixed between county (38%) and state (35%).
Conclusions
This study focused on the format and characteristics of statistics of zoonotic viruses on websites of state public health, wildlife, and agriculture agencies in the context of population health surveillance. Data on zoonotic viruses varied across agencies presenting challenges for researchers needing to integrate animal and human data from different websites.
doi:10.2196/jmir.2487
PMCID: PMC3650930  PMID: 23628771
public health; zoonoses; World Wide Web; epidemiology; data analysis
19.  Wildlife health investigations: needs, challenges and recommendations 
In a fast changing world with growing concerns about biodiversity loss and an increasing number of animal and human diseases emerging from wildlife, the need for effective wildlife health investigations including both surveillance and research is now widely recognized. However, procedures applicable to and knowledge acquired from studies related to domestic animal and human health can be on partly extrapolated to wildlife. This article identifies requirements and challenges inherent in wildlife health investigations, reviews important definitions and novel health investigation methods, and proposes tools and strategies for effective wildlife health surveillance programs. Impediments to wildlife health investigations are largely related to zoological, behavioral and ecological characteristics of wildlife populations and to limited access to investigation materials. These concerns should not be viewed as insurmountable but it is imperative that they are considered in study design, data analysis and result interpretation. It is particularly crucial to remember that health surveillance does not begin in the laboratory but in the fields. In this context, participatory approaches and mutual respect are essential. Furthermore, interdisciplinarity and open minds are necessary because a wide range of tools and knowledge from different fields need to be integrated in wildlife health surveillance and research. The identification of factors contributing to disease emergence requires the comparison of health and ecological data over time and among geographical regions. Finally, there is a need for the development and validation of diagnostic tests for wildlife species and for data on free-ranging population densities. Training of health professionals in wildlife diseases should also be improved. Overall, the article particularly emphasizes five needs of wildlife health investigations: communication and collaboration; use of synergies and triangulation approaches; investments for the long term; systematic collection of metadata; and harmonization of definitions and methods.
doi:10.1186/1746-6148-9-223
PMCID: PMC4228302  PMID: 24188616
Collaboration; Definitions; Harmonization; Health; Impediments; Surveillance; Strategies; Risk factors; Tools; Wildlife
20.  The Distribution of Infectious Related Symptoms in an Internet-based Syndromic Surveillance System in Rural China 
Objective
To describe the distribution of the infectious related symptoms in an internet-based syndromic surveillance system reported by doctors in village health stations, township and county hospitals in rural Jiangxi Province, China, and to identify the major infectious diseases for syndromic surveillance in different levels of health facility.
Introduction
Syndromic surveillance system, which collects non-specific syndromes in the early stages of disease development, has great advantages in promoting early detection of epidemics and reducing the burden of disease confirmation (1). It is especially effective for surveillance in resource-poor settings, where laboratory confirmation is not possible or practical (2). Integrating syndromic surveillance with traditional case report system may generate timely, effective and sensitive information for early warning and control of infectious diseases in rural China (3). A syndromic surveillance system (ISSC) has been implemented in rural Jiangxi Province of China since August 2011.
Methods
Doctors and health workers in the healthcare surveillance units of ISSC, including village health station, township hospital and county hospital, used an internet-based electronic system to collect information of daily outpatients, which included 10 categories of infectious disease related symptoms, i.e., cough, fever, sore throat, diarrhea, headache, rash, nausea/vomit, mucocutaneous hemorrhage, convulsion and disturbance of consciousness. The data from August 1st to December 31st 2011 were extracted from database and analyzed using SPSS 16.0. The combination of symptoms was also analyzed to identify patients with the syndrome of influenza-like illness (ILI) and fever-gastrointestinal syndrome (FGS). ILI were composed by fever (>=38 degree centigrade) plus cough or fever plus sore throat, and FGS were defined as fever plus vomit or diarrhea.
Results
Two county hospitals (CH), 4 township hospitals (TH) and 50 village health stations (VHS) were selected as surveillance unites in the pilot study during 2011/8/1 to 2011/12/31. In total, 152270 outpatient visits were reported, and 35395 patients had a chief complain of at least one surveillance symptom. Of these symptomatic patients, 24130 (68.2%) were from VHS, 4995 (14.1%) from TH and 6810 (19.2%) from CH. The proportion of patients with targeting symptom accounted for 15.5%, 66.4% and 23.9% of total outpatients in CH, TH and VHS respectively. The first 3 reported symptoms were cough (61.8%), fever (28.4%), and sore throat (23.4%), whereas mucocutaneous hemorrhage, convulsion and disturbance of consciousness were the least frequently reported symptoms in all surveillance units. Overall 3582 ILI and 1160 FGS cases were reported accounting for 35% and 11% of fever cases respectively. Of the reported ILI and FGS cases, 75% ILI and 55.9% FGS cases were reported by health workers in the VHS.
Conclusions
Cough, fever and sore throat were the top surveillance symptoms, and the respiratory infectious diseases had more chance to be reported in syndromic surveillance system in rural Jiangxi Province. Training on infectious disease diagnosis especially respiratory diseases for village health workers should be enhanced since large numbers of patients are likely to visit the village health stations.
PMCID: PMC3692925
Syndromic surveillance; rural; influenza-likes illness; fever-gastrointestinal syndrome
21.  Evaluating Usefulness of Maine’s Syndromic Surveillance System for Hospitals, 2012 
Objective
To assess the usefulness and acceptability of Maine’s syndromic surveillance system among hospitals who currently participate.
Introduction
Maine has been conducting syndromic surveillance since 2007 using the Early Aberration Reporting System (EARS). An evaluation of the syndromic surveillance system was conducted to determine if system objectives are being met, assess the system’s usefulness, and identify areas for improvement. According to CDC’s Guidelines for Evaluating Public Health Surveillance Systems, a surveillance system is useful if it contributes to the timely prevention and control of adverse health events. Acceptability includes the willingness of participants to report surveillance data; participation or reporting rate; and completeness of data.
Methods
A survey was created in 2012 to measure usefulness and acceptability among hospital partners who submit emergency department data to Maine CDC for syndromic surveillance. Currently, 24 of Maine’s 37 emergency departments collect syndromic surveillance data and 20 of those receive a weekly syndromic surveillance report from Maine CDC. The survey was included with the report on August 14, 2012, and hospitals were given two weeks for completion. The survey included questions about how useful hospitals find syndromic surveillance and how data is shared back with the hospitals; which syndromes are most and least useful; and chief complaint data collection at individual hospitals.
Results
The survey was completed by 13 out of 22 emergency departments (59% participation rate), and six out of 13 respondents (46%) completed the entire survey. The factors reported as having an influence on a hospital’s decision to submit data for syndromic surveillance were: public health importance of events (6 respondents) and assurance of privacy/confidentiality (5 respondents). The majority of respondents (5 respondents) reported that there are no factors that limit their ability to send emergency department data. Among hospitals that did report factors that limit their ability to send data, lack of information technology support in the hospital (2 respondents) and manually entering data/lack of electronic health records (1 respondent) were the most frequently reported. Six out of seven hospitals who answered (86°%) reported the current method of sharing syndromic surveillance data on a weekly basis, including a statewide data summary, as useful. Respondents also recommended that data be shared back with participants using 30-day line graphs for each syndrome (4 respondents). The three syndromes respondents found most useful were influenzalike illness (7 respondents), gastrointestinal (5 respondents), and respiratory (5 respondents). The three syndromes respondents found least useful were the broad heat syndrome (4 respondents), the narrow heat syndrome (4 respondents), and the other syndrome that captures all visits not classified into any syndrome (4 respondents). Chief complaint data, which is used to classify emergency department visits into syndromes, is most often recorded by a drop-menu (4 respondents).
Conclusions
With a low survey completion rate, it is difficult to generalize responses to all hospitals who participate in syndromic surveillance. Hospitals that did not respond to or complete the survey will be followed up with to determine their reasons for not doing so, as this may be useful information. In general, those who responded have more factors that influence them to contribute to syndromic surveillance than factors that hinder them. Most hospitals find the current method of sharing data back with the hospitals useful. Also, it is advantageous to know which syndromes the hospitals find most useful, as they are the entities that collect and report the data. Opinions differ among system users, which is why it is important to evaluate a system throughout all points of interaction.
PMCID: PMC3692825
Syndromic surveillance; Evaluation; Acceptability
22.  Long-Term Asthma Trend Monitoring in New York City: A Mixed Model Approach 
Objective
Show the benefits of using a generalized linear mixed model (GLMM) to examine long-term trends in asthma syndrome data.
Introduction
Over the last decade, the application of syndromic surveillance systems has expanded beyond early event detection to include long-term disease trend monitoring. However, statistical methods employed for analyzing syndromic data tend to focus on early event detection. Generalized linear mixed models (GLMMs) may be a useful statistical framework for examining long-term disease trends because, unlike other models, GLMMs account for clustering common in syndromic data, and GLMMs can assess disease rates at multiple spatial and temporal levels (1). We show the benefits of the GLMM by using a GLMM to estimate asthma syndrome rates in New York City from 2007 to 2012, and to compare high and low asthma rates in Harlem and the Upper East Side (UES) of Manhattan.
Methods
Asthma related emergency department (ED) visits, and patient age and ZIP code were obtained from data reported daily to the NYC Department of Health and Mental Hygiene. Demographic data were obtained from 2010 US Census. ZIP codes that represented high and low asthma rates in Harlem and the UES of Manhattan were chosen for closer inspection. The ratio of weekly asthma syndrome visits to total ED visits was modeled with a Poisson GLMM with week and ZIP code random intercepts (2). Age and ethnicity were adjusted for because of their association with asthma rates (3).
Results
The GLMM showed citywide asthma rates remained stable from 2007 to 2012, but seasonal differences and significant inter-ZIP code variation were present. The Harlem ZIP code asthma rate that was estimated with the GLMM was significantly higher (5.83%, 95% CI: 3.65%, 9.49%) than the asthma rate in UES ZIP code (0.78%, 95% CI: 0.50%, 1.21%). A linear time component to the GLMM showed no appreciable change over time despite the seasonal fluctuations in asthma rate. GLMM based asthma rates are shown over time (Figure 1).
Conclusions
GLMMs have several strengths as statistical frameworks for monitoring trends including: Disease rates can be estimated at multiple spatial and temporal levels,Standard error adjustment for clustering in syndromic data allows for accurate, statistical assessment of changes over time and differences between subgroups,“Strength borrowed” (4) from the aggregated data informs small subgroups and smooths trends,Integration of covariate data reduces bias in estimated rates.
GLMMs have previously been suggested for early event detection with syndromic surveillance data (5), but the versatility of GLMM makes them useful for monitoring long-term disease trends as well. In comparison to GLMMs, standard errors from single level GLMs do not account for clustering and can lead to inaccurate statistical hypothesis testing. Bayesian hierarchical models (6), share many of the strengths of GLMMS, but are more complicated to fit. In the future, GLMMs could provide a framework for grouping similar ZIP codes based on their model estimates (e.g. seasonal trends and influence on overall trend), and analyzing long-term disease trends with syndromic data.
PMCID: PMC3692769
Asthma; Long term trends; Generalized Mixed Models
23.  Selecting Targeted Symptoms/Syndromes for Syndromic Surveillance in Rural China 
Objective
To select the potential targeted symptoms/syndromes as early warning indicators for epidemics or outbreaks detection in rural China.
Introduction
Patients’ chief complaints (CCs) as a common data source, has been widely used in syndromic surveillance due to its timeliness, accuracy and availability (1). For automated syndromic surveillance, CCs always classified into predefined syndromic categories to facilitate subsequent data aggregation and analysis. However, in rural China, most outpatient doctors recorded the information of patients (e.g. CCs) into clinic logs manually rather than computers. Thus, more convenient surveillance method is needed in the syndromic surveillance project (ISSC). And the first and important thing is to select the targeted symptoms/syndromes.
Methods
Epidemiological analysis was conducted on data from case report system in Jingmen City (one study site in ISSC) from 2004 to 2009. Initial symptoms/syndromes were selected by literature reviews. And finally expert consultation meetings, workshops and field investigation were held to confirm the targeted symptoms/syndromes.
Results
10 kinds of infectious diseases, 6 categories of emergencies, and 4 bioterrorism events (i.e. plague, anthrax, botulism and hemorrhagic fever) were chose as specific diseases/events for monitoring (Table 1). Two surveillance schemes were developed by reviewing on 565 literatures about clinical conditions of specific diseases/events and 14 literatures about CCs based syndromic surveillance. The former one was to monitor symptoms (19 initial symptoms), and then aggregation or analysis on single or combined symptom(s); and the other one was to monitor syndromes (9 initial syndromes) directly (Table 2). The consultation meeting and field investigation identified three issues which should be considered: 1) the abilities of doctors especially village doctors to understand the definitions of symptoms/syndromes; 2) the workload of data collection; 3) the sensitive and specific of each symptom/syndrome. Finally, Scheme 1 was used and 10 targeted symptoms were determined (Table 2).
Conclusions
We should take the simple, stability and feasibility of operation, and also the local conditions into account before establishing a surveillance system. Symptoms were more suitable for monitoring compared to syndromes in resource-poor settings. Further evaluated and validated would be conducted during implementation. Our study might provide methods and evidences for other developing countries with limited conditions in using automated syndromic surveillance system, to construct similar early warning system.
PMCID: PMC3692788
Syndromic surveillance; Chief complaint; Early warning
24.  Leptospirosis in American Samoa – Estimating and Mapping Risk Using Environmental Data 
Background
The recent emergence of leptospirosis has been linked to many environmental drivers of disease transmission. Accurate epidemiological data are lacking because of under-diagnosis, poor laboratory capacity, and inadequate surveillance. Predictive risk maps have been produced for many diseases to identify high-risk areas for infection and guide allocation of public health resources, and are particularly useful where disease surveillance is poor. To date, no predictive risk maps have been produced for leptospirosis. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk.
Methodology and Principal Findings
Data on seroprevalence and risk factors were obtained from a recent study of leptospirosis in American Samoa. Data on environmental variables were obtained from local sources, and included rainfall, altitude, vegetation, soil type, and location of backyard piggeries. Multivariable logistic regression was performed to investigate associations between seropositivity and risk factors. Using the multivariable models, seroprevalence at geographic locations was predicted based on environmental variables. Goodness of fit of models was measured using area under the curve of the receiver operating characteristic, and the percentage of cases correctly classified as seropositive. Environmental predictors of seroprevalence included living below median altitude of a village, in agricultural areas, on clay soil, and higher density of piggeries above the house. Models had acceptable goodness of fit, and correctly classified ∼84% of cases.
Conclusions and Significance
Environmental variables could be used to identify high-risk areas for leptospirosis. Environmental monitoring could potentially be a valuable strategy for leptospirosis control, and allow us to move from disease surveillance to environmental health hazard surveillance as a more cost-effective tool for directing public health interventions.
Author Summary
Leptospirosis is the most common bacterial infection transmitted from animals to humans. Infected animals excrete the bacteria in their urine, and humans can become infected through contact with animals or a contaminated environment such as water and soil. Environmental factors are important in determining the risk of human infection, and differ between ecological settings. The wide range of risk factors include high rainfall and flooding; poor sanitation and hygiene; urbanisation and overcrowding; contact with animals (including rodents, livestock, pets, and wildlife); outdoor recreation and ecotourism; and environmental degradation. Predictive risk maps have been produced for many infectious diseases to identify high-risk areas for transmission and guide allocation of public health resources. Maps are particularly useful where disease surveillance and epidemiological data are poor. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk. This study demonstrated the value of geographic information systems and disease mapping for identifying environmental risk factors for leptospirosis, and enhancing our understanding of disease transmission. Similar principles could be used to investigate the epidemiology of leptospirosis in other areas.
doi:10.1371/journal.pntd.0001669
PMCID: PMC3362644  PMID: 22666516
25.  The Surveillance Window – Contextualizing Data Streams 
Objective
The goal of this project is the evaluation of data stream utility in integrated, global disease surveillance. This effort is part of a larger project with the goal of developing tools to provide decision-makers with timely information to predict, prepare for, and mitigate the spread of disease.
Introduction
Los Alamos National Laboratory has been funded by the Defense Threat Reduction Agency to determine the relevance of data streams for an integrated global biosurveillance system. We used a novel method of evaluating the effectiveness of data streams called the “surveillance window”. The concept of the surveillance window is defined as the brief period of time when information gathered can be used to assist decision makers in effectively responding to an impending outbreak. We used a stepwise approach to defining disease specific surveillance windows; Timeline generation through historical perspectives and epidemiological simulations.Identifying the surveillance windows between changes in “epidemiological state” of an outbreak.Data streams that are used or could have been used due to their availability during the generated timeline are identified. If these data streams fall within a surveillance window, and provide both actionable and non-actionable information, they are deemed to have utility.
Methods
Figure 1 shows the overall approach to using this method for evaluating data stream types. Our first step was identifying a list of priority diseases to build surveillance windows for and our primary sources were our SME panel, CDC priorities, as well as DOD priorities. We also conducted a literature review to support our selection of diseases. We ensured that there was representation of human, animal and plant diseases and there was enough data available for selected outbreaks to facilitate evaluation of all data stream types identified. We then selected representative outbreaks for diseases to generate a timeline for defining surveillance windows. Surveillance windows were then defined (based on four specific biosurveillance goals developed by LANL) and information for applicable data streams was collected for the duration of the outbreak. A data stream was deemed useful if it was determined to be available within the defined surveillance window. In addition, evaluation of the ideal use case of the data streams was performed. In essence, if used more effectively could this data stream provide greater support to understanding, detection, warning or management of disease outbreaks or event situations?
Results
Results presented in this abstract are from retrospective analyses of historical outbreaks selected as being representative of FMD, Ebola, Influenza and E.coli. Graphs indicating case counts and geographical spread were combined and a timeline was created to determine the length of time between changes in “epidemiological state” that defined various surveillance windows. This timeline was then populated with durations when data streams were used during the outbreak. Results showed varying surveillance windows times are dependent on disease characteristics. In turn, epidemiology of the disease affected the occurrence of data streams on the timeline.
Conclusions
Surveillance window based evaluation of data streams during disease outbreaks helped identify data streams that are of significance for developing an effective biosurveillance system. Some data streams were identified to have high utility for early detection and early warning regardless of disease, while others were more disease and operations specific. This work also identified data streams currently not in use that could be exploited for faster outbreak detection. Key useful data streams that are underlying to all disease categories and thus important for integration into global biosurveillance programs will be presented here.
PMCID: PMC3692758
Surveilliance Windows; Data streams; Biosurveilliance

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