Research Article: Increasing influenza vaccination rates via low cost messaging interventions

Date Published: February 14, 2018

Publisher: Public Library of Science

Author(s): Ernest Baskin, Joël Mossong.

http://doi.org/10.1371/journal.pone.0192594

Abstract

This article tests low cost interventions to increase influenza vaccination rates. By changing an email announcement sent out to employees in 2014 (n > 30,000), the following interventions are tested: incentives, attention to the negative impacts of not get vaccinated, and showing a map to the vaccination centers at the end of the email announcement. Only the map condition helped increase influenza vaccination rates. The use of low-cost interventions can improve influenza vaccination rates though not all interventions work as well as others in the field. In particular, while including maps helped increase vaccination rates, other factors such as negative impact reminders and incentives, which previous studies have found to be successful in the laboratory, did not.

Partial Text

Vaccinations are an important preventative measure for disease occurrence. In particular, they can provide protection against the influenza virus [1]. Symptoms of influenza include fever, cough, headache, sore throat, amongst others that can last from 3–7 days but can persist for weeks [2, 3], resulting in missed work and school [4]. These symptoms can also lead to the worsening of chronic diseases that could potentially lead to hospitalization and even death [3]. Due to the highly contagious nature of the influenza virus, vaccination is recommended and is the most effective preventative method [5] (recommended yearly by the Centers of Disease Control and Prevention for most Americans [6]).

Both models with and without interaction terms are reported in Table 2. All conditions as well as the percentage of participants who received an influenza vaccination in each condition can be viewed in Table 1. The full control condition revealed that 32.5% of the university community obtained the vaccination, which is consistent with data from prior years in terms of 30% to 33% vaccination participation. This is also consistent with CDC vaccination projections for the predominant age group in this sample. In both regressions, the only significant variable was the map condition indicating that providing a map increased the probability of getting vaccinated overall by about 2% resulting in approximately 600 additional vaccinations across the university.

The results suggest that, given an average employee sick rate of 20% without the vaccine and an average cost of $1000 per employee away from work due to influenza just in lost labor hours according to the Society for Human Resource Management, adding a simple map to the correspondence related to flu vaccination clinics could potentially save the university $120,000 per year [31]. This does not include any lost revenue from a job not being performed optimally or any costs related to potential comorbidities or physician visits related to influenza. Aside from cost savings, increasing vaccination rates can lead improved community health through the development of herd immunity and may increase general awareness of influenza’s impacts. The results are likely generalizable outside the influenza vaccination context to other public health initiatives that require community members to attend a specific location including STD screenings, blood donation drives, or retailers offering vaccinations to their consumers. However, when generalizing, it is important to consider differences between the community members in this data set and people that the results may be generalized to. The results shown here may have interactions with SES and education level as well as other variables and these variables may differ, on average, in other populations. The closest level of generalizability is likely to be other workplace settings. There may also be other community-wide interventions in the population under study that are unobservable though random sampling should diminish its effects on the results.

 

Source:

http://doi.org/10.1371/journal.pone.0192594

 

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