scholarly journals DoD Global, Laboratory-based Influenza Surveillance Program: 2012–13 Influenza Season.

2015 ◽  
Vol 44 (suppl_1) ◽  
pp. i4-i4
Author(s):  
L. DeMarcus ◽  
T. Parms
Keyword(s):  
Influenza Season ◽  
Influenza Surveillance ◽  
Surveillance Program

scholarly journals Flucast: a real-time tool to predict severity of an influenza season (Preprint)

2018 ◽  
Author(s):  
Aye Moa ◽  
David Muscatello ◽  
Abrar Chughtai ◽  
Xin Chen ◽  
C Raina MacIntyre
Keyword(s):  
Health System ◽  
Real Time ◽  
Capacity Planning ◽  
Predictive Accuracy ◽  
Influenza Season ◽  
Ease Of Use ◽  
Influenza Surveillance ◽  
Seasonal Activity ◽  
Surge Capacity ◽  
Preparedness Planning

BACKGROUND Influenza causes serious illness requiring annual health system surge capacity, yet annual seasonal variation makes it difficult to forecast and plan for the severity of an upcoming season. Research shows that hospital and health system stakeholders indicated a preference of forecasting tools that are easy to use and understand, to assist with surge capacity planning for influenza. OBJECTIVE This study aimed to develop a simple risk prediction tool, Flucast, to predict the severity of an emerging influenza season. METHODS Study data were obtained from the National Notifiable Diseases Surveillance System and Australian Influenza Surveillance Reports, Department of Health, Australia. We tested Flucast using retrospective seasonal data for eleven Australian influenza seasons. We compared five different models, using parameters known early in the season and which may be associated with the severity of the season. To calibrate the tool, the resulting estimates of seasonal severity were validated against independent reports of influenza-attributable morbidity and mortality. A model with highest predictive accuracy against retrospective seasonal activity was chosen as a best fit model to develop the Flucast tool. The tool was prospectively tested against the emerging 2018 influenza season. RESULTS The Flucast tool predicted the severity of all retrospectively studied years correctly for influenza seasonal activity in Australia. For 2018, the tool provided a reliable early prediction of severe seasonal influenza with the use of real-time data. The tool meets stakeholder preferences for simplicity and ease of use to assist with surge capacity planning. CONCLUSIONS The Flucast tool may be useful to inform future health system influenza preparedness planning, surge capacity and intervention programs in real time and can be adapted for different settings and geographic locations. CLINICALTRIAL NA

scholarly journals FluWatchers: Evaluation of a crowdsourced influenza-like illness surveillance application for Canadian influenza seasons 2015–2016 to 2018–2019

2021 ◽  
Vol 47 (09) ◽  
pp. 357-363
Author(s):  
Liza Lee ◽  
Mireille Desroches ◽  
Shamir Mukhi ◽  
Christina Bancej
Keyword(s):  
Respiratory Virus ◽  
Evaluation Criteria ◽  
Influenza Surveillance ◽  
Surveillance Program ◽  
Surveillance Systems ◽  
Virus Infections ◽  
Detection Rates ◽  
Influenza Like Illness ◽  
Syncytial Virus ◽  
Participatory Surveillance

Background: Sentinel influenza-like illness (ILI) surveillance is an essential component of a comprehensive influenza surveillance program. Community-based ILI surveillance systems that rely solely on sentinel healthcare practices omit important segments of the population, including those who do not seek medical care. Participatory surveillance, which relies on community participation in surveillance, may address some limitations of traditional ILI systems. Objective: We aimed to evaluate FluWatchers, a crowdsourced ILI application developed to complement and complete ILI surveillance in Canada. Methods: Using established frameworks for surveillance evaluations, we assessed the acceptability, reliability, accuracy and usefulness of the FluWatchers system 2015–2016, through 2018–2019. Evaluation indicators were compared against national surveillance indicators of ILI and of laboratory confirmed respiratory virus infections. Results: The acceptability of FluWatchers was demonstrated by growth of 50%–100% in season-over-season participation, and a consistent season-over-season retention of 80%. Reliability was greater for FluWatchers than for our traditional ILI system, although both systems had week-over-week fluctuations in the number of participants responding. FluWatchers’ ILI rates had moderate correlation with weekly influenza laboratory detection rates and other winter seasonal respiratory virus detections including respiratory syncytial virus and seasonal coronaviruses. Finally, FluWatchers has demonstrated its usefulness as a source of core FluWatch surveillance information and has the potential to fill data gaps in current programs for influenza surveillance and control. Conclusion: FluWatchers is an example of an innovative digital participatory surveillance program that was created to address limitations of traditional ILI surveillance in Canada. It fulfills the surveillance system evaluation criteria of acceptability, reliability, accuracy and usefulness.

scholarly journals Influenza antiviral susceptibility monitoring activities in relation to national antiviral stockpiles in Europe during the winter 2006/2007 season

2007 ◽  
Vol 12 (4) ◽  
pp. 3-4 ◽  
Author(s):  
A Meijer ◽  
A Lackenby ◽  
A Hay ◽  
M Zambon
Keyword(s):  
Susceptibility Testing ◽  
Influenza Season ◽  
Influenza Pandemic ◽  
Neuraminidase Inhibitor ◽  
European Countries ◽  
Influenza Surveillance ◽  
Surveillance Network ◽  
Virus Susceptibility ◽  
Pandemic Threat ◽  
The Impact

Due to the influenza pandemic threat, many countries are stockpiling antivirals in the hope of limiting the impact of a future pandemic virus. Since resistance to antiviral drugs would probably significantly alter the effectiveness of antivirals, surveillance programmes to monitor the emergence of resistance are of considerable importance. During the 2006/2007 influenza season, an inventory was conducted by the European Surveillance Network for Vigilance against Viral Resistance (VIRGIL) in collaboration with the European Influenza Surveillance Scheme (EISS) to evaluate antiviral susceptibility testing by the National Influenza Reference Laboratories (NIRL) in relation to the national antiviral stockpile in 30 European countries that are members of EISS. All countries except Ukraine had a stockpile of the neuraminidase inhibitor (NAI) oseltamivir. Additionally, four countries had a stockpile of the NAI zanamivir and three of the M2 ion channel inhibitor rimantadine. Of 29 countries with a NAI stockpile, six countries'; NIRLs could determine virus susceptibility by 50% inhibitory concentration (IC50) and in 13 countries it could be done by sequencing. Only in one of the three countries with a rimantadine stockpile could the NIRL determine virus susceptibility, by sequencing only. However, including the 18 countries that had plans to introduce or extend antiviral susceptibility testing, the NIRLs of 21 of the 29 countries with a stockpile would be capable of susceptibility testing appropriate to the stockpiled drug by the end of the 2007/2008 influenza season. Although most European countries in this study have stockpiles of influenza antivirals, susceptibility surveillance capability by the NIRLs appropriate to the stockpiled antivirals is limited.

scholarly journals What will the next influenza season bring about: seasonal influenza or the new A(H1N1)v? An analysis of German influenza surveillance data

2009 ◽  
Vol 14 (32) ◽  
Author(s):  
H Uphoff ◽  
S Geis ◽  
A Grüber ◽  
A M Hauri
Keyword(s):  
Influenza A ◽  
Seasonal Influenza ◽  
Influenza Season ◽  
Influenza Viruses ◽  
Moderate Intensity ◽  
Influenza Surveillance ◽  
Influenza B ◽  
Low Intensity ◽  
Influenza A H1n1 ◽  
Using Data

For the next influenza season (winter 2009-10) the relative contributions to virus circulation and influenza-associated morbidity of the seasonal influenza viruses A(H3N2), A(H1N1) and B, and the new influenza A(H1N1)v are still unknown. We estimated the chances of seasonal influenza to circulate during the upcoming season using data of the German influenza sentinel scheme from 1992 to 2009. We calculated type and subtype-specific indices for past exposure and the corresponding morbidity indices for each season. For the upcoming season 2009-10 our model suggests that it is unlikely that influenza A(H3N2) will circulate with more than a low intensity, seasonal A(H1N1) with more than a low to moderate intensity, and influenza B with more than a low to median intensity. The probability of a competitive circulation of seasonal influenza A with the new A(H1N1)v is low, increasing the chance for the latter to dominate the next influenza season in Germany.

scholarly journals Using a Bayesian Method to Assess Google, Twitter, and Wikipedia for ILI Surveillance

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Danielle Sharpe ◽  
Richard Hopkins ◽  
Robert L. Cook ◽  
Catherine W. Striley
Keyword(s):  
Seasonal Changes ◽  
Bayesian Method ◽  
Influenza Season ◽  
Healthcare Providers ◽  
High Sensitivity ◽  
Change Points ◽  
Influenza Surveillance ◽  
Web Based ◽  
Using Data ◽  
The Web

ObjectiveTo comparatively analyze Google, Twitter, and Wikipedia byevaluating how well change points detected in each web-based sourcecorrespond to change points detected in CDC ILI data.IntroductionTraditional influenza surveillance relies on reports of influenza-like illness (ILI) by healthcare providers, capturing individualswho seek medical care and missing those who may search, post,and tweet about their illnesses instead. Existing research has shownsome promise of using data from Google, Twitter, and Wikipediafor influenza surveillance, but with conflicting findings, studies haveonly evaluated these web-based sources individually or dually withoutcomparing all three of them1-5. A comparative analysis of all threeweb-based sources is needed to know which of the web-based sourcesperforms best in order to be considered to complement traditionalmethods.MethodsWe collected publicly available, de-identified data from the CDCILINet system, Google Flu Trends, HealthTweets.org, and Wikipediafor the 2012-2015 influenza seasons. Bayesian change point analysiswas the method used to detect change points, or seasonal changes,in each of the web-data sources for comparison to change pointsin CDC ILI data. All analyses was conducted using the R package‘bcp’ v4.0.0 in RStudio v0.99.484. Sensitivity and positive predictivevalues (PPV) were then calculated.ResultsDuring the 2012-2015 influenza seasons, a high sensitivity of 92%was found for Google, while the PPV for Google was 85%. A lowsensitivity of 50% was found for Twitter; a low PPV of 43% wasfound for Twitter also. Wikipedia had the lowest sensitivity of 33%and lowest PPV of 40%.ConclusionsGoogle had the best combination of sensitivity and PPV indetecting change points that corresponded with change points found inCDC data. Overall, change points in Google, Twitter, and Wikipediadata occasionally aligned well with change points captured in CDCILI data, yet these sources did not detect all changes in CDC data,which could indicate limitations of the web-based data or signify thatthe Bayesian method is not adequately sensitive. These three web-based sources need to be further studied and compared using otherstatistical methods before being incorporated as surveillance data tocomplement traditional systems.Figure 1. Detection of change points, 2012-2013 influenza seasonFigure 2. Detection of change points, 2013-2014 influenza seasonFigure 3. Detection of change points, 2014-2015 influenza season

scholarly journals Spotlight influenza: The 2019/20 influenza season and the impact of COVID-19 on influenza surveillance in the WHO European Region

2021 ◽  
Vol 26 (40) ◽  
Author(s):  
Cornelia Adlhoch ◽  
Miriam Sneiderman ◽  
Oksana Martinuka ◽  
Angeliki Melidou ◽  
Nick Bundle ◽  
...  
Keyword(s):  
Influenza A ◽  
Influenza Season ◽  
Healthcare Access ◽  
World Health ◽  
European Region ◽  
Influenza Surveillance ◽  
Influenza B ◽  
Rapid Reduction ◽  
Influenza Activity ◽  
The Impact

Background Annual seasonal influenza activity in the northern hemisphere causes a high burden of disease during the winter months, peaking in the first weeks of the year. Aim We describe the 2019/20 influenza season and the impact of the COVID-19 pandemic on sentinel surveillance in the World Health Organization (WHO) European Region. Methods We analysed weekly epidemiological and virological influenza data from sentinel primary care and hospital sources reported by countries, territories and areas (hereafter countries) in the European Region. Results We observed co-circulation of influenza B/Victoria-lineage, A(H1)pdm09 and A(H3) viruses during the 2019/20 season, with different dominance patterns observed across the Region. A higher proportion of patients with influenza A virus infection than type B were observed. The influenza activity started in week 47/2019, and influenza positivity rate was ≥ 50% for 2 weeks (05–06/2020) rather than 5–8 weeks in the previous five seasons. In many countries a rapid reduction in sentinel reports and the highest influenza activity was observed in weeks 09–13/2020. Reporting was reduced from week 14/2020 across the Region coincident with the onset of widespread circulation of SARS-CoV-2. Conclusions Overall, influenza type A viruses dominated; however, there were varying patterns across the Region, with dominance of B/Victoria-lineage viruses in a few countries. The COVID-19 pandemic contributed to an earlier end of the influenza season and reduced influenza virus circulation probably owing to restricted healthcare access and public health measures.

scholarly journals Co-circulation of influenza A(H1N1), A(H3N2), B(Yamagata) and B(Victoria) during the 2017−2018 influenza season in Zhejiang Province, China

2020 ◽  
Vol 148 ◽  
Author(s):  
Haiyan Mao ◽  
Yi Sun ◽  
Yin Chen ◽  
Xiuyu Lou ◽  
Zhao Yu ◽  
...  
Keyword(s):  
Amino Acid ◽  
Influenza A ◽  
Influenza Season ◽  
Phylogenetic Analyses ◽  
Amino Acid Level ◽  
Respiratory Pathogen ◽  
Influenza Surveillance ◽  
Influenza A H1n1 ◽  
Control And Prevention ◽  
Viral Sequencing

Abstract Influenza is a major human respiratory pathogen. Due to the high levels of influenza-like illness (ILI) in Zhejiang, China, the control and prevention of influenza was challenging during the 2017–2018 season. To identify the clinical spectrum of illness related to influenza and characterise the circulating influenza virus strains during this period, the characteristics of ILI were studied. Viral sequencing and phylogenetic analyses were conducted to investigate the virus types, substitutions at the amino acid level and phylogenetic relationships between sequences. This study has shown that the 2017/18 influenza season was characterised by the co-circulation of influenza A (H1N1) pdm09, A (H3N2) and B viruses (both Yamagata and Victoria lineage). From week 36 of 2017 to week 12 of 2018, ILI cases accounted for 5.58% of the total number of outpatient and emergency patient visits at the surveillance sites. Several amino acid substitutions were detected. Vaccination mismatch may be a potential reason for the high percentage of ILI. Furthermore, it is likely that multiple viral introductions played a role in the endemic co-circulation of influenza in Zhejiang, China. More detailed information regarding the molecular epidemiology of influenza should be included in long-term influenza surveillance.

DoD Global Influenza Surveillance Program Season Summary, 2001-2002

2002 ◽  
Author(s):  
Melanie J. Rodriguez ◽  
Andrea R. Krull ◽  
Linda C. Canas ◽  
Luke T. Daum ◽  
James S. Neville
Keyword(s):  
Influenza Surveillance ◽  
Surveillance Program

scholarly journals Rapid Detection of Reassortment of Pandemic H1N1/2009 Influenza Virus

2010 ◽  
Vol 56 (8) ◽  
pp. 1340-1344 ◽  
Author(s):  
Leo L M Poon ◽  
Polly W Y Mak ◽  
Olive T W Li ◽  
Kwok Hung Chan ◽  
Chung Lam Cheung ◽  
...  
Keyword(s):  
Gene Segment ◽  
Swine Influenza ◽  
Influenza Viruses ◽  
Screening Tools ◽  
Influenza Surveillance ◽  
Surveillance Program ◽  
Pandemic H1n1 ◽  
Rt Pcr ◽  
Pandemic H1n1 2009 ◽  
Ongoing Surveillance

BACKGROUND Influenza viruses can generate novel reassortants in coinfected cells. The global circulation and occasional introductions of pandemic H1N1/2009 virus in humans and in pigs, respectively, may allow this virus to reassort with other influenza viruses. These possible reassortment events might alter virulence and/or transmissibility of the new reassortants. Investigations to detect such possible reassortants should be included as a part of pandemic influenza surveillance plans. METHODS We established a real-time reverse-transcription (RT)-PCR–based strategy for the detection of reassortment of pandemic H1N1/2009 virus. Singleplex SYBR green–based RT-PCR assays specific for each gene segment of pandemic H1N1/2009 were developed. These assays were evaluated with influenza viruses of various genetic backgrounds. RESULTS All human pandemic H1N1 (n = 27) and all seasonal human (n = 58) isolates were positive and negative, respectively, for all 8 segments. Of 48 swine influenza viruses isolated from our ongoing surveillance program of influenza viruses in swine, 10 were positive in all reactions. All 8 viral segments of these 10 samples were confirmed to be of pandemic H1N1 origin, indicating that these were caused by zoonotic transmissions from human to pigs. The 38 swine viruses that were nonpandemic H1N1/2009 had 1–6 gene segments positive in the tests. Further characterization of these nonpandemic H1N1/2009 swine viruses indicated that these PCR-positive genes were the precursor genes of the pandemic H1N1/2009 virus. CONCLUSIONS Our results demonstrated that these assays can detect reintroductions of pandemic H1N1/2009 virus in pigs. These assays might be useful screening tools for identifying viral reassortants derived from pandemic H1N1/2009 or its precursors.

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