Skip to content

Advertisement

  • Research article
  • Open Access
  • Open Peer Review

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

  • 1,
  • 2,
  • 3,
  • 4,
  • 5, 6,
  • 7,
  • 8,
  • 9,
  • 10,
  • 11,
  • 12,
  • 13, 14,
  • 2,
  • 1,
  • 1Email author and
BMC Public Health201919:487

https://doi.org/10.1186/s12889-019-6713-5

  • Received: 7 September 2018
  • Accepted: 27 March 2019
  • Published:
Open Peer Review reports

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.

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 [36], 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

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

Fig. 2
Fig. 2

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

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

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

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

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

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

(*)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

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

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

 
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

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

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

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)

 

(*) .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

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

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

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.

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

Declarations

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.

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.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunidad Valenciana (FISABIO), 21 Cataluña Av, 46020 Valencia, Spain
(2)
Ivanovsky Institute of Virology FSBI “N.F. Gamaleya FRCEM” Ministry of Health, Moscow, Russian Federation
(3)
Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Halifax, Canada
(4)
Research Institute of Influenza, WHO National Influenza Centre of Russia, St. Petersburg, Russian Federation
(5)
Medical Research Council, Respiratory and Meningeal Pathogens Research Unit, University of the Witwatersrand, Johannesburg, South Africa
(6)
Department of Science and Technology/National Research Foundation, Vaccine Preventable Diseases, University of the Witwatersrand, Johannesburg, South Africa
(7)
National Institute of Infectious Diseases “Prof. Dr. Matei Bals”, Bucharest (INBI “Prof. Dr. Matei Bals”), București, Romania
(8)
Turkish Society of Internal Medicine, Ankara, Turkey
(9)
Department of Internal and Pulmonary Medicine, Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Soura, India
(10)
National Institute of Public Health, Prague, Czech Republic
(11)
Fudan University, Shanghai, China
(12)
Center for Sanitary-Epidemiological Expertise and Monitoring, Almaty, Kazakhstan
(13)
Pasteur Institute of Tunis, Tunis, Tunisia
(14)
College of Medicine and Medical Sciences, Manama, Bahrain

References

  1. Ortiz JR, Neuzil KM, Shay DK, Rue TC, Neradilek MB, Zhou H, et al. The burden of influenza-associated critical illness hospitalizations. Crit Care Med. 2014;42:2325–32.View ArticleGoogle Scholar
  2. Ortiz JR, Neuzil KM, Rue TC, Zhou H, Shay DK, Cheng PY, et al. Population based incidence estimates of influenza-associated respiratory failure hospitalizations, 2003 to 2009. Am J Respir Crit Care Med. 2013;188:710–5.View ArticleGoogle Scholar
  3. Puig-Barbera J, Burtseva E, Yu H, Cowling BJ, Badur S, Kyncl J, et al. Influenza epidemiology and influenza vaccine effectiveness during the 2014-2015 season: annual report from the global influenza hospital surveillance network. BMC Public Health. 2016;16(Suppl 1):757. https://doi.org/10.1186/s12889-016-3378-1.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Puig-Barberà J, Natividad-Sancho A, Trushakova S, Sominina A, Pisareva M, Ciblak MA, et al. Epidemiology of hospital admissions with influenza during the 2013/2014 northern hemisphere influenza season: results from the global influenza hospital surveillance network. PLoS One. 2016;11(5):e0154970. https://doi.org/10.1371/journal.pone.0154970.View ArticlePubMedPubMed CentralGoogle Scholar
  5. Puig-Barberà J, Natividad-Sancho A, Launay O, Burtseva E, Ciblak MA, Tormos A, et al. 2012-2013 seasonal influenza vaccine effectiveness against influenza hospitalizations: results from the global influenza hospital surveillance network. PLoS One. 2014;9(6):e100497 https://doi.org/10.1371/journal.pone.0100497.View ArticleGoogle Scholar
  6. Puig-Barberà, et al. First-year results of the global influenza hospital surveillance network: 2012 – 2013 northern hemisphere influenza season. BMC Public Health. 2014;14:564.View ArticleGoogle Scholar
  7. Commission of the European Union. Official Journal of the European Union 27.9.2012. Influenza virus – Clinical criteria. L 262/16 (2012).Google Scholar
  8. Sullivan SG, Tay EL, Kelly H. Variable definitions of the influenza season and their impact on vaccine effectiveness estimates. Vaccine. 2013;31:4280–3.View ArticleGoogle Scholar
  9. Puig-Barberà, et al. The global influenza hospital surveillance network (GIHSN): a new platform to describe the epidemiology of severe influenza. Influenza Other Respir Viruses. 2015;9(6):277–86.View ArticleGoogle Scholar
  10. Foppa IM, Haber M, Ferdinands JM, Shay DK. The case test-negative design for studies of the effectiveness of influenza vaccine. Vaccine. 2013;31:3104–9.View ArticleGoogle Scholar
  11. Kirkwood BR, Sterne JAC. Analysis of clustered data. In: Essential medical statistics. Malden: Blackwell Science; 2003. p. 355–70.Google Scholar
  12. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539–58.View ArticleGoogle Scholar
  13. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–60.View ArticleGoogle Scholar
  14. Caini Saverio, Alonso Wladimir J, Séblain Clotilde El-Guerche, Schellevis François, Paget John. The spatiotemporal characteristics of influenza a and B in the WHO European region: can one define influenza transmission zones in Europe?. Euro Surveill. 2017;22(35). https://doi.org/10.2807/1560-7917.ES.2017.22.35.30606
  15. Carrat F, Vergu E, Ferguson NM, Lemaitre M, Cauchemez S, Leach S, Valleron A-J. Time Lines of Infection and Disease in Human Influenza: A Review of Volunteer Challenge Studies. American journal of epidemiology. 2008;167(Issue 7):775–85 https://doi.org/10.1093/aje/kwm375.View ArticleGoogle Scholar
  16. Dirección General de Salud Pública. Prevención y vigilancia de la gripe en la Comunitat Valenciana. Temporada 2016–2017. Available at: http://publicaciones.san.gva.es/publicaciones/documentos/IS-150.pdf, last access 28 Nov 2018.
  17. Esther K, Marc R, I-MOVE/I-MOVE+ study team. Early 2016/17 vaccine effectiveness estimates against influenza a(H3N2): I-MOVE multicentre case control studies at primary care and hospital levels in Europe. Euro Surveill. 2017;22(7) https://doi.org/10.2807/1560-7917.ES.2017.22.7.30464.
  18. Centers for Disease Control and Prevention (CDC) (CDC). Estimated Influenza Illnesses, Medical visits, and Hospitalizations Averted by Vaccination in the United States. Available at: https://www.cdc.gov/flu/about/disease/2016-17.htm, last access 6 Dec 2018.
  19. World Health Organisation (WHO). Recommended composition of influenza virus vaccines for use in the 2016–2017 northern hemisphere influenza season. Available at: https://www.who.int/influenza/vaccines/virus/recommendations/201602_recommendation.pdf?ua=1, last access 6 Dec 2018.

Copyright

© The Author(s). 2019

Advertisement