Incidence Of Influenza-like Illness Research Articles

Surveillance of infections in long-term care facilities (LTCFs): The impact of participation during multiple years on health care-associated infection incidence.

We studied trends in the incidence of health care-associated infections (HAIs) in LTCFs between 2009 and 2015 and determined the effect of participation in our network. Elder-care physicians reported weekly the number of cases of influenza-like illness, gastroenteritis, (probable) pneumonia, urinary tract infections (UTIs) and all-cause mortality. Trends in the incidence of infection and mortality in relation to LTCF characteristics were calculated using multilevel univariate and multivariate logistic regression. Thirty LTCF participated for 3 years or more, 16 for 2 years and the remaining 12 LTCF for 1 year. During the study period, the median number of beds decreased from 158 to 139, whereas the percentage of residents with private bedrooms increased from 14% to 87%. UTIs were the most frequently reported infections, followed by (probable) pneumonia and gastroenteritis. Adjusted for calendar year and season, we observed a statistically significant decrease in the incidence of influenza-like illness (odds ratio (OR) = 0.8, P < 0.01) and (probable) pneumonia (OR = 0.8, P < 0.01) for each extra year an LTCF participated. Although there are other likely contributors, such as more private rooms and enhanced infection control measures, the decreasing trend of HAI in LTCFs participating in surveillance implies that surveillance is a valuable addition to current strategies to optimise infection control.

Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods: Comparison Study.

BackgroundTraditional surveillance systems produce estimates of influenza-like illness (ILI) incidence rates, but with 1- to 3-week delay. Accurate real-time monitoring systems for influenza outbreaks could be useful for making public health decisions. Several studies have investigated the possibility of using internet users’ activity data and different statistical models to predict influenza epidemics in near real time. However, very few studies have investigated hospital big data.ObjectiveHere, we compared internet and electronic health records (EHRs) data and different statistical models to identify the best approach (data type and statistical model) for ILI estimates in real time.MethodsWe used Google data for internet data and the clinical data warehouse eHOP, which included all EHRs from Rennes University Hospital (France), for hospital data. We compared 3 statistical models—random forest, elastic net, and support vector machine (SVM).ResultsFor national ILI incidence rate, the best correlation was 0.98 and the mean squared error (MSE) was 866 obtained with hospital data and the SVM model. For the Brittany region, the best correlation was 0.923 and MSE was 2364 obtained with hospital data and the SVM model.ConclusionsWe found that EHR data together with historical epidemiological information (French Sentinelles network) allowed for accurately predicting ILI incidence rates for the entire France as well as for the Brittany region and outperformed the internet data whatever was the statistical model used. Moreover, the performance of the two statistical models, elastic net and SVM, was comparable.

Shift Work and Respiratory Infections in Health-Care Workers

Recently, there has been interest in whether shift work may enhance susceptibility to infection. Our aim was to determine whether shift workers in the health-care field have a higher incidence, duration, and/or severity of influenza-like illness (ILI) and acute respiratory infection (ARI) than non–shift workers. From September 2016 to June 2017, 501 rotating and/or night-shift workers and 88 non–shift workers from the Klokwerk+ Study (the Netherlands, 2016–2017) registered the occurrence of ILI/ARI symptoms daily using a smartphone application. The incidence rate of ILI/ARI (defined as ≥2 symptoms on the same day/≥1 symptom on 2 consecutive days), the mean duration of each episode, and the incidence rate of severe episodes were compared between shift workers and non–shift workers using negative binomial regression and linear mixed-model analysis. In total, participants completed 110,347 diaries. Shift workers’ incidence rate of ILI/ARI was 1.20 (95% confidence interval (CI): 1.01, 1.43) times higher than that of non–shift workers, and for severe ILI/ARI episodes, shift workers’ incidence rate was 1.22 (95% CI: 1.01, 1.49) times higher. The mean duration of an ILI/ARI episode did not differ (ratio between means = 1.02, 95% CI: 0.87, 1.19). In conclusion, shift workers in health care had more ILI/ARI episodes and more severe ILI/ARI episodes than non–shift workers, but with a similar duration. Insight into underlying mechanisms connecting shift work and infection susceptibility will contribute to the design of preventive initiatives.

Effects of air pollutants on occurrences of influenza-like illness and laboratory-confirmed influenza in Hefei, China.

Accumulating evidence suggests that air pollution is a risk factor for adverse respiratory and cardiovascular health outcomes. However, the different impacts of exposure to air pollutants on influenza virus activity and influenza-like illness (ILI) have not been well documented in epidemiological studies. We examined the association between air pollutants of particular matters < 2.5μm (PM2.5), particular matters < 10μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and influenza occurrences in Hefei, China, from December 2013 to December 2015 by generalized Poisson additive regression models. The result suggested that PM2.5 and PM10 had similar effects on clinical ILI and influenza incidence. PM10 was negatively associated with clinical ILI (relative risk (RR) 0.980, 95% confidence interval (CI) 0.974-0.987), while PM2.5 were positively associated with clinical ILI (RR 1.040; 95% CI 1.032-1.049). RRs for the laboratory-confirmed cases of influenza were 0.813 (95% CI, 0.755-0.875) for PM10 and 1.216 (95% CI, 1.134-1.304) for PM2.5. Nevertheless, the impacts of SO2 and NO2 on ILI and influenza were distinct. SO2 had significant influence on laboratory-confirmed influenza and had no significant linear relationship with ILI. NO2 was negatively correlated with influenza but had no obvious effect on clinical ILI cases. The present study contributes novel evidence on understanding of the effects of various air pollutants on influenza activities, and these findings can be useful and important for the development of influenza surveillance and early warning systems.

The Association of Non-Cardiac ECMO With Influenza Incidence: A Time Series Analysis.

The 2009 H1N1 influenza epidemic saw a rise in the use of extracorporeal membrane oxygenation (ECMO) as a supportive therapy for refractory ARDS. We sought to determine whether ECMO utilization follows a seasonal pattern that matches the influenza season, and whether it can further be explained by the incidence of each influenza subtype. We performed a longitudinal analysis of non-cardiac and cardiac-associated ECMO cases from the National In-patient Sample from 2005 to 2014, using overdispersed Poisson regression to evaluate associations with influenza incidence categorized by influenza-like illness and total positive influenza tests divided by subtype from the Centers for Disease Control and Prevention. Non-cardiac ECMO use was positively associated with influenza-like illness incidence in the current month (incidence risk ratio [IRR] 1.11, 95% confidence interval [CI] 1.07-1.15, P < .001) and with influenza-like illness in the previous month (IRR 1.09, 95% CI 1.05-1.14, P < .001). The 2009 H1N1 subtype had the strongest association with non-cardiac ECMO (IRR 1.19, 95% CI 1.09-1.31, P < .001). Cardiac ECMO was also positively associated with the incidence of influenza-like illness (IRR 1.05, 95% CI 1.01-1.09, P = .02). Non-cardiac and cardiac ECMO use in the United States were significantly associated with influenza incidence. The influenza A, H1N1 2009, subtype had the strongest association.

Geographic transmission hubs of the 2009 influenza pandemic in the United States

A key issue in infectious disease epidemiology is to identify and predict geographic sites of epidemic establishment that contribute to onward spread, especially in the context of invasion waves of emerging pathogens. Conventional wisdom suggests that these sites are likely to be in densely-populated, well-connected areas. For pandemic influenza, however, epidemiological data have not been available at a fine enough geographic resolution to test this assumption. Here, we make use of fine-scale influenza-like illness incidence data derived from electronic medical claims records gathered from 834 3-digit ZIP (postal) codes across the US to identify the key geographic establishment sites, or “hubs”, of the autumn wave of the 2009 A/H1N1pdm influenza pandemic in the United States. A mechanistic spatial transmission model is fit to epidemic onset times inferred from the data. Hubs are identified by tracing the most probable transmission routes back to a likely first establishment site. Four hubs are identified: two in the southeastern US, one in the central valley of California, and one in the midwestern US. According to the model, 75% of the 834 observed ZIP-level outbreaks in the US were seeded by these four hubs or their epidemiological descendants. Counter-intuitively, the pandemic hubs do not coincide with large and well-connected cities, indicating that factors beyond population density and travel volume are necessary to explain the establishment sites of the major autumn wave of the pandemic. Geographic regions are identified where infection can be statistically traced back to a hub, providing a testable prediction of the outbreak's phylogeography. Our method therefore provides an important way forward to reconcile spatial diffusion patterns inferred from epidemiological surveillance data and pathogen sequence data.

Benefit of Inactivated Influenza Vaccine in Infants in Iran: A Community based Randomized Control Trial

Background: Influenza in infants and young children is a major medical problem which causes excess medical visits, antibiotic prescriptions and hospitalization even in otherwise healthy children. Many of the developed countries have recommended influenza vaccination for all children (>6month old), but the economic benefit of this strategy is not clear especially for developing countries. Objectives: To find the difference in the incidence of influenza-like illness (ILI) and economic cost related to it between TIV vaccinated and non-vaccinated infants in Mashhad, Iran. Methods: This was a community randomized controlled trial which was started in November 2005 and ended up at May 2006. Each of the study and control groups were composed of 500 infants between 6 month and 20 months old who were brought for routine vaccination. The study group was given two doses of TIV; the control group received routine care without any extra intervention. Both groups were followed by monthly telephone calls (up to six months after the vaccination) and were asked about signs and symptoms of flu like illnesses and any cost related to them. SPSS 11.5 was used for statistical analysis, P

Indoor Environmental Factors and Influenza-Like Illness in Community Dwelling Older Population of Hong Kong: A Prospective Cohort Study

Background: Previous studies have investigated the impacts of outdoor environmental factors (temperature, relative humidity (RH), absolute humidity (AH), rainfall) on seasonal variations of influenza virus activities. However, the findings were inconsistent to explain the circulation and summer surge of influenza in tropical and subtropical regions. We hypothesize that the controversial findings might be due to the lack of indoor environmental data. We conducted a prospective cohort study in community dwelling older people in Hong Kong to explore the relationship of indoor and outdoor environmental factors with incidence of influenza-like illness (ILI) in older people.Methods: A total of 231 older people aged 65&amp;#43; years in the Hong Kong Island were recruited as index participants from Dec 2016 - Apr 2017. Automatic sensors were installed in the living room of each household to continuously collect the hourly indoor temperature and RH during the study period. The follow-up is still ongoing and expected to end by May 2019.Results: Here we report the preliminary findings of the first-year follow-up data from Dec 2016 - Mar 2018. Mean indoor temperature, RH and AH were 24.4&amp;#176;C, 68.1% and 22.2g/m3 respectively. Indoor temperature and AH were highly correlated with outdoor temperature (r&amp;#61;0.95) and AH (r&amp;#61;0.95). While, indoor RH varied widely during June to September (difference 10.8% &amp;#177; 48.3) and less correlated with outdoor RH (r&amp;#61;0.67). The incidence rate of self-report influenza-like illness was 0.4 per person-year, and most were reported during May - Aug 2017 and Dec 2017 - Feb 2018. Preliminary results showed there was no significant difference between households with and without ILI cases, in terms of indoor environmental factors such as daily mean, minimum, median, maximum, variation of temperature, RH and AH.Discussion: Indoor-outdoor correlation was found high for temperature and AH but moderate for RH. Further analyses will be conducted when more data are collected.

Climatic factors and long-term trends of influenza-like illness rates in The Netherlands, 1970–2016

BackgroundClimatic factors affect the survival and transmissibility of respiratory viruses causing influenza-like illness (ILI), and we hypothesized that changes in absolute humidity and temperature may affect long-term trends of ILI incidence rate in temperate countries. We tested this hypothesis using ILI and meteorological time series in the Netherlands for the period 1970–2016. MethodsWe described the long-term trends of ILI incidence, absolute humidity and temperature; modelled the association between climatic factors and ILI activity using negative binomial regression models; and assessed the strength of the association between the seasonal average absolute humidity (or temperature) and ILI incidence rate using the Spearman's rank correlation coefficient. ResultsThe ILI incidence rate declined from 1970 and reached a minimum in the season 2002–03, but started to increase again from the season 2003–04 onwards. In the negative binominal regression models, the weekly ILI count was inversely associated (p < 0.001) with 0- and 1-week lagged absolute humidity and temperature. After three decades of rising absolute humidity and temperature (1970–2000), the early 2000s represented a trend-reversal point for the climatic time series. The seasonal average ILI incidence rate and absolute humidity (or temperature) were strongly (inversely) correlated. ConclusionsOur findings suggest that climate change may have played a role in the long-term trends of ILI incidence rates in the Netherlands, as we were able to show that lower humidity and temperature in a given week were associated with higher ILI incidence in the next week, there was a clear time point reversal in climatic parameters and ILI rates in the 2000s, and the average annual ILI incidence was inversely related to average annual temperatures and humidity.

Linking temperature and humidity to influenza-like illness: A long-term time series study in the Netherlands, 1970–2016

Introduction Climatic parameters affect the survival and transmissibility of respiratory viruses causing influenza-like illness (ILI), like influenza, respiratory syncytial virus and rhinovirus. In temperate countries, ILI activity is inversely associated with humidity and temperature (which affect both the onset and size of ILI epidemics), and we hypothesized that changes in the average values of these climatic parameters (which have occurred in Europe in recent decades) may explain the declining trends in ILI incidence rates observed during the same period. Here, we tested this hypothesis by linking ILI and climatic time series in the Netherlands for the period 1970–2016. Methods Influenza-like illness surveillance data for the period 1970–2016 were obtained from the Netherlands Institute for Health Services Research (NIVEL), which relies on a network of 60 sentinel general practitioners in 40 practices that are distributed throughout the Netherlands (including urban and rural areas) and cover approximately 0.7% of the Dutch population. Data on daily average absolute humidity (g/m3) and temperature for the weather station of De Bilt (which is located in the middle of the country) for the period 1970–2016 were obtained from the Royal Netherlands Meteorological Institute. Linear regression models were used to assess whether the season average ILI incidence rate changed over time, and whether there was any change over time in daily average absolute humidity and temperature. We modelled the association between climate and ILI activity through negative binomial regression models with the weekly ILI count as dependent variable, absolute humidity (or temperature) with up to three lagged weeks as independent variables, and covariates accounting for contagiousness of ILI-causing agents and presence of immunity. Model-based predictions were made using a leave-one-out cross-validation procedure. The study was funded by Sanofi-Pasteur. Results The season average ILI incidence rate declined significantly (P Conclusions Changes in absolute humidity and temperature were able to satisfactorily explain the long-term trends of ILI incidence rate in the Netherlands during 1970–2016. Temperate countries should monitor climate-related change in infectious diseases epidemiology so that measures to mitigate their impact can be planned and implemented.

Incidence of Healthcare-Associated Influenza-Like Illness After a Primary Care Encounter Among Young Children.

Despite potential respiratory virus transmission in pediatric clinics, little is known about the risk of healthcare-associated viral infections attributable to outpatient encounters. We evaluated whether exposure to a pediatric clinic visit was associated with subsequent influenza-like illness (ILI). Using electronic health record data, we conducted a retrospective cohort study of all children aged <6 years who presented to a provider in a 29-clinic pediatric primary care network for a non-ILI-related encounter over 2 respiratory virus seasons (September 1, 2012, to April 30, 2014). We defined a risk period for potential healthcare-associated (HA) ILI of 1 to 8 days after a non-ILI clinic visit and identified all cases of ILI to compare the incidences of ILI visits 1 to 8 days after a non-ILI encounter and those of visits >8 days after a non-ILI encounter. Among 149987 children <6 years of age (mean age, 2.5 years) with ≥1 non-ILI visit during the study period, 531928 total encounters and 13951 (2.9%) ILI encounters were identified; 1941 (13.9%) occurred within the HA-ILI risk window. The incidence rate ratios (IRRs) for ILI 1 to 8 days after compared with ILI >8 days after a non-ILI visit during season 1 were 1.36 (95% confidence interval, 1.22-1.52) among children ≥2 years of age and 1.01 (95% confidence interval, 0.93-1.09) among children <2 years of age. Estimates remained consistent during season 2 and with a risk window of 3, 4, or 9 days. Pediatric clinic visits during a respiratory virus season were significantly associated with an increased incidence of subsequent ILI among children aged 2 to 6 years but not among those aged <2 years. These findings support the hypothesis that respiratory virus transmission in a pediatric clinic can result in HA ILI in young children.

Real-time predictive seasonal influenza model in Catalonia, Spain.

Influenza surveillance is critical to monitoring the situation during epidemic seasons and predictive mathematic models may aid the early detection of epidemic patterns. The objective of this study was to design a real-time spatial predictive model of ILI (Influenza Like Illness) incidence rate in Catalonia using one- and two-week forecasts. The available data sources used to select explanatory variables to include in the model were the statutory reporting disease system and the sentinel surveillance system in Catalonia for influenza incidence rates, the official climate service in Catalonia for meteorological data, laboratory data and Google Flu Trend. Time series for every explanatory variable with data from the last 4 seasons (from 2010–2011 to 2013–2014) was created. A pilot test was conducted during the 2014–2015 season to select the explanatory variables to be included in the model and the type of model to be applied. During the 2015–2016 season a real-time model was applied weekly, obtaining the intensity level and predicted incidence rates with 95% confidence levels one and two weeks away for each health region. At the end of the season, the confidence interval success rate (CISR) and intensity level success rate (ILSR) were analysed. For the 2015–2016 season a CISR of 85.3% at one week and 87.1% at two weeks and an ILSR of 82.9% and 82% were observed, respectively. The model described is a useful tool although it is hard to evaluate due to uncertainty. The accuracy of prediction at one and two weeks was above 80% globally, but was lower during the peak epidemic period. In order to improve the predictive power, new explanatory variables should be included.

Vaccines for preventing influenza in healthy adults.

Vaccines for preventing influenza in healthy adults.

Performances of statistical methods for the detection of seasonal influenza epidemics using a consensus-based gold standard.

Influenza epidemics are monitored using influenza-like illness (ILI) data reported by health-care professionals. Timely detection of the onset of epidemics is often performed by applying a statistical method on weekly ILI incidence estimates with a large range of methods used worldwide. However, performance evaluation and comparison of these algorithms is hindered by: (1) the absence of a gold standard regarding influenza epidemic periods and (2) the absence of consensual evaluation criteria. As of now, performance evaluations metrics are based only on sensitivity, specificity and timeliness of detection, since definitions are not clear for time-repeated measurements such as weekly epidemic detection. We aimed to evaluate several epidemic detection methods by comparing their alerts to a gold standard determined by international expert consensus. We introduced new performance metrics that meet important objective of influenza surveillance in temperate countries: to detect accurately the start of the single epidemic period each year. Evaluations are presented using ILI incidence in France between 1995 and 2011. We found that the two performance metrics defined allowed discrimination between epidemic detection methods. In the context of performance detection evaluation, other metrics used commonly than the standard could better achieve the needs of real-time influenza surveillance.

Effects of Lactobacillus coryniformis K8 CECT5711 on the immune response to influenza vaccination and the assessment of common respiratory symptoms in elderly subjects: a randomized controlled trial

PurposeElderly people are particularly vulnerable to seasonal influenza. Therefore, vaccination is strongly recommended. However, the vaccine efficacy is lower in the elderly, owing to immunosenescence. The objective of the present study was to evaluate the ability of the probiotic strain Lactobacillus coryniformis K8 CECT5711 to enhance the immune response to the influenza vaccine in the elderly and to assess the effects on symptoms related to respiratory infections.MethodsA randomized, double-blind, placebo-controlled trial was conducted between November 2015 and April 2016. A total of 98 nursing home residents, more than 65 years of age were randomly assigned to receive L. coryniformis K8 CECT5711 (3 × 109 CFU/day) or a placebo for 2 weeks before influenza vaccination. The primary outcome was the percentage of seroconversion. The secondary outcomes were the incidence of influenza-like illness (ILI) and respiratory symptoms associated with respiratory infections during the 5-month follow-up period. The serum cytokine and immunoglobulin levels were also evaluated.ResultsThe percentage of responders to vaccination was higher in the probiotic group than in the control group (p = 0.036). L. coryniformis ingestion was associated with a significantly lower incidence of respiratory symptoms commonly associated with respiratory infections (p = 0.007) and lower consumption of analgesics (p = 0.008).ConclusionThe administration of L. coryniformis K8 CECT5711 to an elderly population increased the immune response against the influenza vaccine and decreased symptoms associated with respiratory infections. Probiotic administration may be a natural and safe strategy to improve the efficacy of vaccines and to protect against common respiratory infections in susceptible populations.

Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe.

BackgroundThe wide availability of the Internet and the growth of digital communication technologies have become an important tool for epidemiological studies and health surveillance. Influenzanet is a participatory surveillance system monitoring the incidence of influenza-like illness (ILI) in Europe since 2003. It is based on data provided by volunteers who self-report their symptoms via the Internet throughout the influenza season and currently involves 10 countries.ObjectiveIn this paper, we describe the Influenzanet system and provide an overview of results from several analyses that have been performed with the collected data, which include participant representativeness analyses, data validation (comparing ILI incidence rates between Influenzanet and sentinel medical practice networks), identification of ILI risk factors, and influenza vaccine effectiveness (VE) studies previously published. Additionally, we present new VE analyses for the Netherlands, stratified by age and chronic illness and offer suggestions for further work and considerations on the continuity and sustainability of the participatory system.MethodsInfluenzanet comprises country-specific websites where residents can register to become volunteers to support influenza surveillance and have access to influenza-related information. Participants are recruited through different communication channels. Following registration, volunteers submit an intake questionnaire with their postal code and sociodemographic and medical characteristics, after which they are invited to report their symptoms via a weekly electronic newsletter reminder. Several thousands of participants have been engaged yearly in Influenzanet, with over 36,000 volunteers in the 2015-16 season alone.ResultsIn summary, for some traits and in some countries (eg, influenza vaccination rates in the Netherlands), Influenzanet participants were representative of the general population. However, for other traits, they were not (eg, participants underrepresent the youngest and oldest age groups in 7 countries). The incidence of ILI in Influenzanet was found to be closely correlated although quantitatively higher than that obtained by the sentinel medical practice networks. Various risk factors for acquiring an ILI infection were identified. The VE studies performed with Influenzanet data suggest that this surveillance system could develop into a complementary tool to measure the effectiveness of the influenza vaccine, eventually in real time.ConclusionsResults from these analyses illustrate that Influenzanet has developed into a fast and flexible monitoring system that can complement the traditional influenza surveillance performed by sentinel medical practices. The uniformity of Influenzanet allows for direct comparison of ILI rates between countries. It also has the important advantage of yielding individual data, which can be used to identify risk factors. The way in which the Influenzanet system is constructed allows the collection of data that could be extended beyond those of ILI cases to monitor pandemic influenza and other common or emerging diseases.

Outbreak detection and evaluation of a school-based influenza-like-illness syndromic surveillance in Tianjin, China.

School-based influenza-like-illness (ILI) syndromic surveillance can be an important part of influenza community surveillance by providing early warnings for outbreaks and leading to a fast response. From September 2012 to December 2014, syndromic surveillance of ILI was carried out in 4 county-level schools. The cumulative sum methods(CUSUM) was used to detect abnormal signals. A susceptible-exposed-infectious/asymptomatic-recovered (SEIAR) model was fit to the influenza outbreak without control measures and compared with the actual influenza outbreak to evaluate the effectiveness of early control efforts. The ILI incidence rates in 2014 (14.51%) was higher than the incidence in 2013 (5.27%) and 2012 (3.59%). Ten school influenza outbreaks were detected by CUSUM. Each outbreak had high transmissibility with a median Runc of 4.62. The interventions in each outbreak had high effectiveness and all Rcon were 0. The early intervention had high effectiveness within the school-based ILI syndromic surveillance. Syndromic surveillance within schools can play an important role in controlling influenza outbreaks.

Hispanic Use of Alternative Medicine as Demonstrated in Internet Searches

Objective: We investigated how cultural shifts occur with respect to the use of traditional medicine for influenza-like illness (ILI) within the Latino population near the US-Mexico border. Methods: We extracted searches of ILI treatments (modern, traditional western, and traditional Hispanic) to the Bing search engine from 5 US states near the US-Mexico border. The incidence of these searches was correlated with county-level demographic data and ILI incidence. Results: The fraction of queries related to Hispanic medicines is correlated with the distance from the US-Mexico border (Spearman rho = -0.24), which is a slower decay than that observed in the use of Spanish (Spearman rho = -0.35). Demographic and socioeconomic factors predict different searches for ILI treatments. Conclusions: People of Hispanic origin rely on traditional Hispanic medicines when treating ILI. Medical providers should guide their patients when such treatments might be clinically detrimental to patients, and know their patients are likely using such medicines.

Coughing, sneezing, and aching online: Twitter and the volume of influenza-like illness in a pediatric hospital.

This study investigates the relation of the incidence of georeferenced tweets related to respiratory illness to the incidence of influenza-like illness (ILI) in the emergency department (ED) and urgent care clinics (UCCs) of a large pediatric hospital. We collected (1) tweets in English originating in our hospital’s primary service area between 11/1/2014 and 5/1/2015 and containing one or more specific terms related to respiratory illness and (2) the daily number of patients presenting to our hospital’s EDs and UCCs with ILI, as captured by ICD-9 codes. A Support Vector Machine classifier was applied to the set of tweets to remove those unlikely to be related to ILI. Time series of the pooled set of remaining tweets involving any term, of tweets involving individual terms, and of the ICD-9 data were constructed, and temporal cross-correlation between the social media and clinical data was computed. A statistically significant correlation (Spearman ρ = 0.23) between tweets involving the term flu and ED and UCC volume related to ILI 11 days in the future was observed. Tweets involving the terms coughing (Spearman ρ = 0.24) and headache (Spearman ρ = 0.19) individually were also significantly correlated to ILI-related clinical volume four and two days in the future, respectively. In the 2014–2015 cold and flu season, the incidence of local tweets containing the terms flu, coughing, and headache were early indicators of the incidence of ILI-related cases presenting to EDs and UCCs at our children’s hospital.

Influenza-like Illness Incidence Is Not Reduced by Influenza Vaccination in a Cohort of Older Adults, Despite Effectively Reducing Laboratory-Confirmed Influenza Virus Infections.

Data on the relative contribution of influenza virus and other respiratory pathogens to respiratory infections in community-dwelling older adults (≥60 years) are needed. A prospective observational cohort study was performed in the Netherlands during 2 winters. Nasopharyngeal and oropharyngeal swabs were collected during influenza-like illness (ILI) episodes and from controls. Viruses and bacteria were identified by multiplex ligation-dependent probe amplification assay and conventional bacterial culture. The ILI incidence in the consecutive seasons was 7.2% and 11.6%, and influenza virus caused 18.9% and 34.2% of ILI episodes. Potential pathogen were detected in 80% of the ILI events with influenza virus, coronaviruses, rhinoviruses, human metapneumovirus, respiratory syncytial virus, parainfluenza viruses, and Haemophilus influenzae being the most common. Influenza vaccination reduced influenza virus infection by 73% (95% confidence interval [CI], 26%-90%) and 51% (95% CI, 7%-74%) in ILI patients. However, ILI incidence was similar between vaccinated (7.6% and 10.8%) and nonvaccinated (4.2% and 11.4%) participants in 2011-2012 and 2012-2013, respectively (P > .05). Influenza virus is a frequent pathogen in older adults with ILI. Vaccination reduces the number of influenza virus infections but not the overall number of ILI episodes: other pathogens fill the gap. We suggest the existence of a pool of individuals with high susceptibility to respiratory infections. NTR3386.