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Evaluation of the Effectiveness of Flu Vaccines



“Discuss the effectiveness of the flu vaccines including cost, prevention rate and at risk groups.”


“Beat flu before it beats you!”

(NHS Wales, 2018)

Doctors’ surgeries are full of posters urging patients to protect themselves with the seasonal influenza vaccination. Last year a record 14 million people in England and over 800,000 people in Wales were vaccinated (Vaccine Knowledge project, 2018; Public Health Wales, 2018) yet the number of influenza cases reported was at its highest since the 2009 pandemic (Public Health Wales, 2018). Behind the slogans, questions remain about the efficacy of the influenza vaccinations.

Influenza is “an acute systemic viral infection that primarily affects the respiratory tract” (Walker et al, p.319). Seasonal influenza occurs in the winter months in temperate climates. Four different seasonal influenza virus groupings are cited, A, B, C and D – each consisting of “seven or eight RNA segments enclosed in an envelope of proteins” (History of vaccines, 2018). As influenza D is not contractable by humans and influenza C “causes milder infections”(WHO, 2014), only influenza A and B are part of vaccination programmes in the UK.




Variations in the haemagglutinin (H) and neuraminidase (N) glycoproteins on the surface of the virus (Walker et al, p.319 result in antigenic drift as the strain mutates from the ancestor strain. The host may not always recognise the new mutated virus and antibodies to previous strains are not effective. (History of vaccines, 2018). Influenza B can only mutate by antigenic drift so its viral evolution is more gradual (CDC 2018, Nobushawa and Katushiko 2006). However, influenza A is also capable of antigenic shift when two or more strains combine, resulting in a virus with a different H or N type to the ancestor strain ie AH2N3. Influenza A is unique as it infects a wide variety of animals as well as humans (History of vaccines, 2018). Antigenic shift occurs when an influenza A virus is transmitted to another animal and mutation happens within the host. The spread of the new strain is determined by the ease with which it can transmitted from human to human. By contrast, influenza B is divided into strains alone, for example, in the 2017/2018 season, influenza B/Yamagata was noted as being the dominant B strain across Europe (NHS Wales, 2018)

Figure 1: Proportion of influenza (sub)types by study, Europe, 2017/18

(Eurosurveillance, 2018)

(n = 6,979)

DK: Denmark study; ES: Spain study;

UK: United Kingdom study; EU-H: European hospital-based multi-country

I-MOVE+ study; EU-PC: European primary care-based multi-country I-MOVE/I-MOVE+ study.


a

Includes two influenza A(H1N1)pdm09/B co-infections; 98 of influenza A(H1N1)pdm09, 122 of A(H3N2) and 454 of B cases were also in ES.

Health authorities first determine what strains are to be vaccinated against and who is to recieve them. The former is based on WHO recommendations which follow global influenza activity (WHO, 2018). As it takes 6-8 months for the vaccine manufacturers to produce the vaccine (Publichealthmatters, 2018), any changes in the virus detected during this period cannot be replicated in the vaccines. Vaccine effectiveness is thus heavily determined by prediction and matching of influenza strains ahead of the season.


NHS guidelines recommend vaccination if:

“…you are 65 years of age or over, are pregnant, have certain medical conditions, are living in a long-stay residential care home or other long-stay care facility , receive a carer’s allowance, or you are the main carer for an elderly or disabled person whose welfare may be at risk if you fall ill”                                                                      (NHS, 2018)

Additionally, vaccines are offered to children over 6 months with long term health conditions, all children between the ages of 2 and 17 and recommended for health and social care workers (NHS, 2018). The vaccinations offered to different groups vary. During the UK influenza season 2017/2018, three different vaccines were used. Trivalent vaccines, offer protection against two strains of influenza A and one influenza B whilst quadrivalent vaccines offer protection against two strains of both A and B influenza. Vaccinations for children aged 2 – 17 use a live attenuated quadrivalent vaccination in the form of a nasal spray rather than injections. People over 65 are given an adjuvanted trivalent vaccine which “help to strengthen and lengthen the immune response to the vaccine.” (Vaccine Knowledge Project, 2018).

With such a spectrum of vaccinations being used on different groups of the population, one begins to build a picture of the complexity of assessing their effectiveness. One of the leaflets handed out in GP surgeries in Wales, states “Flu vaccine usually prevents flu in 4 to 6 people in every 10 who have it.”(NHS Wales, 2018). The inference is therefore that conversely exactly the same number of people who are vaccinated would be affected by the flu. Where are the figures behind the campaigns (Figure 1), and indeed their confusion, being drawn from?

The challenge of compiling, disseminating and indeed making sense of data related to vaccines is apparent in Figure 3 below. However, bright graphics highlighting the rising vaccination uptake cannot counter the fact that the dominant influenza types were mismatched with those in the vaccines.

Figure 1: Main flu leaflet

(NHS Wales, 2018)

The report itself did not have the sufficient end of season estimates for vaccine effectiveness (VE) to draw its own conclusions which raises further questions over the usefulness publishing at this stage and being  put in the public arena. Instead it drew on an interim report from five European countries where VE varied depending on influenza types (the same strains were dominant as in the welsh report) with estimates below 8% for the dominant A(H3N2) and “VE against all influenza ranged between 25 and 52% among all ages”.  (Rondy et al, 2018). In the US, during the same period, “The overall vaccine effectiveness …against both influenza A and B viruses is estimated to be 40%” (CDC, 2018). This is a very variable figure as shown in Figure 4.

Figure 3: Graphic from Annual Influenza Report (Public Health Wales, 2018)

Figure 4: Effectiveness of Seasonal Flu Vaccines from the 2004-2018 Flu Seasons (CDC, 2018)

However, we should also consider that analysis of observational data is one way of extrapolating information but it is far from the standards of a clinical trial. Systematic reviews, such as those carried out by the independent, not for profit Cochrane review team, provide an alternative. Nonetheless, poor study design of many trials alongside questions of bias, notably from industry funded trials, raised concerns over the certainty of their evidence. In 2009, of 270 studies reviewed…the team, led by Dr.Jefferson “ found that only 5% of these studies were reliable, had reliable design and were reliably carried out”(Science-based medicine, 2013). Additionally, there is a lack of clarity around the distinction between influenza and influenza like illness (ILI), caused by up to 200 different viruses as both produce similar symptoms and can only be distinguishable with laboratory testing. Dr. Jefferson summarises“…the actual threat is unknown (but likely to be small) and so is the estimation of the impact of vaccination.”

Nonetheless, the team have published reviews on the moderate level evidence found and conclude that 71 healthy adults would need to be vaccinated to prevent one influenza case. Evidence did not show whether vaccines offered protection to pregnant women (Jefferson et al, 2018). The Cochrane review looking at healthy children was based on RCTs yet once more flagged up questions over bias and study design. Nonetheless, evidence suggests that VE is higher amongst healthy children than adults, with five children needing to be vaccinated to avoid one case of influenza (Jefferson et al, 2018). Assessing vaccine effectiveness in the elderly is an inherently ethically challenging area and “there is evidence for the presence of bias in available observational studies…and that current adjustment methods could not adequately control it” (Trucchi, 2015). The Cochrane review concluded that, on the data analysed, thirty people would need to be vaccinated to one case of influenza, nonetheless “the impact of influenza vaccines in older people is modest, irrespective of setting, outcome, population, and study design” (Jefferson et al, 2018

The implementation and development of influenza vaccination policy also has an economic consideration. Yet cost effectiveness shares the challenge inherent in this area – notably, “poor evidence on vaccination efficacy among people who

are most at risk of complications if they become infected with the flu.” (Franklin and Hochlaf, 2018). This translates as high demand amongst the elderly who are shown to be least protected by vaccination, and such “costs of delivering the vaccine outweigh the benefits” (Franklin and Hochlaf, 2018). It is hardly surprising that NHS policy is aimed at increasing vaccine uptake amongst children (Public Health England, 2018), where the available evidence points more strongly to efficacy (Osterholm et al, 2011). Franklin and Hochlaf’s study attempted to elucidate the complexity of such cost-benefit analysis, beginning with cost of coverage.

Figure 4: Cost of vaccination programme with current and 75% coverage (Hochlaf and Franklin, 2018)

Different scenarios are envisaged with increasing coverage and efficacy leading to fewer hospitalisations, premature deaths, GP visits and sick days. Scenario 1 corresponds to figures from 2016/2017 season, whilst scenario 3 imagines “an ideal scenario where both coverage and efficacy are plausible”. (Hochlaf and Franklin, 2018). Only in this hypothetical scenario is a positive cost-benefit shown.

Figure 5: Net cost savings of different vaccination scenarios (Hochlaf and Franklin, 2018)

Given the considerable pressures that the NHS is under, particularly during the winter months, it is understandable why emphasis should be placed on reducing burden from influenza cases. However the study above suggests that this should be better targeted since vaccination of the elderly does not confer net cost savings. It is also worrying to note that increased vaccination uptake does not necessarily decrease hospitalisation or GP visit numbers – as indicated by last year’s rise in both vaccination and influenza and ILI cases (Public Health Wales, 2018) as well as Cochrane reviews (Jefferson, 2018).  Indeed there is evidence to suggest that influenza vaccination may increase the risk of non-influenza respiratory infections (Cowling et al, 2012).

Lack of any new trials means that the annual Cochrane reviews have been stabilised and not been updated since 2010, leading Dr. Jefferson to damningly reflect that they:

“… will remain as a testimonial to the scientific failure of industry and governments to address the most important clinical outcomes for patients.” (Jefferson, 2018)

Without high quality and low bias data, vaccine effectiveness remains difficult to assess in terms of its prevention rate, cost and efficacy across different groups. Whilst slogans abound and millions are spent, scientific evidence is short and “beating the flu” seems a hollow campaign cry in place of informed policy-making.

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