In June 2009, the World Health Organization declared the H1N1 virus a pandemic. Director Dr. Margaret Chan took to the news waves, stating, “No previous pandemic has been detected so early or watched so closely, in real-time, right at the very beginning. The world can now reap the benefits of investments, over the last five years, in pandemic preparedness.” News outlets across America began running the story, and Americans scrambled for shots, face masks and more. Pandemic coverage was everywhere. And ultimately, many felt that the media’s seemingly relentless coverage of H1N1 was excessive.

Now it turns out that the world’s preparedness, as well as the media’s nonstop coverage of the flu, may have been the key to the lack of deaths in this outbreak. E! Science News reports that a new mathematical model proves that widespread news coverage of a disease can significantly reduce the severity of the outbreak — and this may in fact have had a key positive effect on the H1N1 pandemic. Researchers at the Georgia Institute of Technology and Marshall University in Huntington, W.Va., have shown that if people take significant steps to avoid sickness, they will in fact fall sick at lesser rates.

Howard Weiss is a professor and key researcher on the project at the Georgia Tech School of Mathematics. As he told E! News Science Daily, "The more forcefully the media provides information about pandemic infections and deaths, the more the total number of infections is reduced. Media coverage also reduces the maximum number of infections at any particular time, which is important for allocating the resources needed for treating infectious diseases."

The cause and effect of successful disease communication is simple. During outbreaks, people tend to closely follow media reports. As a result, they stay home, get vaccinated, wear face masks, wash their hands, avoid crowds, and avoid traveling to known hot spots. This is called “self-isolation” and biologist mathematicians have shown that it can alter the course of an outbreak.

The mathematicians used a modified Susceptible-Infected-Removed (SIR) model traditionally used by epidemiologists to come to their conclusions. Essentially, Weiss and his team counted the “susceptible” (to the disease) among the “removed” (from the disease) as the susceptible were so efficient at self-isolating. Weiss told reporters that they assumed that people self-isolate at a rate proportional to the media coverage, but hopes to study that theory in more detail.

The United States has a history of quick communication regarding perilous disease, but other countries do not. Weiss and his team anticipate that their model may encourage other countries to get the word out quickly and efficiently to curb future outbreaks.

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