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The New York City (NYC) Department of Health and Mental Hygiene (DOHMH) receives daily ED data from 49 of NYC’s 52 hospitals, representing approximately 95% of ED visits citywide. Chief complaint (CC) is categorized into syndrome groupings using text recognition of symptom key-words and phrases... Read more

Content type: Abstract

Over the last decade, the application of syndromic surveillance systems has expanded beyond early event detection to include longterm disease trend monitoring. However, statistical methods employed for analyzing syndromic data tend to focus on early event detection. Generalized linear mixed... Read more

Content type: Abstract

The impact of heat on mortality is well documented but deaths tend to lag extreme heat and mortality data is generally not available for timely surveillance during heat waves. Recently, systems for near-real time surveillance of heat illness have been reported but have not been validated as... Read more

Content type: Abstract

Extreme temperatures are consistently shown to have an effect on CVD-related mortality [1, 2]. A large multi-city study of mortality demonstrated a cold-day and hot-day weather effect on CVD-related deaths, with the larger impact occurring on the coldest days [3]. In contrast, the association... Read more

Content type: Abstract

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... Read more

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As technology advances, the implementation of statistically and computationally intensive methods to detect unusual clusters of illness becomes increasingly feasible at the state and local level [2]. Bayesian methods allow for the incorporation of prior knowledge directly into the model, which... Read more

Content type: Abstract

The CC text field is a rich source of information, but its current use for syndromic surveillance is limited to a fixed set of syndromes that are routine, suspected, expected, or discovered by chance. In addition to syndromes that are routinely monitored by the NYC Department of Health and... Read more

Content type: Abstract

ARIMA models use past values (autoregressive terms) and past forecasting errors (moving average terms) to generate future forecasts, making it a potential candidate method for modeling citywide time series of syndromic data [1]. While past research supports the use of ARIMA modeling as a... Read more

Content type: Abstract

Data from the Emergency Departments (EDs) of 49 hospitals in New York City (NYC) is sent to the Department of Health and Mental Hygiene (DOHMH) daily as part of the syndromic surveillance system. Currently, thirty-four of the EDs transmit data as flat files. As part of the Center for Medicare... Read more

Content type: Abstract

The New York City (NYC) syndromic surveillance system has monitored syndromes from NYC emergency department (ED) visits since 2001, using the temporal and spatial scan statistic in SaTScan for aberration detection. Since our syndromic system was initiated, alternative methods have been proposed... Read more

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INTERNATIONAL SOCIETY FOR
DISEASE SURVEILLANCE

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This Knowledge Repository is made possible through the activities of the Centers for Disease Control and Prevention Cooperative Agreement/Grant #1 NU500E000098-01, National Surveillance Program Community of Practice (NSSP-CoP): Strengthening Health Surveillance Capabilities Nationwide, which is in the interest of public health.

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