The test-negative design: validity, accuracy and precision of vaccine efficacy estimates compared to the gold standard of randomised placebo-controlled clinical trials

The test-negative design (TND) is an efficient form of case–control study commonly applied to influenza vaccine effectiveness (VE) estimation. TND validity is predicated on the core assumption that the intervention (vaccine) has no effect on other non-targeted aetiologies resulting in similar illness/disease. Here we verify this core assumption and compare efficacy estimates derived by the TND versus classical perprotocol analysis of four datasets obtained from randomised placebo-controlled clinical trials (RCT) of the live attenuated influenza vaccine (LAIV) in children ≤7 years-old and the elderly ≥60 years-old. We further assess generalisability of the TND approach in two other RCT datasets to evaluate monoclonal antibody in the prevention of respiratory syncytial virus (RSV) hospitalisation. Efficacy estimates and their confidence intervals were virtually identical for per-protocol RCT versus TND analyses of LAIV and also for RSV monoclonal antibody. Neither LAIV nor monoclonal antibodies affected the risk of disease aetiologies that were not specifically targeted by the respective interventions (e.g. other respiratory viruses). This study validates the core assumption of the TND approach for influenza vaccine efficacy estimation and confirms the accuracy and precision of its estimates compared to the gold standard of classic per-protocol RCT analysis of the same data sets. The TND approach is generalisable for other conditions such as RSV for which the core assumption is also met. However, when used in observational studies, the TND, like all designs, still requires assessment for bias and confounding that may exist in the absence of randomised participation and blinded follow-up.

The test-negative design (TND) is an efficient form of case-control study commonly applied to influenza vaccine effectiveness (VE) estimation.TND validity is predicated on the core assumption that the intervention (vaccine) has no effect on other non-targeted aetiologies resulting in similar illness/disease.Here we verify this core assumption and compare efficacy estimates derived by the TND versus classical perprotocol analysis of four datasets obtained from randomised placebo-controlled clinical trials (RCT) of the live attenuated influenza vaccine (LAIV) in children ≤7 years-old and the elderly ≥60 years-old.We further assess generalisability of the TND approach in two other RCT datasets to evaluate monoclonal antibody in the prevention of respiratory syncytial virus (RSV) hospitalisation.Efficacy estimates and their confidence intervals were virtually identical for per-protocol RCT versus TND analyses of LAIV and also for RSV monoclonal antibody.Neither LAIV nor monoclonal antibodies affected the risk of disease aetiologies that were not specifically targeted by the respective interventions (e.g.other respiratory viruses).This study validates the core assumption of the TND approach for influenza vaccine efficacy estimation and confirms the accuracy and precision of its estimates compared to the gold standard of classic per-protocol RCT analysis
The TND is a type of case-control design whereby vaccine status is compared between influenza testpositive cases versus test-negative controls who present to a clinician, generally with some standardised definition of influenza-like illness (ILI).While classical case-control studies require intense efforts to recruit non-diseased controls, the TND draws controls from the same source population as the cases, namely ill patients who are tested to identify a specific aetiology of interest for their illness or disease.It is therefore a convenient and relatively low-cost design that also has recently demonstrated its usefulness in rapidly gauging vaccine protection early in the influenza season [8,13,16].
The simplicity of the TND approach, however, has understandably raised concerns about its validity, including the misclassification of cases as controls due to imperfect test sensitivity.Theoretical work has previously shown that in fact test specificity rather than sensitivity is the most critical factor influencing VE estimation based on the TND [10].Given high test specificity and prevalence of the targeted aetiology (i.e.influenza) equal to or lower than that of other aetiologies (i.e.other respiratory viruses) with similar clinical presentation (i.e.acute respiratory illness (ARI) or ILI), the TND performs comparably to the classical case-control or cohort design, even with suboptimal test sensitivity [9].Most published studies applying this method to influenza VE estimation have used highly specific diagnostic methods such as polymerase chain reaction (PCR) confirmation [1][2][3][4][5][6][7][8][10][11][12][13][14][15][16][17][18].Detection of influenza by culture is nearly 100% specific [19].As culture has historically been considered the gold standard, its sensitivity is very high especially in young children (<5 years-old) although PCR detects 2% to 13% more cases [20].In elderly patients (>65 years-old), viral culture has a sensitivity between 21% and 51% compared to PCR [21].
The efficacy of a preventive intervention (e.g.vaccine) reflects proportionate reduction in the frequency of the targeted disease in those receiving the intervention (vaccine) compared to individuals who did not receive the intervention and is ideally assessed in the optimal conditions of suitably powered randomised placebocontrolled clinical trials (RCT).For vaccines, efficacy is calculated by comparing attack rates (ARs) in the vaccinated and unvaccinated through the relative risk (RR) and according to the following equation [22]: Like efficacy, effectiveness also compares proportionate reduction of risk but this is estimated in field conditions through observational studies of the intervention, without randomisation to address other possible influences.Efficacy and effectiveness are calculated the same way.In RCT and in cohort studies where a census of the source population is available, ARs are calculated by dividing the number of vaccinated and unvaccinated cases of the disease in question by the total number of individuals belonging to their respective categories.In case-control studies where there is no census of the source population, effectiveness can be validly estimated by the odds ratio (OR) assuming that controls are a representative sample of that population and the exposure distribution (e.g.vaccine coverage) is the same as in the source population [23].For this condition to be met and a control series to be valid, the sampling fraction (θ) must be the same in vaccinated and unvaccinated non-diseased controls.The θs then cancel out when calculating the OR which approximates the RR when the disease is rare (Table 1).For the TND approach, the condition of representative exposure distribution (e.g.vaccine coverage) in controls emerging from the same source population will apply if the intervention has no effect on other aetiologies manifesting similar clinical presentation as the target pathogen.For the TND as applied to influenza vaccine efficacy/effectiveness estimation, internal validity is therefore predicated on the core assumption that influenza vaccine has no effect on non-influenza causes (e.g.other respiratory pathogens such as parainfluenza, respiratory syncytial viruses (RSV)) of ARI or ILI.These non-influenza episodes would then be expected to occur at the same mean frequency (f) per vaccinated or unvaccinated individual (i.e.f vaccinated = f un- vaccinated ).Consequently, among individuals affected by these other aetiologies, the proportion who are vaccinated should be similar to the vaccine coverage in the source population (Table 1).
Large double-blind RCTs optimise the comparability of vaccinated and unvaccinated individuals with respect to eligibility criteria, follow-up, and disease ascertainment thereby minimising the influence of bias and confounding.As such, the RCT represents the ideal context to assess the validity of the TND core assumption and to verify the accuracy and precision of efficacy estimates derived in that way.Using four datasets from large double-blind RCTs of live attenuated influenza vaccine (LAIV) among children and the elderly we have therefore directly compared original RCT per-protocol efficacy estimates against those instead derived by TND analysis.To test the core assumption hypothesis that influenza vaccine has no effect on other ARI/ILI aetiologies we have also derived efficacy against noninfluenza causes of illness.Finally, to illustrate the generalisability of the TND we applied it to two RCT datasets collected for the evaluation of humanised monoclonal antibody (palivizumab) in preventing RSV hospitalisation.

Methods
Four datasets from published, double-blind RCTs of LAIV (Flumist, MedImmune) among children and the elderly were used [24][25][26][27].In these studies, after being administered vaccine or placebo, participants were actively followed throughout the winter season by phone calls or home visits and nasal/throat swabs were collected for each episode of ARI (Table 2).Respiratory specimens were tested by viral culture and the primary outcome was culture-confirmed influenza (test-positive) due to any strain regardless of antigenic similarity.Specimens with influenza-negative culture were not further tested to identify other specific causative pathogens.For the RSV studies, we analysed datasets from two published double-blind RCTs of palivizumab administered every 30 days during the RSV season to premature infants (≤35 weeks gestation) or infants with bronchopulmonary dysplasia [28] and to children with haemodynamically significant congenital heart disease [29].The primary outcome was RSV-associated hospitalisation where diagnosis of RSV was confirmed by rapid antigen detection test (sensitivity: 82%, specificity: 95% [30]).No further testing was done to identify the aetiology in patients with RSV negative tests.
Per-protocol randomised cohort estimates of efficacy were calculated using ARs according to the above equation.Three approaches to TND analysis of LAIV protection were conducted.In participant-based analysis without censoring for influenza, controls included participants with any negative swabs without excluding those who may have tested positive for influenza at another time within the study period (Table 1).In participant-based analysis with censoring for influenza, controls included only participants with negative swabs who furthermore never had a positive test for influenza at any other time during the study period (i.e.excludes those test-positive for influenza).In specimen-based analysis, cases were influenza-positive specimens and controls were influenza-negative specimens rather than individuals: this approach accounts for the multiple episodes of respiratory infections not attributable to influenza that an individual can sustain during the study period.
To estimate vaccine effects on other non-influenza ARI aetiologies, the AR of these infections was calculated by dividing the number of participants/specimens testing negative for influenza by the total enrolment in their respective categories of exposure (vaccine or placebo).Per above, this was conducted as participantbased (with/without censoring) and specimen-based analysis.
Each of the above was repeated for the RSV studies, modified for the intervention (palivizumab) and outcome of interest (laboratory-confirmed RSV hospitalisation).
Consistent with the expectation of large, randomised placebo-controlled participation in these RCT data sets, we assumed that risk factors for influenza were similarly distributed in both groups before vaccination and that blinding ensured comparable follow-up and case ascertainment, minimising bias and confounding.Consequently, only crude results are presented without further statistical adjustment.Point estimates of efficacy and their 95% confidence intervals (CI) for TND analyses were computed using Mantel-Haenszel method as (1-(OR or RR) X 100).
f: average number of non-influenza illness episodes during the follow-up period; p: probability of having an episode of non-influenza illness during the follow-up period (episodes past the first do not separately contribute); Θ: sampling fraction of controls.
a Includes as controls participants with any negative swabs (i.e.without excluding those who tested positive for influenza at any other time during the study period).b Includes as controls only participants with negative swabs who furthermore never had a test that was positive for influenza at any other time during the study period (i.e.excludes influenza positive participants).c All non-influenza illness episodes count (without excluding those in participants who tested positive for influenza in another illness episode).

Table 1
Comparison of the randomised placebo-controlled clinical trial (RCT)/cohort, classical case-control and test-negative design (TND) case-control Each of these RCTs had received prior Institutional Review Board/Ethics Committee approval.The current analysis involved only additional statistical analyses of de-identified data and thus no additional approvals were required.

Live attenuated influenza vaccine (LAIV) studies
Three RCT datasets among children ≤7 years of age [24][25][26] and one among adults ≥60 years of age [27] were analysed.Together these trials included 6,077 participants each actively monitored for outcomes of interest accrued over the course of a single season.The first paediatric study included children who were vaccinated with LAIV and followed for one season.The second study recruited the same paediatric participants whose parents gave consent for revaccination and follow-up for a second season.For all LAIV trials, groups were shown in publication to be balanced with respect to baseline characteristics so that further adjustment for residual confounding was not required.
For all LAIV studies, the point estimates and surrounding 95% CIs for efficacy against ARI due to influenza were virtually identical in the classical per-protocol RCT and TND analyses with little variation using these datasets whether TND analysis was participant-based (with/without censoring) or specimen-based (Table 3).Good concordance between TND and RCT analysis approaches was observed both in paediatric studies with high efficacy and in the elderly study where protection was lower.LAIV had negligible effect on non-influenza aetiologies of ARI as shown by the zero or near-zero efficacy associated with test-negativity (Table 3).

Respiratory syncytial virus studies
For the two RSV trials, groups were shown in the original publications to be balanced on baseline characteristics except household smoking in one trial [28]; adjusted analysis did not influence efficacy estimates and we did not pursue adjustment here.In these studies, repeated hospitalisation during the study period was rare.Therefore all three TND analysis approaches gave similar results and we present only the participant-based analysis with censoring (Table 4 and Figure ).Point estimates and 95% CI for palivizumab protection against RSV hospitalisation were virtually identical by the per-protocol RCT and the TND analysis.Palivizumab provided no protection against non-RSV causes of acute respiratory hospitalisation (RSV testnegative) as again shown by the null efficacy.

Discussion
In this analysis, we confirm that estimates of efficacy and their 95% CIs were similar when derived according to the classical per-protocol RCT analysis or various TND approaches and this was observed in children and the elderly at respectively high or reduced efficacy values.When applied to data for an unrelated passive immunising agent targeting RSV, the TND gave similar results, thereby demonstrating its generalisability beyond influenza and to endpoints representing more severe disease outcomes such as hospitalisation.
To obtain valid case-control study results, controls must be representative of the source population [23].
As such, they should belong to the same source population from which cases were identified and should be individuals who theoretically would have been identified as cases had they acquired the targeted aetiology of interest.The actual source population from which clinic or hospital cases emerge is often undefined.In classic case-control studies, controls are usually recruited among patients consulting or admitted to the same facility as cases but the disease for which they consult may be distinct from that which the targeted aetiology typically manifests.In contrast, test-negative controls derived from among patients presenting with similar clinical illness (e.g.ARI or ILI) and tested for diagnosis provide some inherent reassurance that they emerge from the same source population as cases, would have consulted and would have been considered cases had their aetiology been the targeted pathogen rather than otherwise.More than thirty years ago, Broome et al. applied this sort of approach in using patients infected by non-vaccine type invasive pneumococcal infection to serve as controls in their analysis of pneumococcal VE [31].The TND as now applied to influenza VE is an extension of the same logic.The main advantage of the TND is its ease of access to a series of controls representative of the source population.Here we have shown that this simplicity does not necessarily come at the cost of validity.
We explicitly presented three TND analysis approaches.
While in this paper all three approaches performed similarly this may not always be true.Censored/ uncensored participant-based and specimen-based approaches are not intrinsically the same and the choice of one approach over another must be consciously expressed.As displayed in LAIV Belshe Year 2 [25] LAIV Lum [26] LAIV De Villiers [27] RSV IMPACT [28] RSV Feltes [29] Efficacy 95% confidence interval ARI: Acute respiratory illness RSV: respiratory syncytial virus.As information on medical consultation was not collected in Lum's study [26], results presented are those from Table 3. assumption.Even if the vaccine does not actually influence the risk of non-influenza aetiologies, unvaccinated individuals should more often be infected by influenza during the study period assuming that vaccine is protective against influenza.As such, censoring participants based on influenza positivity eliminates more participants with non-influenza aetiologies in the unvaccinated than the vaccinated group thereby introducing a bias that skews findings toward suggesting the vaccinated are at increased risk of these other aetiologies.This bias will increase with greater prevalence of influenza compared to other respiratory infections in the study population.These concerns related to censoring will apply not only to TND, but also to other fixed cohort follow-up or case-control analyses, requiring authors to be explicit in the approach taken when interpreting their results.
In our analysis, there was a statistically significant but slight increased risk of non-influenza respiratory episodes during the first year of the Belshe study but this was not observed in the three other datasets for which efficacy against other respiratory viruses even more closely approximated the null.It may be argued that the same may not extend to inactivated or other influenza vaccine formulations.While another small trial from Cowling et al. involving 115 participants followed during one season reported an increased risk of non-influenza viruses among recipients of inactivated influenza vaccine [32] a much larger study covering six seasons and including more than 3,000 patients found no such association [33].It could be argued that our findings of null vaccine effects against other respiratory viruses are explained by the fact that live virus vaccine is itself predicated on replicating virus and may thereby also directly contribute to broadly cross-protective innate immune mechanisms that are precluded by effective inactivated vaccine (a theory proposed to explain Cowling's findings [32]).Although active follow-up of thousands of participants included in our own datasets resulted in one to 3.5 specimens on average per participant (≤10% positive for influenza), the specific non-influenza cause of ARI was not sought in any of the RCTs we used so that we cannot directly address possible vaccine effects on individual pathogens.However, temporary innate immunity is short-lasting, in the range of several weeks and in each of these trials LAIV was administered well before the winter period.LAIV-induced innate immunity is thus unlikely to have substantially altered the overall risk of other respiratory viruses through the full follow-up period.On that basis we believe that our findings supporting the core assumption of the TND for LAIV can also be extended to inactivated formulations although we encourage direct assessment of that through other similarly available RCT data sets.If vaccine nevertheless truly does increase the likelihood of other noninfluenza infections by whatever mechanism, this would generally tend to over-estimate efficacy/effectiveness against influenza suggesting TND findings are optimistic representations of vaccine performance.
There are other issues and limitations worth considering in our analysis.RCT estimates and cohort studies provide absolute measures (attack rates) whereas under the usual conditions of TND application there is

Table 4
Efficacy of palivizumab to prevent RSV and non-RSV hospitalisation by per-protocol and test-negative design (TND) participant-based analysis with censoring in two randomised placebo-controlled clinical trials (RCT) conducted in children.no census of the source population and analysis can only provide relative measures.We have validated the TND approach for influenza and RSV but this does not imply universal validity in the evaluation of all infectious diseases or their interventions.Before extending the TND to other vaccines or interventions, it is necessary to confirm earlier specified pre-conditions related to test characteristics and the mix of target/non-target disease aetiologies [9] as well as the core assumption of no effect on non-targeted aetiologies of diseases with similar symptomatology.In the influenza vaccine studies we used, influenza was the targeted aetiology of ARI and positive viral culture for influenza was the main outcome.The sensitivity of viral culture to detect influenza in specimens collected early after the onset of disease is expected to be high in young children but lower in the elderly [11].Despite that, the TND performed comparably well to De Villiers' RCT analysis in the elderly.The current analysis took advantage of existing large clinical trial databases where participants had been randomised and followed in blinded fashion to identify the outcome with stringent approaches applied equally to immunised and unimmunised participants.This most likely minimised differences between the two groups, eliminated confounding and provided efficacy estimates.Effectiveness derived from observational studies, in contrast, is susceptible to these additional methodological concerns.As such, the TND approach is valid but cannot compensate for other methodological flaws.Indiscriminate use of the TND in observational studies can lead to errors of interpretation, particularly if testing was applied differentially and varied with the likelihood of immunisation, exposure and/or test-positivity.TND should be considered as a variation on the case-control design and as for all observational designs, one needs to begin from the premise that bias and confounding may be operating.Intense scrutiny of the methods and data set for signals of bias (e.g.selection, information, confounding bias) remains a requirement.
In conclusion, the TND approach appears valid not only for influenza vaccine efficacy and effectiveness assessment but also for other diseases and interventions provided that the core assumption requiring no effect of the preventive intervention on non-targeted aetiologies is fulfilled and that bias as a potential concern for all observational designs is adequately addressed.

Research articles
Laboratory-confirmed invasive meningococcal disease: effect of the Hajj vaccination policy, Saudi Arabia, 1995 to 2011 Z Memish (zmemish@yahoo.com)Saudi Arabia (SA) experienced two large invasive meningococcal disease (IMD) outbreaks during the 2000 and 2001 Hajj pilgrimages.In 2002, polysaccharide quadrivalent ACWY vaccines became mandatory for Mecca and Medina pilgrims/residents older than two years.This study aimed to analyse IMD surveillance data among citizens, residents and pilgrims in SA from 1995 to 2011, focusing on changes before and after the new vaccination policy.For all laboratory-confirmed IMD cases in the national surveillance database from 1995 to 2011, serogroup and age were retrieved.The cases' seasonal distribution as well as the case fatality ratios (CFR) were obtained.For Saudi citizens/residents and Hajj pilgrims, annual rates were calculated using mid-year population estimates.The Student's t-test was used to compare means between the pre-epidemic (1995-1999) and postepidemic (2002-2011) periods, excluding outbreak years.From 1995 to 2011, laboratories notified 1,103 cases.Between the pre-and post-epidemic periods, mean annual IMD rates decreased from 0.20 (standard deviation (SD): 0.1) to 0.06 cases/100,000 (SD: 0.06; p=0.02), mean numbers of Hajj-related cases from 13 (SD: 9.3) to 2 cases/year (SD: 2.3; p=0.02) and the mean age from 31 (SD: 1.3) to 18 years (SD: 1.4; p<0.01).The CFR in Saudi citizens (10.4) was lower than among foreign pilgrims (28.9) and decreased from 19.3% (SD: 1.8) in the pre-epidemic to 11.4% (SD: 7.0; p=0.04) in the post-epidemic phase.The decrease of annual IMD rates, CFR and Hajj-related cases between the pre-and post-vaccine era suggests a possible positive effect of the mandatory ACWY vaccination for pilgrims/residents in Mecca and Medina.Regular surveillance with an annual data analysis is necessary to monitor trends and circulating serotypes and to implement appropriate public health measures to avoid new IMD epidemics during upcoming Hajj seasons.

Introduction
Invasive meningococcal disease (IMD) is caused by the gram-negative coccoid bacterium Neisseria meningitidis [1,2].Transmission via respiratory droplets can lead to bacterial meningitis and septicaemia in the persons who get infected.Six serogroups (A, B, C, W135, X and Y) differentiated by their polysaccharide capsule, account for the majority of IMD cases [3].IMD primarily affects children below five years of age, causing an estimated 500,000 cases and 50,000 deaths annually worldwide [4].Polysaccharide and conjugated vaccines are available for serogroups A, C, W135 and Y [5].One vaccine for serogroup B has been licensed in Europe in January 2013 and other serogroup B vaccines have been used in New Zealand, Cuba and France to control epidemics [6].
In Saudi Arabia (SA), the annual Hajj and the yearround Umrah pilgrimage lead to a particular high risk of outbreaks with invasive N. meningitidis.The Hajj pilgrimage is held on every 12th month of the Islamic calendar (2011 attendance: 2.9 million pilgrims, including 1.8 million from >140 foreign countries), making it one of the largest mass gathering events worldwide [7][8][9].About 45,000 pilgrims arrive from the European Union each year [7].Compared to the Hajj, the Umrah pilgrimage includes slightly different rituals and can be undertaken at any time of the year.Foreign pilgrims generally arrive by air in the city of Jeddah and continue to the pilgrimage sites in Mecca, Mina, Mount Arafat and Muzdalifah.Many end the journey with a visit to the holy sites in Medina [7].Extreme congestion with populations from diverse geographical areas appears to promote a high prevalence of asymptomatic N. meningitidis carriage, with up to 80% reported for Mecca pilgrims [10,11].In comparison carriage prevalence between 3% and 30% has been shown for the African meningitis belt and in a Norwegian randomised study, 9.6% of Norwegian volunteers harboured N. meningitidis [12,13].The United States (US) Centers for Disease Control reported five to 10% of adults as asymptomatic nasopharyngeal carriers [14].
Following an outbreak of serogroup A IMD among pilgrims in 1987, Saudi Arabian health authorities implemented three interventions: (i) the compulsory vaccination before entering SA with bivalent AC vaccine for all Hajj pilgrims, (ii) annual vaccination campaigns for all residents in the proximity of pilgrimage sites and (iii) compulsory oral ciprofloxacin upon entering SA to pilgrims from sub-Saharan Africa to eradicate nasal carriage [11,15,16].
In response to two large IMD outbreaks caused by N. meningitidis serogroup W135 in the 2000 and 2001 Hajj seasons [15,17], the SA Ministry of Health (MoH) adjusted their vaccination policy.In 2002, they required a polysaccharide quadrivalent non-conjugated ACWY meningococcal vaccine for (i) children and adults aged above two years living in Mecca and Medina, (ii) Hajj pilgrims aged above two years from within and outside of SA, (iii) healthcare workers in SA and (iv) government personnel serving the pilgrims [18].Since 2010, a conjugated polysaccharide quadrivalent ACWY meningococcal vaccine is given to the same target groups aged from above two to 55 years.The vaccines are administered during annual vaccination campaigns in Mecca and Medina in a single dose with boosters every three years.As of 2013 no meningococcal vaccines are included in the SA national childhood immunisation schedule (NCIS).This study aims to describe the epidemiology of IMD in Saudi Arabia for the years 1995 to 2011, with a focus on changes in incidence and case fatality ratio (CFR) after the introduction of the polysaccharide quadrivalent ACWY vaccine in 2002, in order to evaluate the effect of this Hajj vaccination policy change.

Methods
A confirmed IMD case was defined as either isolation of N. meningitidis from cerebrospinal fluid (CSF) or blood or detection of capsular antigen in CSF by latex agglutination assay [19].An IMD surveillance system was started in 1994 in SA based on recommendations of the World Health Organization (WHO) [20].Since then, the Preventive Medicine Directorate at the MoH requires laboratories from all 20 health regions in SA to anonymously report confirmed IMD cases.The casebased reporting form collects information on age, sex, nationality, SA residency status, vaccination status, date of onset of symptoms (by Gregorian and Islamic calendar), clinical status and place of laboratory confirmation (health region).Information on the capsular groups, determined by latex agglutination, is also collected on the reporting form.
For the purposes of this study, all IMD cases in the surveillance database from 1 January 1995 to 31 December 2011 were extracted.This included cases among Saudi citizens and residents, foreign pilgrims and illegal immigrants.A citizen was considered a person in possession of the Saudi Arabian nationality, and a resident a person originating from outside SA but residing and working in SA.A foreign pilgrim was defined as a person holding a special visa for the Hajj or Umrah pilgrimage, whereas an illegal immigrant was an unregistered person devoid of any valid entry permit for SA.Hajj-related cases were specified as IMD cases with dates of disease onset during the Hajj season in the cities of Mecca or Medina.

Statistical analysis
Age group-, sex-and region-specific annual and cumulative disease incidences were calculated for IMD cases among Saudi citizens or residents.Age group-(0-4; 5-14; 15-64; >65 years of age) and year-specific population denominators were obtained from the United Nations Development Programme (UNDP) website [21].To calculate the cumulative incidence over several years, mid-period population estimates were used as a denominator.The Ministry of Hajj, Saudi Arabia [22] provided the numbers of foreign and domestic Hajj pilgrims.For foreign Hajj pilgrims, no age or sex specific incidences have been calculated, as no age or sex specific Hajj pilgrim numbers were available.In the absence of a population register to calculate rates, illegal immigrants were excluded from any incidence calculations.
From all cases, regardless of citizenship and nationality, numbers of Hajj-related IMD cases as well as year, age and region specific CFRs were calculated.Relative risks for death from IMD were identified by calculating ratios of case-fatalities and their 95% confidence intervals (95% CIs) for the residence status, seasons, age groups and sex.The Student's t-test was used to compare means (age, CFRs and number of cases) between the pre-epidemic (1995-1999) and post-epidemic (2002-2011) periods, excluding the outbreak years (years 2000, 2001), and linear regression models were fitted to describe trends.A p-value <0.05 was considered statistically significant.Surveillance data were computerised using Excel programme (Microsoft, USA) and statistical analysis was performed with Stata 12 (Statacorp, Texas, USA) software.

Study population
During the study period, the population of SA rose from 18,491,845 in 1995 to 27,448,000 persons in 2011, the latter of which comprises 68% SA citizens and 32% residents of foreign origin [21].In 2011, children less than five years-old and adults above 65 years of age accounted for 10%, and 3% of the population, respectively.The largest population increase has been recorded for the 15 to 64 years age group, which comprised 66.7% of the population in 2011 (compared to 56.1 in 1995).Forty-five percent of the population were female.There were 1,936,124 and 1,858,490 persons registered in the health districts of Mecca and Medina in 2011 respectively, representing 14% of the population in SA.During the study period the number of Hajj pilgrims increased by 57% from 1,865,234 (1,080,465 from outside SA) in 1995 to 2,927,717 (1,828,195 from outside SA) in 2011 [22].

Annual and cumulative invasive meningococcal disease incidences
Between 1995 and 2011, 1,103 cases of IMD were reported to the MoH in SA (Table 1).Of those, 645 cases were Saudi citizens/residents and 299 were foreign Hajj pilgrims.Of the remaining cases, 82 were illegal immigrants (not included in incidence calculations), 73 were foreign Umrah pilgrims and four had unknown identity (combined cumulative incidence of IMD among citizens, residents and foreign Hajj pilgrims: 3.92/100,000 population).Between 1995 and 1999, the mean annual incidence was 0.20/100,000, ranging from 0.25/100,000 in 1995 to 0.06/100,000 in 1999 (Figure 1A).In the two outbreak years of 2000 and 2001, the annual incidence increased to 1.42 and 1.32/100,000, respectively.In the post-epidemic period, the mean annual incidence did not exceed 0.06/100,000, ranging from 0.21/100,000 in 2002 to 0.01/100,000 in 2010, a significant decrease compared to the pre-epidemic period (p=0.02)(Figure 1A).
In an analysis restricted to SA citizens and residents, the cumulative incidence between 1995 and 2011 (2.85 cases/100,000) was lower compared to rates including Hajj pilgrims.Outside the outbreak periods the annual incidence followed the same trend described above (Figure 1A).

Age, sex and region specific incidence for Saudi Arabia citizens and residents
For SA citizens and residents, in the study period, the age group including less than four year-olds had the highest cumulative incidence, with both sexes equally affected (12.3 cases/100,000; Figure 2).Above four years of age, males had a higher cumulative incidence.Among those between 15 and 64 years of age, cumulative incidence among males (1.8 cases/100,000) was three times higher than among females (0.6 cases/100,000).
In the period between 1995 and 2011, citizens and residents in the main Hajj pilgrimage destinations had a high cumulative incidence (Mecca: 9.04 cases/100,000 n=175; Medina: 4.52 cases/100,000 n=84 and Jeddah: 2.28 cases/100,000 n=88), whereas urban regions, not visited by the Hajj pilgrims, such as the capital city Riyadh (1.85 cases/100,000 n=131) had lower cumulative incidences.

Distribution of mean age
In the period between 1995 and 2011, among SA citizens and residents, the age group comprising those younger than four years had the highest disease incidence.However, the mean age of all IMD cases, including pilgrims, between 1995 and 2011 was 25.8 (SD: 0.7) years.The mean age decreased from 31 years (SD: 1.3) in the pre-epidemic period to 18 years (SD: 1.4) in the post-epidemic period (p<0.01;b coefficient -1.27, Figure 3).
The mean age of IMD cases during the Hajj season (37.0 years; SD: 1.0) was higher (p<0.01)than among cases outside this season (17.4 years; SD: 0.8).

Discussion
According to the present study and confirming previous reports, the Hajj season constitutes a special opportunity that is very favourable to IMD epidemics [7,9,10].
The high morbidity and fatality for pilgrims during the Hajj season might be largely explained by epidemiologically unfavourable conditions (e.g.crowding, delayed clinical and laboratory diagnosis).Our study indicates that the incidence of IMD decreased in SA following the introduction of the ACWY vaccine in 2002.More specifically, Hajj-related IMD cases declined after the introduction of the vaccine compared to pre-epidemic years.The results suggest that the compulsory use of the ACWY vaccine for pilgrims and residents of Mecca and Medina may have played a role in reducing not only Hajj-related IMD cases, but also the overall disease incidence in SA.
Children under five, predominantly affected by serogroup B and W135 infections, suffered the highest agespecific incidence of IMD throughout the study period.This is consistent with experience from the United Kingdom (UK), the US and Germany, where B is the most prevalent serogroup in children below five years [23][24][25].The mean age of cases decreased during the study period.Two factors may explain this evolution.First, there could have been a decrease in IMD in adolescent or adult Hajj pilgrims since 2002 because of the vaccine introduction for all Hajj pilgrims.Second,  [10].However, those incidence rates cannot be compared to those in SA, as the serogroup distribution in those countries differs, which changes the disease impact completely.Differences in case definitions, which include different laboratory methods as well as clinical and epidemiological criteria, impede international comparisons, as examples from European and Australian guidelines illustrate [30,31].In the future, introduction of new sensitive polymerase chain reaction (PCR) methods for the detection of N. meningitidis in SA, could enable laboratories to confirm a higher number of suspected IMD cases [32,33].
In the current IMD surveillance database, it proved difficult to distinguish between Hajj related cases and non-Hajj cases.We used the time of disease onset and the region to infer a potential connection to the pilgrimage.As per our criteria, cases outside of Mecca and Medina with contact to Hajj pilgrims, or Hajj pilgrims moving outside both cities, would not be identified as Hajj-related.As this information could be used to implement public health control measures, reporting health personnel should verify the Hajj-related status of every case.
The majority of outbreak-related cases were caused by N. meningitidis serogroup W135.The responsible clone was later found to belong to the ST-11/ET-37 complex [34].Genetic analysis of the clone suggested that a capsular switch from serogroup C to serogroup W135 may have occurred years before the onset of the outbreak [34].The same hypervirulent clone caused serogroup C disease in Belgium, Iceland, Ireland, the Netherlands, Portugal and the UK in the late 1990s and early 2000s [10].Concerns had been raised that mass immunisation with vaccines that do not protect against all serogroups could lead to an increase in incidence of meningococcal disease due to strains not included in the vaccine [35,36].Following the introduction of ACWY vaccines, this phenomenon of serotype replacement, or a major emergence of non-vaccine serotypes, has not been reported in Mecca and Medina, or elsewhere.
Vaccine coverage data are needed to determine whether the vaccine contributed to reduced morbidity.While no coverage data are available for foreign Hajj pilgrims, the entry requirement that is enforced through border checks suggest that coverage should be high.In comparison, compliance among Saudi pilgrims may be poorer, since Saudi citizens do not have to provide proof of vaccination at border controls or check points.In 2006, a study of 134 British and 109 Saudi Hajj pilgrims reported that vaccine coverage was lower among local residents (64%) than among British pilgrims (100%) [37].According to this study, 50% of local pilgrims residing in Mecca and Jeddah had been

Introduction
Measuring the burden of infectious disease is essential for the rational design of public health intervention strategies and for the allocation of resources.For intestinal infectious diseases (IID) there is a massive global burden; the World Health Organization (WHO) estimates around 2 billion cases every year [1].Detailed surveillance studies have shown that there are up to 17 million sporadic community cases of IID and one million general practitioner (GP) consultations annually in the United Kingdom (UK) [2].Routine investigations of IID in the UK include salmonellosis, shigellosis, campylobacteriosis, cholera, infection with verotoxin-producing Escherichia coli O157 (VTEC), rotavirus, norovirus and parasitic infections and yet no cause is identified for over half of the laboratory-investigated diarrhoeal episodes [3].One, often undiagnosed, potential pathogen is enteroaggregative E. coli (EAEC).In England, this pathotype of E. coli, defined by the ability to aggregate to HEp-2 cells [4], has been associated with cases of gastrointestinal infection [2,5,6] at a level comparable to Salmonella [6,7].EAEC gained notoriety during a recent outbreak in Germany and France caused by an E. coli strain that was both a verotoxin-producing and enteroaggregative [8].This outbreak was unusual due to the scale of morbidity and mortality, high even for VTEC infection, and the acquisition of the EAEC plasmid which may have played an important role in adherence to the human gut; the E. coli strain that caused the outbreak lacked the attachment and effacement (eae) gene for intimate adherence to human gut epithelium normally associated with severe disease caused by VTEC [9].The emergence of this hybrid pathogen has been described before in 1996, when an O111:H2 strain had caused an outbreak of haemolytic uraemic syndrome (HUS) in France [10], in 1999, when an O86:H strain associated with HUS was isolated in Japan [11], and most recently in 2011, when an O111:H21 strain was associated with a family outbreak in Ireland [12].All of these cases were associated with severe disease.It is likely that there are more cases of IID caused by EAEC and VTEC hybrids, but the EAEC pathotype is not routinely looked for.
Although EAEC itself has been associated with disease globally [13][14][15][16][17][18][19] including outbreaks (most notably a large outbreak in Japan involving 2,697 children [20]), a considerable proportion of healthy controls in casecontrol studies (16-31%) also harbour this pathotype [21][22][23].Furthermore, research data describing the association of genetic factors with virulence are contradictory [21,24,25].The reliability of virulence factors to identify EAEC for diagnostic purposes is therefore unclear [16].The situation is further complicated by the presence of co-infections in IID [7].When multiple pathogens are present in a diarrhoeic stool, defining which are causing the symptoms can be problematic, and as diagnostic tools improve, mixed infections in the gut are being recognised more frequently [26].This is especially true in studies looking at EAEC infection; in Peru, for instance, multiple pathogens are found in 40% of infants with diarrhoea and with EAEC in their stool [27].
The successful completion of two IID burden studies in the UK [2,6] using quantitative PCR, presented the opportunity to investigate the causal link between gastrointestinal disease and the presence of EAEC in the stool.We estimated bacterial load for EAEC and the presence of co-infection in a well-defined population in the UK and tested the independent association between EAEC presence and disease.

Datasets
Data from two IID studies were used in this analysis: the IID1 case-control study (August 1993-January 1996) [6,7,28] and the IID2 case-only study (April 2008-March 2009) [29].The data had been generated by testing stool samples by real-time PCR for the presence of a range of pathogens and recording the number of PCR cycles (Ct) needed before detection of product, to give a semi-quantitative estimate of bacterial load.The EAEC probe was the anti-aggregation protein transporter gene CVD432/aatD [30].
Cases of IID were defined in the same way in both studies as having had more than one loose stool, or clinically significant vomiting, over a two week period with no underlying non-infectious cause, followed by a symptom-free period of three weeks [2].Healthy controls (IID-free) were only recruited in IID1 and were selected from the study cohort, matched for age and sex, and asked to submit a stool specimen.
The dataset for the IID1 case-control study contained The dataset for the IID2 case-only study [29] contained PCR Ct values from 3,966 stools (all of which were from individuals with diarrhoea); EAEC was detected in 83 of them.These data were used for burden estimations and comparisons of demographic data for cases; there had been no controls recruited in IID2 case-only study, and so IID1 data only were used for comparison of cases with controls.

Statistical methods
One aim of this study was to assess the methods for estimating burden of EAEC in England from the current IID2 study results.However, no controls were recruited to the IID2 study and so a receiver-operating characteristic (ROC) analysis was constructed from the case-control data (IID1), and used to look for a cut-off between case and control in the Ct values.We compared the distribution of Ct values from EAEC-positive cases and controls using Student's t-test.
It is clear that the relationship between presence of EAEC and disease is not absolute and so several methods were used to investigate the association of EAEC with disease:

Carriage rates of EAEC in healthy controls, compared to other pathogens
For each infection, the chi-squared test was used to test if the distribution of the pathogen between cases and controls was as expected by chance.

Association of disease with individual pathogens in persons with multiple pathogens in their stool
For all EAEC-positive individuals with multiple pathogens (both cases and controls), we tested whether individual pathogens were equally distributed between cases and controls using chi-squared tests for independence.Because norovirus was the most common pathogen, we also compared by chi-squared test coinfection in all individuals positive for EAEC and all individuals positive for norovirus to see if the presence of other individual pathogens was dependent on infection with EAEC or norovirus.

Independent association of EAEC presence with disease
A logistic regression of univariate and multivariate analysis was carried out using case or control as outcome, and infecting agent and age as independent variables.In this way we assessed the independent association between EAEC and disease, while controlling for other pathogens.Model results were then used to calculate the population attributable fraction (PAF): PAF = P e (RR e -1) / RR e , where P e is the proportion of cases with the exposure (EAEC) and RR e the relative risk of disease.This form allows for confounding of the exposure if an adjusted RR is used, as recommended in Rockhill et al. [31].In that case, adjusted odds ratios (OR) are substituted into this equation to give an approximate, adjusted PAF.

Defining diagnostic cut-off values for Ct values in EAEC infection
In order to investigate the link between Ct value and disease, the sensitivity and specificity of the Ct value was assessed in EAEC-positive specimens from the casecontrol study (dataset IID1); Ct values were obtained and included 102 cases and 31 controls.Figure 1 shows the resulting ROC curve, and Figure 2 the distribution of Ct values in cases and controls.The cut-off was chosen to balance sensitivity and specificity and was set at a Ct value of 31 (Figure 1).The ratio of false positives versus false negatives with this cut-off point was 1.09 (95% confidence interval (CI): 0.79-1.53)(Figure 2), so the total number of test-positives, although not a good diagnostic for the individual, was a reasonable estimate of the total number of cases.Importantly however, in the population studied, there was a significant association between bacterial load and disease state (p=0.039), and further investigations were carried out using the point of <40 to indicate presence of EAEC.

Descriptive statistics
To test if the analysis of data from the IID1 case-control study remained relevant in 2009, we compared the demographic data from the two periods.There was no significant difference between the rate of EAEC in the IID1 case-control study (1993-96) and IID2 case-only study (2008-09), with 1.4% and 1.9%, respectively; individuals with EAEC present in their stool were distributed evenly across all age groups in both IID1 and IID2 (chi-squared p value for non-independence: 0.253).For EAEC-positive individuals, there was no significant difference in age between cases and controls (p=0.237).We therefore believe that the epidemiology did not change significantly for EAEC infection between the two periods.Cases tended to be slightly older than controls in IID1 (mean age of cases: 30.1 years, standard deviation (SD): 24.7 years; mean age of controls 28.7 years, SD: 23.9 years; p value for difference: 0.051).

Investigation of the association of EAEC presence with disease
Carriage rates of EAEC, compared to other pathogens, in healthy controls Submitting a stool specimen that was positive for EAEC was positively associated with having disease (Figure 3).However, one quarter of all EAEC positive individuals were asymptomatic (38/151).

Association of disease with individual pathogens in persons with multiple pathogens in their stool
The presence of co-infection was almost three times higher in EAEC-positive cases (74/113, 66%) than in EAEC-positive asymptomatic controls (9/38, 24%)_ (Figure 4).Cases had more multiple co-infections

Figure 1
Receiver-operating characteristic analysis of Ct values for enteroaggregative Escherichia coli from gastrointestinal disease cases (n=102) and controls (n=31) , United Kingdom, August 1993-January 1996 The red circle at Ct value 31 indicates the cut-off value which was chosen at the point where sensitivity and specificity were equivalent.

Investigation of the independent association of EAEC presence with disease
The logistic regression of EAEC status (but not Ct value) in univariate analysis gave an OR of 2.55 (95% CI: 1.91-3.39,p≤0.001); in multivaritate analysis, the OR was 2.41 (95% CI: 1.78-3.26,p≤0.001).This means that among IID cases, the odds of EAEC infection were 2.5 times higher compared with asymptomatic controls.The resulting adjusted PAF was 0.033% (95% CI: 0.024-0.039),suggesting that around 3.3% of cases of IDD in the UK were attributable to EAEC.This confirmed that EAEC was an independent cause of IID.
A comparison of co-infections with the most common cause of IID, norovirus, is presented in Figure 5.

Discussion
Although described as a pathogenic group of E. coli, it is well documented that EAEC may be associated with asymptomatic infection [21][22][23].In this study we asked the question how much disease EAEC is responsible for.In an attempt to remove healthy carriers from the case definition (a lower bacterial load might be expected in carriers than in cases), we analysed data from a PCR-based case-control study (IID1).Using the Ct value as an indicator of bacterial load, we were only able to define a cut-off with 60% sensitivity and specificity.These values suggest that estimation of bacterial load by the Ct value of a quantitative PCR for virulence factors is not a useful diagnostic test for EAEC infection.
However, there was a strong association between higher load (low Ct) and being a case, so we tried to define more accurately in which positive individuals EAEC was the causal agent of diarrhoea.The bacterial load data revealed the presence of two overlapping normally distributed data sets for EAEC: one representing the load in health (controls) and one in disease (cases) (see Figure 2).We further addressed any possible confounding effects of age (i.e.acquired immunity) and co-infection using logistic regression confirmed by univariate analysis; the results showed that an individual was 2.5 times more likely to be a case than a control if they had EAEC.Therefore we concluded that EAEC was independently associated with disease and we investigated the factors influencing this association.
Our results suggest that EAEC is common in the absence of disease.This situation is similar for gastrointestinal viral infection where post-infection levels of virus particles, although reduced, persist up to 56 days after symptoms have cleared [32,33].Another possibility is pre-existing immunity to the infection at the time of exposure, which could result in reduced viral replication and a failure to develop symptoms.If preexisting immunity was the cause of symptomless EAEC carriage we would expect to find an age distribution where adults are less frequently infected (older individuals have a higher chance of exposure and therefore a higher chance of immunity).The age distribution was even across the age groups and, as seen in the ROC analysis, the association between bacterial load and symptoms was not strong.Therefore we investigated an alternative explanation, the presence of a co-infecting pathogen.
The presence of increased co-infection in cases raises the possibility that the co-infecting pathogen rather than the EAEC, or a combination of both, is causing disease.To test this hypothesis we took norovirus, an infectious agent known to be present in both symptomatic and asymptomatic infection, as a comparator.As norovirus was a very common infection, we removed cases infected simultaneously with both norovirus and EAEC from the calculation: there were slightly more co-infections in EAEC-positive cases than in noroviruspositive cases (66% versus 43%).For EAEC co-infection, 12.6% were explained by enterotoxigenic E. coli (ETEC) and Shigella co-infections (Figure 5).This suggests that a proportion of EAEC cases can be explained by other pathogens (ETEC and Shigella are associated almost exclusively with symptomatic infection), but by no means all cases.
The logistic regression of co-infection univariate and multivaritate was statistically significant and again confirmed that EAEC was independently associated with disease; the odds of disease were 2.4 times higher if EAEC was present than if not and were still highly significant after controlling for co-infections.
The PAF adjustments indicated that EAEC would be responsible for disease in 3.3% of cases, a significant proportion in gastrointestinal disease, higher than for Salmonella [2].Although age was an independent predictor for disease overall, controlling for age did not change the association of disease with EAEC, and there was no interaction between EAEC and age.
This study did not directly address causality over association, but we believe that bacterial variation best explains the observed association of EAEC with disease for the following reasons.There are two common arguments for EAEC being found in high levels in healthy individuals: (i) Low levels of EAEC are present in a symptomless commensal relationship in the human gut and only increase to detectable levels after infection with a true pathogen because adherence of EAEC to the gut epithelium is stronger than for other commensals; an independent association of EAEC with disease argues against this for at least half of the infections in this study.(ii) Post-infection immunity leads to carriage in apparently healthy individuals; lack of any detectable trends in age distribution and no clear association between pathogen load and disease, as seen in norovirus infection [34], suggest that acquired immunity against EAEC does not protect against infection and is therefore unlikely to lead to symptomless carriage.Transient passage, as with plant viruses, is also unlikely, as there is no known reservoir for exposure to EAEC from outside the human gut.
It seems therefore clear that some, but not all, EAEC cause disease.The explanation for this may be that EAEC are defined by in vitro phenotype rather than by the ability to cause disease: non-pathogenic EAEC, able to agglutinate cells in the laboratory but unable to cause disease in the human host, are found in controls and in co-infections with true pathogens, but pathogenic variants are found as the sole pathogen detected in diarrhoeic stools.Attempts to define genetic markers for EAEC using alternative probes still do not define those EAEC capable of causing disease: the presence of the aat (anti-aggregative transporter) [35] or aggR (a transcriptional activator) [13,18,35] does not correlate precisely with disease, but rather with the ability to agglutinate cells in the laboratory.
It may be that the genetic factors used for EAEC diagnostics are not true virulence factors and that they rather encode the ability to adhere to human intestinal cells and allow colonisation (especially during infection with a true pathogen).It is likely that a combination of the EAEC-associated adherence factors and a true virulence factor allows EAEC to cause primary infection.This was seen in the German ST678 (O104:H4) outbreak [36], where the EAEC adherence genes were present in the same bacterial host as the Shiga-like toxin gene (stx).We suggest that an appropriate diagnostic test for pathogenic EAEC should look for the EAEC plasmid genes and other virulence factors.More work is still needed to define those other virulence factors in diarrhoeagenic EAEC.
The main limitation of this study is the lack of controls in the IID2 study.Although there were 20 years between the IID1 and IID2 studies, the demographic data for cases suggest that the epidemiology has not changed during that period.Although there may have been some change in co-infection rates, we believe the data to be relevant in 2013.Another limitation, but also a strength, of the study is the range of infectious agents identified.Small numbers in some groups of cases with co-infections (six cases or less for EAEC co-infections with C. difficile, Yersinia, Giardia, Cryptosporidium, rotavirus C, VTEC and Staphylococcus) mean that the ability to detect statistical differences between cases and controls was limited.However, the study allowed us, for the first time, to explore the association between EAEC and all potential co-infecting agents as well as the more common pathogens norovirus (n=29) and Campylobacter (n=12).

Conclusion
This study highlights the importance of EAEC as a pathogenic group of bacteria which caused disease in more than 1% of all IID cases in the UK in 2008-09.The EAEC group is most likely to be a mixture of pathotypes which needs to be split into rational subgroups before tests for detection and typing can be implemented.Detailed studies of the genetic content of EAECs from case-control studies are warranted.

Meeting reports
First joint meeting of three European tuberculosis networks M J van der Werf (Marieke.vanderWerf@ecdc.europa.eu)

Implementation of European TB prevention and control plans
Masoud Dara, WHO Regional Office Europe, Copenhagen, Denmark, and Marieke van der Werf, ECDC, Stockholm, Sweden, presented progress made with the implementation of the WHO European Region and EU TB prevention and control plans, respectively.They also presented the TB and MDR-TB epidemiological situation [7], the status of the indicators of the Berlin Declaration Monitoring and Evaluation Framework [7] and, finally, the epidemiological and core operational indicators of the Follow-up of the Framework Action Plan to fight tuberculosis in the EU [3] were assessed.
Since 2011, treatment of MDR-TB patients has been substantially scaled up with more than 97% of patients reported to be on treatment.However, treatment success rate of MDR-TB is far below the target of 75% envisaged for 2015.Furthermore there are frequent stockouts of second-line drugs for TB.The following key steps were presented to support further implementation of the Consolidated Action Plan: • continued technical support to Member States; • identify and address the social determinants of TB and M/XDR-TB; • prepare a compendium of best practices; • scale up best practices and patient-centred ambulatory care; • strengthen country capacity in surveillance for producing reliable estimates of MDR-TB; • introduce rational use of new TB medicines; • develop interventions to move towards TB elimination in low TB incidence countries; • define the role of surgery in TB and M/XDR-TB.
In the EU, only one of four epidemiological targets was met (i.e.overall decline of the five-year trend in TB case notification rates).Furthermore only one of five measured core targets was met (i.e.100% of the national TB reference laboratories achieved a performance level of >80% for smear microscopy, culture and DST for firstand second-line drugs).It was therefore concluded that continued implementation of the Framework Action Plan to Fight Tuberculosis in the EU is needed.
After the general session the meeting focussed on four specific areas: (i) diagnosis; (ii) treatment and care; (iii) infection control, and; (iv) advocacy, partnerships and political commitment.First, selected low incidence and high TB priority countries presented their key achievements and challenges.This was followed by four working groups on the aforementioned themes.

Diagnosis
Gulnoz Uzakova, Global Fund to Fight AIDS, Tuberculosis and Malaria TB grant manager, Tashkent, Uzbekistan, considered the improved diagnostic infrastructure and implementation of an external quality assurance scheme (EQA) in Uzbekistan as key achievements.Also, rapid drug susceptibility tests are implemented both at central and peripheral level.Good political commitment, as well as partnership and collaboration between the national and international organisations have been established.However, the targets for culture confirmation, coverage of first-line drug sensitivity testing (DST), and coverage of second-line DST are not met.The logistics, such as transportation of sputum samples, need to be improved, as well as data interpretation and information flows.
In Italy, key achievements presented by Daniela Cirillo, San Raffaele Scientific Institute, Milan, include a wellfunctioning infrastructure of laboratories on three levels and implementation of EQA for both first and second line DST.There is also a good system for regular training of laboratory staff.The key challenges are the need to strengthen the surveillance system and data reporting within Italy and its regions and from the regional to the national level.There is also a lack of funds for the implementation and support of the regional and national laboratory networks.
The working group on diagnosis addressed several questions, among which the role of national TB reference laboratories, access to rapid TB diagnosis and existing problems in implementation of novel technologies and drug susceptibility testing to second line drugs.The main conclusions were that in principle the national reference laboratory is responsible for the quality of the TB laboratory network at country level.However, in practice not all national reference laboratories are able to perform this function because they are not authorised or because of funding.To ensure a high quality of laboratory test results, TB laboratories should be accredited by designated national bodies and/or have a quality management system.A challenge is that national legislations and regulations differ in the requirements and levels of laboratory accreditation.Universal access to rapid diagnosis of TB is currently hampered by the costs of the tests, administrative obstacles, lack of training and managerial capacity, and inappropriate requests of the tests by clinicians.The working group emphasised the need for a prioritisation of DST for fluoroquinolones (FQ) and injectable second line drugs to detect early XDR cases.Major challenges include the unavailability of laboratory supplies, the lack of EQA, high costs, a lack of standardisation and need to improve the clinical interpretation of test results.

Treatment and care
According to Armen Hayrapetyan National TB Programme, Yerevan, Armenia, the TB notification rate is steadily decreasing in Armenia.Since 2007, the treatment success of MDR-TB has remained low at about 53-55%.Another challenge is the increasing number of individuals co-infected with TB and human immunodeficiency virus (HIV).Key achievements in Armenia are the availability of a TB/MDR/XDR response plan, and national guidelines for TB care.Also drugs for treatment of M/XDR-TB patients are now available.A programme for TB home-based care has been introduced.The key challenges for Armenia are the modernisation of the TB services, and the training of physicians, nurses and TB specialists.
In Hungary, there has been a steady decline of TB and the level of MDR-TB is low (<3%) as reported by Kovács Gábor, Koranyi National Institute for Tuberculosis and Pulmonology, Budapest.There is political commitment and a new national TB control plan is under development.Hungary has protocols for TB treatment and diagnosis which are in line with international recommendations.The country lacks adequate human resources in the healthcare sector in general and for TB specifically.There is a need to improve the model for treatment support to improve the treatment outcomes.
The working group on TB treatment and care discussed progress in improving universal access to TB treatment and care.Considerable progress has been made, especially by involving non-governmental organisations (NGOs) which link with vulnerable and high-risk groups.A key recommendation is to further increase the collaboration with NGOs, especially those working in HIV care.The availability of new drugs, such as bedaquiline, widens the treatment arsenal.Participants agreed that stringent pharmacovigilance, careful planning, ethical clearance and quality controls must be in place to ensure rational and effective use of new medicines.Countries are optimising their TB models of care, shifting from hospital based towards more ambulatory care, while improving quality of care and rational use of inpatient facilities with infection control standards.These need to be accompanied with training and retraining health staff in TB services and primary health care facilities.Another key recommendation is that a shift towards more ambulatory TB models of care should be accompanied by a reform of TB financing, well planned and intensive training of the healthcare workers involved and adequate psycho-social patient support throughout treatment.

Infection control
In Georgia, key achievements within the area of infection control as presented by Nestan Tukvadze, National Center for Tuberculosis and Lung Diseases, Tbilisi include the finalisation of national TB infection control guidelines in line with WHO recommendations, the implementation of a basic infection control risk assessment for TB service points, and the renovation of TB outpatient service points and microscopy laboratories.Currently Georgia is working on expanding the 'three I's' (intensified TB case-finding, initiate TB prevention with isoniazid preventive therapy and early antiretroviral therapy, and TB infection control [8]), training of healthcare workers and developing infection control standards for renovation and construction of healthcare facilities.Some of the key challenges that need to be addressed are monitoring and evaluation of implementation and impact of infection control measures, and adequate maintenance of engineering control measures.
Norway has comprehensive guidelines for TB control, care and prevention which are well disseminated and accepted by the healthcare providers according to Karin Rønning, Norwegian Institute of Public Health, Oslo.National infection control guidelines are available; however, they do not contain a separate TB infection control plan.The implementation of infection control measures is supported by comprehensive regulations and guidelines.The standards of healthcare facilities are generally very high, with adequate isolation capacity available.To stop TB transmission the challenge for Norway is to quickly identify cases and provide them with high quality treatment and care.The working group discussed topics important for adequate TB infection control, such as national TB infection control guidelines and strategic plans, funding and other organisational mechanisms, human resources capacity building, and monitoring and evaluation of TB infection control activities.
The main conclusions were that progress has been made on TB infection control across the Region and that infection control should be an integral part of national strategic TB plans.Countries should focus on best possible (cost)-effective infection control measures.

Key recommendations included:
• ensure a proper funding mechanism for TB infection control measures;

Advocacy, partnerships and political commitment
Jonathan Stillo, TB Europe Coalition, Bucharest, reported that Romania has a significant TB burden with a high number of MDR-TB cases and a treatment success rate for MDR-TB cases below the target.Frequent changes of high level decision-makers have resulted in a lack of coherence and continuity in TB control.
There are serious challenges related to financing of TB control.A step towards strengthening advocacy and a push for political commitment was the formation of the Romanian Stop TB Partnership including 19 NGOs.The presence of the international community is important to build partnerships and to ensure political commitment.
Simon Logan, All-Party Parliamentary Group on Global Tuberculosis, London, United Kingdom, informed about this group which is working across political parties to address TB by arranging meetings in the parliament, working through parliamentary procedures such as debates, oral and written questions and publishing reports.Partnerships among NGOs, academics, civil servants and public health professionals are key to building a strong and united approach.
The working group gathered participants from civil society, national TB programmes and international organisations and aimed to identify the main challenges to advocacy in the region, what action could be taken to remedy these challenges and the tools and resources needed.
The main conclusions are that there is insufficient involvement of all stakeholders in advocacy and a general lack of understanding of its added value.Hence, the inadequacy of funds for advocacy activities, and the lack of capacity and expertise for civil society and others to run such activities.
Key recommendations were to document evidence of the added value of advocacy efforts, build the capacity of TB stakeholders in advocacy, enhance coordination and partnership at country level, increase political awareness of TB and advocate for more funding for advocacy.

Conclusions
The joint day finished with a presentation of the EU Standards for Tuberculosis Care [9].This document describes the standards for four areas, i.e.TB diagnosis, TB treatment, HIV infection and comorbid conditions, public health and TB prevention (including infection control).Three of these had been discussed during the day as well.This first joint meeting helped to facilitate exchange of good practices between professionals working in different areas of TB control and prevention in Europe.Key areas that need strenghtening to reach the targets of the TB control and prevention plans were identified and key recommendations were agreed on.
participant-based analysis with censoring for influenzaParticipants with an episode of non-influenza illness, with censoring for influenza b p

Figure 2 Figure 3
Figure 2Cumulative incidence of invasive meningococcal disease for citizens and residents of Saudi Arabia by age group and sex, 1995-2011 (n=645)

Table 2
Characteristics of participants in the live attenuated influenza vaccine (LAIV) and palivizumab randomised placebocontrolled clinical trials (RCT)

Table 1
Confirmed invasive meningococcal disease cases by residency status in Saudi Arabia,1995-2011 (n=1,103)In the 2000 and 2001 outbreak years, IMD cases from Mecca and Medina during the Hajj accounted for 49% and 31% of all notified annual IMD cases, respectively (Figure1B).In contrast, between 2002 and 2011, only a mean annual 8.1% (standard deviation (SD): 10.1) of all IMD cases were reported from Mecca or Medina during the Hajj season.Since 2006, during Hajj seasons, Medina reported only one case of IMD.The mean numbers of Hajj-related cases was higher (13.4 cases/year; SD: 9.3) during the pre-epidemic than during the postepidemic years (1.7 cases/year; SD: 2.3; p=0.02).
IMD: invasive meningococcal disease; SD: standard deviation.aUnless otherwise specified.bFor the period considered, only the number of citizens and residents combined are available.No reliable numbers for Umrah pilgrims and persons with illegal residency status are available.Hajj-related cases

Table 2
Distribution of serogroups for all typed isolates (n=656) among invasive meningococcal disease cases (n=1,103) and stratification by time periods, age groups, and outcome, Saudi Arabia CFR: case fatality ratio; IMD: invasive meningococcal disease.Of 1,103 isolates from cases of invasive meningococcal disease 369 isolates were not typable and for 78 isolates serogroups were not reported.The CFR for cases with untypable isolates was 9.8% (36 deaths).a Pre-epidemic period.b Epidemic period.c Post-epidemic period.d CFR=Deaths/total number of confirmed IMD cases.

Table 3
Mortality, case fatality ratio and relative risk of dying from invasive meningococcal disease by residency status, Hajj season, age group and sex, SaudiArabia, 1995Arabia,  -2011 (n=1,103)    (n=1,103) CFR: case fatality ratio; CI: confidence interval; NA: not applicable.aCFR=(Number of deaths /Number of confirmed IMD cases) in each category.bTherelative risk of dying from invasive meningococcal disease is calculated by dividing the CFR of the relevant row by the CFR of the reference row.

Table 4
Annual mean case fatality ratio (CFR) by age groups, SaudiArabia, 1995Arabia,  -2011 There were a higher variety of co-infection types, a higher percentage of co-infections and more multiple co-infection in EAEC-positive cases than in EAEC-positive controls.Note: organisms designated sp.include all species of that genus (except Campylobacter sp. which list C. jejuni and C. coli separately), Staphylococcus aureus refers to all S. aureus >106/g.The p values are indicated on the right.

1 , C Erkens 2 , A Gebhard 2 , F Voitzwinkler 3 , M Dara 4
• update regularly national TB infection control regulations; • adapt TB infection control training modules based on country context; • advocate for and develop plans for TB infection control operational research; • develop country-adapted standardised specifications for ventilation systems, and for ultraviolet germicidal irradiation equipment.