Sexually transmitted diseases are reaching record high numbers in the United States, with 50.5 million men and 59.5 million women having STDs. Even with the rise of easily accessible education and means to prevent and treat STDs, they are still spreading.
A major factor contributing to STDs spreading is people being unaware they have contracted an STD and then having intercourse with multiple partners. People don’t even think they are at risk of contracting an STD, and often won’t get tested until full-blown symptoms show up.
With the help of big data, though, it is possible to predict infections in at-risk populations and even help them identify and get treatment for STDs early on.
Who is Most Likely to Contract an STD?
We already know that most new infections happen between the ages of 15 and 24, but there is even more to it. The CDC has identified multiple behaviors that can lead up to contracting STDs, including having multiple partners, incorrect usage of condoms, and combining intercourse with drug or alcohol use.
With big data combining known behaviors with medical records and other demographic data, scientists are finding other trends that might indicate a future possibility of contracting an STD. An example of this is the CDC finding that people who already have or have had an STD are more likely to contract HIV than those who are STD-free.
As more health records are safely opened up for STD research, it’s more likely that researchers will find factors and trends that lead to contracting an STD.
Tracking the Spread of Diseases
Most people don’t get regularly tested for STDs, but a big part of preventing and treating diseases is understanding where they are most common and growing. Since most people are unaware they have an STD, tracking the cases that are found is incredibly useful to understand how it is being spread and where it’s spreading at an alarming rate.
We already know that most people contract their first STD between the ages of 15 and 24, but understanding when, where, and why they are coming in contact with it is important. That way, health officials could better understand what is happening in specific demographics, geographic regions, and more. By tracking where the diseases are spreading, they can get a better understanding of why they’re getting spread and start working to counter them.
Helping Counter the Spread of STDs
The final goal of understanding and tracking the spread of STDs is to find a way to counter the diseases. Depending on the type of STD, countering it could include providing easy access to treatments and medication and/or educating those at risk about the STD and how to prevent getting it.
Instead of just giving general education and treatment options to everybody, with the help of big data, health professionals can better target specific areas against specific diseases. If it’s noticed that high schools in a specific area have an abnormal amount of students with Chlamydia, school and health officials can take steps to increase learning, decrease stigmas or myths around STDs, and help prevent further spread.
Barriers Preventing Big Data From Doing Its Job
There are two major barriers preventing big data from taking control of STDs: lack of access to health records, and people not getting tested. Especially if there is an outbreak, easy access to data, and plenty of it, is incredibly important to those epidemiologists responding to it.
Those studying how STDs spread need access to health records, especially when it comes to diseases people currently have, and public health officials need to encourage sexually active adults to get tested. By doing so, not only will people become more aware of their health, researchers will have larger quantities and higher quality data to work with.
