Influenza Trends Research Articles

Utility of Outpatient Syndromic Data for Monitoring Influenza-like Illness

ObjectiveTo explore how outpatient and urgent care syndromic surveillancefor influenza-like illness (ILI) compare with emergency departmentsyndromic ILI and other seasonal ILI surveillance indicators.IntroductionThe North Dakota Department of Health (NDDoH) collectsoutpatient ILI data through North Dakota Influenza-like IllnessNetwork (ND ILINet), providing situational awareness regardingthe percent of visits for ILI at sentinel sites across the state. Becauseof increased clinic staff time devoted to electronic health initiativesand an expanding population, we have found sentinel sites have beenharder to maintain in recent years, and the number of participatingsentinel sites has decreased. Outpatient sentinel surveillance forinfluenza is an important component of influenza surveillance becausehospital and death surveillance does not capture the full spectrum ofinfluenza illness.Syndromic surveillance (SyS) is another possible source ofinformation for outpatient ILI that can be used for situationalawareness during the influenza season; one benefit of SyS is that itcan provide more timely information than traditional outpatient ILIsurveillance [1,2]. The NDDoH collects SyS data from hospitals(emergency department and inpatient visits) and outpatient clinics,including urgent and primary care locations. Visits include chiefcomplaint and/or diagnosis code data. This data is sent to theBioSense 2.0 SyS platform. We compared our outpatient SyS ILI withour ND ILINet and reported influenza cases, and included hospitaland combined SyS ILI for comparison.MethodsWeekly rates from ND ILINet, SyS ILI, and counts of reportedcases from the influenza season (annual weeks 40 through 20) forthe 2014-2015 and 2015-2016 seasons were compiled. Syndromiccategories for outpatient, hospital (emergency department andinpatient), and combined hospital and outpatient data were created,and the BioSense 2.0 definition for ILI was used. These includeddata from 127,050 outpatient and 323,318 hospital visits for2014-15, and 124,597 outpatient and 424,097 hospital visits for2015-16. Because influenza is a reportable condition in North Dakota,case data is routinely used to represent the seasonal influenza trend,and is useful when other respiratory viruses are circulating. A PearsonCorrelation Coefficient was calculated on all variables using SAS 9.4.Alpha was set to 0.05. There was no overlap between the outpatientclinics providing syndromic surveillance data and clinics participatingin ND ILINet.ResultsAll outpatient, hospital, and combined outpatient and hospitalILI rates from SyS data were positively and significantly correlatedwith both ND ILINet rates and influenza case counts (Table 1). Thecorrelation between outpatient SyS ILI rates and traditional influenzaindicators was lower than for hospital SyS ILI rates for both years,with correlation coefficients ranging from 0.38-0.48 and 0.56-0.92,respectively. Generally SyS data was more highly correlated withcase counts than ND ILINET rates. For the 2014-15 season, hospitalSyS data was the most strongly correlated with traditional influenzaindicators. For 2015-16, combined SyS data was the most stronglycorrelated. Visual inspection of the chief complaint data for ILI visitsfound a significant number of gastrointestinal visits that included thephrase “flu-like illness” in both outpatient and hospital SyS data.ConclusionsAlthough correlation coefficients were lower for outpatient SySILI rates, they are significant enough to be included in our ongoinginfluenza surveillance. One possible confounding factor for therelationship between ED surveillance and reported cases is that peoplewith more severe illness may be more likely to be tested for influenza,and may be more likely to seek medical attention at a hospital setting.This may explain why hospital SyS data provided the strongestcorrelation during the 2014-15 season, a season with higher rates ofmore severe illness than 2015-16. The combination of outpatient dataand hospital data provided the strongest correlation for the 2015-16influenza season, indicating the addition of outpatient data, which mayincrease representativeness of ILI data, may be beneficial to SyS ILIsurveillance. We used an existing ILI syndrome from the BioSense2.0 tool, and revising this syndrome may improve correlationsbetween SyS ILI and ND ILINet and case count data. Negation termsto remove visits for GI illness incorrectly referred to as “flu-like”would be one useful change. The nature of visits for influenza atoutpatient clinic versus hospitals is different, and it is possible thismay account for the difference in the strength of correlations betweenthe two data sources. Use of a different ILI syndrome definition foroutpatient SyS data should be investigated.Table 1. Pearson correlation coefficient values for influenza-like illness in threesyndromic surveillance categories compared with ND ILINET and influenzacase counts.

Syndromic Surveillance Evaluation of Influenza Activity in At-Risk Sub-Populations

Syndromic surveillance can be used not only to monitor overall influenza trends, but is also effective for timely surveillance and estimation of influenza activity in three target populations: a) adults > 65, b) pregnant women, and c) children < 5 in Florida.

Host-Specific and Segment-Specific Evolutionary Dynamics of Avian and Human Influenza A Viruses: A Systematic Review.

Understanding the evolutionary dynamics of influenza viruses is essential to control both avian and human influenza. Here, we analyze host-specific and segment-specific Tajima’s D trends of influenza A virus through a systematic review using viral sequences registered in the National Center for Biotechnology Information. To avoid bias from viral population subdivision, viral sequences were stratified according to their sampling locations and sampling years. As a result, we obtained a total of 580 datasets each of which consists of nucleotide sequences of influenza A viruses isolated from a single population of hosts at a single sampling site within a single year. By analyzing nucleotide sequences in the datasets, we found that Tajima’s D values of viral sequences were different depending on hosts and gene segments. Tajima’s D values of viruses isolated from chicken and human samples showed negative, suggesting purifying selection or a rapid population growth of the viruses. The negative Tajima’s D values in rapidly growing viral population were also observed in computer simulations. Tajima’s D values of PB2, PB1, PA, NP, and M genes of the viruses circulating in wild mallards were close to zero, suggesting that these genes have undergone neutral selection in constant-sized population. On the other hand, Tajima’s D values of HA and NA genes of these viruses were positive, indicating HA and NA have undergone balancing selection in wild mallards. Taken together, these results indicated the existence of unknown factors that maintain viral subtypes in wild mallards.

Clarifying life lost due to cold and heat: a new approach using annual time series

ObjectiveTo clarify whether deaths associated with hot and cold days are among the frail who would have died anyway in the next few weeks or months.DesignTime series regression analysis of...

An Early Warning Influenza Model using Alberta Real- Time Syndromic Data (ARTSSN)

We developed early warning algorithms for influenza using data from the Alberta Real-Time Syndromic Surveillance Net (ARTSSN). In addition to looking for signatures of potential pandemics, the model was operationalized by using the algorithms to provide regular weekly forecasts on the influenza trends in Alberta during 2012-2014. We describe the development of the early warning model and the predicted influenza peak time and attack rate results. We report on the usefulness of this model using real-time ARTSSN data, discuss how it was used by decision makers and suggest future enhancements for this promising tool in influenza planning and preparedness.

Bird Flu Outbreak Prediction via Satellite Tracking

Advanced satellite tracking technologies have collected huge amounts of wild bird migration data. Biologists use these data to understand dynamic migration patterns, study correlations between habitats, and predict global spreading trends of avian influenza. The research discussed here transforms the biological problem into a machine learning problem by converting wild bird migratory paths into graphs. H5N1 outbreak prediction is achieved by discovering weighted closed cliques from the graphs using the mining algorithm High-wEight cLosed cliquE miNing (HELEN). The learning algorithm HELEN-p then predicts potential H5N1 outbreaks at habitats. This prediction method is more accurate than traditional methods used on a migration dataset obtained through a real satellite bird-tracking system. Empirical analysis shows that H5N1 spreads in a manner of high-weight closed cliques and frequent cliques.

Molecular epidemiologic and clinical characteristics of influenza B-associated complications among hospitalized patients during an outbreak in Taiwan

To study the resurgence of influenza B/Yam in Taiwan and summarize clinical findings of influenza B-associated complications among hospitalized patients, in particular the link between clinical and molecular epidemiologic characteristics. Clinical information and isolates were collected through the national surveillance system of the Taiwan Centers for Disease Control. Potential risk factors associated with severe illness were analyzed. Antigenic and genetic analysis of representative hemagglutinin (HA) nucleotide sequences was performed. Of 326 patients admitted to the intensive care unit (ICU), 63.2% were aged ≤18 years or ≥65 years and 12.9% were adults aged 19-49 years. Most of the cases had underlying medical conditions before admission, and more fatal cases had chronic medical conditions than those who convalesced in the ICU. Results of the phylogenetic analysis showed that the majority of isolates from fatal cases in Taiwan were in group 2 (represented by B/Massachusetts/2/2012-like) rather than group 3, which was the predominant group of strains circulating in other Asian countries. Our findings suggest a regional trend of influenza B viruses and showed that new phylogenetic lineages and antigenic variants emerging in neighboring countries were likely to be the progenitors of the epidemic strains in the following seasons.

Monitoring of activity of influenza in Santa Fe, Argentina, 2005-2010

Influenza viruses have a relevant public health impact. To describe the activity of influenza and assess the morbidity and mortality impact during 2005 to 2010 in Santa Fe, Argentina. Epidemiological and virological indicators were calculated based on sentinel surveillance. Mortality data from patients over and under the age of 65 were analyzed using the integrated autoregressive moving average model and an excess of mortality attributable to influenza was determined. The viral circulation effect on morbidity was measured through the evolution in the proportion of influenza-like illness (ILI) patients. Peak incidence was observed between weeks 23 and 33. An excess of deaths was identified in 2007 among patients over 65 and among those under 65 in 2009, which was related with influenza A(H3N2) and A(H1N1)pandemic virus circulation respectively, associated with a higher proportion of virus recovery and a higher ILI percentage. The sentinel surveillance of influenza is a simple and efficient methodology that identifies influenza trends. Our study showed that the virus has caused a rise of mortality in patients > 65 in epidemic periods associated with the H3N2 subtype and in patients < 65 in the pandemic period with the circulation ofA(HIN1)pandemic virus.

The Information Analysis of Avian Influenza Research by Gopubmed

Objective To probe into the status and development trend of avian influenza,so as to provide reference for further research.Methods The article took the avian literature as the object of study,took Gopubmed as the retrieval and statistical tool,made information analysis of the subjects,time,sources,distribution,authors and literature development trends of avian research.Results The main subjects of avian literature involved influenza in birds and influenza,human.There has been a sharp increase on the literature number of avian in the recent decade with the most in 2006.The United States accounted for the most literature and China ranked the second place.The sources of avian literature were mainly the SCI journals from the United States and European countries.Conclusions Gopubmed can show a vivid picture of the current situation and development trend of avian research.Further improvements are needed both in the quality and quantity of avian research in China Key words: Gopubmed; Avian Influenza; Information Analysis

Association of hospitalizations for asthma with seasonal and pandemic influenza

Although influenza has been associated with asthma exacerbations, it is not clear the extent to which this association affects health care use in the United States. The first goal of this project was to determine whether, and to what extent, the incidence of asthma hospitalizations is associated with seasonal variation in influenza. Second, we used influenza trends (2000-2008) to help predict asthma admissions during the 2009 H1N1 influenza pandemic. We identified all hospitalizations between 1998 and 2008 in the Nationwide Inpatient Sample from the Healthcare Cost and Utilization Project during which a primary diagnosis of asthma was recorded. Separately, we identified all hospitalizations during which a diagnosis of influenza was recorded. We performed time series regression analyses to investigate the association of monthly asthma admissions with influenza incidence. Finally, we applied these time series regression models using 1998-2008 data, to forecast monthly asthma admissions during the 2009 influenza pandemic. Based on time series regression models, a strong, significant association exists between concurrent influenza activity and incidence of asthma hospitalizations (P-value < 0.0001). Use of influenza data to predict asthma admissions during the 2009 H1N1 pandemic improved the mean squared prediction error by 60.2%. Influenza activity in the population is significantly associated with asthma hospitalizations in the United States, and this association can be exploited to more accurately forecast asthma admissions. Our results suggest that improvements in influenza surveillance, prevention and treatment may decrease hospitalizations of asthma patients.

Influenza seasonality and predominant subtypes of influenza virus in Guangdong, China, 2004-2012.

Influenza surveillance is carried out in Guangdong province, southern China. A better understanding of influenza seasonality and predominant Subtypes of influenza virus in Guangdong can help to improve evidence-based prevention and control strategies for influenza in the future. THERE ARE THREE CATEGORIES OF INFLUENZA SURVEILLANCE IN GUANGDONG: Influenza-like Illness (ILI) Outpatient Surveillance, ILI Outbreak Surveillance and Influenza Virus Surveillance. This paper summarizes collected influenza surveillance data from January 2004 to December 2012 in Guangdong province. Time series analysis and "peak analysis" were performed to estimate seasonality and temporal trends of influenza activity. During the 9-year study period, a total of 37,571,582 outpatients had been recorded, in which 1,889,684 ILI cases had been reported. The provincial ILI visiting percentage peaked at 6-10%. A total of 107,115 respiratory specimens of ILI outpatients were collected, 17,454 (16.29%) of them tested for influenza virus were positive. Influenza virus peaks appeared in summer mostly with a median epidemic duration of 6 months. A total of 925 outbreaks recorded and 45,322 cases in which were affected. The majority of reported outbreaks (832 outbreaks, 90%) occurred in institutional settings. Influenza circulates periodically every year in Guangdong. Influenza activity had strong and clear seasonality with epidemic periods in summer for last decade. The presence of local unique seasonal pattern and its changes emphasizes the need to optimize timing of influenza vaccine delivery and other public health interventions.

Does Antimicrobial Prescription Data Improve Influenza Surveillance in VA?

Whether antiviral or antibacterial prescriptions correlate with influenza coded encounters is unknown. Oseltamivir, zanamivir and azithromycin outpatient prescriptions from VA Corporate Data Warehouse and respiratory syndrome, influenza-like-illness (ILI) and influenza-specific ICD-9-CM coded visits from outpatient ESSENCE were analyzed for the 2010-2012 influenza seasons in all VA medical centers and outpatient clinics. Significantly more ILI and respiratory syndrome encounters occurred compared to antiviral prescriptions dispensed with marginal temporal correlation between visits and antiviral prescriptions. Azithromycin prescriptions tracked closely with the onset and peaks of the influenza season. Surprisingly, antiviral prescription data provided minimal additional information for influenza trend monitoring in VA.

Pandemic influenza A (H1N1) 2009 in the English- and Dutch-speaking Caribbean: an epidemiological overview.

To describe epidemiological trends of pandemic influenza A (H1N1) in the English and Dutch-speaking Caribbean during the pandemic period. Data on laboratory-confirmed cases and deaths associated with pandemic influenza A (H1N1) contained in two regional databases at the Caribbean Epidemiology Centre (CAREC) were analysed. The data sources were epidemiological and laboratory reports from English and Dutch-speaking countries and the CAREC laboratory information system (LABIS). In the English- and Dutch-speaking Caribbean, pandemic influenza A (H1N1) was the predominant circulating influenza virus type during the pandemic period. There were three distinct phases: a first pandemic wave during mid-April to end of August 2009 (734 cases), a second pandemic wave during September-December 2009 (570 cases) and a phase of low transmission during January to mid-August 2010 (55 cases). The majority of cases (76%) were aged less than 30 years, with children of school age being most affected. Most cases (89%) presented with symptoms of the respiratory tract and smaller proportions (20-40%) presented with gastrointestinal and other symptoms. No cases tested were resistant to oseltamivir. A quarter of cases required hospitalization and the case fatality rate was 1.8%. The epidemiological characteristics of the pandemic in the English- and Dutch-speaking Caribbean were consistent with that in other parts of the world. It is important that post pandemic surveillance (epidemiological and virological) for respiratory illnesses continues to be enhanced in order to give a better understanding of seasonality and changing trends in respiratory illnesses and their aetiologic agents.

Characteristics of Patients With Influenza-Like Illness, Severe Acture Respiratory Illness, and Laboratory-Confirmed Influenza at a Major Children's Hospital in Angola, 2009-2011

There are no published data on influenza trends in Angola, where pneumonia is a leading cause of death among young children. This study aims to describe the seasonal trends, types, and subtypes of influenza virus recovered from patients with respiratory illness who were admitted to the major children's hospital in Angola from May 2009 through April 2011. Nasal and oral swabs were collected from patients seen in the outpatient clinic with influenza-like illness (ILI) or hospitalized with severe acute respiratory illness (SARI) and tested for influenza virus by polymerase chain reaction assays. Of 691 samples collected, 334 (48%) were from case patients with ILI, and 357 (52%) were from case patients with SARI. Most (86%) of these children were <5 years of age. Thirty-nine samples (47% SARI, 53% outpatient) tested positive for influenza virus, including 2009 pandemic influenza A virus subtype H1N1 (A[H1N1]pdm09; n = 9), influenza A virus subtype H3, likely H3N2 (n = 12), and influenza B virus (n = 18). The proportion of specimens positive for influenza virus was 5% for ILI cases and 6% for SARI cases. After the peak of A(H1N1)pdm09 infection from May through September of 2009, additional peaks of ILI and SARI were seen, especially during February-April 2010. Influenza virus causes a small but preventable number of pneumonia cases among children in Angola.

Dynamic prediction on the number of influenza-like cases in Gansu province based on data from the influenza sentinel surveillance program, from 2006 to 2011

To understand the epidemiological trend on the number of influenza-like cases and to explore the feasibility of early warning systems of influenza in Gansu province. Based on data from the influenza sentinel surveillance program, a sequence chart was used to analyze the epidemiological trend on the number of influenza-like illness (ILI) cases. Both control chart and mobile percentile method were used to select the threshold of premium alert for the ILI of sentinel surveillance program. Warning effects were assessed by statistical model. The prevalence of influenza were both low in 2007 and 2008. Alert thresholds for ILI of Sentinel surveillance was built. The thresholds were higher alert in winter, but lower in summer. Both Seasonal Exponential Smoothing Model and Multiplicative Seasonal ARMA Model (1, 1, 1) (0, 1, 0) were used to dynamically predict the weekly percentage of outpatient visits for influenza-like illness (ILI%) of 2011. The concordance rates (predicted = actual) were 100% for both of them. According to the RMSE values, the dynamically predicted effect of the seasonal exponential smoothing model was superior to ARIMA. Dynamic prediction on the number of influenza-like cases could reflect the epidemiological trend of influenza in Gansu province, but with some limitations.

Self-Reported Influenza-Like Illness and Receipt of Influenza Antiviral Drugs During the 2009 Pandemic, United States, 2009–2010

The purpose of our study was to more accurately characterize people reporting influenza-like illness (ILI) and evaluate trends in health care seeking and influenza diagnosis and treatment during the 2009 influenza pandemic. From September 2009 to March 2010, we ascertained ILI (fever with cough or sore throat), health care seeking, and clinical diagnosis and treatment of influenza with influenza antiviral drugs among adults in 51 jurisdictions, and ILI and health care seeking among children in 41 jurisdictions. Among 216,431 adults and 43,511 children, 8.1% and 28.4% reported ILI, respectively. ILI peaked during November interviews and was higher among young people and American Indian/Alaska Natives. Of those with ILI, 40% of adults and 56% of children reported seeking health care; 26% of adults who sought care reported receiving a diagnosis of influenza. Of adults reporting an influenza diagnosis, 36% were treated with influenza antiviral drugs; treatment was highest among adults aged 18 to 49 years. Analysis of ILI data from the Behavioral Risk Factor Surveillance System enabled a better understanding of the factors associated with self-reported ILI, health care seeking, and clinical influenza diagnosis and treatment, and will help inform year-to-year influenza trends.

Temporal trends of influenza A (H1N1) virus seroprevalence following 2009 pandemic wave in Guangdong, China: three cross-sectional serology surveys.

BackgroundTo evaluate the temporal trends of seroprevalence to pH1N1 among the Guangdong population following 2009 H1N1 pandemic wave, we conducted three cross-sectional serology surveys in 2010.Methodology/Principal FindingsThree surveys were carried out consecutively in 2010 from January 8 to January 24, from March 15 to April 10 and from August 23 to September 4. Sample populations comprising of 4725, 4727, and 4721 subjects respectively were randomly selected for study in these three surveys. The level of antibodies against pH1N1 was evaluated by hemagglutination inhibition assay. In survey 1, the seroprevalence of pH1N1 among all the subjects is 25.1%, declining to 18.4% in survey 2 and increasing to 21.4% in survey 3. Among vaccinated subjects, the seroprevalence was 49.0%, 53.0%, and 49.4% in the three consecutive surveys, showing no significant differences. In contrast, among non-vaccinated subjects, the seroprevalence declined significantly from 22.8% (survey 1) to 14.3% (survey 2) and subsequently increased to 18.1% (survey 3). The multivariate logistic regression analysis revealed that seroprevalence to pH1N1 in non-vaccinated individuals correlated with the investigated order of the surveys, age, and region (all P<0.05). However, it was not correlated with gender (P = 0.650), seasonal influenza vaccination history (P = 0.402) and symptoms (P = 0.074).Conclusions/SignificanceIn Guangdong, the seroprevalance to pH1N1 decreased initially and then rebounded modestly during the first 9 months following the 2009 pandemic wave. Our results suggest that the prevalence of pH1N1 is still correlated with age and population density during the post-pandemic period. An early end to the free pH1N1 vaccination program might be another important reason for the slight rebound in seroprevalance. Our study findings can help the Guangdong authorities to make evidence-based decisions about a long-term vaccination strategy and boost immunity in specific population groups (such as children and people living in the capital-city) to prevent further transmission in the future.

The New School Absentees Reporting System for Pandemic Influenza A/H1N1 2009 Infection in Japan

ObjectiveTo evaluate the new Japanese School Absentees Reporting System for Infectious Disease (SARSID) for pandemic influenza A/H1N1 2009 infection in comparison with the National epidemiological Surveillance of Infectious Disease (NESID).MethodsWe used data of 53,223 students (97.7%) in Takamatsu city Japan. Data regarding school absentees in SARSID was compared with that in NESID from Oct 13, 2009 to Jan 12, 2010.ResultsSimilar trends were observed both in SARSID and NESID. However, the epidemic trend for influenza in SARSID was thought to be more sensitive than that in NESID.ConclusionThe epidemic trend for influenza among school-aged children could be easily and rapidly assessed by SARSID compared to NESID. SARSID might be useful for detecting the epidemic trend of influenza.

Evaluating the New York City Emergency Department Syndromic Surveillance for Monitoring Influenza Activity during the 2009-10 Influenza Season

Objective: To use laboratory data to assess the specificity of syndromes used by the New York City emergency department (ED) syndromic surveillance system to monitor influenza activity. Design: For the period from October 1, 2009 through March 31, 2010, we examined the correlation between citywide ED syndrome assignment and laboratory-confirmed influenza and respiratory syncytial virus (RSV). In addition, ED syndromic data from five select NYC hospitals were matched at the patient and visit level to corresponding laboratory reports of influenza and RSV. The matched dataset was used to evaluate syndrome assignment by disease and to calculate the sensitivity and specificity of the influenza-like illness (ILI) syndrome. Results: Citywide ED visits for ILI correlated well with influenza laboratory diagnoses (R=0.92). From October 1, 2009, through March 31, 2010, there were 264,532 ED visits at the five select hospitals, from which the NYC Department of Health and Mental Hygiene (DOHMH) received confirmatory laboratory reports of 655 unique cases of influenza and 1348 cases of RSV. The ED visit of most (56%) influenza cases had been categorized in the fever/flu syndrome; only 15% were labeled ILI. Compared to other influenza-related syndromes, ILI had the lowest sensitivity (15%) but the highest specificity (90%) for laboratory-confirmed influenza. Sensitivity and specificity varied by age group and influenza activity level. Conclusions: The ILI syndrome in the NYC ED syndromic surveillance system served as a specific but not sensitive indicator for influenza during the 2009-2010 influenza season. Despite its limited sensitivity, the ILI syndrome can be more informative for tracking influenza trends than the fever/flu or respiratory syndromes because it is less likely to capture cases of other respiratory viruses. However, ED ILI among specific age groups should be interpreted alongside laboratory surveillance data. ILI remains a valuable tool for monitoring influenza activity and trends as it facilitates comparisons nationally and across jurisdictions and is easily communicated to the public.

Circulating Influenza Virus, Climatic Factors, and Acute Myocardial Infarction: A Time Series Study in England and Wales and Hong Kong

Influenza virus has been associated with acute myocardial infarction (MI), but given seasonal trends of influenza, climatic factors have not been able to be excluded as the true cause. This study compared acute myocardial infarction hospitalizations and deaths with influenza data from two separate climatic regions. England/Wales, with its temperate climate, has its influenza peak during the winter, with a clear seasonal pattern. Hong Kong, on the other hand, with its subtropical climate, has winters that are less severe, with two subsequent peaks in influenza, during the winter and summer months.