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Sentinel Site Surveillance

Description

Salt Lake Valley Health Department uses syndromic surveillance to monitor influenza-like illness (ILI) activity as part of a comprehensive influenza surveillance program that includes pathogen-specific surveillance, sentinel surveillance, school absenteeism and pneumonia, and influenza mortality. During the 2009 spring and fall waves of novel H1N1 influenza, sentinel surveillance became increasingly burdensome for both community clinics and Salt Lake Valley Health Department, and an accurate, more efficient method for ILI surveillance was needed. One study found that syndromic surveillance performed, as well as a sentinel provider system in detecting an influenza outbreak and syndromic surveillance is currently used to monitor regional ILI in the United States.

 

Objective

The objective of this study is to compare the performance of syndromic surveillance with the United States Outpatient Influenza-like Illness Surveillance Network (ILINet), for the

detection of ILI during the fall 2009 wave of H1N1 influenza in Salt Lake County.

Submitted by hparton on
Description

The New York City (NYC) Department of Health and Mental Hygiene monitors visits daily from 49 of 54 NYC emergency departments (EDs), capturing 95% of all ED visits. ED visits for influenza-like illness (ILI) have reflected influenza activity in NYC, better than the more broadly defined fever/flu and respiratory syndromes, but the correlation with H1N1 is unknown. 

Laboratory-confirmed influenza and respiratory syncytial virus (RSV) were made reportable in NYC in February 2008. DOHMH receives electronic reports of positive tests. 

As part of 2009–10 influenza surveillance, five hospitals were selected for ‘sentinel’ surveillance of hospitalized influenza cases, to test all patients with a respiratory condition for influenza. Sentinel hospitals ensured that patient medical record numbers were in the daily ED syndromic file and in the electronic laboratory reports.

 

Objective

To determine the correlation of the ILI syndrome with laboratory-confirmed H1N1 and RSV during the October 2009 to March 2010 H1N1 season in NYC.

Submitted by hparton on
Description

In 1911, Christophers developed an early-warning system for malaria epidemics in Punjab based on rainfall, fever-related deaths and wheat prices. Since that initial system, researchers and practitioners have continued to search for determinants of spatial and temporal variability of malaria to improve systems for forecasting disease burden. Malaria thrives in poor tropical and subtropical countries where resources are limited. Accurate disease prediction and early warning of increased disease burden can provide public health and clinical health services with the information needed to implement targeted approaches for malaria control and prevention that make effective use of limited resources. Malaria forecasting models do not typically consider clinical predictors, such as type of antimalarial treatment, in the forecasting models. 

Objective

The objective of the research was to identify the most accurate models for forecasting malaria at six different sentinel sites in Uganda, using environmental and clinical data sources.

Submitted by elamb on