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      Syndromic surveillance in public health practice, New York City.

      Emerging Infectious Diseases
      Adolescent, Adult, Aged, Child, Child, Preschool, Cluster Analysis, Data Collection, Diarrhea, epidemiology, Disease Outbreaks, Emergency Service, Hospital, statistics & numerical data, utilization, Fever, Humans, Infant, Infant, Newborn, Middle Aged, New York City, Population Surveillance, Public Health Informatics, methods, Public Health Practice, Respiratory Tract Infections, Syndrome, Vomiting

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          Abstract

          The New York City Department of Health and Mental Hygiene has established a syndromic surveillance system that monitors emergency department visits to detect disease outbreaks early. Routinely collected chief complaint information is transmitted electronically to the health department daily and analyzed for temporal and spatial aberrations. Respiratory, fever, diarrhea, and vomiting are the key syndromes analyzed. Statistically significant aberrations or "signals" are investigated to determine their public health importance. In the first year of operation (November 15, 2001, to November 14, 2002), 2.5 million visits were reported from 39 participating emergency departments, covering an estimated 75% of annual visits. Most signals for the respiratory and fever syndromes (64% and 95%, respectively) occurred during periods of peak influenza A and B activity. Eighty-three percent of the signals for diarrhea and 88% of the signals for vomiting occurred during periods of suspected norovirus and rotavirus transmission.

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          Prospective time periodic geographical disease surveillance using a scan statistic

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            Broadening participation in community problem solving: a multidisciplinary model to support collaborative practice and research.

            Over the last 40 years, thousands of communities-in the United States and internationally-have been working to broaden the involvement of people and organizations in addressing community-level problems related to health and other areas. Yet, in spite of this experience, many communities are having substantial difficulty achieving their collaborative objective, and many funders of community partnerships and participation initiatives are looking for ways to get more out of their investment. One of the reasons we are in this predicament is that the practitioners and researchers who are interested in community collaboration come from a variety of contexts, initiatives, and academic disciplines, and few of them have integrated their work with experiences or literatures beyond their own domain. In this article, we seek to overcome some of this fragmentation of effort by presenting a multidisciplinary model that lays out the pathways by which broadly participatory processes lead to more effective community problem solving and to improvements in community health. The model, which builds on a broad array of practical experience as well as conceptual and empirical work in multiple fields, is an outgrowth of a joint-learning work group that was organized to support nine communities in the Turning Point initiative. Following a detailed explication of the model, the article focuses on the implications of the model for research, practice, and policy. It describes how the model can help researchers answer the fundamental effectiveness and "how-to" questions related to community collaboration. In addition, the article explores differences between the model and current practice, suggesting strategies that can help the participants in, and funders of, community collaborations strengthen their efforts.
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              Is Open Access

              Dead Bird Clusters as an Early Warning System for West Nile Virus Activity

              An early warning system for West Nile virus (WNV) outbreaks could provide a basis for targeted public education and surveillance activities as well as more timely larval and adult mosquito control. We adapted the spatial scan statistic for prospective detection of infectious disease outbreaks, applied the results to data on dead birds reported from New York City in 2000, and reviewed its utility in providing an early warning of WNV activity in 2001. Prospective geographic cluster analysis of dead bird reports may provide early warning of increasing viral activity in birds and mosquitoes, allowing jurisdictions to triage limited mosquito-collection and laboratory resources and more effectively prevent human disease caused by the virus. This adaptation of the scan statistic could also be useful in other infectious disease surveillance systems, including that for bioterrorism.
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