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How Computers Can Fight Diseases

By Katie Lee on 2018-10-18

Diseases are nasty bacterial or even viral epidemics that can often be hard to prevent in today’s hands-on society. Researchers have created an algorithm to help reduce the spread of highly contagious diseases by informing the population to stop unknown spreading.

Public outreach campaigns are the most common way policymakers attempt to inform the population of contagious diseases. While these are quite effective, they fall flat in actually reaching everyone so the disease in question still spreads, often without patient zero even knowing they have it.

We know that informing people of the nature of a disease is the most important step in preventing a pandemics, but how can we reach every single person in every single home?

Researchers at the USC Viterbi school of engineering are creating an algorithm to effectively inform most, if not all, people about a specific disease.

Creating the algorithm took a lot of data concerning disease trends during epidemics, pandemics and among different demographics. This would allow the researchers to know who was at the most risk at any one time for any one illness. For instance, if disease X usually spreads among children under the age of 15 for a few weeks, then it would be important that there would be programs to quickly and effectively inform mothers or fathers with children of that age about disease x. Then if a few weeks later, the disease would begin to spread to people of ages greater than 50, it would be important the programs be able to predict that that would happen before the fact to inform those people.

These patterns were founded through a plethora of computer simulations that show the trend of spread of different diseases. The team used two different diseases to test the algorithm. They tested tuberculosis in India and gonorrhea in the United States. In both cases, the algorithm was the most efficient method in reducing the spread of the diseases.

The first author of the study, Wilder, says "Our study shows that a sophisticated algorithm can substantially reduce disease spread overall," says Wilder, the first author of the paper. "We can make a big difference, and even save lives, just by being a little bit smarter about how we use resources and share health information with the public."

Another important factor that determined the success of the algorithm was the appropriation of resources. If the algorithm was successful but used an overabundance of resources, it would not be efficient. The algorithm, however, did have a strategic use of resources as compared to public outreach programs and other methods.

The mathematical model is also extremely advanced since it manages to take into account human nature. People move, people are born and people die. They incorporated these things by using statistics of how many people are born on average each year, how many move and how many die. One issue would arise since it is not known exactly where the people move from or to so it would be kind of difficult to know where the disease could spread.

"While there are many methods to identify patient populations for health outreach campaigns, not many consider the interaction between changing population patterns and disease dynamics over time," says Suen, an assistant professor for Health Policy and Economics.

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