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Abstract

Background

Most reports of influenza vaccine effectiveness consider current-season vaccination only.

Aim

We evaluated a method to estimate the effect of influenza vaccinations (EIV) considering vaccination history.

Methods

We used a test-negative design with well-documented vaccination history to evaluate the average EIV over eight influenza seasons (2011/12–2018/19; n = 10,356). Modifying effect was considered as difference in effects of vaccination in current and previous seasons and current-season vaccination only. We also explored differences between current-season estimates excluding from the reference category people vaccinated in any of the five previous seasons and estimates without this exclusion or only for one or three previous seasons.

Results

The EIV was 50%, 45% and 38% in people vaccinated in the current season who had previously received none, one to two and three to five doses, respectively, and it was 30% and 43% for one to two and three to five prior doses only. Vaccination in at least three previous seasons reduced the effect of current-season vaccination by 12 percentage points overall, 31 among outpatients, 22 in 9–65 year-olds, and 23 against influenza B. Including people vaccinated in previous seasons only in the unvaccinated category underestimated EIV by 9 percentage points on average (31% vs 40%). Estimates considering vaccination of three or five previous seasons were similar.

Conclusions

Vaccine effectiveness studies should consider influenza vaccination in previous seasons, as it can retain effect and is often an effect modifier. Vaccination status in three categories (current season, previous seasons only, unvaccinated) reflects the whole EIV.

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This work is licensed under a Creative Commons Attribution 4.0 International License.
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2021-08-12
2024-04-19
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2021.26.32.2001099
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Simple models to include influenza vaccination history when evaluating the effect of influenza vaccination
<p class="citation"> <span>Citation style for this article:</span> <span class="meta-value authors"> <a href="/search?value1=Iv%C3%A1n+Mart%C3%ADnez-Baz&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Martínez-Baz Iván</a>, <a href="/search?value1=Ana+Navascu%C3%A9s&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Navascués Ana</a>, <a href="/search?value1=Itziar+Casado&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Casado Itziar</a>, <a href="/search?value1=Aitziber+Aguinaga&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Aguinaga Aitziber</a>, <a href="/search?value1=Carmen+Ezpeleta&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Ezpeleta Carmen</a>, <a href="/search?value1=Jes%C3%BAs+Castilla&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Castilla Jesús</a></span>. Simple models to include influenza vaccination history when evaluating the effect of influenza vaccination. <a href="/content/ecdc">Euro Surveill.</a> 2021;26(32):pii=2001099. <a href="https://doi.org/10.2807/1560-7917.ES.2021.26.32.2001099" title="doi link" target="_blank">https://doi.org/10.2807/1560-7917.ES.2021.26.32.2001099</a> <span class="ES_Article_citation"> <span class="generated">Received</span>: 29 May 2020;&nbsp;&nbsp; <span class="generated">Accepted</span>: 27 Oct 2020 </span> </p>
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