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Pelt Wilfrid

Accurately assigning causes or contributing causes to deaths remains a universal challenge, especially in the elderly with underlying disease. Cause of death statistics commonly record the underlying cause of death, and influenza deaths in winter are often attributed to underlying circulatory disorders. Estimating the number of deaths attributable to influenza is, therefore, usually performed using statistical models. These regression models (usually linear or poisson regression are applied) are flexible and can be built to incorporate trends in addition to influenza virus activity such as surveillance data on other viruses, bacteria, pure seasonal trends and temperature trends.

 

Objective

Mortality exhibits clear seasonality mainly caused by an increase in deaths in the elderly in winter. As there may be substantial hidden mortality for a number of common pathogens, we estimated the number of elderly deaths attributable to common seasonal viruses and bacteria for which robust weekly laboratory surveillance data were available.

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Objective

To study if syndromic surveillance would have an added value over existing surveillance systems, we retrospectively evaluated whether known trends in respiratory pathogens are reflected in medical registrations in the Netherlands when using respiratory syndrome groupings.

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Objective

Understanding the baseline dynamics of syndrome counts is essential for use in prospective syndromic surveillance. Therefore we studied to what extent the known seasonal dynamics of gastro-intestinal (GI) pathogens explain the dynamics in GI syndrome in general practitioner and hospital data.

 

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Crude mortality could be valuable for infectious disease surveillance if available in a complete and timely fashion. Syndromic surveillance with weekly deaths has been demonstrated to be useful in France. Such data can be of use for detecting, and tracking the impact, of unusual health events (e.g. pandemic influenza) or other unexpected or unknown events of infectious nature. To evaluate whether these aims can be achieved with crude mortality monitoring in the Netherlands, we investigated trends in death notifications and we tested whether retrospective crude mortality trends, at different days of delay, reflect known trends in infectious pathogens that are associated with death (such as influenza).

 

Objective

To evaluate the potential of mortality data in the Netherlands for real-time surveillance of infectious events.

Referenced File
Submitted by elamb on

Crude mortality could be valuable for infectious disease surveillance if available in a complete and timely fashion. Such data can be of used for detecting, and tracking the impact of unusual health events (e.g. pandemic influenza) or other unexpected or unknown events of infectious nature.

To evaluate whether these goals can be achieved with crude mortality monitoring in the Netherlands, a pilot study was set up in 2008 in which death counts were received from Statistics Netherlands. 

The aims of this pilot are: 1) Setting up communication and data transmission. 2) Calculating expected mortality counts (depending on the season) and a prediction interval. 3) Detecting deviations in mortality counts above the threshold. 4) Comparing such deviations (and lags hereof) with other public health information (such as sentinel influenza-like-illness surveillance, and web-based selfreported ILI). 4) Evaluating the additional value of such a system for infectious disease public health.

 

Objective

To evaluate the potential use of mortality data in the Netherlands for real-time surveillance of infectious disease events through a pilot study.

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Submitted by elamb on

To evaluate the added value of a syndromic surveillance system in detecting a large severe respiratory disease outbreak with a point-source we used the Legionnaires' disease (LD) outbreak of 1999 in the Netherlands as a case-study. We retrospectively simulated a prospective syndromic surveillance for space-time clusters of patients with pneumonia in hospital records to detect the LD outbreak.

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Syndromic surveillance may be suited for detection of emerging respiratory disease elevations that could pass undiagnosed. The syndromes under surveillance should then retrospectively reflect known respiratory pathogen activity. To validate this for respiratory syndromes we analyzed dutch medical registration data from 1999-2003 (national hospital discharge diagnoses and causes of death). We assume that syndromes with a good reflection of pathogen activity have the potential ability to reflect unexpected respiratory pathogen activity in prospective surveillance.

Objective

As a validation for syndromic surveillance we studied whether respiratory syndromes indeed reflect the activity of respiratory pathogens. Therefore we retrospectively estimated the temporal trend of two respiratory syndromes by the seasonal dynamics of common respiratory pathogens.

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Submitted by elamb on

To estimate diagnostic demand in case of pandemic threat using trends in respiratory syndromes (as input for a laboratory preparedness program).

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