DOES INFLUENZA VACCINATION OF HEALTHCARE WORKERS PREVENT TRANSMISSION WITHIN CARE HOMES?

This review was co-authored by Dr. Frederik Feys.

INTRODUCTION

One of the most common types in human infection are the highly transmissible influenza respiratory viruses (types A, B and C) inducing mild to severe symptoms: fever, muscle pains, headaches, sore throat, respiratory aches and general fatigue.  Influenza is a major cause of winter deaths in Europe and associated with high rates of mortality amongst OAs in LTRCs, known to be well-confined settings inducing rapid spread of the virus (Janafi et al. 2017).  OAs are vulnerable due to comorbidities as existing chronic diseases become worse in intensity (Constantino and Vitale 2016).

VACCINES

Hay et al. (2001) argue that a major feature of influenza viruses is their ability to change genetic strains and develop into a novel virus subtype bypassing human immunity.  As vaccinations are developed yearly, on basis of changing strains within a period of 6 months prior to the release of the vaccine, they might be ineffective.  If strains in the vaccine are not matched sufficiently with the mutated virus, efficiency may be limited (Jiménez-Jorge et al. 2012).

OLDER ADULTS

The population under investigation are OAs being 60 years of age or older and residing in a long-term care institution.  65 years and older is the age-frame widely accepted to define people at greater risk of developing diseases and comorbidities (CDC 2017).  Thomas, Jefferson and Lasserson (2016) suggest using 60 years of age as a benchmark as people also tend to seek placement in specialised facilities if prematurely struck by life-changing processes.  Preference is given in this report using ‘older adults’ instead of ‘elderly people’ or ‘geriatric residents’.

VACCINE EFFICACY IN OLDER ADULTS

Influenza Outbreak Research

Camelloni et al. (2010) performed a cohort-study evaluating vaccine efficacy (VE) of a trivalent vaccination in one LTRC in Umbria (Italy).  Despite vaccination, 43.4% became infected.  The vaccine did not lead to the minimum of 60% level of protection as required.  Potential flaws are noticed in the analyses.  Recalibrating the non-parametric data to fit the t-test may have been unnecessary as a Wilcoxon/Man-U-Whitney-test would have fitted the purpose as it does not require the assumption of a normal distribution.  Also, the use of a Chi-square is questionable as it follows the central limit theorem (Statsoft 2017).

During the 2011-2012 influenza season, three LTRCs in Spain were investigated by Castilla et al. (2012) after a reported influenza-like illness (ILI) outbreak.  ILI is defined as the onset of a general symptom (fever and muscle aches) in combination with any respiratory symptom (cough, soreness of throat or respiratory problems).  The vaccination rate ranged from 82% to 97% in 611 residents, the VE was estimated at 50% and 57 OAs were confirmed by laboratory testing to have total vaccine failure.

The retrospective cohort-study by Castilla et al. (2012) used non-parametric testing with the two-tailed Fisher’s exact test which is more defendable as an approach (du Prel et al. 2010) than the recalibration of data by Camilloni et al. (2010).

Immunosenescence or Failing to Convert to Antibodies

A decline in cellular response capacity leads to less immune responsiveness from the humoral system and is called immunosenescence (IS) (Haq and McElhaney 2014).  Haralambieva et al. (2015) performed fundamental immunological laboratory research; investigating associations between vaccination, age and IS in 106 healthy OAs (50-74 years old) using blood samples and analysing them at baseline and after 3, 28 onto 75-days post-intervention.  The seroconversion rate (immunity) was limited to 39% after 28 days. Researchers used non-parametric statistical analysis due to skewness in distributions. Wilcoxon sign rank test and Friedman rank sum were applied.  To assess correlation, Spearman’s test was used with a p-value <0.05.

Covariates were analysed with ANCOVA.  The median age of the sample was 59.7 years, with 61,3% males and 38.7% females.  The strength of this study lies in the extensive investigation of humoral variables.  This robust study underpins immunosenescence within a relatively young sample of OAs.

The more age increases, the more difficult seroconversion leads to protection (Haralambieva et al. 2015). Yang et al. (2020) found OAs having faces previous natural infections remain at high protective levels, enhanced by vaccination.

VE in OAs appears more limited than in younger populations.  Informing stakeholders about the VE and promoting PPMs as an alternative can be considered (De Serres et al. 2017).

FLAWED DATA AND METHODOLOGICAL BIAS

Influenza vaccination in HCWs is recommended by the WHO, Centre for Disease Control and Prevention (CDC) in the USA and by the European Centre for Disease Prevention and Control (ECDC) within the European Union (EU).  The CDC recommends all HCWs to be vaccinated as the ECDC aims at reaching 75% coverage within the EU (CDC 2016; ECDC 2017; WHO 2017b).

The WHO refers in its Seasonal Influenza Report on HCWs and the impact on OAs (WHO 2012) to four clustered-Randomized Controlled Trials (cRCTs); Carman et al. (2000) (643 citations), Hayward et al. (2006) (286 citations), Lemaitre et al. (2009) (129 citations) and Potter et al. (1997) (532 citations).

RCTs are considered the ‘golden standard’ in evidence hierarchy (Bothwell 2016), although cRCTs have reduced statistical efficiency (Donner and Klar 2004). Aforementioned cRCTs have been referenced a total of 1590 times in other scientific publications, hence the recommendations of the CDC and ECDC based on these WHO guidelines in vaccinating HCWs in LTRCs (CDC 2016; ECDC 2017).

Potter et al. (1997) recommend vaccinating HCWs in LTRCs as a preventative measure against influenza in OAs.  A decrease in mortality was noted in the Carman et al. (2000) study which was published in The Lancet, where they evaluated the VE of HCWs and related mortality in OAs in LTRCs.  Hayward et al. (2006) concluded vaccination of 8 HCWs could prevent 1 death among OAs residing in a LTRC.  Finally, the fourth cRCT by Lemaitre et al. (2009) argued a 20% lower mortality of OAs within the vaccinated HCW group, supporting the call for overall vaccination of HCWs in LTRC.

Critique on the Four Most Cited Relevant cRCTs

It is observed that recent evidence undermines guidelines and needs addressing, it may change approaches in tackling viral outbreaks.

Evaluating the cRCTs using the ‘Grades of Recommendation’ by the Joanna Briggs Institute (2017) we conclude that the quality of the four aforementioned studies are weak as not all included cases of influenza were laboratory confirmed.

The Cochrane Database of Systematic Reviews published a review by Thomas, Jefferson and Lasserson (2016) entitled: “Influenza vaccination for healthcare workers who care for people aged 60 or older living in long-term care institutions”.

The authors identified a total of 2815 articles and after selection withheld five studies, amongst those the four cRTCs as previously cited.  Selection bias was found in Potter et al. (1997) and Carman et al. (2000). Potter et al. (1997) included nearly 600 cases of suspected viral illness and suspected deaths related to influenza and deaths from all causes.

In both studies performance bias was detected as vaccination levels of HCWs only ranged from 33% to 67% of staff, also Lemaitre et al. (2009) may have been biased due to a vaccination level of 51% in HCWs.  The Potter et al. (1997) study corrected statistically for clustering; the other three studies did not, which makes them vulnerable to statistical bias.  Furthermore, no study applied a double-blinded approach. Thomas, Jefferson and Lasserson (2016) conclude a high risk of bias in all four studies as analysis of pooled data showed no evidence of positive outcome.

A review by De Serres et al. (2017) critically analysed the evidence presented by Thomas, Jefferson and Lasserson (2016) using this as a basis for further investigation.  For their analysis, the authors looked at VE, outcomes and the mathematical principle of dilution of the four cRTCs.

De Serres et al. (2017) suggest that only laboratory-confirmed influenza infections should have been used as merely fever, coughs and other respiratory problems may occur through infection of other microorganisms.  Authors further argue comorbidities contribute to ILI-related deaths and these figures will influence the basic mathematical principle of dilution.

They claim this principle to govern the inverse relationship between influenza-related disease reduction and the percentage of contribution of comorbidities. The more comorbidities contribute to the outcome, the lower the percentage reduction of the targeted intervention must be.  This requires the percentage reduction of VE to be lower when comorbidities are included in a study outcome than when only influenza infection is calculated.  They argue when two groups are compared evaluating the positive effects of vaccination; the reduction in percentage will be proportional to the absolute difference (AD) in coverage when comparing the two groups.  Following formula is proposed (De Serres et al. 2017):

% reduction in outcome= (% VE) x (% influenza outcome) x (AD% in vaccine coverage)

The investigated cRCTs did not acknowledge this principle, which De Serres et al. (2017) consider a de facto major flaw and used this to recalculate the findings of the four cRCTs.  They noticed percentage reductions for non-laboratory confirmed influenza were 8 times higher in the study of Hayward et al. (2006) compared to the predicted values (De Serres et al. fig.1).  The other cRCTs also showed 3 to 4-fold higher results.

Fig 1.: Reported and predicted percentage reductions in patient outcomes between intervention and controls among cRTCs assessing indirect patient benefits from increased influenza vaccine coverage of healthcare workers in long- term care facilities. (Δ VC = AD in vaccine coverage; LCI = laboratory-confirmed influenza; ACM = all-cause mortality) (De Serres et al. 2017).

Evaluating indirect mortality prevention, possibly induced by the HCWs, they calculated the number of needed vaccinated individuals (NNV) using the figures of the previously mentioned cRCTs.  The NNV is commonly defined as absolute risk reduction (Irwig, Irwig and Trevena 2008).

Number of unvaccinated HCWs
NNV= _____________________________________________________

Number of patient deaths preventable by HCWs vaccination

After their recalculation, De Serres et al. (2017) conclude HCWs vaccination could have only reduced the negative outcomes for 9%, leaving more than 80% of reductions unaccounted for.  They further notice Hayward et al. (2006) to conclude that 8 HCWs should be vaccinated to prevent 1 death.  De Serres et al. (2017) extrapolated this figure based on 5.5 million HCWs in the US, taking the principle of dilution and NNV into account and concluded almost 700.000 deaths could be prevented each year. This is unrealistic, knowing the specific mortality rates have never been higher than 49.000 for influenza in the US.

The authors were surprised that other scientific literature never used the NNV in reviewing existing data.  De Serres et al. (2017) refute enforced vaccination of HCWs as evidence is insufficient to conclude this being of preventative importance for OAs in LTRCs.

As De Serres et al. (2017) state, the current recommendations are based on little evidence, therefore it is suggested to shift focus towards PPMs and keeping vaccination voluntary.

COST-EFFECTIVENESS OF INFLUENZA VACCINATION

A systematic review (Shields, Elvidge and Davies 2017) on health economics of seasonal vaccination in OAs included 8 articles out of 326 that were eligible to set criteria.  Cost-effectiveness remains unconfirmed as they found methodological flaws and lack of robust data.  Calculations ranged from €1,065 per quality-adjusted life-year (QALY) up to €572,305 per QALY.

Comparisons were difficult as studies used many different variables.  Authors did not encounter one study that used the proposed WHO framework on health economics.  Peasah et al. (2013) also conducted a systematic review; out of 27 studies only 8 reported a cost-effectiveness in vaccinating OAs based on the international accepted threshold of $50,000/QALY.  Authors found no data from developing countries.

Cost-effectiveness is still very much a point of debate as researchers do not follow a standardized framework collecting data (Shields, Elvidge and Davies 2017).  Hodgson et al. (2017) note the incremental cost-effectiveness ratio (ICER) should be less than £20,000 per QALY in the UK to be deemed cost- effective in influenza vaccination, whereas Brogan et al. (2016) argue $50,000 (£37,500) is acceptable in the US and Neumann, Cohen and Weinstein (2014) claim a threshold of $150,000 per QALY (£112,500) to be more realistic.

No studies have been retrieved evaluating cost-effectiveness in vaccinating HCWs to prevent infection in OAs.

SOCIAL FACTORS INFLUENCING VACCINE UPTAKE

Age, higher education levels, high income/social class, underlying diseases and known vaccinated peers are some of the predictors of higher uptake (Shaham et al. 2020).  However, other research shows that higher status may not be the key driver as self-awareness of potential underlying risks is of great importance (Isler et al. 2020).

Within the population of HCWs believe of vaccine-efficacy, peer-pressure and facing chronic disease enhance vaccination rates.  Personal reflections and perspectives take a role in developing underlying behavioural patterns.  HCWs personally focusing on a healthy lifestyle see guidance in human physiology and the strength of natural ways of combatting flu-illness (Asma et al. 2016).

Furthermore, if the social context in which HWCs live shows a positive attitude towards vaccination HCWs data show a higher responsiveness.  On the contrary leads critical scepticism to lower uptake (Konstantinou et al. 2021).  Social networks, peer-information and peer-pressure appear to guidance decision making more than the science behind the vaccinations.

Although our analysis shows that influenza vaccination does not appear to be sufficient in preventing transmission to OAs, recent research about vaccine hesitancy is still based on the widely (falsely) accepted premises that influenza vaccination is a main driver in mitigating outbreaks.  From this perspective behaviour is also evaluated in a recent review which concludes vaccine-hesitancy is driven by: false beliefs, disinformation, ‘the believe the natural immune system can handle it’, a.o.  The supposition in the use of words by Guillari et al. (2021) as such seems biased as it starts form preconceived ideas around influenza-vaccination that have been refuted as our further analysis will show.

PSYCHOLOGICAL FACTORS AND RESPONSIVENESS TO INFLUENZA VACCINATIONS

A plethora of psychological and behavioural factors increase the risk of non- responsiveness to vaccines.  For example, in OAs having an influenza vaccine, the immediate inflammatory response usually lasts a few days.  But in those who are depressed it gets prolonged (Glaser et al. 2003).  Studies (Glaser et al. 1998; Kiecolt-Glaser et al. 1996; Vedhara et al. 1999) found that stress reduced the secondary response to influenza vaccination.  This is quite provocative.

It suggests that OAs confronted with an enduring and severe stressor develop antibodies to influenza immunizations at a slower rate (and possibly less antibody overall) than non-stressed control subjects.  These data suggest that stress at immunization is associated with decreased protection up to 6 weeks after influenza immunization.

In a sample of OAs, bereavement in the year before getting a renewed influenza vaccination predicted a poorer antibody response after 1 month, whereas those who were married and had high marital satisfaction had a stronger antibody response (Phillips et al. 2006).

In previously vaccinated OAs, those with lower BMI had higher antibody responses, but only if they were also low in distress.  Somehow surprisingly, distress was more strongly associated with larger post-vaccination interleukine-6 levels at older ages (~ 80 years) (Segerstrom et al. 2012).

The findings from Kohut et al. (2002) suggest that there is an association between physical activity, diet, psychosocial factors, and the immune response to influenza immunization in OAs; e.g. physically active OAs had better anti- influenza antibody levels.  This benefit of being fit at older age was also found by Keylock et al. (2007).

In a study by Vedhara et al. (2003), influenza vaccination after 8 weeks of cognitive-behavioural stress management (sessions 1 hour a week) for chronically stressed OAs, a large effect was seen on antibody responses. Mindfulness-based stress reduction (MBSR) or exercise in a younger group of OAs (~60 years), yielded no significant antibody response improvements. However, both exercise and MBSR reduced the number of days sick from all- cause acute respiratory infection illness (Hayney et al., 2014).  Yang et al. (2008) found 20 weeks of combined Taiji/Qigong meditation (3 x 1 hour sessions per week) in OAs resulted in improved antibody levels in comparison to a control waiting list group.

STRENGTHENING YOUR NATURAL IMMUNITY AGAINST INFLUENZA

The conventional Western immunity doctrine in which antigens lead to an immune response involves many molecules enhanced by plant and algal polysaccharides as described in Chinese medicine (Ai et al., 2020; Zhang et al. 2020).

Starch (e.g. potatoes, rice, peas, corn, beans) cellulose rich and chitin do not appear to have biological activity, rather high plant polysaccharides (also called non-starchy vegetables) like: spinach, artichoke, asparagus, broccoli, sprouts, cabbage, carrots, salad greens and tomato are proven to support your immune response (Zhang et al. 2020).

In a broader sense, Asian oriented herbal treatments seem to contribute to some extent in the prevention of influenza-like illnesses (Shahrajabian et al. 2020).

Western medicine primarily promotes physical exercise (Cao Dinh et al. 2017; Laddu et al. 2021) and some supplementary vitamins (Gombart et al. 2020; Pecora et al. 2020) although Wang et al. (2019) conclude in a review that evidence remains limited on the real-life impact of supplementary uptake of vitamins and micronutrients in strengthening the immune system.

Ayurveda medicine contributes on several levels within an integrative approach consisting of a decent sleep pattern combined with balanced food, physical exercise and attention for psychological wellbeing which combined lead to a better immune response (Thakur et al. 2021).  Ayurveda as a holistic approach has some guiding evidence, however research also points towards limited knowledge of the physiological backgrounds (efficacy and safety) of some therapies (Umesh et al. 2021).

CONCLUSION

Influenza vaccination in HCWs shows little evidence-based underpinning as a preventative measure in controlling possible outbreaks or limiting mortality rates amongst OAs. Vaccine-uptake within HCWs should not be guided by social or peer-pressure.

Immunosenescence or the declining natural capacity to create antibodies, a process notably starting within age-specific group above 50, is hardly ever considered as a potential issue.  Moreover, age appears strongly associated with declining counts of antibodies.  We strongly suggest that healthcare providers recognize the effect of immunosenescence and the consequences this shall have on the efficiency of ILI-related vaccines within both the elderly and older HWCs.

Evidence-based practice should inform HCWs based on substantiated research. Unfortunately, many ILI-like vaccines campaigns and policies seem to be based on unsubstantiated science and require reevaluation.  The latter should lead to the dissemination of correct EBM-evidence regarding vaccinating HCWs working in elderly care homes.  We may assume these findings to be adequately valuable for the public at large, as some evaluated variables (workplace, age) are not necessarily workplace-specific.

We further suggest a focus on preventive approaches that aim at ameliorating natural immunity in populations without underlying diseases. Integrative health promotion should form the basis of any related policy.

Cost-benefit analysis on vaccinating HCWs as a preventative measure appear not to lead to many benefits for public health, nor for the individuals involved.  There is an absolute need for further cost-benefit research aimed at evaluating preventative measures in reducing transmission of ILIs within vulnerable population groups.

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