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Valcic, Miroslav, e Sonja Radojicic. "Influenza - flu". Veterinarski glasnik 64, n.º 1-2 (2010): 109–25. http://dx.doi.org/10.2298/vetgl1002109v.
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In epidemiology or in epizootiology, there are some infectious diseases that have potential for significant reduction of the susceptible species population. Over the past few decades, epidemiologists were concentrated on diseases that were 'modern' and made front-page news in tabloids. One should recall diseases like bovine spongiform encephalopathy, SARS and AIDS syndromes. However, we should always be aware of the most dangerous diseases such as our old friend, influenza, or simply, flu. In the past decade, we heard about 'bird' or 'swine' influenza. It is the same disease for different animal species as well as for man. Influenza owes its characteristics to specific virus biology as well as to the epidemiology-epizootiology characteristics of the susceptible species. Antigenic changes that took place thanks to reassortment mechanisms of the viral gene segments cause the onset of the new antigenic combinations of the hemaglutinin and neuraminidase molecules. As a result, new H and/or N antigenic formulas appear for the first time in totally susceptible animal and human populations. That means that in such circumstances, no person in the world is immune to the virus. In that case, such a virus can cause a pandemic with disastrous consequences since influenza is a disease with significant mortality, especially in some segments of the human (as well as animal) population. Birds and swine are virus reservoirs, but these species are at the same time live test tubes in which the virus resides, changes and adapts itself not only to the original species but to other species as well. That means that there is no 'bird' or 'swine' flu. Influenza is an infection of several important animal species as well as man that have potential not only for the reduction of the population size but, in case of the human population, for influencing social and economic life. .
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&NA;. "Influenza (“the flu”)". Nursing 37, n.º 10 (outubro de 2007): 47. http://dx.doi.org/10.1097/01.nurse.0000291990.47055.4c.
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Keilman, Linda J. "Seasonal Influenza (Flu)". Nursing Clinics of North America 54, n.º 2 (junho de 2019): 227–43. http://dx.doi.org/10.1016/j.cnur.2019.02.009.
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Mondal, Pritish, Ankita Sinharoy e Suparna Gope. "The Influence of COVID-19 on Influenza and Respiratory Syncytial Virus Activities". Infectious Disease Reports 14, n.º 1 (14 de fevereiro de 2022): 134–41. http://dx.doi.org/10.3390/idr14010017.
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Background: Respiratory viral diseases have considerably declined since the COVID-19 outbreak, perhaps through influence by nonpharmaceutical interventions. We conducted a cross-sectional study using the CDC database to compare the pre- vs. post-pandemic flu activity (incidence) between the US states. Our secondary objectives were to estimate the association between flu activity and flu vaccination rates and compare the national trends of flu and RSV activities since the pandemic outbreak. Methods: We estimated the difference between pre-pandemic (April 2019–March 2020) and post-pandemic (April 2020–March 2021) flu activity between individual states using the Wilcoxon signed-rank test. The association between flu activity and immunization rates was also measured. Finally, parallel time trend graphs for flu and RSV activities were illustrated with a time series modeler. Results: The median (IQR) pre-pandemic flu activity was 4.10 (1.38), higher than the post-pandemic activity (1.38 (0.71)) (p-value < 0.001). There was no difference between pre-pandemic (45.50% (39.10%)) and post-pandemic (45.0% (19.84%)) flu vaccine acceptance (p-value > 0.05). Flu activity and vaccination rates were not associated (p-value > 0.05). Flu activity has declined since the COVID-19 outbreak, while RSV made a strong comeback in June 2021. Conclusion: Flu activity has significantly diminished throughout the pandemic while a sudden upsurge in RSV is a public health concern indicative of possible resurgence of other viruses. Flu vaccine acceptance neither changed during the pandemic nor influenced the diminished Flu activity.
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Juozapaitis, Mindaugas, e Linas Antoniukas. "Influenza virus". Medicina 43, n.º 12 (8 de dezembro de 2007): 919. http://dx.doi.org/10.3390/medicina43120119.
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Every year, especially during the cold season, many people catch an acute respiratory disease, namely flu. It is easy to catch this disease; therefore, it spreads very rapidly and often becomes an epidemic or a global pandemic. Airway inflammation and other body ailments, which form in a very short period, torment the patient several weeks. After that, the symptoms of the disease usually disappear as quickly as they emerged. The great epidemics of flu have rather unique characteristics; therefore, it is possible to identify descriptions of such epidemics in historic sources. Already in the 4th century BC, Hippocrates himself wrote about one of them. It is known now that flu epidemics emerge rather frequently, but there are no regular intervals between those events. The epidemics can differ in their consequences, but usually they cause an increased mortality of elderly people. The great flu epidemics of the last century took millions of human lives. In 1918–19, during “The Spanish” pandemic of flu, there were around 40–50 millions of deaths all over the world; “Pandemic of Asia” in 1957 took up to one million lives, etc. Influenza virus can cause various disorders of the respiratory system: from mild inflammations of upper airways to acute pneumonia that finally results in the patient’s death. Scientist Richard E. Shope, who investigated swine flu in 1920, had a suspicion that the cause of this disease might be a virus. Already in 1933, scientists from the National Institute for Medical Research in London – Wilson Smith, Sir Christopher Andrewes, and Sir Patrick Laidlaw – for the first time isolated the virus, which caused human flu. Then scientific community started the exhaustive research of influenza virus, and the great interest in this virus and its unique features is still active even today.
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Wang, Dina, Hao Lei, Dayan Wang, Yuelong Shu e Shenglan Xiao. "Association between Temperature and Influenza Activity across Different Regions of China during 2010–2017". Viruses 15, n.º 3 (21 de fevereiro de 2023): 594. http://dx.doi.org/10.3390/v15030594.
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Influenza causes a significant disease burden as an acute respiratory infection. Evidence suggests that meteorological factors can influence the spread of influenza; however, the association between these factors and influenza activity remains controversial. In this study, we investigated the impact of temperature on influenza across different regions of China based on the meteorological data and influenza data from 554 sentinel hospitals in 30 provinces and municipalities in China from 2010 to 2017. A distributed lag nonlinear model (DLNM) was used to analyze the exposure lag response of daily mean temperatures to the risk of influenza-like illness (ILI), influenza A (Flu A), and influenza B (Flu B). We found that in northern China, low temperatures increased the risk of ILI, Flu A, and Flu B, while in central and southern China, both low and high temperatures increased the risk of ILI and Flu A, and only low temperatures increased the risk of Flu B. This study suggests that temperature is closely associated with the influenza activity in China. Temperature should be integrated into the current public health surveillance system for highly accurate influenza warnings and the timely implementation of disease prevention and control measures.
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Lucas, GN. "Avian influenza (Bird flu)". Sri Lanka Journal of Child Health 35, n.º 2 (23 de setembro de 2008): 43. http://dx.doi.org/10.4038/sljch.v35i2.11.
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&NA;. "Influenza vaccine prevents flu". Inpharma Weekly &NA;, n.º 1222 (janeiro de 2000): 10. http://dx.doi.org/10.2165/00128413-200012220-00022.
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&NA;. "Seasonal influenza (the flu)". Nursing 40, n.º 9 (setembro de 2010): 33. http://dx.doi.org/10.1097/01.nurse.0000387238.05776.38.
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Fogel, Benjamin N., e Steven D. Hicks. "“Flu-Floppers”: Factors Influencing Families’ Fickle Flu Vaccination Patterns". Clinical Pediatrics 59, n.º 4-5 (22 de janeiro de 2020): 352–59. http://dx.doi.org/10.1177/0009922819901002.
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While influenza vaccination in the prior year is a strong predictor of subsequent vaccination, many families do not have static vaccination patterns. This study examined factors guiding influenza vaccination decisions among parents whose children sporadically received the influenza vaccination (flu-floppers). We administered surveys to 141 flu-flopper families. Surveys included 21 factors associated with vaccine decision making. A conceptual framework of “passive” and “active” decision making was used to assess parental motivators behind vaccine decisions. The most common reason for vaccinating was a desire to prevent influenza (45%). The most common reason for not vaccinating was a belief that influenza vaccination is not effective (29%). Most parents (88%) reported an active reason in years when their child was vaccinated, while only 43% reported an active reason when their child was not vaccinated ( P < .00001). These findings may guide efforts to increase influenza vaccination rates in children most amenable to vaccination.
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Simon, Chantal. "Influenza". InnovAiT: Education and inspiration for general practice 7, n.º 10 (27 de agosto de 2014): 616–23. http://dx.doi.org/10.1177/1755738014546537.
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Influenza (or flu) is an acute infection of the respiratory tract that causes sporadic respiratory illness, usually during Autumn and Winter. In the UK, it is responsible for at least 100 deaths a year, with epidemics every 2 to 3 years leading to a 10-fold increase in deaths, and pandemics every 30–40 years killing many more. This article aims to provide an overview of influenza for GPs involved in the management of flu, from prevention, to diagnosis and management of the acute illness in the community.
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Wahyutomo, Ridha, V. Rizke Ciptaningtyas e Purnomo Hadi. "Prevalence of Influenza Viruses (Influenza Like Illness) In Regional Laboratory Avian Influenza Semarang". Sains Medika : Jurnal Kedokteran dan Kesehatan 3, n.º 2 (17 de dezembro de 2011): 157. http://dx.doi.org/10.30659/sainsmed.v3i2.398.
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Background: Influenza is the major health threat worldwide causing illness and death every year. However, data on the epidemiology of influenza in tropical countries, including Indonesia, are still limited. Up dated data for its prevalence is needed to monitor its spreading and to evaluate its outbreak. Therefore a working regional laboratory in surveillance of ILI (Influenza Like Illness) was formed. This research was conducted to provide updated data on prevalence of ILI in regional laboratorium avian influenza Semarang.Design and Method: Data from patients examined in the regional laboratory of avian influenza Semarang from April 2009 until December 2010 was collected. Samples were obtained from Malang sentinel, Yogyakarta sentinel and Semarang sentinel. Samples were examined using PCR to detect influenza A, influenza B, and swine flu.Result: out 1367 patients tested, 279 patients (20.41%) were from Yogyakarta sentinel, 619 patients (45.28%) were from Malang sentinel, and 467 patients (34.16%) were from Semarang sentinel. Flu A virus was detected in 117 patients (8.5%). Influenza B virus was found in 39 patients (2.8%). H1 virus was detected in 5 patients (0.36%). H3 virus was detected in 45 patients (3.29%). Swine flu virus was detected in 3 patients in Malang.Conclusion: The highest prevalence of flu A and flu B examined in avian influenza regional laboratory Semarang was from Semarang sentinel, followed by Yogyakarta sentinel and Malang (Sains Medika, 3(2):157-161).
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Sandhu, Avnish, Jordan Polistico, Ashwin Ganesan, Erin Goldman, Jennifer LeRose e Teena Chopra. "Rapid PCR Influenza Testing Decreases Inappropriate Empiric Antibiotic Use". Infection Control & Hospital Epidemiology 41, S1 (outubro de 2020): s366. http://dx.doi.org/10.1017/ice.2020.991.
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Background: The clinical picture of influenza-like illness can mimic bacterial pneumonia, and empiric treatment is often initiated with antibacterial agents. Molecular testing such as polymerase chain reaction (PCR) is often used to diagnose influenza. However, traditional PCR tests have a slow turnaround time and cannot deliver results soon enough to influence the clinical decision making. The Detroit Medical Center (DMC) implemented the Xpert Flu test for all patients presenting with influenza-like illness (ILI). We evaluated antibacterial use after implementation of rapid influenza PCR Xpert Flu. Methods: We conducted a retrospective study comparing all pediatric and adult patients tested using traditional RT PCR during the 2017–2018 flu season to patients tested using the rapid influenza Xpert Flu during the 2018–2019 flu season in a tertiary-care hospital in Detroit, Michigan. These patients were further divided into 3 groups: not admitted (NA), admitted to acute-care floor (ACF), or admitted to intensive care unit (ICU). The groups were then compared with respect to percentage of antibacterial use after traditional RT PCR versus rapid influenza Xpert Flu testing during their hospital visit for ILI. The χ2 test was used for statistical analyses. Results: In total, 20,923 patients presented with influenza-like illness during the study period: 26% (n = 5,569) had the rapid influenza Xpert Flu and 73.4% (n= 15,354) had traditional RT PCR. For a comparison of the number of patients in 3 groups (NA, ACF, and ICU) and type of influenza PCR performed among these patients, please refer to Table 1. When comparing antibacterial use in the NA group, the proportions of patients who received antibacterial agents in the traditional RT PCR group versus the rapid influenza Xpert Flu group were 24.4% (n = 695) versus 3.9% (n = 450), respectively (P < .0001). In the ACF group, the proportions of patients who received antibacterial agents in the traditional RT PCR group versus the rapid influenza Xpert Flu group was 62.3% (n = 1,406) versus 27.7% (n = 994), respectively (P < .001). In the ICU group, the proportions of patients who received antibacterials in the traditional RT PCR group versus the rapid influenza Xpert Flu group were 80.3% (n = 382) versus 38.3% (n = 204), respectively (P < .0001). Conclusions: With rising antimicrobial resistance and increasing influenza morbidity and mortality, rapid diagnostics not only can help diagnose influenza faster but also can reduce inappropriate antimicrobial use.Funding: NoneDisclosures: None
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Bianchi, Roberto, e Giovanni Gozzini. "Glocal Spanish Influenza". PASSATO E PRESENTE 42, n.º 122 (maio de 2024): 5–6. http://dx.doi.org/10.3280/pass2024-122001.
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In order to understand the dimensions and consequences of the Spanish flu, the great influenza pandemic of 1918-1920, it is necessary to carry out analytical research at the local and regional level, in order to compare the results with similar research carried out in other national and international contexts. The Glocal Spanish Influenza project focuses on the case of Tuscany and aims to reconstruct both the number of deaths and the number of sick peoplemortality and morbidity figures, as well as the institutional responses to the crisis, the political consequences, collec- tive behaviour, memories and displacements. Here we present two contributions by Roberto Bianchi, who compares the Spanish flu and Covid-19, and by Giovanni Gozzini, who analyses the numbers of the Spanish flu.
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Polistico, Jordan, Avnish Sandhu, Teena Chopra, Erin Goldman, Jennifer LeRose e Ashwin Ganesan. "Impact of Rapid PCR Influenza Testing on the Rate of Inpatient Admissions During Influenza Season at a Tertiary-Care Center". Infection Control & Hospital Epidemiology 41, S1 (outubro de 2020): s263—s264. http://dx.doi.org/10.1017/ice.2020.830.
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Background: Influenza causes a high burden of disease in the United States, with an estimate of 960,000 hospitalizations in the 2017–2018 flu season. Traditional flu diagnostic polymerase chain reaction (PCR) tests have a longer (24 hours or more) turnaround time that may lead to an increase in unnecessary inpatient admissions during peak influenza season. A new point-of-care rapid PCR assays, Xpert Flu, is an FDA-approved PCR test that has a significant decrease in turnaround time (2 hours). The present study sought to understand the impact of implementing a new Xpert Flu test on the rate of inpatient admissions. Methods: A retrospective study was conducted to compare rates of inpatient admissions in patients tested with traditional flu PCR during the 2017–2018 flu season and the rapid flu PCR during the 2018–2019 flu season in a tertiary-care center in greater Detroit area. The center has 1 pediatric hospital (hospital A) and 3 adult hospitals (hospital B, C, D). Patients with influenza-like illness who presented to all 4 hospitals during 2 consecutive influenza seasons were analyzed. Results: In total, 20,923 patients were tested with either the rapid flu PCR or the traditional flu PCR. Among these, 14,124 patients (67.2%) were discharged from the emergency department and 6,844 (32.7%) were admitted. There was a significant decrease in inpatient admissions in the traditional flu PCR group compared to the rapid flu PCR group across all hospitals (49.56% vs 26.6% respectively; P < .001). As expected, a significant proportion of influenza testing was performed in the pediatric hospital, 10,513 (50.2%). A greater reduction (30% decrease in the rapid flu PCR group compared to the traditional flu PCR group) was observed in inpatient admissions in the pediatric hospital (Table 1) Conclusions: Rapid molecular influenza testing can significantly decrease inpatient admissions in a busy tertiary-care hospital, which can indirectly lead to improved patient quality with easy bed availability and less time spent in a private room with droplet precautions. Last but not the least, this testing method can certainly lead to lower healthcare costs.Funding: NoneDisclosures: None
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SHEKHAR, CHANDRA. "Swine flu (Influenza A/H1N1)". VETERINARY SCIENCE RESEARCH JOURNAL 6, n.º 2 (15 de outubro de 2015): 113–21. http://dx.doi.org/10.15740/has/vsrj/6.2/113-121.
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Lewis, David B. "Avian Flu to Human Influenza". Annual Review of Medicine 57, n.º 1 (fevereiro de 2006): 139–54. http://dx.doi.org/10.1146/annurev.med.57.121304.131333.
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Fleming, Douglas. "Influenza pandemics and avian flu". BMJ 331, n.º 7524 (3 de novembro de 2005): 1066–69. http://dx.doi.org/10.1136/bmj.331.7524.1066.
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Lucas, Gerard Nimal. "Novel Influenza AH1N1 (Swine Flu)". Sri Lanka Journal of Child Health 38, n.º 3 (2 de setembro de 2009): 83. http://dx.doi.org/10.4038/sljch.v38i3.1005.
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Sebastian, Meghna R., Rakesh Lodha e S. K. Kabra. "Swine origin influenza (swine flu)". Indian Journal of Pediatrics 76, n.º 8 (agosto de 2009): 833–41. http://dx.doi.org/10.1007/s12098-009-0170-6.
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Santibanez, Tammy A., Anup Srivastav, Yusheng Zhai e James A. Singleton. "Trends in Childhood Influenza Vaccination Coverage, United States, 2012-2019". Public Health Reports 135, n.º 5 (12 de agosto de 2020): 640–49. http://dx.doi.org/10.1177/0033354920944867.
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Objective The objective was to compare estimates of childhood influenza vaccination across 7 consecutive influenza seasons based on 2 survey systems. Methods We analyzed data from the National Health Interview Survey (NHIS) and the National Immunization Survey–Flu (NIS-Flu) using Kaplan-Meier survival analysis to estimate receipt, based on parental report, of at least 1 dose of influenza vaccine among children aged 6 months to 17 years. Results We found no significant increasing trend in influenza vaccination coverage among children overall from 2012 to 2018 based on the NHIS or from 2012 to 2019 based on the NIS-Flu. We found 4 seasons with a significant increase in influenza vaccination coverage compared with the previous season (2012-2013 [NHIS, NIS-Flu], 2013-2014 [NIS-Flu], 2017-2018 [NHIS], and 2018-2019 [NIS-Flu]). As of the 2018-2019 season, based on NIS-Flu, influenza vaccination coverage was only 62.6%. Children with health conditions that put them at increased risk for complications from influenza had higher influenza vaccination coverage than children without these health conditions for all the seasons studied except 2014-2015. For all seasons studied, influenza vaccination coverage estimates for children were higher based on NIS-Flu data compared with NHIS data. Trends across seasons and differences in vaccination coverage between age groups were similar between the 2 surveys. Conclusions Influenza vaccination coverage among children appears to have plateaued. Only about half of the children in the United States were vaccinated against influenza. Improvements in measurement of influenza vaccination and development and review of strategies to increase childhood influenza vaccination coverage are needed.
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Popowitch, Elena B., e Melissa B. Miller. "Performance Characteristics of Xpert Flu/RSV XC Assay". Journal of Clinical Microbiology 53, n.º 8 (27 de maio de 2015): 2720–21. http://dx.doi.org/10.1128/jcm.00972-15.
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The Xpert Flu/RSV XC assay was compared to laboratory-developed tests (LDTs) ( n = 207) and the Xpert Flu assay ( n = 147) using archived nasopharyngeal swabs. The percentages of positive agreements with LDTs were 97.8% for influenza A, 97.2% for influenza B, and 89.3% for RSV. The sensitivity of influenza detection was improved with the Xpert Flu/RSV XC assay compared to the Xpert Flu assay.
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Vanderven, Hillary A., Kathleen Wragg, Fernanda Ana-Sosa-Batiz, Anne B. Kristensen, Sinthujan Jegaskanda, Adam K. Wheatley, Deborah Wentworth et al. "Anti-Influenza Hyperimmune Immunoglobulin Enhances Fc-Functional Antibody Immunity During Human Influenza Infection". Journal of Infectious Diseases 218, n.º 9 (31 de maio de 2018): 1383–93. http://dx.doi.org/10.1093/infdis/jiy328.
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Anti-influenza hyperimmune immunoglobulin (Flu-IVIG) generally contained higher concentrations of influenza-specific Fc-functional antibodies than standard intravenous immunoglobulins against an array of influenza virus strains and subtypes. Passive infusion of Flu-IVIG into influenza-infected patients transiently boosted Fc-functional antibodies early after infusion.
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Wahrenbrock, Mark G., Scott Matushek, Sue Boonlayangoor, Vera Tesic, Kathleen G. Beavis e Angella Charnot-Katsikas. "Comparison of Cepheid Xpert Flu/RSV XC and BioFire FilmArray for Detection of Influenza A, Influenza B, and Respiratory Syncytial Virus: TABLE 1". Journal of Clinical Microbiology 54, n.º 7 (20 de abril de 2016): 1902–3. http://dx.doi.org/10.1128/jcm.00084-16.
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The Xpert Flu/RSV XC was compared to the FilmArray respiratory panel for detection of influenza (Flu) A, Flu B, and respiratory syncytial virus (RSV), using 128 nasopharyngeal swabs. Positive agreements were 100% for Flu A and RSV and 92.3% for Flu B. The Xpert may be useful in clinical situations when extensive testing is not required and may serve an important role in laboratories already performing broader respiratory panel testing.
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Preis, Tobias, e Helen Susannah Moat. "Adaptive nowcasting of influenza outbreaks using Google searches". Royal Society Open Science 1, n.º 2 (outubro de 2014): 140095. http://dx.doi.org/10.1098/rsos.140095.
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Seasonal influenza outbreaks and pandemics of new strains of the influenza virus affect humans around the globe. However, traditional systems for measuring the spread of flu infections deliver results with one or two weeks delay. Recent research suggests that data on queries made to the search engine Google can be used to address this problem, providing real-time estimates of levels of influenza-like illness in a population. Others have however argued that equally good estimates of current flu levels can be forecast using historic flu measurements. Here, we build dynamic ‘nowcasting’ models; in other words, forecasting models that estimate current levels of influenza, before the release of official data one week later. We find that when using Google Flu Trends data in combination with historic flu levels, the mean absolute error (MAE) of in-sample ‘nowcasts’ can be significantly reduced by 14.4%, compared with a baseline model that uses historic data on flu levels only. We further demonstrate that the MAE of out-of-sample nowcasts can also be significantly reduced by between 16.0% and 52.7%, depending on the length of the sliding training interval. We conclude that, using adaptive models, Google Flu Trends data can indeed be used to improve real-time influenza monitoring, even when official reports of flu infections are available with only one week's delay.
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Zhdanov, K. V., K. Kasyanenko, O. V. Mal'cev, N. I. L'vov, D. A. Lioznov, I. I. Lapikov e K. S. Ivanov. "Evaluation of Seasonal Inactivated Influenza Vaccines Prophylactic Efficacy". Epidemiology and Vaccinal Prevention 21, n.º 5 (19 de novembro de 2022): 98–106. http://dx.doi.org/10.31631/2073-3046-2022-21-5-98-106.
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Relevance. Seasonal flu vaccination is still the most effective way to protect against flu viruses and help to reduce the burden of flu illnesses. Another possible benefit is the impact of yearly vaccines on severity of breakthrough infection. In this regard, the issue of choosing safe vaccine with high immunogenicity becomes relevant.Aims. To evaluate the prophylactic efficacy of inactivated seasonal flu vaccines (quadrivalent subunit vaccine with adjuvant and trivalent vaccine) and reactogenicity of quadrivalent vaccine.Materials and methods. 491 cases were included in our study: 152 cases received adjuvanted quadrivalent subunit flu vaccine «Grippol Quadrivalent», 118 cases received trivalent inactivated flu vaccine and 221 cases who have received no vaccinations during 2018–2019 epidemic season.Results. inactivated vaccines showed high prophylactic efficacy in preventing seasonal influenza. Incidence of influenza and other viral respiratory disease cases was lowest in «Grippol Quadrivalent» group. Breakthrough influenza cases in individuals vaccinated with inactivated vaccine were predominantly mild, no severe cases were reported. The early post-vaccination period in «Grippol Quadrivalent» group showed no variation in adverse events with other vaccines.Conclusion. Adjuvanted quadrivalent subunit flu vaccine was the most efficacious in preventing influenza in 2018–2019 epidemic season.
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Popov, A. F., e O. I. Kiselev. "FLU IN PREGNANT WOMEN". Epidemiology and Infectious Diseases 18, n.º 3 (15 de junho de 2013): 40–43. http://dx.doi.org/10.17816/eid40731.
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It is shown that in addition to increased susceptibility in pregnant women to influenza virus in them more often severe and complicated forms of the infection are recorded. The frequency of mortality from influenza, complicated by pneumonia, in the mothers during the pandemic period in 2009 was 2.5% and perinatal loss amounted to 8.3%. There are presented data on the relationship of the disease of pregnant women with influenza with developmental malformations in their offsprings. Obstetric tactic is determined individually for each pregnant depending on the period of parturition. Antiviral therapy of influenza A (H1N1) pdm09 in pregnant with arbidol drugs, oseltamivir, viferon reduced the rate of preterm labors, congenital pneumonia and cerebral ischemia in newborns. The main methods of preventing influenza is vaccination, which is allowed from the II trimester of gestation. Post-exposure antiviral chemoprophylaxis in pregnants is expedient to perform with zanamivir. There are listed all the errors in the management of pregnant women with influenza, which significantly reduced the effectiveness of treatment and increased incidence of adverse outcomes.
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Raza, Sania, Muhammad Usman e Imran Ahmad. "Seasonal trends of Influenza in Islamabad, Pakistan". Journal of Islamabad Medical & Dental College 10, n.º 1 (31 de março de 2021): 318–22. http://dx.doi.org/10.35787/jimdc.v10i1.549.
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Background: Viral outbreaks have always been a challenging task for clinicians and Influenza virus has been on top of the list. The history of influenza epidemic reveals its devastating effects in the form of multiple deaths and economic burden. Hence this study was planned to recognize the peak activity time span of Influenza infection and its frequency in our set-up at Shifa International Hospital, Islamabad Pakistan.
Material and Methods: A cross sectional study was performed in Pathology Laboratory, Shifa international hospital Islamabad from April 2016 to March 2019. Nasopharyngeal swabs were collected from patients of all age groups, with clinically suspected influenza infection throughout the year, irrespective of gender, according to hospital’s standard policy. Samples were analysed on GeneXpert kit (Xpert Flu Assay). Data collected was entered and then analysed in SPSS version 17.
Results: Of the total 591 samples included in study, 233 (39.4%) were positive for influenza (Flu A or Flu B), while 358 (60.6%) showed negative results. Total 172 (73.8%) were positive for Flu A while 61 (26.1%) were positive for Flu B. Among Flu A cases, 107 (62.2%) were positive for H1N1. Most of the positive cases (n=206; 88.4%) were reported in the months of January and February during the three-year period (2016-2019) of this study.
Conclusions: Influenza virus has peak activity in the months of January and February. Both Influenza A and B are circulating in the environment but Flu A is predominant and H1N1 is more prevalent.
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Campbell, Melissa, Amber James, Iyanna Fairweather, Jose Rivera-Vinas, Richard Kaslow, Marie-Louise Landry, David Peaper e Richard Martinello. "Outcomes of Patients With Hospital-Acquired Influenza". Infection Control & Hospital Epidemiology 41, S1 (outubro de 2020): s340. http://dx.doi.org/10.1017/ice.2020.951.
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Background: Hospital-acquired influenza (HA flu) lacks a consensus definition. However, it is known to be associated with increased inpatient morbidity and mortality. Objective: To describe the clinical course of HA flu in a cohort population. Methods: A retrospective cohort study was conducted at a tertiary-care adult and pediatric teaching hospital. Patients with HA flu during 3 seasons, 2016 through 2019, were identified from medical record information based on timing of the onset of signs and symptoms and positive virologic testing >72 hours after admission. Influenza infection was confirmed by multiplex respiratory PCR, influenza A/B PCR, or direct fluorescent antibody tests. Chart review was performed to abstract patient demographics and comorbidities, length of stay, testing, and timing to antiviral administration as well as diagnosis of pneumonia, coinfections, and 30-day mortality. Escalation of care during hospitalization was defined as a new requirement of supplemental oxygen, invasive or noninvasive ventilation, and transfer to an intensive care unit. Results: During the 3 flu seasons, 132 patients were identified with HA flu; 76 (58%) were women, 6 (4.6%) were aged <18 years, and 126 (95.4%) were adults. Annually, HA-flu patients accounted for 5%–7.8% of all patients hospitalized with laboratory-proven influenza. The median duration between hospitalization and positive flu test was 15 days, and the median length of stay after influenza diagnosis was 6 days. Antiviral treatment was received by 96% of the patients. In total, 41 patients (31%) showed radiographic evidence for pneumonia. Coinfection with either a viral or bacterial pathogen was identified in 25% of the cases. In addition, 26% of the patients experienced an escalation of care, and 20 patients (15%) were transferred to the intensive care unit after HA flu diagnosis. Furthermore, 4 deaths (3%) were attributed to influenza during their hospitalization. Conclusions: HA flu was a frequent cause for escalation in care and was associated with a mortality rate substantially higher than is typically seen in community-based populations with influenza. Coinfection was mostly related to bacteremia and pneumonia, yet not all pneumonias had an associated microbiological diagnosis other than influenza, and there was no significant association between coinfection and mortality. Future work should explore more precise definitions for HA flu as well as its complications.Funding: NoneDisclosures: None
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Queljoe, Jean F. de, F. Y. Rumlawang e L. J. Sinay. "ANALISIS KESTABILAN TERHADAP PENYEBARAN PENYAKIT FLU BURUNG (AVIAN INFLUENZA)". PARAMETER: Jurnal Matematika, Statistika dan Terapannya 1, n.º 1 (21 de novembro de 2022): 35–50. http://dx.doi.org/10.30598/parameterv1i1pp35-50.
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Flu burung atau dikenal dengan istilah avian flu atau Avian Influenza (AI) adalah penyakit menular yang disebabkan oleh virus influenza tipe A dengan diameter 90-120 nanometer. Model matematika mengenai penyebaran penyakit (model epidemi) adalah metode yang tepat untuk mempresentasikan pola penyebaran penyakit flu burung dari unggas ke manusia. Model dasar epidemi dikenal dengan SIR. Dari pembahasan diperoleh model dua titik kesetimbangan yaitu titik kesetimbangan bebas penyakit dan titik kesetimbangan endemik. Berdasarkan analisis yang dilakukan diperoleh , sehingga jika maka titik kesetimbangan endemik stabil atau penyakit flu burung akan menghilang dan jika maka titik kesetimbangan bebas penyakit stabil atau penyakit flu burung akan menghilang. Dalam penelitian ini digunakan software Maple untuk proses simulasi numerik.
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Nordin, Musa Mohd. "Influenza – Beyond Respiratory Illness". International Journal of Human and Health Sciences (IJHHS) 7, n.º 70 (22 de janeiro de 2023): 9. http://dx.doi.org/10.31344/ijhhs.v7i70.512.
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Annual epidemics of seasonal influenza cause hundreds of thousands of deaths, high levels of morbidity, and substantial economic loss.Global influenza circulation has been heavily suppressed by public health measures and travel restrictions during COVID-19 pandemic. As many countries are now transitioning to COVID-19 endemic state, restrictions have been loosened or been lifted entirely, creating an opening for influenza and other respiratory viruses. As such, many more people might catch the flu and potentially be at risk of serious illness. Although influenza is primarily considered a respiratory infection and causes significant respiratory mortality, evidence suggests that influenza has an additional burden due to broader consequences of the illness. Some of these broader consequences include cardiovascular events, exacerbations of chronic underlying conditions, increased susceptibility to secondary bacterial infections, functional decline, and poor pregnancy outcomes, all of which may lead to an increased risk for hospitalization and death. Flu vaccination could be more important than ever now, both to protect those most at risk, as well as to protect health systems that are already under pressure due to COVID-19. The World Health Organization (WHO) and the Centers for Disease Control (CDC) recommends that almost everyone aged 6 months and older get a seasonal flu vaccine each year. Flu vaccines are updated each season to keep up with changing viruses. Also, immunity wanes over a year so annual vaccination is needed to ensure the best possible protection against the flu. Despite health authorities’ recommendation, many at-risk adults are not aware of the impact of influenza and the importance of prevention. Healthcare provider’s recommendation can make a difference. Clinicians are the most valued and trusted source of health information for adults. CDC recommended a systematic communication to help patients make an informed decision about vaccinations. International Journal of Human and Health Sciences Supplementary Issue: 2023 Page: S9
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Sani, Tommaso, Ilaria Morelli, Donatella Sarti, Giovanni Tassinari, Maria Capalbo, Emma Espinosa, Beatrice Gasperini e Emilia Prospero. "Attitudes of Healthcare Workers toward Influenza Vaccination in the COVID-19 Era". Vaccines 10, n.º 6 (31 de maio de 2022): 883. http://dx.doi.org/10.3390/vaccines10060883.
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Healthcare workers (HCWs) are reluctant to participate in the influenza vaccination program, despite their high risk to contract and diffuse influenza due to professional exposure. The onset of the COVID-19 pandemic could raise HCW flu vaccination adherence. The aim of this study was to assess HCW attitudes toward influenza vaccination in the COVID-19 era. A multicenter observational study was carried out in three Italian hospitals (two in Pesaro and one in Fano, Marche region, Italy). Data about HCW influenza vaccination between 2013 and 2021 were extracted from the vaccination registers. An online questionnaire was sent to HCWs from July to October 2020 to assess their opinion about influenza vaccination in terms of knowledge, attitude, and practice during the COVID-19 pandemic. The number of flu-vaccinated HCWs increased from 3.7% in the 2013–2014 flu season to 53.6% in the 2020–2021 flu season (p < 0.001). About 15% (n = 324) of HCWs responded to the online questionnaire, and 30.5% of them declared that they had changed their minds on flu vaccination after the COVID-19 pandemic, deciding to get vaccinated. The COVID-19 pandemic significantly increased HCWs’ attitudes toward flu vaccination. However, flu vaccination adherence remained low and should be improved.
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Galar, Alicia, Lourdes Vicent, Iago Sousa-Casasnovas, Maricela Valerio, Miriam Juárez, Pilar Catalán, Carolina Devesa-Cordero et al. "1784. The Value of a Systematic Screening of Influenza Virus and Vaccination on Emergent Admissions to a Cardiac Intensive Care Unit (C-ICU)". Open Forum Infectious Diseases 6, Supplement_2 (outubro de 2019): S657. http://dx.doi.org/10.1093/ofid/ofz360.1647.
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Abstract Background Influenza is a potential inducer of acute cardiac events. However, the incidence of influenza in patients admitted to a C-ICU, the accuracy of clinical suspicion and the compliance of influenza vaccination of high-risk patients, are not well known. Objectives: To evaluate the incidence of influenza at C-ICU admission during influenza season, the potential underdiagnosis and the vaccination rate. Methods Prospective study at a tertiary institution including all patients admitted to a C-ICU during 2017–2018 flu season. A nasopharyngeal swab was collected at admission from all patients who consented (198/201, 98.5%) and tested using Xpert® Flu/RSV assay. Clinical data were registered. Results Influenza was detected in 14/198 (7.1%) patients (11 FluA, 3 FluB) and initially suspected by the cardiologist in 57.1% cases. When compared with patients without influenza, flu-positive patients had more respiratory (21.4% vs. 6.0%, P = 0.03) or neurologic diseases (21.4% vs. 4.3%, P < 0.01), contact with relatives with flu-like illnesses (35.7% vs. 14.4%, P = 0.03), antimicrobials use (71.4% vs. 36.4%, P = 0.01) and need for mechanical ventilation (28.6% vs. 3.3%, P < 0.01). Reasons for C-ICU admission between both groups were similar. All patients promptly received oseltamivir and no patient with flu died (0 vs. 3.8%, P = 0.46) despite a high rate of severe presentations (85.7%) and related complications (78.6%). Seasonal flu vaccination was received by 44.9% of the patients admitted to the C-ICU and 52.0% of patients who had indication for flu vaccination. The incidence of influenza in the vaccinated and non-vaccinated population (with flu vaccine indication) was, respectively 12.6% vs. 4.1% (P = 0.08). Flu episodes in vaccinated patients required less mechanical ventilation (20% vs. 75%, P = 0.05) and showed a trend toward shorter length of in-hospital stay (6 vs. 15d, NS). Risks factors for no vaccination despite indication were: younger age (67 vs. 75y-o, P < 0.05) and less comorbidity (Charlson index 4 vs. 5, P < 0.01). Conclusion Seven percent of patients admitted to the C-ICU had influenza, only half of the influenza cases diagnosed were suspected at admission and only half of the patients with indication for flu vaccination, received the vaccine. A clinical score to recognize influenza in these patients is needed. Disclosures All authors: No reported disclosures.
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Wang, Yufang, Kuai Xu, Yun Kang, Haiyan Wang, Feng Wang e Adrian Avram. "Regional Influenza Prediction with Sampling Twitter Data and PDE Model". International Journal of Environmental Research and Public Health 17, n.º 3 (21 de janeiro de 2020): 678. http://dx.doi.org/10.3390/ijerph17030678.
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The large volume of geotagged Twitter streaming data on flu epidemics provides chances for researchers to explore, model, and predict the trends of flu cases in a timely manner. However, the explosive growth of data from social media makes data sampling a natural choice. In this paper, we develop a method for influenza prediction based on the real-time tweet data from social media, and this method ensures real-time prediction and is applicable to sampling data. Specifically, we first simulate the sampling process of flu tweets, and then develop a specific partial differential equation (PDE) model to characterize and predict the aggregated flu tweet volumes. Our PDE model incorporates the effects of flu spreading, flu recovery, and active human interventions for reducing flu. Our extensive simulation results show that this PDE model can almost eliminate the data reduction effects from the sampling process: It requires lesser historical data but achieves stronger prediction results with a relative accuracy of over 90% on the 1% sampling data. Even for the more aggressive data sampling ratios such as 0.1% and 0.01% sampling, our model is still able to achieve relative accuracies of 85% and 83%, respectively. These promising results highlight the ability of our mechanistic PDE model in predicting temporal–spatial patterns of flu trends even in the scenario of small sampling Twitter data.
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Rohman, Muhammad Ghofar. "SISTEM PAKAR DIAGNOSA VIRUS INFLUENZA MENGGUNAKAN METODE CERTAINTY FACTOR BERBASIS WEB". Joutica 5, n.º 2 (30 de setembro de 2020): 367. http://dx.doi.org/10.30736/jti.v5i2.449.
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Penelitian ini bertujuan untuk membuat suatu sistem pakar supaya pengguna mendapatkan informasi yang akurat tentang diagnosa gejala dan jenis virus influenza. Pada penelitian ini menggunakan metode certainty factor, certainty factor ini digunakan membuktikan yang tidak pasti menjadi pasti dan menjawab pertanyaan pengguna yang masih ragu dengan kondisi kesehatanya. Variabel input pada penelitian ini adalah gejala-gejala pada jenis influenza, yaitu: Flu Australia, Flu Spanyol, Flu Singapura, Flu Hongkong. Outputnya adalah berupa nilai presentasi pada jenis virus nfluenza, kesimpulan jenis virus influenza yang menginfeksi dan saran untuk mengetahui diagnosa dan informasi yang akurat tentang diagnosa gejala penyakit. Hasil penelitian ini menyatakan bahwa dari hasil akhir konsultasi bahwa nilai lebih dominan dari perhitungan metode certainty factor adalah nilai CF penyakit flu Australia maka tingkat keyakinan diagnosa lebih besar dibanding penyakit yang lainnya dengan nilai akurasi 98%.
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McCarthy, Carol A., Leslie L. Carson, George H. Russell e F. L. Lucas. "1391. Enhanced Education and Administration of Influenza Vaccine in a Pediatric Subspecialty Practice". Open Forum Infectious Diseases 7, Supplement_1 (1 de outubro de 2020): S705. http://dx.doi.org/10.1093/ofid/ofaa439.1573.
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Abstract Background Strategies to increase influenza (flu) immunization rates are desirable. Some children who are at increased risk for severe disease may only be seen in a subspecialty office during the months when flu vaccine is offered. Subspecialists may also provide education for families that are uncertain about benefits of vaccines. Methods During the 2019- 2020 season, our multispecialty pediatric practice, which includes divisions of Endocrinology, Gastroenterology, Infectious Disease, Nephrology, Pulmonary, and Surgery, initiated a quality project to increase delivery of flu vaccine during visits. Beginning 10/1/19, providers were encouraged to use tools in the electronic medical record (EMR) to ask about flu vaccine status and administer if indicated and accepted. Flu immunizations given for all divisions, as well as individual divisions, were compared with the previous 2018–2019 season. Results From 9/1/19 -3/31/20, 615 doses of flu vaccine were administered for 5667 patients for a rate of 10.9 %. This was an increase from 9/1/18- 3/31/19 when 256 doses were given for 5760 patients (4.4%, p< .0001). All divisions had a significant increase in flu vaccine rates except for infectious disease. Review of certain high risk disorders showed significant increased rates for diabetes and asthma but not for inflammatory bowel disease, HIV infection, chronic renal disease, or cystic fibrosis. During this project an EMR flu tool was not used for 1788 patients (32%). Of the remaining 3879 patients, 1982 (51%) reported prior receipt of flu vaccine and 579 (15%) were not eligible for state supplied vaccine. For 1318 eligible patients, flu vaccine was accepted by 631 (48%) and given to 615 patients. Flu vaccine was declined by 687 (52%) patients. Conclusion There is opportunity to provide education and flu vaccine during pediatric subspecialty visits. All specialties increased the number of flu vaccine given except for infectious disease. This is likely because this division has routinely offered flu vaccine and visits for travel declined in 2020. Although the practice overall gave more flu vaccine from the prior year, there appear to be missed opportunities. Further quality improvement work will strengthen the EMR flu screening tools to increase participation and learn more about why flu vaccine is declined. Disclosures All Authors: No reported disclosures
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Saraswati, Ratih Dian, e Risqa Novita. "VAKSIN FLU BURUNG DI MANUSIA SEBAGAI UPAYA ALTERNATIF PENCEGAHAN TERHADAP RE-EMERGING VIRUS H5N1". Vektora : Jurnal Vektor dan Reservoir Penyakit 13, n.º 1 (27 de agosto de 2021): 35–44. http://dx.doi.org/10.22435/vk.v13i1.4231.
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A total of 182 human cases of avian influenza have been reported in Indonesia in the period 2004-2011, with a case fatality rate (CFR) among them of 86%. Various risk factors for avian influenza transmission have also been identified, including a high population, having many types of poultry (broiler, layer, village chickens, etc), traditional poultry systems that promote close human relationships, and the presence of several areas in Indonesia which are strategic locations as a place to rest and meet various wild birds. Vaccination is one of the efforts to prevent the re-emergence of H5N1 avian influenza transmission. However, the avian influenza vaccine for the public is not yet available in Indonesia. The purpose of this review article is to examine the avian influenza vaccine in humans as a preventive measure against the re-emergence of avian influenza in Indonesia, and to determine the progress of developing avian influenza vaccines. The results of the review show that several avian influenza vaccine candidates have been approved by WHO, one of which is a vaccine candidate using an isolated virus from Indonesia. This information on the development of avian influenza vaccines for humans is useful and can be used as an avian influenza pre-pandemic preparedness in Indonesia.
Abstrak
Sebanyak 182 kasus flu burung pada manusia telah dilaporkan di Indonesia pada periode tahun 2004-2011, dengan case fatality rate (CFR) sebesar 86%. Berbagai faktor risiko penularan flu burung juga telah diidentifikasi, antara lain jumlah penduduk yang tinggi, memiliki banyak jenis unggas (ayam broiler, layer, kampong, dsb), sistem perunggasan tradisional yang membuat kedekatan hubungan antara manusia, dan adanya beberpa wilayah di Indonesia yang menjadi lokasi strategis sebagai tempat istirahat dan bertemunya berbagai unggas liar. Vaksinasi merupakan salah satu upaya untuk mencegah munculnya kembali penularan flu burung H5N1. Namun demikian, vaksin flu burung untuk masyarakat belum tersedia hingga saat ini. Tujuan dari review artikel ini adalah untuk mengkaji vaksin flu burung pada manusia sebagai tindakan pencegahan terhadap kemunculan kembali flu burung di Indonesia, dan untuk mengetahui kemajuan pengembangan vaksin flu burung. Hasil review menunjukkan beberapa kandidat vaksin flu burung telah disetujui oleh WHO, salah satunya adalah kandidat vaksin menggunakan isolat virus asal Indonesia. Informasi perkembangan vaksin flu burung bagi manusia ini bermanfaat dan dapat digunakan sebagai kesiapsiagaan prepandemi flu burung di Indonesia.
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Pineo, Ronn. "Four Flu Pandemics: Lessons that Need to Be Learned". Journal of Developing Societies 37, n.º 4 (26 de outubro de 2021): 398–448. http://dx.doi.org/10.1177/0169796x211047221.
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This article explores the history of influenza, focusing on the four major flu pandemics in the last century and a half, outbreaks starting in 1889, 1918, 1957, and 1968. The article looks closely at flu etiology and the historical puzzles over which flu subtype was responsible for each major outbreak. Some mysteries regarding pandemic influenza remain, with core questions stubbornly refusing to yield answers. This article seeks to explore the history of flu in the hope that we can take away some lessons learned as we try to get ready for potential future flu pandemics.
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Bosevska, Golubinka, Nikola Panovski, Elizabeta Janceska, Vladimir Mikik, Irena Kondova Topuzovska e Zvonko Milenkovik. "Clinical Investigations. Comparison of Directigen Flu A+B with Real Time PCR in the Diagnosis of Influenza / Сравнение Иммунохроматографического Метода (Directigen Flu A+B) И Теста RT-PCR При Инфекциях Гриппа". Folia Medica 57, n.º 2 (1 de junho de 2015): 104–10. http://dx.doi.org/10.1515/folmed-2015-0027.
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AbstractEarly diagnosis and treatment of patients with influenza is the reason why physicians need rapid high-sensitivity influenza diagnostic tests that require no complex lab equipment and can be performed and interpreted within 15 min. The Aim of this study was to compare the rapid Directigen Flu A+B test with real time PCR for detection of influenza viruses in the Republic of Macedonia. MATERIALS AND METHODS: One-hundred-eight respiratory samples (combined nose and throat swabs) were routinely collected for detection of influenza virus during influenza seasons. Forty-one patients were pediatric cases and 59 were adult. Their mean age was 23 years. The patients were allocated into 6 age groups: 0 - 4 yrs, 5 - 9 yrs, 10 - 14 yrs, 15 - 19 yrs, 20-64 yrs and > 65 yrs. Each sample was tested with Directigen Flu A+B and CDC real time PCR kit for detection and typisation/subtypisation of influenza according to the lab diagnostic protocol. RESULTS: Directigen Flu A+B identified influenza A virus in 20 (18.5%) samples and influenza B virus in two 2 (1.9%) samples. The high specificity (100%) and PPV of Directigen Flu A+B we found in our study shows that the positive results do not need to be confirmed. The overall sensitivity of Directigen Flu A+B is 35.1% for influenza A virus and 33.0% for influenza B virus. The sensitivity for influenza A is higher among children hospitalized (45.0%) and outpatients (40.0%) versus adults. CONCLUSION: Directigen Flu A+B has relatively low sensitivity for detection of influenza viruses in combined nose and throat swabs. Negative results must be confirmed.
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Guidry, Jeanine P. D., Lucinda L. Austin, Nicole H. O’Donnell, Ioana A. Coman, Alessandro Lovari e Marcus Messner. "Tweeting the #flushot: Beliefs, Barriers, and Threats During Different Periods of the 2018 to 2019 Flu Season". Journal of Primary Care & Community Health 11 (janeiro de 2020): 215013272093272. http://dx.doi.org/10.1177/2150132720932722.
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Influenza epidemics happen every year, with more than 8 million severe cases in 2017. The most effective way to prevent seasonal influenza is vaccination. In recent years, misinformation regarding vaccines abounds on social media, but the flu vaccine is relatively understudied in this area, and the current study is the first 1 to explore the content and nature of influenza information that is shared on Twitter, comparing tweets published in the early flu season with those posted in peak flu season. Using a quantitative content analysis, 1000 tweets from both parts of the flu season were analyzed for use of Health Belief Model (HBM) variables, engagement, and flu vaccine specific variables. Findings show several promising opportunities for health organizations and professionals: HBM constructs were present more frequently than in previous, related studies, and fewer vaccine-hesitant tweets appear to be present. However, the presence of high barriers to flu vaccine uptake increased significantly from early to peak season, including an increase in the mention of conspiracy theories. Flu vaccine related tweets appear to vary in misinformation level and density throughout the flu season. While this should be confirmed by further studies over multiple flu seasons, this a finding that should be considered by public health organizations when developing flu vaccine campaigns on social media.
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Hoskins, Dorian, Cynthia Kaplan, Andrea Pruitt e Andrea McCarter. "Geographic Evaluation of Georgia Vaccination Disparity Among Laboratory-Confirmed Influenza Cases in a Children’s Hospital". Infection Control & Hospital Epidemiology 41, S1 (outubro de 2020): s239. http://dx.doi.org/10.1017/ice.2020.795.
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Background: Vaccination coverage among children aged ≤18 years in Georgia remains one of the lowest in the nation with 39.3% coverage. During the 2018–2019 influenza season, the CDC reported 142 pediatric deaths, 3 of which occurred in Georgia. In a time of increasing complexity of immunization schedules, increase severity with a high level of flu-related deaths and hospitalization, it is important to understand localized factors that contribute to decrease influenza immunization and increased flu-related hospital visits among children. Methods: Data include electronic medical record chart review of 5,827 laboratory confirmed Children’s Healthcare of Atlanta visitor cases from October 1, 2016, to September 24, 2019. System-wide county level data included 3 pediatric hospitals, 5 primary care facilities, 8 urgent care facilities, and 2 outpatient clinics. Characteristics associated with disparities in vaccine were explored using univariate and multiple regressions analysis. Of those children with a primary care physician (PCP), 30% had flu vaccinations, whereas only 16.5% of those without a PCP had been vaccinated (P ≤ .00001). There was a positive relationship between increased county influenza rate and percentage of children in county who were preschoolers <5 years old (r = 0.93; P ≤ .05). Moreover, 78% of children who received the flu vaccine ≤ 2 weeks prior to a confirmed flu diagnosis got the flu during peak flu periods (r = 0.29; P ≤ .05). Predictors of increased flu rate per 1,000 children were associated with flu vaccines given ≤2 weeks before a lab confirmed flu diagnosis (P ≤ .02). Children in counties that had a higher rate of flu during the peak period also had an overall higher rate of flu (P ≤ .005). The higher the percentage of children who got flu during peak flu period, the lower the vaccination rate for the county (P ≤ .001). The percentage of children ≤18 years old with no health insurance was associated with lower vaccination rates in the county (P ≤ .004). There appears to be a positive relationship between receiving flu vaccine 2 weeks prior to lab-confirmed flu diagnosis and onset of illness during the peak flu periods. Missed opportunities to obtain a flu vaccine by a PCP were associated with increased flu-related hospital visits and lower vaccination rates. Results may support predischarge hospital vaccinations and the promotion of flu vaccination education. Pediatric research is needed to facilitate localized PCP vaccination or predischarge hospital vaccinations prior to peak flu periods when hospital-related flu visits increase.Funding: NoneDisclosures: None
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Kim, Jeeyong, Jeonghun Nam, Woongsik Jang e Chae Seung Lim. "Clinical Performance of the AllplexTM Respiratory Panel 1 Test Compared to SimplexaTM Flu A/B and RSV for Detection of Influenza Virus and Respiratory Syncytial Virus Infection Including Their Subtyping". Medical Principles and Practice 28, n.º 4 (2019): 380–86. http://dx.doi.org/10.1159/000499313.
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Objective: TheAllplexTM Respiratory Panel 1 (ARP) is a new assay based on a real-time polymerase chain reaction (RT-PCR) for the detection of influenza A (Flu A), influenza B virus (Flu B), and respiratory syncytial virus (RSV), including subtyping by multiple detection temperature (MuDT) technology. We evaluated the performance of the Allplex Respiratory Panel compared to the SimplexaTM Flu A/B & RSV assay (SP) and other diagnostic tools. Materials and Methods: A total of 372 samples were collected from patients at the Korea University Guro Hospital in Seoul, Korea. All samples were tested for influenza virus and RSV by ARP, SP, and an in-house RT-PCR. Results: The sensitivity of ARP was 95.56, 100, and 95.24% for Flu A, Flu B, and RSV, respectively. The specificity of ARP was 100, 100, and 100% for Flu A, Flu B, and RSV, respectively. SP had sensitivities and specificities of 98.89 and 100% for Flu A, 100 and 100% for Flu B, and 100 and 100% for RSV. Conclusion: The Allplex panelshowed high sensitivity, specificity, positive predictive, and negative predictive values for the detection of Flu A, Flu B, and RSV. This assay is fast and easy to perform because it takes only about 150 min and there is no need for post-PCR electrophoresis. The ARP can be used as a reliable and convenient assay in clinical laboratories.
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Belingheri, M., M. E. Paladino, R. Latocca, G. De Vito e M. A. Riva. "Association between seasonal flu vaccination and COVID-19 among healthcare workers". Occupational Medicine 70, n.º 9 (1 de dezembro de 2020): 665–71. http://dx.doi.org/10.1093/occmed/kqaa197.
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Abstract Background In next fall and winter, SARS-CoV-2 could circulate in parallel with seasonal influenza. The dual epidemics will result in considerable morbidity and mortality; therefore, influenza vaccination may be essential. Recent studies found increased risk of coronavirus in individuals receiving influenza vaccination. Aims Our aim is to analyse the association between influenza vaccination and COVID-19 in a population of healthcare workers (HCWs). Methods IgG antibodies against SARS-CoV-2 were detected in 3520 HCWs at a large hospital in Northern Italy. For each participant, we collected data on flu immunization status for the last five flu seasons. Logistic regression was used to test associations between seasonal flu vaccination status and a positive serology tests for COVID-19. Results During the last five flu seasons, 2492 vaccinations were administered. Serology tests were negative for 3196 (91%) HCWs and residents and only 21 (1%) people had an equivocal test (12.0–15.0 AU/mL). Only 128 (4%) people received a diagnosis of COVID-19, with a positive swab test. No flu vaccinations for the last five flu seasons were specifically associated with diagnosis of COVID-19 or with positive results of serology tests. Conclusions Flu vaccinations did not appear to be associated with SARS-CoV-2 infection. Influenza vaccination should continue to be recommended for HCWs and for individuals at increased risk for severe illness from respiratory infection.
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Kałucka, Sylwia, Agnieszka Głowacka, Elżbieta Dziankowska-Zaborszczyk e Izabela Grzegorczyk-Karolak. "Knowledge, Beliefs and Attitudes towards the Influenza Vaccine among Future Healthcare Workers in Poland". International Journal of Environmental Research and Public Health 18, n.º 4 (22 de fevereiro de 2021): 2105. http://dx.doi.org/10.3390/ijerph18042105.
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The flu vaccine is the best treatment for avoiding the flu and its complications. The aim of the study was to evaluate the knowledge of the flu vaccine and attitude towards the influenza vaccine among medical students in four majors of study (Nursing, Midwifery, Pharmacy, and Public health) in all years of study. A total number of 1137 subjects took part in the study. Most of the vaccinated students assessed the flu vaccine positively (78.5%, 73.7%, 60.7%, and 65.1%, according to their respective majors) and reported that they did not get the flu during the period of vaccination (90.4%, 92.1%, 87.4%, and 97.7%, respectively). Therefore, 65% of the students of Pharmacy, 78% of Midwifery, and 83% of Nursing who were vaccinated once in the last three years recommended the influenza vaccination, and 100% of all students received a regular vaccination every year. The univariate and multivariate logistic regressions showed that a maximum of four factors had a significant impact on the students’ knowledge of the influenza vaccine. Knowledge about the flu vaccine was the highest among Pharmacy students and lowest among Public health students. Final-year students answered the questions better than the younger ones (p < 0.05). Their place of residence and flu vaccination status also appeared to influence their answers. Although all students demonstrated good knowledge of the flu vaccine and demonstrated positive attitudes towards the vaccine, their rate of immunization was low. Therefore, health promotion programs are needed to improve immunization coverage among medical students who are future healthcare workers.
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Lieber, Carolin M., Megha Aggarwal, Jeong-Joong Yoon, Robert M. Cox, Hae-Ji Kang, Julien Sourimant, Mart Toots et al. "4’-Fluorouridine mitigates lethal infection with pandemic human and highly pathogenic avian influenza viruses". PLOS Pathogens 19, n.º 4 (17 de abril de 2023): e1011342. http://dx.doi.org/10.1371/journal.ppat.1011342.
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Influenza outbreaks are associated with substantial morbidity, mortality and economic burden. Next generation antivirals are needed to treat seasonal infections and prepare against zoonotic spillover of avian influenza viruses with pandemic potential. Having previously identified oral efficacy of the nucleoside analog 4’-Fluorouridine (4’-FlU, EIDD-2749) against SARS-CoV-2 and respiratory syncytial virus (RSV), we explored activity of the compound against seasonal and highly pathogenic influenza (HPAI) viruses in cell culture, human airway epithelium (HAE) models, and/or two animal models, ferrets and mice, that assess IAV transmission and lethal viral pneumonia, respectively. 4’-FlU inhibited a panel of relevant influenza A and B viruses with nanomolar to sub-micromolar potency in HAE cells. In vitro polymerase assays revealed immediate chain termination of IAV polymerase after 4’-FlU incorporation, in contrast to delayed chain termination of SARS-CoV-2 and RSV polymerase. Once-daily oral treatment of ferrets with 2 mg/kg 4’-FlU initiated 12 hours after infection rapidly stopped virus shedding and prevented transmission to untreated sentinels. Treatment of mice infected with a lethal inoculum of pandemic A/CA/07/2009 (H1N1)pdm09 (pdmCa09) with 4’-FlU alleviated pneumonia. Three doses mediated complete survival when treatment was initiated up to 60 hours after infection, indicating a broad time window for effective intervention. Therapeutic oral 4’-FlU ensured survival of animals infected with HPAI A/VN/12/2003 (H5N1) and of immunocompromised mice infected with pdmCa09. Recoverees were protected against homologous reinfection. This study defines the mechanistic foundation for high sensitivity of influenza viruses to 4’-FlU and supports 4’-FlU as developmental candidate for the treatment of seasonal and pandemic influenza.
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Prowse, Stephen J., e John S. MacKenzie. "2009 human H1N1 influenza (swine flu)". Microbiology Australia 30, n.º 4 (2009): 127. http://dx.doi.org/10.1071/ma09127.
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The 2009 H1N1 influenza, initially known as swine flu, originated in North America in early 2009. This new strain of influenza A virus (H1N1) came to the attention of the international public health community when several foci of influenza-like illness were identified in Mexico, which had more than 850 cases of pneumonia, of whom 59 had died. Mild cases of influenza-like illness were also reported from Texas and California. Virus isolates were obtained from the cases in California and from samples of cases sent from Mexico to the Canadian National Public Health Laboratory in Winnipeg. Molecular analysis of these virus isolates showed that they were virtually identical and indicated that they represented a completely new, rapidly spreading strain of H1N1 virus, which appeared to have originated in swine. This was the first reassorted influenza virus to emerge since the 1968-1969 pandemic caused by the Hong Kong influenza virus. Under the new International Health Regulations (2005), this rapidly spreading, novel virus was quickly recognised by the World Health Organization as constituting a Public Health Emergency of International Concern, the first such emergency since the new International Health Regulations were introduced in mid-2007.
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Dugas, Andrea Freyer, Mehdi Jalalpour, Yulia Gel, Scott Levin, Fred Torcaso, Takeru Igusa e Richard E. Rothman. "Influenza Forecasting with Google Flu Trends". PLoS ONE 8, n.º 2 (14 de fevereiro de 2013): e56176. http://dx.doi.org/10.1371/journal.pone.0056176.
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McTier, Brian C., Yiuman Tse e John K. Wald. "Do Stock Markets Catch the Flu?" Journal of Financial and Quantitative Analysis 48, n.º 3 (24 de maio de 2013): 979–1000. http://dx.doi.org/10.1017/s0022109013000239.
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AbstractWe examine the impact of influenza on stock markets. For the United States, a higher incidence of flu is associated with decreased trading, decreased volatility, decreased returns, and higher bid-ask spreads. Consistent with the flu affecting institutional investors and market makers, the decrease in trading activity and volatility is primarily driven by the incidence of influenza in the greater New York City area. However, the effect of the flu on bid-ask spreads and returns is related to the incidence of flu nationally. International data confirm our findings of a decrease in trading activity and returns when flu incidence is high.
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Rattanaburi, Somruthai, Vorthon Sawaswong, Suwalak Chitcharoen, Pavaret Sivapornnukul, Pattaraporn Nimsamer, Nungruthai Suntronwong, Jiratchaya Puenpa, Yong Poovorawan e Sunchai Payungporn. "Bacterial microbiota in upper respiratory tract of COVID-19 and influenza patients". Experimental Biology and Medicine 247, n.º 5 (13 de novembro de 2021): 409–15. http://dx.doi.org/10.1177/15353702211057473.
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The upper respiratory tract is inhabited by diverse range of commensal microbiota which plays a role in protecting the mucosal surface from pathogens. Alterations of the bacterial community from respiratory viral infections could increase the susceptibility to secondary infections and disease severities. We compared the upper respiratory bacterial profiles among Thai patients with influenza or COVID-19 by using 16S rDNA high-throughput sequencing based on MiSeq platform. The Chao1 richness was not significantly different among groups, whereas the Shannon diversity of Flu A and Flu B groups were significantly lower than Non-Flu & COVID-19 group. The beta diversity revealed that the microbial communities of influenza (Flu A and Flu B), COVID-19, and Non-Flu & COVID-19 were significantly different; however, the comparison of the community structure was similar between Flu A and Flu B groups. The bacterial classification revealed that Enterobacteriaceae was predominant in influenza patients, while Staphylococcus and Pseudomonas were significantly enriched in the COVID-19 patients. These implied that respiratory viral infections might be related to alteration of upper respiratory bacterial community and susceptibility to secondary bacterial infections. Moreover, the bacteria that observed in Non-Flu & COVID-19 patients had high abundance of Streptococcus, Prevotella, Veillonella, and Fusobacterium. This study provides the basic knowledge for further investigation of the relationship between upper respiratory microbiota and respiratory disease which might be useful for better understanding the mechanism of viral infectious diseases.
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Tamoufe, Ubald, Nancy Ortiz, Karen Saylors, Matt LeBreton, Viviane Meguia, Cyrille Djoko e Richard Njouom. "687. Modeling the Impact of Introduction of Influenza Vaccination on ILI Cumulative Case Count in Cameroon". Open Forum Infectious Diseases 5, suppl_1 (novembro de 2018): S248. http://dx.doi.org/10.1093/ofid/ofy210.694.
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Abstract Background Influenza illness can range from mild to severe, with serious outcomes occurring in children and the elderly. Flu has been studied extensively in geographies where vaccine is often plentiful. The burden of influenza is not well known in tropical regions where vaccine coverage is scant. Our study examines the impact of introducing flu vaccination on cumulative incidence in a Cameroonian population with <0.2% influenza vaccine utilization Methods The data consists of 1 year of flu surveillance from patients presenting with influenza-like-illness at clinics in Cameroon. Samples underwent RT-PCR influenza screening. Analysis was performed in Berkeley Madonna. We developed ordinary differential equations (ODE)s under the SEIR compartmental model and calculated R0. We estimated the proportion of cases the clinics observed to make inferences to the catchment population of these health facilities. We developed another set of ODEs to introduce vaccination using a pulse function with a 50% efficacy and 45% vaccination coverage. Results We observed 82.9% reduction in flu cases by introducing vaccination at 45% coverage (US average). Cameroon would likely achieve reduced coverage. Therefore, we examined introducing vaccination with 10% coverage, and observed that flu cases were cut by over one third. Conclusion This analysis demonstrates that introducing vaccination in Cameroon clinics would reduce influenza cases substantially even with only a small proportion of the population vaccinated. Flu vaccination campaigns should be strongly considered as they can reduce case count which may reduce the likelihood of transmitting flu to those who are at risk the most severe outcomes. Disclosures All authors: No reported disclosures.