scholarly journals Syndromic Surveillance System for MERS-CoV as New Early Warning and Identification Approach [Corrigendum]

2020 ◽  
Vol Volume 13 ◽  
pp. 163-164
Author(s):  
Maryam Salamatbakhsh ◽  
Kazhal Mobaraki ◽  
Jamal Ahmadzadeh
Keyword(s):  
Early Warning ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Syndromic Surveillance System ◽  
Identification Approach

scholarly journals Early warning epidemic surveillance in the Pacific island nations: an evaluation of the Pacific syndromic surveillance system

2016 ◽  
Vol 21 (7) ◽  
pp. 917-927 ◽  
Author(s):  
Adam T. Craig ◽  
Mike Kama ◽  
Marcus Samo ◽  
Saine Vaai ◽  
Jane Matanaicake ◽  
...  
Keyword(s):  
Early Warning ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Pacific Island ◽  
Syndromic Surveillance System ◽  
The Pacific ◽  
Pacific Island Nations

scholarly journals Can syndromic surveillance data detect local outbreaks of communicable disease? A model using a historical cryptosporidiosis outbreak

2005 ◽  
Vol 134 (1) ◽  
pp. 13-20 ◽  
Author(s):  
D. L. COOPER ◽  
N. Q. VERLANDER ◽  
G. E. SMITH ◽  
A. CHARLETT ◽  
E. GERARD ◽  
...  
Keyword(s):  
Early Warning ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Communicable Disease ◽  
Terrorist Attack ◽  
Syndromic Surveillance System ◽  
The Public ◽  
Health Team ◽  
Nhs Direct ◽  
Common Infection

SUMMARYA national UK surveillance system currently uses data from a health helpline (NHS Direct) in an attempt to provide early warning of a bio-terrorist attack, or an outbreak caused by a more common infection. To test this syndromic surveillance system we superimposed data from a historical outbreak of cryptosporidiosis onto a statistical model of NHS Direct call data. We modelled whether calls about diarrhoea (a proxy for cryptosporidiosis) exceeded a statistical threshold, thus alerting the surveillance team to the outbreak. On the date that the public health team were first notified of the outbreak our model predicted a 4% chance of detection when we assumed that one-twentieth of cryptosporidiosis cases telephoned the helpline. This rose to a 72% chance when we assumed nine-tenths of cases telephoned. The NHS Direct surveillance system is currently unlikely to detect an event similar to the cryptosporidiosis outbreak used here and may be most suited to detecting more widespread rises in syndromes in the community, as previously demonstrated. However, the expected rise in NHS Direct call rates, should improve early warning of outbreaks using call data.

scholarly journals A national syndromic surveillance system for England and Wales using calls to a telephone helpline

2006 ◽  
Vol 11 (12) ◽  
pp. 9-10 ◽  
Author(s):  
G E Smith ◽  
D L Cooper ◽  
P Loveridge ◽  
F Chinemana ◽  
E Gerard ◽  
...  
Keyword(s):  
Early Warning ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Influenza Pandemic ◽  
Daily Basis ◽  
Health Protection ◽  
Chemical Agent ◽  
Syndromic Surveillance System ◽  
England And Wales ◽  
Nhs Direct

Routine primary care data provide the means to monitor a variety of syndromes which could give early warning of health protection issues. In the United Kingdom, a national syndromic surveillance system, operated jointly by the UK Health Protection Agency (HPA) and NHS Direct (a national telephone health helpline), examines symptoms reported to NHS Direct. The aim of the system is to identify an increase in syndromes indicative of common infections and diseases, or the early stages of illness caused by the deliberate release of a biological or chemical agent. Data relating to 11 key symptoms/syndromes are received electronically from all 22 NHS Direct call centres covering England and Wales and analysed by the HPA on a daily basis. Statistically significant excesses in calls are automatically highlighted and assessed by a multi-disciplinary team. Although the surveillance system has characterised many sudden rises in syndromes reported to NHS Direct, no evidence of a biological or chemical attack has been detected. Benefits of this work, however, are early warning and tracking of rises in community morbidity (e.g. influenza-like illness, heatstroke); providing reassurance during times of perceived high risk (e.g. after the 7 July 2005 London bombs and December 2005 Buncefield oil depot fire); and timely surveillance data for influenza pandemic planning and epidemic modeling.

Algorithm for Statistical Detection of Peaks - Syndromic Surveillance System for the Athens 2004 Olympic Games

2004 ◽  
Author(s):  
Urania G. Dafni ◽  
S. Tsiodras ◽  
D. Panagiotakos ◽  
K. Gkolfinopoulou ◽  
G. Kouvatscas ◽  
...  
Keyword(s):  
Surveillance System ◽  
Syndromic Surveillance ◽  
Olympic Games ◽  
Syndromic Surveillance System ◽  
Statistical Detection
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