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. 2019 May 2;19:487. doi: 10.1186/s12889-019-6713-5

Influenza epidemiology and influenza vaccine effectiveness during the 2016–2017 season in the Global Influenza Hospital Surveillance Network (GIHSN)

Víctor Baselga-Moreno 1, Svetlana Trushakova 2, Shelly McNeil 3, Anna Sominina 4, Marta C Nunes 5,6, Anca Draganescu 7, Serhat Unal 8, Parvaiz Koul 9, Jan Kyncl 10, Tao Zhang 11, Ainagul Kuatbayeva 12, Afif Ben-Salah 13,14, Elena Burtseva 2, Joan Puig-Barberà 1, Javier Díez-Domingo 1,✉; for the Global Influenza Hospital Surveillance Network (GIHSN)
PMCID: PMC6498567  PMID: 31046725

Abstract

Background

The Global Influenza Hospital Surveillance Network (GIHSN) aims to determine the burden of severe influenza disease and Influenza Vaccine Effectiveness (IVE). This is a prospective, active surveillance and hospital-based epidemiological study to collect epidemiological data in the GIHSN. In the 2016–2017 influenza season, 15 sites in 14 countries participated in the GIHSN, although the analyses could not be performed in 2 sites. A common core protocol was used in order to make results comparable. Here we present the results of the GIHSN 2016–2017 influenza season.

Methods

A RT-PCR test was performed to all patients that accomplished the requirements detailed on a common core protocol. Patients admitted were included in the study after signing the informed consent, if they were residents, not institutionalised, not discharged in the previous 30 days from other hospitalisation with symptoms onset within the 7 days prior to admission. Patients 5 years old or more must also complied the Influenza-Like Illness definition. A test negative-design was implemented to perform IVE analysis. IVE was estimated using a logistic regression model, with the formula IVE = (1-aOR) × 100, where aOR is the adjusted Odds Ratio comparing cases and controls.

Results

Among 21,967 screened patients, 10,140 (46.16%) were included, as they accomplished the inclusion criteria, and tested, and therefore 11,827 (53.84%) patients were excluded. Around 60% of all patients included with laboratory results were recruited at 3 sites. The predominant strain was A(H3N2), detected in 63.6% of the cases (1840 patients), followed by B/Victoria, in 21.3% of the cases (618 patients). There were 2895 influenza positive patients (28.6% of the included patients). A(H1N1)pdm09 strain was mainly found in Mexico. IVE could only be performed in 6 sites separately. Overall IVE was 27.24 (95% CI 15.62–37.27. Vaccination seemed to confer better protection against influenza B and in people 2–4 years, or 85 years old or older. The aOR for hospitalized and testing positive for influenza was 3.02 (95% CI 1.59–5.76) comparing pregnant with non-pregnant women.

Conclusions

Vaccination prevented around 1 in 4 hospitalisations with influenza. Sparse numbers didn’t allow estimating IVE in all sites separately. Pregnancy was found a risk factor for influenza, having 3 times more risk of being admitted with influenza for pregnant women.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6713-5) contains supplementary material, which is available to authorized users.

Keywords: Influenza virus, Surveillance, Vaccine effectiveness, Epidemiology

Background

Influenza is a major public health problem that can cause hospitalisations, and it is related with respiratory failures [1, 2]. The Global Influenza Hospital Surveillance Network (GIHSN) is an international public-private collaboration that started in 2012. The GIHSN goals are to improve understanding of influenza epidemiology, quantifying the circulation of the different types and subtypes of influenza, in order to measure the effectiveness of seasonal influenza vaccines and better inform public health policy decisions. We conduct a prospective, active surveillance, hospital-based epidemiological study that collects epidemiological and virological data from those sites that are included in the network. Each season results are presented in annual meetings and, since 2012, have been published [3–6], with the agreement of the Principal Investigators of all concerned sites. The implementation and data collection for the last season (2016–2017) was led by the Foundation for the Promotion of Health and Biomedical Research of Valencia Region (FISABIO), a regional public health institution in Valencia, Spain, and funded by the Foundation for Influenza Epidemiology. Fifteen sites in fourteen countries participated in the GIHSN in the season 2016–2017. Among them, there were 12 sites (St. Petersburg, Moscow, Kazakhstan, Czech Rep., Canada, Romania, Turkey, Spain, Tunisia, Suzhou/Shanghai, India and Mexico) from Northern Hemisphere countries not situated in the tropics and three sites (Ivory Coast, Peru and South Africa) from the tropics or the Southern Hemisphere. Since Peru and Ivory Coast only reported two positive cases for influenza in the influenza season, the analysis was performed without the data from these countries, and therefore, results are reported for 13 sites. A common core protocol and standard operating procedures are used for all participating sites, in order to allow comparisons among countries, and analyse results of all sites.

Methods

This study aims to determine the frequency of influenza-related hospitalisations in different countries, by circulating strains and age groups, to study risk factors for influenza-associated hospitalisations and estimate Influenza Vaccine Effectiveness (IVE) by site, age group and strain. Each site had one or more hospitals that recruited patients for the study, between October 2016 and May 2017 in Northern Hemisphere sites, except China, whose patients were recruited between June and September. For Southern Hemisphere sites, patients were recruited between May and November. Patients were included in the study if they presented any of the admission diagnoses included in the protocol, and only if they signed the informed consent to participate in the study. Among them, we selected for the study only those who were residents in the predefined hospital catchment’s area in the previous past 6 months, who were not institutionalised, who hadn’t been discharged from other hospitalisation in the last 30 days, and who had symptoms possibly related to influenza in 7 days or less prior to admission (Fig. 1). We also excluded patients who had previously tested positive for influenza in the current season, and also patients for whom the difference between the date of the onset of symptoms and the date of swabbing was 10 days or more (that is, those admitted after the 7th day after the onset of symptoms+maximum delay in swabbing). For patients 5 years old or more, they must also have complied with the Influenza-Like Illness (ILI) definition, detailed in European Centre for Disease Prevention and Control (ECDC) protocols, according to the decision of the Commission of the European Union of 8 August 2012 [7]. Patients enrolled outside the influenza epidemic period of each of the participating sites were also excluded. Influenza seasons were previously determined by each site, following recommendations of previous studies [8]. This methodology has been used in the GIHSN since the beginning of the network, and has been previously described [9]. For patients under 14 years old, nasal and/or nasopharyngeal swabs were collected, whereas, for patients 14 years old or more, pharyngeal and/or nasopharyngeal swabs were taken. Reverse transcription-polymerase chain reaction (RT-PCR) was used, according to each site’s protocol, in order to detect influenza virus; viral subtyping was performed in order to identify A(H1N1)pdm09, A(H3N2), B/Yamagata-lineage, and B/Victoria-lineage strains in the positive specimens.

Fig. 1.

Fig. 1

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Overview of the methodology used by the GIHSN

We performed a test-negative study [10] in order to compare positives (cases) and negatives (controls) for influenza and estimate Influenza Vaccine Effectiveness (IVE). Odds Ratios were used to estimate IVE, comparing cases and controls of patients depending on the vaccination status. Patients were considered vaccinated if they received an influenza vaccine in the current season, at least 15 days before the onset of symptoms. Patients with contra-indication to influenza vaccination were excluded from the IVE analysis, but were included in the analysis regarding influenza circulation. Vaccination status was ascertained either by recall or by vaccination registries. Adjusted odds ratios (aOR) were calculated using a logistic regression model including sex, occupational social class, obesity status, pregnancy, underlying conditions, general practitioner (GP) consultations in last 3 months, smoking habits, days from onset of symptoms to swabbing as fixed effects, age and epidemiological week of admission using cubic splines, and site as a cluster variable, in order to consider sites variability [11]. IVE was calculated as (1-aOR) × 100. The same factors were used to adjust IVE by strain or age group. The variables relative to the Barthel Index (in patients 65 years old or older) and the previous hospitalisations in the last year were initially considered to be included in the model, but were excluded from the final model as they were not statistically significant considering all variables mentioned above. The model did not include the number of consultations at the GP in the last 3 months to estimate IVE in Canada, as this site did not provide information for this variable. Severe outcomes were also studied, defining them as an influenza positive patient admitted to ICU during the hospitalisation, or with COPD exacerbation, respiratory failure, any cardiovascular complication, shock or death during hospitalisation. Heterogeneity was studied, using the I2 test, and considering that heterogeneity was relevant if I2 ≥ 50% [12, 13].

Results

Included patients: distribution, characteristics and influenza positives and negatives

There were 21,967 eligible admissions between October 1, 2016 and November 9, 2017. However, only 10,140 patients complied with the conditions described above, and had laboratory results, hence only these were included in the analysis. Among them, 2895 (28.6%) tested positive for influenza, and 7245 (71.4%) tested negative for influenza (Table 1). The most common reason of exclusion was the fact that patients didn’t have ILI symptoms in the 7 days previous to admission. It is important to note that 2/3 of all included patients in the GIHSN came from 4 sites (St. Petersburg, Moscow, Canada and Valencia). These 4 sites also have the highest numbers of influenza positive cases, including 77.8% of all influenza positives in the GIHSN, and 84.3% of the A(H3N2) influenza positives among all participant sites. A (H3N2) was the predominant strain this season, being detected in 63.6% of all influenza positive cases (1840 patients), followed by B/Victoria, with 21.3% among the influenza positive cases (618 patients) (Table 1). Influenza A(H3N2) was detected throughout the season, whereas B/Victoria started to increase in the second week of 2017 in the Northern Hemisphere, and in the 31st week of 2017 in the Southern Hemisphere, approximately in the middle of the season in each Hemisphere (Fig. 2).

Table 1.

Patients included and excluded in the current analyses, inclusion criteria and influenza laboratory results

Category St. Pet Moscow Kazakhstan Czech Rep. Canada Romania Turkey Valencia Tunisia Suzhou/ Shanghai India Mexico South Africa Total
n % n % n % n % n % N % n % n % n % n % n % n % n % n %
Screened admissions 2012 2244 661 201 2450 902 917 6913 106 1264 693 1480 2124 21967
Exclusion criteria
 Non resident 2 0.1 167 7.4 0 0.0 3 1.5 1 0.0 394 43.7 78 8.5 25 0.4 9 8.5 180 14.2 5 0.7 294 19.9 0 0.0 1158 5.3
 institutionalised 1 0.0 19 0.8 21 3.2 0 0.0 461 18.8 1 0.1 20 2.2 358 5.2 0 0.0 1 0.1 0 0.0 9 0.6 0 0.0 891 4.1
 Previous discharged < 30 days 3 0.1 114 5.1 44 6.7 7 3.5 145 5.9 68 7.5 173 18.9 1131 16.4 5 4.7 65 5.1 33 4.8 216 14.6 0 0.0 2004 9.1
 Unable to communicate 10 0.5 136 6.1 0 0.0 11 5.5 0 0.0 0 0.0 50 5.5 367 5.3 0 0.0 30 2.4 0 0.0 126 8.5 282 13.3 1012 4.6
 Not giving consent 44 2.2 8 0.4 49 7.4 13 6.5 0 0.0 1 0.1 15 1.6 275 4.0 0 0.0 3 0.2 1 0.1 54 3.6 90 4.2 553 2.5
 No ILI symptoms ≥5 years 0 0.0 42 1.9 9 1.4 37 18.4 573 23.4 41 4.5 140 15.3 2164 31.3 0 0.0 0 0.0 0 0.0 108 7.3 215 10.1 3329 15.2
 Admission within 7 days of symptoms onset 4 0.2 124 5.5 279 42.2 8 4.0 137 5.6 4 0.4 3 0.3 335 4.8 4 3.8 301 23.8 2 0.3 216 14.6 170 8.0 1587 7.2
 Previous influenza infection 2 0.1 0 0.0 0 0.0 0 0.0 0 0.0 6 0.7 7 0.8 1 0.0 0 0.0 15 1.2 0 0.0 9 0.6 1 0.0 41 0.2
 Onset of symptoms to swab > 9 days 0 0.0 1 0.0 0 0.0 0 0.0 0 0.0 0 0.0 2 0.2 1 0.0 6 5.7 1 0.1 0 0.0 0 0.0 0 0.0 11 0.1
 Sample inadequate 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0
 Sample lost 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 25 23.6 0 0.0 0 0.0 0 0.0 0 0.0 25 0.1
 Recruited outside periods with continuous influenza positive admissions 9 0.4 13 0.6 100 15.1 11 5.5 1 0.0 0 0.0 16 1.7 131 1.9 18 17.0 198 15.7 159 22.9 98 6.6 462 21.8 1216 5.5
 Included with valid laboratory results 1937 96.3 1620 72.2 159 24.1 111 55.2 1132 46.2 387 42.9 413 45.0 2125 30.7 39 36.8 470 37.2 493 71.1 350 23.6 904 42.6 10140 46.2
RT-PCR result
 Influenza negative 1417 73.2 869 53.6 128 80.5 69 62.2 414 36.6 221 57.1 311 75.3 1862 87.6 30 76.9 433 92.1 425 86.2 259 74.0 807 89.3 7245 71.4
 Influenza positive 520 26.8 751 46.4 31 19.5 42 37.8 718 63.4 166 42.9 102 24.7 263 12.4 9 23.1 37 7.9 68 13.8 91 26.0 97 10.7 2895 28.6
Subtype and lineage
 A(H1N1)pdm09 1 0.2 0 0.0 0 0.0 1 2.4 3 0.3 0 0.0 0 0.0 0 0.0 1 11.1 1 2.7 11 16.2 56 61.5 2 2.1 76 2.6
 A(H3N2) 296 56.9 420 55.9 15 48.4 32 76.2 585 51.7 39 23.5 81 79.4 251 95.4 6 66.7 21 56.8 21 30.9 12 13.2 61 62.9 1840 63.6
 A not subtyped 34 6.5 4 0.5 0 0.0 2 4.8 67 5.9 4 2.4 3 2.9 12 4.6 0 0.0 0 0.0 0 0.0 0 0.0 3 3.1 129 4.5
 B/Yamagata lineage 2 0.4 0 0.0 0 0.0 4 9.5 35 3.1 0 0.0 19 18.6 0 0.0 2 22.2 1 2.7 0 0.0 15 16.5 30 30.9 108 3.7
 B/Victoria lineage 187 36.0 299 39.8 0 0.0 1 2.4 4 0.4 74 44.6 2 2.0 0 0.0 0 0.0 14 37.8 37 54.4 0 0.0 0 0.0 618 21.3
 B not subtyped 0 0.0 28 3.7 16 51.6 2 4.8 24 2.1 50 30.1 1 1.0 0 0.0 0 0.0 0 0.0 0 0.0 11 12.1 3 3.1 135 4.7
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Fig. 2.

Fig. 2

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Influenza-associated admissions by epidemiological week and virus type/subtype

In the Northern Hemisphere, there was a significant increase in the number of influenza cases in week #49 of 2016, with a peak in the number of positive cases during the second week of 2017 and starting to descend at the eighth week of 2017. Influenza B/Victoria started to increase clearly in the second week of 2017, as A(H3N2) started to descend. 70.3% of all influenza cases were positive for influenza A, whereas 29.7% were positive for influenza B, with a clear different distribution among sites.

A(H3N2) was predominant in all sites, except in Mexico, where the predominant strain was A(H1N1)pdm09, and Romania and India with a predominance of B/Victoria-lineage. Both B lineages circulated during this season, with geographical differences, so in Canada, Czech Republic, Turkey, Tunisia, Mexico and South Africa, B/Yamagata was more often detected, while the B/Victoria was elsewhere. Influenza B cases generally appeared as a second influenza wave (Fig. 3). In Valencia, no cases were positive for influenza B.

Fig. 3.

Fig. 3

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Admissions with influenza by site, epidemiological week and virus type/subtype

Influenza B was mainly observed in the youngest, and was the predominant strain in the age group 5–17 years old. Among the two influenza B lineages, in general B/Victoria was detected more often than B/Yamagata, except in the age group 50–64 years (Fig. 4).

Fig. 4.

Fig. 4

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Percentages of influenza-associated admissions by age group and type/subtype

The distribution of influenza cases among the age groups was clearly different among sites, but differences were mainly due to the characteristics of the participating hospitals for each site. Tunisia and Czech Republic only recruited patients 18 years old or older, while Suzhou/Shanghai only enrolled patients under 18 years old. In Moscow, the majority of influenza positives were pregnant women (which represented the 49.4% of the included patients), and therefore, the highest number of influenza positives among the different age groups was situated in the age group 18–49 years old in this site. Influenza positive cases were mainly found in patients 65 years old or older in Valencia and Canada, but 89.8% of the included patients from Canada were 50 years old or older. In St. Petersburg and South Africa, due to the characteristics of the patients of the participating hospitals (mainly children) there were more influenza positive cases in the youngest groups (Fig. 5).

Fig. 5.

Fig. 5

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Admissions with influenza by site, age group and virus type/subtype

25.8% of the included patients were previously hospitalised in the same year and 36.6% of the included patients had at least one underlying condition, but this percentage varied among sites, in Canada, for example, more than 90% of the included patients had at least one underlying condition, whereas in St. Petersburg, this percentage was lower than 10% and in Turkey was 48.2%, but these percentages could be related to the age distribution of the included patients in each site. Among the different comorbidities, the most common were cardiovascular (20.7% of the included patients), diabetes (10.4%) and chronic obstructive pulmonary disease (COPD) (9.9%). Obesity was also found in more than 14% of the included patients, being more relevant in Canada (29.6%), Valencia (26.3%) and Czech Republic (23.4%). Moscow was the site with the highest number of pregnant women among all sites (800 pregnant in Moscow among 940 pregnant women in all sites), being 49.4% of the included patients in this site. In Kazakhstan, pregnant women represented 22.6% of the included patients. The Barthel Index in those over 65 years showed that almost 90% of these subjects were not dependent or had a mild dependence. 68.3% of the patients who tested negative for influenza were swabbed from 0 to 4 days after symptoms started, but this percentage was 78.4% for influenza positive cases (p-value< 0.0001).

Vaccination coverage differed among sites. Patients were considered as vaccinated if vaccination was at least 15 days before symptoms onset (Table 2). Targeted patients for vaccination criteria were different among sites (Additional file 1: Complementary Table S1). Vaccination coverage was 11.1% among the influenza positives and 18.4% among the influenza negatives overall. Cardiovascular diseases, renal impairment, chronic obstructive pulmonary disease and diabetes were the most common comorbidities among influenza positives (Table 3). Seasonality had also a clear geographical distribution. Sites in higher latitudes had, generally, an earlier start of the influenza season.

Table 2.

Characteristics of included patients overall and by site

Characteristic St. Pet Moscow Kazakhstan Czech Rep. Canada Romania Turkey Valencia Tunisia Suzhou/ Shanghai India Mexico South Africa Total
N = 1937 N = 1620 N = 159 N = 111 N = 1132 N = 387 N = 413 N = 2125 N = 39 N = 470 N = 493 N = 350 N = 904 N = 10,140
n % n % n % n % n % n % n % n % n % n % n % n % n % n %
Age in years, median (range) 3 (0–87) 24 (0–91) 17 (1–76) 64 (18–90) 76 (17–105) 5 (0–63) 3 (0–95) 68 (0–102) 58 (14–84) 0 (0–13) 60 (0–99) 3 (0–96) 0 (0–91) 20 (0–105)
Age group
 0–1 y 684 35.3 167 10.3 34 21.4 0 0.0 0 0.0 89 23.0 179 43.3 421 19.8 0 0.0 334 71.1 57 11.6 151 43.1 576 63.7 2692 27.0
 2–4 y 483 24.9 156 9.6 33 20.8 0 0.0 0 0.0 87 22.5 39 9.4 108 5.1 0 0.0 96 20.4 19 3.9 50 14.3 146 16.2 1217 12.2
 5–17 y 310 16.0 182 11.2 14 8.8 0 0.0 1 0.1 118 30.5 32 7.7 54 2.5 1 2.6 40 8.5 16 3.2 43 12.3 16 1.8 827 8.3
 18–49 y 388 20.0 1052 64.9 73 45.9 37 33.3 97 8.6 72 18.6 14 3.4 145 6.8 9 23.1 0 0.0 79 16.0 52 14.9 82 9.1 2100 21.1
 50–64 y 49 2.5 34 2.1 2 1.3 20 18.0 156 13.8 21 5.4 45 10.9 227 10.7 12 30.8 0 0.0 100 20.3 21 6.0 48 5.3 735 7.4
 65–74 y 12 0.6 12 0.7 2 1.3 24 21.6 196 17.3 0 0.0 29 7.0 335 15.8 8 20.5 0 0.0 143 29.0 11 3.1 21 2.3 793 8.0
 75–84 y 9 0.5 10 0.6 1 0.6 20 18.0 264 23.3 0 0.0 55 13.3 462 21.7 9 23.1 0 0.0 51 10.3 11 3.1 11 1.2 903 9.0
  ≥ 85 y 2 0.1 7 0.4 0 0.0 10 9.0 246 21.7 0 0.0 20 4.8 373 17.6 0 0.0 0 0.0 28 5.7 11 3.1 4 0.4 701 7.0
Sex
 Male 1050 54.2 607 37.5 76 47.8 64 57.7 541 47.8 205 53.0 224 54.2 1125 52.9 27 69.2 287 61.1 242 49.1 171 48.9 486 53.8 5105 50.3
 Female 887 45.8 1013 62.5 83 52.2 47 42.3 591 52.2 182 47.0 189 45.8 1000 47.1 12 30.8 183 38.9 251 50.9 179 51.1 418 46.2 5035 49.7
Chronic conditions
 0 1758 90.8 1382 85.3 111 69.8 35 31.5 99 8.7 349 90.2 214 51.8 803 37.8 7 17.9 443 94.3 129 26.2 218 62.3 878 97.1 6426 63.4
 1 157 8.1 187 11.5 42 26.4 40 36.0 307 27.1 28 7.2 87 21.1 626 29.5 18 46.2 27 5.7 182 36.9 85 24.3 26 2.9 1812 17.9
  ≥2 22 1.1 51 3.1 6 3.8 36 32.4 726 64.1 10 2.6 112 27.1 696 32.8 14 35.9 0 0.0 182 36.9 47 13.4 0 0.0 1902 18.7
Previously hospitalised (last 12 months)
 No 1447 74.7 1354 83.6 143 89.9 80 72.1 – – 279 72.1 272 65.9 1457 68.6 30 76.9 329 70.0 312 63.3 240 68.6 745 82.4 6688 74.2
 Yes 490 25.3 266 16.4 16 10.1 31 27.9 – – 108 27.9 141 34.1 668 31.4 9 23.1 141 30.0 181 36.7 110 31.4 159 17.6 2320 25.8
Underlying chronic conditions
 Cardiovascular disease 49 2.5 70 4.3 5 3.1 50 45.0 872 77.0 17 4.4 110 26.6 602 28.3 15 38.5 24 5.1 199 40.4 65 18.6 16 1.8 2094 20.7
 Chronic obstructive pulmonary disease 21 1.1 23 1.4 24 15.1 7 6.3 134 11.8 1 0.3 70 16.9 500 23.5 21 53.8 0 0.0 177 35.9 28 8.0 2 0.2 1008 9.9
 Asthma 28 1.4 29 1.8 0 0.0 7 6.3 146 12.9 2 0.5 46 11.1 162 7.6 2 5.1 2 0.4 5 1.0 27 7.7 7 0.8 463 4.6
 Immunodeficiency/organ transplant 13 0.7 1 0.1 1 0.6 4 3.6 114 10.1 8 2.1 18 4.4 29 1.4 1 2.6 0 0.0 17 3.4 16 4.6 0 0.0 222 2.2
 Diabetes 7 0.4 16 1.0 3 1.9 25 22.5 344 30.4 6 1.6 47 11.4 500 23.5 7 17.9 0 0.0 71 14.4 23 6.6 0 0.0 1049 10.3
 Renal impairment 4 0.2 74 4.6 15 9.4 3 2.7 167 14.8 4 1.0 27 6.5 274 12.9 4 10.3 1 0.2 29 5.9 14 4.0 1 0.1 617 6.1
 Neuromuscular disease 56 2.9 29 1.8 6 3.8 6 5.4 182 16.1 0 0.0 31 7.5 57 2.7 1 2.6 0 0.0 45 9.1 13 3.7 0 0.0 426 4.2
 Neoplasm 0 0.0 15 0.9 0 0.0 11 9.9 239 21.1 5 1.3 27 6.5 141 6.6 0 0.0 0 0.0 33 6.7 8 2.3 0 0.0 479 4.7
 Cirrhosis/liver disease 18 0.9 18 1.1 1 0.6 3 2.7 22 1.9 5 1.3 6 1.5 62 2.9 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 135 1.3
 Autoimmune disease 7 0.4 29 1.8 0 0.0 5 4.5 1 0.1 5 1.3 5 1.2 43 2.0 2 5.1 0 0.0 22 4.5 12 3.4 0 0.0 131 1.3
Pregnant (women 15–45 y) 72 3.7 800 49.4 36 22.6 3 2.7 14 1.2 7 1.8 0 0.0 2 0.1 0 0.0 0 0.0 0 0.0 2 0.6 4 0.4 940 9.3
Obese (all ages) 165 8.5 150 9.3 13 8.2 26 23.4 197 29.6 35 9.0 76 18.4 559 26.3 5 12.8 77 16.4 37 7.5 46 13.1 71 9.6 1457 14.4
Outpatient consultations last 3 months
 0 894 46.2 658 40.6 116 73.0 33 29.7 – – 166 42.9 148 35.8 233 11.0 14 35.9 44 9.4 120 24.3 81 23.1 776 85.8 3283 36.4
 1 624 32.2 238 14.7 43 27.0 34 30.6 – – 121 31.3 100 24.2 413 19.4 11 28.2 123 28.3 59 12.0 70 20.0 82 9.1 1928 21.4
  ≥ 2 419 21.6 724 44.7 0 0.0 44 39.6 – – 100 25.8 165 40.0 1479 69.6 14 35.9 293 62.3 314 63.7 199 56.9 46 5.1 3797 42.2
Smoking habits (patients ≥18 y)
 Never smoker 222 48.3 698 62.6 58 74.4 51 45.9 431 43.5 55 59.1 85 52.1 784 50.8 15 39.5 0 – 198 49.4 57 53.8 102 61.4 2756 52.4
 Past smoker 46 10.0 263 23.6 16 20.5 24 21.6 387 39.1 6 6.5 59 36.2 464 30.1 12 31.6 0 – 121 30.2 34 32.1 35 21.1 1467 27.9
 Current smoker 192 41.7 154 13.8 4 5.1 36 32.4 172 17.4 32 34.4 19 11.7 294 19.1 11 28.9 0 – 82 20.4 15 14.2 29 17.5 1040 19.7
Functional status impairment (Barthel score; patients ≥65 y)
 Total (0–15) 0 0.0 0 0.0 0 0.0 0 0.0 14 2.8 0 – 8 8.3 94 8.0 0 0.0 0 – 13 5.9 0 0.0 1 5.6 130 6.0
 Severe (20–35) 0 0.0 0 0.0 0 0.0 0 0.0 11 2.2 0 – 3 3.1 26 2.2 3 17.6 0 – 3 1.4 3 9.1 1 5.6 50 2.3
 Moderate (40–55) 0 0.0 2 6.9 0 0.0 1 1.9 15 3.0 0 – 3 3.1 54 4.6 8 47.1 0 – 8 3.6 1 3.0 1 5.6 93 4.3
 Mild (60–90) 4 18.2 7 24.1 2 66.7 14 25.9 90 17.9 0 – 35 36.5 261 22.3 4 23.5 0 – 62 27.9 12 36.4 9 50.0 500 23.1
 Minimal (95–100) 18 81.8 20 69.0 1 33.3 39 72.2 373 74.2 0 – 47 49.0 735 62.8 2 11.8 0 – 136 61.3 17 51.5 6 33.3 1394 64.3
Sampling time
 0–2 days 1160 59.9 843 52.0 109 68.6 31 27.9 474 41.9 76 19.6 59 14.3 386 18.2 7 17.9 8 1.7 44 8.9 67 19.1 321 39.1 3585 35.6
 3–4 days 568 29.3 595 36.7 46 28.9 42 37.8 387 34.2 155 40.1 161 39.0 892 42.0 14 35.9 107 22.8 175 35.5 123 35.1 308 37.5 3573 35.5
 5–7 days 209 10.8 179 11.0 4 2.5 37 33.3 259 22.9 144 37.2 181 43.8 655 30.8 18 46.2 264 56.2 274 55.6 141 40.3 140 17.1 2505 24.9
 8–9 days 0 0.0 3 0.2 0 0.0 1 0.9 12 1.1 12 3.1 12 2.9 192 9.0 0 0.0 91 19.4 0 0.0 19 5.4 52 6.3 394 3.9
Influenza vaccination ≥15 days from symptom onset 86 4.4 65 4.0 0 0.0 6 5.4 139 12.3 7 1.8 21 5.1 825 38.8 2 5.1 1 0.2 11 2.2 49 14.0 5 0.6 1217 12.0
Influenza vaccination ≥15 days from symptom onset (age ≥ 65) 2 8.7 5 17.2 0 0.0 6 11.1 124 14.1 0 – 14 13.5 701 59.9 2 11.8 0 – 5 2.3 9 27.3 0 0.0 868 33.8
Influenza vaccination ≥15 days from symptom onset (targeted groups) 65 4.5 30 2.2 0 0.0 6 7.0 138 12.7 3 4.4 21 9.0 806 50.3 2 6.1 1 0.4 8 2.1 43 16.0 2 1.5 1125 16.0
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Table 3.

Characteristics of included patients according to RT-PCR result

Influenza negative Influenza positive A (H1N1)pdm09 A (H3N2) A not subtyped B/Yamagata B/Victoria B not subtyped
N = 7245 N = 2895 N = 76 N = 1840 N = 129 N = 108 N = 618 N = 135
Characteristic n % n % P vs. negative n % P vs. negative n % P vs. negative n % P vs. negative n % P vs. negative n % P vs. negative n % P vs. negative
Age in years, median (range) 12 (0–105) 28 (0–103) < 0.001 35 (0–84) 0.083 35 (0–103) < 0.001 48 (0–102) < 0.001 13 (0–92) 0.840 18 (0–89) 0.008 7 (0–94) 0.139
Age group < 0.0001 0.0001 < 0.0001 < 0.0001 0.0003 < 0.0001 < 0.0001
 0–1 y 2361 32.8 331 11.9 11 14.5 220 12.5 16 16.0 20 19.8 47 7.6 20 14.9
 2–4 y 906 12.6 311 11.2 12 15.8 162 9.2 13 13.0 16 15.8 86 13.9 24 17.9
 5–17 y 446 6.2 381 13.7 7 9.2 143 8.1 7 7.0 15 14.9 176 28.5 35 26.1
 18–49 y 1305 18.1 795 28.7 23 30.3 440 25.1 15 15.0 10 9.9 282 45.6 26 19.4
 50–64 y 540 7.5 195 7.0 13 17.1 159 9.1 3 3.0 12 11.9 5 0.8 4 3.0
 65–74 y 565 7.9 228 8.2 7 9.2 178 10.1 15 15.0 7 6.9 11 1.8 10 7.5
 75–84 y 631 8.8 272 9.8 3 3.9 223 12.7 16 16.0 11 10.9 9 1.5 12 9.0
  ≥ 85 y 441 6.1 260 9.4 0 0.0 230 13.1 15 15.0 10 9.9 2 0.3 3 2.2
Sex < 0.0001 0.1374 < 0.0001 0.3877 0.6826 < 0.0001 0.5137
 Male 3766 52.0 1339 46.3 33 43.4 859 46.7 72 55.8 54 50.0 254 41.1 74 54.8
 Female 3479 48.0 1556 53.7 43 56.6 981 53.3 57 44.2 54 50.0 364 58.9 61 45.2
Chronic conditions < 0.0001 0.1801 < 0.0001 < 0.0001 0.0025 < 0.0001 0.6485
 0 4765 65.8 1661 57.4 44 57.9 894 48.6 51 39.5 58 53.7 528 85.4 92 68.1
 1 1240 17.1 572 19.8 19 25.0 415 22.6 27 20.9 18 16.7 71 11.5 24 17.8
  ≥2 1240 17.1 662 22.9 13 17.1 531 28.9 51 39.5 32 29.6 19 3.1 19 14.1
Previously hospitalised (last 12 months) 0.0163 0.2604 0.9969 0.6372 0.8445 0.0002 0.0086
 No 5029 73.6 1659 76.2 58 79.5 924 73.6 44 71.0 53 72.6 494 80.5 94 84.7
 Yes 1802 26.4 518 23.8 15 20.5 331 26.4 18 29.0 20 27.4 120 19.5 17 15.3
Underlying chronic conditions
 Cardiovascular disease 1298 17.9 796 27.5 < 0.0001 17 22.4 0.3145 627 34.1 < 0.0001 60 46.5 < 0.0001 37 34.3 < 0.0001 30 4.9 < 0.0001 28 20.7 0.3970
 Chronic obstructive pulmonary disease 802 11.1 206 7.1 < 0.0001 8 10.5 0.8806 159 8.6 0.0025 10 7.8 0.2328 10 9.3 0.5513 16 2.6 < 0.0001 7 5.2 0.0301
 Asthma 276 3.8 187 6.5 < 0.0001 6 7.9 0.0656 147 8.0 < 0.0001 14 10.9 < 0.0001 8 7.4 0.0541 8 1.3 0.0013 4 3.0 0.6100
 Immunodeficiency/organ transplant 155 2.1 67 2.3 0.5867 3 3.9 0.2806 49 2.7 0.1758 7 5.4 0.0116 3 2.8 0.6497 2 0.3 0.0020 3 2.2 0.9475
 Diabetes 687 9.5 362 12.5 < 0.0001 11 14.5 0.1405 292 15.9 < 0.0001 33 25.6 < 0.0001 13 12.0 0.3693 5 0.8 < 0.0001 8 5.9 0.1610
 Renal impairment 409 5.6 208 7.2 0.0034 4 5.3 0.8858 161 8.8 < 0.0001 11 8.5 0.1616 7 6.5 0.7089 19 3.1 0.0069 7 5.2 0.8184
 Neuromuscular disease 234 3.2 192 6.6 < 0.0001 2 2.6 0.7690 147 8.0 < 0.0001 15 11.6 < 0.0001 8 7.4 0.0157 12 1.9 0.0775 9 6.7 0.0266
 Neoplasm 311 4.3 168 5.8 0.0012 0 0.0 0.0649 133 7.2 < 0.0001 20 15.5 < 0.0001 7 6.5 0.2670 4 0.6 < 0.0001 5 3.7 0.7377
 Cirrhosis/liver disease 97 1.3 38 1.3 0.9171 0 0.0 0.3099 29 1.6 0.4372 3 2.3 0.3369 1 0.9 0.7103 4 0.6 0.1428 1 0.7 0.5475
 Autoimmune disease 96 1.3 35 1.2 0.6402 1 1.3 0.9944 16 0.9 0.1139 1 0.8 0.5869 4 3.7 0.0341 12 1.9 0.2061 1 0.7 0.5548
Pregnant (women 15–45 y) 459 58.0 481 82.7 < 0.0001 1 10.0 0.0023 272 83.7 < 0.0001 2 28.6 0.1164 1 14.3 0.0198 196 89.9 < 0.0001 9 56.3 0.8866
Obese (all ages) 1083 15.6 374 14.6 0.1967 18 25.4 0.0250 271 17.0 0.1905 13 17.1 0.7231 17 18.3 0.4834 46 7.4 < 0.0001 12 9.6 0.0654
Outpatient consultations last 3 months 0.6362 0.7448 0.0005 0.7360 0.0061 0.0120 0.0008
 0 2504 36.7 779 35.8 25 34.2 388 30.9 20 32.3 40 54.8 262 42.7 48 43.2
 1 1448 21.2 480 22.0 14 19.2 287 22.9 15 24.2 11 15.1 121 19.7 35 31.5
  ≥ 2 2879 42.1 918 42.2 34 46.6 580 46.2 27 43.5 22 30.1 231 37.6 28 25.2
Smoking habits (patients ≥18 y) < 0.0001 0.0753 < 0.0001 0.1387 0.9041 0.1663 0.0818
 Never smoker 4106 57.0 1598 57.5 42 56.0 993 56.7 62 53.9 57 56.4 367 59.5 84 64.1
 Past smoker 1366 19.0 640 23.0 21 28.0 459 26.2 23 20.0 18 17.8 98 15.9 15 11.5
 Current smoker 1728 24.0 542 19.5 12 16.0 300 17.1 30 26.1 26 25.7 152 24.6 32 24.4
Functional status impairment (Barthel score; patients ≥65 y) 0.0764 0.5686 0.1750 0.9911 0.4228 0.6788 0.0012
 Total (0–15) 106 6.8 24 3.9 0 0.0 21 4.2 3 7.3 0 0.0 0 0.0 0 0.0
 Severe (20–35) 35 2.3 15 2.4 0 0.0 11 2.2 1 2.4 0 0.0 0 0.0 3 13.0
 Moderate (40–55) 62 4.0 31 5.0 0 0.0 26 5.2 1 2.4 0 0.0 1 4.5 3 13.0
 Mild (60–90) 364 23.5 136 22.1 4 44.4 109 21.9 10 24.4 6 24.0 5 22.7 3 13.0
 Minimal (95–100) 985 63.5 409 66.5 5 55.6 330 66.4 26 63.4 19 76.0 16 72.7 14 60.9
Sampling time < 0.0001 0.0051 < 0.0001 0.0797 0.7704 < 0.0001 0.3919
 0–2 days 2374 33.1 1211 42.0 16 21.1 830 45.3 54 41.9 35 32.7 237 38.3 40 29.6
 3–4 days 2521 35.2 1052 36.5 22 28.9 657 35.9 38 29.5 41 38.3 244 39.5 53 39.3
 5–7 days 1941 27.1 564 19.5 34 44.7 303 16.5 35 27.1 28 26.2 132 21.4 39 28.9
 8–9 days 335 4.7 59 2.0 4 5.3 42 2.3 2 1.6 3 2.8 5 0.8 3 2.2
Influenza vaccination ≥15 days from symptom onset 938 13.0 279 9.6 < 0.0001 7 9.2 0.3339 221 12.0 0.2825 10 7.8 0.0806 9 8.3 0.1554 25 4.1 < 0.0001 8 5.9 0.0156
Influenza vaccination ≥15 days from symptom onset (age ≥ 65) 673 39.9 195 22.1 < 0.0001 1 10.0 0.0541 175 24.4 < 0.0001 8 10.7 < 0.0001 6 17.1 0.0064 1 4.6 0.0008 4 15.4 0.0112
Influenza vaccination ≥15 days from symptom onset (targeted groups) 869 18.4 256 11.1 < 0.0001 7 13.0 0.3047 214 13.6 < 0.0001 8 7.2 0.0025 7 11.1 0.1373 14 3.1 < 0.0001 7 9.7 0.0586
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Patients with a qualified occupation had a higher risk of being admitted with influenza. Patients with a swab taken 8–9 days after symptoms onset appeared with less risk of being admitted with influenza, suggesting a decrease in the influenza viral load for these patients (Table 4).

Table 4.

Subject characteristics and risk of admission with influenza

All admissions Influenza-positive Crude OR Heterogeneity by strain (I2) aOR(*)
N = 10140 N = 2895
Characteristic N N % Value 95% CI Value 95% CI
Age group
 0–1 years 2692 331 12.3 1.00 – 79.4% 1.00 –
 2–4 years 1217 311 25.6 2.45 2.06–2.92 75.6% 0.86 0.67–1.09
 5–17 years 827 381 46.1 6.09 5.03–7.38 94.6% 1.59 0.85–2.96
 18–49 years 2100 795 37.9 4.35 3.73–5.06 96.4% 0.65 0.22–1.97
 50–64 years 735 195 26.5 2.58 2.10–3.15 96.6% 0.59 0.25–1.39
 65–74 years 793 228 28.8 2.88 2.37–3.50 95.3% 0.61 0.31–1.22
 75–84 years 903 272 30.1 3.07 2.55–3.71 96.9% 0.50 0.21–1.20
 ≥ 85 years 701 260 37.1 4.21 3.45–5.13 98.4% 0.49 0.19–1.28
Sex
 Male 5105 1339 26,2% 1.00 54.0% 1.00
 Female 5035 1556 30,9% 1.26 1.15–1.37 46.5% 0.84 0.74–0.95
Smoking habits
 Current smoker 2270 542 23,9% 1.00 81.7% 1.00
 Past smoker 2006 640 31,9% 1.49 1.30–1.71 88.4% 1.04 0.89–1.22
 Never smoker 5704 1598 28,0% 1.24 1.11–1.39 34.0% 1.09 0.93–1.28
Consultations at the GP (last 3 months)
 No 3283 779 23,7% 1.00 95.0% 1.00
 Yes 5725 1398 24,4% 1.04 0.94–1.15 92.6% 0.91 0.69–1.18
Occupation / Social class
 Qualified 3810 1255 32,9% 1.00 97.1% 1.00
  Skilled 1376 355 25,8% 0.71 0.62–0.81 81.9% 0.83 0.72–0.94
  Low or unskilled 3411 591 17,3% 0.43 0.38–0.48 91.5% 0.63 0.50–0.78
Other risk factors
 Comorbidity 3714 1234 33,2% 1.43 1.31–1.56 98.7% 0.90 0.63–1.30
 Cardiovascular disease 2094 796 38,0% 1.74 1.57–1.92 98.7% 1.01 0.72–1.40
 Chronic obstructive pulmonary disease 1008 206 20,4% 0.62 0.52–0.72 92.5% 0.66 0.45–0.98
 Asthma 463 187 40,4% 1.74 1.44–2.11 94.3% 1.31 0.96–1.77
 Immunodeficiency/organ transplant 222 67 30,2% 1.08 0.81–1.45 85.2% 0.57 0.28–1.17
 Diabetes 1049 362 34,5% 1.36 1.19–1.56 98.1% 1.19 1.03–1.37
 Chronic renal impairment 617 208 33,7% 1.29 1.09–1.54 89.2% 1.06 0.89–1.27
 Chronic neuromuscular disease 426 192 45,1% 2.13 1.75–2.59 91.7% 1.08 0.75–1.56
 Active neoplasm 479 168 35,1% 1.37 1.13–1.67 96.8% 0.63 0.42–0.95
 Chronic liver disease 135 38 28,1% 0.98 0.67–1.43 38.8% 1.09 0.79–1.50
 Autoimmune disease 131 35 26,7% 0.91 0.62–1.35 23.8% 1.14 0.84–1.56
 Obesity 1457 374 25,7% 0.92 0.81–1.04 93.3% 0.83 0.69–1.00
 Pregnancy 942 483 51,3% 2.96 2.58–3.40 97.6% 3.02 1.59–5.76
Days from onset of symptoms to swabbing
 0–2 days 3585 1211 33,8% 1.00 92.8% 1.00
 3–4 days 3573 1052 29,4% 0.82 0.74–0.90 36.9% 1.05 0.99–1.12
 5–7 days 2505 564 22,5% 0.57 0.51–0.64 83.4% 0.82 0.64–1.07
 8–9 days 394 59 15,0% 0.35 0.26–0.46 65.2% 0.60 0.47–0.77
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(*)Adjusted Odds Ratios were obtained using the model described in the ‘Methods’ section (pg.6)

Pregnant women had a 3 times higher risk of having influenza at admission than non-pregnant. Also subjects with diabetes had 1.19 times higher risk of being an influenza case. On the other hand, patients with COPD or neoplasm had lower risk of testing positive for influenza. Despite there was a high number of admissions with cardiovascular diseases (CVD), no difference in the risk of influenza was found in these patients. (Fig. 6).

Fig. 6.

Fig. 6

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Adjusted Odds Ratio (aOR) and number of admissions with influenza according to comorbidity

During pregnancy, the risk of testing positive for influenza was higher during the third trimester than in the first trimester, and also if they had any comorbidity in the first trimester (Fig. 7).

Fig. 7.

Fig. 7

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Predicted probability of having an admission with influenza in pregnant and non-pregnant women by trimester

There were no significant statistical differences among influenza positives and negatives for those who were admitted to ICU or who received mechanical ventilation or those who died while they were hospitalised, and differences for those with extracorporeal membrane oxygenation could be due to sparse numbers of patients who received extracorporeal membrane oxygenation. Apart from influenza, the main discharge diagnosis was pneumonia, either for influenza-negatives or influenza-positives (Table 5).

Table 5.

Influenza severity and complications 232 by RT-PCR results

Influenza-negative Influenza-positive A(H1N1)pdm09 A (H3N2) A not subtyped B/Yamagata B/Victoria B not subtyped
N=7245 N=2895 N=76 N=1840 N=129 N=108 N=618 N=135
Category n % n % P vs. negative n % n % n % n % n % n % P-value for distribution by strain
Severity indicator
 Intensive care unit admission 317 4.4 132 4.6 0.6656 9 11.8 102 5.5 5 3.9 5 4.6 6 1.0 6 4.4 <0.0001
 Mechanical ventilation 225 3.1 75 2.6 0.1728 5 6.6 61 3.3 3 2.3 2 1.9 3 0.5 2 1.5 0.0018
 Extracorporeal membrane oxygenation 89 1.2 9 0.3 0.0000 0 0.0 5 0.3 3 2.3 0 0.0 1 0.2 0 0.0 0.0035
 Death during hospitalisation 183 2.5 69 2.4 0.6904 4 5.3 52 2.8 3 2.3 3 2.8 5 0.8 2 1.5 0.0745
 Length of stay (days), median (interquartile range) 6 (3-8) 5 (3-8) <0.001 6 (3-10) 5 (3-8) 6 (3-9) 4 (2-6.5) 6 (4-8) 5 (3-7) 0.004
Respiratory diagnoses <0.0001 0.3163
 None 2052 28.3 1828 63.1 15 19.7 1191 64.7 79 61.2 51 47.2 435 70.4 60 44.4
 Pneumonia 2335 32.2 658 22.7 58 76.3 362 19.7 37 28.7 40 37.0 112 18.1 55 40.7
 COPD exacerbation 192 2.7 91 3.1 2 2.6 74 4.0 5 3.9 3 2.8 3 0.5 4 3.0
 Respiratory failure 109 1.5 12 0.4 1 1.3 9 0.5 1 0.8 0 0.0 0 0.0 1 0.7
 Asthma exacerbation 53 0.7 30 1.0 0 0.0 29 1.6 0 0.0 0 0.0 1 0.2 0 0.0
 Acute respiratory distress syndrome 18 0.2 2 0.1 0 0.0 0 0.0 0 0.0 0 0.0 2 0.3 0 0.0
 Pneumotorax 1 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0
 Bronchiolitis 383 5.3 48 1.7 0 0.0 29 1.6 1 0.8 0 0.0 12 1.9 6 4.4
 Upper respiratory infection 2101 29.0 226 7.8 0 0.0 146 7.9 6 4.7 14 13.0 53 8.6 9 6.7
Metabolic failure 0.1725 0.2106
 No 7016 96.8 2827 97.7 72 94.7 1803 98.0 126 97.7 106 98.1 604 97.7 127 94.1
 Acute renal failure 85 1.2 19 0.7 3 3.9 10 0.5 2 1.6 2 1.9 0 0.0 2 1.5
 Diabetic coma 8 0.1 1 0.0 0 0.0 1 0.1 0 0.0 0 0.0 0 0.0 0 0.0
 Fluid/electrolyte/acid-base/balance disorders 136 1.9 48 1.7 1 1.3 26 1.4 1 0.8 0 0.0 14 2.3 6 4.4
Cardiovascular events <0.0001 <0.0001
 None 6674 92.1 2766 95.5 69 90.8 1741 94.6 122 94.6 104 96.3 611 98.9 129 95.6
 Acute myocardial infarction 6 0.1 1 0.0 0 0.0 1 0.1 0 0.0 0 0.0 0 0.0 0 0.0
 Arterial or venous embolia 1 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0
 Carditis 2 0.0 1 0.0 0 0.0 0 0.0 0 0.0 0 0.0 1 0.2 0 0.0
 Cardiac arrest 1 0.0 1 0.0 0 0.0 1 0.1 0 0.0 0 0.0 0 0.0 0 0.0
 Malignant hypertension 1 0.0 3 0.1 0 0.0 2 0.1 0 0.0 0 0.0 0 0.0 1 0.7
 Any cardiovascular condition 560 7.7 123 4.2 7 9.2 95 5.2 7 5.4 4 3.7 6 1.0 5 3.7
Neurologic events 0.4268 0.4345
 No 7241 99.9 2894 100.0 76 100.0 1839 99.9 129 100.0 108 100.0 618 100.0 135 100.0
 Altered mental status 3 0.0 1 0.0 0 0.0 1 0.1 0 0.0 0 0.0 0 0.0 0 0.0
 Convulsions 1 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0
Major discharge diagnoses <0.0001 <0.0001
 Influenza 241 3.3 2272 78.5 40 52.6 1401 76.1 97 75.2 39 36.1 584 94.5 113 83.7
 Pneumonia 2427 33.5 238 8.2 31 40.8 145 7.9 12 9.3 29 26.9 13 2.1 12 8.9
 Other respiratory disease 2683 37.0 177 6.1 1 1.3 132 7.2 8 6.2 15 13.9 17 2.8 6 4.4
 Cardiovascular 267 3.7 34 1.2 1 1.3 31 1.7 1 0.8 1 0.9 0 0.0 1 0.7
 Other 1627 22.5 174 6.0 3 3.9 131 7.1 11 8.5 24 22.2 4 0.6 3 2.2
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Probabilities of most common severe outcomes by strain by age and influenza strains are displayed in Fig. 8. This probability had an upward trend up to 80 years old after a shock. The probability point estimates of having any cardiovascular complication increased greatly from 90 years old for those who had influenza. Similar trends were found for each individual strain for these discharge diagnoses.

Fig. 8.

Fig. 8

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Predicted probability of severe outcome by strain

Vaccination coverage was 9% or higher for targeted groups only in 4 sites (Fig. 9), and only 6 sites had at least 20 patients vaccinated among the patients targeted for vaccination. The IVE analysis was restricted to the sites with the highest vaccination coverage in targeted groups for vaccination having at least 20 patients vaccinated in these groups. These sites were Valencia, Canada, St. Petersburg, Mexico, Moscow and Turkey.

Fig. 9.

Fig. 9

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Vaccination coverage in targeted groups by site

The IVE analysis, therefore, will be carried out in these six sites and globally. Vaccination coverage in pregnant women was 0% in Kazakhstan among the included patients, and in Moscow, only 1.3% (10 out of 800) of the admitted pregnant women received the vaccine at least 15 days before symptoms onset, therefore, adjusted IVE could not be estimated for pregnant women.

Vaccination coverage was higher in patients older than 65 years and in patients with two or more comorbidities. Among immunized women 15 to 45 years old, 19 of 47 were pregnant (40.4%), and among all vaccinated patients, 26.7% were obese.

Of the subjects vaccinated, 78.0% were also vaccinated in season 2015–2016 and 67.2% were vaccinated in season 2014–2015. However, 8.0% of the unvaccinated patients in the current season were vaccinated in the season 2015–2016, and 6.6% in the season 2014–2015 (Table 6).

Table 6.

Characteristics of patients included in the primary analysis by vaccination status

Risk variables Unvaccinated Vaccinated P value
Category n % n %
Number of patients, n (%) Controls 6307 70.7 938 77.1 < 0.0001
Cases 2616 29.3 279 22.9
Age (y) Median (range) 11.4 (0–105.3) 76.5 (0.6–102.8) < 0.0001
Age group, n (%) (2) 0–5 months 1254 14.3% 0 0.0% < 0.0001
6–11 months 643 7.3% 13 1.1%
1–4 yrs 1948 22.2% 51 4.3%
5–17 yrs 760 8.7% 67 5.6%
18–49 yrs 1988 22.7% 112 9.4%
50–64 yrs 628 7.2% 106 8.9%
65–74 yrs 583 6.6% 210 17.6%
75–84 yrs 566 6.5% 337 28.2%
≥85 y 403 4.6% 299 25.0%
Sex, n (%) Male 4462 50.0% 643 52.8% 0.0641
Female 4461 50.0% 574 47.2%
Comorbidities, n (%) None 6123 68.6% 303 24.9% < 0.0001
1 1457 16.3% 355 29.2%
> 1 1343 15.1% 559 45.9%
Pregnant, n (%) – 921 69.5% 19 40.4% < 0.0001
Obesity, n (%) – 1148 13.8% 309 26.7% < 0.0001
Previous hospitalisation within 12 months, n (%) – 1914 24.1% 406 37.7% < 0.0001
GP visit within 3 months, n (%) None 3074 38.8% 209 19.4% < 0.0001
1 1740 21.9% 188 17.4%
> 1 3116 39.3% 681 63.2%
Smoking, n (%) Current 2112 24.1% 158 13.0% < 0.0001
Past 1618 18.5% 388 32.0%
Never 5037 57.5% 667 55.0%
Functional impairment in ≥65 y, n (%) None or minimal 72 5.4% 58 7.0% 0.4086
Mild 32 2.4% 18 2.2%
Moderate 52 3.9% 41 4.9%
Severe 309 23.1% 191 23.0%
Total 871 65.2% 523 62.9%
Sampling interval (days) Median (range) 3 (0–9) 4 (0–9) < 0.0001
Sampling interval, n (%) ≤4 days 6377 72.1% 781 64.2% < 0.0001
5–7 days 2148 24.3% 357 29.3%
8–9 days 315 3.6% 79 6.5%
Site, n (%) St. Pet 1851 20.7% 86 7.1% < 0.0001
Moscow 1555 17.4% 65 5.3%
Kazakhstan 159 1.8% 0 0.0%
Czech Republic 105 1.2% 6 0.5%
Canada 993 11.1% 139 11.4%
Romania 380 4.3% 7 0.6%
Turkey 392 4.4% 21 1.7%
Valencia 1300 14.6% 825 67.8%
Tunisia 37 0.4% 2 0.2%
Suzhou/Shanghai 469 5.3% 1 0.1%
India 482 5.4% 11 0.9%
Mexico 301 3.4% 49 4.0%
South Africa 899 10.1% 5 0.4%
Vaccinated, n (%) In 2015–2016 718 8.0% 949 78.0% < 0.0001
In 2014–2015 589 6.6% 818 67.2% < 0.0001
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IVE estimates for included patients

In the selected sites for IVE estimates, vaccination coverage was 11.7% among the influenza positives and 22.2% among the influenza negatives. The overall IVE was 27.24% (95% CI 15.62 to 37.27%) in targeted groups for vaccination. Table 7 shows IVE for different strains, Fig. 10 by study country.

Table 7.

IVE for all cases and for targeted groups only by age and strain

Influenza-positive Influenza-negative Adjusted IVE(*)
Population Strain Age Total Vaccinated Total Vaccinated Percent
(95% CI)		 P-value
Overall Any Any 2895 279 7245 938 27 (15, 38)
<65 y 2013 84 5558 265 27 (−1, 48) 0.804
≥65 y 882 195 1687 673 25 (3, 43)
A (H1N1) pdm09 Any 76 7 7245 938 39 (−68, 78)
<65 y 66 6 5558 265 2 (−138, 60) 0.346
≥65 y 10 1 1687 673 99 (1, 100)
A (H3N2) Any 1840 221 7245 938 25 (13, 35)
<65 y 1124 46 5558 265 31 (1, 51) 0.703
≥65 y 716 175 1687 673 19 (−10, 40)
B/Yamagata Any 108 9 7245 938 41 (−110, 84)
<65 y 73 3 5558 265 7 (−178, 69) 0.203
≥65 y 35 6 1687 673 73 (−38, 95)
B/Victoria Any 618 25 7245 938 43 (−15, 71)
<65 y 596 24 5558 265 27 (−14, 54) 0.191
≥65 y 22 1 1687 673 89 (40, 98)
Targeted groups only Any Any 2314 256 4723 869 27 (16, 37)
<65 y 1432 61 3036 196 37 (0, 47) 0.657
≥65 y 882 195 1687 673 25 (3, 43)
A (H1N1) pdm09 Any 54 7 4723 869 18 (−142, 72)
<65 y 44 6 3036 196 −62 (−303, 35) 0.423
≥65 y 10 1 1687 673 99 (1, 100)
A (H3N2) Any 1572 214 4723 869 23 (9, 34)
<65 y 856 39 3036 196 27 (−7, 50) 0.485
≥65 y 716 175 1687 673 19 (−10, 40)
B/Yamagata Any 63 7 4723 869 72 (8, 92)
<65 y 28 1 3036 196 65 (−35, 91) 0.037
≥65 y 35 6 1687 673 73 (−38, 95)
B/Victoria Any 449 14 4723 869 66 (3, 80)
<65 y 427 13 3036 196 41 (10, 62) 0.262
≥65 y 22 1 1687 673 89 (40, 98)
Open in a new tab

(*) .IVE was obtained in each case using the same model (described in the ‘Methods’ section) but restricting it by strain, age or targeted groups.. P-value obtained comparing patients <65 y and ≥ 65 y

Fig. 10.

Fig. 10

Open in a new tab

Adjusted Influenza Vaccine Effectiveness by site

IVE was statistically significant for all strains except for A(H1N1)pdm09 due to the limited sample size, and the point estimate was higher for both influenza B lineages, even using the trivalent vaccine (Fig. 11). Heterogeneity among influenza types/subtypes was relevant (I2 = 57.4%).

Fig. 11.

Fig. 11

Open in a new tab

Adjusted Influenza Vaccine Effectiveness by strain

This season IVE estimate was higher in patients 85 years old or older (51.17% [95% CI: 35.13 to 63.24]). IVE was also high and statistically significant for patients 2 to 4 years old (49.37% [95% CI: 21.60 to 67.30]) (Fig. 12). Heterogeneity among the different age groups was relevant (I2 = 69%).

Fig. 12.

Fig. 12

Open in a new tab

Adjusted Influenza Vaccine Effectiveness by age group

Discussion

The GIHSN included sites from the two hemispheres in the 2016/17 season. However, Ivory Coast and Peru were not included in the epidemiology study or in the IVE study due to the low influenza cases detected. This season was characterized by a predominance in the circulation of A(H3N2) virus, and a second wave of B/Victoria. However, A(H1N1)pdm09 was predominant in Mexico. B/Yamagata-strain, which was not included in the vaccine, also circulated in some areas.

Influenza A(H1N1)pdm09 was mainly found in Mexico. A low vaccination coverage was seen in most of the GIHSN sites.

The GIHSN represents an opportunity to analyse the epidemiology of hospitalized influenza cases, and an assessment of the vaccine effectiveness worldwide. However, there are some limitations that should be mentioned:

  • Although the same protocol was developed, the adaptation to different countries or sites produced some heterogeneity in the results, as previously reported in the network [3].

  • In general vaccination coverage was low in most sites, even among high risk groups.

  • Other factors as number of cases per site, and variability in the vaccination coverage, increased the heterogeneity in the reporting and analysis.

All of these limitations contributed to the complexity of the interpretation of the results.

In the northern hemisphere, the season differed by latitude [14], and this may have implications in the calendar of the vaccination campaigns.

Patients tested for influenza 8 to 9 days after symptoms onset had a higher proportion of samples negative for influenza than patients tested within the first 7 days after symptoms onset, as that viral load decreases with increasing time since infection, [15]. However, there were a few cases in our study as we collected all cases whose admission was in the 7 days after ILI symptoms started, and any delay in approaching the patient could result in a late swabbing.

Among inpatients with COPD, there was not a higher risk of testing for influenza. As all the cases were hospitalized, this result cannot be interpreted as COPD not being a risk factor for influenza hospitalization, as any other respiratory infection may decompensate the respiratory condition and force an admission. Besides vaccination coverage is higher in subjects with chronic conditions [16] and therefore, protection from the vaccine may also impact on our finding.

The risk of testing positive for influenza in diabetic patients was slightly higher than non-diabetic patients, as it also happened in previous seasons [3, 4]. Pregnancy also increased the probability of having influenza in women, particularly if they had at least one comorbidity in the first trimester.

Despite differences in the characteristics of the included patients relative to the age or pregnancy status, heterogeneity in the IVE analysis among the 6 sites with the highest numbers of vaccinated patients was low. Point estimates of the overall IVE from a two-step pooling was 27.2% (95% CI: 15.62 to 37.27) in hospitalized, which is higher than that reported in Europe for hospitalised patients [17], that ranged from 2.4 to 7.9%, depending on the age group, and lower to that estimated by the US CDC, which was 40% (95% CI: 32 to 46) [18].

Pooled Influenza vaccine effectiveness showed protection against all influenza virus that circulated, although for A(H1N1)pdm09 did not reach statistical significance, as the circulation of the virus was low except in Mexico. There was a significant effectiveness against both B lineages, even though most of the vaccines used were trivalent, i.e. only contained the B/Victoria linage, following recommendations of the World Health Organisation (WHO) for trivalent vaccines in the Northern Hemisphere [19]. Although antigenically different, there has been shown some degree of cross-protection among both B lineages.

Conclusion

The GIHSN provides an opportunity to analyse influenza epidemiology and vaccine effectiveness worldwide. In the 2016/17 season, A(H3N2) was the predominant influenza strain this season (first wave), followed by B/Victoria (second wave). Influenza A(H1N1)pdm09 was mainly found in Mexico. A low vaccination coverage was seen in most of the GIHSN sites.

Differences in the distribution of influenza cases among the age groups were mainly due to the characteristics of the participating hospitals. Pregnant women had higher risk of testing positive for influenza, as occurred with diabetics, however this difference was not seen in COPD subjects.

Overall IVE was low to moderate 27.24 (95% CI 15.62 to 37.27) in this season. A moderate to high effectiveness was seen for both influenza B lineages, and a non-significant low effectiveness for Influenza A(H1N1)pdm09.

Additional file

Additional file 1: (178.8KB, docx)

Complementary Table S1. (DOCX 142 kb)

Acknowledgements

The authors would like to acknowledge the Foundation for Influenza Epidemiology for the financial support and all members of the GIHSN, which are listed below (sites are firstly ordered by contribution to this manuscript and secondly by alphabetical order):

Valencia: B Escribano-López, S García Esteban, B Guglieri-López, M Martín-Navarro, A Mira-Iglesias and M J Sánchez-Catalán from FISABIO-Salud Pública, Valencia, Spain, and X López-Labrador from FISABIO-Salud Pública, Valencia, Spain and the Consorcio de Investigación Biomédica de Epidemiología y Salud Pública, Spain, Instituto Carlos III, Madrid, Spain; E Adriana-Magos and M Carballido-Fernández from the Hospital General de Castellón, Castellón, Spain; J Mollar Maseres and M Roldán-Aguado from the Hospital Universitario y Politécnico La Fe, Valencia, Spain; J Fernández-Dopazo and M Tortajada-Girbés from the Hospital Doctor Peset, Valencia, Spain, and P Llorente-Nieto and G Schwarz-Chavarri from the Hospital General de Alicante, Alicante, Spain.

Moscow: E Garina, L Kisteneva, L Kolobukhina, K Krasnoslobotsev, I Kruzhkova, L Merkulova and E Mukasheva from the D.I. Ivanovsky Institute of Virology FSBI “N.F. Gamaleya FRCEM” Ministry of Health, Moscow, Russian Federation.

Canada: A Ambrose, M Andrew, M ElSherif, D MacKinnon-Cameron, M Nichols-Evans and P Ye from the Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Halifax, Canada.

St. Petersburg: O Afanasieva, A Afanasieva, S Demina, E Dondurei, M Eropkin, A Fadeev, L Generalova, A Go, E Golovacheva, V Gonchar, A Komissarov, N Konovalova, S Kuvarzina, T Levanyuk, T Lobova, L Osidak, M Pisareva, E Rozhkova, K Sintsova, Z Sirotkina, E Smorodintseva, K Stolyarov, V Sukhovetskaya, M Tamila, L Voloshuk, M Yanina and P Zarishnyuk from the Research Institute of Influenza, St. Petersburg, Russian Federation.

South Africa: S. A. Madhi from the Medical Research Council, Respiratory and Meningeal Pathogens Research Unit, University of the Witwatersrand, Johannesburg, South Africa.

Romania: V Aramă, D.Florea, M Luminos, D Otelea, O Sandulescu and O Vlaicu, from the National Institute of Infectious Diseases “Prof. Dr.MateiBals”, Bucharest (INBIMB), Romania, and D Pitigoi from the National Institute of Infectious Diseases “Prof. Dr.MateiBals”, Bucharest (INBIMB) and the University of Medicine and Pharmacy “Carol Davila” Bucharest, Romania.

Turkey: K Aykac, T Bagcı Bosi, E Bilgin, M Durusu, A Kara, L Ozisik and S Tanir Basaranoglu from the Hacettepe University Faculty of Medicine, Ankara, Turkey; T Bedir Demirdag, O Guzel Tunccan, O Ozgen and H Tezer from the Gazi University Faculty of Medicine, Ankara, Turkey; B Gulhan and A Ozkaya-Parlakay from the Ankara Hematology Oncology Children’s Training and Research Hospital, Ankara, Turkey; M Ozsoy and N Tulek from the Ankara Research and Training Hospital, Ankara, Turkey, and M Akcay Ciblak, from Sanofi Pasteur, Turkey.

Mexico: A Galindo Fraga, M L Guerrero Almeida and G M Ruiz-Palacios from the National Institute of Medical Sciences and Nutrition Salvador Zubirán (INCMNSZ), Mexico; A de Colsa Ranero and W Dolores Domínguez-Viveros from the Instituto Nacional de Pediatría, Mexico; I Jiménez-Escobar, J P Ramírez-Hinojosa and R P Vidal-Vázquez from the Hospital General Dr. Manuel Gea González, Mexico; D de la Rosa-Zamboni, A E Gamiño-Arroyo and S Moreno-Espinosa from the Hospital Infantil de México, Mexico, and A Hernández from the Instituto Nacional de Enfermedades Infecciosas Ismael Cosio Villegas, Mexico.

India: S Ali, M Khan, H Mir, Soumya and R Yusuf from the Sher-i-Kashmir Institute of Medical Sciences (SKIMS), India, and N Bali from the Department of Clinical Microbiology, Government Medical College, Srinagar, India.

Czech Republic: M Havlickova, H Jirincova, R Kralova, Z Mandakova, J Prochazkova, H Sebestova from the National Institute of Public Health, Prague, Czech Republic, and D Dvorska, K Herrmanova, H Rohacova, T Rudova and I Standerova from the Hospital Na Bulovce, Prague, Czech Republic

Suzhou/Shanghai: K Chen, W Shan, F Zhang, G Zhao from the Fudan University, Shanghai, China; Y Yan from the Soochow University Affiliated Children Hospital, Suzhou, China; J Zheng from the Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China, and J Pan from the State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Diseases, National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.

Kazakhstan: N Gaukhar from the Center for Sanitary-Epidemiological Expertise and Monitoring, Almaty, Kazakhstan.

Tunisia: S Amine from the Hôpital Charles-Nicolle, Tunis, Tunisia; J Ben Khelil from the Medical Intensive Care Unit, Abderrahmen Mami Hospital, Ariana, Tunisia; M Ben Jeema and M Koubâa from the Hedi Chaker Hospital, Sfax, Tunisia; K Menif from the Children’s Hospital of Tunis, Tunis, Tunisia; A Boukthir, S Chlif, M K Dellagi, A Gharbi, H Louzir, R Yazidi and W Zid from the Pasteur Institute of Tunis, Tunisia.

Peru: A Laguna, from the Instituto de Medicina Tropical Daniel Alcides Carrión, UNMSM, Lima, Peru; J Pérez-Bao, from the United States Naval Medical Research Center Detachment, Iquitos and Lima, Peru, and N Reyes from the Universidad Nacional Mayor de San Marcos, Lima, Peru.

Ivory Coast: D Coulibaly, from the Pasteur Institute of Côte d’Ivoire, Abidjan, Côte d’Ivoire.

Funding

The study was funded by FISABIO-Public Health and the participating institutions of the manuscript (listed in the affiliations in the author list), and Sanofi Pasteur, who had no role in the analysis or discussion of the results. All participating institutions contributed to the data collection of the corresponding site, as well as the datasets transfer to FISABIO and the interpretation of GIHSN results. FISABIO-Public Health contributed to the design of the study, the recruitment and data collection of patients from Valencia Region and all participant sites, and the data analysis and interpretation of GIHSN results.

Availability of data and materials

Datasets were collected by each participating site and gathered on a pooled database by FISABIO. An authorisation is needed to any participating site in order to require sites databases. Data cannot be publicly shared due to confidentiality reasons, as some confidential patient data should not be shared, and in order to accomplish privacy laws from the participating sites. The corresponding author must be contacted with in order to ask for information about databases.

Abbreviations

AOR

Adjusted odds ratio

CI

Confidence interval

GIHSN

Global Influenza Hospital Surveillance Network

IVE

Influenza vaccine effectiveness

OR

Odds ratio

RT-PCR

Reverse transcription-polymerase chain reaction

Authors’ contributions

VBM wrote the manuscript and performed the statistical analysis. VBM, ST, SM, AS, MN, AD, SU, PK, JK, TZ, AK, ABS, EB, JDD, JPB (all authors) participated in the data collection, preparation and revision of the manuscript and approval of the final version and agreed with the common core protocol and the standard operating procedures of the GIHSN in order to keep the accuracy of the data.

Ethics approval and consent to participate

This study has been approved by the Ethics Committees of the participating sites, who have approved their participation in the GIHSN network. Each adult patient tested for influenza had signed an informed consent in order to be included in the study. In case the patient did not reach the legal age or is impaired, parents or legal guardians signed the informed consent. The Ethics Committees of the participating sites are listed below:

  • St. Petersburg: Local Ethical Committee under the FGBU “Research Institute of Influenza” of the Ministry of Health of the Russian Federation

  • Moscow: The local Ethic Committee of Hospital #1 for Infectious Diseases of Moscow Health Department

  • Kazakhstan: The study was carried in Almaty, Kazakhstan as part of the implementation of the national Severe Acute Respiratory Infections (SARI) surveillance program in Kazakhstan for purposes of communicable disease control. Ethical approval was not required but informed consent was obtained before inclusion. Informed consent provided in accordance with the Constitution of the Republic of Kazakhstan (section II article 29)

  • Czech Republic: Ethics Committee of the Hospital Na Bulovce

  • Canada: The Nova Scotia Health Authority Research Ethics Board and the IWK Research Ethics Board (IWK: Isaak Walton Killam)

  • Romania: Bioethics Committee of the National Institute for Infectious Diseases “Prof. Dr. Matei Bals” Bucharest, Romania

  • Turkey: Hacettepe University Non-interventional Clinical Research Ethics Board

  • Valencia: Comité Ético de Investigación Clínica Dirección General de Salud Pública-Centro Superior de Investigación en Salud Pública (CEIC-DGSP-CSISP)

  • Tunisia: The ethics committee of Abderrahmane Mami hospital, Ariana, Tunisia

  • Suzhou/Shanghai: Fudan University School of Public Health Institutional Review Board

  • India: Institutional Ethics Committee of the Sher-i-Kashmir Institute of Medical Sciences, Srinagar

  • Mexico: Research Ethics Committee of the National Institute of Medical Science and Nutrition Salvador Zubiran & Research Committee of the National Institute of Medical Science and Nutrition Salvador Zubiran

  • South Africa: The Human Research Ethics Committee of the University of the Witwatersrand

All of these Ethics Committees approved the participation of the site in the study and the data transfer to FISABIO, who led the implementation and data collection in the 2016–2017 season.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Víctor Baselga-Moreno, Email: basvic28@gmail.com.

Svetlana Trushakova, Email: s.trushakova@gmail.com.

Shelly McNeil, Email: Shelly.McNeil@nshealth.ca.

Anna Sominina, Email: anna.sominina@influenza.spb.ru.

Marta C. Nunes, Email: nunesm@rmpru.co.za

Anca Draganescu, Email: drdraganescu@yahoo.com.

Serhat Unal, Email: sunal@hacettepe.edu.tr.

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Tao Zhang, Email: tzhang@shmu.edu.cn.

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Afif Ben-Salah, Email: afif.bensalah@pasteur.rns.tn.

Elena Burtseva, Email: elena_burceva@mail.ru.

Joan Puig-Barberà, Email: jpuigb55@gmail.com.

Javier Díez-Domingo, Email: jdiezdomingo@gmail.com.

for the Global Influenza Hospital Surveillance Network (GIHSN):

B. Escribano-López, S. García Esteban, B. Guglieri-López, M. Martín-Navarro, A. Mira-Iglesias, M. J. Sánchez-Catalán, X. López-Labrador, E. Adriana-Magos, M. Carballido-Fernández, J. Mollar Maseres, M. Roldán-Aguado, J. Fernández-Dopazo, M. Tortajada-Girbés, P. Llorente-Nieto, G. Schwarz-Chavarri, E. Garina, L. Kisteneva, L. Kolobukhina, K. Krasnoslobotsev, I. Kruzhkova, L. Merkulova, E. Mukasheva, A. Ambrose, M. Andrew, M. ElSherif, D. MacKinnon-Cameron, M. Nichols-Evans, P. Ye, O. Afanasieva, A. Afanasieva, S. Demina, E. Dondurei, M. Eropkin, A. Fadeev, L. Generalova, A. Go, E. Golovacheva, V. Gonchar, A. Komissarov, N. Konovalova, S. Kuvarzina, T. Levanyuk, T. Lobova, L. Osidak, M. Pisareva, E. Rozhkova, K. Sintsova, Z. Sirotkina, E. Smorodintseva, K. Stolyarov, V. Sukhovetskaya, M. Tamila, L. Voloshuk, M. Yanina, P. Zarishnyuk, S. A. Madhi, V. Aramă, D. Florea, M. Luminos, D. Otelea, O. Sandulescu, O. Vlaicu, D. Pitigoi, K. Aykac, T. Bagcı Bosi, E. Bilgin, M. Durusu, A. Kara, L. Ozisik, S. Tanir Basaranoglu, T. Bedir Demirdag, O. Guzel Tunccan, O. Ozgen, H. Tezer, B. Gulhan, A. Ozkaya-Parlakay, M. Ozsoy, N. Tulek, M. Akcay Ciblak, A. Galindo Fraga, M. L. Guerrero Almeida, G. M. Ruiz-Palacios, A. de Colsa Ranero, W. Dolores Domínguez-Viveros, I. Jiménez-Escobar, J. P. Ramírez-Hinojosa, R. P. Vidal-Vázquez, D. de la Rosa-Zamboni, A. E. Gamiño-Arroyo, S. Moreno-Espinosa, A. Hernández, S. Ali, M. Khan, H. Mir Soumya, R. Yusuf, N. Bali, M. Havlickova, H. Jirincova, R. Kralova, Z. Mandakova, J. Prochazkova, H. Sebestova, D. Dvorska, K. Herrmanova, H. Rohacova, T. Rudova, I. Standerova, K. Chen, W. Shan, F. Zhang, G. Zhao, Y. Yan, J. Zheng, J. Pan, N. Gaukhar, S. Amine, J. Ben Khelil, M. Ben Jeema, M. Koubâa, K. Menif, A. Boukthir, S. Chlif, M. K. Dellagi, A. Gharbi, H. Louzir, R. Yazidi, W. Zid, A. Laguna, J. Pérez-Bao, N. Reyes, and D. Coulibaly

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Additional file 1: (178.8KB, docx)

Complementary Table S1. (DOCX 142 kb)

Data Availability Statement

Datasets were collected by each participating site and gathered on a pooled database by FISABIO. An authorisation is needed to any participating site in order to require sites databases. Data cannot be publicly shared due to confidentiality reasons, as some confidential patient data should not be shared, and in order to accomplish privacy laws from the participating sites. The corresponding author must be contacted with in order to ask for information about databases.

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