Texas Tech prediction model shows what it would take to eliminate COVID-19 in Texas

Texas Tech professors create COVID-19 prediction model, recognized by CDC

LUBBOCK, Texas (KCBD) - The CDC now recognizes a new COVID-19 epidemic model constructed by three Texas Tech professors.

“SQUIDER,” is a model that can predict future COVID-19 deaths and future COVID-19 cases in several states, based on data from John Hopkins University. There are seven coupled differential equations used to evaluate recorded data on cases and deaths.

“SQUIDER” is an acronym for the seven groups of people recognized in this model.

Those groups include:

  • susceptible
  • undetected infected
  • detected infected
  • detected recovered
  • social distancing
  • undetected recovery/death
  • detected death
A new epidemiological compartment model for Covid-19.
A new epidemiological compartment model for Covid-19. (Source: squider)

According to the most recent model created in late July, there are three major take-aways.

  • COVID-19 will become endemic, which means the virus will linger like a cold or the flu.
  • If we decrease our contact rate by 10%, by increasing social distancing and mask-wearing behaviors, then we could eradicate infections in Texas within a year.
  • If we increase testing by 15%, we could eradicate infections in Texas within a year.

Assistant research professor Zeina Khan helped build the model with Fazle Hussain, the President’s Endowed Distinguished Chair in Engineering, Science & Medicine; and Frank Van Bussel, a postdoctoral researcher.

Together, they created a unique prediction model. It’s unique because it recognizes that during a lock down, essential workers will still return to work and their model considers the lack of immunity after recovering from the virus.

“SQUIDER” can predict future cases and deaths, which makes it one out of 31 modeling groups contributed to the CDC death projections and 23 modeling groups contributed to case predictions.

Although the model can predict future COVID-19 deaths, Khan said the model shows a much higher rate of deaths than the rate of documented Coronavirus deaths.

Khan hypothesizes that the model and reality do not match because there could possibly be an under count in deaths: doctors are getting better at treating the virus, new drugs are helping people recover or the virus has mutated into a new strain. These are all educated guesses as to why the “SQUIDER” model does not match the recorded COVID-19 death data.

Khan said it’s important to understand how our actions impact our future.

“It’s important to have an idea of how things are going to look. For the social distancing and the mask wearing, if people can see that it not only has an effect now, but have a stronger and more positive effect in the future than I think someone is more likely to comply rather than- you just do as your told,” said Khan.

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