Staged Alert COVID-19 System Linked to Shorter Lockdowns and Lives Saved

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City of COVID Austin Dashboard

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From June 16, Austin’s Staged Alert System. Credit: City of Austin

A staged alert system, developed by researchers and public health authorities to direct regional policies, assisted one city avoid healthcare facility rises and long lockdowns, according to brand-new research study released in the journal Nature Communications.

In a brand-new research study led by The University of Texas at Austin COVID-19 Modeling Consortium in partnership with Northwestern University, scientists explain the system that has actually assisted COVID-19 policies in Austin, Texas, for more than a year, assisting to secure the healthcare system and prevent expensive steps. It tracks the variety of brand-new day-to-day COVID-19 healthcare facility admissions and activates modifications in assistance when admissions cross particular limit worths. While utilizing this staged alert system, the Austin city has actually sustained the most affordable per capita COVID-19 death rate amongst all big Texas cities.

“Austin’s alert system was optimized to balance the city’s public health and socioeconomic goals,” stated Lauren Ancel Meyers, a teacher of integrative biology and director of The University of Texas COVID-19 Modeling Consortium. “For over a year, it has helped our community adapt to rapidly changing risks, protected the integrity of our hospital systems, and limited the economic damage.”

Throughout the COVID-19 pandemic, policymakers had a hard time to fight COVID-19 while decreasing social and financial repercussions. Governments around the world enacted a range of alert systems that set off lockdowns when cases or hospitalizations reach important levels. According to the paper, Austin’s system was much better at avoiding frustrating healthcare facility rises than the ICU-based triggers utilized in France and much better at preventing lockdowns than commonly pointed out suggestions from Harvard Global Health.

“Our flexible method can design adaptive policies to combat COVID-19 worldwide and prepare for future pandemic threats,” Meyers stated. “When we compared Austin’s optimized triggers to other similar alert systems, we found that it does a much better job of balancing competing public health and economic goals.”

Northwestern University’s David Morton developed the research study with Meyers and Haoxiang Yang, a postdoctoral research study partner at the Center for Nonlinear Studies (CNLS) at Los Alamos National Lab.

“The success of Austin’s system stems partly from its reliance on hospital admission data, which provides a more reliable signal of COVID-19 transmission than reported cases, and partly from our rigorous optimization of the alert triggers,” Morton stated. The scientists obtained limits that supplied a 95% assurance that healthcare facilities would not be overrun.

The 3 Austin-location healthcare facility systems, Ascension Seton, St. David’s HealthCare, and Baylor Scott & White Health, supplied crucial information that were not readily available in a lot of other U.S. cities in the early months of the pandemic, consisting of price quotes for ICU and healthcare facility capability and day-to-day reports of brand-new COVID-19 healthcare facility admissions.

“The pandemic motivated a level of cooperation among the various health players across this community in a very special and effective way,” stated Clay Johnston, dean of Dell Medical School at UT Austin. “Together, we created a system of triggers based on the latest local data, which was central to a coordinated response that helped prevent ICUs from exceeding capacity and ultimately saved lives.”

“The staged alert system was developed by working with the hospital systems, and members of the UT COVID-19 Modeling Consortium in Austin,” stated Dr. Desmar Walkes of the Austin-Travis County Health Authority. “It resulted from a unique partnership between city leaders, the three hospital systems and academics. This is proof that that communicating behavioral change is most effective when it is driven by science and data.”

Reference: “Design of COVID-19 staged alert systems to ensure healthcare capacity with minimal closures” by Haoxiang Yang, Özge Sürer, Daniel Duque, David P. Morton, Bismark Singh, Spencer J. Fox, Remy Pasco, Kelly Pierce, Paul Rathouz, Victoria Valencia, Zhanwei Du, Michael Pignone, Mark E. Escott, Stephen I. Adler, S. Claiborne Johnston and Lauren Ancel Meyers,  18 June 2021, Nature Communications.
DOI: 10.1038/s41467-021-23989-x

In addition to Chief Medical Officer Mark Escott, Austin’s Mayor Steve Adler, Johnson, Meyers, Morton and Yang, authors of the brand-new paper are Özge Sürer, Daniel Duque, Bismark Singh, Spencer J. Fox, Rémy Pasco, Kelly Pierce, Paul Rathouz, Zhanwei Du and Michael Pignone.

This work was supported by the National Institutes of Health, the Texas Department of Human Services, the Centers for Disease Control and Prevention, CNSL, the Bavarian-Czech Academic Agency and the Texas Advanced Computing Center at The University of Texas at Austin. The UT COVID-19 Modeling Consortium is enabled, in part, by the generous assistance of Tito’s Handmade Vodka. Meyers holds the Denton A. Cooley Centennial Professorship at The University of Texas at Austin.



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