High vaccination rate key to future course of COVID-19 pandemic, computer modeling shows – ScienceDaily

Data scientists at the Mayo Clinic who have developed highly precise computer modeling to predict trends in COVID-19 cases nationwide have new research that shows how important a high vaccination rate is in reducing the number of cases and control the pandemic.

Vaccination is making a striking difference in Minnesota and is preventing the current level of positive cases from becoming an emergency that overwhelms ICUs and leads to more illness and death, according to a study published in Proceedings of the Mayo Clinic. The study, titled “Quantifying the Importance of COVID-19 Vaccination for Our Future Prospects,” describes how Mayo’s predictive COVID-19 modeling can assess future trends based on the pace of vaccination , and how immunization trends are critical to the future course of the pandemic.

Mayo researchers estimate that a peak of more than 800 patients would be in hospital ICUs in Minnesota this spring if no vaccine had been developed. The projections take into account new variants of the SARS-CoV-2 virus as well as current public health measures and masking standards.

Predicted ICU census levels would be more than double the number of Minnesota COVID-19 patients who were hospitalized in ICUs on December 1, at the height of the most recent outbreak last year.

“It is difficult to determine to what extent this high rate of spread is currently due to new variants as opposed to changes in social behavior,” say the authors, but “for whatever reason, the lack of vaccinations in the current environment were likely to result in by far the largest increase to date. “

If Minnesota had completed the vaccination of 75% of the population in early April, the study estimates that the 7-day average of cases per 100,000 population, the number of COVID-19 patients hospitalized and the number in ICUs would drop in early July. “According to the model, this level of vaccination would suppress growth completely (even in the face of the recent increase in the rate of spread) and immediately reduce cases and hospitalizations to very low levels,” say the authors.

The Mayo Clinic study was led by Curtis Storlie, Ph.D., and Sean Dowdy, MD, whose team developed the computer model to predict the impact of COVID-19 on hospital use which helped guide Mayo’s response to the pandemic. Mayo Clinic’s predictive modeling has also been shared with Minnesota public health leaders to help inform critical decisions over the past year.

The Mayo Clinic’s predictions on COVID-19 trends nationwide are available online at the Mayo Clinic COVID-19 Resource Center (https://www.mayoclinic.org/coronavirus-covid-19). The Coronavirus Map Tracker contains county-by-county information on COVID-19 cases and trends nationwide.

When the pandemic first emerged last year, scientists at the Mayo Clinic developed predictive modeling to assess when and where COVID-19 hotspots would occur. The model accurately predicted the timing and extent of COVID-19 cases and peak hospitalizations, allowing the Mayo Clinic to prepare and ensure it could provide the best care while ensuring patient and staff safety.

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Material provided by Mayo Clinic. Original written by Jay Furst. Note: Content can be changed for style and length.

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