Impact of implementation strategy on catch-up vaccine uptake among girls born 1993–98 and stratified by two age-groups, Sweden 2012–2014.

<p>Impact of implementation strategy on catch-up vaccine uptake among girls born 1993–98 and stratified by two age-groups, Sweden 2012–2014.</p

Description of information channels and vaccination settings used among counties to implement catch-up vaccination of girls born 1993–1998, Sweden 2012–2014.

<p>Description of information channels and vaccination settings used among counties to implement catch-up vaccination of girls born 1993–1998, Sweden 2012–2014.</p

Catch-up vaccine uptake.

<p>Percentage of girls born 1993–1998 that had received at least one dose of HPV vaccine on 30 September 2014, presented by county.</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

Summary of system components of the IMS and PBS during the influenza seasons 2011–2012 and 2012–2013.

<p>Summary of system components of the IMS and PBS during the influenza seasons 2011–2012 and 2012–2013.</p

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

Bland-Altman plots 2011–2012 and 2012–2013.

<p>The upper graph shows a Bland-Altman plot of data from the 2011–2012 season and the lower graph shows a Bland-Altman plot of data from the 2012–2013 season. The black dots represents the differences of the weekly incidence proportions between the IMS and PBS (y) by the average of the IMS and PBS weekly incidence proportions (x). The thick blue line represents a simple linear regression model of the differences on the averages, while the thin blue lines represent the respective 95% limits of agreement. The limits of agreement for the difference between the IMS and PBS can be calculated from the equation in the bottom of the graphs, when their average is known. With the equations at the top of the graphs one system’s incidence proportions can be transformed to the other.</p

The Validity of Self-Initiated, Event-Driven Infectious Disease Reporting in General Population Cohorts

<div><p>Background</p><p>The 2009/2010 pandemic influenza highlighted the need for valid and timely incidence data. In 2007 we started the development of a passive surveillance scheme based on passive follow-up of representative general population cohorts. Cohort members are asked to spontaneously report all instances of colds and fevers as soon as they occur for up to 9 months. Suspecting that compliance might be poor, we aimed to assess the validity of self-initiated, event-driven outcome reporting over long periods.</p><p>Methods</p><p>During two 8 week periods in 2008 and 2009, 2376 and 2514 cohort members in Stockholm County were sent one-week recall questionnaires, which served as reference method.</p><p>Results</p><p>The questionnaires were completed by 88% and 86% of the cohort members. Whilst the false positive proportion (1–specificity) in the reporting was low (upper bound of the 95% confidence interval [CI] ≤2% in each season), the false negative proportion (failure to report, 1–sensitivity) was considerable (60% [95% CI 52%–67%] in each season). Still, the resulting epidemic curves for influenza-like illness compared well with those from existing General Practitioner-based sentinel surveillance in terms of shape, timing of peak, and year-to-year variation. This suggested that the error was fairly constant.</p><p>Conclusions</p><p>Passive long-term surveillance through self-initiated, event-driven outcome reporting underestimates incidence rates of common upper respiratory tract infections. However, because underreporting appears predictable, simple corrections could potentially restore validity.</p></div

The population-based surveillance system and validation study during the influenza season 2007/2008.

<p>Following an invitation to a randomly selected population sample at ages 0–95 years around October 1^st 2007, registered cohort members were followed passively, relying on self-initiated, event-driven reporting of all colds and fevers, until May 30^th 2008. Reminders were sent out at Christmas and Easter, and an end-of-follow-up questionnaire around May 30^th. The validation study consisted of 2–3 randomly selected validation weeks per participant between January 14 and March 9 2008, with 1-week recall questionnaires. *Participation rate 2082/2376 (88%); another 43 were excluded due to uninterpretable reports or interference in the last week by the Easter reminder. The Easter reminder arrived when it was still possible to submit a legitimate event-driven report.</p

Observed false negative proportion, false positive proportion and predictive values in the 2008 and 2009 validation divided by age group and overall.

<p>Observed false negative proportion, false positive proportion and predictive values in the 2008 and 2009 validation divided by age group and overall.</p