We compared the accuracy of online data obtained from the Flutracking surveillance system during pandemic (H1N1) 2009 in Australia with data from other influenza surveillance systems. Flutracking accurately identified peak influenza activity timing and community influenza-like illness activity and was significantly less biased by treatment-seeking behavior and laboratory testing protocols than other systems.
A variety of surveillance methods were used to monitor the incidence and severity of influenza A pandemic (H1N1) 2009 in Australia. Severity of illness was measured by number of hospitalizations, intensive care unit (ICU) admissions, and deaths. Influenza disease incidence was monitored through laboratory-confirmed cases, general practitioner sentinel surveillance of influenza-like illness (ILI), emergency department visits for ILI, absenteeism data from large employers, and the Flutracking surveillance system (
Flutracking is a national weekly online survey of ILI (completed by >8,000 participating community members each week in 2009); it is the only ILI surveillance system that provides comparable data across Australia’s states and territories. Flutracking integrates participants’ ILI symptom information with their influenza vaccination status (
From May 4, 2009, through October 31, 2010, participants received an automatically generated weekly email link to the online questionnaire, which asked whether they had experienced fever or cough and how many days they had been absent from work or normal duties because of these signs (recruitment details in
The weekly proportion of participants with ILI signs or symptoms was calculated as the proportion of participants for that week who reported both fever and cough within the previous 7 days. These proportions were compared with influenza activity recorded in 2009 by other established New South Wales influenza surveillance systems, i.e., number of patients who visited emergency departments with ILI symptoms (
Surveillance data were compared with data from 2007 and 2008. NSW was selected because no other states had sufficient Flutracking participants in 2007 and 2008 to allow year-to-year comparisons. The number of NSW participants who completed
The concordance across NSW influenza surveillance systems was high for ILI peak weeks during the past 3 years. During 2009, Flutracking, laboratory influenza notifications, and Google Flu Trends peaked 1 week before emergency department ILI, workplace absenteeism, and ASPREN ILI surveillance (
| Surveillance system/weekly measure used | Peak week of ILI (week ending) | Peak ILI/influenza-related values | |||||
|---|---|---|---|---|---|---|---|
| 2007 | 2008 | 2009 | 2007 | 2008 | 2009 | ||
| Flutracking, fever and cough rate, % | Aug 5 | Aug 24 | Jul 12 | 9.4 | 5.8 | 6.8 | |
| No. laboratory notifications | Aug 5 | Aug 31 | Jul 12 | 133 | 69 | 1,167 | |
| No. ED ILI visits | Aug 19 | Aug 31 | Jul19 | 374 | 170 | 1,024 | |
| Google Flu Trends | |||||||
| Influenza-related search term counts | Jul 22 | Aug 31 | Jul 12 | 1,933 | 1075 | 1,022 | |
| Workplace absenteeism, weekly rate, % | Jul 15 | ND | Jul 19 | 1.5 | ND | 1.4 | |
| ASPREN, ILI/1,000 consultations, % | Aug 12 | Sep 7 | Jul 19 | 73.7 | 62.8 | 74.3 | |
*ILI, influenza-like illness; ED, emergency department; ND, no data collected; ASPREN, Australian Sentinel Practice Research Network.
A comparison of the weekly scale of NSW Flutracking fever and cough symptom rates during 2007, 2008, and 2009 showed that the peak attack rate of 6.8% in 2009 was significantly lower than that of 9.4% in 2007 and only slightly higher than the peak rate of 5.8% in 2008 (
Flutracking fever and cough rates, counts of emergency department visits for influenza, and number of laboratory notifications for influenza, New South Wales, Australia, 2007–2009. PHREDSS, Public Health Real Time Emergency Department Surveillance System
The attack rate pattern for NSW Google Flu Trends data was similar to that of Flutracking; attack rates for 2009 were slightly lower than those for 2008 and about half those of for 2007. ASPREN ILI rates were slightly higher in 2009 than in 2007 and 2008. Workplace absenteeism data demonstrated a slightly more severe influenza season in 2007 than in 2009 (
When the surveillance systems were compared, laboratory notifications and emergency department surveillance appeared to be more affected by health-seeking behavior and changes in physician’s testing protocols and may not have reflected true community ILI rates, in contrast to Flutracking, Google Flu Trends, workplace absenteeism, and ASPREN. Potential biases in laboratory notifications and emergency department surveillance may vary, depending on the pandemic phase. For example, during the protect phase of the pandemic, testing for influenza was recommended only for those admitted to the hospital for ILI or when test results could alter clinical care of a patient. Before the protect phase (during the contain phase), testing for pandemic (H1N1) 2009 virus was conducted to confirm diagnosis for anyone with ILI.
Flutracking’s finding of a 2009 peak ILI rate similar to those of previous years was also consistent with NSW mortality data. The number of NSW deaths attributed to influenza or pneumonia suggested that the 2009 influenza season did not result in excess overall deaths but rather a redistribution of deaths with a relative increase of deaths in younger age groups (
Because Flutracking does not rely on the health sector for ILI or laboratory reporting, it is not biased by changes in testing, treatment seeking, jurisdictional protocols, or resource constraints. Flutracking, Gripenet, and other similar Internet-based surveillance could potentially facilitate near real-time comparison of ILI activity between regional jurisdictions and among countries to assist with monitoring the global spread of influenza (
During the initial pandemic (H1N1) 2009 outbreak, Flutracking demonstrated its ability to accurately identify peak influenza activity timing and the relative magnitude of community influenza activity when compared with influenza tracking efforts in previous years. Its results were also less affected by treatment-seeking behavior and by laboratory testing protocols during different pandemic phases than was health system–based surveillance.
We thank the thousands of Flutracking participants who give their time freely each week to contribute to influenza surveillance. We are also grateful to the University of Newcastle for their continued support and to the Australian Government Department of Health and Ageing and the Hunter Medical Research Institute for their funding and support.
Ms Carlson is a statistician for the Flutracking surveillance system at Hunter New England Population Health, Newcastle. Her primary research interest is influenza surveillance.