Medication

Swine flu vaccine predictions

Scientists have published research estimating how effective the swine flu vaccine will at reducing infection rates in the US this autumn. This research involves complex statistical modelling based on what is already known about swine flu and assumptions based on a range of flu vaccination strategies. The study suggests that strategies that aim to vaccinate everyone before the start of an autumn spread of the virus or of a phased vaccination at the onset of an autumn surge are likely to be effective as long as 70% of the population is vaccinated.

This type of complex modelling study is important for estimating the effects of epidemics and pandemics, and the best ways of reducing their effects. The results of such models are dependent on what assumptions are fed into them, and this is why researchers looked at what happened if they varied a number of assumptions in their models. Whether these models accurately predict what will happen is dependent on how closely these assumptions match the real situation.

This model aimed to estimate the effects of vaccination in the US, and therefore the underlying assumptions and results may not be representative of other countries, but its results will undoubtedly be of interest to policy makers planning vaccination strategies in both the US and other countries.

Where did the story come from?

Dr Yang Yang and colleagues from the University of Washington carried out this research. No sources of funding were reported for the study. It was published in the peer-reviewed journal, Science.

What kind of scientific study was this?

This was a mathematical modelling study that aimed to predict how effective potential swine flu vaccination strategies would be in the US.

The researchers estimated the transmission pattern of swine flu based on data on US flu-like illness rates during the early stages of the pandemic. They first used statistical models to estimate the probability that someone with swine flu will pass the infection on to someone else in the household. As an influenza A H1N1 outbreak seen in 1978-1979 was predominantly in children (which also seems to be the case in the current swine flu outbreak), the researchers then estimated how many children would be likely to contract the virus from a single schoolmate with swine flu, based on one school outbreak. They then estimated how many flu transmissions occur in both households and schools using data from household studies and modelling.

Using these parameters the researchers then created a complex statistical model to estimate the effects of the swine flu vaccine during the autumn of 2009. As there is not yet any data on how effective these vaccines will be the researchers based their calculations on the assumption that the swine flu vaccine had a similar efficacy to seasonal flu vaccines. They also assumed that two doses of vaccine would be needed, given at least three weeks apart.

To create their model, the researchers used data from various sources, including vaccine trials and observational studies. They modelled two separate scenarios varying how good a match there was between the vaccine and the circulating virus. They assumed that few people would have immunity to swine flu due to limited spread in the US during the spring and summer.

The researchers also created different models based on two different vaccination strategies. A universal vaccination of all individuals before the virus spread, and phased vaccination. The phased vaccination involved the vaccine being given either at the beginning of the spread or 30 days after the spread begins, and is either given to children first or gradually delivered to all individuals as the epidemic progressed.

Achieving an infection rate of 15% or less was considered to be successful, reducing in the impact of the epidemic to that of a “relatively mild seasonal flu epidemic”.

What were the results of the study?

The researchers estimated that there was about a 27% chance of a person with swine flu infecting another person in their household. This placed swine flu among the more infectious influenza viruses.
They estimated that a child with swine flu is likely to pass on the infection to an average of 2.4 schoolmates. Around 20% of flu transmissions were estimated to occur in schools, 30 to 40% in households, and the remainder in the general community, workplaces and other settings. Based on these figures the researchers estimated that on average one person with swine flu will infect between 1.3 to 2.1 other people, and that the average time between a person being infected and them passing the virus on was between 2.6 and 3.2 days.

Universal vaccination strategy
The researchers produced a number of models based on a universal vaccination programme before the spread of the virus in the US and the use of a vaccine that was a good match for the circulating virus. They calculated that only 70% of the population would need to have the vaccine to reduce the impact of the virus to that of a relatively mild seasonal flu epidemic (assuming that one person infected an average two other people or fewer).

Vaccinating 50% of the population would only be successful if the virus was slightly less infectious, with one person infecting an average of 1.8 people or fewer. Vaccinating 30% of the population in the  universal vaccination programme would not be enough to successfully reduce the infection rate to below 15% but could slow the spread of the virus if one person infected an average of 1.6 people or fewer.

If the vaccine was not a good match for the circulating virus then achieving 50-70% vaccination would only successfully reduce the infection rate to 15% or less if one person infected an average of 1.7 people or fewer, although it could still slow the spread of the virus if it was more infectious. Varying their assumptions about the efficacy of the vaccine would be did not affect these results.

Phased vaccination strategy
The researchers’ model suggested that phased vaccination achieving 70% coverage could have a large effect on reducing the spread of the virus, but would not delay the peak of the epidemic by much. If a phased vaccination was started 30 days after the start of the spread, the phased child-first vaccination strategy would successfully reduce epidemic spread as long as one person infected an average of 1.7 people or fewer.

A phased universal strategy would be similarly successful if it was initiated at the same time as the spread started, but would be less effective if started 30 days later. These results assumed a good match between the vaccine and the circulating virus. If the vaccine was not a good match, then phased child-first vaccination with a 30-day delay or phased universal vaccination with no delay would be effective mitigation strategies, as long as one person infected an average of 1.5 people or fewer.

What interpretations did the researchers draw from these results?

The researchers concluded that all of the vaccination strategies they modelled would successfully reduce the infection rate of the epidemic if they achieved 70% coverage of the population.

What does the NHS Knowledge Service make of this study?

This type of complex modelling study is important for estimating the effects of epidemics and pandemics and the best ways of minimising their effects. The results of such models are dependent on what assumptions are made and this is why researchers look at a range of assumptions in their models. Whether these models accurately predict what will happen is dependent on how closely these assumptions match the real situation.

This model aimed to estimate the effects of vaccination in the US, and therefore the underlying assumptions and results may not be representative of other countries. These results suggest that if a relatively high vaccination coverage in the population can be achieved this could reduce the impact of swine flu, and that slightly different strategies may still have similar effects. This study will undoubtedly be of interest to policy makers planning vaccination strategies in both the US and other countries.


NHS Attribution