Snot Science: Stopping the sneeze | Science News for Students

Snot Science: Stopping the sneeze

How well does a tissue help stop a spew of snot?
Jan 30, 2019 — 6:30 am EST
a photo of a girl covering her nose with a paper tissue

We’ve all been told to cover our noses when we sneeze. But how well does it stop snot spread?

AnneMS/iStockphoto

Cold and flu season mean that sneezing and runny noses are everywhere you look. Standing far away might seem like protection from infection. But you have to step pretty far back. Some scientific studies have shown that droplets from a sneeze can fly up to eight meters (26 feet)! If you’re lucky, the sneezer will have a tissue handy. But does sneezing into a tissue really stop the snot? Science has the answer.

How far does a sneeze travel? We did an experiment to find out.
SSP/Explainr

In my very first DIY Science video, I asked how far a sneeze could travel and whether thick or thin snot traveled the farthest. I found that thin snot (using colored water as a stand-in, no real boogers involved) shot an average of three meters (9.8 feet). Thick snot (gelatin and corn syrup) only sprayed about a meter (3.3 feet).

If people are polite, though, they usually don’t just let a sneeze fly free. There’s an elbow or a hand in the way. If they’re very well prepared, they might have a tissue at the ready.

But tissues are flimsy, soft sheets of paper. Can something that tears so easily stop a virus in its tracks? To find out, I need to do another experiment.

Snotty studies

I’ll start with a hypothesis — a statement that I can test. I hypothesize that a tissue in front a sneeze will make snot fly a shorter distance than a free sneeze.

Instead of tickling the noses of a bunch of people to make them sneeze, I’m using a model of a sneeze. I filled a dropper with one milliliter of colored water. Then I squirted the dropper for my “sneeze.” To measure how far my “snot” flew, I used a plastic tarp marked every half meter (50 centimeters, or 20 inches).

a spreadsheet showing maximum distance, in centimeters, that snot flew with and without a tissue
This spreadsheet shows the maximum distance, in centimeters, that snot flew with and without a tissue in the way. 
B. Brookshire/SSP

Ideally, to detect a large difference I would repeat the experiment 26 times. Unfortunately, reality intervened, and I only had time for 12 repetitions of each sneeze type, tissue and no tissue.

Each time I squirted the dropper, I wrote down how far the farthest drop flew. That gave me the maximum distance for the sneeze. I also counted how many drops landed in each half-meter segment of tarp. That would tell me where the sneeze concentrated.

Booger blockade

The spreadsheet shows the maximum distance the sneezes flew, with and without a tissue. At the bottom I’ve calculated the mean — the average total distance — for each condition. For my no-tissue control, my sneezes spread a mean of 382 centimeters (150 inches), a little farther than in my previous study. With the tissue, the snot flew an average of 76 centimeters (29 inches).

These numbers seem very different, but to be sure, I need to do some statistics — tests to analyze data and interpret their meaning. In this case, I used a t test — a test used to find the differences between groups. I will be looking for two numbers. The first is a p value. This is a probability measure — or how likely it is that I would have found by accident a difference as big as the one I saw. Many scientists consider a p value of less than 0.05 (or a five percent chance) as statistically significant. There are lots of free sites that will do these calculations. I used this one.

This graph shows the maximum snot distance traveled with and without a tissue.
This graph shows the maximum snot distance traveled with and without a tissue.
B. Brookshire/SSP

The calculator told me that the p value for my data was 0.0001. That’s a 0.01 percent chance that this difference happened by accident. However, this doesn’t tell me how big the difference is in my data. To find that, I looked for a measure called Cohen’s d. I will need a standard deviation for this — a measure of how much the data spread around my means. You can find out more about that in one of my previous posts. I plugged the means, standard deviations and number of samples into this calculator.

My Cohen’s d value was 8.2. Generally, scientists define a Cohen’s d below 0.2 as a small effect size and above 0.8 as a large one. So this Cohen’s d is gigantic. A tissue, it turns out, makes a big difference.

Snot spread

The snot did not make it as far with a tissue as without. It also changed how the snot concentrated along the flight path. Below is the data for how many droplets fell per 50 cm (20 in) of tarp. I then took that data and created a graph to show what the two groups look like when compared to each other.graph showing how droplets distributed along the tarp with and without a tissue presentdata for droplet spread for snot with no tissuedata for droplet spread for snot with the tissue present

You can see that without a tissue, the snot droplets concentrate farther out, between 200 and 400 cm (79 and 157 in). With the tissue present, snot droplets concentrate much closer to the sneezer.

Of course, this isn’t a perfect study. I could run more trials, or I could use real noses with real sneezes. But this experiment still helped me test my hypothesis. I hypothesized that a tissue in front a sneeze will make snot fly a shorter distance than a free sneeze. My results appear to support my hypothesis. A tissue in front of a sneeze shortened the snot range.

So the next time someone sneezes and doesn’t cover their mouth, hand them a tissue. You’ve got science on your side.

Power Words

(more about Power Words)

average     (in science) A term for the arithmetic mean, which is the sum of a group of numbers that is then divided by the size of the group.

control     A part of an experiment where there is no change from normal conditions. The control is essential to scientific experiments. It shows that any new effect is likely due only to the part of the test that a researcher has altered. For example, if scientists were testing different types of fertilizer in a garden, they would want one section of it to remain unfertilized, as the control. Its area would show how plants in this garden grow under normal conditions. And that gives scientists something against which they can compare their experimental data.

data     Facts and/or statistics collected together for analysis but not necessarily organized in a way that gives them meaning. For digital information (the type stored by computers), those data typically are numbers stored in a binary code, portrayed as strings of zeros and ones.

gelatin     A substance made from animal collagen, usually bones and cow or pig hides. It starts out as a pale colored, tasteless powder. It contains proteins and amino acids. It can make jiggly desserts (like those known as Jell-O). But this substance also is used in yogurt, soups, candies and more. It can even be used as the basis of the clear capsules used to hold single-serving amounts of dry medicines.

hypothesis     (v. hypothesize) A proposed explanation for a phenomenon. In science, a hypothesis is an idea that must be rigorously tested before it is accepted or rejected.

infection     A disease that can spread from one organism to another. It’s usually caused by some type of germ.

mean     One of several measures of the “average size” of a data set. Most commonly used is the arithmetic mean, obtained by adding the data and dividing by the number of data points.

model     A simulation of a real-world event (usually using a computer) that has been developed to predict one or more likely outcomes. Or an individual that is meant to display how something would work in or look on others.

p value     (in research and statistics) This is the probability of seeing a difference as big or bigger than the one observed if there is no effect of the variable being tested. Scientists generally conclude that a p value of less than five percent (written 0.05) is statistically significant, or unlikely to occur due to some factor other than the one tested.

plastic     Any of a series of materials that are easily deformable; or synthetic materials that have been made from polymers (long strings of some building-block molecule) that tend to be lightweight, inexpensive and resistant to degradation.

probability     A mathematical calculation or assessment (essentially the chance) of how likely something is to occur.

range     The full extent or distribution of something. For instance, a plant or animal’s range is the area over which it naturally exists. (in math or for measurements) The extent to which variation in values is possible. Also, the distance within which something can be reached or perceived.

standard deviation     (in statistics) The amount that each a set of data varies from the mean.

statistics     The practice or science of collecting and analyzing numerical data in large quantities and interpreting their meaning. Much of this work involves reducing errors that might be attributable to random variation. A professional who works in this field is called a statistician.

tissue     Made of cells, it is any of the distinct types of materials that make up animals, plants or fungi. Cells within a tissue work as a unit to perform a particular function in living organisms. Different organs of the human body, for instance, often are made from many different types of tissues.

virus     Tiny infectious particles consisting of RNA or DNA surrounded by protein. Viruses can reproduce only by injecting their genetic material into the cells of living creatures. Although scientists frequently refer to viruses as live or dead, in fact no virus is truly alive. It doesn’t eat like animals do, or make its own food the way plants do. It must hijack the cellular machinery of a living cell in order to survive.