View clinical trials related to Influenza.
Filter by:Influenza (influenza for short) is an acute respiratory infectious disease caused by influenza virus. The symptoms of the disease range from mild, moderate to severe, and severe cases require hospitalization and may die. According to estimates by the US Centers for Disease Control and Prevention in 2018, influenza causes approximately 290,000 to 640,000 deaths worldwide each year. Therefore, the prevention and treatment of influenza has become a serious public health problem.
This phase II trial studies the effect of baloxavir in combination with oseltamivir in treating severe influenza infection in patients who have previously received a hematopoietic (blood) stem cell transplant or have a hematological malignancy. Baloxavir is an antiviral drug that inhibits the growth of influenza virus, reduces viral load and prevents further influenza infection. Osetamivir is an antiviral drug that blocks enzymes on the surfaces of influenza viruses, interfering with cell release of complete viral particles. Giving baloxavir in combination with oseltamivir may shorten or decrease the intensity of influenza infection compared to oseltamivir alone.
This was an extensive, double-blind, randomized, placebo-controlled phase 3 study that aimed to evaluate the safety and immunogenicity of the seasonal inactivated, split virion, trivalent influenza vaccine (IVACFLU-S) in children from 6 months to under 18 years old and the elderly over 60 years old in Vietnam. The main target: Evaluating the safety of the single or double dose of seasonal influenza vaccine (IVACFLU-S) in Vietnamese children aged 6 months to 17 years and adults over 60 years old. Evaluating the immunogenicity of the seasonal inactivated, split virion, trivalent influenza vaccine (IVACFLU-S) after 1st injection on day 22 (+7) for groups ≥ 9 years old or day 49 (+7) for groups of 6 months to 8 years for each antigenic component of the vaccine.
The purpose of this study is to evaluate the AFIX-OB model to determine its impact on the change in flu and pertussis (Tdap) uptake, provider knowledge, attitudes and beliefs, and patient knowledge, attitudes and beliefs regarding maternal vaccination. The structure of the model and quality improvement interventions are guided by theory including the elaboration likelihood model and P3 model. These quality improvement measures will be implemented in OB clinics within the Yale New Haven Health System.
The investigators hypothesize that sex, age, area of exposure and purpose of travel are associated with different travel-related infections. The investigators also hypothesize that certain infections will have long-term sequelae. Health-data will be collected from travellers from Switzerland and Europe. The project starts with a pilot study for 50 travellers, followed by the recruiting of 10,000 travellers. The data collection will be via a mobile App (ITIT). The ITIT App will collect active data from travellers. The participants will download the App after signing an electronic consent form and completing a baseline questionnaire. Then the travellers will answer a short daily questionnaire about illness symptoms during travel. The ITIT App will also collect passive data (GPS localisation, environmental and weather data). The project will provide real-time data on travel-related infections and profile travel illness by age, sex and purpose of travel and also identify outbreaks.
This trial is taking place in Los Angeles, CA among patients from primary care practices within the UCLA Health System. The study design is a parallel 2-arm trial. The parallel arms are 1) a reminder letter for the second dose of influenza vaccine (reminder messages sent via the patient portal) with a direct appointment scheduling link included in the reminder and 2) a reminder letter for the second dose of influenza vaccine, but no direct appointment scheduling link included.
Respiratory infections such as colds, flu and pneumonia affect millions of people around the world every year. Most cases are mild, but some people become very unwell. Influenza ('flu') is one of the most common causes of lung infection. Seasonal flu affects between 10% and 46% of the population each year and causes around 12 deaths in every 100,000 people infected. In addition, both influenza and coronaviruses have caused pandemics in recent years, leading to severe disease in many people. Although flu vaccines are available, these need to change every year to overcome rapid changes in the virus and are not completely protective. This study aims to find and develop predictive tests to better understand how and when flu-like illness progresses to more severe disease. This may help to decide which people need to be admitted to hospital, and how their treatment needs to be increased or decreased during infection. The aim is to recruit 100 patients admitted to hospital due to a respiratory infection. It is voluntary to take part and participants can choose to withdraw at any time. The study will involve some blood and nose samples. This will be done on Day 0, Day 2 and Discharge from hospital, and an out-patient follow-up visit on Day 28. The data will be used to develop novel diagnostic tools to assist in rational treatment decisions that will benefit both individual patients and resource allocation. It will also establish research preparedness for upcoming pandemics.
This is a prospective observational study using a mobile study platform (app) that is designed for use on Android phones. Study participants will provide baseline demographic and medical information and report symptoms of respiratory infection on a weekly basis using the app. Participants will also report use of prevention techniques on the weekly survey. Mobility data will be collected passively using the sensors on the participant's smartphone, if the participant has granted the proper device permissions. The overall goals of the study are to track spread of coronavirus-like illness (CLI), influenza-like illness (ILI) and non-specific respiratory illness (NSRI) on a near-real time basis and identify specific behaviors associated with an increased or decreased risk of developing these conditions.
This study examined the etiology of acute respiratory viral infections (ARVI) during the 2015-2016 season, evaluated the statistics of the incidence of influenza and ARVI in this period (epidemiology: severity of the disease and bacterial exacerbations; demographics of patients; duration and timing of treatment; safety; quality of treatment), and evaluated the effectiveness of complex therapy with an emphasis on the using of interferon inducers in hospitalized children aged 3 to 11 years.
This study evaluates the use of Kagocel for the prevention of acute respiratory viral infections (ARVI) and influenza during the epidemic rise in the incidence of diseases in Russia in 2018 (epidemiology: the number of cases during the period of Kagocel administration and follow-up, bacterial exacerbations, the number of repeated episodes (reinfection), demographics of patients, safety, adherence to treatment) in students at risk due to stress, lack of sleep and fatigue.