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Being critical of data, even when you agree with it


One of the most infuriating things about research is when I come across widely shared images of data across different social media platforms. While I love how quickly we are able to share information and data and learn about so many topics that we previously had no interest it, it has become so easy to create an easily digestible image using data to help prove whatever point you want and no one seems to fact check them when they back up your argument.

For example, here’s a widely shared image circulating the vaccine-hesitate Facebook groups.


Chart highlighting the mortality of vaccines over the diseases they protect against.

Typo non-withstanding, on the surface this chart seems to make a powerful point. The seem to rely on both data from the Center for Disease Control and Prevention (CDC) and the Vaccine Adverse Event Reporting System (VAERS). Seemingly, it appears that there is a greater chance of death from the vaccine than dying from the actual disease itself (except for the meningococcal B vaccine). This would be an amazingly powerful statement and chart, if only it wasn’t riddled with errors.

There is a long list of misteps with this chart but the three most egregious errors are with how chance of death is calculated, the reported numbers, and the assumption of zero deaths by a disease means that it is not a threat.

  1. The chance of death percentage in this chart is calculated as if every person in the US has been exposed to the vaccine and disease. This charts reports that 50 people died from the Hepatitis B vaccine and calculated the 0.00001572% from dividing 50 by 317 million (the estimated number of people in 2014). This number should be calculated from the number of people who received the vaccine in 2014. Similarly, the chance of death of the disease should be calculated using the number of people who contracted the disease in 2014, not the whole US population.

  2. The numbers reported are also simply wrong. There is no accuracy of the incidence numbers reported. For example, going to CDC’s website, they clearly state 50,622 people died from pneumonia in 2014, not 20 like this chart reports. This is consistent with other reported figures. CDC reports 76 cases of death from Hepatitis A in 2014, not 13. In addition, VAERS has its own issues of data validity as anyone can file an adverse reaction and these reports are not verified. While arguably, this means there could be an underreporting of cases, but there can also be an over reporting of cases as well if a person suspects a reaction is vaccine related but it is not. In addition, reported numbers for any given year reflect cases reported to VAERS that year, not the number of cases that occurred that year; you are able to report incidences well after the date they occur, but are included into the current year.

  3. While it is true that there have been no deaths in 2014 related to some of these diseases, like measles, this does not mean they are not a potential threat and this does not reflect incidence rate. The purpose of vaccines is to prevent the spread and contraction of communicable diseases. Arguably, if a vaccine is effective and disseminated into the population, we can see the incidence and mortality rate of that disease drop, like we have with measles, mumps, polio, and other childhood diseases. Therefore, reporting “0” cases of death related to polio does not mean we should stop vaccinating for polio in the US.

It took less than 30 seconds to perform a fact check on this chart. The point of this article is not to criticize vaccine resistant people, but to highlight the susceptibility of falling for these charts. It is fairly widely known that you can manipulate data and charts to tell different stories as easily as adjusting the x and y axis on a chart. As interest and fascination with fake news increases, fake and manipulated data and charts should be put under just as much scrutiny.

I picked a particularly easy image to dissect as most people believe vaccines are safe and effective, but we are much less prone to be critical of something that supports our values and our beliefs. If this chart highlighted the effectiveness of vaccines overtime, I would want you to be just as critical of it. There is a lot of finger pointing to the “other side” about how ridiculous they are for falling for fake news or fake charts like this, but we can all become victim to it. We see something that uses data that supports something we like and we immediately want to share it with our friends which continues the cycle. Be critical and proactive. Check out the source for yourself. Don’t just rely on and share a graphic someone put together.

Just think about how you would feel if someone fact checked you and proved that what you shared was incorrect. Take the minute to be critical. This has to be our first step in curbing the spreading of false information.

Originally posted on Medium

#Vaccines #Data #FakeNews

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