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Article ; Online: Is annual vaccination best? A modelling study of influenza vaccination strategies in children.

Ainslie, Kylie E C / Riley, Steven

2022 Volume 40, Issue 21, Page(s) 2940–2948

Abstract: Introduction: Annual vaccination of children against influenza is a key component of vaccination programs in many countries. However, past infection and vaccination may affect an individual's susceptibility to infection. Little research has evaluated ... ...

Abstract	Introduction: Annual vaccination of children against influenza is a key component of vaccination programs in many countries. However, past infection and vaccination may affect an individual's susceptibility to infection. Little research has evaluated whether annual vaccination is the best strategy. Using the United Kingdom as our motivating example, we developed a framework to assess the impact of different childhood vaccination strategies, specifically annual and biennial (every other year), on attack rate and expected number of infections. Methods and findings: We present a multi-annual, individual-based, stochastic, force of infection model that accounts for individual exposure histories and disease/vaccine dynamics influencing susceptibility. We simulate birth cohorts that experience yearly influenza epidemics and follow them until age 18 to determine attack rates and the number of infections during childhood. We perform simulations under baseline conditions, with an assumed vaccination coverage of 44%, to compare annual vaccination to no and biennial vaccination. We relax our baseline assumptions to explore how our model assumptions impact vaccination program performance. At baseline, we observed less than half the number of infections between the ages 2 and 10 under annual vaccination in children who had been vaccinated at least half the time compared to no vaccination. When averaged over all ages 0-18, the number of infections under annual vaccination was 2.07 (2.06, 2.08) compared to 2.63 (2.62, 2.64) under no vaccination, and 2.38 (2.37, 2.40) under biennial vaccination. When we introduced a penalty for repeated exposures, we observed a decrease in the difference in infections between the vaccination strategies. Specifically, the difference in childhood infections under biennial compared to annual vaccination decreased from 0.31 to 0.04 as exposure penalty increased. Conclusion: Our results indicate that while annual vaccination averts more childhood infections than biennial vaccination, this difference is small. Our work confirms the value of annual vaccination in children, even with modest vaccination coverage, but also shows that similar benefits of vaccination may be obtained by implementing a biennial vaccination program. Author summary: Many countries include annual vaccination of children against influenza in their vaccination programs. In the United Kingdom (UK), annual vaccination of children aged of 2 to 10 against influenza is recommended. However, little research has evaluated whether annual vaccination is the best strategy, while accounting for how past infection and vaccination may affect an individual's susceptibility to infection in the current influenza season. Prior work has suggested that there may be a negative effect of repeated vaccination. In this work we developed a stochastic, individual-based model to assess the impact of repeated vaccination strategies on childhood infections. Specifically, we first compare annual vaccination to no vaccination and then annual vaccination to biennial (every other year) vaccination. We use the UK as our motivating example. We found that an annual vaccination strategy resulted in the fewest childhood infections, followed by biennial vaccination. The difference in number of childhood infections between the different vaccination strategies decreased when we introduced a penalty for repeated exposures. Our work confirms the value of annual vaccination in children, but also shows that similar benefits of vaccination can be obtained by implementing a biennial vaccination program, particularly when there is a negative effect of repeated vaccinations.
MeSH term(s)	Child ; Child, Preschool ; Humans ; Immunization Programs ; Influenza Vaccines/adverse effects ; Influenza, Human/epidemiology ; Influenza, Human/prevention & control ; Seasons ; Vaccination
Chemical Substances	Influenza Vaccines
Language	English
Publishing date	2022-04-08
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	605674-x
ISSN	1873-2518 ; 0264-410X
ISSN (online)	1873-2518
ISSN	0264-410X
DOI	10.1016/j.vaccine.2022.03.065
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Article ; Online: Reported effectiveness of COVID-19 monovalent booster vaccines and hybrid immunity against mild and severe Omicron disease in adults: A systematic review and

Nealon, Joshua / Mefsin, Yonatan M / McMenamin, Martina E / Ainslie, Kylie E C / Cowling, Benjamin J

Vaccine: X

2024 Volume 17, Page(s) 100451

Abstract: Background: Waning of COVID-19 vaccine efficacy/effectiveness (VE) has been observed across settings and epidemiological contexts. We conducted a systematic review of COVID-19 VE studies and performed a : Methods: Systematic review of PubMed, medRxiv ...

Abstract	Background: Waning of COVID-19 vaccine efficacy/effectiveness (VE) has been observed across settings and epidemiological contexts. We conducted a systematic review of COVID-19 VE studies and performed a Methods: Systematic review of PubMed, medRxiv and the WHO-International Vaccine Access Center database summarizing VE studies on 31 December 2022. Studies were those presenting primary adult VE data from hybrid immunity or third/fourth mRNA COVID-19 monovalent vaccine doses [due to limited data with other vaccines] against Omicron, compared with unvaccinated individuals or individuals eligible for corresponding booster doses but who did not receive them. We used Results: We identified 55 eligible studies reporting 269 VE estimates. Most estimates (180/269; 67 %) described effectiveness of third dose vaccination; with 48 (18 %) and 41 (15 %) describing hybrid immunity and fourth dose effectiveness, respectively, mostly (200; 74 %) derived from test-negative design studies. Most estimates (176/269; 65 %) reported VE compared with unvaccinated comparison groups. Estimated VE against mild outcomes declined following third dose vaccination from 62 % (95 % CI: 58 % - 66 %) after 4 weeks to 48 % (41 % - 55 %) after 20 weeks. Fourth dose VE against mild COVID-19 declined from 48 % (41 % - 56 %) after 4 weeks to 47 % (19 % - 65 %) after 20 weeks. VE for severe outcomes was higher and declined in the three-dose group from 90 % (87 % - 92 %) after 4 weeks to 70 % (65 - 74 %) after 20 weeks. Conclusions: Time-since vaccination is an important determinant of booster dose VE, a finding which may support seasonal COVID-19 booster doses. Integration of VE and immunological parameters - and longer-term data including from other vaccine types - are needed to better-understand determinants of clinical protection.
Language	English
Publishing date	2024-02-02
Publishing country	England
Document type	Journal Article
ISSN	2590-1362
ISSN (online)	2590-1362
DOI	10.1016/j.jvacx.2024.100451
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Article: Is annual vaccination best? A modelling study of influenza vaccination strategies in children

Ainslie, Kylie E.C. / Riley, Steven

Vaccine. 2022 May 09, v. 40, no. 21

2022

Abstract: Annual vaccination of children against influenza is a key component of vaccination programs in many countries. However, past infection and vaccination may affect an individual’s susceptibility to infection. Little research has evaluated whether annual ... ...

Abstract	Annual vaccination of children against influenza is a key component of vaccination programs in many countries. However, past infection and vaccination may affect an individual’s susceptibility to infection. Little research has evaluated whether annual vaccination is the best strategy. Using the United Kingdom as our motivating example, we developed a framework to assess the impact of different childhood vaccination strategies, specifically annual and biennial (every other year), on attack rate and expected number of infections. We present a multi-annual, individual-based, stochastic, force of infection model that accounts for individual exposure histories and disease/vaccine dynamics influencing susceptibility. We simulate birth cohorts that experience yearly influenza epidemics and follow them until age 18 to determine attack rates and the number of infections during childhood. We perform simulations under baseline conditions, with an assumed vaccination coverage of 44%, to compare annual vaccination to no and biennial vaccination. We relax our baseline assumptions to explore how our model assumptions impact vaccination program performance. At baseline, we observed less than half the number of infections between the ages 2 and 10 under annual vaccination in children who had been vaccinated at least half the time compared to no vaccination. When averaged over all ages 0–18, the number of infections under annual vaccination was 2.07 (2.06, 2.08) compared to 2.63 (2.62, 2.64) under no vaccination, and 2.38 (2.37, 2.40) under biennial vaccination. When we introduced a penalty for repeated exposures, we observed a decrease in the difference in infections between the vaccination strategies. Specifically, the difference in childhood infections under biennial compared to annual vaccination decreased from 0.31 to 0.04 as exposure penalty increased. Our results indicate that while annual vaccination averts more childhood infections than biennial vaccination, this difference is small. Our work confirms the value of annual vaccination in children, even with modest vaccination coverage, but also shows that similar benefits of vaccination may be obtained by implementing a biennial vaccination program. Many countries include annual vaccination of children against influenza in their vaccination programs. In the United Kingdom (UK), annual vaccination of children aged of 2 to 10 against influenza is recommended. However, little research has evaluated whether annual vaccination is the best strategy, while accounting for how past infection and vaccination may affect an individual’s susceptibility to infection in the current influenza season. Prior work has suggested that there may be a negative effect of repeated vaccination. In this work we developed a stochastic, individual-based model to assess the impact of repeated vaccination strategies on childhood infections. Specifically, we first compare annual vaccination to no vaccination and then annual vaccination to biennial (every other year) vaccination. We use the UK as our motivating example. We found that an annual vaccination strategy resulted in the fewest childhood infections, followed by biennial vaccination. The difference in number of childhood infections between the different vaccination strategies decreased when we introduced a penalty for repeated exposures. Our work confirms the value of annual vaccination in children, but also shows that similar benefits of vaccination can be obtained by implementing a biennial vaccination program, particularly when there is a negative effect of repeated vaccinations.
Keywords	childhood ; influenza ; influenza vaccination ; models ; vaccines ; United Kingdom
Language	English
Dates of publication	2022-0509
Size	p. 2940-2948.
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	605674-x
ISSN	1873-2518 ; 0264-410X
ISSN (online)	1873-2518
ISSN	0264-410X
DOI	10.1016/j.vaccine.2022.03.065
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Zs.A 1930: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
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Article ; Online: Ethical frameworks should be applied to computational modelling of infectious disease interventions.

Zachreson, Cameron / Savulescu, Julian / Shearer, Freya M / Plank, Michael J / Coghlan, Simon / Miller, Joel C / Ainslie, Kylie E C / Geard, Nicholas

PLoS computational biology

2024 Volume 20, Issue 3, Page(s) e1011933

Abstract: This perspective is part of an international effort to improve epidemiological models with the goal of reducing the unintended consequences of infectious disease interventions. The scenarios in which models are applied often involve difficult trade-offs ... ...

Abstract	This perspective is part of an international effort to improve epidemiological models with the goal of reducing the unintended consequences of infectious disease interventions. The scenarios in which models are applied often involve difficult trade-offs that are well recognised in public health ethics. Unless these trade-offs are explicitly accounted for, models risk overlooking contested ethical choices and values, leading to an increased risk of unintended consequences. We argue that such risks could be reduced if modellers were more aware of ethical frameworks and had the capacity to explicitly account for the relevant values in their models. We propose that public health ethics can provide a conceptual foundation for developing this capacity. After reviewing relevant concepts in public health and clinical ethics, we discuss examples from the COVID-19 pandemic to illustrate the current separation between public health ethics and infectious disease modelling. We conclude by describing practical steps to build the capacity for ethically aware modelling. Developing this capacity constitutes a critical step towards ethical practice in computational modelling of public health interventions, which will require collaboration with experts on public health ethics, decision support, behavioural interventions, and social determinants of health, as well as direct consultation with communities and policy makers.
MeSH term(s)	Humans ; Pandemics/prevention & control ; Public Health ; Communicable Diseases/epidemiology ; Computer Simulation
Language	English
Publishing date	2024-03-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1011933
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Article ; Online: Association of COVID-19 vaccination with duration of hospitalization in older adults in Hong Kong.

Chen, Dongxuan / Cowling, Benjamin J / Ainslie, Kylie E C / Lin, Yun / Wong, Jessica Y / Lau, Eric H Y / Wu, Peng / Nealon, Joshua

Vaccine

2024 Volume 42, Issue 9, Page(s) 2385–2393

Abstract: Introduction: The association between COVID-19 vaccination and length of hospital stay may provide further insight into vaccination benefits, but few studies have investigated such associations in detail. We aimed to investigate the association between ... ...

Abstract	Introduction: The association between COVID-19 vaccination and length of hospital stay may provide further insight into vaccination benefits, but few studies have investigated such associations in detail. We aimed to investigate the association between COVID-19 vaccination and length of hospital stay in COVID-19 patients during Omicron waves in Hong Kong, and explore potential predictors. Methods: This retrospective cohort study was conducted on local patients aged ≥60 years who were admitted due to COVID-19 infection in Hong Kong in 2022, from 1 February to 22 November, and with 28 days of follow-up since admission. The exposure was either not vaccinated; or having received 2/3/4 doses of CoronaVac (Sinovac); or 2/3/4 doses of BNT162b2 (BioNTech/Fosun Pharma/Pfizer). Length of stay in hospital was the main outcome. Accelerated failure time models were used to quantify variation in hospital stay for vaccinated compared with unvaccinated patients, accounting for age, sex, comorbidity, type of vaccine and number of doses received, care home residence and admission timing; stratified by age groups and epidemic waves. Results: This study included 32,398 patients aged 60 years and above for main analysis, their median (IQR) age was 79 (71-87) years, 53% were men, and 40% were unvaccinated. The patients were stratified by confirmation prior to or since 23 May 2022, resulting in a sample size of 15,803 and 16,595 in those two waves respectively. Vaccinated patients were found to have 13-39% shorter hospital stay compared to unvaccinated patients. More vaccine doses received were associated with shorter hospital stay, and BNT162b2 recipients had slightly shorter hospital stays than CoronaVac recipients. Conclusion: Vaccination was associated with reduced hospital stay in breakthrough infections. Increased vaccination uptake in older adults may improve hospital bed turnover and public health outcomes especially during large community epidemics.
MeSH term(s)	Male ; Humans ; Aged ; Female ; BNT162 Vaccine ; Hong Kong/epidemiology ; COVID-19 Vaccines ; Retrospective Studies ; COVID-19/epidemiology ; COVID-19/prevention & control ; Hospitalization ; Vaccination
Chemical Substances	BNT162 Vaccine ; COVID-19 Vaccines
Language	English
Publishing date	2024-03-05
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	605674-x
ISSN	1873-2518 ; 0264-410X
ISSN (online)	1873-2518
ISSN	0264-410X
DOI	10.1016/j.vaccine.2024.02.074
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Article ; Online: Time Scales of Human Mpox Transmission in The Netherlands.

Miura, Fuminari / Backer, Jantien A / van Rijckevorsel, Gini / Bavalia, Roisin / Raven, Stijn / Petrignani, Mariska / Ainslie, Kylie E C / Wallinga, Jacco

The Journal of infectious diseases

2023 Volume 229, Issue 3, Page(s) 800–804

Abstract: Mpox has spread rapidly to many countries in nonendemic regions. After reviewing detailed exposure histories of 109 pairs of mpox cases in the Netherlands, we identified 34 pairs where transmission was likely and the infectee reported a single potential ... ...

Abstract	Mpox has spread rapidly to many countries in nonendemic regions. After reviewing detailed exposure histories of 109 pairs of mpox cases in the Netherlands, we identified 34 pairs where transmission was likely and the infectee reported a single potential infector with a mean serial interval of 10.1 days (95% credible interval, 6.6-14.7 days). Further investigation into pairs from 1 regional public health service revealed that presymptomatic transmission may have occurred in 5 of 18 pairs. These findings emphasize that precaution remains key, regardless of the presence of recognizable symptoms of mpox.
MeSH term(s)	Humans ; Netherlands ; Mpox (monkeypox)
Language	English
Publishing date	2023-04-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	3019-3
ISSN	1537-6613 ; 0022-1899
ISSN (online)	1537-6613
ISSN	0022-1899
DOI	10.1093/infdis/jiad091
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Article ; Online: Bias of influenza vaccine effectiveness estimates from test-negative studies conducted during an influenza pandemic.

Ainslie, Kylie E C / Haber, Michael / Orenstein, Walter A

Vaccine

2019 Volume 37, Issue 14, Page(s) 1987–1993

Abstract: Test-negative (TN) studies have become the most widely used study design for the estimation of influenza vaccine effectiveness (VE) and are easily incorporated into existing influenza surveillance networks. We seek to determine the bias of TN-based VE ... ...

Abstract	Test-negative (TN) studies have become the most widely used study design for the estimation of influenza vaccine effectiveness (VE) and are easily incorporated into existing influenza surveillance networks. We seek to determine the bias of TN-based VE estimates during a pandemic using a dynamic probability model. The model is used to evaluate and compare the bias of VE estimates under various sources of bias when vaccination occurs after the beginning of an outbreak, such as during a pandemic. The model includes two covariates (health status and health awareness), which may affect the probabilities of vaccination, developing influenza and non-influenza acute respiratory illness (ARI), and seeking medical care. Specifically, we evaluate the bias of VE estimates when (1) vaccination affects the probability of developing a non-influenza ARI; (2) vaccination affects the probability of seeking medical care; (3) a covariate (e.g. health status) is related to both the probabilities of vaccination and developing an ARI; and (4) a covariate (e.g. health awareness) is related to both the probabilities of vaccination and of seeking medical care. We considered two outcomes against which the vaccine is supposed to protect: symptomatic influenza and medically-attended influenza. When vaccination begins during an outbreak, we found that the effect of delayed onset of vaccination is unpredictable. VE estimates from TN studies were biased regardless of the source of bias present. However, if the core assumption of the TN design is satisfied, that is, if vaccination does not affect the probability of non-influenza ARI, then TN-based VE estimates against medically-attended influenza will only suffer from small (<0.05) to moderate bias (≥0.05 and <0.10). These results suggest that if sources of bias listed above are ruled out, TN studies are a valid study design for the estimation of VE during a pandemic.
MeSH term(s)	Algorithms ; Humans ; Influenza Vaccines/immunology ; Influenza, Human/diagnosis ; Influenza, Human/epidemiology ; Influenza, Human/prevention & control ; Influenza, Human/virology ; Models, Theoretical ; Outcome Assessment, Health Care ; Vaccination
Chemical Substances	Influenza Vaccines
Language	English
Publishing date	2019-03-02
Publishing country	Netherlands
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	605674-x
ISSN	1873-2518 ; 0264-410X
ISSN (online)	1873-2518
ISSN	0264-410X
DOI	10.1016/j.vaccine.2019.02.036
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Article ; Online: Challenges in estimating influenza vaccine effectiveness.

Ainslie, Kylie E C / Haber, Michael / Orenstein, Walt A

Expert review of vaccines

2019 Volume 18, Issue 6, Page(s) 615–628

Abstract: ... ...

Abstract	Introduction
MeSH term(s)	Asymptomatic Infections ; Humans ; Incidence ; Influenza A virus/immunology ; Influenza Vaccines/immunology ; Influenza, Human/epidemiology ; Influenza, Human/prevention & control ; Observational Studies as Topic ; Randomized Controlled Trials as Topic ; Research Design ; Vaccination
Chemical Substances	Influenza Vaccines
Language	English
Publishing date	2019-05-31
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	2181284-6
ISSN	1744-8395 ; 1476-0584
ISSN (online)	1744-8395
ISSN	1476-0584
DOI	10.1080/14760584.2019.1622419
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Article ; Online: Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization.

Miura, Fuminari / Leung, Ka Yin / Klinkenberg, Don / Ainslie, Kylie E C / Wallinga, Jacco

PLoS computational biology

2021 Volume 17, Issue 12, Page(s) e1009697

Abstract: For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to ... ...

Abstract	For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.
MeSH term(s)	Age Factors ; Algorithms ; COVID-19/epidemiology ; COVID-19/immunology ; COVID-19/prevention & control ; COVID-19 Vaccines/supply & distribution ; COVID-19 Vaccines/therapeutic use ; Computational Biology ; Computer Simulation ; Health Care Rationing/methods ; Health Care Rationing/statistics & numerical data ; Humans ; Mass Vaccination/methods ; Mass Vaccination/statistics & numerical data ; Netherlands/epidemiology ; Pandemics/prevention & control ; Pandemics/statistics & numerical data ; SARS-CoV-2/immunology ; Vaccination/methods ; Vaccination/statistics & numerical data
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2021-12-13
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1009697
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Article ; Online: A Dynamic Model for Evaluation of the Bias of Influenza Vaccine Effectiveness Estimates From Observational Studies.

Ainslie, Kylie E C / Shi, Meng / Haber, Michael / Orenstein, Walter A

American journal of epidemiology

2019 Volume 188, Issue 2, Page(s) 451–460

Abstract: Given that influenza vaccination is now widely recommended in the United States, observational studies based on patients with acute respiratory illness (ARI) remain as the only option to estimate influenza vaccine effectiveness (VE). We developed a ... ...

Abstract	Given that influenza vaccination is now widely recommended in the United States, observational studies based on patients with acute respiratory illness (ARI) remain as the only option to estimate influenza vaccine effectiveness (VE). We developed a dynamic probability model to evaluate bias of VE estimates from passive surveillance cohort, test-negative, and traditional case-control studies. The model includes 2 covariates (health status and health awareness) that might affect the probabilities of vaccination, developing ARI, and seeking medical care. Our results suggest that test-negative studies produce unbiased estimates of VE against medically attended influenza when: 1) Vaccination does not affect the probability of noninfluenza ARI; and 2) health status has the same effect on the probability of influenza and noninfluenza ARIs. The same estimate might be severely biased (i.e., estimated VE - true VE ≥ 0.20) for estimating VE against symptomatic influenza if the vaccine affects the probability of seeking care against influenza ARI. VE estimates from test-negative studies might also be severely biased for both outcomes of interest when vaccination affects the probability of noninfluenza ARI, but estimates from passive surveillance cohort studies are unbiased in this case. Finally, VE estimates from traditional case-control studies suffer from bias regardless of the source of bias.
MeSH term(s)	Bias ; Epidemiologic Methods ; Health Knowledge, Attitudes, Practice ; Health Status ; Humans ; Influenza Vaccines/immunology ; Influenza, Human/epidemiology ; Models, Statistical ; Observational Studies as Topic/standards ; Respiratory Tract Diseases/epidemiology
Chemical Substances	Influenza Vaccines
Language	English
Publishing date	2019-01-07
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2937-3
ISSN	1476-6256 ; 0002-9262
ISSN (online)	1476-6256
ISSN	0002-9262
DOI	10.1093/aje/kwy240
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