Tracking the spatial diffusion of influenza and norovirus using telehealth data: A spatiotemporal analysis of syndromic data
2008

Tracking the Spread of Influenza and Norovirus Using Telehealth Data

Sample size: 4728939 publication Evidence: moderate

Author Information

Author(s): Cooper Duncan L, Smith Gillian E, Regan Martyn, Large Shirley, Groenewegen Peter P

Primary Institution: Bradford and Airedale tPCT, West Yorkshire, UK

Hypothesis

Can telehealth data effectively track the geographical spread of influenza and norovirus outbreaks?

Conclusion

Telehealth data can provide timely insights into the spread of influenza outbreaks, although tracking norovirus is more challenging due to inconsistent data.

Supporting Evidence

  • Two distinct periods of elevated fever calls were identified during the study.
  • The first rise in fever calls originated in North-West England and spread south-east.
  • The second rise began in Central England and moved southwards.
  • Significantly elevated levels of vomiting calls were identified in South-East England during winter 2005–2006.
  • Telehealth data provided a unique description of the evolution of a national influenza outbreak.

Takeaway

This study looked at calls to a health hotline to see how well they could show where flu and stomach virus outbreaks were happening. They found it worked well for flu but not as much for the stomach virus.

Methodology

Data from NHS Direct calls about fever and vomiting were analyzed using the SaTScan space-time permutation model to identify significant clusters of calls.

Potential Biases

The data may not represent the entire population's health issues, as certain demographics are more likely to use telehealth services.

Limitations

The study's findings on norovirus were limited by inconsistent outbreak data and the exclusion of calls from younger children.

Participant Demographics

Calls were primarily from school-age children for fever and from individuals aged 5 and older for vomiting.

Statistical Information

P-Value

p ≤ 0.05

Statistical Significance

p ≤ 0.05

Digital Object Identifier (DOI)

10.1186/1741-7015-6-16

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