A flow-chart of the statistical analysis.

<p>A flow-chart of the statistical analysis.</p

R2 values and mean predictive errors using leave-one-out cross validation for all generated models for the sentinel and the laboratory models respectively.

<p>The values for the chosen models (using 4 components) are marked in bold.</p

The relative contribution of the scaled and centred queries to each component in the model predicting sentinel values.

<p>The relative contribution of the scaled and centred queries to each component in the model predicting sentinel values.</p

Observed values (black), predicted values from the full models (red, with circles), and predicted values using a model fitted on data from the opposite season (blue, with squares) for the model predicting sentinel values and for the model predicting laboratory values.

<p>Observed values (black), predicted values from the full models (red, with circles), and predicted values using a model fitted on data from the opposite season (blue, with squares) for the model predicting sentinel values and for the model predicting laboratory values.</p

Summary of investigated queries, with genuine examples in Swedish (one complete query per line) in addition to their English translations.

<p>The table also shows the total number of queries for the two seasons, as well as the percentage of queries matching the query type.</p

The relative contribution of the scaled and centred queries to each component in the model predicting laboratory values.

<p>The relative contribution of the scaled and centred queries to each component in the model predicting laboratory values.</p

The number of queries matching the selected query types plotted over time.

<p>The number of queries matching the selected query types plotted over time.</p

An overview of the sentinel and the laboratory data for the two investigated influenza seasons (2005/2006 and 2006/2007).

<p>An overview of the sentinel and the laboratory data for the two investigated influenza seasons (2005/2006 and 2006/2007).</p

Evaluation of an Internet-Based Monitoring System for Influenza-Like Illness in Sweden

<div><p>To complement traditional influenza surveillance with data on disease occurrence not only among care-seeking individuals, the Swedish Institute for Communicable Disease Control (SMI) has tested an Internet-based monitoring system (IMS) with self-recruited volunteers submitting weekly on-line reports about their health in the preceding week, upon weekly reminders. We evaluated IMS acceptability and to which extent participants represented the Swedish population. We also studied the agreement of data on influenza-like illness (ILI) occurrence from IMS with data from a previously evaluated population-based system (PBS) with an actively recruited random sample of the population who spontaneously report disease onsets in real-time via telephone/Internet, and with traditional general practitioner based sentinel and virological influenza surveillance, in the 2011–2012 and 2012–2013 influenza seasons. We assessed acceptability by calculating the participation proportion in an invited IMS-sample and the weekly reporting proportion of enrolled self-recruited IMS participants. We compared distributions of socio-demographic indicators of self-recruited IMS participants to the general Swedish population using chi-square tests. Finally, we assessed the agreement of weekly incidence proportions (%) of ILI in IMS and PBS with cross-correlation analyses. Among 2,511 invited persons, 166 (6.6%) agreed to participate in the IMS. In each season, 2,552 and 2,486 self-recruited persons participated in the IMS respectively. The weekly reporting proportion among self-recruited participants decreased from 87% to 23% (2011–2012) and 82% to 45% (2012–2013). Women, highly educated, and middle-aged persons were overrepresented among self-recruited IMS participants (p<0.01). IMS (invited and self-recruited) and PBS weekly incidence proportions correlated strongest when no lags were applied (r = 0.71 and r = 0.69, p<0.05). This evaluation revealed socio-demographic misrepresentation and limited compliance among the self-recruited IMS participants. Yet, IMS offered a reasonable representation of the temporal ILI pattern in the community overall during the 2011–2012 and 2012–2013 influenza seasons and could be a simple tool for collecting community-based ILI data.</p></div

Distribution of socio-demographic characteristics among self-recruited and invited IMS participants during the 2011–2012 and 2012–2013 influenza seasons and the corresponding distribution of the general Swedish population 2011 and 2012.

<p>*Chi square goodness of fit test participants vs. Swedish population.</p><p>**Participants who contributed with at least one <i>active</i> report. For definition of active reports, see Methods section.</p><p>***Among participants 16–95+ year old.</p><p>****Including children in age group 0–15 yrs.</p