in most winters , influenza causes substantial morbidity and mortality [ 1 , 2 ] , with 
 widely variable clinical manifestations ranging from subclinical infection to fatal illness 
 . although many persons become infected , 
 seroprevalence studies indicate that only a minority make use of health services . nevertheless , those that do create considerable 
 pressure on both primary- and secondary - care services [ 5 , 6 ] . the risk of serious illness involving 
 hospital admission or death is thought to be higher in persons with chronic illness , but the total impact of influenza on health services 
 comes at least as much from otherwise healthy persons . in the uk this impact is concentrated in a comparatively short epidemic period 
 of around 8 weeks , creating surge pressures on 
 health services , commonly in midwinter , when the impact of other respiratory viral 
 infections is also highest . policies to prevent and treat influenza need to accommodate the varying threat from 
 different virus strain types , changes in severity of epidemics over time , advances in 
 vaccines , the ageing population , increasing population expectancies from healthcare and 
 changes in healthcare delivery . these factors interact to influence the cost effectiveness 
 of medical intervention , and create the need to update burden assessments on a continuing 
 basis using measurements from several seasons . most estimates of the influenza burden employ modelling methods in which the identification 
 of the influenza epidemic period is determined from available virology data and the impact 
 measured in the commensurate changes in the chosen outcome [ 1115 ] . in some modelling 
 studies , influenza virus data have been used exclusively , but the confounding effect of 
 other viruses has prompted the inclusion of data for other viruses , especially respiratory 
 syncytial virus ( rsv ) . in a few studies , this study aims to provide a comprehensive analysis of the burden of persons 
 consulting a general practitioner ( gp ) for a cause attributable to influenza over many 
 seasons , to inform cost - benefit analyses of vaccination and treatment interventions . we used 
 consultation data from the clinical practice research datalink ( cprd ) and virology data from 
 public health england ( phe ) in a linear regression model to estimate influenza - attributable 
 consultations and antibiotic prescriptions over 14 seasons , while controlling for rsv and 
 other seasonal variables , and stratifying the analyses by age , comorbidity risk and 
 influenza vaccination status . viral surveillance time - series regression models were used to estimate the number of 
 persons consulting a gp for influenza - attributable respiratory disease in england in each 
 season ( july in the index year through june the following year ) , from 1995 to 2009 , 
 stratifying by age , risk status and vaccination status ( www.clinicaltrials.gov : nct01520935 ) . seasons after july 2009 were not included as 
 we were concerned to establish the normal or average seasonal burden of influenza , which 
 was disturbed by the pandemic experience in summer 2009 . at the midpoint of the study ( january 2001 ) the monitored population was around 37 
 million . influenza reports are based on 
 regular returns of virus swab - positive tests to phe , mainly from community - based 
 investigation of persons with influenza - like illness . rsv reports are mainly confirmed 
 infections in young children admitted to hospital with respiratory infections . all analyses of cprd were restricted to english practices to match the coverage of 
 virology data . a gp episode was counted as the first in a series of consultations for a particular 
 diagnosis / diagnostic group . a minimum of 28 days was required following any previous 
 consultation for that same diagnosis / diagnostic group before defining a new episode . diagnostic read codes were combined into respiratory diagnoses consistent with recognized 
 icd-10 groupings ( table 1 ) ( see supplementary 
 material ) . we undertook a preliminary search of records to find codes that increased 
 during influenza active periods . our  respiratory disease broadly defined outcome 
 included all disorders in the icd-10 respiratory disease chapter , otitis media , as well as 
 selected presenting symptom codes we found were used by some gps in lieu of specifying a 
 clinical diagnosis . a negative control outcome ( urinary tract infection ) with no seasonal 
 pattern and association with influenza was included to control for the possibility of bias 
 in model attribution over the entire study period . table 1.outcomes : general practitioner consultations ( cprd)*outcomeicd-10 codes 
 respiratory diseases 
 respiratory disease  broadly 
 defined : resp  dis  +  symptoms  +  sepsisj0099 , r0506 , b34 , a4041 , p36  respiratory diseasej0099  acute upper respiratory  diseasej00 , j0206  pneumonia and influenzaj0918  bronchitis / bronchiolitisj2022 , j40  influenza - like illnessj0911 , b34 
 non - respiratory diseases 
 otitis mediah6566 , h70  urinary tract infectionn39 
 drug prescriptions 
 antibiotics ( broad  spectrum penicillins , 
 macrolides ,  tetracyclines ) 
 risk factor definitions 
 chronic heart disease ; renal ; diabetes 
 ( diagnosis / monitoring ) ; liver ; stroke / tia ; ms - cns ; copd_no_asthma ; asthma ; 
 immuno ; immuno_suppressant treatment ; anti - asthmatic treatment*any clinical practice research datalink ( cprd ) gp episode , including office 
 visits , home visits , telephone consults and other types , for subjects registered 
 with research quality data in cprd . cprd diagnostic data are coded using read 
 codes selected to correspond to icd-10 definitions . outcomes : general practitioner consultations ( cprd ) * any clinical practice research datalink ( cprd ) gp episode , including office 
 visits , home visits , telephone consults and other types , for subjects registered 
 with research quality data in cprd . cprd diagnostic data are coded using read 
 codes selected to correspond to icd-10 definitions . time - series of numbers of prescriptions of broad spectrum penicillin , tetracycline and 
 macrolide antibiotics , which are widely prescribed for acute respiratory infections , were 
 also examined as an outcome category . the cprd dataset contains unique patient identifiers , allowing patients to be followed 
 longitudinally . since almost all influenza vaccination during the study period was 
 undertaken by gps and recorded using specific codes , we were able to check the vaccination 
 status for each person in each season . vaccine coverage in the cprd population was used to 
 estimate the vaccination coverage in each age - risk stratum . we also externally validated 
 the cprd vaccination coverage estimates against national data on vaccination coverage 
 . we classified each patient as  high or 
  low risk by the prior occurrence of diagnoses that would prioritize the patient to 
 receive influenza vaccination by reference to the accumulated historical records in the 
 database ( table 1 ) . the cprd covers a population which is representative of england in age and gender 
 distribution and is thus a suitable population - denominated database for the assessment of 
 vaccination status and national patterns of comorbidity in age- and gender - specific groups 
 . we found excellent agreement between cprd 
 and independent data sources for the uk with respect to the population age structure , the 
 prevalence of various risk factors , and influenza vaccination coverage ; for example , cprd 
 data yielded an average vaccination rate of 71% for persons aged 65 years for the years 
 20012008 , in close agreement with phe estimates . the 2001 uk population ( office of national statistics ) was thus used to weight the english cprd population by age to 
 reflect the uk profile . weekly 
 time - series of the number of specimens positive for influenza a , influenza b and rsv were 
 generated using phe virology surveillance data . weekly time - series for multiple 
 influenza - related health outcomes ( table 1 ) were 
 generated from the cprd for age groups < 5 , 517 , 1849 , 5064 , and 65 years ( for 
 selected analyses age groups 6574 and 75 were examined separately ) and low-/high - risk 
 groups . a multiple linear regression model was applied to each age group to associate gp 
 episodes to influenza a or b , while controlling for rsv and unspecified seasonal factors 
 ( fig . major changes in virus detection 
 methodology were undertaken by phe in 2001 ; thus , to avoid bias the model separated the 
 periods before and after this date :   where , y is the incidence ( rate ) of outcome definition 
 for each time period t ( weeks ) , rsv and influenza are the proportion of 
 laboratory isolates during t , sin and cos are harmonic functions of 
 t , and the remaining terms track other types of secular trends in the 
 data . the time period t used in the model is a running index of weeks 
 starting 1 october 1997 and ending 31 march 2009 . 1.attribution modelling showing excess gp episodes attributable to influenza a and b 
 and respiratory syncytial virus ( rsv ) in children aged 517 years . attribution modelling showing excess gp episodes attributable to influenza a and b 
 and respiratory syncytial virus ( rsv ) in children aged 517 years . p1ainfluenza a(pre - july 
 2001 )  +  p1binfluenza 
 a(post - july 2001 ) are influenza terms pre- and post - july , 2001 . the rsv terms control for 
 rsv epidemics . influenza a , influenza b and rsv are observed counts of positive tests from 
 the phe labbase dataset . outcome and pathogen series were tri - mean - smoothed , i.e. the smoothed value of 
 x at week t is 
 ( xt1  +  xt  +  xt+1)/3 . the week numbers ( t ) were calculated 
 as iso 8601  v - weeks . the weekly attribution to each virus was computed as the product of 
 the observed value of the explanatory variable ( i.e. number of positive virology samples ) 
 and the corresponding regression coefficient 
 ( p1ap2b ) , 
 and the weekly estimates summed to produce the seasonal estimates . the variability of 
 seasonal estimates was assessed using standard deviations but limited to all - age 
 estimates . this standard deviation represents the variability of the attributable burden 
 between seasons and not the uncertainty of the individual seasonal estimates . results were 
 expressed as numbers of persons consulting a gp ( gp episodes ) and as the mean seasonal 
 ( from september to mid - may ) rates of persons consulting a gp per 100  000 population . outside pandemics , influenza is exclusively a winter illness and thus summertime data 
 were excluded from the analysis . previous evidence suggests that winter increases in the 
 incidence of rsv - associated outcomes ( e.g. acute bronchitis ) in adults follow those in 
 children by 23 weeks . therefore , for age 
 groups aged 18 years , we lagged the rsv time - series by 2 weeks and achieved an improved 
 model fit ; we did not lag the influenza time - series as doing so did not substantially 
 alter model fit or influenza burden attributions . the time - series of prescriptions of 
 antibiotics was modelled in the same way as the health outcome time - series to estimate 
 antibiotic prescribing attributable to influenza . the model did not attribute any positive 
 influenza burden to the control outcome ( urinary tract infection ) . the protocol was approved by the independent scientific advisory committee of the 
 clinical practice research datalink ( cprd , formerly the general practice research 
 database ) . the onset of the influenza epidemic period usually followed rsv , and influenza a usually 
 preceded influenza b ( illustrated for the 517 years age group in fig . the goodness - of - fit was assessed using adjusted r. the model 
 fit in most strata was very good , with adjusted r between 
 075 and 086 for the respiratory broad outcome ( supplementary table s1 ) . moreover , we 
 found a substantial  lift in the adjusted r value when 
 introducing the virology terms into the base secular model . we did not adjust the model 
 form ( by including or excluding terms ) individually for each outcome , age , and risk 
 stratum , but applied the given form across all strata . in a mean season there were an estimated 857  996 gp episodes in persons of all ages ( 15% 
 of the population ) for influenza - attributable respiratory disease ( broadly defined ) , of 
 which around 75% ( 649  219 ) were for influenza a ( table 
 2 ) . there was wide inter - seasonal variability in influenza a- and b - attributable 
 gp episodes , compared to a more stable consulting rate for rsv ( fig . 2 ) . in the seasons studied the number of gp episodes for an 
 influenza - attributable respiratory disease ranged between 174  305 ( 20022003 ) and 
 1  340  937 ( 19951996 ) for influenza a , and between 2075 ( 19971998 ) and 646  457 
 ( 19961997 ) for influenza b. the highest rates of gp episodes for influenza a - attributable 
 respiratory disease were observed in children aged < 5 years ( table 2 ) . the highest seasonal incidence rates for influenza b were 
 observed in those aged 517 years . 2.seasonal rates ( with 95% confidence intervals ) of gp episodes for respiratory 
 disease ( broadly defined ) attributable to influenza a , influenza b and respiratory 
 syncytial virus ( rsv ) . table 2.persons consulting a general practitioner in a mean season ( number and rate/100  000 
 population ) attributable to influenza in the uk , by age ( 19952009)influenza ainfluenza boutcomeage , yrn ( s.d.)rate ( s.d.)n ( s.d.)rate ( s.d.)respiratory diseasebroadly 
 defined0484  806243618  781539517120  151121798  3809961849234  47689975  1602885064110  768107618  38617965102  5131140681076all ages649  219 ( 366  681)1105 ( 624)208  777 ( 218  110)355 ( 371)bronchitis andbronchiolitis0410  0272880051717  07817310  058102184964  17924618  77472506450  6404926603646563  621707373542all ages210  607 ( 137  270)359 ( 234)38  120 ( 46  417)65 ( 79)influenza - like illness0421  955631426012251733  15333619  103193184991  20235025  95499506438  0453696100596525  589284211023all ages209  154 ( 146  553)356 ( 250)55  969 ( 61  902)95 ( 105)pneumonia andinfluenza04892325612473651719  991202897891184973  27328120  18177506432  3943154521446525  722286215824all ages161  228 ( 123  129)274 ( 210)36  541 ( 43  993)62 ( 75)otitis media0418  202523658918951719  09319315  0411521849881634292411506487891052106515823153all ages44  534 ( 25  065)76 ( 43)24  243 ( 28  284)41 ( 48)antibioticprescriptions0449  759142912  13034851769  00869959  4276021849159  65061254  858210506493  80691115  2861486588  172980554762all ages461  839 ( 262  785)786 ( 447)142  203 ( 162  168)242 ( 276)n , number of episodes ; seasonal rates ( with 95% confidence intervals ) of gp episodes for respiratory 
 disease ( broadly defined ) attributable to influenza a , influenza b and respiratory 
 syncytial virus ( rsv ) . persons consulting a general practitioner in a mean season ( number and rate/100  000 
 population ) attributable to influenza in the uk , by age ( 19952009 ) n , number of episodes ; s.d . , standard deviation . the rate of gp episodes for influenza a - attributable respiratory disease tended to 
 increase after age 50 years , whereas gp episodes for influenza b - attributable respiratory 
 disease decreased with age ( table 2 ) . in the 75 
 years age group , the rate of gp episodes for respiratory disease was 1255/100  000 for 
 influenza a and 93/100  000 for influenza b. in a mean season , the rate of gp episodes for influenza a - attributable bronchitis was 
 higher in adults than in children , whereas the rate of gp episodes for influenza - like 
 illness was higher in children than adults ( table 
 2 ) . the rates of influenza a - attributable gp episodes for  pneumonia and influenza 
 were higher in adults than in children . in those aged 75 years , the mean seasonal rate of 
 gp episodes for  pneumonia and influenza was 309/100  000 for influenza a , and 24/100  000 
 for influenza b. influenza a and b contributed to 68  777 gp episodes for otitis media per season , with the 
 highest number in children ( table 2 ) . around one 
 third of the gp episodes for otitis media were attributed to influenza b. there were 604  042 prescriptions for antibiotics attributed to influenza - associated 
 respiratory disease ( as measured in the broad respiratory outcome ) per season across all 
 age groups ( table 2 ) . individuals with comorbid conditions that put them at high risk of severe influenza 
 infection were more likely to consult a gp for an influenza - attributable respiratory 
 disease than individuals at low risk ( table 3 ) . the exceptions were children aged < 5 years for influenza a , and adults aged 5064 
 years for influenza b. the average seasonal rates of influenza a - attributable gp episodes 
 in the unvaccinated high comorbid risk group were 179- , 156- and 183-fold higher than 
 in the low comorbid risk group for older adults aged 5064 , 6574 and 75 years , 
 respectively . trends for influenza b were similar for the 6574 and 75 years age groups 
 ( 174- and 297-fold higher rates in high comorbid risk group , respectively ) . table 3.persons consulting a general practitioner in a mean season ( rate/100  000 
 population ) for outcomes attributed to influenza a and b by comorbid risk statusinfluenza ainfluenza boutcomeage , yrlow risk ( s.d.)high risk ( s.d.)low risk ( s.d.)high risk ( s.d.)respiratory broadly defined042482171352874551711661562953131518498311454286309506494815341921416588914396798all ages1024 ( 569)1464 ( 920)374 ( 390)289 ( 299)bronchitis and bronchiolitis04279417095517148335911811849212523699850644117786565655169343160all ages275 ( 179)718 ( 496)62 ( 74)82 ( 103)influenza - like illness0461582812114951731646518625218493305159712150643394826055652423372126all ages339 ( 231)435 ( 341)99 ( 109)81 ( 91)pneumonia and influenza042483623544517189295881101849264425759750642854254541652263621832all ages251 ( 187)383 ( 316)63 ( 76)58 ( 72)s.d . , standard deviation . persons consulting a general practitioner in a mean season ( rate/100  000 
 population ) for outcomes attributed to influenza a and b by comorbid risk status s.d . , standard deviation . higher rates of gp episodes were observed in all age groups when comorbid risk factors 
 were present than when they were absent for the other outcomes studied . between 2000 and 2008 influenza vaccine coverage in the cprd population aged 65 years 
 ranged between 64% and 76% , which was similar to coverage estimated by phe . in each season studied the rate of influenza 
 a - attributable gp episodes in the high comorbid risk group aged 1849 years was 06- to 
 089-fold lower in vaccinated compared to unvaccinated individuals . the rate ratio of 
 influenza a - attributable gp episodes in the high comorbid risk group in vaccinated over 
 unvaccinated individuals was between 074 and 076 in those aged 5064 years , and 
 081085 in those aged 65 years . similarly , in these age groups the rate of gp episodes was lower in vaccinated 
 vs. unvaccinated persons at low risk : the rate ratio of influenza - a 
 attributable gp episodes in the low comorbid risk group in vaccinated over unvaccinated 
 was 0781 in those aged 1849 years , 079092 in those aged 5064 years , and 076098 
 in those aged 65 years . a wide spectrum of diseases that resulted in a gp episode was attributable to influenza a 
 and b ( fig . 3 ) . the relative proportions 
 attributable to influenza a and b varied with the gp - reported diagnoses , highlighting the 
 importance of influenza b in the 517 years age group ; especially so since influenza b 
 seasons are less frequent than influenza a. fig . 3.the percentage of the estimated burdens for several outcomes attributed to 
 influenza a and influenza b by five age groups ( mean across seasons ) . the total 
 number of gp episodes for each outcome was : respiratory disease ( broadly defined ) 
 ( n  =  857  996 ) , bronchitis and bronchiolitis 
 ( n  =  248  727 ) , influenza - like illness 
 ( n  =  265  123 ) , pneumonia and influenza 
 ( n  =  197  769 ) , otitis media ( n  =  68  777 ) , 
 antibiotic use ( n  =  604  042 ) . the percentage of the estimated burdens for several outcomes attributed to 
 influenza a and influenza b by five age groups ( mean across seasons ) . the total 
 number of gp episodes for each outcome was : respiratory disease ( broadly defined ) 
 ( n  =  857  996 ) , bronchitis and bronchiolitis 
 ( n  =  248  727 ) , influenza - like illness 
 ( n  =  265  123 ) , pneumonia and influenza 
 ( n  =  197  769 ) , otitis media ( n  =  68  777 ) , 
 antibiotic use ( n  =  604  042 ) . we used the cprd in the uk , a promising but as yet underutilized nationally representative 
 database for influenza burden assessment , to estimate the age - specific influenza burden in 
 primary care . we employed traditional methods 
 used for hospitalization and mortality studies , and applied them to time - series of gp 
 episodes for a diverse range of outcomes forming part of the burden of influenza , such as 
 comorbidity risk status and antibiotic prescriptions , after taking account of the 
 potentially confounding effects of rsv . in a mean season , around 15% of the uk population 
 were estimated to present to gps with diverse respiratory syndromes attributable to 
 influenza a or b. the estimated mean seasonal burden of influenza a was much larger than 
 influenza b in all age groups and for most respiratory outcomes . approximately 07% of 
 children aged < 5 years were estimated to consult a gp for influenza - related otitis 
 media in a mean season , and nearly 2% of all children received antibiotic prescriptions 
 which were attributable to influenza . compared to the relatively stable disease burden 
 attributable to rsv in each season , the influenza burden was characterized by marked 
 inter - seasonal variability according to epidemic activity . that used the cprd data 
 source to study gp office visits examined only a single season ( 20022003 ) . in that study , this is higher 
 than our estimate for that season of 330  763 gp episodes , but closer to our mean seasonal 
 estimate encompassing 14 seasons . as well as the inherent instability of estimates produced 
 using a single season , the model used by pitman et al . reported two alternative estimates obtained by 
 models with and without a bacterial pathogen series included in the explanatory variables . the bacterial series , 
 characterized by a dominant sinusoidal pattern , likely affected the influenza burden 
 estimate similarly to our use of cyclic components . estimates of the number of persons infected with influenza in an average season vary 
 widely , but when measured as persons consulting with clinical illness they are mostly less 
 than 5% of the population , depending on the diagnostic outcomes measured [ 8 , 9 , 21 , 22 ] . our 
 findings are consistent with a simpler analysis conducted in a database of the royal college 
 of general practitioners , which estimated an influenza burden affecting 21% of the 
 population of england and wales in seasons 19891999 . we observed that in persons with comorbid conditions that placed them in a high risk group 
 and in all persons aged < 65 years , there were fewer gp episodes for 
 influenza - attributable respiratory disease in vaccinated than non - vaccinated persons . this 
 finding is difficult to interpret because our study was not designed to measure vaccine 
 effectiveness , which would require a different study design . such studies would require an 
 analysis of the propensity to consult , which differs between vaccinated and non - vaccinated 
 persons , and between those with high and those with low comorbidity risk . population - based studies of the influenza burden relying on individual laboratory - confirmed 
 cases alone are not practical , due to the lack of standard testing , the expense of 
 large - scale testing using sensitive pcr - based assays , and the fact that infections are often 
 resolved by the time patients seek medical care ( if they seek such care at all ) . instead , 
 indirect modelling approaches have been used for many years to estimate the burden of 
 influenza [ 12 , 23 ] . we used a previously described linear regression model , which adopted a recent refinement of regression techniques guided 
 by virus surveillance data as described in studies by pitman et al .   and other models used to estimate the burden of 
 respiratory infections , such as poisson regression with a natural logarithm for the link 
 function [ 11 , 26 ] , imply multiplicative effects of respiratory viruses ( i.e. the effect of 
 multiple simultaneously circulating respiratory viruses is different from the sum of their 
 individual effects ) . the 
 linear regression model has the advantage over other methods of being an additive model , 
 which corresponds to the view that the total burden in the population is due to the sum of 
 outcomes due to different causes , including viral infections [ 27 , 29 ] . the strengths of our model include the use of large nationally representative databases , 
 which limited the potential for sampling error ; inclusion of data over a long period that 
 covered 14 seasons ; and the use of control outcomes with no inherent seasonality and no 
 association to influenza . by defining a new outcome category (  respiratory disease broadly 
 defined ) , we aimed to improve the sensitivity in capturing the full burden of 
 influenza - attributable disease , while retaining sufficient specificity ; for example , the 
 additional codes in the  respiratory broad outcome increased the average seasonal all - age 
 estimate by 14% over the stricter  respiratory outcome , but left the confidence intervals 
 and the model fit virtually unchanged ( data not shown ) . age stratification allowed detailed 
 estimation of the age - specific burden , controlled for the observed age effect on 
 consultation rates and overcame possible confounding due to higher frequency of viral 
 testing in some age groups . finally , weekly occurrences of outcomes were assumed to be 
 determined by the circulation of influenza , rsv , and other causes which follow a seasonality 
 that was estimated using a combination of sine and cosine terms . the inclusion of both 
 cyclical terms ( sine and cosine functions ) controlled for confounders for which data are not 
 available . tri - mean smoothing of pathogens and outcomes series mitigated short - term effects 
 such as national holidays and extreme weather conditions on viral testing and gp 
 consultations . a potential limitation of the study is the exclusive analysis of influenza and rsv virus 
 time - series with no consideration of other respiratory pathogens ; if such pathogens 
 consistently circulate at the same time as influenza , the influenza burden could be 
 overestimated . we did not generate time - series for influenza subtypes as we did not have 
 access to subtyped data . we did not evaluate the effect of pneumococcal vaccination in 
 children or older age groups , or consider 
 changes in herd immunity during the period of study , nor did we consider the effects of 
 obesity [ 31 , 32 ] . the study is also dependent on the quality and consistency of routine recording 
 in the practice network . the burden of illness as encountered in primary care , which is the 
 primary objective of this study , includes all consulting persons regardless of their 
 propensity to consult . we did not study the indirect burden of illness in individuals with 
 influenza who did not consult . while our study provides up - to - date and detailed information 
 on health service utilization , the study does not provide information for evaluation of 
 indirect medical costs associated with influenza . none of the potential limitations of the 
 study are likely to have influenced the model estimates in any major way . in addition to influenza - attributable respiratory disease , we estimated the burden of 
 influenza - attributable otitis media , which has often been regarded as a common complication 
 of influenza . our study found almost as many 
 children ( aged < 5 years ) were diagnosed at presentation with influenza - attributable 
 otitis media as with influenza - like illness , suggesting that otitis media is part of the 
 primary symptomatology of influenza . the diverse range of presenting illnesses identified as 
 attributable to influenza in our study questions the relevance of diagnostic criteria by 
 which influenza is defined clinically . like other studies that have tried unsuccessfully to 
 correlate specific symptoms with a diagnosis of influenza [ 34 , 35 ] , our study suggests that 
 collections of symptoms with / without fever are largely inadequate for measuring the burden 
 of illness . finally , the model estimated that more than 600  000 antibiotic courses were prescribed for 
 influenza - associated respiratory disease per season . the potential misuse of antibiotics is 
 a well - recognized cause for concern , particularly in relation to common respiratory 
 infections . a simple test that is able to 
 discriminate between bacterial and viral infection would be a great step forward , as would 
 timely local influenza surveillance data that would allow physicians to assess the 
 probability that an acute respiratory infection is caused by influenza . health economic models can inform policy choices , but they depend on accurate and 
 age - specific parameter estimates of the disease burden . furthermore , it is critical to use 
 estimates based on recent assessments of the burden : earlier publications could overestimate 
 the current burden . because the effectiveness of influenza vaccination in preventing otitis 
 media appears similar to that of pneumococcal conjugate vaccines , it is important that estimates of the otitis media burden and the 
 potentially preventable fraction be included in cost - benefit estimates of influenza 
 interventions in this age group . our study provides a source for understanding the national 
 influenza burden and undertaking cost evaluations .
summaryinfluenza is rarely laboratory - confirmed and the outpatient influenza burden is rarely 
 studied due to a lack of suitable data . 
 we used the clinical practice research datalink 
 ( cprd ) and surveillance data from public health england in a linear regression model to 
 assess the number of persons consulting uk general practitioners ( gp episodes ) for 
 respiratory illness , otitis media and antibiotic prescriptions attributable to influenza 
 during 14 seasons , 19952009 . 
 in cprd we ascertained influenza vaccination status in each 
 season and risk status ( conditions associated with severe influenza outcomes ) . 
 seasonal 
 mean estimates of influenza - attributable gp episodes in the uk were 857 996 for 
 respiratory disease including 68 777 for otitis media , with wide inter - seasonal 
 variability . in an average season , 
 24%/05% of children aged < 5 years and 
 13%/01% of seniors aged 75 years had a gp episode for respiratory illness attributed to 
 influenza a / b . 
 two - thirds of influenza - attributable gp episodes were estimated to result 
 in prescription of antibiotics . 
 these estimates are substantially greater than those 
 derived from clinically reported influenza - like illness in surveillance programmes . 
 because health service costs of influenza are largely borne in general practice , these are 
 important findings for cost - benefit assessment of influenza vaccination programmes .