The 2017-2018 Flu season is worse than the recent ones. Simply put, in the winter of 2017-18, more people are infected with the flu virus than in previous winters. The best way to protect against the flu is to get the yearly vaccine.
A bit of background context on the flu virus and the flu vaccine development (feel free to skip)
The reason why each year there is a different flu vaccine is that the flu virus mutates relatively often and last year’s vaccine doesn’t protect against this year’s version of the flu virus.
The relatively fast mutations of the flu virus make the development of flu vaccines a decision under uncertainty. In order to get the new vaccine to market in the beginning of the next flu season (end of the year), the research work is done in the beginning of the year (6-9 months before the flu season starts).
This implies that researchers can’t know for sure which version (mutation) of the flu virus will affect the population. Thus, researchers estimate which 2-3 versions of the flu virus are most likely to strike.
The best estimates don't mean certainty. The development of flu vaccine and its effectiveness involve probability thinking and (some) uncertainty.
In the 2017-18 flu season, the large number of flu cases suggests that the vaccine is less effective than in other years.
From a decision-making psychology perspective, US Public Health spokespeople communicate the flu vaccine’s effectiveness in a severely flawed manner.
They mention the "Guesstimate" 30% as the effectiveness of this year’s flu vaccine.
The “Guesstimate” part is understandable because the 2017-2018 flu season is not over yet and centralizing and analyzing data is slow.
A thirty percent effectiveness of the flu vaccine is exceptionally vague. The ordinary citizen who’s not a specialist in epidemiology naturally asks:
“What does that mean? If I get the flu shot, I get only 30% of the symptoms? Or do I have a 30% chance of getting the flu?”
An analogous confusion is presented by Gerd Gigerenzer in his book “Risk Savvy”. Professor Gigerenzer writes about the confusion generated by weather forecasts that say that for tomorrow there is a “40% chance of rain”. The common person doesn’t understand what that means. Some people believe that tomorrow it will rain 40% of the day. Others understand that tomorrow it will rain in only 40% of the area for which the forecast was issued. It actually means that in it rained in 40% of days with similar forecasts in the past.
Saying that the 2017-2018 flu vaccine is 30% effective is vague and confusing for two reasons.
First, the public doesn’t know what “effective” means for a vaccine. Does effectiveness mean full immunity – a vaccinated person doesn’t get the flu? Does it mean partial immunity – a vaccinated person who gets the flu develops less severe symptoms? Does it mean both – full immunity + partial immunity? Is there a score of effectiveness based on a formula that weights differently full and respectively partial immunity?
Second, people are rather bad at understanding and processing relative probabilities such as z%. Professor Gigerenzer’s research shows that framing risk information as natural frequencies such as “three out of ten” allows people to better understand and process the information.
Personally, I am not a medical practitioner and I do not know what vaccine effectiveness actually means. For the purpose of the next paragraph, I will assume that vaccine effectiveness means both full and partial immunity.
The guesstimate of 30% effectiveness of the 2017-18 vaccine could have been reframed as:
Based on the available data, we estimate that three out of ten people who received the flu vaccine would either not get the flu or experience a milder form of the disease.
Public authorities (especially those in healthcare) must communicate to ordinary citizens in ways in which ordinary citizens understand the message. Communicating risk information to the general public is a bit more complicated than just throwing around percentages. Needless to say that there is a lot of room for improvement.