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As Connecticut approaches the peak of the holiday season and families weigh whether to have in-person gatherings, there are a lot of variables to consider.

One of the biggest factors is the risk of their holiday activities spreading COVID-19 to friends and family. An analysis of recent trends in daily new infections by age shows that younger people are testing positive for COVID-19 at much higher rates than during the height of the pandemic in April. In the months following the start of the school year and as the cold weather began forcing people to gather indoors, Connecticut has seen persistent sharp increases in new cases; initially among young people and now in all age groups.

The danger that this trend poses to families during the holidays is very real. While people under 40 account for 49% of new COVID-19 cases in Connecticut, they only account for approximately 23% of new hospitalizations, according to data from US Department of Health and Human Services. Younger people seem to be at higher risk of bringing the novel coronavirus home from school or work, but they appear to be at much lower risk of having severe symptoms that require hospitalization.

In order to better understand possible reasons why infection rates vary so much by age, it helps to combine the nine age ranges into four categories based on the school, work, and social habits of each.

• People in the School Age group are less than 20 years old and the majority of this group is either in Pre K-12th grade or in college.

• People in the Working Age group are between 20 and 39 years old and are generally not students anymore, but are also not fully established in a career. The Working Age are also more likely to work in jobs that cannot be done remotely.

• The Middle Age group is made up of people between 40 and 59. They are more likely to be parents and are more likely to have jobs that allow them to work from home.

• The Retirement Age group are people who are 60 or older. This group is less likely to live in a household with young people and more likely to be retired, approaching retirement, or well-established in their career.

None of these categories are perfect, but they provide a useful frame for analyzing the current spikes in COVID-19 cases by age group.

The Retirement Age group saw the highest number of daily new cases at the height of the first wave in April. Then, over the summer, new cases among the Working Age group begin to accelerate. By early October, new cases had begun to increase in all age categories.

It’s possible that reopening schools had an influence in starting Connecticut’s second wave. School openings across the state were staggered this year. Most colleges and universities began welcoming students back by August 31 and most school districts had begun in-person classes by mid-September. From August 27 (the end of the week before schools began opening) to October 1 (when cases started to spike statewide), the greatest increase in total cases was 41% among the School Age group and the lowest was a 4% increase among the Retirement Age group.

Infections continued to increase through October and November and spiked again after Thanksgiving, but this time, all age groups saw large increases in total suspected or confirmed cases. From November 19 (the end of the week before Thanksgiving) to December 17, total cases in all age groups dramatically increased. Cases were up another 87% among the School Age group and 47% among the Retirement Age group.

The danger that these spikes in new cases pose to families during the remainder of the holiday season is significant. As families and friends gather to celebrate, surging infection rates among less symptomatic younger people are likely to spread to older, more vulnerable groups. Mid-to-late January will probably see a surge in new coronavirus cases even higher than what we have experienced since Thanksgiving.

Next up: How the various types of jobs among Working Age people may be driving new cases and how infections among young people could be spreading within households.

Christopher D. Brechlin is a data scientist from Wethersfield, Connecticut. Find him on Twitter @CTDataGuy or on LinkedIn. Perspectives are his own.

The views, opinions, positions, or strategies expressed by the author are theirs alone, and do not necessarily reflect the views, opinions, or positions of