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. 2024 Jan 9;17:100435. doi: 10.1016/j.jvacx.2024.100435

Characteristics and determinants of seasonal influenza vaccination in Manitoba, Canada: A population-wide record-linkage study

George N Okoli a,b,c,⁎, Christiaan H Righolt b, Geng Zhang a,b, Silvia Alessi-Severini a, Paul Van Caeseele d,e, I fan Kuo a,f, Salaheddin M Mahmud a,b
PMCID: PMC10825609  PMID: 38299203

Abstract

Background

Seasonal influenza vaccine (SIV) uptake (receipt of vaccine) in Manitoba, Canada is consistently low notwithstanding vaccine availability and free-of-charge vaccination. Despite, there is a lack of published evidence on the determinants of uptake of the vaccine. We sought to assess the association between SIV uptake and certain population and primary care physician (PCP) characteristics in Manitoba.

Methods

We conducted a longitudinal study utilizing Manitoba administrative health databases. We summarized SIV uptake from 2000/01–2019/20 influenza seasons across subpopulations defined by socioeconomic, health-related and PCP characteristics. Utilizing multivariable generalized estimating equation logistic regression models, we assessed the association between SIV uptake and the socioeconomic, health-related and PCP characteristics, stratified by age group (<5-, 5–17-, 18–44-, 45–64-, ≥65-year-olds) and sex. Results are adjusted odds ratios with associated 95 % confidence intervals.

Results

SIV uptake percentage increased over time with 4.4 %, 13.1 %, 17.5 % and 21.7 % of < 5-year-olds, 2 %, 4.9 %, 9.7 % and 13.1 % of 5–17-year-olds, 5.4 %, 8.8 %, 10.7 % and 13.5 % of 18–44-year-olds, 16.8 %, 21.3 %, 23.6 % and 24.6 % of 45–64-year-olds receiving the SIV in 2000–2004, 2005–2009, 2010–2014 and 2015–2019, respectively. There was a decline among ≥ 65-year-olds from 58.5 % to 53.5 %. We observed a similar pattern across subpopulations. There were significantly increased odds of SIV uptake among females within the age groups ≥ 18 years, in higher income quintiles, mostly with increased contact with a PCP/hospitalization within age groups ≥ 18 years, among those who had older or female PCPs (the opposite observation among ≥ 65-year-olds) and whose PCP administered at least one SIV in prior influenza season. These observations were largely consistent irrespective of sex.

Conclusion

SIV uptake in Manitoba appears to increase with age, and many socioeconomic, health-related and PCP characteristics appear to be associated with it. These findings may inform targeted vaccination programs to optimize influenza vaccination in Manitoba and similar Canadian jurisdictions.

Keywords: Seasonal influenza, Vaccine uptake, Characteristics, Determinants, Canada

Introduction

Seasonal influenza (commonly referred to as the flu) is an acute respiratory infection caused by influenza viruses. Infections are mostly asymptomatic or mildly symptomatic and infected persons usually recover within a few days without needing medical attention. [1] However, some infections could be severe and may require hospitalization and occasionally leading to death especially among high-risk persons such as infants, older adults (≥65 year-olds), pregnant women, and persons with certain chronic medical conditions, [2], [3] thus, making seasonal influenza a disease of global public health concern. [3], [4] Even so, influenza is ranked among the top ten leading causes of death in Canada. [5].

While there are antiviral drugs for prophylaxis and treatment of influenza, [6], [7] vaccination remains an effective and practical prevention strategy against influenza. [8] However, due to genetic changes that occur in the influenza viruses over time (antigenic drift), influenza vaccine is reformulated every year for a better protection against circulating seasonal virus strains. [9] Despite availability of seasonal influenza vaccine (SIV) and free-of-charge influenza vaccination, SIV uptake (receipt of vaccine) in Manitoba, Canada remains far lower than the Canadian government target. [10] Notwithstanding, there is a lack of published literature on the individual socioeconomic, health-related and primary care provider characteristics that may be associated with uptake of the vaccine.

Refusing or delaying receipt of a vaccine despite the vaccine and vaccinating services availability has been labelled ‘vaccine hesitancy’. [11] Health belief factors such as perceived seriousness and susceptibility to a disease, and accessibility, trust and confidence in vaccine have been associated with acceptance and uptake of a vaccine. [12], [13] Studies have established various determinants of SIV uptake, including knowledge, perceptions and attitudes towards the vaccination. [14], [15] Further, some socioeconomic and health-related characteristics of individuals, [16], [17], [18] and characteristics of primary care providers and health systems have also been suggested to influence SIV uptake. [19], [20].

Determinants of SIV uptake in Canada have typically been assessed using cross-sectional questionnaire-based surveys involving small numbers of people who may not be well representative of the populations. [21], [22], [23], [24] Moreover, these surveys are prone to recall and social desirability reporting biases. [25], [26] Further, many published retrospective analysis of influenza vaccination records in Canada tend to utilize records from one or two influenza seasons to assess determinants of the vaccine uptake, [27], [28], [29] thus, not taking into consideration, changes in individual characteristics that may influence vaccine uptake over time such as age, employment status, income, educational attainment, and healthcare utilization. The availability of a comprehensive population-based province-wide immunization registry and several linkable administrative health databases in Manitoba, which are less prone to the biases inherent in surveys, [30] provides the opportunity to examine several years of seasonal influenza vaccination in Manitoba. We aimed to summarize and characterize seasonal influenza vaccination in Manitoba, and to assess the associations between SIV uptake and certain individual socioeconomic, health-related and primary care physician (PCP) characteristics, taking into consideration changes in these characteristics over time.

Methods

Study design

We conducted a longitudinal study utilizing data from several linked anonymized Manitoba Health and Seniors Care (MH) administrative health databases. The study period was from September 01, 2000, to March 31, 2020. This study received the necessary approvals from the University of Manitoba Health Research Ethics Board (HS21763 (H2018:170)) and the Health Information Privacy Committee of MH (HIPC No. 2018/2019–04). Our findings are reported following the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines. [31].

Data sources

MH maintains several centralized, administrative electronic databases linkable using a unique personal health identification number (PHIN). The completeness and accuracy of these databases are well established. [32], [33] We utilized an encrypted version of the PHIN for this study and detailed information regarding the data sources is available as Supplementary Table 1.

Using the appropriate codes for SIV (excluding the 2009 pandemic influenza vaccine), we obtained seasonal influenza vaccination information from the Manitoba Immunization Monitoring System (MIMS), a comprehensive population-based electronic immunization registry for monitoring immunizations and providing immunization reminders to help ensure that Manitobans (residents of Manitoba) receive recommended immunizations. [34] Demographic information such as age, sex, and area/region of residence were obtained from the Manitoba Health Insurance Registry. [35] Information regarding dispensed prescription drugs was obtained from the Drug Program Information Network (DPIN). [36] In-hospital diagnosis and treatment were obtained from the Hospital Abstracts Database (HAD), [33] and information regarding services provided by physicians in offices and outpatient departments from the Medical Services Database (MSD). [33] Physician and practice information were obtained from the Provider Registry. [37].

Study population

The study participants were residents of Manitoba registered in the Manitoba Health Insurance Registry, [35] and at least six months old on September 01 during the study period, with an influenza season commencing on September 01 and ending on March 31 of the following year. Exit from the study was if an individual loses insurance coverage, for example, due to emigration out of Manitoba or death.

Exposures, covariates and outcomes

The exposures/covariates consisted of two classes. The first class was individual socioeconomic and health-related characteristics (sex, income quintile, region of residence, categorized number of visits to PCP/hospitalization one year prior to an influenza season, and chronic medical conditions). Income quintiles were determined based on area of residence and census data, using the Manitoba Center for Health Policy definition of income quintiles. We grouped region of residence as appropriate, under one of the Manitoba regional health authorities, with Winnipeg Regional Health Authority (WRHA), which has more heterogeneous areas or residence, divided based on census socioeconomic data, for more appropriate comparison with other regions of residence. We determined chronic medical conditions from the DPIN, HAD, and MSD using previously validated algorithms. If an individual visited more than one PCP, we considered the most visited. The second class was individual PCP characteristics (age, sex, specialty, and years of practice, remuneration option, and number of influenza vaccine administered to patients in the previous influenza season). PCPs were family physicians, internists, paediatricians, and obstetricians and gynaecologists. The outcome was SIV uptake (receipt of vaccine by an individual) between September 01 and March 31 of each influenza season.

Statistical analysis

We conducted analyses stratified by age group (<5-, 5–17-, 18–44-, 45–64-, ≥65-year-olds). For the descriptive analysis, we calculated 5-yearly (2000–2004, 2005–2009, 2010–2014 and 2015–2019) average SIV uptake percentages, and the overall (all influenza seasons) average SIV uptake percentages within age groups across the individual socioeconomic, health-related and PCP characteristics. We presented the percentages in a tabular form and as bar charts by sex and the individual characteristics.

To determine whether the timing to seasonal influenza vaccination during the influenza seasons differed across age groups, we plotted survival curves (cumulative incidence) of SIV uptake in each influenza season among age groups using Kaplan-Meier method. We tested the null hypothesis of no statistical difference between the survival curves using the Log-rank test statistic. To determine the relative position of the curves with respect to the point of commencement of influenza circulation in each influenza season, we defined the point of commencement of influenza circulation in a season to be the beginning of laboratory confirmations of influenza from respiratory specimens of patients with influenza-like symptoms. We utilized the annual influenza epidemiological data reports by MH for this purpose, [10] and compared the survival curves against the point of commencement of influenza circulation for each influenza season.

We assessed the associations between SIV uptake and the individual socioeconomic, health-related and PCP characteristics, utilizing the generalized estimating equation (GEE) logistic regression models to estimate crude and multivariable adjusted odds ratios (ORs) and associated 95 % confidence intervals (CIs). [38] We specified clustering at individual level and utilized an autoregressive working correlation matrix, a logit link function, and a binomial family function. Model fit was assessed using the quasi-likelihood under the independence model criterion (QIC), a modification of the Akaike’s information criterion (AIC). [39] Selection of covariates for the adjusted analysis was determined using the directed acyclic graph (DAG), a causal diagram, [40] implemented in DAGitty (https://www.dagitty.net/), a web-based platform for creating and analyzing causal diagrams (Supplementary Fig. 1). A detailed list of the adjusted covariates for each analysis (adjustment for estimating direct effect) is presented as Supplementary Table 2 We conducted subgroup analysis by sex. All data analyses were performed using Stata version 16 (StataCorp, College Station, Texas).

Results

Descriptive analysis

The 5-yearly average SIV uptake percentage increased over time with 4.4 %, 13.1 %, 17.5 % and 21.7 % of < 5-year-olds, 2 %, 4.9 %, 9.7 % and 13.1 % of 5–17-year-olds, 5.4 %, 8.8 %, 10.7 % and 13.5 % of 18–44-year-olds, 16.8 %, 21.3 %, 23.6 % and 24.6 % of 45–64-year-olds, receiving the SIV in 2000–2004, 2005–2009, 2010–2014 and 2015–2019, respectively. There was a decline among ≥ 65-year-olds from 58.5 % to 53.5 %. We observed a similar pattern across strata of almost all individual and PCP characteristics (Table 1). The percentages were comparable for males and females among < 5-year-olds and 5–17-year-olds, but among the other age groups, females had considerably higher percentages compared with males. The percentages mostly increased with increase in income quintile particularly among < 5- and ≥ 65-year-olds. However, the percentages increased consistently with increased visits to PCP/hospitalization one year prior to influenza season. Further, the percentages were almost highest within Winnipeg’s Southern suburb compared with the other regions of residence and increased consistently with increase in the number of visits to PCP/hospitalization one year prior to an influenza season and was higher among those who have a chronic disease compared with those who do not have a chronic disease. We observed consistently higher percentages among those who had a female PCP compared with those who had a male PCP, and the percentage mostly increased with increased PCP’s number of years of practice, particularly among 45–64- and ≥ 65-year-olds. Further, the percentage was higher among those whose PCP administered at least one SIV in previous influenza season compared with those whose PCP did not administer vaccine. The overall average SIV uptake percentage from 2000/01 to 2019/20 influenza seasons across age group by sex are presented for income quintile (Fig. 1), region of residence (Fig. 2), number of visits to PCP/hospitalization one year prior to an influenza season (Fig. 3), and chronic disease status (Fig. 4).

Table 1.

5-yearly average seasonal influenza vaccine (SIV) uptake percentage (%) across age groups and by certain individual socioeconomic, health-related and primary care physician (PCP) characteristics in Manitoba, Canada from 2000/01 to 2019/20 influenza seasons.

<5 years 5–17 years 18–44 years 45–64 years ≥65 years
2000–04 2005–09 2010–14 2015–19 2000–04 2005–09 2010–14 2015–19 2000–04 2005–09 2010–14 2015–19 2000–04 2005–09 2010–14 2015–19 2000–04 2005–09 2010–14 2015–19
Overall 4.4 13.1 17.5 21.7 2.0 4.9 9.7 13.1 5.4 8.8 10.7 13.5 16.8 21.3 23.6 24.6 58.5 60.6 54.8 53.5
Sex
Female 4.2 12.9 17.4 22.1 2.0 4.9 9.9 13.3 7.2 11.1 13.4 16.4 20.3 25.0 27.2 27.8 59.0 61.6 56.0 54.6
Male 4.5 13.3 17.5 21.4 2.1 4.9 9.6 12.9 3.5 6.5 8.0 10.6 13.4 17.6 20.0 21.3 57.9 59.2 53.4 52.3
Income quintile
Q1 (lowest) 3.9 10.6 14.9 16.4 1.9 4.7 10.0 11.1 5.2 8.3 10.7 12.1 17.7 21.1 22.7 22.1 56.8 58.5 52.0 49.4
Q2 4.0 11.7 16.5 19.1 2.0 4.6 9.8 11.9 5.4 8.4 10.5 12.6 17.4 20.9 22.6 22.9 58.0 59.4 53.1 50.7
Q3 4.1 12.0 16.0 21.3 1.8 4.2 8.3 11.8 5.1 8.2 9.7 12.7 16.6 20.7 22.8 23.6 59.2 60.6 54.6 53.5
Q4 4.6 14.9 18.3 23.6 2.1 5.2 9.1 12.8 5.3 9.0 10.2 13.2 16.6 21.6 24.1 25.7 59.3 61.2 55.3 54.6
Q5 (highest) 5.6 17.4 21.6 28.3 2.2 5.6 10.7 16.1 5.4 9.7 11.4 15.2 15.5 21.5 24.7 27.2 60.2 61.9 56.3 56.3
Unknown 5.8 15.5 22.0 27.0 3.1 7.9 12.0 16.0 16.4 18.6 14.2 16.9 30.4 37.7 26.8 25.9 58.4 70.9 63.8 58.7
Region of residence
Winnipeg's southern
suburbs		 5.7 18.4 24.9 32.9 2.2 5.4 11.5 18.4 5.0 9.2 11.8 16.9 15.9 22.3 26.0 28.5 62.1 65.2 59.3 59.4
Winnipeg's northern
suburbs		 4.9 16.4 21.5 29.7 2.0 5.2 10.3 15.3 4.9 8.8 10.9 14.4 16.0 21.7 24.5 25.6 59.5 61.9 55.5 53.6
Winnipeg's inner city 4.7 14.6 19.4 24.0 1.8 5.0 10.5 13.9 4.8 8.6 11.2 13.4 15.7 20.7 22.9 23.1 52.9 55.7 48.8 45.7
Interlake-Eastern 4.4 11.6 15.0 18.9 1.9 4.5 8.4 11.3 5.2 7.6 9.3 11.2 17.8 20.5 22.4 23.3 57.3 58.0 53.3 52.5
Prairie Mountain 3.5 9.0 11.6 13.5 1.9 4.6 8.1 9.7 6.3 9.1 9.6 11.0 18.7 21.4 22.5 23.1 58.3 59.6 53.5 52.6
Southern 3.2 7.8 9.5 12.1 1.7 3.1 5.5 7.6 4.9 6.6 7.0 9.1 15.5 16.8 17.8 18.4 55.7 55.4 49.7 47.5
Northern 3.0 9.6 16.2 10.3 2.7 7.1 14.7 10.7 7.1 11.9 15.3 12.2 21.3 25.4 26.2 21.1 48.6 49.6 48.5 42.1
Unknown address 9.2 20.2 21.9 21.9 3.9 9.2 14.8 14.8 43.6 44.3 29.4 23.5 55.1 61.8 58.4 51.2 59.2 70.3 67.7 54.6
Visits to PCP/hospitalization one year prior to an influenza season
0 1.7 5.1 9.7 9.0 1.0 2.7 6.7 7.7 2.6 4.5 5.8 6.8 7.0 9.0 9.8 9.9 28.1 28.8 23.7 22.1
1 to 2 2.2 7.1 13.1 17.2 1.5 4.0 9.2 13.4 4.2 7.5 9.4 12.5 11.4 15.3 17.6 18.8 48.9 49.1 42.0 41.3
3 to 5 3.5 11.9 17.9 23.9 2.5 6.7 12.4 17.4 6.2 10.5 12.8 16.7 17.3 22.9 25.2 26.0 60.1 61.1 53.3 52.4
≥6 6.9 21.6 25.7 32.4 5.2 11.3 16.4 21.0 10.0 15.8 18.2 21.6 28.0 33.6 35.1 34.5 66.6 68.5 62.7 60.6
Having a chronic disease
No chronic disease 4.0 12.6 17.2 21.5 1.4 3.9 9.0 12.4 4.2 7.4 9.3 12.1 10.3 14.4 17.2 18.9 44.7 46.4 40.9 41.2
Chronic disease 8.3 18.6 21.7 26.0 7.2 12.8 16.3 19.2 13.0 17.0 18.3 20.1 27.7 31.7 32.6 31.7 63.7 65.0 59.1 57.3
Chronicmedicalconditions
Asthma 8.1 18.6 21.1 26.8 7.1 12.8 16.3 19.6 14.6 18.7 18.1 19.8 39.7 42.9 39.4 37.0 69.0 70.5 65.1 63.4
Chronic obstructive
pulmonary disease		 5.6 15.1 20.3 18.6 6.1 11.3 15.0 15.8 14.2 17.3 17.5 17.9 37.3 39.2 36.3 33.2 66.8 67.9 61.6 58.5
Ischemic heart disease 28.6 23.1 25.0 40.0 13.8 15.4 30.9 17.3 17.8 22.2 22.7 22.0 37.0 40.0 37.4 34.3 66.1 67.2 61.5 59.3
Stroke NA NA NA NA NA NA NA NA 19.7 23.8 22.2 22.0 40.0 41.0 37.1 31.6 62.0 64.2 58.4 53.0
Hypertension 16.7 28.4 29.1 32.1 12.0 17.7 20.1 20.2 12.4 16.9 20.4 22.3 26.1 30.7 33.3 33.0 64.5 65.4 59.6 58.1
Peripheral cardiovascular
disease		 15.2 24.2 27.0 31.2 7.4 11.0 15.1 21.1 10.0 14.5 16.3 20.3 24.9 29.7 31.1 31.9 63.1 65.8 60.1 58.8
Diabetes 35.2 30.8 18.8 20.0 19.4 21.8 19.1 17.4 20.9 21.9 22.3 21.8 38.7 40.5 37.8 34.3 64.1 65.0 59.7 57.5
Obesity 4.0 9.3 21.5 23.5 4.5 8.3 14.4 17.0 12.4 17.6 19.6 21.2 28.5 33.5 36.7 35.7 63.6 64.4 59.3 58.3
Chronic renal failure 19.4 31.9 30.2 33.6 29.5 30.9 24.8 23.1 34.0 32.7 28.8 25.7 45.7 44.9 44.2 40.4 58.5 62.8 58.4 56.2
Chronic liver disease 20.7 15.4 22.7 27.6 20.9 22.6 19.9 22.8 15.4 18.5 19.8 22.2 32.4 35.2 34.4 33.2 55.4 57.6 54.5 53.4
Dementia NA NA NA NA NA NA NA NA 13.0 17.0 19.8 20.1 34.1 37.6 39.5 37.8 61.3 68.0 64.3 57.8
Cancer (excluding non
melanoma skin cancer)		 26.5 37.7 36.8 29.6 23.1 26.1 31.8 29.6 15.5 20.6 18.9 22.5 35.0 38.6 36.2 35.1 60.2 62.0 56.3 55.9
HIV/AIDS 33.3 25.0 44.4 33.3 11.5 14.3 18.4 23.8 28.7 40.7 42.2 35.2 35.7 46.0 50.2 43.8 60.0 60.3 60.3 55.2
Other immune deficiency 23.1 45.5 50.0 56.3 35.5 21.2 26.7 37.8 13.0 19.0 18.4 34.8 25.2 33.3 50.9 44.6 31.6 61.5 50.0 63.7
Organ transplant 20.0 25.0 31.8 31.3 50.0 75.6 48.4 44.4 35.3 41.8 33.6 29.1 46.7 50.8 48.5 43.7 56.6 57.3 52.1 49.3
PCP's age on season start date
<40 3.3 11.6 20.3 24.4 2.2 5.5 11.1 14.3 6.6 10.6 12.7 16.2 19.4 23.8 25.5 25.7 60.6 62.0 55.8 53.4
40 to 64 5.2 15.5 18.5 24.5 2.6 6.2 11.3 16.1 6.5 10.8 12.9 16.6 19.6 24.8 27.2 28.2 63.0 64.7 58.4 57.1
≥65 5.6 13.9 20.3 24.9 2.5 5.6 11.1 16.3 5.8 9.0 13.1 16.1 18.0 21.9 26.8 28.5 59.0 60.2 55.8 56.2
PCP's gender
Female 5.3 16.2 21.1 27.8 2.9 6.6 12.1 17.2 7.2 12.0 14.1 18.3 20.0 25.3 27.6 28.8 62.4 63.8 57.7 56.6
Male 4.6 14.0 18.1 22.4 2.3 5.7 10.9 14.9 6.2 10.0 12.3 15.3 19.2 24.1 26.6 27.3 62.1 63.7 57.7 56.3
PCP's specialty
General practitioner 3.4 10.5 14.8 17.7 2.0 5.1 10.1 13.7 6.4 10.4 12.5 16.0 19.3 24.2 26.9 27.9 62.4 64.0 58.0 56.6
Paediatrician 6.5 19.3 24.8 33.8 3.5 7.9 14.1 20.9 5.6 10.4 13.2 20.8 12.2 30.0 19.9 23.2 45.0 68.8 35.2 41.7
Internist 5.4 9.7 17.2 18.5 2.7 6.3 10.9 16.9 10.1 15.8 17.4 19.9 23.4 28.8 28.9 28.6 59.3 59.7 52.9 52.2
Obstetrician 0.0 8.3 6.3 14.2 2.1 5.2 11.1 13.6 5.6 11.5 15.8 20.6 14.4 19.5 22.1 24.1 52.5 54.9 48.9 50.8
PCP's number of years of practice
<5 3.5 10.6 18.0 23.0 2.1 5.3 10.5 14.2 6.4 10.0 11.8 15.8 19.0 22.3 23.6 24.7 57.8 58.6 53.1 52.5
5–9 4.2 13.1 17.8 26.0 2.2 5.3 11.5 16.5 6.2 10.2 12.9 16.5 19.0 23.4 25.1 25.9 60.9 60.6 55.1 53.3
10–19 5.2 16.9 18.7 23.7 2.4 6.1 11.1 16.5 6.4 11.0 13.4 17.3 19.0 25.0 27.5 28.5 63.4 65.5 57.5 56.4
≥20 5.6 15.6 20.6 25.4 2.9 6.5 11.8 15.9 6.8 10.9 13.4 16.3 20.2 25.3 29.0 30.3 63.7 65.7 60.5 59.4
PCP's remuneration option
Salaried Physician 4.2 13.5 16.2 17.7 2.6 6.6 11.5 14.2 8.4 12.4 14.1 16.6 22.5 25.4 26.4 26.8 58.6 59.1 54.7 53.7
Normal Cheque 4.9 14.6 19.4 25.0 2.5 5.9 11.2 15.9 6.3 10.5 12.8 16.5 19.2 24.3 26.9 27.9 62.4 64.2 58.0 56.6
SIV administered by PCP in previous season
No vaccine provided 2.9 10.4 15.6 14.1 2.2 5.9 11.0 12.1 6.0 10.9 13.6 15.4 18.1 23.1 25.1 24.8 55.9 56.6 53.4 50.7
One or more vaccine
provided		 5.7 15.5 19.9 26.5 2.6 6.0 11.3 16.5 6.6 10.5 12.7 16.8 19.8 24.6 27.2 28.5 63.8 65.1 58.5 57.5
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NA = not applicable; HIV = human immunodeficiency virus; AIDS = acquired immunodeficiency syndrome; SIV = seasonal influenza vaccine.

Fig. 1.

Fig. 1

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Summary of seasonal influenza vaccine uptake across income quintiles by sex and age group.

Fig. 2.

Fig. 2

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Summary of seasonal influenza vaccine uptake across regions of residence by sex and age group.

Fig. 3.

Fig. 3

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Summary of seasonal influenza vaccine uptake according to categorized number of visits to primary care physician/hospitalization one year prior to influenza season start by sex and age group.

Fig. 4.

Fig. 4

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Summary of seasonal influenza vaccine uptake according to chronic disease status by sex and age group.

Differences between survival curves (cumulative incidence) of SIV uptake among age groups and relative position of the curves with respect to the point of commencement of influenza circulation in each influenza season

The Kaplan-Meier survival curves of SIV uptake among age groups for each influenza season are presented in Fig. 5. Overall, SIV uptake mostly commenced from October and ended around February, with most of the vaccinated individuals receiving the vaccine by December. Vaccine uptake patterns were largely similar across the seasons, with slight differences observed in 2003/04, 2009/10 and 2013/14 seasons. The Log rank test showed that there is a difference between the survival curves across the age groups in terms of the distribution of time until SIV uptake in all the seasons (p < 0.001). The point of commencement of influenza circulation, represented by the vertical dashed lines, was mostly (85 %) between November and January, with earlier commencements observed in 2003/04, 2009/10, and 2018/19 seasons, and later commencement observed in 2002/03. There was a high cumulative probability of SIV uptake (≥0.75) across all age groups before the point of commencement of influenza circulation in 60 % of the seasons (2000/01, 2001/02, 2002/03, 2005/06, 2006/07, 2007/08, 2008/09, 2011/12, 2012/13, 2014/15, 2015/16, 2016/17). There was a moderate cumulative probability of SIV uptake (>0.5 and < 0.75) across all age groups before the point of commencement of influenza circulation in 10 % of the seasons (2004/05 and 2013/14). There was a low cumulative probability of SIV uptake (<0.5) across age groups before the point of commencement of influenza circulation in 30 % of the seasons (2003/04, 2009/10, 2010/11, 2017/18, 2018/19, 2019/20). These findings were largely consistent among females (Supplementary Fig. 2) and for males (Supplementary Fig. 3).

Fig. 5.

Fig. 5

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Seasonal influenza vaccine uptake relative to commencement of influenza circulation by age group among the vaccinated individuals across influenza seasons. Note: Vertical red line represents the point of commencement of influenza circulation (influenza activity). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Association between SIV uptake and individual socioeconomic and health-related characteristics

The crude and the adjusted results are presented in Table 2. In the adjusted analyses, sex was not associated with SIV uptake among < 5-year-olds. However, among 5–17-year-olds, compared with females, males had increased odds of SIV uptake: OR 1.04 (1.03–1.06) whereas males had decreased odds of SIV uptake among 18–44-year-olds: OR 0.80 (0.79–0.81), 45–64-year-olds: OR 0.77 (0.77–0.78), and ≥ 65-year-olds: 0.96 (0.95–0.96). Compared with the lowest income quintile across all age groups, those in higher income quintiles mostly had higher odds of SIV uptake. The odds of SIV uptake increased with an increase in income quintile among < 5-year-olds, but a clear trend was not observed among the other age groups. Compared with living in Winnipeg’s Southern suburb, living in any of the other regions of residence was associated with decreased odds of SIV uptake across all age groups except among 18–44-year-olds in Northern Manitoba for whom we observed increased odds of SIV uptake: OR 1.04 (CI 1.02–1.07). Across age groups, there was mostly increased odds of SIV uptake among those with increased contact with the PCP/hospitalization one year prior to an influenza season particularly with 3–5 and ≥ 6 contacts. Compared with individuals who did not have a chronic disease, those who had a chronic disease had increased odds of SIV uptake except for < 5-year-olds. While variable, we observed mostly increased odds of SIV uptake among individual chronic disease patient populations particularly among 5–17-, 18–44-, and 45–64-year-olds, with the strongest predictors of SIV uptake found to be ischaemic heart disease, stroke, chronic renal failure, and cancer. We made similar observations among females (Supplementary Table 3) and males (Supplementary Table 4).

Table 2.

Odds ratio [OR] (95% confidence interval [CI]) of the association between seasonal influenza vaccine (SIV) uptake and certain individual socioeconomic, health-related and primary care physician (PCP) characteristics across age groups.

<5 years 5–17 years 18–44 years 45–64 years ≥65 years
N = 360,383 N = 526,029 N = 897,925 N = 595,823 N = 366,420
Crude OR
(95 % CI)		 Adjusted OR (95 % CI) Crude OR
(95 % CI)		 Adjusted OR (95 % CI) Crude OR
(95 % CI)		 Adjusted OR (95 % CI) Crude OR
(95 % CI)		 Adjusted OR (95 % CI) Crude OR
(95 % CI)		 Adjusted OR (95 % CI)
Sex
Female ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
Male 1.00 (0.98–1.01) 0.99 (0.98–1.01) 1.06 (1.04–1.08) 1.04 (1.03–1.06) 0.77 (0.76–0.78) 0.80 (0.79–0.81) 0.82 (0.81–0.82) 0.77 (0.77–0.78) 0.96 (0.95–0.97) 0.96 (0.95–0.96)
Income quintile
Q1 (lowest) ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
Q2 1.13 (1.11–1.16) 1.11 (1.09–1.13) 1.06 (1.03–1.08) 1.04 (1.02–1.07) 1.03 (1.01–1.04) 1.05 (1.04–1.06) 1.01 (1.00–1.02) 1.06 (1.05–1.08) 1.05 (1.04–1.06) 1.05 (1.04–1.07)
Q3 1.16 (1.13–1.18) 1.13 (1.11–1.16) 1.01 (0.98–1.03) 1.00 (0.97–1.02) 0.99 (0.98–1.01) 1.03 (1.01–1.04) 1.01 (0.99–1.02) 1.08 (1.07–1.09) 1.10 (1.08–1.11) 1.10 (1.09–1.12)
Q4 1.31 (1.28–1.34) 1.25 (1.22–1.28) 1.08 (1.05–1.10) 1.05 (1.02–1.08) 1.02 (1.00–1.03) 1.06 (1.04–1.07) 1.05 (1.03–1.06) 1.14 (1.12–1.15) 1.13 (1.11–1.14) 1.13 (1.11–1.14)
Q5 (highest) 1.57 (1.54–1.60) 1.47 (1.44–1.50) 1.26 (1.23–1.30) 1.23 (1.20–1.26) 1.08 (1.06–1.09) 1.14 (1.12–1.15) 1.05 (1.04–1.06) 1.18 (1.16–1.19) 1.16 (1.15–1.18) 1.17 (1.16–1.19)
Region of residence
Winnipeg's southern suburbs ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
Winnipeg's northern suburbs 0.86 (0.85–0.88) 0.91 (0.89–0.93) 0.89 (0.87–0.91) 0.91 (0.89–0.93) 0.96 (0.95–0.98) 0.96 (0.95–0.97) 0.95 (0.94–0.96) 0.93 (0.92–0.94) 0.88 (0.87–0.89) 0.89 (0.87–0.90)
Winnipeg's inner city 0.78 (0.77–0.80) 0.95 (0.92–0.97) 0.88 (0.85–0.90) 0.95 (0.92–0.97) 0.95 (0.94–0.97) 0.96 (0.94–0.97) 0.91 (0.90–0.92) 0.90 (0.88–0.91) 0.75 (0.73–0.76) 0.78 (0.77–0.80)
Interlake-Eastern 0.64 (0.62–0.65) 0.69 (0.67–0.71) 0.69 (0.67–0.71) 0.71 (0.68–0.73) 0.84 (0.83–0.86) 0.82 (0.80–0.83) 0.93 (0.92–0.95) 0.89 (0.88–0.91) 0.79 (0.77–0.80) 0.78 (0.77–0.79)
Prairie Mountain 0.43 (0.42–0.44) 0.56 (0.54–0.57) 0.56 (0.55–0.58) 0.63 (0.61–0.65) 0.86 (0.84–0.87) 0.87 (0.85–0.88) 0.90 (0.89–0.92) 0.91 (0.90–0.93) 0.78 (0.77–0.79) 0.81 (0.80–0.82)
Southern 0.42 (0.41–0.43) 0.48 (0.47–0.50) 0.58 (0.56–0.60) 0.61 (0.59–0.63) 0.72 (0.71–0.73) 0.72 (0.71–0.73) 0.74 (0.72–0.75) 0.73 (0.72–0.74) 0.68 (0.67–0.69) 0.68 (0.67–0.69)
Northern 0.46 (0.44–0.47) 0.65 (0.63–0.68) 0.70 (0.66–0.73) 0.79 (0.75–0.83) 1.07 (1.04–1.10) 1.04 (1.02–1.07) 0.97 (0.95–1.00) 0.91 (0.89–0.93) 0.59 (0.57–0.61) 0.61 (0.59–0.63)
Visits to PCP/hospitalization one year prior to an influenza season
0 ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
1 to 2 0.95 (0.78–1.15) 0.90 (0.73–1.12) 0.91 (0.84–1.00) 0.93 (0.84–1.03) 0.89 (0.86–0.91) 1.00 (0.97–1.02) 0.98 (0.96–1.00) 1.04 (1.02–1.06) 0.97 (0.95–0.99) 0.97 (0.95–0.99)
3 to 5 1.07 (0.89–1.30) 1.02 (0.83–1.26) 0.94 (0.86–1.03) 0.95 (0.86–1.05) 0.98 (0.96–1.01) 1.10 (1.07–1.12) 1.09 (1.07–1.12) 1.14 (1.11–1.16) 1.06 (1.04–1.08) 1.05 (1.03–1.08)
6+ 1.43 (1.18–1.73) 1.35 (1.10–1.67) 1.01 (0.92–1.11) 1.00 (0.91–1.10) 1.15 (1.12–1.18) 1.25 (1.22–1.28) 1.25 (1.23–1.28) 1.25 (1.22–1.28) 1.12 (1.10–1.15) 1.12 (1.10–1.15)
Chronicmedicalconditions
Having a chronic disease 1.06 (1.04–1.09) 1.01 (0.91–1.12) 1.49 (1.47–1.52) 1.15 (1.08–1.23) 1.61 (1.59–1.62) 1.11 (1.09–1.13) 1.55 (1.54–1.56) 1.17 (1.16–1.18) 1.15 (1.14–1.16) 1.15 (1.14–1.16)
Asthma 1.02 (1.00–1.05) 0.98 (0.96–1.01) 1.46 (1.43–1.48) 1.44 (1.41–1.46) 1.55 (1.53–1.58) 1.50 (1.47–1.52) 1.53 (1.51–1.55) 1.46 (1.44–1.48) 1.18 (1.17–1.20) 1.16 (1.14–1.17)
Chronic obstructive pulmonary
disease		 0.94 (0.87–1.01) 0.98 (0.90–1.06) 1.24 (1.15–1.33) 1.19 (1.10–1.28) 1.36 (1.32–1.40) 1.18 (1.15–1.22) 1.41 (1.39–1.43) 1.28 (1.26–1.29) 1.07 (1.06–1.08) 1.06 (1.05–1.07)
Ischemic heart disease 2.30 (1.32–4.00) 1.83 (1.05–3.20) 1.52 (1.01–2.29) 1.39 (0.92–2.11) 1.74 (1.64–1.83) 1.32 (1.25–1.40) 1.52 (1.50–1.54) 1.30 (1.29–1.32) 1.06 (1.06–1.07) 1.06 (1.05–1.07)
Stroke N/A N/A N/A N/A 1.68 (1.52–1.85) 1.31 (1.19–1.45) 1.36 (1.31–1.40) 1.11 (1.07–1.14) 0.87 (0.86–0.88) 0.86 (0.85–0.88)
Hypertension 1.90 (1.61–2.26) 1.19 (0.95–1.49) 1.78 (1.60–1.97) 1.18 (1.03–1.35) 1.52 (1.49–1.54) 1.30 (1.28–1.32) 1.33 (1.32–1.34) 1.20 (1.19–1.21) 1.09 (1.08–1.09) 1.08 (1.07–1.09)
Peripheral cardiovascular disease 1.59 (1.43–1.78) 1.38 (1.23–1.54) 1.46 (1.32–1.61) 1.34 (1.21–1.47) 1.24 (1.21–1.27) 1.16 (1.14–1.19) 1.13 (1.12–1.15) 1.08 (1.06–1.09) 1.00 (0.99–1.01) 1.00 (0.99–1.01)
Diabetes 1.66 (1.35–2.04) 1.50 (1.22–1.84) 1.95 (1.82–2.09) 1.86 (1.73–1.99) 1.96 (1.93–2.00) 1.74 (1.71–1.78) 1.72 (1.71–1.74) 1.58 (1.57–1.60) 1.01 (1.00–1.02) 1.00 (0.99–1.01)
Obesity 0.93 (0.73–1.18) 0.94 (0.73–1.20) 1.14 (1.05–1.24) 1.02 (0.94–1.11) 1.44 (1.41–1.48) 1.22 (1.19–1.25) 1.27 (1.25–1.29) 1.09 (1.07–1.11) 0.97 (0.96–0.99) 0.96 (0.94–0.98)
Chronic renal failure 2.19 (1.84–2.60) 1.66 (1.32–2.08) 2.31 (2.04–2.61) 1.78 (1.52–2.08) 2.54 (2.39–2.70) 1.79 (1.68–1.90) 1.59 (1.54–1.64) 1.23 (1.19–1.27) 0.78 (0.77–0.79) 0.77 (0.76–0.79)
Chronic liver disease 1.45 (1.01–2.07) 1.05 (0.73–1.51) 1.70 (1.35–2.14) 1.37 (1.09–1.72) 1.49 (1.41–1.58) 1.24 (1.17–1.31) 1.24 (1.20–1.27) 1.10 (1.07–1.13) 0.77 (0.74–0.79) 0.78 (0.75–0.80)
Dementia N/A N/A N/A N/A 1.30 (1.22–1.38) 1.18 (1.11–1.25) 1.30 (1.26–1.34) 1.20 (1.16–1.24) 0.93 (0.92–0.94) 0.93 (0.92–0.94)
Cancer (excluding non-melanoma
skin cancer)		 2.03 (1.73–2.38) 1.80 (1.53–2.12) 2.17 (1.91–2.47) 2.09 (1.84–2.37) 1.41 (1.35–1.48) 1.34 (1.28–1.41) 1.23 (1.21–1.25) 1.20 (1.18–1.22) 0.86 (0.85–0.87) 0.86 (0.85–0.86)
HIV/AIDS 2.30 (1.04–5.09) 2.25 (1.00–5.06) 1.10 (0.74–1.63) 1.09 (0.72–1.63) 2.73 (2.52–2.95) 2.69 (2.48–2.91) 1.83 (1.69–1.99) 1.93 (1.78–2.10) 0.98 (0.81–1.18) 1.07 (0.88–1.29)
Other immune deficiency 1.53 (0.90–2.60) 1.14 (0.67–1.94) 1.57 (1.00–2.47) 1.36 (0.89–2.08) 1.01 (0.67–1.53) 0.84 (0.56–1.26) 0.98 (0.79–1.23) 0.89 (0.71–1.11) 0.63 (0.51–0.78) 0.65 (0.52–0.81)
Organ transplant 1.04 (0.52–2.06) 0.83 (0.43–1.58) 1.87 (1.22–2.85) 1.49 (1.02–2.18) 1.36 (1.06–1.76) 0.98 (0.77–1.23) 0.96 (0.83–1.10) 0.83 (0.73–0.95) 0.69 (0.58–0.81) 0.72 (0.61–0.85)
PCP's age on season start date
<40 ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
40 to 64 1.04 (1.03–1.06) 1.04 (1.02–1.05) 1.08 (1.06–1.09) 1.07 (1.05–1.08) 1.03 (1.02–1.04) 1.03 (1.02–1.03) 1.04 (1.03–1.04) 1.04 (1.03–1.04) 1.05 (1.04–1.05) 1.05 (1.04–1.05)
≥65 1.10 (1.08–1.12) 1.11 (1.09–1.13) 1.11 (1.09–1.13) 1.11 (1.08–1.13) 1.02 (1.01–1.04) 1.02 (1.01–1.04) 1.03 (1.02–1.04) 1.02 (1.01–1.03) 0.99 (0.98–1.00) 0.99 (0.98–1.00)
PCP's sex
Female ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
Male 0.82 (0.81–0.83) 0.83 (0.82–0.84) 0.87 (0.86–0.88) 0.87 (0.86–0.88) 0.91 (0.90–0.91) 0.90 (0.89–0.91) 0.98 (0.98–0.99) 0.97 (0.96–0.98) 1.02 (1.01–1.02) 1.02 (1.01–1.03)
PCP's specialty
General practitioner ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
Paediatrician 1.63 (1.61–1.65) 1.57 (1.55–1.59) 1.21 (1.20–1.23) 1.18 (1.17–1.20) 0.88 (0.84–0.92) 0.89 (0.85–0.93) 0.84 (0.77–0.91) 0.80 (0.74–0.87) 0.62 (0.55–0.71) 0.63 (0.55–0.71)
Internist 1.20 (1.07–1.33) 1.25 (1.11–1.41) 1.19 (1.12–1.26) 1.14 (1.07–1.22) 1.19 (1.17–1.21) 1.16 (1.13–1.18) 1.06 (1.05–1.07) 1.06 (1.05–1.08) 0.95 (0.94–0.96) 0.99 (0.97–1.00)
Obstetrician 1.05 (0.61–1.82) 1.16 (0.66–2.03) 0.88 (0.81–0.97) 0.89 (0.81–0.98) 1.09 (1.08–1.11) 1.13 (1.11–1.14) 0.93 (0.92–0.95) 0.99 (0.98–1.01) 0.98 (0.95–1.01) 1.01 (0.98–1.05)
PCP's number of years of practice
<5 ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
5–9 1.04 (1.03–1.06) 1.04 (1.02–1.06) 1.07 (1.05–1.08) 1.06 (1.05–1.08) 1.03 (1.02–1.04) 1.03 (1.02–1.04) 1.01 (1.00–1.02) 1.01 (1.00–1.02) 1.02 (1.01–1.02) 1.02 (1.01–1.03)
10–19 1.01 (0.99–1.03) 0.99 (0.97–1.01) 0.99 (0.98–1.01) 0.98 (0.96–1.00) 1.00 (0.99–1.01) 1.00 (0.99–1.01) 1.03 (1.03–1.04) 1.04 (1.03–1.05) 1.09 (1.08–1.10) 1.09 (1.08–1.10)
≥20 1.06 (1.05–1.08) 1.04 (1.02–1.05) 1.02 (1.01–1.04) 1.01 (0.99–1.02) 1.01 (1.00–1.02) 1.01 (1.00–1.02) 1.08 (1.07–1.09) 1.09 (1.08–1.10) 1.12 (1.11–1.13) 1.13 (1.12–1.14)
PCP's remuneration option
Salaried Physician ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
Normal Cheque 1.22 (1.19–1.25) 1.18 (1.15–1.21) 1.08 (1.05–1.11) 1.06 (1.03–1.09) 0.95 (0.94–0.97) 0.95 (0.94–0.97) 1.00 (0.98–1.01) 1.00 (0.99–1.01) 1.08 (1.07–1.10) 1.08 (1.07–1.09)
SIV administered by PCP in previous season
No vaccine provided ref. ref. ref. ref. ref. ref. ref. ref. ref. ref.
One or more vaccine provided 1.53 (1.51–1.55) 1.51 (1.48–1.53) 1.19 (1.18–1.21) 1.21 (1.19–1.22) 1.05 (1.04–1.05) 1.04 (1.04–1.05) 1.06 (1.05–1.07) 1.05 (1.04–1.06) 1.06 (1.05–1.07) 1.05 (1.04–1.05)
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See SupplementaryTable 2for adjusted covariates; N/A = not applicable; HIV = human immunodeficiency virus; AIDS = acquired immunodeficiency syndrome.

Association between SIV uptake and PCP characteristics

The crude and the adjusted results are presented in Table 2. In the adjusted analyses, compared with those whose PCP is < 40-years of age, there was mostly increased odds of SIV uptake among those who had an older PCP. There was decreased odds of SIV uptake among those who had a male PCP compared with a female PCP except for ≥ 65-year-olds among whom we observed slightly increased odds: OR 1.02 (1.01–1.03). Compared with those who had a General Practitioner as a PCP, there was increased odds of SIV uptake among < 5- and 5–17-year-olds who had a Paediatrician or an Internist as a PCP, and mostly increased odds among 18–44-, 45–64-, and ≥ 65-year-olds who had an Internist as PCP. There was decreased odds of SIV uptake among 5–17-year-olds: OR 0.89 (0.81–0.98) and increased odds among 18–44-year-olds: OR 1.13 (1.11–1.14) who had an Obstetrician as a PCP compared with those who had a General Practitioner. Compared with those whose PCP had < 5 years of practice, there was generally an associated increased odds of SIV uptake across age groups among those whose PCP had more years of practice. While there was increased odds of SIV uptake among those whose PCP received normal cheque payment compared with salary payment among < 5-year-olds: OR 1.18 (1.15–1.21), 5–17-year-olds: OR 1.06 (1.03–1.09), and ≥ 65-year-olds: OR 1.08 (1.07–1.09), we observed the opposite among 18–44-year-olds: OR 0.95 (0.94–0.97) and no association among 45–64-year-olds. There was increased odds of SIV uptake across all age groups among those whose PCP administered at least one SIV in prior influenza season compared with no administration of vaccine. We made mostly similar observations among females (Supplementary Table 3) and males (Supplementary Table 4).

Discussion

In temperate countries such as Canada, seasonal peak in influenza circulation typically occurs during the winter months. However, variability in patterns of seasonality complicate the optimal timing of influenza vaccinations. [41] For the Northern Hemisphere to which Canada belongs, seasonal influenza vaccination typically starts in September of each year and ends in December or early January of the following year. [41] In Manitoba, Canada, influenza vaccination typically commences in October, and it usually takes ten to 14 days for an immune response and development of protection following influenza vaccination, [42] with the protection provided by the vaccine expected to last up to the end of the influenza season. Due to the seasonality of influenza and seasonal peak in influenza activity mostly in the winter months (December to March), some experts have proposed delaying influenza vaccination program commencement to late November. [42] However, our findings suggest that such a delay may not be ideal for Manitoba considering that a majority of influenza circulation commencement in the seasons that we assessed was between November and January, and mostly in November, with an observed high cumulative probability of SIV uptake before influenza circulation commencement across age groups in 60 % of the seasons. Moreover, it is likely that influenza circulation may have started even much earlier than determined with our proxy method for determining influenza activity commencement, a method that may not be entirely accurate. Based on this fact, a slightly earlier seasonal influenza vaccination commencement; perhaps, in September, may provide better protection for Manitobans. Nevertheless, SIV uptake patterns were largely similar among age groups across the twenty influenza seasons assessed in this study, and the average SIV uptake percentage increased over time in all age groups and across the various individual socioeconomic, health-related and PCP characteristics, except for ≥ 65-year-olds among whom there was a decline.

The observed higher SIV uptake with increasing age may suggest increased incidence of chronic diseases with aging, especially from middle age, which may increase the frequency of contact with PCPs and, consequently, increase the probability of an offer and receipt of SIV. Surprisingly, we made this observation across the strata of all individual and PCP characteristics, thus, suggesting a strong influence of age on SIV uptake. Further, the mostly associated increased odds of SIV uptake with increased contact with the health system, and with having a chronic disease, both of which have been associated with age, [43] further support this notion. Additionally, among chronic medical conditions, the strongest predictors of SIV uptake were ischaemic heart disease, stroke, chronic renal failure, and cancer, chronic conditions that are mostly age-related. We made many of these observations in our published systematic reviews and meta-analyses of determinants of SIV uptake among ≥ 65 year-olds in North America, [44] and globally. [16] Even though the population for the reviews was older adults, advancing age, having a chronic disease and visits to the PCPs were associated with higher SIV uptake. Only one of these reviews included a study from Canada; [22] thus, reflecting a lack of published evidence from Canada on the determinants of SIV uptake among older adults despite the importance of this age group. Nonetheless, most of the individual studies included in the reviews largely support our findings. Another systematic review of factors associated with SIV uptake in 18–64-year-olds also found that older age and having a chronic disease were strongly predictive of influenza vaccination. [12] This also supports the correlation between aging and chronic diseases. Further, similar findings have been reported; however, among at-risk adults in England, [45] adding to the suggestion that aging has a strong influence on SIV uptake. Nevertheless, a study conducted in China found that older adults were more likely to receive recommendations from healthcare professionals and perceive the severity of seasonal influenza more, and were less likely to worry about side effects of vaccination. [46] The authors concluded that age disparity in SIV uptake between older and younger adults (48.7 % vs 16.0 %) could be due to differing professional recommendations and public perceptions. These findings strongly suggest that in addition to chronic diseases, aging may also correlate with other predictors of SIV uptake, including a higher social class, having a higher education, and poor self-health assessment. [16].

The observed lack of association between SIV uptake and sex among < 5 year-olds was not a surprise finding as this has been alluded to by a previous study; thus, suggesting that a child’s gender is unlikely a predictor of parents’ deciding on vaccination for their children. [47] Just as we found an associated increased odds of SIV uptake among adult females compared with adult males, previous studies have also shown that females are more likely than males to consult with the primary care providers, [48], [49] and frequent visits to the physicians has been associated with increased SIV uptake. [50] We observed associated increased odds of SIV uptake among those in the higher income quintiles across all age groups. This finding was as expected and have been previously reported, [44] with employment and level of education also having been found to be associated with both income and higher uptake of SIV [16,44]. The evidence is strengthened by the observed increasing trend in the odds of SIV uptake with increase in income quintile across almost all age groups. This socioeconomic disparity may be indicative of underlying issues such as education, employment, ethnicity/race and barriers to vaccination. Moreover, socioeconomic deprivation is known to be associated with poor healthcare utilization, particularly preventative care. This may explain our finding that residing in Winnipeg’s Southern suburb, arguably, the most affluent of all the areas of residence in Manitoba, was generally associated with increased odds of SIV uptake compared with residing in other regions of Manitoba known to have substantially higher populations of ethnic minorities in comparison to Winnipeg’s Southern suburb. Although we did not have data on ethnicity to assess its association with SIV uptake, considering the known relationship between socioeconomic deprivation and ethnicity, our findings may also suggest lower uptake of SIV among ethnic minorities in Manitoba. However, other factors such as vaccination timing, vaccine availability, ease of obtaining a doctor’s appointment, and differences in region-specific public health programs and strategies may also influence SIV uptake in the regions of residence. In order to address this observed socioeconomic disparity in uptake of SIV in Manitoba, regional health authorities in Manitoba may consider prioritizing improving access to preventative care by increasing the health workforce and health clinics, and targeted health education especially in the disadvantaged areas.

The increased odds of SIV uptake among those who had an older PCP may be explained by the higher uptake of SIV among those whose PCP had more years of practice, which may imply more awareness of preventative care with years of practice and may suggest the need for targeted education of younger physicians on preventative care and available services. This becomes even more important especially because health care providers are among the most important advocates of preventative care and a major source of information regarding vaccinations. [51], [52] We observed increased odds of SIV uptake among those whose PCP received normal cheque compared with salary remuneration and although this observation was made only among < 5-, 5–17-, and ≥ 65-year-olds (the opposite observed among 18–44-year-olds), it may be due to the encouraging influence of remuneration for service as we found in our published systematic review. [53] A similar study in Valencia, Spain examined whether physician’s age, gender, specialty in family and community medicine, years of professional practice, and total number of patients on physician’s list, among others, were predictors of SIV uptake among older adult patients (65 + year-olds). [19] However, the study found none of these PCP characteristics to be a significant predictor of SIV uptake although the study involved a small number of physicians (73 physicians), and therefore may not have been well powered, which may explain why. Another study also examined provider factors predictive of self-reported influenza vaccination rates among a diverse sample of older adult patients from rural, suburban, Veterans Affairs, and inner-city practices in the United States of America. [54] Utilizing a two-stage, stratified, random-cluster sampling to select 71 clinicians and a random sample of 925 of their patients, the authors assessed only predisposing, reinforcing, enabling, and environmental factors that may determine SIV uptake. While the study did not assess provider sociodemographic characteristics, it found all the assessed factors to have a significant association with SIV uptake. There is a paucity of published evidence on associations between SIV uptake and PCPs sociodemographic characteristics across jurisdictions. Therefore, our study provides substantial insights that may form the basis for further studies in different populations.

Limitations and merits

Since we could not determine with certainty, the exact time point when influenza circulation commenced during the assessed influenza seasons, we utilized a proxy for this, using the time for the first set of laboratory confirmations of influenza from respiratory specimens of patients presenting with influenza-like symptoms as reported in the annual influenza epidemiological data reports by MH. However, this approach did not consider any asymptomatic persons and those individuals who chose to self-manage rather than present at a clinic but would have tested positive for influenza if tested. It may therefore be that influenza circulation started much earlier than documented since we based laboratory confirmation only on the testing of respiratory specimens of individuals who had influenza-like symptoms, presented to a clinic and had swabs collected and tested, and the test results documented.

There is the possibility that our GEE model may not have accounted for everything necessary, and misspecification of the within individual working covariance structure in the model was also possible, with the potential for biased parameter estimations. However, we appropriately assessed for model fit and parameter estimates from the GEE are consistent even when the covariance structure is wrongly specified, albeit under mild regularity conditions. [38] While we adjusted for potential confounders as appropriately determined using a DAG, some established predictors of SIV uptake such as ethnicity, [55] level of education, employment status, smoking and alcohol consumption, [16] religious beliefs and attitudes towards vaccination were not available in our dataset and therefore not considered in our models even if any was suggested by the DAG. We were also unable to account for media/social influence. All of these posed the potential for residual confounding in our analyses, and while we could mitigate the impact of some of them by collection of survey data, such an approach would be expensive and time consuming and may not even be feasible. Moreover, such data based on self-report would then introduce the biases that are inherent in surveys such as recall and social desirability biases, [30] thus, reducing the validity of our findings. Even so, any unknown and therefore not measured determinant of SIV uptake may have also confounded our analysis. Further, we conducted a retrospective data analysis and therefore, there was the possibility for misclassification of our outcome and exposures due to documentation and measurement errors. However, the completeness and accuracy of the important elements of the immunization registry and the other administrative health databases utilized for this study are well established. [32], [33], [34].

These limitations notwithstanding, we conducted a unique analysis of many years of SIV uptake data since public funding of seasonal influenza vaccination in Manitoba, and our study is the first of its kind from Manitoba. This study has an immensely large sample size and the analyses were conducted by age group and important population characteristics; thus, enabling exploration of similarities and differences in effect across age groups and strata of population characteristics. While our findings may not be generalizable to the whole of Canada, they provide novel insights for Manitoba and may form the basis for further assessments of the individual and PCP characteristics that may determine SIV uptake especially within important subpopulations. Further, the observed decline in SIV uptake among ≥ 65-year-olds require public health attention and further investigations. Our findings may help inform targeted vaccination programs and public health education to optimize seasonal influenza vaccination in Manitoba and potentially, similar jurisdictions.

Contributors: Okoli was responsible for study design. Mahmud and Righolt were responsible for study supervision. Alessi-Severini, Van Caeseele, Kuo, and Mahmud provided overall guidance on the study. Okoli, Righolt and Zhang were responsible for data extraction. Okoli and Zhang accessed and verified the data. Okoli was responsible for data analysis. Okoli, Alessi-Severini, Van Caeseele, Kuo, and Mahmud were responsible for data interpretation. Okoli drafted the manuscript. All authors reviewed and approved the manuscript. Okoli (corresponding author) and Mahmud (senior author) had full access to all of the data in the study and the final responsibility to submit for publication.

Data sharing: The data used for this study was derived from Manitoba government administrative health and social databases. The data was provided under specific data sharing agreements only for approved use at Manitoba Centre for Health Policy (MCHP). Neither the researchers nor the MCHP own the original source data and therefore, the data cannot be provided to a public repository. The original data sources and approval for use are noted in this paper. Where necessary, source data specific to this study may be reviewed at the MCHP with the consent of the original data providers and the required privacy and ethical review bodies.

CRediT authorship contribution statement

George N. Okoli: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing. Christiaan H. Righolt: Data curation, Investigation, Resources, Supervision, Validation, Writing – review & editing. Geng Zhang: Data curation, Investigation, Resources, Validation, Writing – review & editing. Silvia Alessi-Severini: . Paul Van Caeseele: Investigation, Project administration, Visualization, Writing – review & editing. I fan Kuo: . Salaheddin M. Mahmud: Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – review & editing.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Mahmud has received unrestricted research grants from GlaxoSmithKline, Merck, Pfizer, Sanofi Pasteur, and Roche-Assurex for unrelated studies, and fees as a consultant and advisory board member for GlaxoSmithKline, Merck, Pfizer, Sanofi Pasteur, and Seqirus. Righolt has received an unrestricted research grant from Pfizer for an unrelated study. The other authors declare that they have no conflicts of interest].

Acknowledgements

We acknowledge the MCHP for use of data contained in the Manitoba Population Research Data Repository, and specifically thank Heather Prior and Charles Burchill of the Manitoba Centre for Health Policy for their assistance with data collation and for responding to our enquiries. The results and conclusions presented in this paper are those of the authors and no official endorsement by the Manitoba Centre for Health Policy or Manitoba Health and Seniors Care.

Funding: This study received no specific funding. Okoli is a recipient of the Manitoba Training Program Fellowship Award, the Centre on Aging Betty Havens Memorial Graduate Fellowship Award, and the Evelyn Shapiro Award, all for health services research. Mahmud is supported, in part, by funding from the Canada Research Chairs Program. The authors accept responsibility to submit for publication.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jvacx.2024.100435.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Supplementary data 1
mmc1.pdf (37.9KB, pdf)
Supplementary data 2
mmc2.pdf (443.3KB, pdf)
Supplementary data 3
mmc3.pdf (443.4KB, pdf)
Supplementary data 4
mmc4.docx (41.5KB, docx)

Data availability

The authors do not have permission to share data.

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Associated Data

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

Supplementary Materials

Supplementary data 1
mmc1.pdf (37.9KB, pdf)
Supplementary data 2
mmc2.pdf (443.3KB, pdf)
Supplementary data 3
mmc3.pdf (443.4KB, pdf)
Supplementary data 4
mmc4.docx (41.5KB, docx)

Data Availability Statement

The authors do not have permission to share data.

Articles from Vaccine: X are provided here courtesy of Elsevier

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