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van Asten Liselotte

Surveillance of severe influenza infections is lacking in the Netherlands. Ambulance dispatch (AD) data may provide information about severity of the influenza epidemic and its burden on emergency services. The current gold standard, primary care-based surveillance of influenza-like-illness (ILI), mainly captures mild to moderate influenza cases, and does not provide adequate information on severe disease. Monitoring the severity of the annual epidemic, particularly among groups most at risk of complications, is of importance for the planning of health services and the public health response.

Objective: We aim to assess whether influenza circulation, as measured through influenza-like-illness (ILI) in primary care, is reflected in ambulance dispatch (AD) calls.

Submitted by elamb on

While influenza-like-illness (ILI) surveillance is well-organized at primary care level in Europe, little data is available on more severe cases. With retrospective data from ICU's we aim to fill this current knowledge gap and to explore its worth for prospective surveillance. Using multiple parameters proposed by the World Health Organization we estimated the burden of severe acute respiratory infections (SARI) to ICU and how this varies between influenza epidemics.

Objective: Intensive Care Unit (ICU) data are registered for quality monitoring in the Netherlands with near 100% coverage. They are a big data type source that may be useful for infectious disease surveillance. We explored their potential to enhance the surveillance of influenza which is currently based on the milder end of the disease spectrum. We ultimately aim to set up a real-surveillance system of severe acute respiratory infections.

Submitted by elamb on

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.

Referenced File
Submitted by hparton on

The mortality monitoring system (initiated in 2009 during the influenza A(H1N1) pandemic) is a collaboration between the Centre for Infectious Disease Control (CIb) of National Institute for Public Health and the Environment (RIVM) and Statistics Netherlands. The system monitors nation-wide reported number of deaths (population size 2017: 17 million) from all causes, as cause of death information is not available real-time. Data is received from Statistics Netherlands by weekly emails.

Objective:

Weekly numbers of deaths are monitored to increase the capacity to deal with both expected and unusual (disease) events such as pandemic influenza, other infections and non-infectious incidents. The monitoring information can potentially be used to detect, track and estimate the impact of an outbreak or incident on all-cause mortality.

Submitted by elamb on
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