Browsing by Author "Guiomar, Raquel"
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- Epidemiology and genetic variability of respiratory syncytial virus in Portugal, 2014–2018Publication . Sáez-López, Emma; Cristóvão, Paula; Costa, Inês; Pechirra, Pedro; Conde, Patrícia; Guiomar, Raquel; Peres, Maria João; Viseu, Regina; Lopes, Paulo; Soares, Vânia; Vale, Fátima; Fonseca, Patrícia; Freitas, Ludivina; Alves, Jose; Pessanha, Maria Ana; Toscano, Cristina; Mota-Vieira, Luísa; Veloso, Rita Cabral; Côrte-Real, Rita; Branquinho, Paula; Pereira‑Vaz, João; Rodrigues, Fernando; Cunha, Mário; Martins, Luís; Mota, Paula; Couto, Ana Rita; J, Bruges Armas; Almeida, Sofia; Rodrigues, DéboraRespiratory syncytial virus (RSV) is associated with substantial morbidity and mortality since it is a predominant viral agent causing respiratory tract infections in infants, young children and the elderly. Considering the availability of the RSV vaccines in the coming years, molecular understanding in RSV is necessary.
- Estimates of 2012/13 influenza vaccine effectiveness using the case test-negative control design with different influenza negative control groupsPublication . Nunes, Baltazar; Machado, Ausenda; Guiomar, Raquel; Pechirra, Pedro; Conde, Patrícia; Cristovão, Paula; Falcão, IsabelBackground: In recent years several reports of influenza vaccine effectiveness (VE) have been made early for public health decision. The majority of these studies use the case test-negative control design (TND),which has been showed to provide, under certain conditions, unbiased estimates of influenza VE. Nevertheless, discussions have been taken on the best influenza negative control group to use. The presentstudy aims to contribute to the knowledge on this field by comparing influenza VE estimates using three test-negative controls: all influenza negative, non-influenza respiratory virus and pan-negative.Methods: Incident ILI patients were prospectively selected and swabbed by a sample of general practitioners. Cases were ILI patients tested positive for influenza and controls ILI patients tested negative forinfluenza. The influenza negative control group was divided into non-influenza virus control group andpan-negative control group. Data were collected on vaccination status and confounding factors. InfluenzaVE was estimated as one minus the odds ratio of been vaccinated in cases versus controls adjusted for confounding effect by logistic regression.Results: Confounder adjusted influenza VE against medically attended laboratory-confirmed influenza was 68.4% (95% CI: 20.7–87.4%) using all influenza negatives controls, 82.1% (95% CI: 47.6–93.9%) usingnon-influenza controls and 49.4% (95% CI: −44.7% to 82.3%) using pan-negative controls.Conclusions: Influenza VE estimates differed according to the influenza negative control group used.These results are in accordance with the expected under the hypothesis of differential viral interference between influenza vaccinated and unvaccinated individuals. Given the wide importance of TND study further studies should be conducted in order to clarify the observed differences.
- Monitoring influenza vaccine effectiveness using the national influenza surveillance systemPublication . Machado, Ausenda; Freitas, Graça; Guiomar, Raquel; Dias, Carlos Matias; Nunes, BaltazarBackground: Flu vaccine composition is reformulated on a yearly basis. As such, the vaccine effectiveness (VE) from previous seasons cannot be considered for subsequent years, and it is necessary to monitor the VE for each season. This study (MonitorEVA- monitoring vaccine effectiveness) intends to evaluate the feasibility of using the national influenza surveillance system (NISS) for monitoring the influenza VE. Material and methods: Data was collected within NISS during 2004 to 2014 seasons. We used a case-control design where laboratory confirmed incident influenza like illness (ILI) patients (cases) were compared to controls (ILI influenza negative). Eligible individuals consisted on all aged individuals that consult a general practitioner or emergency room with ILI symptoms with a swab collected within seven days of symptoms onset. VE was estimated as 1- odds ratio of being vaccinated in cases versus controls adjusted for age and month of onset by logistic regression. Sensitivity analyses were conducted to test possible effect of assumptions on vaccination status, ILI definition and timing of swabs (<3 days after onset). Results: During the 2004-2014 period, a total of 5302 ILI patients were collected but 798 ILI were excluded for not complying with inclusion criteria. After data restriction the sample size in both groups was higher than 148 individuals/ season; minimum sample size needed to detect a VE of at least 50% considering a level of significance of 5% and 80% power. Crude VE point estimates were under 45% in 2004/05, 2005/06, 2011/12 and 2013/14 season; between 50%-70% in 2006/07, 2008/09 and 2010/11 seasons, and above 70% in 2007/08 and 2012/13 season. From season 2006/07 to 2013/14, all crude VE estimates were statistically significant. After adjustment for age group and month of onset, the VE point estimates decreased and only 2008/09, 2012/13 and 2013/14 seasons were significant. Discussion and Conclusions: MonitorEVA was able to provide VE estimates for all seasons, including the pandemic, indicating if the VE was higher than 70% and less than 50%. When comparing with other observational studies, MonitorEVA estimates were comparable but less precise and VE estimates were in accordance with the antigenic match of the circulating virus/ vaccine strains. Given the sensitivity results, we propose a MonitorEVA based on: a) Vaccination status defined independently of number of days between vaccination and symptoms onset; b) use of all ILI data independent of the definition; c) stratification of VE according to time between onset and swab (< 3 and ≥3 days).