Browsing by Author "Guerrisi, Caroline"
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- COVID-19 Vaccine Effectiveness in Autumn and Winter 2022 to 2023 Among Older EuropeansPublication . Laniece Delaunay, Charlotte; Mazagatos, Clara; Martínez-Baz, Iván; Túri, Gergő; Goerlitz, Luise; Domegan, Lisa; Meijer, Adam; Rodrigues, Ana Paula; Sève, Noémie; Ilić, Maja; Latorre-Margalef, Neus; Lazar, Mihaela; Maurel, Marine; Melo, Aryse; Andreu Ivorra, Blanca; Casado, Itziar; Horváth, Judit Krisztina; Buda, Silke; Bennett, Charlene; de Lange, Marit; Guiomar, Raquel; Enouf, Vincent; Mlinarić, Ivan; Samuelsson Hagey, Tove; Dinu, Sorin; Rumayor, Mercedes; Castilla, Jesús; Oroszi, Beatrix; Dürrwald, Ralf; O’Donnell, Joan; Hooiveld, Mariëtte; Gómez, Verónica; Falchi, Alessandra; Kurečić Filipović, Sanja; Dillner, Lena; Popescu, Rodica; Bacci, Sabrina; Kaczmarek, Marlena; Kissling, Esther; Gallardo García, Virtudes; Perez Morilla, Esteban; Pedrosa Corral, Irene; García Vázquez, Miriam; Milagro-Beamonte, Ana; Fernandez Ibañez, Ana; Margolles Martins, Mario; Giménez Duran, Jaume; Sastre Palou, Bartolomé; López Causapé, Carla; Viloria Raymundo, Luis Javier; Vega Alonso, Tomás; Ordax Díez, Ana; Lozano Alonso, Jose Eugenio; Rojo Bello, Silvia; Mendioroz, Jacobo; Basile, Luca; Martínez Mateo, Ana Isabel; Ruiz de Porras, Carlota; Moya Garcés, Alba; Marcos, Mª Ángeles; López Maside, Aurora; Botella Quijal, Francesc; Miralles Espi, Maite; Andreu Salete, Cristina; García Rodríguez, María del Carmen; Linares, Juan Antonio; García Comas, Luis; Barranco, Mª Isabel; Chirlaque, María-Dolores; Moreno Docón, Antonio; Ramos Marín, Violeta; Castrillejo, Daniel; Gómez Anés, Atanasio; Larrauro, Amparo; Pérez-Gimeno, Gloria; Lozano Álvarez, Marcos; Vega, Lorena; Galindo, Silvia; Puma, Tania; Monge, Susana; Pozo, Francisco; Casas, Inmaculada; Sandonis, Virginia; Vázquez-Morón, Sonia; Echeverría, Aitziber; Trobajo-Sanmartín, Camino; García Cenoz, Manuel; Ezpeleta, Guillermo; Ezpeleta, Carmen; Navascués, Ana; Krisztalovics, Katalin; Mucsányiné Juhász, Krisztina; Kristóf, Katalin; Preuss, Ute; Wedde, Marianne; Biere, Barbara; Reiche, Janine; Oh, Djin-Ye; McKenna, Adele; Connell, Jeff; Joyce, Michael; Bagheri, Mariam; Bos, Sanne; van den Brink, Sharon; Dijkstra, Frederika; Eggink, Dirk; van Gageldonk-Lafeber, Rianne; Goderski, Gabriel; Herrebrugh, Chantal; Jenniskens, Liz; Reukers, Daphne; Sluimer, John; Sprong, Tara; Teirlinck, Anne; Veldhijzen, Nienke; van der Burgh, Ruben; Kager, Cathrien; Klinkhamer, Mayra; Knottnerus, Bart; Riethof, Marloes; van den Broek, Ruud; Wortel, Safira; Machado, Ausenda; Kislaya, Irina; Aniceto, Carlos; Gomes, Licínia; Verdasca, Nuno; Henriques, Camila; Dias, Daniela; Lança, Miguel; Blanchon, Thierry; Guerrisi, Caroline; Renard, Aubane; Launay, Titouan; Masse, Shirley; Chazelle, Marie; Ferenčak, Ivana; Kaić, Bernard; Višekruna Vučina, Vesna; Čusek Adamić, Katica; Kosanović Ličina, Mirjana Lana; Lakošeljac, Danijela; Mihin Huskić, Ivana; Nonković, Diana; Carnahan, Annasara; Hansson-Pihlainen, Eva; Arvesen, Elin; Nid, Nora; Hansen, Anna-Lena; Andersson, Emmi; Dillner, Lena; Jidovu, Adrian; Timnea, Olivia Carmen; Pascu, Cătălina; Oprea, Mihaela; Bistriceanu, Iulia; Ivanciuc, Alina; Mihai, Maria Elena; VEBIS Primary Care Vaccine Effectiveness GroupKey Points: - Question: What was the effectiveness of COVID-19 vaccines administered in autumn and winter 2022 to 2023 against symptomatic SARS-CoV-2 infection among people aged 60 years or older in Europe, and how did different exposed or reference groups affect effectiveness? - Findings: In this case-control study of 9308 primary care patients at 11 European sites, within 3 months of vaccination, all COVID-19 vaccine effectiveness (CVE) estimates were 29% to 39% against SARS-CoV-2 viruses and 44% to 52% against the XBB variants. All point estimates decreased by time after vaccination, with no vaccine protection after 6 months. - Meaning: Findings of this study suggest that COVID-19 vaccination campaigns should precede peaks in SARS-CoV-2 incidence and that effectiveness of new vaccines against emerging variants should be continually monitored using seasonal CVE approaches.
- Influenzanet: citizens among 10 countries collaborating to monitor influenza in EuropePublication . Koppeschaar, Carl E.; Colizza, Vittoria; Guerrisi, Caroline; Turbelin, Clément; Duggan, Jim; Edmunds, W John; Kjelsø, Charlotte; Mexia, Ricardo; Moreno, Yamir; Meloni, Sandro; Paolotti, Daniela; Perrotta, Daniela; van Straten, Edward; Franco, Ana O.Background: The wide availability of the Internet and the growth of digital communication technologies have become an important tool for epidemiological studies and health surveillance. Influenzanet is a participatory surveillance system monitoring the incidence of influenza-like illness (ILI) in Europe since 2003. It is based on data provided by volunteers who self-report their symptoms via the Internet throughout the influenza season and currently involves 10 countries. Objective: In this paper, we describe the Influenzanet system and provide an overview of results from several analyses that have been performed with the collected data, which include participant representativeness analyses, data validation (comparing ILI incidence rates between Influenzanet and sentinel medical practice networks), identification of ILI risk factors, and influenza vaccine effectiveness (VE) studies previously published. Additionally, we present new VE analyses for the Netherlands, stratified by age and chronic illness and offer suggestions for further work and considerations on the continuity and sustainability of the participatory system. Methods: Influenzanet comprises country-specific websites where residents can register to become volunteers to support influenza surveillance and have access to influenza-related information. Participants are recruited through different communication channels. Following registration, volunteers submit an intake questionnaire with their postal code and sociodemographic and medical characteristics, after which they are invited to report their symptoms via a weekly electronic newsletter reminder. Several thousands of participants have been engaged yearly in Influenzanet, with over 36,000 volunteers in the 2015-16 season alone. Results: In summary, for some traits and in some countries (eg, influenza vaccination rates in the Netherlands), Influenzanet participants were representative of the general population. However, for other traits, they were not (eg, participants underrepresent the youngest and oldest age groups in 7 countries). The incidence of ILI in Influenzanet was found to be closely correlated although quantitatively higher than that obtained by the sentinel medical practice networks. Various risk factors for acquiring an ILI infection were identified. The VE studies performed with Influenzanet data suggest that this surveillance system could develop into a complementary tool to measure the effectiveness of the influenza vaccine, eventually in real time. Conclusions: Results from these analyses illustrate that Influenzanet has developed into a fast and flexible monitoring system that can complement the traditional influenza surveillance performed by sentinel medical practices. The uniformity of Influenzanet allows for direct comparison of ILI rates between countries. It also has the important advantage of yielding individual data, which can be used to identify risk factors. The way in which the Influenzanet system is constructed allows the collection of data that could be extended beyond those of ILI cases to monitor pandemic influenza and other common or emerging diseases.
- Participatory Syndromic Surveillance of Influenza in EuropePublication . Guerrisi, Caroline; Turbelin, Clément; Blanchon, Thierry; Hanslik, Thomas; Bonmarin, Isabelle; Levy-Bruhl, Daniel; Perrotta, Daniela; Paolotti, Daniela; Smallenburg, Ronald; Koppeschaar, Carl; Franco, Ana O.; Mexia, Ricardo; Edmunds, W. John; Sile, Bersabeh; Pebody, Richard; van Straten, Edward; Meloni, Sandro; Moreno, Yamir; Duggan, Jim; Kjelsø, Charlotte; Colizza, VittoriaThe growth of digital communication technologies for public health is offering an unconventional means to engage the general public in monitoring community health. Here we present Influenzanet, a participatory system for the syndromic surveillance of influenza-like illness (ILI) in Europe. Through standardized online surveys, the system collects detailed profile information and self-reported symptoms volunteered by participants resident in the Influenzanet countries. Established in 2009, it now includes 10 countries representing more than half of the 28 member states of the European Union population. The experience of 7 influenza seasons illustrates how Influenzanet has become an adjunct to existing ILI surveillance networks, offering coherence across countries, inclusion of nonmedically attended ILI, flexibility in case definition, and facilitating individual-level epidemiological analyses generally not possible in standard systems. Having the sensitivity to timely detect substantial changes in population health, Influenzanet has the potential to become a viable instrument for a wide variety of applications in public health preparedness and control.
- Unsupervised extraction of epidemic syndromes from participatory influenza surveillance self-reported symptomsPublication . Kalimeri, Kyriaki; Delfino, Matteo; Cattuto, Ciro; Perrotta, Daniela; Colizza, Vittoria; Guerrisi, Caroline; Turbelin, Clement; Duggan, Jim; Edmunds, John; Obi, Chinelo; Pebody, Richard; Franco, Ana O.; Moreno, Yamir; Meloni, Sandro; Koppeschaar, Carl; Kjelsø, Charlotte; Mexia, Ricardo; Paolotti, DanielaAbstract: Seasonal influenza surveillance is usually carried out by sentinel general practitioners (GPs) who compile weekly reports based on the number of influenza-like illness (ILI) clinical cases observed among visited patients. This traditional practice for surveillance generally presents several issues, such as a delay of one week or more in releasing reports, population biases in the health-seeking behaviour, and the lack of a common definition of ILI case. On the other hand, the availability of novel data streams has recently led to the emergence of non-traditional approaches for disease surveillance that can alleviate these issues. In Europe, a participatory web-based surveillance system called Influenzanet represents a powerful tool for monitoring seasonal influenza epidemics thanks to aid of self-selected volunteers from the general population who monitor and report their health status through Internet-based surveys, thus allowing a real-time estimate of the level of influenza circulating in the population. In this work, we propose an unsupervised probabilistic framework that combines time series analysis of self-reported symptoms collected by the Influenzanet platforms and performs an algorithmic detection of groups of symptoms, called syndromes. The aim of this study is to show that participatory web-based surveillance systems are capable of detecting the temporal trends of influenza-like illness even without relying on a specific case definition. The methodology was applied to data collected by Influenzanet platforms over the course of six influenza seasons, from 2011-2012 to 2016-2017, with an average of 34,000 participants per season. Results show that our framework is capable of selecting temporal trends of syndromes that closely follow the ILI incidence rates reported by the traditional surveillance systems in the various countries (Pearson correlations ranging from 0.69 for Italy to 0.88 for the Netherlands, with the sole exception of Ireland with a correlation of 0.38). The proposed framework was able to forecast quite accurately the ILI trend of the forthcoming influenza season (2016-2017) based only on the available information of the previous years (2011-2016). Furthermore, to broaden the scope of our approach, we applied it both in a forecasting fashion to predict the ILI trend of the 2016-2017 influenza season (Pearson correlations ranging from 0.60 for Ireland and UK, and 0.85 for the Netherlands) and also to detect gastrointestinal syndrome in France (Pearson correlation of 0.66). The final result is a near-real-time flexible surveillance framework not constrained by any specific case definition and capable of capturing the heterogeneity in symptoms circulation during influenza epidemics in the various European countries.