COVID-19 UPDATE: Researchers find out how to use stats to prepare for next pandemic

Jun 16, 2021 at 10:34 am by WGNS

Researchers have found that cultural and demographic factors can help predict how COVID-19 and future outbreaks could progress.

When looking at COVID numbers locally, Rutherford County has recorded 43,697 positive cases to date with 43,142 being closed or recovered. As of Wednesday (6/16/21) morning, there were 109 ACTIVE cases in our community. 446-COVID related deaths have been recorded in Rutherford County since the start of the pandemic. 

When looking at recent research tied to cultural and demographic factors,  authors say their techniques could be used to figure out how an infectious disease will move beyond hot spots to regions that are not yet affected.

Librarian for STEM research at Vanderbilt University Joshua Borycz says using predictive modeling, a handful of risk factors predicted coronavirus spread in U-S counties, including population size and density, public transportation, and percentage of Black Americans.

Some of the more specific numbers in Tennessee show that the lowest percentage of those who have or have had COVID-19 were 81-years-old or older, which added up to 3% of the current and past cases. Two groups tied for having the second lowest number of positive cases and those groups included newborn to 10-year-olds at 6% and those who are between the ages of 71 and 80-at 6%.

The most impacted age group to test positive for COVID were those between the ages of 21 and 30, which accounted for 18% of the COVID cases. The third most impacted age group were 31 to 40-year-olds at 16% of the total cases.

As governments struggle to predict and plan for the next disease outbreak, Borycz says the data-driven approach could help save lives. He adds that the U-S scored high on many of the socio-cultural risk factors for an outbreak, including low trust in institutions and high levels of obesity. Nearly 600-thousand people in the US have died from the coronavirus.

Furthermore, the recent study found that voting patterns could be used to predict disease spread. Borycz says the data show that in large cities, even when controlled for population density and other differences, areas with more Democratic voters had a higher rate of infection and death from COVID-19.

Borycz also notes the analysis made some surprising predictions about the spread of COVID-19 around the world — showing that, for example, African countries would not be heavily affected by COVID-19. So far, around 133-thousand people have died from the coronavirus on the African continent, far lower than elsewhere around the globe.

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