A social media intervention for communicating vaccine safety in low- and middle-income countries: protocol for a pilot study.

Vaccine safety is a concern that continues to drive hesitancy and refusal in populations in low-and-middle income countries (LMICs). Communicating about vaccine safety is a strategy that can successfully change personal and community perceptions and behaviors toward vaccination. The COVID-19 infodemic emergency with the rapid rollout of new vaccines and new technology, demonstrated the need for good and effective vaccine safety communication. The Vaccine Safety Net (VSN), a WHO-led global network of websites that provide reliable information on vaccine safety offers the ideal environment for gathering web and social media analytics for measuring impact of vaccine safety messages. Its members work with a wide range of populations, in different geographic locations and at many levels including national, regional, and local. We propose to undertake a pilot study to evaluate the feasibility of implementing COVID-19 vaccine safety communications with VSN members working in LMICs and to assess the impact of communications on public knowledge, attitudes, and perceptions.

Prioritizing educational initiatives on emerging technologies for Italian pediatricians: bibliometric review and a survey.

BACKGROUND: Emerging technologies have demonstrated outstanding potential in improving healthcare, yet their full integration remains a challenge for all medical specialties, including pediatrics. To support the swift implementation of technologies, we identified the current trends through a bibliometric review, and we conducted a survey on Italian pediatricians to gauge educational needs and willingness to integrate technologies into clinical practice. METHODS: A working group of pediatricians representing various backgrounds designed and coordinated the study. To identify relevant topics for educational strategy development, we focused on virtual reality, telehealth, natural language processing, smartphone applications, robotics, genomics, and artificial intelligence. A bibliometric analysis limited to 2018-2023 was performed to identify trends and emerging applications within each topic. Based on the results, a questionnaire was developed and made available online to all Italian pediatricians. The results were analyzed through descriptive analysis and a multivariable logistic regression to explore associations between technology adoption and sociodemographic characteristics. RESULTS: A total of 3,253 publications were found, with Telehealth and Telemedicine having the highest number of publications and Natural Language Processing the lowest. The number of respondents to the online questionnaire was 1,540, predominantly medical doctors with over 20 years of experience working as family pediatricians. Telehealth had the highest level of knowledge (95.2%), followed by smartphone applications (89.1%) and genomics (63.2%). The greatest potential for increased use through education programs was projected for natural language processing (+ 43.1%), artificial intelligence (+ 39.6%), and virtual and mixed reality (+ 38.1%). Female respondents and older individuals were less likely to use emerging technologies. Hospital pediatricians and residents were more likely to use AI. CONCLUSIONS: We developed a replicable strategy to identify emerging themes in medical technologies relevant to pediatrics and assess the educational needs of pediatricians. A significant gap still exists between current and potential usage of emerging technologies among Italian pediatricians although they showed a positive attitude towards implementing these technologies following specific education programs. The study highlights the need for comprehensive education programs on emerging technologies in pediatrics and recommends addressing gender and age disparities in technology adoption.

Machine learning clinical decision support systems for surveillance: a case study on pertussis and RSV in children.

We tested the performance of a machine learning (ML) algorithm based on signs and symptoms for the diagnosis of RSV infection or pertussis in the first year of age to support clinical decisions and provide timely data for public health surveillance. We used data from a retrospective case series of children in the first year of life investigated for acute respiratory infections in the emergency room from 2015 to 2020. We collected data from PCR laboratory tests for confirming pertussis or RSV infection, clinical symptoms, and routine blood testing results, which were used for the algorithm development. We used a LightGBM model to develop 2 sets of models for predicting pertussis and RSV infection: for each type of infection, we developed one model trained with the combination of clinical symptoms and results from routine blood test (white blood cell count, lymphocyte fraction and C-reactive protein), and one with symptoms only. All analyses were performed using Python 3.7.4 with Shapley values (Shap values) visualization package for predictor visualization. The performance of the models was assessed through confusion matrices. The models were developed on a dataset of 599 children. The recall for the pertussis model combining symptoms and routine laboratory tests was 0.72, and 0.74 with clinical symptoms only. For RSV infection, recall was 0.68 with clinical symptoms and laboratory tests and 0.71 with clinical symptoms only. The F1 score for the pertussis model was 0.72 in both models, and, for RSV infection, it was 0.69 and 0.75. ML models can support the diagnosis and surveillance of infectious diseases such as pertussis or RSV infection in children based on common symptoms and laboratory tests. ML-based clinical decision support systems may be developed in the future in large networks to create accurate tools for clinical support and public health surveillance.

Exploring the vaccine conversation on TikTok in Italy: beyond classic vaccine stances.

TikTok, a social media platform for creating and sharing short videos, has seen a surge in popularity during the COVID-19 pandemic. To analyse the Italian vaccine conversation on TikTok, we downloaded a sample of videos with a high play count (Top Videos), identified through an unofficial Application Programming Interface (consistent with TikTok's Terms of Service), and collected public videos from vaccine sceptic users through snowball sampling (Vaccine Sceptics' videos). The videos were analysed using qualitative and quantitative methods, in terms of vaccine stance, tone of voice, topic, conformity with TikTok style, and other characteristics. The final datasets consisted of 754 Top Videos (by 510 single users) plus 180 Vaccine Sceptics' videos (by 29 single users), posted between January 2020 and March 2021. In 40.5% of the Top Videos the stance was promotional, 33.9% were indefinite-ironic, 11.3% were neutral, 9.7% were discouraging, and 3.1% were ambiguous (i.e. expressing an ambivalent stance towards vaccines); 43% of promotional videos were from healthcare professionals. More than 95% of the Vaccine Sceptic videos were discouraging. Multiple correspondence analysis showed that, compared to other stances, promotional videos were more frequently created by healthcare professionals and by females, and their most frequent topic was herd immunity. Discouraging videos were associated with a polemical tone of voice and their topics were conspiracy and freedom of choice. Our analysis shows that Italian vaccine-sceptic users on TikTok are limited in number and vocality, and the large proportion of videos with an indefinite-ironic stance might imply that the incidence of affective polarisation could be lower on TikTok, compared to other social media, in the Italian context. Safety is the most frequent concern of users, and we recorded an interesting presence of healthcare professionals among the creators. TikTok should be considered as a medium for vaccine communication and for vaccine promotion campaigns.

Public Engagement in Digital Recommendations for Promoting Healthy Parental Behaviours from Preconception through the First 1000 Days.

Web-based digital interventions may play a central role for health promoting strategies in the first "1000 days", from conception through the first 2 years of life. We developed a web platform providing evidence-based recommendations in the first 1000 days through short videos, and we studied engagement by users from preconception through parenthood in the second year of life. We described the access to videos by topic and used a multilevel model to explore the user characteristics associated with access to the video recommendations. Overall, breastfeeding, physical activity and nutrition were the most popular topics (normalized views: 89.2%, 87.2% and 86.4% respectively), while content on paternal health and smoking and alcohol was less engaging (37.3% and 42.0%). Nutrition content was the most viewed in the preconception period and during the first two trimesters of pregnancy. Nutrition and breastfeeding were also the most popular topics for users with children less than 2 years old. Higher levels of health literacy were associated only with child health content. The study findings indicate that digital strategies should be adapted according to the time period in the first 1000 days. Alternative digital promotion strategies for the less engaging topics should be considered.

Feasibility of a VR Intervention to Decrease Anxiety in Children with Tumors Undergoing CVC Dressing.

Virtual reality (VR) represents a promising digital intervention for managing distress and anxiety in children with tumors undergoing painful medical procedures. In an experimental cross-over study, we administered a VR intervention consisting of relaxing games during central venous catheter (CVC) dressing. The VR sessions were compared with no-VR during CVC medication. We used the distress thermometer and RCMAS-2 scale to assess distress and anxiety levels. We also explored the satisfaction level in patients and families. We enrolled 22 children. The distress levels after medication were lower in the VR group than in those without VR (VR: median 2; IQR 0-2; no-VR: median 4; IQR: 3-5). No variation in anxiety levels was detected by VR intervention. Satisfaction for using VR was very high in children and their families although a total of 12% of children were disappointed by the effect of VR. Most healthcare workers felt that VR would be useful in routine clinical practice. A VR intervention is highly acceptable, may be efficacious in decreasing distress in children with cancer undergoing painful procedures, but it is less likely that it has a measurable impact on anxiety. Evidence from larger studies is needed to assess VR translation into the clinical workflow.

Understanding the vaccine stance of Italian tweets and addressing language changes through the COVID-19 pandemic: Development and validation of a machine learning model.

Social media is increasingly being used to express opinions and attitudes toward vaccines. The vaccine stance of social media posts can be classified in almost real-time using machine learning. We describe the use of a Transformer-based machine learning model for analyzing vaccine stance of Italian tweets, and demonstrate the need to address changes over time in vaccine-related language, through periodic model retraining. Vaccine-related tweets were collected through a platform developed for the European Joint Action on Vaccination. Two datasets were collected, the first between November 2019 and June 2020, the second from April to September 2021. The tweets were manually categorized by three independent annotators. After cleaning, the total dataset consisted of 1,736 tweets with 3 categories (promotional, neutral, and discouraging). The manually classified tweets were used to train and test various machine learning models. The model that classified the data most similarly to humans was XLM-Roberta-large, a multilingual version of the Transformer-based model RoBERTa. The model hyper-parameters were tuned and then the model ran five times. The fine-tuned model with the best F-score over the validation dataset was selected. Running the selected fine-tuned model on just the first test dataset resulted in an accuracy of 72.8% (F-score 0.713). Using this model on the second test dataset resulted in a 10% drop in accuracy to 62.1% (F-score 0.617), indicating that the model recognized a difference in language between the datasets. On the combined test datasets the accuracy was 70.1% (F-score 0.689). Retraining the model using data from the first and second datasets increased the accuracy over the second test dataset to 71.3% (F-score 0.713), a 9% improvement from when using just the first dataset for training. The accuracy over the first test dataset remained the same at 72.8% (F-score 0.721). The accuracy over the combined test datasets was then 72.4% (F-score 0.720), a 2% improvement. Through fine-tuning a machine-learning model on task-specific data, the accuracy achieved in categorizing tweets was close to that expected by a single human annotator. Regular training of machine-learning models with recent data is advisable to maximize accuracy.

How the Italian Twitter Conversation on Vaccines Changed During the First Phase of the Pandemic: A Mixed-Method Analysis.

In the context of the European Joint Action on Vaccination, we analyzed, through quantitative and qualitative methods, a random sample of vaccine-related tweets published in Italy between November 2019 and June 2020, with the aim of understanding how the Twitter conversation on vaccines changed during the first phase of the pandemic, compared to the pre-pandemic months. Tweets were analyzed by a multidisciplinary team in terms of kind of vaccine, vaccine stance, tone of voice, population target, mentioned source of information. Multiple correspondence analysis was used to identify variables associated with vaccine stance. We analyzed 2,473 tweets. 58.2% mentioned the COVID-19 vaccine. Most had a discouraging stance (38.1%), followed by promotional (32.5%), neutral (22%) and ambiguous (2.5%). The discouraging stance was the most represented before the pandemic (69.6%). In February and March 2020, discouraging tweets decreased intensely and promotional and neutral tweets dominated the conversation. Between April and June 2020, promotional tweets remained more represented (36.5%), followed by discouraging (30%) and neutral (24.3%). The tweets' tone of voice was mainly polemical/complaining, both for promotional and for discouraging tweets. The multiple correspondence analysis identified a definite profile for discouraging and neutral tweets, compared to promotional and ambiguous tweets. In conclusion, the emergence of SARS-CoV-2 caused a deep change in the vaccination discourse on Twitter in Italy, with an increase of promotional and ambiguous tweets. Systematic monitoring of Twitter and other social media, ideally combined with traditional surveys, would enable us to better understand Italian vaccine hesitancy and plan tailored, data-based communication strategies.

The future for COVID-19 vaccines: public health assessment and perspectives based on scientific evidence.

The development and use of messenger RNA-based (mRNA) vaccines against the SARS-CoV-2 spike protein have proven to be highly effective against symptomatic COVID-19, especially for severe forms. Since the declaration of a public health emergency in early 2020, however, the SARS-CoV-2 virus has continuously evolved, giving rise to several variants that have caused and continue to cause concern in the scientific community. Currently, viruses circulating worldwide belong to the Omicron lineage, with several identified sub-variants. In response to virus mutation, mRNA vaccines have been adapted into bivalent vaccines containing two mRNAs: one encoding the original Wuhan SARS-CoV-2 spike protein and one encoding the BA.1 or BA.4-5 spike protein of the Omicron sub-variant. This strategy is based on the hypothesis that the immune system's response improves when variants are included in the vaccine, leading to an increase in the magnitude and diversity of both the humoral and cellular immune response. The evidence gathered to date confirms the use of bivalent vaccines as the optimal strategy. In the light of current knowledge, and in the awareness of the impossibility of making precise predictions on the evolution of the COVID-19 pandemic, as a group of experts we propose some considerations for the progressive evolution of vaccination against SARS-CoV-2 from pandemic to endemic vaccination.

Digital tools, multidisciplinarity and innovation for communicating vaccine safety in the COVID-19 era.

The research on the anti-SARS-CoV-2 vaccines and their commercialization is an opportunity to test and consolidate the current knowledge along with the diverse available tools related to vaccine communication.In this paper we explore the value of a multidisciplinary approach in this field: vaccine communication activities can be combined with insights from data science, risk communication, behavior change, design thinking and digital marketing. Methodologies derived from innovation and human-centered design can contribute to the development and testing of vaccine promotion campaigns, speeding up processes and streamlining the production of evidence in this area. The multiple activities involving the anti-SARS-CoV-2 vaccine could be the fertile ground in which to develop, test and refine effective frameworks to transfer data acquired through listening strategies into effective vaccine promotion campaigns. The World Health Organization's Vaccine Safety Net is an interesting example of trusted information sources that aim toward using digital tools and innovative methodologies for communicating science-based information on vaccine safety at the global level.

Intention of Parents to Immunize Children against SARS-CoV-2 in Italy.

Several countries have targeted adolescents for immunization against SARS-CoV-2 to mitigate COVID-19 spread. In Italy, immunization for children ≥ 12 years has been available starting from June 2021. We conducted a cross-sectional study to investigate the knowledge, attitude and intention to vaccinate children < 18 years in Italian families. We used a multinomial logistic regression model to investigate factors associated with intention to vaccinate. We collected a total of 1696 responses. Among the 491 families of children ≥ 12 years, 41.2% would not vaccinate their children and 21.2% were uncertain, while among the 1205 families of children < 12 years, 36.1% would not vaccinate and 33.8% were uncertain. Determinants of intention to vaccinate both age groups were perceived safety and efficacy of vaccines and perceived risk of transmitting infection to adults. For children < 12 years, additional determinants were perceived risk of being infected and being hospitalized because of COVID-19. In view of the expanding strategy to vaccinate adolescents and the availability of immunization for children < 12 years, our results call for a communication strategy targeted at families of children focused on the safety and efficacy of COVID-19 vaccine in children and on the dynamics of infection spread across different age groups. As perceptions in families are volatile and may change rapidly over time, repeated surveys for measuring attitudes to vaccinate would be advisable.

Digital Surveillance Through an Online Decision Support Tool for COVID-19 Over One Year of the Pandemic in Italy: Observational Study.

BACKGROUND: Italy has experienced severe consequences (ie, hospitalizations and deaths) during the COVID-19 pandemic. Online decision support systems (DSS) and self-triage applications have been used in several settings to supplement health authority recommendations to prevent and manage COVID-19. A digital Italian health tech startup, Paginemediche, developed a noncommercial, online DSS with a chat user interface to assist individuals in Italy manage their potential exposure to COVID-19 and interpret their symptoms since early in the pandemic. OBJECTIVE: This study aimed to compare the trend in online DSS sessions with that of COVID-19 cases reported by the national health surveillance system in Italy, from February 2020 to March 2021. METHODS: We compared the number of sessions by users with a COVID-19-positive contact and users with COVID-19-compatible symptoms with the number of cases reported by the national surveillance system. To calculate the distance between the time series, we used the dynamic time warping algorithm. We applied Symbolic Aggregate approXimation (SAX) encoding to the time series in 1-week periods. We calculated the Hamming distance between the SAX strings. We shifted time series of online DSS sessions 1 week ahead. We measured the improvement in Hamming distance to verify the hypothesis that online DSS sessions anticipate the trends in cases reported to the official surveillance system. RESULTS: We analyzed 75,557 sessions in the online DSS; 65,207 were sessions by symptomatic users, while 19,062 were by contacts of individuals with COVID-19. The highest number of online DSS sessions was recorded early in the pandemic. Second and third peaks were observed in October 2020 and March 2021, respectively, preceding the surge in notified COVID-19 cases by approximately 1 week. The distance between sessions by users with COVID-19 contacts and reported cases calculated by dynamic time warping was 61.23; the distance between sessions by symptomatic users was 93.72. The time series of users with a COVID-19 contact was more consistent with the trend in confirmed cases. With the 1-week shift, the Hamming distance between the time series of sessions by users with a COVID-19 contact and reported cases improved from 0.49 to 0.46. We repeated the analysis, restricting the time window to between July 2020 and December 2020. The corresponding Hamming distance was 0.16 before and improved to 0.08 after the time shift. CONCLUSIONS: Temporal trends in the number of online COVID-19 DSS sessions may precede the trend in reported COVID-19 cases through traditional surveillance. The trends in sessions by users with a contact with COVID-19 may better predict reported cases of COVID-19 than sessions by symptomatic users. Data from online DSS may represent a useful supplement to traditional surveillance and support the identification of early warning signals in the COVID-19 pandemic.

Sars-Cov2 Not Detected in a Pediatric Population With Acute Respiratory Infection in Primary Care in Central and Southern Italy From November 2019 to Early March 2020.

Background: In December 2019, a novel coronavirus named SARS-CoV-2 started circulating in China and this led to a major epidemic in Northern Italy between February and May 2020. Young children (aged <5 years) seem to be less affected by this coronavirus disease (COVID-19) compared to adults, although there is very little information on the circulation of this new virus among children in Italy. We retrospectively tested nasopharyngeal swabs for SARS-CoV-2 in samples collected in young children between November, 2019 and March, 2020 in the context of the RSV ComNet study. Methods: Two networks of primary care pediatricians in Lazio (Central Italy) and Puglia (Southern Italy) collected nasopharyngeal swabs from children, aged <5 years, presenting with symptoms for an acute respiratory infection (ARI). The RSV ComNet study is a multicenter study implemented to estimate the burden of RSV in young children (aged <5 years) in the community. Swabs were sent to a central reference laboratory and tested for 14 respiratory viruses through RT-PCR. All collected samples were retrospectively tested for SARS-CoV-2 using RT-PCR (Istituto Superiore di Sanità protocol). Results: A total of 293 children with ARI were identified in the two participating networks. The highest number of cases were recruited in weeks 51/2019 and 3/2020. The majority of patients (57%) came from the Lazio region. All of the 293 samples tested negative for SARS-Cov2. Rhinovirus was the most frequently detected virus (44%), followed by RSV (41%) and influenza viruses (14%). Conclusions: Our study shows that in Lazio (a region of intermediate SARS-COV-2 incidence) and Puglia (a region of low incidence), the SARS-Cov2 virus did not circulate in a sample of ARI pediatric cases consulting primary care pediatricians between November 2019 and March 2020.

Knowledge and Perception of COVID-19 Pandemic during the First Wave (Feb-May 2020): A Cross-Sectional Study among Italian Healthcare Workers.

Italy was the first country in Europe to face the coronavirus pandemic. The aim of the study was to analyze healthcare workers' (HCWs) level of information, practice, and risk perception towards COVID-19. We set up a cross-sectional study through SurveyMonkey® and distributed the link through Facebook and Whatsapp closed groups. The research instrument was a 31 items questionnaire distributed using Facebook and Whatsapp. It was conducted in Italy from February to May 2020. The study participants were general practitioners, pediatricians and other health professionals. A total of 958 participants were included: 320 (33.4%) general practitioners, 248 (25.9%) pediatricians and 390 (40.7%) other health professionals. The highest response rate was from Northern Italy (48.1%), followed by Central Italy (29.9%) and Southern Italy (22.0%). Less than a half (46%) of respondents felt they had a good level of information of COVID-19 case definition and of national prevention guidelines. Respondents reported to have changed their clinical practice; particularly, they increased the use of masks (87.1%, p < 0.001), disinfection and sanitization of doctors' offices (75.8%, p < 0.001), the use of protective glasses (71.2%, p < 0.001), alcoholic hand solution (71.2%, p < 0.001), and hand washing (31.8%, p = 0.028). HCWs are at high risk of infection; less than a half of them felt adequately prepared to face COVID-19 pandemic, so they need extensive information and awareness of the disease to take adequate precautionary measures, and they are crucial to disseminate good practices.

Digital tools in the informed consent process: a systematic review.

BACKGROUND: Providing understandable information to patients is necessary to achieve the aims of the Informed Consent process: respecting and promoting patients' autonomy and protecting patients from harm. In recent decades, new, primarily digital technologies have been used to apply and test innovative formats of Informed Consent. We conducted a systematic review to explore the impact of using digital tools for Informed Consent in both clinical research and in clinical practice. Understanding, satisfaction and participation were compared for digital tools versus the non-digital Informed Consent process. METHODS: We searched for studies on available electronic databases, including Pubmed, EMBASE, and Cochrane. Studies were identified using specific Mesh-terms/keywords. We included studies, published from January 2012 to October 2020, that focused on the use of digital Informed Consent tools for clinical research, or clinical procedures. Digital interventions were defined as interventions that used multimedia or audio-video to provide information to patients. We classified the interventions into 3 different categories: video only, non-interactive multimedia, and interactive multimedia. RESULTS: Our search yielded 19,579 publications. After title and abstract screening 100 studies were retained for full-text analysis, of which 73 publications were included. Studies examined interactive multimedia (29/73), non-interactive multimedia (13/73), and videos (31/73), and most (34/38) studies were conducted on adults. Innovations in consent were tested for clinical/surgical procedures (26/38) and clinical research (12/38). For research IC, 21 outcomes were explored, with a positive effect on at least one of the studied outcomes being observed in 8/12 studies. For clinical/surgical procedures 49 outcomes were explored, and 21/26 studies reported a positive effect on at least one of the studied outcomes. CONCLUSIONS: Digital technologies for informed consent were not found to negatively affect any of the outcomes, and overall, multimedia tools seem desirable. Multimedia tools indicated a higher impact than videos only. Presence of a researcher may potentially enhance efficacy of different outcomes in research IC processes. Studies were heterogeneous in design, making evaluation of impact challenging. Robust study design including standardization is needed to conclusively assess impact.

Narrative Diaries in Pediatrics: A Scoping Review.

PROBLEM: Health diaries with both clinical and narrative elements have been widely used in pediatrics to study children's and families' experiences of illness and coping strategies. The objective of this study is to obtain a synthesis of the literature about narrative health diaries using the PRISMA extension for scoping reviews. ELIGIBILITY CRITERIA: Sources were limited to: English language; narrative diaries; children/adolescents and/or parents/caregivers. SAMPLE: The following databases were searched: PubMed, Embase and CINAHL with no time limits. RESULTS: Among 36 articles included the most common context where a diary was implemented was the home (61%), the hospital (17%) and the school (14%). The most common diarist is the child or adolescent (50%). Paper diary was the most common type (53%), followed by the video diary (19%), the e-diary (8%) or the audio diary (8%). None of the studies explored the impact of the use of diaries on patient outcomes. CONCLUSIONS: The narrative health diary is used to report patient experiences of illness or common life from the point of view of the child, adolescent or other family members. The diversity of the diaries found shows how the narrative diary may be 'adapted' to different settings and pediatric populations. IMPLICATIONS: The narrative diary is a relevant tool for the exploration of children's and adolescents' experiences of illness and common life. Studies are still needed to describe the impact of narrative diaries keeping on children's health outcomes.

Online health information seeking behaviours of parents of children undergoing surgery in a pediatric hospital in Rome, Italy: a survey.

BACKGROUND: People increasingly search online for health information. Particularly, parents of patients often use the Internet as a source for health information. We conducted a survey to investigate the online searching behavior of parents of patients < 18 years, admitted for surgery in an Italian pediatric hospital. METHODS: The cross-sectional survey was nested in a prospective cohort study on surgical procedures. Parents of patients undergoing surgical procedures at Bambino Gesù Children's Hospital, Rome, Italy, were enrolled and contacted by phone after the procedure. We recorded socio-demographic data, sex, length of stay following surgery, proximity of residence to the hospital, use of the internet to search for information on the surgery before and after the intervention and effect of information found online. RESULTS: The majority (91%) of parents of children undergoing surgical intervention used the internet. Of these, 74.3% of parents searched for information before surgery, and 26.1% searched for information after. Most parents searched for information on the care provider's website. Two thirds of parents reported that information found online had increased their understanding of the child's condition. Multivariate analyses indicated that families living far from the hospital (> 43 km) were more likely to search for health information (OR 2.3; 95% CI 1.34-4.00), as were families of patients undergoing a major surgery (OR = 2.1; 95% CI 1.04-4.11). CONCLUSIONS: Parents of children undergoing surgery often search online for information on their child's intervention, in particular those whose child is scheduled for a major surgery and those living far from the hospital. A survey like the present one allows to understand parents' information needs, to better guide them in online information seeking and to better tailor information provided on the care provider's website.

The use of web analytics combined with other data streams for tailoring online vaccine safety information at global level: The Vaccine Safety Net's web analytics project.

The Vaccine Safety Net's Web Analytics Project (VSN-WAP) was launched in October 2017 to monitor the behavior of users visiting websites belonging to the VSN, a global network of websites providing science-based information on vaccine safety. Participating websites could provide web metrics in two ways: through a Google Analytics (GA) script, which automatically forwarded metrics to a central account and through manual input (MI) of a reduced subset of metrics (Sessions, Page Views, New Users, Bounce Rate, Views/Session and Average Session Duration), which were pooled with the metrics obtained through GA. Additional metrics were obtained from websites providing data through Google Analytics (Country, Age, Sex, Device). We report results from February 2018 to March 2019. In March 2019, 32 websites were participating in the project (21 through GA, 11 through MI). From February 2018 to March 2019 we recorded 22,471,535 sessions, with 38,307,349 page views. Sessions, New Users and Page views progressively increased, Views/Session, Bounce Rate and Average Session Duration remained stable. Most users were female (68%) and belonged to the 25-34 age range (37%), followed by 35-44 (22%) and 18-24 (19%). Fifty-four percent of users connected from a mobile device, 42% from a desktop and 4% from a tablet. Digital media monitoring techniques can provide insights on the characteristics of users with a specific interest in vaccines. These data can be exploited to improve the performance of websites providing information on vaccines to the general public.

Moderate Vaccine Effectiveness against Severe Acute Respiratory Infection Caused by A(H1N1)pdm09 Influenza Virus and No Effectiveness against A(H3N2) Influenza Virus in the 2018/2019 Season in Italy.

Every season, circulating influenza viruses change; therefore, vaccines must be reformulated each year. We aimed to estimate vaccine effectiveness (VE) against severe influenza infection for the 2018/19 season in Italy. We conducted a test-negative design case-control study at five Italian hospitals. We estimated influenza VE against severe acute respiratory infection (SARI) requiring hospitalisation overall, and by virus subtype, vaccine brand, and age. The 2018/19 season was characterised by A(H1N1)pmd09 and A(H3N2) influenza viruses. Vaccine coverage among <18 years recruited SARI cases was very low (3.2%). Seasonal vaccines were moderately effective against type A influenza overall (adjusted VE = 40.5%; 95% confidence interval (CI) = 18.7-56.4%) and subtype A(H1N1)pmd09 viruses (adjusted VE = 55%; 95% CI = 34.5-69.1%), but ineffective against subtype A(H3N2) viruses (adjusted VE = 2.5%; 95% CI = -50.0-36.7%). Both Fluad and Fluarix Tetra vaccines were effective against type A influenza overall and subtype A(H1N1)pdm09 viruses. VE appeared to be similar across age groups (0-64 years, ≥65 years). Seasonal influenza vaccines in the 2018/19 season were moderately effective in preventing SARI caused by A(H1N1)pdm09 influenza but ineffective against A(H3N2).