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Harmon Robert

Influenza affects millions of people and causes about 36,000 deaths in the United States each winter. Pandemics of influenza emerge at irregular intervals. National influenza surveillance is used to detect the emergence and spread of influenza virus variants and to monitor influenza-related morbidity and mortality. Existing surveillance consists of seven data types, which are reported weekly. Newly available national electronic data sources created as part of the routine delivery of medical care might supplement current data sources. Nurse call data offer national coverage, are timely, and do not require any extra manual data entry. Using such data for influenza-like illness (ILI) surveillance may lead to earlier detection of ILI in the community, both because people with ILI may call a nurse line before seeking care at a health-care facility and because the data are more timely than existing weekly data.

 

Objective

Our purpose was to compare nurse call data for respiratory and ILI against CDC national influenza surveillance data from the 2004-2005 season by region to determine if the call data were informative and might allow earlier detection of influenza activity.

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National surveillance is used to detect the emergence and spread of influenza virus variants and to monitor influenza-related morbidity and mortality. Nurse telephone triage (“call”) data may serve as a useful complement to traditional influenza surveillance, especially at times or in places traditional surveillance is not operating. It may also be useful to detect increased occurrence of non-influenza respiratory infection.

 

Objective

We compared state-level nurse call data to CDC national influenza surveillance data to determine how well call data performed relative to CDC sentinel provider and viral isolate data. This quantitative analysis extends an earlier semiquantitative regional analysis of the same data.

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The purpose of this study is to depict a local county health departmentís analysis and dissemination algorithm of surveillance system (SS) aberration (alarm) to designated stakeholders within the community.

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Public Health departments are increasingly called upon to be innovative in quality service delivery under a dwindling resource climate as highlighted in several publications of the Institute of Medicine. Collaboration with other entities in the delivery of core public health services has emerged as a recurring theme. One model of this collaboration is an academic health department: a formal affiliation between a health professions school and a local health department. Initially targeted at workforce development, this model of collaboration has since yielded dividends in other core public health service areas including community assessment, program evaluation, community-based participatory research and data analysis.

The Duval County Health Department (DCHD), Florida, presents a unique community-centered model of the academic health department. Prominence in local informatics infrastructure capacity building and hosting a CDC-CSTE applied public health informatics fellowship (APHIF) in the Institute for Public Health Informatics and Research (IPHIR) in partnership with the Center for Health Equity Research, University of Florida & Shands medical center are direct dividends of this collaborative model.

 

Objective

Highlight one academic health department’s unique approach to optimizing collaborative opportunities for capacity development and document the implications for chronic disease surveillance and population health.

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