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

Abstract

Background: Telehealth systems have a large potential for informing public health authorities in an early stage of outbreaks of communicable disease. Influenza and norovirus are common viruses that cause significant respiratory and gastrointestinal disease worldwide. Data about these viruses are not routinely mapped for surveillance purposes in the UK, so the spatial diffusion of national outbreaks and epidemics is not known as such incidents occur. We aim to describe the geographical origin and diffusion of rises in fever and vomiting calls to a national telehealth system, and consider the usefulness of these findings for influenza and norovirus surveillance.

Methods: Data about fever calls (5- to 14-year-old age group) and vomiting calls (> or = 5-year-old age group) in school-age children, proxies for influenza and norovirus, respectively, were extracted from the NHS Direct national telehealth database for the period June 2005 to May 2006. The SaTScan space-time permutation model was used to retrospectively detect statistically significant clusters of calls on a week-by-week basis. These syndromic results were validated against existing laboratory and clinical surveillance data.

Results: We identified two distinct periods of elevated fever calls. The first originated in the North-West of England during November 2005 and spread in a south-east direction, the second began in Central England during January 2006 and moved southwards. The timing, geographical location, and age structure of these rises in fever calls were similar to a national influenza B outbreak that occurred during winter 2005-2006. We also identified significantly elevated levels of vomiting calls in South-East England during winter 2005-2006.

Conclusion: Spatiotemporal analyses of telehealth data, specifically fever calls, provided a timely and unique description of the evolution of a national influenza outbreak. In a similar way the tool may be useful for tracking norovirus, although the lack of consistent comparison data makes this more difficult to assess. In interpreting these results, care must be taken to consider other infectious and non-infectious causes of fever and vomiting. The scan statistic should be considered for spatial analyses of telehealth data elsewhere and will be used to initiate prospective geographical surveillance of influenza in England.

Figure 1

Annual total call rate per 1000 population. Annual total call rate per 1000 population per year (June 2005 to May 2006) mapped by Primary Care Trust.

Figure 2

Areas of significantly high or low annual total call rates. Areas of significantly high or low annual total call rates (June 2005 to May 2006) displayed as relative risks and mapped by Primary Care Trust.

Figure 3

Areas with significantly high numbers of fever calls. Areas with significantly high numbers of fever calls (clusters) displayed as observed/expected ratios by week and location of the first reported influenza B outbreaks. There were no significant clusters prior to week 47 in 2005 and after week 14 in 2006 during our test period.

Figure 4

Areas with significantly high numbers of vomiting calls. Areas with significantly high numbers of vomiting calls (clusters) displayed as observed/expected ratios by week. There were no significant clusters prior to week 40 in 2005 and after week 12 in 2006 during our test period.

Figure 5

Weekly GP influenza-like-illness consultation rates. Weekly GP influenza-like-illness consultation rates for the 5- to 14-year-old age group for Northern, Central and Southern England; weekly numbers (all ages combined) of positive influenza samples (influenza A and B separately) from community sources; and NHS Direct fever calls as a percentage of total calls (5 to 14 years) for England and Wales.