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Background:
Systematic Review

Influenza and Pertussis Vaccination During Pregnancy: A Systematic Review of Vaccination Rates and Vaccination Determinants

by
Panagiota Georgia Maltezou
1,*,
Maria Eleni Papakonstantinou
1,
Eleni Kourkouni
2,
Dimitra Kousi
2,
Christos Hadjichristodoulou
3,
Despoina Briana
1 and
Vasiliki Papaevangelou
1
1
Third Department of Pediatrics, University Hospital Attikon, 124 62 Athens, Greece
2
Center for Clinical Epidemiology and Outcomes Research (CLEO), 154 51 Athens, Greece
3
Laboratory of Hygiene and Epidemiology, University of Thessaly, 382 21 Larissa, Greece
*
Author to whom correspondence should be addressed.
Vaccines 2026, 14(4), 325; https://doi.org/10.3390/vaccines14040325
Submission received: 25 February 2026 / Revised: 29 March 2026 / Accepted: 3 April 2026 / Published: 6 April 2026
(This article belongs to the Special Issue Vaccination in Pregnancy and Early Life: Evidence, Challenges, and Innovations)
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Abstract

Background: Pertussis and influenza immunization during pregnancy protects both mother and infant through transplacental transfer of antibodies. However, global vaccination coverage among pregnant women remains suboptimal. Aim: This systematic review aimed to assess influenza and pertussis vaccination coverage during pregnancy and identify determinants influencing vaccine uptake. Methods: A systematic search of MEDLINE, SCOPUS, and grey literature was conducted for studies published between 2000 and 2023. Studies reporting actual vaccination rates for influenza and/or pertussis among pregnant women were included, while those assessing only willingness were excluded. Studies on H1N1 pandemic vaccination in pregnant women were excluded to avoid bias, as awareness levels during the pandemic differed from routine influenza vaccination. Determinants of vaccine acceptance were recorded. Study quality was evaluated using the Newcastle–Ottawa Scale. Results: Of 3251 identified records, 78 studies on influenza (N1 = 287,124 participants) and 51 on pertussis (N2 = 172,801) met inclusion criteria after removing overlapping populations. Most influenza studies (55/78) reported vaccination coverage below 50%. A key determinant of influenza vaccination uptake was physician recommendation, while maternal attitudes, parity, and previous influenza vaccination also had a significant impact. For pertussis, vaccination coverage was primarily driven by physician recommendation, with parity and maternal perceptions of vaccine safety and effectiveness further influencing uptake. Regarding quality assessment, 52.5% of influenza studies and 37.5% of pertussis studies scored above 6 on the Newcastle–Ottawa Scale. Conclusions: Maternal vaccination coverage for influenza and pertussis remains inadequate worldwide and is shaped by national strategies, healthcare provider practices, and maternal perceptions. Addressing vaccine hesitancy and improving awareness are essential to increase uptake.

1. Introduction

Vaccination during pregnancy is an important public health tool for preventing infections among pregnant women, their fetuses, and infants during the first months of life [1]. Antibodies induced by vaccination during pregnancy are actively transmitted through the placenta to the fetus and by breast milk to the infant. Thus, both the fetus and newborn later are protected from life-threatening diseases during the first months of life, when both cellular and humoral immunity are weak and infant immunization has not yet started [2].
The Advisory Committee on Immunization Practices (ACIP) recommends that all pregnant women should be vaccinated with the inactivated influenza vaccine and pertussis vaccine (combined with diphtheria toxin) [3]. Currently, similar recommendations have been made by the respective vaccination committees in many other countries such as the United Kingdom (since 2010), Belgium, Germany, and Greece [4].
The World Health Organization (WHO) recommendations on maternal immunization have played a pivotal role in shaping influenza and pertussis vaccination coverage over time. Following the prioritization of pregnant women for influenza vaccination in 2012 and the endorsement of maternal pertussis immunization in 2015, several countries adopted or strengthened national recommendations, leading to notable increases in vaccine uptake. Since 2012, studies—especially from high-income countries—have reported markedly higher maternal vaccination coverage, although the magnitude of improvement depends on the strength and implementation of national recommendations [5,6,7,8]. However, the impact of these global guidelines appears to depend on their translation into country-specific policies, as variations in timing, implementation, and integration into antenatal care have resulted in substantial differences in coverage between settings. Overall, both international guidance and national-level recommendations are key determinants of maternal vaccination trends, which have shown a general increase over time [5,6,7,8].
After the COVID-19 pandemic, vaccination against SARS-CoV-2 was added to the maternal immunization schedule, while maternal vaccination against Respiratory Syncytial Virus (RSV) during weeks 32 through 36 of pregnancy has been recently established in many countries [9,10]. The COVID-19 pandemic appears to have had a mixed impact on maternal vaccination coverage. While increased awareness of infectious diseases and vaccination may have contributed to improved uptake in some settings, multiple studies report disruptions in routine healthcare services and reduced access to antenatal care, leading to declines or stagnation in influenza and pertussis vaccination coverage in others. Overall, the evidence suggests that the pandemic introduced both opportunities and setbacks, with its net effect varying across countries depending on healthcare system resilience and public health response [11,12].
Despite scientific evidence confirming the major benefit of vaccinations during pregnancy, epidemiological studies show that pregnant women have poor immunization coverage, even in countries where explicit immunization guidelines for pregnant women exist [1]. This may be attributed to maternal concerns regarding the safety of vaccination during pregnancy, inadequate awareness of vaccine efficacy and the disease burden associated with the respective infections, limited vaccine availability, and insufficient information provided by healthcare professionals [13,14]. Worldwide studies have tried to document pregnant women’s knowledge, attitudes, and practices regarding prenatal vaccination. Most studies show that pregnant women have low vaccination coverage against influenza and pertussis, primarily due to insufficient information from the healthcare provider (HCP) and concerns regarding adverse events [15,16,17,18].
Conducting a systematic review and critical appraisal of relevant data—including vaccination coverage and the determinants of vaccine uptake—can provide valuable insights into the current state of maternal immunization. Such an analysis enables the identification of gaps in coverage, highlights key factors influencing vaccine acceptance, and underscores disparities across different populations or regions. By offering a comprehensive understanding of these issues, the review can support evidence-based decision making and guide the formulation of targeted interventions. Ultimately, these findings may contribute to the development of effective strategies aiming at increasing vaccination coverage and improving maternal and neonatal health outcomes.

2. Materials and Methods

The systematic review was conducted according to PRISMA 2020 guidelines [19] (Table S1). The PROSPERO database was searched by the reviewers to make sure that no other research group was working on a systematic review of the subject. PROSPERO received the protocol along with the Prospero registration number, CRD42024605576. Two reviewers (PGM and MEP) independently and blindly conducted a systematic literature search of the MEDLINE and Google scholar databases using an assortment of associated key terms such as “vaccination”, “immunization”, “influenza”, “flu”, “pertussis”, “whooping cough”, “pregnancy”, “pregnant women”. The search query used in Pubmed Medline database was: ((vaccin*[Title/Abstract] OR immuni*[Title/Abstract]) AND (pregnan*[Title/Abstract] OR prenatal*[Title/Abstract])) AND (pertussis [Title/Abstract] OR Bordetella [Title/Abstract] OR “bordetella pertussis” [Title/Abstract] OR flu [Title/Abstract] OR influenza [Title/Abstract]) (File S1). In addition, using a “snowball procedure”, reference lists from all relevant reviews and identified eligible studies, as well as Google Scholar, were manually searched for potentially eligible articles. The grey literature and other relevant articles were identified in this manner. Articles written in English, referring to humans and published between January 2000 and December 2023 and documenting vaccination coverage during pregnancy for either influenza, pertussis or both were included in the analysis. The year 2000 was selected as the lower date limit for this review. The World Health Organization (WHO) and national health agencies began expanding their guidance on maternal immunization, while influenza and pertussis vaccination recommendations for pregnant individuals were significantly revised in 2012 and 2015, respectively [20]. Tracking vaccination rates over the past decade as well could provide a clearer depiction of coverage trends. On the other hand, articles recording influenza or pertussis vaccine uptake during the postpartum period, articles recording solely H1N1 vaccine coverage and articles recording only willingness of vaccination were excluded from the systematic review.
The selection of studies was completed in two stages. First, the titles and/or abstracts of the identified studies were assessed, and those that clearly did not relate to the purpose of the review or did not meet the selection criteria were removed. For further screening of the remaining studies, complete papers were retrieved. Duplicate citations were eliminated after the literature review, and two investigators (PGM and MEP) independently examined the remaining papers to find those that satisfied the pre-established inclusion requirements. Team consensus was used to reach a final decision, in the event of disagreement during the study selection or snowball procedure. If more than one article was discovered with overlapping study populations, the most recent or comprehensive publication was considered eligible. The studies included in the systematic review were assessed using the Newcastle–Ottawa Scale adapted for cross-sectional studies by two reviewers.

Data Analysis

The study variables of publication year, location, study design, study period, number of mothers or pregnant women involved in the study, and vaccination rate for each vaccine (pertussis and influenza) were extracted from each eligible publication by two reviewers (PGM and MEP). Furthermore, potential factors impacting vaccination rates that were examined by each research team were recorded for all eligible studies. A systematic review regarding vaccination rates and main factors involved in vaccine acceptance was conducted. Moreover, an attempt was made to correlate vaccination rates with different vaccination programs and maternal vaccination recommendations. However, we could not perform a meta-analysis, a fact attributed mainly to the wide variety of statistical analysis and results interpretation methods used in the eligible studies. Missing data in each of the eligible studies were marked as “not available (NA)” and were not included in the systematic review or the qualitative synthesis of the articles.

3. Results

A total of 3251 articles were reviewed for both influenza and pertussis immunization. Out of these, 2801 records were excluded based on Title or Abstract (Figure 1).
The survey conducted by Specker et al. was excluded as vaccination rate—the primary outcome of our review—was not reported [21]. Kay et al. recorded the flu vaccine uptake peripartum and concluded that 76.9% of the responders had been vaccinated during pregnancy or during the first 2 weeks postpartum. However, since our primary outcome refers to prenatal vaccine uptake, this study was excluded from the final review [22]. Similarly, Bettinger et al. recorded both prenatal and postnatal maternal vaccination rates, namely 45.7% in total, a fact that disqualified their study from being included in our review [23]. After the additional exclusion of influenza and pertussis studies with overlapping populations, 78 and 51 articles, respectively were identified as suitable to be included in the analysis (Figure 1). Risk of bias was assessed using the Newcastle–Ottawa Assessment Scale adapted for cross-sectional studies. Most of the studies reviewed received a score ranging from 6 to 8 points. Points were deducted mainly because of low response rates, lack of multivariable analysis, or due to the use of non-validated screening tools. Studies scoring below 4 points were primarily qualitative studies and interviews that did not quantify and analyze their results using statistics.

3.1. Influenza Vaccination During Pregnancy

The detailed characteristics of the 78 eligible studies are depicted in Table 1. The vast majority (77/78, 98.7%) reported findings from cross-sectional studies conducted through either self-completed questionnaires or interviews. Bartolo et al., Descamps et al. and Schlaudecker et al. recorded responses from questionnaires and confirmed data from medical files as well [16,24,25]. Most studies were conducted in the United States (USA) (n = 13), while 18 studies were conducted in low- and middle-income countries. The studies recorded immunization rate from a total of 287,124 pregnant women or new mothers. In addition to vaccination, willingness for immunization was recorded in 14 studies. In 11 studies, separate recordings for seasonal and H1N1 influenza vaccinations were conducted, and the respective data were available. Studies focusing on the H1N1 pandemic and the vaccination of pregnant women with the corresponding vaccine were excluded from the systematic review, as the degree of awareness differed and would introduce bias in the qualitative assessment of the results.
In 37 studies, the vaccination rate against influenza recorded was between 0% to 30%, while 17 surveys concluded that 30–50% of the responders had been vaccinated against flu. In 16 studies, the vaccination rate recorded was 50–70% and 7 studies concluded in a vaccination uptake higher than 70%. Ahluwalia et al. recorded vaccination rates in two different USA regions (Georgia: 18.4% and Rhode Island: 31.9%). The highest vaccination rate, namely 81%, was found in two studies conducted in the USA. The first one was a survey that was carried out by Goldfarb et al. between January and March of 2010, while the second one tracked pregnant women’s vaccination rates from October 2010 to June 2011 [88,90].
Influenza vaccination coverage during pregnancy varied widely across and within country income groups. Higher uptake was generally observed in high-income countries, with rates often exceeding 50% in settings such as Australia, the United States, and the United Kingdom. However, substantial heterogeneity was noted, as some high-income countries (e.g., Italy and France) reported consistently low coverage. Upper- and lower-middle-income countries showed highly variable estimates, ranging from near zero to moderate levels [98]. Overall, these findings suggest that while country income influences vaccination uptake, it does not fully account for the observed differences, indicating a key role for national policies and healthcare system factors.
Vaccination coverage increased over time, with studies conducted before 2010 reporting consistently low uptake. A notable rise was observed following the 2009 H1N1 pandemic and the World Health Organization’s recommendation to prioritize pregnant women for influenza vaccination around 2012. Post-2012 studies, particularly in high-income countries, showed substantially higher coverage rates. Although the introduction of national recommendations was generally associated with improved uptake, the extent of this increase varied across countries, with persistently low coverage in settings where implementation was limited [99].
Most countries introduced recommendations for influenza vaccination during pregnancy between 2009 and 2012, following the H1N1 pandemic and WHO prioritization. In the included studies, higher vaccination coverage was generally observed in settings where national recommendations were implemented earlier and more effectively, whereas countries with delayed or limited adoption showed persistently low uptake. Additionally, higher vaccination rates were observed in studies that had been conducted after the implementation of influenza vaccine uptake during pregnancy.
Post-COVID-19 studies indicate that vaccination uptake during pregnancy varies considerably across countries, without a consistent global trend. High-income countries (e.g., Australia, USA, UK) generally show moderate to high coverage with gradual improvement over time, whereas several European countries maintain lower rates, and some low- and middle-income settings report minimal uptake. The pandemic appears to have had a mixed impact: while increased awareness of infectious diseases may have supported vaccine acceptance in some populations, many studies report persistent or increased vaccine hesitancy among pregnant women, mainly due to safety concerns and mistrust. Overall, COVID-19 did not uniformly increase maternal vaccination coverage but rather highlighted existing disparities among countries.

Determinants Affecting Influenza Vaccination

The four main factors that seem to affect vaccine uptake were doctor’s recommendation, maternal positive views regarding influenza vaccine, number of children, and previous influenza immunization. Table 2 depicts the eligible studies that documented these main associations.
Table 3 presents the studies that recorded a statistically significant association between healthcare practiioner’s (HCP’s) recommendation and vaccine uptake.
Expectant mothers’ positive attitude towards influenza vaccination was also correlated with higher vaccination rates in 19 studies (Table 2). Table 4 depicts the statistically significant associations found in eligible studies, as well as the statistical method used.
In 11 studies, parity was examined as a potential determinant of maternal influenza (Table 2). In seven studies, the correlation was proved statistically significant (Table 5). However, the results were contradictory. Namely, in four studies, nulliparity statistically significantly favored influenza vaccination [16,24,39,85], while a statistically significant higher vaccine uptake was clearly recorded in multiparous mothers in two studies [17,64].
Prior vaccination was a main determinant of influenza vaccine uptake in 13 studies. In six studies, the association was proved statistically significant (Table 6).
Regarding Newcastle–Ottawa Scale adapted for cross-sectional studies, the mean score for the eligible studies was 6.18 (Table S2).

3.2. Pertussis Vaccination During Pregnancy

Overall, 51 studies on pertussis vaccination during pregnancy were qualified for the systematic review (Table 7). All studies were cross-sectional. In two studies, medical records were used additionally [56,100], while in the study conducted by Kharbanda et al., data regarding study population’s vaccination status was retrieved from the vaccine safety datalink [101]. From the eligible studies, 18 studies were conducted in Europe, while 14 studies were conducted in the USA. Six studies were conducted in low- and middle-income countries. In total, eligible studies included 172,801 women, either pregnant or new mothers, for whom vaccine uptake during pregnancy was recorded. The largest study detected through the literature review was conducted by Butler et al. and published in 2017 (N = 1,147,711) [102]. However, the study had been excluded during the initial steps, due to a high risk of population overlap with other studies conducted in the USA.
The highest vaccination rate, namely 100%, was recorded in the study of Larson Williams et al. conducted in Zambia in 2016 and including 27 women [126]. Notably, in seven studies, authors tried to record the maternal immunization rate as well as the respective willingness of vaccine uptake. In nine studies, the pertussis maternal vaccination rate was less than 30%. In 13 studies, the proportion of vaccinated responders ranged between 30% and 50%, while in 14 studies, the pertussis vaccine uptake was 50–70%. In 14 studies, more than 70% of the participants stated that they had the pertussis vaccine during their pregnancy. In the study conducted by Ben Natan et al. in Israel from January to March 2016, the vaccination rates for native-born women and women derived from the former Soviet Union were 52% and 31%, respectively [108].
Pertussis vaccination coverage during pregnancy varied across income groups. High-income countries generally showed higher uptake, with rates often exceeding 60% in recent studies, although early uptake was lower in some settings (e.g., UK 26% in 2013–2014). Upper-middle-income countries exhibited more variability (Turkey 11–47%, Mexico 74%), while limited data from lower-middle income countries (Zambia) showed very high coverage in targeted programs. These findings indicate that both country income and national policy implementation influence vaccination coverage.
Coverage increased over time in most countries, particularly after the introduction of national recommendations for pertussis vaccination in pregnancy (generally post-2011–2012 following WHO guidance). Strong, well-integrated programs (e.g., Australia, USA, UK) showed substantial improvements, whereas countries with delayed or partial implementation had persistently lower coverage. These results highlight the importance of policy adoption and program integration in achieving high vaccination uptake.

Determinants Affecting Pertussis Vaccination

Factors primarily influencing the acceptance of pertussis vaccination were also noted. Doctor’s recommendation, mother’s perception on safety and effectiveness of the vaccine, and parity were main factors that guided maternal immunization (Table 8).
In 20 studies, healthcare provider’s recommendation was declared as an important determinant of pertussis maternal immunization (Table 8). The statistical approach and the respective analysis widely varied. In Table 9, the 14 eligible studies in which statistically significant correlations between HCP’s recommendation and vaccine uptake were recorded are demonstrated.
In six studies, concerns about vaccine safety were stated as an important factor discouraging vaccination (Table 8). However, not all the research teams quantified this association. In three studies, this correlation was proved statistically significant. In five eligible studies, the association between vaccine uptake and pregnant women’s perceptions regarding possible benefits of the antenatal vaccine administration was highlighted. Table 10 and Table 11 depict the statistically significant associations.
Parity was identified as a significant determinant of vaccine acceptance in eight studies (Table 8). In three studies, nulliparous mothers were more likely to get vaccinated when compared to multiparous (Table 12).
Regarding the Newcastle–Ottawa Scale adapted for cross-sectional studies, the mean score of the eligible studies was calculated at 6.13 (Table S3).

4. Discussion

Despite the difficulties in synthesizing a vast and diverse body of literature, we have recorded the maternal vaccination rates against influenza and pertussis in many countries worldwide. Additionally, we have estimated the role that several specific beliefs and behaviors play in maternal vaccination. Data from different countries worldwide were combined taking into consideration diverse health systems, immunization strategies, and populations’ perceptions. This systematic review concerns a wide time frame from 2000 till 2023, while the previous respective systematic review published was limited to studies published by November 2018 [127]. Data extracted from CDC recordings has not been used due to the high risk of overlapping populations with studies conducted in the USA. However, the influenza vaccination rates published by the CDC ranged from 40.4% to 50.7% and are equivalent to rates recorded in individual cross-sectional studies from the USA [3,128,129,130,131,132]. It was not possible for a meta-analysis [6] to be performed, since statistical analysis methods had a high heterogeneity and the studies’ methodologies widely differed. Regarding quality assessment, 52.5% of studies concerning influenza vaccine and 37.5% of studies concerning pertussis vaccine scored higher than 6 in the Newcastle–Ottawa Quality Assessment Scale.
In this systematic review, HCPs’ and mothers’ perceptions on vaccine safety and efficacy seem to have a crucial contribution to expectant mothers’ decisions to get vaccinated or not. This finding is also strongly related to each country’s healthcare system and to the HCP who is responsible for pregnant women’s health and follow-up. Only a limited number of studies identified concerns about vaccine adverse events as a key factor influencing maternal vaccination uptake; however, this finding should be interpreted in the context of the historical delay in introducing the Tdap vaccine during pregnancy, which was largely driven by safety concerns for both mothers and infants. Notably, the World Health Organization recommended maternal Tdap vaccination only in 2015, following accumulating evidence demonstrating its safety and effectiveness, while more recent post-COVID-19 studies suggest that vaccine hesitancy related to safety concerns has become increasingly prominent again [6].
Regarding influenza maternal immunization, the lowest rate (0%) was recorded in a study conducted in India during the flu season 2012–2013 [55]. Due to insufficient safety evidence for pregnant Indian women, the influenza vaccine has not yet been made available through immunization programs in India [133]. The highest influenza vaccination rates, reaching 81%, were reported in two U.S. studies conducted immediately following the 2009 H1N1 pandemic—one by Goldfarb et al. from January to March 2010 and another tracking pregnant women from October 2010 to June 2011—which aligns with evidence that the H1N1 pandemic heightened awareness and acceptance of influenza vaccines among pregnant populations [89,90,134]. The respective recommendations from the Advisory Committee on Immunization Practices are strong and prioritize pregnant women as a high-risk group [135,136].
In the present systematic review, the lowest pertussis vaccine uptake recorded in Australia was reported in a study conducted from 2012–2013 [29]. Pregnant women have been gradually enrolled in funded pertussis immunization programs across all Australian states and territories from August 2014 to June 2015, much later than the period the study had recorded. Some of these programs had implemented cocooning strategies as well [137]. The high immunization rate recorded in the study conducted in Zambia may be attributed to the high awareness of infectious diseases in developing countries, the small number of participants, and to the organized funded vaccination strategies imposed in these areas [126]. Our analysis of pertussis vaccination coverage in pregnancy highlights the critical role of national recommendations and program implementation. Countries that introduced formal recommendations earlier (e.g., USA 2011, UK 2012, Belgium 2013–2014, Australia 2015) generally showed higher uptake over time. However, coverage varies widely depending on whether the vaccine was fully integrated into antenatal care and provided free of charge. High-income countries with strong policy support and cost coverage (e.g., Australia, USA, UK, New Zealand) reached coverage often above 70–80%, while countries with partial implementation or out-of-pocket costs (e.g., Turkey, Italy, some regions of Belgium) had lower or more variable coverage. In the study by Ben Natan et al. conducted in Israel (2016), a notable disparity in maternal vaccination coverage was observed, with higher uptake among native-born women compared to those from the former Soviet Union [108]. This difference may reflect variations in health literacy, cultural beliefs, and trust in healthcare systems, as well as potential barriers such as language and access to information. These findings highlight the need for culturally tailored interventions to improve vaccination uptake among migrant populations [108]. These findings underscore that policy recommendation alone is not sufficient; effective integration into healthcare systems and financial accessibility are key determinants of maternal vaccine uptake [138,139,140].
In a previous systematic review and meta-analysis, published in 2020, 21 qualitative studies and 49 quantitative studies were included [127]. Pregnant women who got a recommendation from HCPs had ten to twelve times higher odds of getting vaccinated against influenza or pertussis. In a systematic review of influenza vaccination determinants, which included studies published up to November 2013, the conclusions were similar. Vaccination uptake ranged from 1.7% to 88.4% for seasonal influenza, and from 6.2% to 85.7% for A/H1N1 pandemic influenza. Many pregnant women were unaware that they were at high risk for influenza and its complications during pregnancy. Although HCPs’ recommendations were consistently associated with vaccine uptake, most did not recommend the vaccine to their pregnant clients [141].
Maternal vaccination coverage often decreases with increasing parity, as women with multiple children may face time constraints or perceive lower risk. High- and upper-middle-income countries generally report higher coverage across all parity groups, while low- and lower-middle-income countries show lower uptake, especially among multiparous women. This suggests that access to healthcare, public health recommendations, and socioeconomic factors interact with parity to influence vaccine uptake. Targeted strategies are needed to improve coverage among women with multiple children in lower-income settings [142].
Cyclical influenza and pertussis outbreaks appear to increase vaccine acceptance by raising risk awareness, although this effect is often temporary and depends on sustained public health messaging and access to vaccination services; conversely, in countries such as China and India, where public funding and universal maternal vaccination recommendations have been limited, consistently low vaccination coverage reflects both structural barriers and weaker policy implementation. In addition, regional variations in vaccination coverage observed in the United States and Israel may reflect differences in local acceptance, healthcare access, and prior exposure to outbreaks, suggesting that both epidemiological context and health system factors shape maternal vaccination uptake [11,12,134,138].
In a systematic literature review published by Gkentzi et al., articles regarding pertussis maternal vaccine uptake were reviewed from January 2011 to May 2016, and the main determinants associated with maternal vaccination acceptance were retrieved. Young maternal age, lack of public insurance and premature delivery were factors not favoring vaccine uptake. HCP recommendations proved valuable in this review as well, since in studies conducted in Mexico, Korea and UK, mothers were much more likely to get vaccinated if they had been informed by their HCPs [143].
The main limitations of this systematic review involve the heterogeneity of the eligible studies as far as the study design and the extracted data are concerned. Consequently, the eligible studies did not include the same determinants, and the statistical data analysis was not presented and captured in a single way. It should be noted that different parameters were used for statistical analysis. Some studies used odds ratios to assess the relationship between vaccination rate and specific determinants, while others reported relative risks or prevalence ratios. This resulted in a restrictive descriptive analysis for both qualitative and quantitative data syntheses, making data comparability and data meta-analysis precarious.

5. Conclusions

Maternal vaccination rates against influenza and pertussis range worldwide and depend not only on diverse immunization programs and strategies but also on health services and populations’ perceptions. Mothers’ attitudes and knowledge regarding vaccinations and related diseases are crucial regarding maternal vaccination acceptance. Therefore, raising vaccination coverage requires addressing hesitancy and disseminating information about maternal immunization.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/vaccines14040325/s1: Table S1: PRISMA 2020 Checklist; Table S2: Newcastle-Ottawa Assessment Scoring of eligible studies recording influenza maternal immunization; Table S3: Newcastle-Ottawa Assessment Scoring of eligible studies recording pertussis maternal immunization; File S1: Research keywords.

Author Contributions

Conceptualization, P.G.M., M.E.P., C.H., D.B., and V.P.; Methodology, P.G.M., M.E.P., E.K., D.K., C.H., D.B., and V.P.; Software, E.K. and D.K.; Validation, P.G.M., M.E.P., E.K., D.K., and V.P.; Formal Analysis, P.G.M., M.E.P., E.K., D.K., and V.P.; Investigation, P.G.M., M.E.P., and V.P.; Resources, V.P.; Data Curation, P.G.M., M.E.P., E.K., and D.K.; Writing–Original Draft Preparation, P.G.M., M.E.P., E.K., and D.K.; Writing—Review and Editing, E.K., D.K., and V.P.; Visualization, P.G.M., M.E.P., E.K., D.K., and V.P.; Supervision, V.P.; Project Administration, P.G.M. and V.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data supporting reported results are available as anonymized databases upon request.

Acknowledgments

Research included in this systematic review was partly completed at Attikon University Hospital, Athens, Greece and at the Center for Clinical Epidemiology and Outcomes Research (CLEO), Athens, Greece.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ACIPAdvisory Committee on Immunization Practices
RSVRespiratory Syncytial Virus
HCPHealthcare provider/practitioner
WHOWorld Health Organization
SDStandard Deviation
UKUnited Kingdom
USAUnited States of America
GPGeneral Practitioners
OROdds Ratio
RRRelative Risk
PRPrevalence Ratio
95% CI95% Confidence Intervals
aORAdjusted Odds Ratio

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Vaccines 14 00325 g001
Figure 1. Flowchart of the systematic review [13].
Figure 1. Flowchart of the systematic review [13].
Vaccines 14 00325 g001
Table 1. Eligible studies included in the systematic review concerning maternal influenza vaccination.
Table 1. Eligible studies included in the systematic review concerning maternal influenza vaccination.
CountryPublication YearFirst AuthorStudy PeriodStudy DesignRespondersAge (Years) §Vaccination
Rate 		Country’s Recommendation
Australia2013Taksdal [26]November 2012Cross-Sectional416NA25%2010
Australia2013Wiley [27]July to November 2011 Cross-Sectional815NA27%2010
Australia2013Maher [28]November 2011 to December 2012 Cross-Sectional 462NA25%2010
Australia2014Collins [29]2011–2012Cross-Sectional 17NA11.8% 2010
Australia2015Hayles [30]November 2010 to June 2013Cross-Sectional 2483NA39.1%2010
Australia2015Mak [31]2012–2013Cross-Sectional 831NA36.5%Seasonal2010
Australia2015McCarthy [32]Each July, 2010 to 2014Cross-Sectional1086NA42.3% General (29.6% in 2010 to 51.3% In 2014) 2010
Australia2015O’ Grady [33]January To April 2014Mixed Methods (Cross-Sectional Survey and Yarning Circles (Focus Groups))5325 (Range: 17–39)17%2010
Australia2016Regan [34]2012–2014 (Every November)Cross-Sectional2018NA35.3% 2010
Australia2022McRae [35]July to September 2017Cross-Sectional642NA57.5% 2010
Australia2018Lotter [36]2015Cross-Sectional 10026.3 (Range: 18–43)62%2010
Australia2018Mak [37]April and October 2015Cross-Sectional 424NA60.6% 2010
Australia2018Mohammed [38]November 2014
And June-2016		Cross-Sectional18031.1 (Range: 21–43)76%2010
Australia2021McHugh [39]2012–2015Cross-Sectional882731.8 (Range: 28.5–35.2)37%2010
Belgium2015Laenen [40]2015–2018Cross-Sectional36,032 14.61%2010–2011
Brazil2019Mendoza-Sassi [41]January 1 and December 31, 2016Cross-sectional2670NA53.9%2010
Canada2008Tong [42]December 2003 to March 2004 Cross-Sectional18532.2 (Range: 16–44) 14%~2007–2009
Canada2009Yudin [43]October to December 2006 Cross-Sectional58NA19%~2007–2009
Canada2011Gracie [44]November 2009 to March 2010 Prospective Cohort Study40231 (19–47)29.4% Seasonal and H1N1/1.7% Seasonal~2007–2009
China2010Lau [45]November 2005 To January 2006 Cross-Sectional 568NA3.9%NA
China2013Tarrant [46]February to June 2010 Cross-Sectional549NA4.9% Seasonal/
2.2% Seasonal and H1N1		NA
China2017Song [47]2012–2014Cross-Sectional1673NA0%NA
China2018Li [48]May 2015 to February 2016Cross-Sectional 108NA0%NA
Czech Republic2023Kynčl [49]September 2020 to August 2021Cross-Sectional461733 (Range: 18–51)Less than 2%~2018–2020
Equador2021Erazo [50]from September 2016 to January 2017Cross-Sectional842NA36.6%~2010–2013
France2016Loubet [51]2014–2015Cross-Sectional and Surveillance System integrated to the European Project Influenzanet15334 ± 4.326%~2012
France2016Gaudelus [52]September to December
2014		Cross-Sectional300NA7%~2012
France2019Bartolo [16]November 2014 to June 2015 Cross-Sectional and Data from Medical Files2045NA35.50%~2012
France2020Descamps [24]March 2016Cross-Sectional And Medical Records11,712NA7.4%~2012
Germany2014Boedeker [53]2013Cross-Sectional838NA10.90%2010
Greece2019Psarris [54]April to June 2018Cross-Sectional197NA16.2%~2010
India2014Koul [55]October 2012 to April 2013 Cross-Sectional 100037 (Range: 18–41)0%limited/risk-based
Iran2012Honarvar [56]2010–2011Cross-Sectional 41627.06 ± 5.276%ΝA
Iran2015Abasi [57]2013Cross-sectional384NA1.80%ΝA
Ireland2018Barrett [58]2016Cross-Sectional198NA55.1%2010
Ireland2018Hallissey [59]November 2015 to March 2016 Cross-Sectional 8831 (Range 18–42)40%2010
Ireland2018O’Shea [60]January and June 2016Cross-Sectional1733 (Range: 23–44)76.40%2010
Ireland2018Ugezu [61]2018Cross-Sectional113NA42.50%2010
Israel2020Drezner [62]December 2017 to July 2018 Cross-Sectional29030.5 (19–44)34.5%~2009
Italy2016Maurici [63]October to December 2013Cross-Sectional 30933.9 ± 4.80%~2012
Italy2017Napolitano [15]December 2015 And February 2016Cross-Sectional372NA9.7%~2012
Italy2018D’ Alessandro [64]2017–2018Cross-Sectional 35831 ± 5.7 (18–44)1.4% ~2012
Italy2022Scatigna [65]June to September 2019Cross-Sectional251NA5.7%~2012
Italy2021Vilca [66]2018–2019Cross-Sectional483NA14.9%~2012
Italy2023Ferrari [67]2019–2022Cross-Sectional25,160NA18.9%~2012
Japan2015Yamada [68]March to July 2014Cross-Sectional1713NA51%Before 2010
Korea2021Kang [69]October to December 2019Cross-Sectional522NA63.2%~2010
Mexico2014Varan [70]2012Cross-Sectional38724 (Range: 15–43)45%2011–2012
Nicaragua2013Yuet [71]April to June 2011 Cross-Sectional2822NA1.70%~2013
Nicaragua2018Arriola [72]June to August 2016 Cross-Sectional130323 y (Range: 13–44)42%~2013
Nicaragua2016Arriola [73]October to December 2013Cross-Sectional1807NA71%~2013
Saudi Arabia2017Mayet [17]July To August 2013Cross-Sectional 99828.4 ± 6.118.%2010–2012
Singapore2019Offeddu [74]September to November 2017Cross-Sectional500NA9.8%~2017
South Korea2014Kim [75]2013Cross-Sectional 218NA48.60%2009–2010
Spain2018Castro-Sanchez [76]November 2015 to May 2016Cross-sectional11932.3 ± 5.5 52%2005
Spain2018Tuells [77]2014–2015Cross-Sectional934NA27.9% 2005
Spain2019Rodríguez-Blanco [78]October 2015 to January 2016 Cross-Sectional68330.4 ± 5.661.6%2005
Switzerland2012Blanchard-Rohner [79]March 2011 Cross-Sectional261NA18%~2009–2010
Switzerland2012Schindler [80]March 2011Cross-Sectional2934 (Range: 19–40)17.2% ~2009–2010
Switzerland2022Lumbreras Areta [81]November 2020 and March to April 2021Cross-Sectional950 49.8%~2009–2010
Turkey2014Celikel [82]2010Cross-Sectional198NA3% Seasonal~2010
Turkey2020Yakut [83]November 2015 to May 2016Cross-Sectional46527.8 (Range: 17–42)19.80%~2010
UΚ2018Wilcox [18]July 2017 to January 2018Cross-Sectional314NA38%2010
UK2021Walker [84]2010/2011–2015/2016Cross-Sectional152,132NA39.1%2010
UK2023Berendes [85]April to September 2022Cross-Sectional38NA50%2010
USA2001Silverman & Greif [86]January to March 2000Cross-Sectional242 NA8%2004
USA2010Ahluwalia [87]2006 and 2007Cross-Sectional 5424NAGeorgia:18.4%
Rhode Island: 31.9%		2004
USA2011Ding [88]April to June 2010 Cross-Sectional 244 NA32.1%Seasonal2004
USA2011Fisher [89]November 2009 to May 2010 Cross-Sectional 813NA64% Seasonal2004
USA2011Goldfarb [90]January to March 2010 Cross-Sectional 37029.8 (15–46)81% Seasonal and H1N1/7.4% Seasonal2004
USA2012Drees [91]February to April 2010Cross-Sectional 307NA60% Seasonal2004
USA/Canada2012Gorman [92]Oct2010 to June2011 Cross-Sectional199NA81%2004/
~2007–2009
USA2013Eppes [93]October 2009 to June 2010 Cross-Sectional 88NA69% Seasonal2004
USA2013Meharry [94]May to June 2010Cross-Sectional6033 (Range: 19–40)51.60%2004
USA2015Henninger [95]2010–2011Cross-Sectional1105NA63%2004
USA2016Stark [96]September 2013 to April 2014 and September 2014 to April 2015Cross-Sectional984NA71.9%2004
USA2018Strassberg [97]December 2014 to April 2015Cross-Sectional338NA70.7% 2004
USA2019Schlaudecker [25]2017Cross-Sectional and medical files265NA64.9%2004
§ Age of responders is documented as median age, mean age ± standard deviation (SD) or median age and respective age range in brackets according to data available.
Table 2. Eligible studies documenting main determinants of influenza vaccine uptake during pregnancy.
Table 2. Eligible studies documenting main determinants of influenza vaccine uptake during pregnancy.
First Author, YearDoctor’s
Recommendation		AttitudeParityPrevious Influenza
Vaccination
Ahluwalia, 2010 [87]✓ ✓✓
Arriola, 2018 [72]✓ ✓✓
Arriola, 2016 [73]✓
Bartolo, 2019 [16]✓ ✓✓
Blanchard-Rohner, 2012 [79]✓
Celikel, 2014 [82]✓
D’ Alessandro, 2018 [64] ✓✓
Descamps, 2020 [24] ✓
Drees, 2012 [91]✓ ✓
Eppes, 2013 [93]✓✓
Erazo, 2021 [50]✓✓
Ferrari, 2023 [67]✓
Gaudelus, 2016 [52] ✓
Goldfarb, 2011 [90]✓✓
Kang, 2021 [69]✓
Lau, 2010 [45]✓✓
Lotter, 2018 [36]✓
Loubet, 2016 [51]✓
Maher, 2013 [28]✓
Mak, 2015 [31]✓
Mak, 2018 [37]✓
Mayet, 2017 [17] ✓✓
McCarthy, 2015 [32]✓ ✓
McRae, 2022 [35]✓✓✓✓
Mohammed, 2018 [38]✓ ✓✓
Napolitano, 2017 [15] ✓
Offeddu, 2019 [74]✓✓ ✓
Scatigna, 2022 [65]✓✓
Schlaudecker, 2019 [25] ✓
Stark, 2016 [96] ✓ ✓
Taksdal, 2013 [26]✓
Tarrant, 2013 [46] ✓
Tong, 2008 [42]✓✓
Varan, 2014 [70]✓
Vilca, 2021 [66]✓✓
Wiley, 2013 [27]✓✓
Yamada, 2015 [68] ✓✓
Yuet, 2013 [71]✓✓ ✓
Table 3. Statistically significant association between influenza vaccine uptake and doctor’s recommendation .
Table 3. Statistically significant association between influenza vaccine uptake and doctor’s recommendation .
First AuthorYearOR (95% CI)p-ValueRR (95% CI)PR (95% CI)
Ahluwalia [87]201056.62 (37.43–85.63)NANANA
Arriola [72]201874.11 (36.63–149.94)NANANA
Arriola [73]201614.22 (10.45–18.40)NANANA
Bartolo [16]201918.8 (10.0–35.8)NANANA
Blanchard-Rohner [79]2012107NANANA
Celikel [82]2014NAp < 0.001NANA
Drees [91]2012NANA3.9 (2.1–7.4)NA
Eppes [93]2013NAp = 0.04NANA
Erazo [50]2021NANANAReceiving recommendation/not offer → 3.17 (1.57–6.40)/Receiving both recommendation and offer → 15.84 (9.62–26.10) [compared to women who did not receive a recommendation/offer]
Goldfarb [90]20113.06 (1.27–7.38)NANANA
Henninger [95]20153.14 (1.99–4.96)NANANA
Kang [69]202111.44 (5.46–24.00)NANANA
Lau [45]201015.91p < 0.01NANA
Lotter [36]201815.6 (4.9–49.5)NANANA
Loubet [51]201641.9 (20.7–84.9)NANANA
Maher [28]201341.89 (20.68–84.86)p < 0.001NANA
Mak [31]201511.1 (7.9–15.5)NANANA
Mak [37]2018influenza recommendation: 4.47 (1.89–10.59)
both influenza and pertussis recommendation: 33.3 (15.15–73.38)		p < 0.001NANA
McCarthy [32]2015NAp < 0.001NANA
McRae [35]20226.06 (3.50, 10.50)p < 0.001NANA
Mohammed [38]20188.0 (3.06–20.9)p < 0.001NANA
Offeddu [74]2019NANANAPR  =  7.11;
95% CI = 3.92–12.90
Scatigna [65]2022NAp < 0.001NANA
Taksdal [26]201315.58 (6.055–40.094)p < 0.001NANA
Tong [42]200832.3 (10.4–100)p < 0.0001NANA
Varan [70]20141.95 (1.21–3.15)NANANA
Vilca [66]202129.8 (13.1–78.4)NANANA
Wiley [27]201320.0 (10.9–36.9)p < 0.01NANA
Yuet [71]20136.30 (3.19–12.46)NANANA
OR: Odds Ratio; RR: Relative Risk; PR: Prevalence Ratio; 95% CI: 95% Confidence Interval.
Table 4. Statistically significant association between influenza vaccine uptake and maternal attitude .
Table 4. Statistically significant association between influenza vaccine uptake and maternal attitude .
First AuthorYearOR (95% CI)p-ValuePR (95% CI)
Eppes [93]2013NAp < 0.01NA
Erazo [50]2021NANA1.53 (1.03–2.37)
Goldfarb [90]2011OR = 3.92; 95% CI =1.48–10.43NANA
Henninger [95]2015participants’ positive views: 2.18 (1.72–2.78)/negative views: 0.36 (0.28–0.460)NANA
Lau [45]20104.97p < 0.01NA
Napolitano [15]20171.35 (1.14–1.59)NANA
Offeddu [74]2019NANAPR  =  1.62;
95% CI = 1.30–2.01
Scatigna [65]2022NAp < 0.001NA
Schlaudecker [25]2019effective in preventing influenza in themselves (OR 9.0) or their babies (OR 8.1)NANA
Stark [96]20161.708 p < 0.01NA
Tarrant [46]20133.52 (1.37–9.07)NANA
Tong [42]2008medium attitude vs. low: 1.62 (1.25–2.1) (p = 0.0002)/high attitude vs. low: 4.69 (1.63–13.5) (p < 0.0001)NANA
Vilca [66]20212.5 (1.2–6.2)NANA
Wiley [27]20137.6 p < 0.01NA
Yuet [71]20139.98 (3.79–26.24)NANA
OR: Odds Ratio; PR: Prevalence Ratio; 95% CI: 95% Confidence Interval.
Table 5. Statistically significant association between influenza vaccine uptake and parity .
Table 5. Statistically significant association between influenza vaccine uptake and parity .
First AuthorYearOR (95% CI)p-ValueRR (95% CI)PR (95% CI)
Ahluwalia [87]20100.60 (0.40–0.89)NANANA
Bartolo [16]20192.5 for nulliparityNANANA
D’Alessandro [64]20181.87 for multiparity
(1.02–3.41)		NANANA
Descamps [24]2020NANANAPR = 2.1 for nulliparity
95% CI = 1.4–3.2
Mayet [17]2017NAp < 0.001NANA
Mohammed [38]20180.43 for multiparity; (0.19–0.99)p = 0.048NANA
Yamada [68]2015NAp < 0.05NANA
OR: Odds Ratio; RR: Relative Risk; PR: Prevalence Ratio; 95% CI: 95% Confidence Interval.
Table 6. Statistically significant association between influenza vaccine uptake and previous influenza vaccination .
Table 6. Statistically significant association between influenza vaccine uptake and previous influenza vaccination .
First AuthorYearOR (95% CI)p-ValueRR (95% CI)PR (95% CI)
Bartolo [16]20194.1 (3.1–5.5)NANANA
Drees [91]2012NANAPrior influenza vaccination
[1.6(1.3–2.0)]/receipt of seasonal influenza
vaccination [2.2(1.7–2.9)]		NA
Offeddu [74]2019NANANA2.51 (1.54–4.11)
Stark [96]2016NAp < 0.01NANA
Yuet [71]20132.47 (1.25–4.91)NANANA
OR: Odds RatioRR: Relative Risk; PR: Prevalence Ratio; 95% CI: 95% Confidence Interval.
Table 7. Eligible studies included in the systematic review concerning maternal pertussis vaccination.
Table 7. Eligible studies included in the systematic review concerning maternal pertussis vaccination.
CountryPublication YearFirst
Author		Study PeriodStudy
Design		RespondersAge (Years) §Vaccination
Rate		Country’s Recommendation
Australia2014Collins [29]2011–2012Cross-Sectional17NA11.8%2015
Australia2015Mak [31]2012–2013Cross-Sectional800NA71%2015
Australia2018Lotter [36]2015Cross-Sectional10026.3 (Range: 18–43)63%2015
Australia2018Mohammed [38]November 2014 and June 2016Cross-Sectional18031.1 (Range 21–43)81%2015
Australia2020Moir [103]January 2017 to January 2018Cross-Sectional1305NA82.9%2015
Belgium2015Laenen [40]December 2013 to February 2014Cross-Sectional250NA39.2%2013–2014
Belgium2016Maertens [104]October 2014 and May 2015Cross-Sectional82329.8 ± 4.864%2013–2014
Canada2022Li [105]April to October 2019Cross-Sectional94631 (Range: 28–35)73.6%2012–2013
Canada2022Gilbert [106]September 2018 to March 2019Cross-Sectional4607NA43%2012–2013
Canada2023Wright [107]2018–2020Cross-Sectional243NA31.3%2012–2013
France2016Gaudelus [52]September to December 2014.Cross-Sectional300 30.87%2014–2015
Ireland2018Hallissey [59]2015–2016Cross-Sectional8831 (Range: 18–42)67%2016
Ireland2018O’Shea [60]2016Cross-Sectional1733 (Range: 23–43)52.90%2016
Ireland2018Ugezu [61]2018Cross-Sectional113NA31%2016
Israel2017Ben Natan [108]January to March 2016.Cross-Sectional20028.7 ± 4.4. (Range:21–42)52% of Native-born women compared to 31% of women born in the former Soviet Union2016
Israel2020Drezner [62]December 2017 to July 2018Cross-Sectional290 30.5 ± 5.2
(Range:19–44)		76%2016
Italy2018D’ Alessandro [64]2017–2018Cross-Sectional35831 ± 5.7
(Range: 18–44)		0%2019
Italy2022Scatigna [65]June to September 2019Cross-Sectional251NA16.3%2019
Italy2021Vilca [66]2018–2019Cross-Sectional483NA60.9%2019
Italy2021Zambri [109]October 2019 to January 2021Cross-Sectional30033.3 (Range: 27.3–39.3)48.3% 2019
Italy2023Ferrari [67]2019–2022Cross-Sectional25,160NA56.5%2019
Greece2019Psarris [54]April to June 2018Cross-Sectional197NA0%2018
Korea2021Kim [75]October to December 2019Cross-Sectional466NA67%2019
Mexico2014Varan [70]2012Cross-dectional387NA74%2012
New Zealand2016Gauld [110]2014Cross-Sectional37Range: 18–4346%2013
New Zealand2018Hill [111]2013Cross-Sectional596ΝA74%2013
New Zealand2018Deverall [112]2017Clinical audit111NA44%2013
Spain2018Castro-Sanchez [76]2015–2016Cross-Sectional11932.3 ± 5.5 94%2015
Switzerland2022Lumbreras Areta [81]November 2020 and March to April 2021Cross-Sectional950NA86.2%2020
Turkey2014Celikel [82]March to May 2010Cross-Sectional198NA47% 2015
Turkey2020Yakut [83]November 2015 to May 2016Cross-Sectional46527.8 (Range: 17–42)11.20%2015
UK2015Donaldson [113]2013–2014Cross-Sectional20031(Range: 18–34)26% vaccinated/
47.5% willingness		2012
UK2018Wilcox [18]2017–2018Cross-Sectional314NA56.%2012
UK2021Walker [84]2012–2015Cross-Sectional68,090NA67.3%2012
UK2023Berendes [85]Between April and September 2022semi-structured interviews and focus group discussion38NA71%2012
USA2014Goldfarb [114]February to June 2013Cohort retrospective1467NA81.6%2011
USA2014Housey [115]November 2011 and February 2013Cross-Sectional15,1812114.3%2011
USA2015Healy [116]May 2013 to February 2014Cross-Sectional82530.2 (Range:18–45)51.6%2011
USA2016Dempsey [117]2014Cross-sectional316NA82%2011
USA2016O’Halloran [118]2013Cross-Sectional2958NA41.8%2011
USA2018Koerner [119]October 2013 to September 2014Cross-Sectional237NA65.8%2011
USA2018Strassberg [97]2014–2015Cross-Sectional338NA35.8%2011
USA2018New [120]2016Cross-Sectional66NA39%2011
USA2018Khan [121]March to April 2018Cross-Sectional700NA54.4%2011
USA2019Kriss [122]June to July 2014Cross-Sectional486NA41%2011
USA2020Wales [123]January to April 2016Cross-Sectional40029.665.8%2011
USA2019Shlaudecker [25]2017Cross-Sectional265NA89.8%2011
USA2020Badreldin [124]November 2011–2012, December 2012 and December 2015Cross-Sectional2460NA44.9% (preguidelines)2011
USA2020Murthy [125]March to April 2018Cross-Sectional700NA54.4%2011
USA2022Bernstein [100]March to August 2017Cross-Sectional/electronic medical record1571NA43.8%.2011
Zambia2018Larson Williams [126]2016Cross-Sectional50 Median: 27100%2016
§ Age of responders is documented as median age. mean age ± SD or median age and respective age range in brackets according to data available.
Table 8. Principal determinants affecting maternal pertussis immunization.
Table 8. Principal determinants affecting maternal pertussis immunization.
First Author, YearDoctor’s
Recommendation		Adverse EventsBenefitsParity
Badreldin, 2020 [124] ✓
Ben Natan, 2017 [108] ✓
Bernstein, 2022 [100]✓✓
Castro-Sanchez, 2018 [76]✓
Celikel, 2014 [82]✓
Collins, 2014 [29]✓
D’ Alessandro, 2018 [64] ✓
Dempsey, 2016 [117] ✓
Donaldson, 2015 [113]✓
Ferrari, 2023 [67]✓ ✓
Gauld, 2016 [110]✓✓
Goldfarb, 2014 [114] ✓
Healy, 2015 [116] ✓
Kim, 2021 [75]✓
Kriss, 2019 [122]✓✓
Lotter, 2018 [36]✓
Maertens, 2016 [104] ✓
Mak, 2015 [31]✓
Mohammed, 2018 [38]✓ ✓
Moir, 2020 [103]✓ ✓
Murthy, 2020 [125] ✓
O’ Halloran, 2016 [118] ✓
Scatigna, 2022 [65]✓ ✓
Schlaudecker, 2019 [25]✓
Strassberg, 2018 [97]✓
Varan, 2014 [70]✓✓
Vilca, 2021 [66]✓✓✓
Wales, 2020 [123]✓
Zambri. 2021 [109]✓
Table 9. Statistically significant association between pertussis vaccine uptake and doctor’s recommendation .
Table 9. Statistically significant association between pertussis vaccine uptake and doctor’s recommendation .
First AuthorYearOR (95% CI)p-Value
Bernstein [100]2022No HCP’s recommendation:
0.39 (0.23–0.65)		p = 0.0003
Celikel [82]2014NAp < 0.001
Kim [75]20214.426 (2.114–9.267)p < 0.001
Lotter [36] 201813.3 (4.6–38.0)NA
Mak [31]201533.3 (15.15–73.38)p < 0.001
Mohammed [38]20187.8 (3.3–18.3)p < 0.001
Moir [103]202041.78 (20.03–87.17)NA
Scatigna [65]2022NAp < 0.001
Schlaudecker [25]20195.4NA
Strassberg [97]201810.231 (3.246–32.247)NA
Varan [70]20141.95 (1.21–3.15)NA
Vilca [66]202155.8 (27–127.6)NA
Wales [123]2019NAp = 0.001
Zambri [109]20212.8 (1.4–5.7)p = 0.01
OR: Odds Ratio; 95% CI: 95% Confidence Interval.
Table 10. Statistically significant association between pertussis vaccine uptake and perceptions about vaccine’s adverse events .
Table 10. Statistically significant association between pertussis vaccine uptake and perceptions about vaccine’s adverse events .
First AuthorYearOR (95% CI)p-Value
Bernstein [100]20221.59 (1.12–3.24)p = 0.009
Varan [70]20141.75 (1.16–2.63)p = 0.008
Vilca [66]20212.5 (1.1–6)NA
OR: Odds Ratios of not being vaccinated when fear of vaccine’s adverse events is expressed.
Table 11. Statistically significant association between pertussis vaccine uptake and perceptions about vaccine’s benefits .
Table 11. Statistically significant association between pertussis vaccine uptake and perceptions about vaccine’s benefits .
First AuthorYearOR (95% CI)p-Value
Ben Natan [108]2017NA<0.001
Dempsey [117]2016NA0.008
Scatigna [65]2022NAp < 0.001
Vilca [60]20213.5 (1.5–8.7)NA
OR: Odds Ratio; 95% CI: 95% Confidence Interval.
Table 12. Statistically significant association between pertussis vaccine uptake and parity .
Table 12. Statistically significant association between pertussis vaccine uptake and parity .
First AuthorYearOR (95% CI)p-ValueRR (95% CI)PR (95% CI)
Badreldin [124]20201.43 (1.05–1.94)p = 0.002N/ANA
D’Alessandro [64]20181.87 (1.02–3.41)p < 0.05NANA
Goldfard [114]20140.72 (0.55–0.94)0.01NANA
Maerteus [104]2016NAp = 0.005NANA
Moir [103]20200.38 (0.24–0.6)
(second child);
0.18 (0.11–0.31)
(subsequent child)		p < 0.001NANA
O’Halloran [118]2016NAp < 0.05NANA
OR: Odds Ratio; RR: Relative Risk; PR: Prevalence Ratio; 95% CI: 95% Confidence Interval.
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Maltezou, P.G.; Papakonstantinou, M.E.; Kourkouni, E.; Kousi, D.; Hadjichristodoulou, C.; Briana, D.; Papaevangelou, V. Influenza and Pertussis Vaccination During Pregnancy: A Systematic Review of Vaccination Rates and Vaccination Determinants. Vaccines 2026, 14, 325. https://doi.org/10.3390/vaccines14040325

AMA Style

Maltezou PG, Papakonstantinou ME, Kourkouni E, Kousi D, Hadjichristodoulou C, Briana D, Papaevangelou V. Influenza and Pertussis Vaccination During Pregnancy: A Systematic Review of Vaccination Rates and Vaccination Determinants. Vaccines. 2026; 14(4):325. https://doi.org/10.3390/vaccines14040325

Chicago/Turabian Style

Maltezou, Panagiota Georgia, Maria Eleni Papakonstantinou, Eleni Kourkouni, Dimitra Kousi, Christos Hadjichristodoulou, Despoina Briana, and Vasiliki Papaevangelou. 2026. "Influenza and Pertussis Vaccination During Pregnancy: A Systematic Review of Vaccination Rates and Vaccination Determinants" Vaccines 14, no. 4: 325. https://doi.org/10.3390/vaccines14040325

APA Style

Maltezou, P. G., Papakonstantinou, M. E., Kourkouni, E., Kousi, D., Hadjichristodoulou, C., Briana, D., & Papaevangelou, V. (2026). Influenza and Pertussis Vaccination During Pregnancy: A Systematic Review of Vaccination Rates and Vaccination Determinants. Vaccines, 14(4), 325. https://doi.org/10.3390/vaccines14040325

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