Literature DB >> 18032426

Can syndromic thresholds provide early warning of national influenza outbreaks?

D L Cooper1, N Q Verlander, A J Elliot, C A Joseph, G E Smith.   

Abstract

BACKGROUND: Influenza incidence thresholds are used to help predict the likely impact of influenza and inform health professionals and the public of current activity. We evaluate the potential of syndromic data (calls to a UK health helpline NHS Direct) to provide early warning of national influenza outbreaks.
METHODS: Time series of NHS Direct calls concerning 'cold/flu' and fever syndromes for England and Wales were compared against influenza-like-illness clinical incidence data and laboratory reports of influenza. Poisson regression models were used to derive NHS Direct thresholds. The early warning potential of thresholds was evaluated retrospectively for 2002-06 and prospectively for winter 2006-07.
RESULTS: NHS Direct 'cold/flu' and fever calls generally rose and peaked at the same time as clinical and laboratory influenza data. We derived a national 'cold/flu' threshold of 1.2% of total calls and a fever (5-14 years) threshold of 9%. An initial lower fever threshold of 7.7% was discarded as it produced false alarms. Thresholds provided 2 weeks advanced warning of seasonal influenza activity during three of the four winters studied retrospectively, and 6 days advance warning during prospective evaluation.
CONCLUSION: Syndromic thresholds based on NHS Direct data provide advance warning of influenza circulating in the community. We recommend that age-group specific thresholds be developed for other clinical influenza surveillance systems in the UK and elsewhere.

Entities:  

Mesh:

Year:  2007        PMID: 18032426     DOI: 10.1093/pubmed/fdm068

Source DB:  PubMed          Journal:  J Public Health (Oxf)        ISSN: 1741-3842            Impact factor:   2.341


  26 in total

1.  [Syndromic surveillance of Influenza-like illness in primary care: a complement to the sentinel surveillance network for periods of increased incidence of Influenza].

Authors:  J Arranz Izquierdo; A Leiva Rus; E Carandell Jäger; A Pujol Buades; M C Méndez Castell; A Salvà Fiol; M Esteva Cantó
Journal:  Aten Primaria       Date:  2011-09-15       Impact factor: 1.137

2.  Developing and validating a new national remote health advice syndromic surveillance system in England.

Authors:  S E Harcourt; R A Morbey; P Loveridge; L Carrilho; D Baynham; E Povey; P Fox; J Rutter; P Moores; J Tiffen; S Bellerby; P McIntosh; S Large; J McMenamin; A Reynolds; S Ibbotson; G E Smith; A J Elliot
Journal:  J Public Health (Oxf)       Date:  2017-03-01       Impact factor: 2.341

3.  Enhanced Influenza Surveillance Using Telephone Triage and Electronic Syndromic Surveillance in the Department of Veterans Affairs, 2011-2015.

Authors:  Cynthia Lucero-Obusan; Carla A Winston; Patricia L Schirmer; Gina Oda; Mark Holodniy
Journal:  Public Health Rep       Date:  2017 Jul/Aug       Impact factor: 2.792

4.  Establishing a web-based integrated surveillance system for early detection of infectious disease epidemic in rural China: a field experimental study.

Authors:  Wei-rong Yan; Shao-fa Nie; Biao Xu; Heng-jin Dong; Lars Palm; Vinod K Diwan
Journal:  BMC Med Inform Decis Mak       Date:  2012-02-03       Impact factor: 2.796

5.  ISS--an electronic syndromic surveillance system for infectious disease in rural China.

Authors:  Weirong Yan; Lars Palm; Xin Lu; Shaofa Nie; Biao Xu; Qi Zhao; Tao Tao; Liwei Cheng; Li Tan; Hengjin Dong; Vinod K Diwan
Journal:  PLoS One       Date:  2013-04-23       Impact factor: 3.240

6.  Internet-based remote health self-checker symptom data as an adjuvant to a national syndromic surveillance system.

Authors:  A J Elliot; E O Kara; P Loveridge; Z Bawa; R A Morbey; M Moth; S Large; G E Smith
Journal:  Epidemiol Infect       Date:  2015-04-10       Impact factor: 4.434

7.  The burden of seasonal respiratory infections on a national telehealth service in England.

Authors:  R A Morbey; S Harcourt; R Pebody; M Zambon; J Hutchison; J Rutter; H Thomas; G E Smith; A J Elliot
Journal:  Epidemiol Infect       Date:  2017-04-17       Impact factor: 4.434

8.  Monitoring the emergence of community transmission of influenza A/H1N1 2009 in England: a cross sectional opportunistic survey of self sampled telephone callers to NHS Direct.

Authors:  Alex J Elliot; Cassandra Powers; Alicia Thornton; Chinelo Obi; Caterina Hill; Ian Simms; Pauline Waight; Helen Maguire; David Foord; Enid Povey; Tim Wreghitt; Nichola Goddard; Joanna Ellis; Alison Bermingham; Praveen Sebastianpillai; Angie Lackenby; Maria Zambon; David Brown; Gillian E Smith; O Noel Gill
Journal:  BMJ       Date:  2009-08-27

9.  The use of syndromic surveillance for decision-making during the H1N1 pandemic: a qualitative study.

Authors:  Anna Chu; Rachel Savage; Don Willison; Natasha S Crowcroft; Laura C Rosella; Doug Sider; Jason Garay; Ian Gemmill; Anne-Luise Winter; Richard F Davies; Ian Johnson
Journal:  BMC Public Health       Date:  2012-10-30       Impact factor: 3.295

10.  What is the utility of using syndromic surveillance systems during large subnational infectious gastrointestinal disease outbreaks? An observational study using case studies from the past 5 years in England.

Authors:  D Todkill; A J Elliot; R Morbey; J Harris; J Hawker; O Edeghere; G E Smith
Journal:  Epidemiol Infect       Date:  2016-04-01       Impact factor: 4.434

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.