Dataset Information

Estimating the Population Impact of a New Pediatric Influenza Vaccination Program in England Using Social Media Content.

ABSTRACT: BACKGROUND:The rollout of a new childhood live attenuated influenza vaccine program was launched in England in 2013, which consisted of a national campaign for all 2 and 3 year olds and several pilot locations offering the vaccine to primary school-age children (4-11 years of age) during the influenza season. The 2014/2015 influenza season saw the national program extended to include additional pilot regions, some of which offered the vaccine to secondary school children (11-13 years of age) as well. OBJECTIVE:We utilized social media content to obtain a complementary assessment of the population impact of the programs that were launched in England during the 2013/2014 and 2014/2015 flu seasons. The overall community-wide impact on transmission in pilot areas was estimated for the different age groups that were targeted for vaccination. METHODS:A previously developed statistical framework was applied, which consisted of a nonlinear regression model that was trained to infer influenza-like illness (ILI) rates from Twitter posts originating in pilot (school-age vaccinated) and control (unvaccinated) areas. The control areas were then used to estimate ILI rates in pilot areas, had the intervention not taken place. These predictions were compared with their corresponding Twitter-based ILI estimates. RESULTS:Results suggest a reduction in ILI rates of 14% (1-25%) and 17% (2-30%) across all ages in only the primary school-age vaccine pilot areas during the 2013/2014 and 2014/2015 influenza seasons, respectively. No significant impact was observed in areas where two age cohorts of secondary school children were vaccinated. CONCLUSIONS:These findings corroborate independent assessments from traditional surveillance data, thereby supporting the ongoing rollout of the program to primary school-age children and providing evidence of the value of social media content as an additional syndromic surveillance tool.

SUBMITTER: Wagner M

PROVIDER: S-EPMC6257312 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Estimating the Population Impact of a New Pediatric Influenza Vaccination Program in England Using Social Media Content.

Wagner Moritz M Lampos Vasileios V Yom-Tov Elad E Pebody Richard R Cox Ingemar J IJ

Journal of medical Internet research 20171221 12

<h4>Background</h4>The rollout of a new childhood live attenuated influenza vaccine program was launched in England in 2013, which consisted of a national campaign for all 2 and 3 year olds and several pilot locations offering the vaccine to primary school-age children (4-11 years of age) during the influenza season. The 2014/2015 influenza season saw the national program extended to include additional pilot regions, some of which offered the vaccine to secondary school children (11-13 years of ...[more]

PMID: 29269339

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Project description:BackgroundSocial media is often used for health communication and can facilitate fast information exchange. Despite its increasing use, little is known about child health information sharing and engagement over social media.ObjectiveThe primary objectives of this study are to systematically describe the content of social media posts about child pain and sleep and identify the level of research evidence in these posts. The secondary objective is to examine user engagement with information shared over social media.MethodsTwitter, Instagram, and Facebook were searched by members of the research team over a 2-week period using a comprehensive search strategy. Codes were used to categorize the content of posts to identify the frequency of content categories shared over social media platforms. Posts were evaluated by content experts to determine the frequency of posts consistent with existing research evidence. User engagement was analyzed using Netlytic, a social network analysis program, to examine visual networks illustrating the level of user engagement.ResultsFrom the 2-week period, nearly 1500 pain-related and 3800 sleep-related posts were identified and analyzed. Twitter was used most often to share knowledge about child pain (639/1133, 56.40% of posts), and personal experiences for child sleep (2255/3008, 75.00% of posts). For both topics, Instagram posts shared personal experiences (53/68, 78% pain; 413/478, 86.4% sleep), Facebook group posts shared personal experiences (30/49, 61% pain; 230/345, 66.7% sleep) and Facebook pages shared knowledge (68/198, 34.3% pain; 452/1026, 44.05% sleep). Across platforms, research evidence was shared in 21.96% (318/1448) of pain- and 9.16% (445/4857) of sleep-related posts; 5.38% (61/1133) of all pain posts and 2.82% (85/3008) of all sleep posts shared information inconsistent with the evidence, while the rest were absent of evidence. User interactions were indirect, with mostly one-way, rather than reciprocal conversations.ConclusionsSocial media is commonly used to discuss child health, yet the majority of posts do not contain research evidence, and user engagement is primarily one-way. These findings represent an opportunity to expand engagement through open conversations with credible sources. Research and health care communities can benefit from incorporating specific information about evidence within social media posts to improve communication with the public and empower users to distinguish evidence-based content better. Together, these findings have identified potential gaps in social media communication that may be informative targets to guide future strategies for improving the translation of child health evidence over social media.

Project description:BACKGROUND:Measures of the contribution of influenza to Streptococcus pneumoniae infections, both in the seasonal and pandemic setting, are needed to predict the burden of secondary bacterial infections in future pandemics to inform stockpiling. The magnitude of the interaction between these two pathogens has been difficult to quantify because both infections are mainly clinically diagnosed based on signs and symptoms; a combined viral-bacterial testing is rarely performed in routine clinical practice; and surveillance data suffer from confounding problems common to all ecological studies. We proposed a novel multivariate model for age-stratified disease incidence, incorporating contact patterns and estimating disease transmission within and across groups. METHODS AND FINDINGS:We used surveillance data from England over the years 2009 to 2017. Influenza infections were identified through the virological testing of samples taken from patients diagnosed with influenza-like illness (ILI) within the sentinel scheme run by the Royal College of General Practitioners (RCGP). Invasive pneumococcal disease (IPD) cases were routinely reported to Public Health England (PHE) by all the microbiology laboratories included in the national surveillance system. IPD counts at week t, conditional on the previous time point t-1, were assumed to be negative binomially distributed. Influenza counts were linearly included in the model for the mean IPD counts along with an endemic component describing some seasonal background and an autoregressive component mimicking pneumococcal transmission. Using age-specific counts, Akaike information criterion (AIC)-based model selection suggested that the best fit was obtained when the endemic component was expressed as a function of observed temperature and rainfall. Pneumococcal transmission within the same age group was estimated to explain 33.0% (confidence interval [CI] 24.9%-39.9%) of new cases in the elderly, whereas 50.7% (CI 38.8%-63.2%) of incidence in adults aged 15-44 years was attributed to transmission from another age group. The contribution of influenza on IPD during the 2009 pandemic also appeared to vary greatly across subgroups, being highest in school-age children and adults (18.3%, CI 9.4%-28.2%, and 6.07%, CI 2.83%-9.76%, respectively). Other viral infections, such as respiratory syncytial virus (RSV) and rhinovirus, also seemed to have an impact on IPD: RSV contributed 1.87% (CI 0.89%-3.08%) to pneumococcal infections in the 65+ group, whereas 2.14% (CI 0.87%-3.57%) of cases in the group of 45- to 64-year-olds were attributed to rhinovirus. The validity of this modelling strategy relies on the assumption that viral surveillance adequately represents the true incidence of influenza in the population, whereas the small numbers of IPD cases observed in the younger age groups led to significant uncertainty around some parameter estimates. CONCLUSIONS:Our estimates suggested that a pandemic wave of influenza A/H1N1 with comparable severity to the 2009 pandemic could have a modest impact on school-age children and adults in terms of IPD and a small to negligible impact on infants and the elderly. The seasonal impact of other viruses such as RSV and rhinovirus was instead more important in the older population groups.

Project description:Web-based approaches, specifically social media sites, represent a promising approach for recruiting young gay and bisexual men for research studies. Little is known, however, about how the performance of social media advertisements (ads) used to recruit this population is affected by ad content (ie, image and text).The aim of this study was to evaluate the effects of different images and text included in social media ads used to recruit young gay and bisexual men for the pilot test of a Web-based human papillomavirus (HPV) vaccination intervention.In July and September 2016, we used paid Facebook advertisements to recruit men who were aged 18-25 years, self-identified as gay or bisexual, US resident, and had not received HPV vaccine. A 4x2x2 factorial experiment varied ad image (a single young adult male, a young adult male couple, a group of young adult men, or a young adult male talking to a doctor), content focus (text mentioning HPV or HPV vaccine), and disease framing (text mentioning cancer or a sexually transmitted disease [STD]). Poisson regression determined whether these experimental factors affected ad performance.The recruitment campaign reached a total of 35,646 users who viewed ads for 36,395 times. This resulted in an overall unique click-through rate of 2.01% (717/35,646) and an overall conversion rate of 0.66% (241/36,395). Reach was higher for ads that included an image of a couple (incidence rate ratio, IRR=4.91, 95% CI 2.68-8.97, P<.001) or a group (IRR=2.65, 95% CI 1.08-6.50, P=.03) compared with those that included an image of a single person. Ads that included an image of a couple also had a higher conversion rate (IRR=2.56, 95% CI 1.13-5.77, P=.02) than ads that included an image of a single person. Ads with text mentioning an STD had a higher unique click-through rate compared with ads with text mentioning cancer (IRR=1.34, 95% CI 1.06-1.69, P=.01). The campaign cost a total of US $413.72 and resulted in 150 eligible and enrolled individuals (US $2.76 per enrolled participant).Facebook ads are a convenient and cost-efficient strategy for reaching and recruiting young gay and bisexual men for a Web-based HPV vaccination intervention. To help optimize ad performance among this population, researchers should consider the importance of the text and image included in the social media recruitment ads.

Dataset Information

Estimating the Population Impact of a New Pediatric Influenza Vaccination Program in England Using Social Media Content.

Publications

Estimating the Population Impact of a New Pediatric Influenza Vaccination Program in England Using Social Media Content.

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