In the last decade, worldwide several major infectious disease events occurred — like the anthrax attacks in the
USA in 2001, the SARS epidemic in 2003 and the 2009 influenza pandemic. As a result, public-health authorities
worldwide have acknowledged the need for improved surveillance for emerging infectious diseases, as early
detection and control may well mitigate the impact of emerging outbreaks. For instance, the SARS epidemic
could have caused a major pandemic with millions of deaths if it had not been contained by public health
measures. Still, the SARS epidemic was only recognized several months after its emergence, and in the end it
infected 8096 patients in 27 countries and caused 774 deaths before it could be controlled. SARS, and most
other pathogens that are considered a high threat for public health, cause symptoms that are common in clinical
practice, like pneumonia (e.g. B. anthracis, SARS or pandemic influenza), gastro-enteritis (e.g. Vibrio cholerae)
or neurological disease (e.g. West Nile virus). That is why traditional outbreak detection based on astute
clinicians and laboratory diagnoses can have blind spots for such emerging diseases, because patients reporting
with such common symptoms might not alarm clinicians — especially since individual clinicians may only see
one or a few of these “new” cases — and uncommon pathogens can remain undetected by the laboratory.
To reveal such blind spots, many countries have implemented so called syndromic surveillance systems that
aim to capture infectious disease events earlier and more completely than traditional surveillance; they do this by
monitoring new health indicators, such as basic symptom information or clinical diagnoses, rather than positive
laboratory results for specific pathogens. Surveillance of symptom based data has been used since decades
for surveillance of polio (acute flaccid paralysis) and influenza (influenza-like illness), but the increasing
availability of electronic health-care data with information on specific morbidity in time, has made large-scale
real-time monitoring of syndromes possible. Syndromic surveillance was initially developed for early-warning
detection of bioterrorism attacks, but is also used for early detection of naturally occurring (local) outbreaks,
following the size and spread of ongoing outbreaks, monitoring disease trends in the general population, and
providing reassurance that an outbreak has not occurred. At the same time, in light of limited resources for
public health, there has been an ongoing debate about the actual added value of syndromic surveillance, with
particular concerns about its specificity.
Because little validation had been done to address these concerns, we chose to evaluate the potential
value of syndromic surveillance for infectious disease surveillance and control, before starting any implementation.
This thesis is the result of that evaluation project.
http://repub.eur.nl/res/pub/22640/7898_omslag_wijngaard_lr_voor%20mail.pdf
http://repub.eur.nl/res/pub/22640/7898_omslag_wijngaard_lr_voor%20mail.pdf
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