University of Groningen
Varying Vaccination Rates Among Patients Seeking Care for Acute Respiratory Illness
Shehadeh, Fadi; Zacharioudakis, Ioannis M; Kalligeros, Markos; Mylona, Evangelia K; Karki,
Tanka; van Aalst, Robertus; Chit, Ayman; Mylonakis, Eleftherios
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Open Forum Infectious Diseases
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10.1093/ofid/ofaa234
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Shehadeh, F., Zacharioudakis, I. M., Kalligeros, M., Mylona, E. K., Karki, T., van Aalst, R., Chit, A., & Mylonakis, E. (2020). Varying Vaccination Rates Among Patients Seeking Care for Acute Respiratory Illness: A Systematic Review and Meta-analysis. Open Forum Infectious Diseases, 7(7), [ofaa234]. https://doi.org/10.1093/ofid/ofaa234
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M A J O R A R T I C L E
Open Forum Infectious Diseases
Received 3 March 2020; editorial decision 8 June 2020; accepted 11 June 2020.
Correspondence: Eleftherios Mylonakis, MD, PhD, FIDSA, Infectious Diseases Division, Warren Alpert Medical School of Brown University, Rhode Island Hospital, 593 Eddy Street, POB, 3rd Floor, Suite 328/330, Providence, RI 02903 (emylonakis@lifespan.org).
Open Forum Infectious Diseases®
© The Author(s) 2020. Published by Oxford University Press on behalf of Infectious Diseases Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/ by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com DOI: 10.1093/ofid/ofaa234
Varying Vaccination Rates Among Patients Seeking Care
for Acute Respiratory Illness: A Systematic Review and
Meta-analysis
Fadi Shehadeh,1 Ioannis M. Zacharioudakis,2 Markos Kalligeros,1 Evangelia K. Mylona,1 Tanka Karki,1 Robertus van Aalst,3,4 Ayman Chit,3,5 and Eleftherios Mylonakis1
1Infectious Diseases Division, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA, 2Division of Infectious Diseases and Immunology, Department of Medicine, NYU School of Medicine, New York, New York, USA, 3Vaccine Epidemiology and Modelling, Sanofi Pasteur, Swiftwater, Pennsylvania, USA, 4Faculty of Medical Sciences, University of Groningen, Groningen, the Netherlands, and 5Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada
Background. Complications following influenza infection are a major cause of morbidity and mortality, and the Centers for Disease
Control Advisory Committee on Immunization Practices recommends universal annual vaccination. However, vaccination rates have re-mained significantly lower than the Department of Health and Human Services goal. The aim of this work was to assess the vaccination rate among patients who present to health care providers with influenza-like illness and identify groups with lower vaccination rates.
Methods. We performed a systematic search of the PubMed and EMBASE databases with a time frame of January 1, 2010, to
March 1, 2019 and focused on the vaccination rate among patients seeking care for acute respiratory illness in the United States. A random effects meta-analysis was performed to estimate the pooled seasonal influenza vaccination rate, and we used a time trend analysis to identify differences in annual vaccination over time.
Results. The overall pooled influenza vaccination rate was 48.61% (whites: 50.87%; blacks: 36.05%; Hispanics: 41.45%). There
was no significant difference among gender groups (men: 46.43%; women: 50.11%). Interestingly, the vaccination rate varied by age group and was significantly higher among adults aged >65 (78.04%) and significantly lower among children 9–17 years old (36.45%). Finally, we found a significant upward time trend in the overall influenza vaccination rate among whites (coef. = .0107; P = .027).
Conclusions. In conclusion, because of the significantly lower influenza vaccination rates in black and Hispanic communities, societal
initiatives and community outreach programs should focus on these populations and on children and adolescents aged 9–17 years. Keywords. acute respiratory illness; influenza; meta-analysis; systematic review; vaccination.
Influenza infections are a major cause of morbidity and mor-tality. The Centers for Disease Control and Prevention (CDC) has estimated that during the 2017–2018 season, there were 48.8 million influenza infections that resulted in 22.7 million am-bulatory health care visits, 959000 hospitalizations, and 79400 deaths [1]. Vaccination is widely considered to be the most cost-effective strategy against influenza infection [2]. Following the influenza A(H1N1)pdm09 pandemic, the CDC Advisory Committee on Immunization Practices (ACIP) expanded the existing guidelines and recommended universal annual vacci-nation in adults and children older than 6 months of age [3]. The CDC estimates that in the 2017–2018 season in the United
States, the vaccination rate was 37.1% for adults [4] and 57.9% for children 6 months to 18 years old [5]. However, vaccination rates have remained significantly lower than the Department of Health and Human Services goal, which has been set at 80% for healthy adults and 90% for high-risk adults and elderly individ-uals [6].
Given the expanded recommendations, population-wide assessments of vaccination rate and effectiveness have be-come important [7]. To estimate the vaccination rate for the US population, the CDC analyzes data from the Behavioral Risk Factor Surveillance System (BRFSS), a state-based pro-gram that uses telephone surveys to collect information on health conditions of randomly selected individuals [8]. Estimates following the influenza A(H1N1)pdm09 pan-demic ranged from a nadir of 37.1% in 2017–2018 to a peak of 43.6% in 2014–2015 [4]. Although this approach is likely to give an accurate estimate of the vaccination rate of the total US population, it might be less sensitive in reflecting the compliance of individuals in contact with the health care system [9]. Moreover, patients with comorbidities are at high risk for complications and are more likely to seek health care during a respiratory illness, making this population of
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particular interest regarding influenza vaccine uptake [10]. In this systematic review, we aim to assess the vaccination rate among patients who present to health care providers with influenza-like illness and identify subgroups with lower vaccination rates.
METHODS
We performed a systematic search of the PubMed and EMBASE databases from the implementation of the 2010 guidelines to March 1, 2019, to identify all studies reporting influenza vaccination status among patients seeking care for acute respiratory illness. We used the following search terms: (influenza OR flu) AND (vaccine OR vaccination) AND (respiratory illness OR respiratory infection). Titles and ab-stracts were screened independently by 2 authors (M.K., F.S.), and all relevant studies were accessed in full text. References of the studies that were eligible for inclusion were also re-viewed. As vaccination data and guidelines vary, only data from the Unites States were analyzed. This systematic review and meta-analysis was conducted according to the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines (Supplementary Table 1) [11].
Study Selection and Outcomes of Interest
Studies were considered eligible and included in our study if they reported extractable data on the rate of influenza vaccina-tion among patients with medically attended acute respiratory illness in the United States starting in the 2011–2012 season. Studies that did not provide data on influenza vaccination, grouped by race, gender, and age, and studies reporting only summary data from multiple influenza seasons were excluded. The primary outcome of interest was the cumulative annual in-fluenza vaccination rate of patients seeking care for acute respi-ratory illness. Subgroup estimates for age, gender, and race were examined. As a secondary outcome of interest, we performed a time trend analysis to identify differences in annual vaccination over time.
Data Extraction and Quality Assessment
Two authors (M.K. and F.S.) independently screened and evalu-ated eligible articles. Data from the eligible studies were ex-tracted by F.S. and T.K. Discrepancies were resolved by a third reviewer (M.K.) and consensus. The following information was extracted from each included study: influenza season, total number of vaccinated and unvaccinated subjects, number of vaccinated and unvaccinated subjects per race, number of vac-cinated and unvacvac-cinated subjects per gender, and number of vaccinated and unvaccinated subjects per age group.
The quality of the eligible studies was assessed independ-ently by 2 reviewers (F.S., M.K.) using the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies [12].
Data Synthesis and Analysis
We performed a random effects meta-analysis to estimate the pooled seasonal influenza vaccination rates, grouped by gender, age, and race, and their 95% confidence inter-vals using the DerSimonian and Laird approach [13]. The Freeman Tukey double arcsine transformation was utilized to stabilize the variances [14]. A random effects approach was chosen because we assumed that the effects were heteroge-neous due to differences in the study settings and the param-eters affecting vaccination each year. Heterogeneity between studies and subgroups was assessed using the I2 statistic [14],
and the Egger’s test was used to check for publication bias and small study effects.
A metaregression analysis was performed to model time trends using the first year of each influenza season as a contin-uous variable. Plots with prediction confidence intervals were produced to display and interpret the results of the time trend analysis. Stata, version 15.1 (Stata Corporation, College Station, TX, USA), was used for the statistical analysis. The significance threshold was set at .05.
RESULTS
Our systematic search yielded 1716 nonduplicate citations to evaluate. After title and abstract screening, 57 studies were identified as eligible for full-text review. Of these studies, 9 fulfilled our inclusion criteria and were included in our meta-analysis (Table 1). The detailed review process is shown in Supplementary Figure 1. The included studies provided data from 46462 patients and included data from the 2011–2012 through the 2018–2019 flu seasons, published from 2014 to 2019.
All included studies were prospective and multicenter. Eight studies included data from the US Flu Vaccine Effectiveness Network sites in MI, PA, TX, WA, WI [7, 15–17, 19, 21, 22]. One study included data from sites in NC, TN, TX, WI [18]. All the studies included visits to outpatient clinics only. Patients were enrolled if they presented with acute respira-tory illness and cough in 7 studies [15–17, 19, 21, 22], acute respiratory illness and fever in 1 study [18], and acute respi-ratory illness and cough or fever in 1 study [7]. Vaccination status was ascertained from medical records, vaccine regis-tries, and self-report (Table 1). No study was excluded due to quality concerns.
The proportion of vaccinated subjects seeking care for acute respiratory illness varied from 44.59% to 54.98% (Figure 1), and the overall pooled influenza vaccination rate was 48.61% (95% CI, 46.66%–50.56%). Egger’s test for publication bias de-tected no evidence of small-study effects (bias, 5.72; P = .413). The I2 statistic found considerable heterogeneity between the
studies (I2 = 94.3%; P < .001). When subgrouped by race, the
vaccination rate was significantly higher for whites (50.87%;
95% CI, 48.81%–52.94%), compared with blacks (36.05%; 95% CI, 33.20%–38.90%) and Hispanics (41.45%; 95% CI, 38.89%– 44.02%) (Figure 2).
Subgrouped by gender, the influenza vaccination rate pooled estimate varied, but the difference did not reach statistical sig-nificance and was 46.43% (95% CI, 44.37%–48.50%) for men
Table 1. Study Characteristics
Study Season Subjects, No. Age, Male, % Setting
Vaccination
Docu-mentation ARI Definition States McLean et al., 2015 [15] 2012–2013 6452 ≥6 mo, 41% Outpatient
clinics MR, VR, SR ARI and cough MI, PA, TX, WA, WI Ohmit et al., 2014 [7] 2011–2012 4771 ≥6 mo, 51% Outpatient
clinics MR, VR ARI and cough or fever MI, PA, TX, WA, WI Gaglani et al., 2016 [16] 2013–2014 5637 ≥6 mo, 42% Outpatient
clinics MR, VR, SR ARI and cough MI, PA, TX, WA, WI Zimmerman et al., 2016 [17] 2014–2015 9311 ≥6 mo, 42% Outpatient
clinics
MR, VR, SR ARI and cough MI, PA, TX, WA, WI McLean et al., 2017 [18] 2014–2015 1511 2–17 y, 50% Outpatient
clinics
MR, VR ARI and fever NC, TN, TX, WI Flannery et al., 2018 [19] 2017–2018
interim
4562 ≥6 mo, 41% Outpatient clinics
MR, VR, SR ARI and cough MI, PA, TX, WA, WI Rolfes et al., 2019 [20] 2017–2018 8436 ≥6 mo, 41% Outpatient
clinics
MR, VR, SR ARI and cough MI, PA, TX, WA, WI Flannery et al., 2018 [21] 2016–2017 7083 ≥6 mo, 42% Outpatient
clinics
MR, VR, SR ARI and cough MI, PA, TX, WA, WI Doyle et al., 2019 [22] 2018–2019 3254 ≥6 mo, 41% Outpatient
clinics MR, VR, SR ARI and cough MI, PA, TX, WA, WI
Abbreviations: ARI, acute respiratory illness; MR, medical records; SR, self-report; VR, vaccine registries.
Study Ohmit et al., 2014 McLean et al., 2015 Gaglani et al., 2016 Zimmerman et al., 2016 McLean et al., 2017 Flannery et al., 2018 Rolfes et al., 2019 Doyle et al., 2019 Overall (I2 = 94.3%, P = .000) 0 .434 .567
Influenza Vaccination Rate
ES (95% CI) 0.4303 (0.4462, 0.4745) 0.4459 (0.4338, 0.4581) 0.5017 (0.4886, 0.5147) 0.4683 (0.4581, 0.4784) 0.4851 (0.4600, 0.5103) 0.4929 (0.4813, 0.5046) 0.4876 (0.4769, 0.4982) 0.5498 (0.5326, 0.5668) 0.4861 (0.4666, 0.5056) 12.57 12.79 12.69 12.99 10.98 12.84 12.94 12.20 100.00 Weight %
Figure 1. Forest plot of included studies.
and 50.11% (95% CI, 47.95%–52.28%) for women (Figure 3). When subgrouped by age, the vaccination rate varied by age group and was significantly higher in the elderly population and significantly lower in children 9 to 17 years old, compared with adults 18 to 64 years old and children 6 months to 8 years old (Figure 4). In particular, the influenza vaccination rate was 49.48% (95% CI, 46.52%–52.44%) for children 6 months to 8 years old, 36.45% (95% CI, 34.54%–38.35%) for children and adolescents 9 to 17 years old, 44.30% (95% CI, 41.83%–46.76%) for adults 18 to 64 years old, and 78.04% (95% CI, 75.63%– 80.45%) for adults older than 65.
A metaregression analysis was performed to evaluate the time trend of influenza vaccination rate, yielding a significant upward trend in the overall influenza vaccination rate (coef. = .0097;
P = .030), as shown in Figure 5A. When subgrouping for race,
the vaccination rate of white populations followed a signifi-cant upward trend (coef. = .0107; P = .027) and a slight up-ward trend for black populations that did not reach significance (coef. = .0120; P = .057), while remaining significantly different for all flu seasons throughout the years studied (Figure 5B). The time trend analysis of the vaccination rate of Hispanics did not show a significant trend (P = .853).
When subgrouping by gender, time trend analysis yielded a significant upward trend for vaccination of women (coef. = .0113; P = .013) but did not show a significant trend for men (P = .210), and the trends were not statistically different, as evidenced by the overlap between their confidence intervals for all the flu seasons studied (Figure 5C).
Finally, when subgrouping by age (Figure 5D), time trend analysis yielded a slight upward trend for the 4 age groups
Study White Ohmit et al., 2014 0.4812 (0.4643, 0.4981) 4.50 4.53 4.52 4.55 4.27 4.53 4.54 4.45 0.4694 (0.4554, 0.4834) 0.5189 (0.5040, 0.5338) 0.4869 (0.4751, 0.4987) 0.5147 (0.4824, 0.5469) 0.5080 (0.4946, 0.5214) 0.5144 (0.5019, 0.5270) 0.5819 (0.5611, 0.6024) 0.5087 (0.4881, 0.5294) 0.4212 (0.3751, 0.4686) 0.3734 (0.3337, 0.4149) 0.4470 (0.4009, 0.4940) 0.3738 (0.3417, 0.4070) 0.4816 (0.4198, 0.5440) 35.88 3.96 4.10 3.96 4.26 3.57 0.4366 (0.3976, 0.4763) 4.12 0.3848 (0.3532, 0.4174) 4.27 0.4360 (0.3834, 0.4901) 3.79 0.4145 (0.3889, 0.4402) 0.3327 (0.2929, 0.3750) 0.3125 (0.2739, 0.3539) 32.03 4.09 4.11 0.3563 (0.3113, 0.4039) 3.97 0.3358 (0.3015, 0.3719) 4.21 0.3689 (0.3085, 0.4336) 3.56 0.4149 (0.3745, 0.4564) 4.09 0.3435 (0.3082, 0.3806) 4.19 0.4331 (0.3842, 0.4832) 3.89 0.3605 (0.3320, 0.3890) 0.4325(0.4074, 0.4576)
Influenza Vaccination Rate
32.09 100.00 McLean et al., 2015 Gaglani et al., 2016 Zimmerman et al., 2016 McLean et al., 2017 Flannery et al., 2018 Rolfes et al., 2018 Doyle et al., 2019 Subtotal (I2 = 93.0%, P = .0000) Hispanic Ohmit et al., 2014 MeLean et al, 2015 Gaglani et al., 2016 Zimmerman et al., 2016 McLean et al., 2017 Flannery et al., 2018 Rolfes et al., 2018 Doyle et al., 2019 Subtotal (I2 = 65.5%, P = .0049) Ohmit et al., 2014 MeLean et al, 2015 Gaglani et al., 2016 Zimmerman et al., 2016 McLean et al., 2017 Flannery et al., 2018 Rolfes et al., 2018 Doyle et al., 2019 Subtotal (I2 = 71.7%, P = .0009) Heterogeneity between groups: P = .000 Overall (I2 = 96.0024%, P = .0000)
0 .274 .602
Black
ES (95% CI) Weight%
Figure 2. Forest plot of included studies stratified by race.
examined. The trend was significant for adults 18 to 64 years old (coef. = .0107; P = .034) but did not reach statistical significance for children 6 months to 8 years old (coef. = .0024; P = .749), children and adolescents 9 to 17 years old (coef. = .0039;
P = .429), or adults older than 65 (coef. = .0999; P = .71). DISCUSSION
We systematically assessed the vaccination rate among indi-viduals who presented to an outpatient clinic seeking medical care for acute respiratory illness after the expanded recom-mendations for universal immunization in adults and children older than 6 months of age. We found a low cumulative vac-cination rate of 48.61% among medically attended patients with acute respiratory illness. Although a significant upward trend over time was observed for white populations, there was no time trend observed for black or Hispanic populations and
vaccination coverage remained low. Furthermore, there were significant differences among demographic groups, with a sig-nificantly higher vaccination rate in elderly patients aged >65, compared with children and young adults, as well as among white individuals compared with blacks and Hispanics.
The cumulative vaccination rate of almost 50% that we found among all patients who presented for an ambulatory health care visit for acute respiratory illness on or after the 2011–2012 season is higher than the CDC overall estimates for the same time period, which range from a nadir of 37.1% in 2017–2018 [4] to a peak of 43.6% in 2014–2015 [23]. The observed higher vaccination compliance among the patient subgroup that pre-sented for evaluation to the health care system could be sec-ondary to the overrepresentation of patients who were at higher risk of developing influenza-related complications in our anal-ysis [10]. Differences in sampling methods could also have con-tributed to the higher vaccination rate observed in our analysis.
Study % ES (95% CI) Weight Female Mele Ohmit et al., 2014 0.4660 (0.4459, 0.4862) 0.4547 (0.4349, 0.4746) 0.4702 (0.4544, 0.4861) 0.5168 (0.4997, 0.5339) 0.4766 (0.4633, 0.4900) 0.4762 (0.4408, 0.5118) 0.5214 (0.5061, 0.5367) 0.5137 (0.4999, 0.5276) 0.5655 (0.5432, 0.5875) 0.5011 (0.4795, 0.5228) 6.43 6.58 5.39 6.50 6.56 6.18 50.40 6.30 0.4111 (0.3925, 0.4299) 6.36 0.4808 (0.4607, 0.5009) 0.4568 (0.4413, 0.4724) 0.4940 (0.4585, 0.5296) 0.4541 (0.4364, 0.4720) 0.4498 (0.4332, 0.4664) 0.5269 (0.5001, 0.5536) 0.4643 (0.4437, 0.4850) 0.4831 (0.4651, 0.5011) 6.29 6.49 5.38 6.40 6.45 5.93 49.60 100.00 6.29 6.48 Ohmit et al., 2014 McLean et al., 2015 Gaglani et al., 2016 Zimmerman et al,, 2016 McLean et al., 2017 Flannery et al., 2018 Rolfes et al., 2019 Doyle et al., 2019 Subtotal (I2 = 91.9%, P = .0000)
Heterogeneity between groups: P = .016
Overall (I2 = 93.4397%, P = .0000);
0 .392 .588
Influenza Vaccination Rate McLean et al., 2015 Gaglani et al., 2016 Zimmerman et al,, 2016 McLean et al., 2017 Flannery et al., 2018 Rolfes et al., 2019 Doyle et al., 2019 Subtotal (I2 = 88.3%, P = .0000)
Figure 3. Forest plot of included studies stratified by gender.
The CDC analyzes data from the Behavioral Risk Factor Surveillance System, which is a state-based telephone survey that has been collecting information on health conditions and risk behaviors since 1984 [8]. As response to the telephone sur-veys is voluntary, selection bias may have been introduced from a high nonresponse rate in BRFSS surveys, which was >50% for the 2017–2018 season [24]. Indeed, a study that compared the BRFSS national estimates to the National Health Interview Survey (NHIS), which is conducted by the National Center for Health Statistics of the Centers for Disease Control and Prevention through a personal household interview, showed that BRFSS estimates for influenza immunization were 2.3% lower than the NHIS estimates [25]. Also, unlike studies in-cluded in the present analysis, the majority of which verified self-reporting of influenza vaccination status with medical
record data, BRFSS vaccination rates are based on patient re-call. Studies have estimated that while the sensitivity of self-reporting is high, there is low specificity [26] and therefore BRFSS data might underestimate the influenza vaccination rate.
Unlike CDC estimates that the influenza vaccination rate has remained stable over the last 10 years, we detected a significant upward trend over time. This could again be secondary to the facts that the patient population of our study is more likely to have come in contact with the health care system and the inten-sified efforts to increase vaccination compliance in this patient subgroup over time. On the other hand, based on the NHIS survey in 2017, almost 40% of adults aged 18–44 years reported that they had not had contact with a health care provider in the last ≥6 months [27]. More importantly, based on a Kaiser Family Foundation analysis of the BRFSS 2015–2017 Survey
6 mo-8 y Study ES (95% CI) 0.5295 (0.5041. 0.5548) 3.58 3.55 3.57 3.54 3.58 3.57 3.54 3.47 24.82 3.59 3.60 3.60 3.60 3.60 3.60 3.59 25.18 3.52 3.56 3.57 3.58 3.58 3.59 3.56 24.96 100.00 3.58 3.57 3.59 3.58 3.57 3.56 25.04 0.4467 (0.4217. 0.4718) 0.5102 (0.4810, 0.5393) 0.4924 (0.4725, 0.5123) 0.4423 (0.4175, 0.4673) 0.4872 (0.4578, 0.5168) 0.5613 (0.5269, 0.5952) 0.4948 (0.4652, 0.5244) 0.3453 (0.3102, 0.3823) 0.3344 (0.3055, 0.3645 0.4000 (0.3623, 0.4389) 0.3770 (0.3515, 0.4033) 0.3600 (0.3310, 0.3901) 0.3469 (0.3096, 0.3863) 0.4110 (0.3560, 0.4682) 0.3645 (0.3454, 0.3835) 0.3996 (0.3795, 0.4201) 0.7448 (0.6989, 0.7858) 0.7313 (0.6961, 0.7638) 0.8106 (0.7780, 0.8394) 0.7595 (0.7346, 0.7828) 0.7885 (0.7625, 0.8124) 0.7867 (0.7622, 0.8093) 0.8355 (0.7990, 0.8665) 0.7804 (0.7563, 0.8045) 0.5215 (0.4695, 0.5736)
Influenza Vaccination Rate
0.4221 (0.4054, 0.4390) 0.4593 (0.4422, 0.4764) 0.4670 (0.4506, 0.4835) 0.4623 (0.4476, 0.4771) 0.4903 (0.4665, 0.5141) 0.4430 (0.4183, 0.4676) 0.4022 (0.3877, 0.4168) % Weight 9–17 y 18–64 y Over 65 McLean et al., 2015 Ohmit et al., 2014 Gaglani et al., 2016 Zimmerman et al., 2016 Flannery et al., 2018 Flannery et al., 2018 Doyle et al., 2019 McLean et al., 2015 Ohmit et al., 2014 Gaglani et al., 2016 Zimmerman et al., 2016 Flannery et al., 2018 Flannery et al., 2018 Doyle et al., 2019 McLean et al., 2015 Ohmit et al., 2014 Gaglani et al., 2016 Zimmerman et al., 2016 Flannery et al., 2018 Rolfes et al., 2019 Subtotal (I2 = 93.1 %, P = .000) Subtotal (I2 = 78.6%, P = .0001)
Heterogeneity between groups: P = .000 Overall (I2 = 99.2335%, P = .000); 0 .306 .867 Doyle et al., 2019 McLean et al., 2015 Ohmit et al., 2014 Gaglani et al., 2016 Zimmerman et al., 2016 Flannery et al., 2018 Rolfes et al., 2019 Doyle et al., 2019 Subtotal (I2 = 88.8%, P = .0000) Subtotal (I2 = 52.8%, P = .0479)
Figure 4. Forest plot of included studies stratified by age.
Results, 28% of men and 17% of women do not have a primary care provider [28]. Taken together with the absence of societal initiatives and community outreach to increase vaccine uptake [29], surveys on the vaccination compliance of the general pop-ulation might not be able to detect coverage increases in high-risk patient subgroups.
Despite the upward trend in our analysis, vaccination rates remain low overall. Identifying specific factors that play a role in an individual’s decision to receive vaccination is an important step toward tailored interventions. Two previous literature re-views that included >500 studies examined the potential factors behind vaccine hesitancy and found that factors such as low dis-ease risk perception, high perceived risk of vaccine side effects, negative past experience, personal attitudes, lack of knowledge, and perceived behavioral control may negatively impact influ-enza vaccine uptake among individuals [30, 31]. Furthermore, vaccine uptake has been associated with socioeconomic factors and education level [32]. In general, the reasons behind vaccine hesitancy can be summarized by the 4C model: Complacency, lack of Convenience, lack of Confidence, and Calculation (ie, vaccination risks outweigh potential benefits) [33]. On the
other hand, the feeling of social benefit, a history of previous vaccination, the presence of social pressure, a direct recommen-dation from medical personnel, and interaction with the health care system may play a positive role toward vaccine uptake [31]. Finally, although the impact of the few existing strategies to address vaccine hesitancy is not well established to date, strat-egies that have multiple components, are dialogue-based, and address specific patients’ concerns or doubts tend to perform better [31, 34].
In agreement with BRFSS data [4] and data from Medicare beneficiaries [35], we observed racial disparities, with whites having a higher vaccination rate than Hispanics and blacks. The above observation is likely multifactorial and might be par-tially explained by differences in socioeconomic status and ac-cess to care [35, 36]. In addition, ethnic minorities might be more prone to missing opportunities to vaccinate during med-ical visits [37]. Of note, while we observed an increase in vac-cination rate among white populations, it is worrisome that the vaccination rate among black and Hispanic populations has re-mained relatively stable and low. Interestingly, when Chen et al. [38] examined the main barriers to vaccination among different
.55 .6 1 .8 .6 .4 .2 .55 .5 .45 .4 .6 .5 .4 .3 .2
Influenza vaccination rate
Influenza vaccination rate
Influenza vaccination rate
Influenza vaccination rate
.5 .45 .4 2011 A C D B 2012 2013
Prediction interval Influenza vaccination rate
White Prediction interval
6 mo-8 y Prediction interval 9–17 y prediction interval Over 65 Prediction interval 9–17 y
Over 65 18–64 y prediction interval
6 mo–8 y 18–64 y Male Prediction interval
Male
Black Prediction interval White
Hispanic Hispanic Prediction interval
Female prediction interval Female Black 2014 2015 2016 2017 2018 2011 2012 2013 2014 2015 2016 2017 2018 2011 2012 2013 2014 2015 2016 2017 2018 2011 2012 2013 2014 2015 2016 2017 2018
Figure 5. Time trend analysis of the influenza vaccination rate (A) overall, (B) stratified by race, (C) stratified by gender, and (D) stratified by age.
ethnic groups, they found that Hispanics were more likely to report access and cost as vaccination barriers, while black in-dividuals were more likely to raise issues of mistrust against influenza vaccine. In this regard, public policies should be tai-lored to address specific minority barriers, and future studies should examine initiatives to increase vaccine uptake in these populations.
The limitations of this study include that the published studies are not representative of the entire US population and some states are not represented in the studies included in our analysis, while certain medical sites are overrepresented. Furthermore, data on some of the subgroups were missing in some studies, while there were sites in the included studies that did not verify immunization status by medical records.
CONCLUSIONS
We examined the vaccination rate among individuals who sought care for acute respiratory illness in the United States, and almost half were vaccinated. While significantly lower than the goal of 80% to 90% for 2020, the calculated vacci-nation rate was higher and with an increasing trend, com-pared with that reported by nationwide surveys. However, racial and age disparities were detected, with lower influ-enza vaccination rates among black and Hispanic popula-tions and among children and adolescents aged 9–17 years. The analysis identifies subgroups with lower immunization compliance that should be targeted by societal initiatives and community outreach programs.
Supplementary Data
Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
Acknowledgments
Financial support. The authors received no financial support for the re-search, authorship, and/or publication of this article.
Potential conflicts of interest. Dr. Mylonakis has received grant sup-port from T2 Biosystems, Sanofi-Aventis, Kaleido Biosciences, and Cidara Therapeutics. Mr. van Aalst and Dr. Chit report having been employees of Sanofi-Pasteur during the conduct of the study. The rest of the authors have disclosed no conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the edi-tors consider relevant to the content of the manuscript have been disclosed. Author contributions. F.S., I.M.Z., M.K., E.K.M., T.K., R.v.A., A.C., and E.M. contributed to the study concept and design. F.S., M.K., and T.K. per-formed the literature search and data extraction. F.S. and E.K.M. perT.K. per-formed the statistical analysis. All authors were involved in data analysis or review and manuscript preparation. F.S. is the guarantor and takes responsibility for the integrity of the data and the accuracy of the data analysis.
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