Articles: pandemics.
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Pregnant women and their unborn children are at high risk from both pandemic and seasonal influenza. ⋯ Policy makers need to be cognisant of women's concerns and develop resources for both pregnant women and healthcare workers as part of both future pandemic planning and seasonal vaccination efforts.
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Pediatr. Infect. Dis. J. · May 2019
Priority Needs for Conducting Pandemic-relevant Clinical Research With Children in Europe: A Consensus Study With Pediatric Clinician-researchers.
Infectious disease (ID) pandemics pose a considerable global threat and can disproportionately affect vulnerable populations including children. Pediatric clinical research in pandemics is essential to improve children's healthcare and minimize risks of harm by interventions that lack an adequate evidence base for this population. The unique features of ID pandemics require consideration of special processes to facilitate clinical research. We aimed to obtain consensus on pediatric clinician-researchers' perceptions of the priorities to feasibly conduct clinical pediatric pandemic research in Europe. ⋯ Results suggest that changes need to be made to the current regulatory environment to facilitate and improve pediatric research in the pandemic context. These findings can provide expert evidence to research policy decision-makers and regulators and to develop a strategy to lobby for change.
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Australas Psychiatry · Apr 2019
Comparative StudyNothing to sneeze at - uptake of protective measures against an influenza pandemic by people with schizophrenia: willingness and perceived barriers.
To examine willingness to adopt protective behaviours, and perceived barriers, during a pandemic influenza, in people with schizophrenia. ⋯ People with schizophrenia report being generally willing to adopt protective measures, especially increased hand washing, during a pandemic influenza. Understanding perceived barriers may enable development of effective interventions to increase uptake of protective measures.
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Test-negative (TN) studies have become the most widely used study design for the estimation of influenza vaccine effectiveness (VE) and are easily incorporated into existing influenza surveillance networks. We seek to determine the bias of TN-based VE estimates during a pandemic using a dynamic probability model. The model is used to evaluate and compare the bias of VE estimates under various sources of bias when vaccination occurs after the beginning of an outbreak, such as during a pandemic. ⋯ VE estimates from TN studies were biased regardless of the source of bias present. However, if the core assumption of the TN design is satisfied, that is, if vaccination does not affect the probability of non-influenza ARI, then TN-based VE estimates against medically-attended influenza will only suffer from small (<0.05) to moderate bias (≥0.05 and <0.10). These results suggest that if sources of bias listed above are ruled out, TN studies are a valid study design for the estimation of VE during a pandemic.